Terry Boo Chee Yee, Li Sheng | P2211194, P2309110 | DAAA/FT/2B/22 | Deep Learning CA2 - Part A (GAN)

Generative Adverserial Network

Overview

We have generated 260 images, with 10 images from each of the 26 classes. To achieve this, we used a combination of CGAN and DCGAN models. For the images from classes A to Y, we utilized the CGAN as the generated images required specific class conditioning, which CGANs handle effectively. However, for the final 'Z' class, we used a DCGAN because the CGAN was not performing well for this particular class. The DCGAN was more suitable for generating high-quality images specifically for the 'Z' class, focusing on this challenging aspect without the need for class labels.

The process of generating the 260 images began with exploratory data analysis (EDA), followed by dataset cleaning and feature engineering. After processing the data, we explored the use of DCGAN, starting with a base model and attempting various improvements to generate the best possible images. Similarly, for CGAN, we began with a base model and made adjustments in an effort to enhance the quality of the generated images and find the best-performing model. For WGAN, we also started with a base configuration and experimented with improvements to achieve the highest quality images.

The final model was evaluated by comparing the generated images with real images and analyzing metrics such as loss, accuracy, and KL divergence.

Final CGAN Performance

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• Classes A, C, D, E, F, I, J, K, L, N, O, P, R, S, T, U, V, and X have sharp and well-defined features, showing the generator's strong ability to produce high-quality images.

• Classes B, Y, W, Q, M, H, and G have details that are not that well captured.

• Class Z has significant issues, highlighting areas where the Generator's performance is lacking.

• The generator's loss decreases and stabilizes around 0.7 after 200 epochs, while the discriminator's loss increases and stabilizes around 0.7, indicating the generator is improving.

• Accuracy starts at 100% and decreases, fluctuating between 40% and 60%, reflecting the generator's improved ability to produce realistic images.

• A value of 0.1776 shows the generator's success in mimicking the real data distribution, capturing essential features and variations.

Together, these metrics form a comprehensive evaluation framework that allows us to understand the strengths and weaknesses of our GAN model. The consistency in generated image quality for most classes, the balanced training losses, and the relatively low KL Divergence all point to a generally well-performing model.

In conclusion, our GAN model demonstrates strong potential, with effective learning for most classes and a balanced training dynamic.

The Z Problem

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Previously, the generator is not generating the Z class well

Solution: DCGAN for Class “Z”

• DCGAN generates images without class labels, simplifying training for "Z" without additional complexity.

• Training DCGAN on "Z" images allows the model to specialize, producing higher-quality images for that class.

• Results in Enhanced clarity and structure in generated "Z" images.

• Results in Improved samples of generated "Z" images, showcasing better quality

Note: We will use our final CGAN model and this additional DCGAN model to generate the 260 images (10 images/class)

Summary of the process we went through (Workflow)

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1. EDA
2. Data Cleaning
   • Excluding Images with Constant Pixel Values
3. Feature Engineering
   • Flipping the Images Upright
   • Normalizing the Images (to [0 1])
   • Data Augmentation
4. DCGAN (With tunning)
5. CGAN (With tunning)
6. WGAN (With tunning)
7. Final Model Evaluation (CGAN)
   • Model Architecture
   • Sample of generated images VS real images
   • Loss
   • Accuracy
   • KL divergence
   • Final Verdict
8. Generate the images

Data Cleaning Process

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Excluding Images with Constant Pixel Values

Images with constant pixel values lack variability and do not provide any meaningful features or patterns that can be used for training models. They do not contribute to learning useful representations.

Feature Engineering Process

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Flipping the Images Upright

GANs generate images based on learned patterns from the training data. If the images are flipped or rotated, the model will learn incorrect associations, leading to unrealistic outputs (Images generated will not be upright too).

Normalizing the Images

Normalization helps standardize the pixel values, allowing the GAN to learn patterns more effectively.Normalized inputs can lead to more stable training, reducing issues like vanishing or exploding gradients. Normalization prevents the model from being overly influenced by the absolute values of pixel intensities, helping it focus on the relative features of the images.

Data Augmentation

Data augmentation introduces variations in the training images, allowing the GAN to learn more robust features and reducing the risk of overfitting. Additionally, augmented images make the GAN more resilient to variations in input, such as changes in orientation and scale. By exposing the GAN to various transformations, it can learn to generate more diverse and realistic images, ultimately improving the quality of its outputs.

Additionally, not all classes initially had the same number of images. Augmentation helps to balance the dataset by ensuring each class has an equal number of images.

Optimization Process of Deep Convolutional GAN (DCGAN)

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Base Model

Base Model

Improve the discriminator

From the baseline model, it is evident that the GAN is not generating images effectively. While some letters are partially represented, many others are not recognizable at all. To address this issue, we decided to enhance the discriminator. By strengthening the discriminator's ability to differentiate between real and generated images, we aim to provide more precise feedback to the generator. This improved feedback will help the generator refine its outputs and create more realistic and diverse representations of handwritten letters. Ultimately, our goal is to achieve higher-quality image generation, ensuring that each letter is accurately represented in the final dataset.

Using ReLu for the generator's activation function

Despite the improved quality of the images generated in the previous model, the generator is still struggling to learn the image patterns effectively, resulting in some blurry images with patches of white. Therefore, we have decided to use ReLU to enhance the learning process. By incorporating ReLU, we aim to leverage its properties to better capture the intricate details of the images and improve the overall clarity and realism of the generated outputs.

Adding more dense unit to the generator

We increased the number of dense units for the generator to enhance its capacity to learn and represent complex patterns in the data. With more dense units, the generator can capture a greater variety of features and nuances, which is essential for producing high-quality, detailed images.

Optimization Process of Conditional GAN (CGAN)

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Base Model

Base Model

Increase the number of dense units in the generator

By increasing the number of units (neurons) in this layer, we increase the capacity of the generator to learn and capture more complex patterns and features from the input noise vector. This allows the generator to potentially model more intricate relationships and variations in the data distribution it aims to mimic.

Remove batch normalization layer from the generator

Batch normalization (BN) layers are typically used to stabilize and speed up the training of neural networks by normalizing activations and reducing internal covariate shift. In the context of GANs, the training dynamics can be quite sensitive, and batch normalization might interfere with the adversarial training process.

Optimization Process of Wasserstein GAN (WGAN)

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Base Model

Base Model

Removing dropout and batch normalization layer from the generator

Removing dropout and batch normalization layers can lead to more stable gradient updates. Dropout, while useful in regular neural networks to prevent overfitting, can introduce noise and instability in the gradients, which might disrupt the delicate balance required for effective WGAN training.

Using TanH activation with normalization to the range of (-1, 1)

Normalizing the input data to the range of (-1, 1) and using Tanh activation functions can significantly benefit the learning process. Tanh activation, which outputs values in the range (-1, 1), aligns well with the normalization range, ensuring that the data is centered around zero.

This can help in maintaining a stable training process by avoiding issues like saturation and vanishing gradients, which are common with activations that output larger ranges.

Tanh activation function encourages stronger gradient signals compared to the sigmoid function, especially when inputs are centered around zero. This can lead to more efficient and faster convergence during training, ultimately improving the quality of the generated images.

Considerations for GANs

If you are asked to generate images of a specific class, propose a way of doing it

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We can use Conditional GAN (CGAN). Conditional GANs are an extension of standard GANs and consist of two main components: the generator and the discriminator. Unlike a typical DCGAN, where the generator only takes in a noise vector (random input) and the discriminator only determines whether the image is real or generated, the generator in CGANs takes both a noise vector and a class label as inputs to generate an image corresponding to the specified class. Similarly, the discriminator takes both an image and a class label as inputs to determine whether the image is real (from the dataset) or generated (by the generator).

During the training process of a CGAN, a noise vector and a class label are fed into the generator to produce a synthetic image corresponding to the given class. Real images from the dataset, paired with their class labels, are then combined with the generated images and labels. The discriminator is trained on this mixed set, learning to distinguish between real and generated images. This process involves calculating the loss for both real and fake images and updating the discriminator's weights accordingly. After training the discriminator, the generator is trained to fool the discriminator by generating images that appear real. This is done by freezing the discriminator's weights and updating the generator's weights based on the discriminator's feedback. The generator's loss is calculated based on how well it can generate images that the discriminator classifies as real. This cycle continues for many iterations, gradually improving both the generator's ability to produce realistic images and the discriminator's ability to distinguish real from fake images, with the added conditional element allowing for class-specific image generation.

In conclusion, CGANs are trained on additional infomation such as class labels, thus allowing them to generate images based on specific classes.

If you are asked to generate coloured images instead of black-and-white ones, do you think it would be easier or harder to produce better quality results

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It would be harder to produce better quality of coloured images.

1. Coloured images have three channels (Red, Green, and Blue) compared to the single channel in black-and-white images. This increase in dimensionality means the model has to learn more detailed and complex patterns.

2. The complexity of colored images can exacerbate training instability, making it harder to achieve convergence and maintain consistent performance.

3. The increased complexity in the images means increased computational requirements, which can lead to longer training times and a need for more powerful hardware.

4. Accurately representing how light interacts with colored surfaces is more complex compared to black-and-white images. Colored images require the model to handle reflections, shadows, and color bleeding effects, which add layers of complexity that are not present in black-and-white images, where light interactions are simpler and often rely on shades of gray.

What class(es) is/are relatively easier/harder to generate? Why?

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Classes that are relatively easier to generate

Straightforward (e.g., "I", "L", "O")

These letters have simpler shapes and fewer strokes, making them less complex for the GAN to learn. Additionally, they typically have more consistent representations in handwriting, reducing variability.

Letters where lowercase and uppercase forms are similar (e.g., "C", "O", "V", "K", "P", "U")

Letters in which uppercase and lowercase forms maintain the same basic shape, with size as the primary difference, allow the GAN to learn a consistent representation without needing to adapt to drastically different forms. The minimal structural differences also result in fewer variations in how these letters can be written, reducing the complexity the GAN must manage.

Classes that are relatively harder to generate

Complex Letters (e.g., "S", "G", "Q")

These letters often have more intricate curves and loops, which can introduce greater variability in styles and representations. The added complexity can challenge the GAN's ability to generate accurate samples.

Letters with variability in different handwriting styles (e.g., "A")

The same letter can look very different depending on individual writing styles, leading to variations in structure and positioning. When a letter can have multiple forms, the GAN must learn to generate a wider range of structures and styles. This complexity requires the model to capture more nuanced features, which can be challenging.

Table of contents

• 1. Background Research
• 2. Set Up
  • 2.1 Importing Libraries
  • 2.2 Loading the Dataset
• 3. Exploratory Data Analysis
  • 3.1 Shape of the Data
  • 3.2 Identify Images with Constant Pixel Values
  • 3.3 Unique Classes in the Dataset
  • 3.4 Sample Images From Each Class
  • 3.5 Number of Images in Each Class
  • 3.6 Pixel Variability in Each Class
• 4. Data Cleaning
  • 4.1 Excluding Images with Constant Pixel Values
• 5. Feature Engineering
  • 5.1 Flipping the Images Upright
  • 5.2 Normalizing the Images
  • 5.3 Data Augmentation
• 6. Evaluation Metrics
  • 6.1 Loss (Generator Loss and Discriminator Loss)
  • 6.2 Accuracy (Discriminator Accuracy)
  • 6.3 Wasserstein Distances
  • 6.4 Kullback-Leibler (KL) Divergence
  • 6.5 Samples of Generated Images VS Real Images
• 7. Deep Convolutional GAN (DCGAN)
  • 7.1 Base Model (DCGAN)
  • 7.2 Improving the Discriminator
  • 7.3 Using ReLU for The Generator's Activation Function
  • 7.4 Adding More Dense Units to The Generator
• 8. Conditional GAN (CGAN)
  • 8.1 Base Model (CGAN)
  • 8.2 Increase the Number of Dense Units in the Generator
  • 8.3 Remove Batch Normalization Layer from the Generator
• 9. Wasserstein GAN (WGAN)
  • 9.1 Base Model (WGAN)
  • 9.2 Removing Dropout and Batch normalization Layers From the Critic
  • 9.3 Using Tanh activation with normalization to the range of (-1, 1)
• 10. Final Model
• 11. Final Model Evaluation
  • 11.1 Model Architecture
    • 11.1.1 Generator
    • 11.1.2 Discriminator
  • 11.2 Generated Images at Different Epochs
  • 11.3 Sample of Generated Images VS Real Images
  • 11.4 Loss
  • 11.5 Accuracy
    • 11.5.1 Accuracy Throughout Training
    • 11.5.2 Accuracy of Predicting Real Images
    • 11.5.3 Accuracy of Predicting Fake Images
  • 11.6 KL Divergence
  • 11.7 Save the Model
  • 11.8 Final Verdict on The Performance of The Final Model
• 12. Generate 260 Images
  • 12.1 Generate all classes other than Z
  • 12.2 Geneate Z class
• 13. Conclusions

Background Research

Extended MNIST (EMNIST) Letters dataset

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The EMNIST Letters dataset contains 26 classes, corresponding to the 26 letters of the English alphabet (A-Z).

Similar to the MNIST dataset, the images in EMNIST are grayscale and of size 28x28 pixels. Each pixel value is an integer between 0 and 255, where 0 represents a black pixel and 255 represents a white pixel.

The labels for the images are numeric values from 1 to 26, corresponding to the letters A-Z.

Task

---

In our project, we aim to create 260 small black-and-white images of handwritten letters using the EMNIST Letters dataset. This task involves several key steps, including data cleaning, feature engineering, model selection, training the GAN, fine-tuning the GAN, evaluation, and image generation.

Solution

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In our project, we will explore various types of Generative Adversarial Networks (GANs) to generate 260 small black-and-white images of handwritten letters from the EMNIST Letters dataset. Each GAN variant comes with its own advantages and disadvantages, which we will weigh to determine the best-performing model for our task.

Why use GAN models for this task

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Since we are focused on generating images, Generative Adversarial Networks (GANs) are especially well-suited for this task. GANs are specifically designed to create realistic images by learning the underlying data distribution, enabling them to produce high-quality handwritten letters that closely mimic real samples. Moreover, GANs can generate a diverse range of images, which is crucial for our project. They can capture various styles and handwriting variations, ensuring that the resulting dataset is rich and diverse.

What are GANs

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Generative modeling is an unsupervised learning task in machine learning that involves automatically discovering and learning the regularities or patterns in input data in such a way that the model can be used to generate or output new examples that plausibly could have been drawn from the original dataset.

Main components of GAN

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Discriminator

The discriminator in a GAN is simply a classifier. It tries to distinguish real data from the data created by the generator. It could use any network architecture appropriate to the type of data it's classifying.

Generator

The generator part of a GAN learns to create fake data by incorporating feedback from the discriminator. It learns to make the discriminator classify its output as real.

How Gan works

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First, the generator creates samples from random noise inputs and feeds these generated samples into the discriminator. The discriminator then tries to classify whether each sample is real (from the actual data distribution) or generated (fake).

Applications of GAN

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Image-to-Image Translation

GANs can translate images from one domain to another, such as converting sketches to realistic images, day images to night images, and black-and-white images to color images. This has applications in fields like computer graphics and virtual reality.

Text-to-Image Translation

GANs (Generative Adversarial Networks) are increasingly used in text-to-image translation, where they generate detailed and contextually accurate images based on textual descriptions. This technology is particularly useful in creative industries, allowing artists and designers to visualize concepts from textual input.

Super Resolution

Super Resolution Generative Adversarial Networks (SRGANs) are highly effective in enhancing the resolution of images, significantly increasing their clarity and detail. This can be particularly useful in several areas, such as improving the resolution of medical scans for better diagnosis, enhancing the quality of surveillance footage for clearer identification, and improving satellite images for more detailed geographical and environmental analysis.

Photograph Editing

GANs are widely utilized in photograph editing to enhance and transform images through various innovative tasks. For instance, they can effectively replace the background of a photograph with an entirely different scene, making it easier to create composites or adjust the context of an image. Additionally, GANs can change facial attributes, allowing for modifications such as altering expressions, changing hairstyles, or even aging or de-aging subjects. Furthermore, they enable the modification of specific attributes of objects within photos, such as changing the color of a car, altering the texture of a building, or modifying clothing in fashion images.

Photo Inpainting

GANs (Generative Adversarial Networks) are employed in photo inpainting to restore missing parts of an image or remove unwanted objects by generating content that seamlessly blends with the surrounding areas. They are particularly effective in filling gaps in damaged photographs, removing unwanted elements, and reconstructing incomplete parts of images.

Deep Fake

GANs are a key technology in the creation of deepfakes, which are realistic audio and video forgeries. By leveraging the capabilities of GANs, creators can generate highly convincing synthetic media that can swap faces in videos, create realistic lip-syncing, or even simulate a person's voice. In entertainment, deepfakes can be used for special effects in films, allowing for seamless integration of actors into various scenes without extensive makeup or CGI.

How is GANs Used in The Industry

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Healthcare

In medical imaging, GANs enhance the resolution of scans (e.g., MRI, CT) to improve diagnosis accuracy. This improved clarity helps healthcare professionals identify conditions more effectively and tailor treatment plans to individual patients.

Advertising and Marketing

Companies use GANs to create personalized ads, generate synthetic images for campaigns, and modify existing content to better target specific audiences. By leveraging GAN-generated content, brands can engage consumers with more relevant and appealing visuals, increasing the effectiveness of their marketing efforts.

Art and Entertainment

GANs assist artists in generating unique artworks and animations, enabling new forms of creativity. They can also create deepfakes for film and media, allowing for innovative storytelling and character development while raising important discussions around authenticity and ethics in digital content.

Gaming

Game developers use GANs to create realistic textures, environments, and characters, streamlining asset creation and enhancing visual quality. This technology allows for more immersive gaming experiences and reduces the time and resources needed for traditional asset development.

Architecture

In architecture, GANs help visualize building designs and modifications by generating realistic renderings of architectural plans, allowing architects and clients to better understand spatial relationships and aesthetics before construction begins

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References

https://arxiv.org/pdf/1702.05373

https://machinelearningmastery.com/what-are-generative-adversarial-networks-gans/

https://developers.google.com/machine-learning/gan/gan_structure

https://machinelearningmastery.com/impressive-applications-of-generative-adversarial-networks/

Set Up

Importing Libraries

# Basic Libraries
import pandas as pd
import numpy as np
import random
import os
import shutil
import tensorflow as tf
import math
from PIL import Image
from collections import Counter
import cv2
from keras import backend as K

# Visualizations Libraries
import matplotlib.pyplot as plt

# Utility  Libraries
from sklearn.utils import resample
from tensorflow.keras.utils import Sequence
import tensorflow.keras.utils as image
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.utils import image_dataset_from_directory

# Pre-Processing Libraries
from tensorflow.keras.preprocessing import image_dataset_from_directory
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.preprocessing import image
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import LabelBinarizer

# Model Libraries
from tensorflow.keras.models import Sequential
from tensorflow.keras.models import Model

#Layers Libraries
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Input
from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import Dropout
from tensorflow.keras.layers import Flatten
from tensorflow.keras.layers import MaxPooling2D
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import LeakyReLU
from tensorflow.keras.layers import Reshape
from tensorflow.keras.layers import Conv2DTranspose
from tensorflow.keras.layers import UpSampling2D
from tensorflow.keras.layers import Activation
from tensorflow.keras.layers import ZeroPadding2D
from tensorflow.keras.layers import multiply
from tensorflow.keras.layers import Embedding
from tensorflow.keras.layers import InputLayer

#Callback Libraries
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.keras.callbacks import ModelCheckpoint

# Optimizer Libraries 
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.optimizers import RMSprop

# Evaluation Libraries
from sklearn.metrics import classification_report
from visualkeras import layered_view
from sklearn.metrics import confusion_matrix

# ignore warnings
import pickle
import warnings
warnings.filterwarnings("ignore")

Loading the Dataset

# Load the CSV file into a DataFrame
df = pd.read_csv('emnist-letters-train.csv', header=None)
df.head()

	0	1	2	3	4	5	6	7	8	9	...	775	776	777	778	779	780	781	782	783	784
0	23	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
1	7	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
2	16	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
3	15	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
4	23	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0

5 rows × 785 columns

Exploratory Data Analysis

df_eda = df.copy()
# A function to map the labels from numbers to alphabets
def map_labels(x):
    label_map = {
        -1: '-1', 1: 'A', 2: 'B', 3: 'C', 4: 'D', 5: 'E', 
        6: 'F', 7: 'G', 8: 'H', 9: 'I', 10: 'J', 
        11: 'K', 12: 'L', 13: 'M', 14: 'N', 15: 'O', 
        16: 'P', 17: 'Q', 18: 'R', 19: 'S', 20: 'T', 
        21: 'U', 22: 'V', 23: 'W', 24: 'X', 25: 'Y', 26: 'Z'
    }

    if isinstance(x, str) and len(x) < 3:
        # If the label is already mapped and is a single character, return it as is
        return x
    else:
        return label_map.get(x)

# Applying mapping to the first column and convert to string
df_eda[0] = df_eda[0].apply(map_labels).astype(str)
df_eda.head()

	0	1	2	3	4	5	6	7	8	9	...	775	776	777	778	779	780	781	782	783	784
0	W	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
1	G	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
2	P	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
3	O	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0
4	W	0	0	0	0	0	0	0	0	0	...	0	0	0	0	0	0	0	0	0	0

5 rows × 785 columns

Shape of the Data

# Convert DataFrame to NumPy array
data = df_eda.values
# Check the shape of the data
print("Shape of data array:", data.shape)

Shape of data array: (99040, 785)

Results

This dataset comprises 99,040 images with 785 columns, where the first column represents the class label, and the subsequent columns contain pixel values.

Identify Images with Constant Pixel Values

What are constant pixel values

Constant pixel values, when referred to in the context of an entire image, mean that every pixel in the image has the same value. This results in a completely uniform image without any variation in color or intensity.

def is_constant_image(row):
    pixel_values = row.iloc[1:].values 
    # If the rest of the pixel values is the same as the first pixel value
    return np.all(pixel_values == pixel_values[0])

# Apply the function to each row and filter for constant pixel value rows
constant_images = df_eda[df_eda.apply(is_constant_image, axis=1)]

print(f"Number of constant pixel value images: {constant_images.shape[0]}")


# Retrieve unique class labels for constant pixel value images
unique_constant_pixel_class = np.unique(constant_images.iloc[:, 0].values)


print(f'Class labels for images with constant pixel values: {unique_constant_pixel_class}')

Number of constant pixel value images: 10240
Class labels for images with constant pixel values: ['-1']

no_minus_one_images = len(df_eda[df_eda.iloc[:, 0] == '-1'])  # Counting rows where the first column equals '-1'

print(f'Number of images in the \'-1\' class: {no_minus_one_images}')

Number of images in the '-1' class: 10240

Results

The dataset includes 10,240 images with uniform pixel values, all categorized under the '-1' class.

Since there are 10,240 images in the '-1' class, all the images in the '-1' class are images with uniform pixel values

We will take note of the images with uniform pixel values during the Data Cleaning process

Unique Classes in the Dataset

# Extract the first column
classes = data[:, 0]

# Get unique classes
unique_classes = np.unique(classes)

# Print the unique classes array
print("Unique classes array:")
print(unique_classes)

Unique classes array:
['-1' 'A' 'B' 'C' 'D' 'E' 'F' 'G' 'H' 'I' 'J' 'K' 'L' 'M' 'N' 'O' 'P' 'Q'
 'R' 'S' 'T' 'U' 'V' 'W' 'X' 'Y' 'Z']

Results

The Dataset contains images images of A - Z class and there is a '-1' class.

Sample Images From Each Class

def plot_random_images_per_class_from_dataframe(df, image_size, num_images_per_row=5):
    # Extract labels and pixel data
    labels = df.iloc[:, 0]  # Assuming the first column contains labels
    pixel_data = df.iloc[:, 1:]  # Assuming pixel data starts from the second column

    # Reshape pixel data into images
    num_images = len(df)
    images = pixel_data.values.reshape(num_images, image_size, image_size)

    # Get unique classes and sort them alphabetically
    unique_classes = sorted(labels.unique())

    # Calculate number of rows needed for subplots
    num_classes = len(unique_classes)
    num_rows = (num_classes + num_images_per_row - 1) // num_images_per_row  # Equivalent to ceil(num_classes / num_images_per_row)

    # Create subplots
    fig, axes = plt.subplots(num_rows, num_images_per_row, figsize=(num_images_per_row * 2, num_rows * 2))

    # Plot random image from each class
    for i, cls in enumerate(unique_classes):
        class_indices = labels[labels == cls].index
        cls = map_labels(cls)
        random_index = random.choice(class_indices)
        row = i // num_images_per_row
        col = i % num_images_per_row
        axes[row, col].imshow(images[random_index], cmap='gray')
        axes[row, col].set_title(f'Class {cls}')
        axes[row, col].axis('off')

    # Hide any extra subplots if num_classes is not a multiple of num_images_per_row
    for j in range(num_classes, num_rows * num_images_per_row):
        axes.flatten()[j].axis('off')

    plt.tight_layout()
    plt.show()

plot_random_images_per_class_from_dataframe(df_eda, image_size=28, num_images_per_row=5)

Results

Looks like the images are representing their labels correctly, but they are not oriented in an upright position. In addition, the '-1' class contains images of solid colors

Number of Images in Each Class

def count_images_per_class(data):
    # Extract classes from the first column
    classes = data.iloc[:, 0]

    # Get unique classes and count occurrences
    unique_classes, counts = np.unique(classes, return_counts=True)

    # Create a dictionary to store class counts
    class_counts = dict(zip(unique_classes, counts))

    return class_counts

def plot_class_distribution(data):
    classes = data.iloc[:, 0]

    # Check if the classes are numerical and need mapping
    if classes.apply(lambda x: isinstance(x, int)).all():
        # Map numerical labels to alphabet labels
        mapped_classes = classes.apply(map_labels)
    else:
        mapped_classes = classes

    # Get unique classes and count occurrences
    unique_classes, counts = np.unique(mapped_classes, return_counts=True)

    # Plotting the graph
    plt.figure(figsize=(10, 6))
    plt.bar(unique_classes, counts, color='skyblue')
    plt.xlabel('Class')
    plt.ylabel('Number of Images')
    plt.title('Number of Images in Each Class')
    plt.xticks(unique_classes)
    plt.show()

plot_class_distribution(df_eda)

Results

There are approximately 10,000 images in the '-1' class, whereas the other classes each have around 3,700 images.

Pixel Variability in Each Class

What is pixel variability

Pixel variability refers to the differences in pixel values within an image or a set of images. High pixel variability indicates that there are significant changes in color, intensity, or texture throughout the image, while low pixel variability suggests that the image has more uniform or constant regions.

# Extract labels and pixel data
labels = df_eda.iloc[:, 0] 
pixel_data = df_eda.iloc[:, 1:]  

# Get unique classes and sort them alphabetically
unique_classes = sorted(labels.unique())

# Initialize a dictionary to store standard deviation for each class
std_per_class = {}

# Calculate standard deviation for each class
for cls in unique_classes:
    class_indices = labels[labels == cls].index
    class_pixel_data = pixel_data.loc[class_indices]
    std_per_class[cls] = class_pixel_data.values.std(axis=0).mean()

# Plotting the pixel variability
plt.figure(figsize=(10, 5))
plt.bar(std_per_class.keys(), std_per_class.values())
plt.xlabel('Class')
plt.ylabel('Average Pixel Standard Deviation')
plt.title('Pixel Variability per Class')
plt.show()

Results

The '-1' class exhibits the highest pixel variability, whereas the 'I' class shows the least variability.

We don't need to be concerned about pixel variability because we will normalize the images during the Feature Engineering step. Normalization will ensure that the pixel values are scaled properly for training.

Data Cleaning

Excluding Images with Constant Pixel Values

What are constant pixel values

Constant pixel values, when referred to in the context of an entire image, mean that every pixel in the image has the same value. This results in a completely uniform image without any variation in color or intensity.

Why do we exclude images with constant pixel values

Images with constant pixel values lack variability and do not provide any meaningful features or patterns that can be used for training models. They do not contribute to learning useful representations.

Including such images can reduce the efficiency of training processes. The model might spend unnecessary computation cycles processing these uninformative images, which can slow down the overall training process.

In datasets where variability is crucial (e.g., object detection, classification, or segmentation), constant pixel value images act as noise. They do not help in learning the distribution of the target data and can lead to suboptimal performance.

# Duplicate DF
cleaned_df = df.copy()

# Filtering
cleaned_df = cleaned_df[cleaned_df.iloc[:, 0] != -1]

# Print the number of images after removing blank images
print(f'Number of images after removing blank images: {cleaned_df.shape[0]}')
plot_class_distribution(cleaned_df)

Number of images after removing blank images: 88800

Feature Engineering

Flipping the Images Upright

What we realised

We have realised that the images are flipped vertically and are rotated 90 degree anti clockwise

Why do we have to flip the images upright

GANs generate images based on learned patterns from the training data. If the images are flipped or rotated, the model will learn incorrect associations, leading to unrealistic outputs (Images generated will not be upright too).

What will we do to flip the images upright

We will first flip the images vertically and next rotate the images 90 degrees clockwise

# Define a function to reshape and process images
def process_image(row):
    label = row[0] 
    pixels = np.array(row[1:], dtype=np.uint8) 
    image = pixels.reshape(28, 28)  # Reshape to original image dimensions (assuming 28x28)
    return label, image

# Flip vertically and rotate 90 degrees using cv2
def flip_and_rotate(image):
    # Flip vertically
    flipped_image = cv2.flip(image, 0)
    # Rotate 90 degrees clockwise
    rotated_image = cv2.rotate(flipped_image, cv2.ROTATE_90_CLOCKWISE)
    return rotated_image.flatten()

# Process each row in the dataframe
processed_images = []
for index, row in cleaned_df.iterrows():
    label, image = process_image(row)
    processed_image = flip_and_rotate(image)
    processed_images.append((label, processed_image))

# Convert processed images back to dataframe if needed
upright_image_df = pd.DataFrame(processed_images, columns=['Label', 'Processed_Image'])

# Convert the pixels to columns
upright_image_df_pixels = upright_image_df['Processed_Image'].apply(pd.Series)

# Rename columns
upright_image_df_pixels.columns = [f'{i+1}' for i in range(len(upright_image_df_pixels.columns))]

# Concatenate Label column with the new pixel columns
upright_image_df = pd.concat([upright_image_df['Label'], upright_image_df_pixels], axis=1)

plot_random_images_per_class_from_dataframe(upright_image_df, image_size=28, num_images_per_row=5)

Normalizing the Images

What is Normalizing the Images

Normalizing images refers to the process of adjusting the pixel values of the images to a common scale such as [0, 1] or [-1, 1].

Why did we normalize the images

• Normalization helps standardize the pixel values, allowing the GAN to learn patterns more effectively.

• Normalized inputs can lead to more stable training, reducing issues like vanishing or exploding gradients.

• Normalization prevents the model from being overly influenced by the absolute values of pixel intensities, helping it focus on the relative features of the images.

What we did

We have normalized the images to a [0, 1] scale

# Convert DataFrame to NumPy array
data = upright_image_df.values

# Assuming each image is 28x28 pixels and the remaining columns are pixel values
image_size = 28
num_images = data.shape[0]

# Extract labels and pixel data
labels = data[:, 0]
pixel_data = data[:, 1:]

# Extract pixel data and reshape each row into a 28x28 array
original_images = data[:, 1:].reshape(num_images, image_size, image_size).astype(np.uint8)

# Normalize pixel values
normalized_images = original_images / 255.0

# Flatten the normalized images back to rows
flattened_normalized_images = normalized_images.reshape(num_images, -1)

# Combine labels and flattened normalized images
combined_data = np.column_stack((labels, flattened_normalized_images))

# Create a new dataframe with the combined data
normalized_df = pd.DataFrame(combined_data, columns=cleaned_df.columns)

# Display the first few rows of the new dataframe
normalized_df

	0	1	2	3	4	5	6	7	8	9	...	775	776	777	778	779	780	781	782	783	784
0	23.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1	7.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	16.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
3	15.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
4	23.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
88795	26.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
88796	23.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
88797	18.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
88798	24.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
88799	19.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

88800 rows × 785 columns

Data Augmentation

What is data augmentation

Data augmentation is a technique used to artificially increase the size of a training dataset by applying various transformations to the existing data samples. These transformations include rotations, translations, flips, changes in brightness and contrast, cropping, and more. This diversify the training data and expose the model to a wider range of variations.

Why did we augment the dataset

Data augmentation introduces variations in the training images, allowing the GAN to learn more robust features and reducing the risk of overfitting. Additionally, augmented images make the GAN more resilient to variations in input, such as changes in orientation and scale. By exposing the GAN to various transformations, it can learn to generate more diverse and realistic images, ultimately improving the quality of its outputs.

Additionally, not all classes initially had the same number of images. Augmentation helps to balance the dataset by ensuring each class has an equal number of images.

Steps taken to augment the data

1. Resample the train dataset and put the resampled images into a Data Frame
2. Define an Image Data Generator to Augment the data
3. Augment the data
4. Combine the augmented data with the original train dataset

References

https://machinelearningmastery.com/improve-deep-learning-performance/

count_per_class = count_images_per_class(normalized_df)
count_per_class

{1.0: 3396,
 2.0: 3396,
 3.0: 3419,
 4.0: 3398,
 5.0: 3437,
 6.0: 3394,
 7.0: 3385,
 8.0: 3424,
 9.0: 3428,
 10.0: 3402,
 11.0: 3438,
 12.0: 3415,
 13.0: 3402,
 14.0: 3365,
 15.0: 3408,
 16.0: 3430,
 17.0: 3435,
 18.0: 3419,
 19.0: 3392,
 20.0: 3436,
 21.0: 3419,
 22.0: 3422,
 23.0: 3423,
 24.0: 3437,
 25.0: 3453,
 26.0: 3427}

Image needed for each class

target_per_class = 3500
no_images_needed_per_class = {}
print('Image needed for each class')
for key, value in count_per_class.items():
    no_images_needed_per_class[key] = target_per_class - value
no_images_needed_per_class

Image needed for each class

{1.0: 104,
 2.0: 104,
 3.0: 81,
 4.0: 102,
 5.0: 63,
 6.0: 106,
 7.0: 115,
 8.0: 76,
 9.0: 72,
 10.0: 98,
 11.0: 62,
 12.0: 85,
 13.0: 98,
 14.0: 135,
 15.0: 92,
 16.0: 70,
 17.0: 65,
 18.0: 81,
 19.0: 108,
 20.0: 64,
 21.0: 81,
 22.0: 78,
 23.0: 77,
 24.0: 63,
 25.0: 47,
 26.0: 73}

Resample data

resampled_df_data = []
for class_label, target_count in no_images_needed_per_class.items():
    class_data = normalized_df[normalized_df[0] == class_label]
    # Resample the images
    resampled_df_data.append(resample(class_data, n_samples = target_count, random_state=42))

resampled_df = pd.concat(resampled_df_data)
resampled_df

	0	1	2	3	4	5	6	7	8	9	...	775	776	777	778	779	780	781	782	783	784
82575	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
22521	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
33586	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
29379	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
28419	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
77509	26.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
39088	26.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
66412	26.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
20396	26.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
881	26.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

2200 rows × 785 columns

# Extract the labels and images
labels = resampled_df.iloc[:, 0].values
images = resampled_df.iloc[:, 1:].values.reshape(-1, 28, 28, 1)

# Define the ImageDataGenerator with augmentations
datagen = ImageDataGenerator(
    rotation_range=10,
    width_shift_range=0.1,
    height_shift_range=0.1,
    zoom_range=0.1,
)

# Augment the entire dataset
augmented_images = []
augmented_labels = []

for image, label in zip(images, labels):
    image = image.reshape(1, 28, 28, 1)  # Reshape to (1, 28, 28, 1) for the generator
    aug_iter = datagen.flow(image, batch_size=1)
    aug_image = next(aug_iter)[0].astype(np.float32)  # Normalize the image
    augmented_images.append(aug_image)
    augmented_labels.append(label)

# Convert lists to numpy arrays
augmented_images = np.array(augmented_images)
augmented_labels = np.array(augmented_labels)


# Flatten images back to the original format and create a new DataFrame
flattened_images = augmented_images.reshape(-1, 28*28)
augmented_df = pd.DataFrame(flattened_images)
augmented_df.insert(0, 'label', augmented_labels)

augmented_df.head()

	label	0	1	2	3	4	5	6	7	8	...	774	775	776	777	778	779	780	781	782	783
0	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
3	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
4	1.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.065547	0.006435	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

5 rows × 785 columns

Sample of the augmented dataframe

plot_random_images_per_class_from_dataframe(augmented_df, image_size=28, num_images_per_row=5)

Add the augmented images back to the dataframe

# Create a dictionary to rename columns from their current names to 0 to 784
column_names = {old_name: new_name for old_name, new_name in zip(augmented_df.columns, range(len(augmented_df.columns)))}

# Rename the columns of augmented_df
augmented_df.rename(columns=column_names, inplace=True)
augmented_df

# Concatenate the dataframes (Normalized DF and Augmented DF)
preprocessed_df = pd.concat([normalized_df, augmented_df], axis=0, ignore_index=True)
preprocessed_df[0] = preprocessed_df[0].astype(int)
# Display the first few rows of the combined dataframe
preprocessed_df

	0	1	2	3	4	5	6	7	8	9	...	775	776	777	778	779	780	781	782	783	784
0	23	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
1	7	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
2	16	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
3	15	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
4	23	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
90995	26	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
90996	26	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.002375	0.001046	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
90997	26	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.005981	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
90998	26	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
90999	26	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	...	0.000000	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

91000 rows × 785 columns

plot_class_distribution(preprocessed_df)

Evaluation Metrics

Loss (Generator Loss and Discriminator Loss)

Generator Loss

The generator loss measures how well the generator is performing in producing realistic images that can fool the discriminator. It is calculated based on the discriminator's feedback for the images generated by the generator. The goal of the generator is to minimize this loss, which means it aims to improve its ability to create images that the discriminator classifies as real.

Discriminator Loss

The discriminator loss evaluates how effectively the discriminator can distinguish between real and generated images. It is calculated by measuring the discriminator's accuracy in classifying real images from the training dataset as real (label 1) and the generated images as fake (label 0). The discriminator aims to minimize this loss, enhancing its ability to accurately differentiate between real and generated images.

Optimal Values

For optimal performance, both losses should be balanced. If the generator loss is significantly lower than the discriminator loss, it suggests that the generator is dominating the training, while if the discriminator loss is very low, it may indicate that the generator is struggling to produce convincing images.

def plot_losses(d_losses, g_losses):
    plt.figure(figsize=(10, 5))
    plt.plot(range(len(d_losses)), d_losses, label="Discriminator loss")
    plt.plot(range(len(g_losses)), g_losses, label="Generator loss")
    plt.title("Training Losses")
    plt.xlabel("Epoch")
    plt.ylabel("Loss")
    plt.legend()
    plt.grid(True)
    plt.show()

Accuracy (Discriminator Accuracy)

What discriminator accuracy measures

Discriminator accuracy reflects the model's ability to correctly identify real images as real (label 1) and generated images as fake (label 0).

Balance in Training

Ideally, the discriminator's accuracy should fluctuate during training. This fluctuation indicates that the generator is effectively challenging the discriminator, contributing to a balanced training process where both components of the GAN improve.

def plot_accuracy(d_accuracy):
    plt.figure(figsize=(10, 5))
    plt.plot(range(len(d_accuracy)), d_accuracy, label="Discriminator Accuracy")
    plt.title("Training Accuracy")
    plt.xlabel("Epoch")
    plt.ylabel("Accuracy")
    plt.legend()
    plt.grid(True)
    plt.show()

Wasserstein Distances

What is Wasserstein Distances

Wasserstein distance, also known as Earth Mover's Distance (EMD), is a measure of the distance between two probability distributions. It quantifies how much "work" is needed to transform one distribution into another, considering the distribution's underlying geometry.

What is Wasserstein Distances used for

Wasserstein GANs (WGANs) represent an improvement over traditional GANs by utilizing Wasserstein distance as their loss function, which enhances the stability of the training process. This approach effectively addresses common challenges faced in GAN training, such as mode collapse, where the generator produces a limited variety of outputs, and the vanishing gradient problem, which can hinder the learning of the generator and discriminator.

References

https://www.stat.cmu.edu/~larry/=sml/Opt.pdf

def plot_wasserstein_distance(wasserstein_distances):
    plt.plot(wasserstein_distances, label='Wasserstein Distance')
    plt.xlabel('Epoch')
    plt.ylabel('Wasserstein Distance')
    plt.legend()
    plt.title('Wasserstein Distance Over Epochs')
    plt.show()

Kullback-Leibler (KL) Divergence

What is KL Divergence

Kullback-Leibler divergence metric (relative entropy) is a statistical measurement from information theory that is commonly used to quantify the difference between one probability distribution from a reference probability distribution.

The divergence between two probability distributions quantifies how much the two differ from each other.

Formula for KL Divergence

How is KL Divergence used to evaluate GANs

GANs aim to generate samples that resemble the true data distribution. KL divergence can quantify how well the distribution of generated samples matches the distribution of real data.

By comparing the distributions of generated and real samples, we can compute KL divergence to assess the fidelity and diversity of the generated samples.

What is 'Good' Value for Kullback-Leibler (KL) Divergence

KL divergence is a measure of difference between distributions and does not have a standardized scale. The value of KL divergence depends on the specific distributions being compared and their variability.

Typically, in GANs, the goal of the generator is to minimize the KL divergence between the distribution of generated samples and the distribution of real data. A lower KL divergence indicates that the generator is producing samples that closely match the real data distribution in terms of statistical properties. Therefore, from this perspective, a lower value of KL divergence is considered better.

References

https://towardsdatascience.com/understanding-kl-divergence-f3ddc8dff254

def compute_kl_divergence(generator, real_images, num_samples):
    # Generate fake images using the generator
    noise = np.random.normal(0, 1, (num_samples, 100))
    labels = np.random.randint(1, 27, num_samples).reshape(-1, 1)
    fake_images = generator.predict([noise, labels])
    
    # Compute histograms of pixel intensities for real and generated images
    hist_real, _ = np.histogram(real_images.flatten(), bins=256, range=(0, 1))
    hist_gen, _ = np.histogram(fake_images.flatten(), bins=256, range=(0, 1))
    
    # Normalize histograms to sum to 1
    hist_real = hist_real / np.sum(hist_real)
    hist_gen = hist_gen / np.sum(hist_gen)
    
    # Clip hist_gen to avoid log(0)
    hist_gen = np.clip(hist_gen, 1e-8, None)
    
    # Compute KL divergence
    kl_divergence = np.sum(hist_real * np.log(hist_real / hist_gen))
    
    return kl_divergence

Samples of Generated Images VS Real Images

What will we be doing

To compare real and generated images side by side, we place samples from both datasets next to each other to assess how closely they resemble each other visually, their overall quality, and how well they capture the characteristics of the original data distribution.

Criterias

• Evaluate how clear and detailed the images are. Real images typically have sharp details, and generated images should strive to match this quality.
• Look for any distortions, blurriness, or unnatural patterns in the generated images that are not present in real images.
• Look for diversity among generated images. A good generator should produce a variety of images that cover different aspects of the data distribution, rather than repeating a few similar patterns

def generate_images_for_class(cgan, class_label, num_samples=5):
    noise = np.random.normal(0, 1, (num_samples, cgan.latent_dim))
    sampled_labels = np.full((num_samples, 1), class_label)
    gen_imgs = cgan.generator.predict([noise, sampled_labels])
    gen_imgs = 0.5 * gen_imgs + 0.5  # Rescale images to 0 - 1 range
    return gen_imgs

def get_real_images_for_class(df, class_label, img_shape, num_samples=5):
    class_df = df[df.iloc[:, 0] == class_label]
    if len(class_df) < num_samples:
        print(f"Class {class_label} has less than {num_samples} images.")
        return np.empty((0, img_shape[0], img_shape[1], img_shape[2]))
    real_imgs = class_df.iloc[:num_samples, 1:].values
    real_imgs = real_imgs.reshape(-1, img_shape[0], img_shape[1], img_shape[2])
    return real_imgs

def compare_images(cgan, real_df, img_shape, num_samples=5):
    num_classes = cgan.num_classes
    fig, axs = plt.subplots(2 * num_classes, num_samples, figsize=(20, 10 * num_classes))  # Increase figure height for more space per row
    for class_label in range(1, num_classes + 1):  # Class labels start from 1
        gen_imgs = generate_images_for_class(cgan, class_label, num_samples)
        real_imgs = get_real_images_for_class(real_df, class_label, img_shape, num_samples)
        for i in range(num_samples):
            axs[2 * (class_label - 1), i].imshow(gen_imgs[i, :, :, 0], cmap='gray', aspect='auto', interpolation='nearest')  # Ensure nearest interpolation for sharp display
            axs[2 * (class_label - 1), i].set_title(f'Generated\nClass {map_labels(class_label)}')
            axs[2 * (class_label - 1), i].axis('off')
            axs[2 * (class_label - 1), i].set_aspect('equal')  # Ensure equal aspect ratio
            
            axs[2 * (class_label - 1) + 1, i].imshow(real_imgs[i, :, :, 0], cmap='gray', aspect='auto', interpolation='nearest')  # Ensure nearest interpolation for sharp display
            axs[2 * (class_label - 1) + 1, i].set_title(f'Real\nClass {map_labels(class_label)}')
            axs[2 * (class_label - 1) + 1, i].axis('off')
            axs[2 * (class_label - 1) + 1, i].set_aspect('equal')  # Ensure equal aspect ratio
                
    plt.tight_layout()
    plt.show()

Deep Convolutional GAN (DCGAN)

What is Deep Convolutional GAN

---

Deep Convolutional Generative Adversarial Network (DCGAN) is a type of GAN that leverages deep convolutional neural networks (CNNs) in both its generator and discriminator models.

Main Components of Deep Convolutional GAN

---

Generator Network

• Input Layer

  The input layer accepts a noise vector (latent space) typically sampled from a normal distribution.

• Dense Layer

  The dense layer transforms the noise vector into a higher-dimensional space

• Reshape Layer

  The reshape layer reshapes the dense layer output into a 3D tensor (height, width, channels)

• Upsampling Layer

  The upsampling layer increase the spatial dimensions of the input tensor (height and width) while keeping the number of channels the same

• Convolutional Layer

  The convolutional layer apply convolutional filters to the upsampled tensor to generate feature maps. These layers help in refining the upsampled image and adding more details

• Batch Normalization Layer

  The batch normalization layer normalize the outputs of the convolutional layers to improve training stability and performance

• Activation Functions

  Activation functions introduce non-linearity to the network, allowing it to learn more complex patterns

Discriminator Network

• Convolutional Layer

  The convolutional layer extract features from the input image. Each filter within the layer learns to detect specific patterns or features, such as edges, textures, shapes, or more complex structures, by convolving with the input data. Ultimately it converts the image into numerical values, allowing the neural network to interpret and extract relevant patterns

• Leaky ReLU Activation

  The leaky ReLU activation introduce non-linearity into the network, allowing it to learn more complex patterns. The Leaky ReLU helps prevent the dying ReLU problem by allowing a small gradient when the unit is not active.

• Dropout Layer

  The dropout layer prevent overfitting by randomly setting a fraction of input units to 0 during training. This forces the network to learn more robust features.

• Flatten Layer

  Convert the 3D tensor output from the convolutional layers into a 1D vector, which can be fed into a dense layer

• Dense Layer (Output)

  Perform the final classification by producing a single scalar output. This output is passed through a sigmoid activation function to produce a probability

How Deep Convolutional GAN Works

---

The generator starts with a random noise vector, typically sampled from a Gaussian or uniform distribution. This noise vector is fed through a series of deconvolutional (transposed convolutional) layers, which progressively upsample and refine it into a realistic image. The goal of the generator is to produce images that are indistinguishable from real ones.

On the other hand, the discriminator takes an image as input, which can either be a real image from the training dataset or a fake image generated by the generator. This image is processed through a series of convolutional layers that downsample it and extract key features, helping the discriminator learn to distinguish between real and fake images. The discriminator outputs a probability score indicating whether the image is real or fake.

The Training Process of Deep Convolutional GAN

---

First, real images are fed into the discriminator, and its weights are updated to maximize the probability of correctly identifying them as real. Next, generated images are fed into the discriminator, and its weights are updated to minimize the probability of incorrectly identifying them as real. This ensures the discriminator becomes better at distinguishing real images from generated ones.

After updating the discriminator, the generator is trained. During this step, the discriminator's weights are typically frozen to prevent them from being updated based on the generator's training. The generator's loss is calculated based on the discriminator's feedback, specifically aiming to minimize the probability of the discriminator correctly identifying generated images as fake.

---

References

https://www.oreilly.com/content/deep-convolutional-generative-adversarial-networks-with-tensorflow/

https://jonathan-hui.medium.com/gan-dcgan-deep-convolutional-generative-adversarial-networks-df855c438f

Base Model

class DCGAN():
    
    # this is the function to build the generator neural network
    def build_generator(self):
        model = Sequential()

        model.add(Dense(128 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 128)))
        
        model.add(UpSampling2D())
        model.add(Conv2D(128, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(UpSampling2D())
        model.add(Conv2D(64, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(self.channels, kernel_size=3, padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)
    
    
    def build_discriminator(self):
        model = Sequential(name='Discriminator')
        
        model.add(Conv2D(128, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Flatten())
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        img = Input(shape=self.img_shape)
        validity = model(img)
        return Model(img, validity)
        
        
    def __init__(self, rows, cols, channels, z = 100):
        # Input shape
        self.img_rows = rows  # generated image height
        self.img_cols = cols  # generated image width
        self.channels = channels  # generated image channel
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = z  # the input is 1-D vector of noise
        # Reduce learning rate from 0.001 to 0.0002, and beta1 from 0.9 to 0.5, which can stablize training and reduce oscillation
        optimizer = Adam(learning_rate=0.0002, beta_1=0.5)
        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss='binary_crossentropy',
            optimizer=optimizer,
            metrics=['accuracy'])
        # Build the generator
        self.generator = self.build_generator()
        # The generator takes noise as input and generates images
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)
        # For the combined model we will only train the generator
        self.discriminator.trainable = False
        # The discriminator takes generated images as input and determines validity
        valid = self.discriminator(img)
        # The combined model (stacked generator and discriminator)
        # Trains the generator to fool the discriminator
        self.combined = Model(z, valid)
        self.combined.compile(loss='binary_crossentropy',
            optimizer=optimizer)
        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []
        
    def train(self, epochs, batch_size=128, save_interval=50):
        # Assuming your data is in a pandas DataFrame `df`
        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values  # assuming first column is labels, rest are pixels
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)  # reshape to image shape
        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))
        
        for epoch in range(epochs):
            # ---------------------
            # Train Discriminator
            # ---------------------
            # Select a random half of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs = X_train[idx]
            
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            gen_imgs = self.generator.predict(noise)
            
            # Train the discriminator (classify real images as 1 and generated images as 0)
            d_loss_real = self.discriminator.train_on_batch(imgs, valid)
            d_loss_fake = self.discriminator.train_on_batch(gen_imgs, fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)
            
            # ---------------------
            # Train Generator
            # ---------------------
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            
            # Train the generator (generator wants discriminator to predict generated images as 1)
            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            # Print progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100 * d_loss[1], g_loss))
            
            # If at save interval => save generated image samples
            if epoch % save_interval == 0:
                self.save_imgs(epoch)

    def save_imgs(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        # gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/dcgan', exist_ok=True)
        os.makedirs('generated_images/dcgan/base', exist_ok=True)
        fig.savefig("generated_images/dcgan/base/dcgan_{:d}.png".format(epoch))
        plt.close()

dcgan = DCGAN(28,28,1)
dcgan.train(epochs=5000, batch_size=256, save_interval=100)

Model: "Discriminator"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d (Conv2D)             (None, 14, 14, 128)       1280      
                                                                 
 leaky_re_lu (LeakyReLU)     (None, 14, 14, 128)       0         
                                                                 
 dropout (Dropout)           (None, 14, 14, 128)       0         
                                                                 
 conv2d_1 (Conv2D)           (None, 7, 7, 128)         147584    
                                                                 
 leaky_re_lu_1 (LeakyReLU)   (None, 7, 7, 128)         0         
                                                                 
 dropout_1 (Dropout)         (None, 7, 7, 128)         0         
                                                                 
 flatten (Flatten)           (None, 6272)              0         
                                                                 
 dense (Dense)               (None, 1)                 6273      
                                                                 
=================================================================
Total params: 155,137
Trainable params: 155,137
Non-trainable params: 0
_________________________________________________________________
Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_1 (Dense)             (None, 6272)              633472    
                                                                 
 reshape (Reshape)           (None, 7, 7, 128)         0         
                                                                 
 up_sampling2d (UpSampling2D  (None, 14, 14, 128)      0         
 )                                                               
                                                                 
 conv2d_2 (Conv2D)           (None, 14, 14, 128)       147584    
                                                                 
 batch_normalization (BatchN  (None, 14, 14, 128)      512       
 ormalization)                                                   
                                                                 
 leaky_re_lu_2 (LeakyReLU)   (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_1 (UpSampling  (None, 28, 28, 128)      0         
 2D)                                                             
                                                                 
 conv2d_3 (Conv2D)           (None, 28, 28, 64)        73792     
                                                                 
 batch_normalization_1 (Batc  (None, 28, 28, 64)       256       
 hNormalization)                                                 
                                                                 
 leaky_re_lu_3 (LeakyReLU)   (None, 28, 28, 64)        0         
                                                                 
 conv2d_4 (Conv2D)           (None, 28, 28, 1)         577       
                                                                 
 activation (Activation)     (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 856,193
Trainable params: 855,809
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 6s 3ms/step
0 [D loss: 0.709658, acc.: 37.89%] [G loss: 0.685417]
1/1 [==============================] - 0s 85ms/step
8/8 [==============================] - 0s 2ms/step
1 [D loss: 0.686491, acc.: 58.01%] [G loss: 0.710151]
8/8 [==============================] - 0s 2ms/step
2 [D loss: 0.664212, acc.: 83.59%] [G loss: 0.735865]
8/8 [==============================] - 0s 2ms/step
3 [D loss: 0.645622, acc.: 86.91%] [G loss: 0.761861]
8/8 [==============================] - 0s 2ms/step
4 [D loss: 0.626898, acc.: 85.16%] [G loss: 0.772953]
8/8 [==============================] - 0s 2ms/step
5 [D loss: 0.606446, acc.: 84.77%] [G loss: 0.786104]
8/8 [==============================] - 0s 2ms/step
6 [D loss: 0.588422, acc.: 84.18%] [G loss: 0.802528]
8/8 [==============================] - 0s 2ms/step
7 [D loss: 0.575564, acc.: 85.35%] [G loss: 0.807789]
8/8 [==============================] - 0s 2ms/step
8 [D loss: 0.573172, acc.: 79.10%] [G loss: 0.808588]
8/8 [==============================] - 0s 2ms/step
9 [D loss: 0.574138, acc.: 79.88%] [G loss: 0.799699]
8/8 [==============================] - 0s 2ms/step
10 [D loss: 0.580853, acc.: 82.81%] [G loss: 0.787338]
8/8 [==============================] - 0s 2ms/step
11 [D loss: 0.592003, acc.: 80.86%] [G loss: 0.757857]
8/8 [==============================] - 0s 2ms/step
12 [D loss: 0.594574, acc.: 82.23%] [G loss: 0.748037]
8/8 [==============================] - 0s 2ms/step
13 [D loss: 0.610064, acc.: 83.98%] [G loss: 0.730371]
8/8 [==============================] - 0s 2ms/step
14 [D loss: 0.628482, acc.: 83.01%] [G loss: 0.734116]
8/8 [==============================] - 0s 2ms/step
15 [D loss: 0.665008, acc.: 71.48%] [G loss: 0.714510]
8/8 [==============================] - 0s 2ms/step
16 [D loss: 0.679875, acc.: 61.72%] [G loss: 0.720695]
8/8 [==============================] - 0s 2ms/step
17 [D loss: 0.684688, acc.: 57.62%] [G loss: 0.730161]
8/8 [==============================] - 0s 2ms/step
18 [D loss: 0.680623, acc.: 61.33%] [G loss: 0.747187]
8/8 [==============================] - 0s 2ms/step
19 [D loss: 0.677030, acc.: 63.67%] [G loss: 0.763751]
8/8 [==============================] - 0s 2ms/step
20 [D loss: 0.677925, acc.: 66.60%] [G loss: 0.781976]
8/8 [==============================] - 0s 2ms/step
21 [D loss: 0.683043, acc.: 61.91%] [G loss: 0.789370]
8/8 [==============================] - 0s 2ms/step
22 [D loss: 0.684497, acc.: 57.81%] [G loss: 0.782611]
8/8 [==============================] - 0s 2ms/step
23 [D loss: 0.687542, acc.: 50.20%] [G loss: 0.764532]
8/8 [==============================] - 0s 2ms/step
24 [D loss: 0.700121, acc.: 39.45%] [G loss: 0.739196]
8/8 [==============================] - 0s 2ms/step
25 [D loss: 0.707980, acc.: 41.02%] [G loss: 0.699268]
8/8 [==============================] - 0s 2ms/step
26 [D loss: 0.710594, acc.: 44.34%] [G loss: 0.660402]
8/8 [==============================] - 0s 2ms/step
27 [D loss: 0.700660, acc.: 46.88%] [G loss: 0.629640]
8/8 [==============================] - 0s 2ms/step
28 [D loss: 0.698915, acc.: 48.63%] [G loss: 0.608487]
8/8 [==============================] - 0s 2ms/step
29 [D loss: 0.697305, acc.: 49.02%] [G loss: 0.602865]
8/8 [==============================] - 0s 2ms/step
30 [D loss: 0.699444, acc.: 49.80%] [G loss: 0.612350]
8/8 [==============================] - 0s 2ms/step
31 [D loss: 0.696531, acc.: 49.41%] [G loss: 0.622947]
8/8 [==============================] - 0s 2ms/step
32 [D loss: 0.701067, acc.: 47.66%] [G loss: 0.636942]
8/8 [==============================] - 0s 2ms/step
33 [D loss: 0.703377, acc.: 46.88%] [G loss: 0.644833]
8/8 [==============================] - 0s 2ms/step
34 [D loss: 0.703233, acc.: 46.29%] [G loss: 0.652210]
8/8 [==============================] - 0s 2ms/step
35 [D loss: 0.696969, acc.: 46.88%] [G loss: 0.657976]
8/8 [==============================] - 0s 2ms/step
36 [D loss: 0.690229, acc.: 47.46%] [G loss: 0.665662]
8/8 [==============================] - 0s 2ms/step
37 [D loss: 0.680264, acc.: 50.20%] [G loss: 0.671345]
8/8 [==============================] - 0s 2ms/step
38 [D loss: 0.675822, acc.: 51.56%] [G loss: 0.679657]
8/8 [==============================] - 0s 2ms/step
39 [D loss: 0.676599, acc.: 51.56%] [G loss: 0.683317]
8/8 [==============================] - 0s 2ms/step
40 [D loss: 0.669990, acc.: 59.57%] [G loss: 0.686317]
8/8 [==============================] - 0s 2ms/step
41 [D loss: 0.668502, acc.: 60.16%] [G loss: 0.687444]
8/8 [==============================] - 0s 2ms/step
42 [D loss: 0.672059, acc.: 59.96%] [G loss: 0.687400]
8/8 [==============================] - 0s 2ms/step
43 [D loss: 0.664539, acc.: 64.45%] [G loss: 0.686888]
8/8 [==============================] - 0s 2ms/step
44 [D loss: 0.662282, acc.: 66.21%] [G loss: 0.675845]
8/8 [==============================] - 0s 2ms/step
45 [D loss: 0.662179, acc.: 69.34%] [G loss: 0.662251]
8/8 [==============================] - 0s 2ms/step
46 [D loss: 0.655503, acc.: 72.27%] [G loss: 0.649617]
8/8 [==============================] - 0s 2ms/step
47 [D loss: 0.660491, acc.: 71.29%] [G loss: 0.633266]
8/8 [==============================] - 0s 2ms/step
48 [D loss: 0.673529, acc.: 53.91%] [G loss: 0.621036]
8/8 [==============================] - 0s 2ms/step
49 [D loss: 0.670747, acc.: 58.98%] [G loss: 0.607406]
8/8 [==============================] - 0s 2ms/step
50 [D loss: 0.676096, acc.: 53.52%] [G loss: 0.597678]
8/8 [==============================] - 0s 2ms/step
51 [D loss: 0.689258, acc.: 45.31%] [G loss: 0.588384]
8/8 [==============================] - 0s 2ms/step
52 [D loss: 0.691264, acc.: 45.51%] [G loss: 0.584862]
8/8 [==============================] - 0s 2ms/step
53 [D loss: 0.695672, acc.: 44.14%] [G loss: 0.579142]
8/8 [==============================] - 0s 2ms/step
54 [D loss: 0.699198, acc.: 42.77%] [G loss: 0.580807]
8/8 [==============================] - 0s 2ms/step
55 [D loss: 0.710798, acc.: 42.77%] [G loss: 0.579843]
8/8 [==============================] - 0s 2ms/step
56 [D loss: 0.708637, acc.: 43.75%] [G loss: 0.582975]
8/8 [==============================] - 0s 2ms/step
57 [D loss: 0.708183, acc.: 44.53%] [G loss: 0.585483]
8/8 [==============================] - 0s 2ms/step
58 [D loss: 0.708645, acc.: 45.70%] [G loss: 0.589875]
8/8 [==============================] - 0s 2ms/step
59 [D loss: 0.707482, acc.: 47.27%] [G loss: 0.593368]
8/8 [==============================] - 0s 2ms/step
60 [D loss: 0.698961, acc.: 49.22%] [G loss: 0.598285]
8/8 [==============================] - 0s 2ms/step
61 [D loss: 0.698751, acc.: 48.63%] [G loss: 0.602704]
8/8 [==============================] - 0s 2ms/step
62 [D loss: 0.694276, acc.: 49.41%] [G loss: 0.607757]
8/8 [==============================] - 0s 2ms/step
63 [D loss: 0.689281, acc.: 49.80%] [G loss: 0.606589]
8/8 [==============================] - 0s 2ms/step
64 [D loss: 0.684446, acc.: 49.80%] [G loss: 0.607108]
8/8 [==============================] - 0s 2ms/step
65 [D loss: 0.684858, acc.: 50.00%] [G loss: 0.606809]
8/8 [==============================] - 0s 2ms/step
66 [D loss: 0.675560, acc.: 50.00%] [G loss: 0.610130]
8/8 [==============================] - 0s 2ms/step
67 [D loss: 0.681586, acc.: 49.80%] [G loss: 0.608948]
8/8 [==============================] - 0s 2ms/step
68 [D loss: 0.684985, acc.: 49.80%] [G loss: 0.607713]
8/8 [==============================] - 0s 2ms/step
69 [D loss: 0.685957, acc.: 50.00%] [G loss: 0.605888]
8/8 [==============================] - 0s 2ms/step
70 [D loss: 0.693763, acc.: 50.00%] [G loss: 0.608174]
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71 [D loss: 0.693571, acc.: 49.61%] [G loss: 0.609280]
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72 [D loss: 0.707518, acc.: 49.22%] [G loss: 0.600123]
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73 [D loss: 0.712471, acc.: 48.63%] [G loss: 0.604275]
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74 [D loss: 0.718882, acc.: 48.44%] [G loss: 0.607934]
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75 [D loss: 0.722337, acc.: 47.66%] [G loss: 0.622676]
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76 [D loss: 0.716234, acc.: 45.51%] [G loss: 0.641760]
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77 [D loss: 0.709880, acc.: 44.92%] [G loss: 0.660846]
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78 [D loss: 0.707253, acc.: 43.36%] [G loss: 0.679252]
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79 [D loss: 0.704174, acc.: 40.23%] [G loss: 0.689054]
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80 [D loss: 0.702056, acc.: 42.77%] [G loss: 0.697428]
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81 [D loss: 0.690994, acc.: 49.22%] [G loss: 0.705645]
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82 [D loss: 0.683445, acc.: 55.08%] [G loss: 0.712229]
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83 [D loss: 0.680418, acc.: 59.18%] [G loss: 0.710131]
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84 [D loss: 0.678711, acc.: 58.40%] [G loss: 0.711635]
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85 [D loss: 0.672419, acc.: 61.72%] [G loss: 0.708417]
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86 [D loss: 0.679423, acc.: 57.62%] [G loss: 0.692648]
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87 [D loss: 0.693500, acc.: 50.20%] [G loss: 0.677325]
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88 [D loss: 0.700785, acc.: 46.68%] [G loss: 0.654928]
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89 [D loss: 0.701207, acc.: 43.36%] [G loss: 0.634065]
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90 [D loss: 0.699708, acc.: 43.16%] [G loss: 0.620629]
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91 [D loss: 0.703284, acc.: 42.38%] [G loss: 0.607868]
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92 [D loss: 0.707067, acc.: 40.82%] [G loss: 0.606617]
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93 [D loss: 0.716004, acc.: 35.55%] [G loss: 0.601594]
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94 [D loss: 0.726803, acc.: 31.64%] [G loss: 0.603354]
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95 [D loss: 0.722025, acc.: 35.35%] [G loss: 0.604943]
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96 [D loss: 0.728348, acc.: 32.03%] [G loss: 0.610271]
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97 [D loss: 0.724364, acc.: 33.98%] [G loss: 0.617990]
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98 [D loss: 0.717681, acc.: 38.09%] [G loss: 0.624353]
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99 [D loss: 0.715488, acc.: 37.30%] [G loss: 0.631835]
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100 [D loss: 0.708204, acc.: 39.84%] [G loss: 0.639044]
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101 [D loss: 0.700623, acc.: 43.55%] [G loss: 0.645388]
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102 [D loss: 0.690060, acc.: 48.05%] [G loss: 0.650628]
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103 [D loss: 0.683370, acc.: 48.83%] [G loss: 0.653791]
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104 [D loss: 0.676974, acc.: 50.20%] [G loss: 0.658118]
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105 [D loss: 0.673786, acc.: 51.17%] [G loss: 0.660597]
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106 [D loss: 0.668835, acc.: 52.34%] [G loss: 0.663809]
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107 [D loss: 0.662821, acc.: 52.15%] [G loss: 0.664069]
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108 [D loss: 0.662785, acc.: 54.69%] [G loss: 0.660676]
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109 [D loss: 0.664305, acc.: 51.76%] [G loss: 0.662998]
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110 [D loss: 0.664626, acc.: 52.54%] [G loss: 0.657488]
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111 [D loss: 0.671309, acc.: 51.76%] [G loss: 0.658214]
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112 [D loss: 0.673669, acc.: 51.37%] [G loss: 0.656794]
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113 [D loss: 0.686572, acc.: 48.24%] [G loss: 0.658421]
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114 [D loss: 0.691074, acc.: 49.02%] [G loss: 0.652063]
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115 [D loss: 0.706119, acc.: 47.46%] [G loss: 0.643915]
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116 [D loss: 0.716657, acc.: 43.36%] [G loss: 0.641328]
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117 [D loss: 0.724980, acc.: 41.41%] [G loss: 0.645321]
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118 [D loss: 0.723994, acc.: 38.48%] [G loss: 0.645306]
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119 [D loss: 0.724181, acc.: 33.79%] [G loss: 0.657014]
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120 [D loss: 0.722705, acc.: 33.59%] [G loss: 0.668776]
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121 [D loss: 0.714894, acc.: 37.89%] [G loss: 0.686524]
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122 [D loss: 0.707688, acc.: 38.87%] [G loss: 0.712135]
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123 [D loss: 0.697013, acc.: 49.41%] [G loss: 0.729687]
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124 [D loss: 0.693063, acc.: 53.52%] [G loss: 0.744630]
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125 [D loss: 0.697270, acc.: 48.44%] [G loss: 0.748033]
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126 [D loss: 0.703832, acc.: 40.23%] [G loss: 0.734335]
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127 [D loss: 0.702321, acc.: 38.67%] [G loss: 0.712747]
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128 [D loss: 0.706451, acc.: 34.38%] [G loss: 0.693371]
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129 [D loss: 0.695654, acc.: 40.62%] [G loss: 0.675920]
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130 [D loss: 0.692138, acc.: 44.34%] [G loss: 0.665591]
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131 [D loss: 0.690857, acc.: 47.07%] [G loss: 0.656218]
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132 [D loss: 0.691347, acc.: 48.05%] [G loss: 0.646929]
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133 [D loss: 0.696492, acc.: 44.73%] [G loss: 0.653626]
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134 [D loss: 0.693102, acc.: 48.83%] [G loss: 0.653736]
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135 [D loss: 0.691806, acc.: 49.80%] [G loss: 0.661847]
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136 [D loss: 0.695882, acc.: 46.88%] [G loss: 0.663859]
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137 [D loss: 0.700428, acc.: 47.07%] [G loss: 0.663878]
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138 [D loss: 0.711321, acc.: 37.30%] [G loss: 0.654347]
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139 [D loss: 0.721814, acc.: 33.20%] [G loss: 0.651702]
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140 [D loss: 0.725108, acc.: 33.01%] [G loss: 0.643341]
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141 [D loss: 0.725854, acc.: 32.23%] [G loss: 0.639463]
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142 [D loss: 0.719329, acc.: 35.94%] [G loss: 0.639847]
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143 [D loss: 0.717710, acc.: 33.79%] [G loss: 0.649845]
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144 [D loss: 0.716030, acc.: 34.57%] [G loss: 0.658777]
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145 [D loss: 0.712705, acc.: 35.16%] [G loss: 0.664926]
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146 [D loss: 0.707574, acc.: 38.09%] [G loss: 0.671459]
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147 [D loss: 0.704390, acc.: 36.91%] [G loss: 0.683592]
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148 [D loss: 0.699349, acc.: 41.41%] [G loss: 0.689957]
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149 [D loss: 0.690353, acc.: 50.78%] [G loss: 0.696522]
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150 [D loss: 0.683804, acc.: 55.66%] [G loss: 0.701413]
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151 [D loss: 0.679601, acc.: 61.13%] [G loss: 0.702805]
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152 [D loss: 0.677011, acc.: 63.28%] [G loss: 0.705644]
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153 [D loss: 0.674268, acc.: 63.87%] [G loss: 0.701868]
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154 [D loss: 0.673320, acc.: 62.89%] [G loss: 0.704053]
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155 [D loss: 0.677835, acc.: 58.01%] [G loss: 0.703707]
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156 [D loss: 0.681729, acc.: 54.69%] [G loss: 0.702099]
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157 [D loss: 0.684411, acc.: 55.27%] [G loss: 0.702409]
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158 [D loss: 0.691170, acc.: 50.20%] [G loss: 0.702021]
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159 [D loss: 0.698878, acc.: 45.31%] [G loss: 0.705629]
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160 [D loss: 0.700611, acc.: 45.90%] [G loss: 0.702651]
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161 [D loss: 0.704572, acc.: 42.38%] [G loss: 0.692301]
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162 [D loss: 0.709771, acc.: 35.16%] [G loss: 0.687151]
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163 [D loss: 0.715974, acc.: 31.84%] [G loss: 0.674024]
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164 [D loss: 0.720080, acc.: 32.03%] [G loss: 0.672535]
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165 [D loss: 0.720532, acc.: 30.86%] [G loss: 0.675485]
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166 [D loss: 0.712668, acc.: 39.45%] [G loss: 0.688918]
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167 [D loss: 0.704099, acc.: 44.14%] [G loss: 0.708260]
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168 [D loss: 0.695704, acc.: 48.44%] [G loss: 0.727233]
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169 [D loss: 0.688582, acc.: 57.23%] [G loss: 0.742252]
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170 [D loss: 0.690588, acc.: 54.69%] [G loss: 0.742770]
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171 [D loss: 0.691313, acc.: 52.34%] [G loss: 0.730618]
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172 [D loss: 0.697197, acc.: 43.16%] [G loss: 0.713735]
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173 [D loss: 0.697804, acc.: 43.75%] [G loss: 0.694733]
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174 [D loss: 0.696890, acc.: 42.97%] [G loss: 0.674166]
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175 [D loss: 0.699912, acc.: 44.14%] [G loss: 0.665703]
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176 [D loss: 0.701974, acc.: 45.31%] [G loss: 0.658983]
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177 [D loss: 0.702593, acc.: 45.12%] [G loss: 0.653528]
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178 [D loss: 0.705396, acc.: 45.70%] [G loss: 0.655614]
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179 [D loss: 0.703729, acc.: 40.62%] [G loss: 0.664298]
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180 [D loss: 0.705655, acc.: 40.62%] [G loss: 0.668977]
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181 [D loss: 0.708852, acc.: 36.72%] [G loss: 0.671619]
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182 [D loss: 0.707869, acc.: 37.50%] [G loss: 0.673231]
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183 [D loss: 0.709681, acc.: 33.01%] [G loss: 0.674651]
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184 [D loss: 0.706478, acc.: 36.91%] [G loss: 0.678312]
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185 [D loss: 0.705563, acc.: 34.77%] [G loss: 0.677698]
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186 [D loss: 0.701207, acc.: 41.60%] [G loss: 0.679314]
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187 [D loss: 0.697336, acc.: 44.73%] [G loss: 0.679708]
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188 [D loss: 0.694835, acc.: 47.66%] [G loss: 0.678818]
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189 [D loss: 0.694897, acc.: 45.90%] [G loss: 0.681339]
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190 [D loss: 0.693272, acc.: 50.59%] [G loss: 0.683618]
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191 [D loss: 0.690043, acc.: 52.54%] [G loss: 0.687902]
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192 [D loss: 0.691678, acc.: 49.61%] [G loss: 0.689788]
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193 [D loss: 0.690719, acc.: 54.88%] [G loss: 0.688059]
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194 [D loss: 0.695160, acc.: 46.09%] [G loss: 0.691872]
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195 [D loss: 0.692646, acc.: 49.61%] [G loss: 0.694626]
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196 [D loss: 0.694513, acc.: 47.66%] [G loss: 0.692286]
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197 [D loss: 0.694707, acc.: 48.05%] [G loss: 0.688595]
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198 [D loss: 0.696562, acc.: 46.09%] [G loss: 0.691351]
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199 [D loss: 0.700007, acc.: 43.55%] [G loss: 0.691161]
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200 [D loss: 0.699989, acc.: 42.19%] [G loss: 0.693214]
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201 [D loss: 0.703421, acc.: 38.48%] [G loss: 0.694375]
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202 [D loss: 0.700996, acc.: 39.65%] [G loss: 0.696253]
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203 [D loss: 0.701475, acc.: 39.45%] [G loss: 0.698740]
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204 [D loss: 0.698211, acc.: 44.34%] [G loss: 0.701741]
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205 [D loss: 0.700949, acc.: 39.84%] [G loss: 0.706733]
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206 [D loss: 0.694668, acc.: 49.22%] [G loss: 0.707659]
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207 [D loss: 0.698042, acc.: 44.73%] [G loss: 0.708530]
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208 [D loss: 0.698651, acc.: 43.36%] [G loss: 0.707555]
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209 [D loss: 0.698716, acc.: 44.53%] [G loss: 0.705172]
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210 [D loss: 0.697376, acc.: 46.48%] [G loss: 0.707161]
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211 [D loss: 0.698180, acc.: 43.36%] [G loss: 0.708078]
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212 [D loss: 0.693452, acc.: 52.15%] [G loss: 0.706597]
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213 [D loss: 0.698535, acc.: 46.29%] [G loss: 0.705233]
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214 [D loss: 0.695482, acc.: 47.66%] [G loss: 0.700439]
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215 [D loss: 0.697129, acc.: 47.66%] [G loss: 0.693616]
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216 [D loss: 0.699425, acc.: 43.55%] [G loss: 0.697997]
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217 [D loss: 0.698189, acc.: 44.73%] [G loss: 0.691323]
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218 [D loss: 0.697310, acc.: 46.88%] [G loss: 0.689577]
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219 [D loss: 0.698010, acc.: 47.66%] [G loss: 0.684314]
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220 [D loss: 0.698338, acc.: 44.73%] [G loss: 0.685139]
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221 [D loss: 0.698130, acc.: 46.09%] [G loss: 0.684185]
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222 [D loss: 0.696920, acc.: 49.02%] [G loss: 0.686809]
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223 [D loss: 0.695128, acc.: 47.07%] [G loss: 0.688200]
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224 [D loss: 0.697748, acc.: 43.55%] [G loss: 0.689712]
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225 [D loss: 0.697403, acc.: 45.31%] [G loss: 0.689679]
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226 [D loss: 0.696546, acc.: 47.07%] [G loss: 0.686508]
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227 [D loss: 0.700829, acc.: 43.55%] [G loss: 0.682759]
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228 [D loss: 0.703149, acc.: 41.21%] [G loss: 0.684747]
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229 [D loss: 0.700737, acc.: 42.38%] [G loss: 0.682480]
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230 [D loss: 0.700042, acc.: 41.99%] [G loss: 0.682540]
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231 [D loss: 0.699896, acc.: 42.77%] [G loss: 0.684048]
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232 [D loss: 0.697500, acc.: 43.36%] [G loss: 0.683117]
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233 [D loss: 0.696215, acc.: 44.14%] [G loss: 0.684670]
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234 [D loss: 0.694726, acc.: 45.51%] [G loss: 0.684305]
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235 [D loss: 0.695247, acc.: 46.09%] [G loss: 0.686541]
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236 [D loss: 0.691949, acc.: 49.41%] [G loss: 0.692566]
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237 [D loss: 0.689992, acc.: 53.32%] [G loss: 0.692100]
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238 [D loss: 0.688433, acc.: 54.88%] [G loss: 0.694439]
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239 [D loss: 0.687268, acc.: 59.77%] [G loss: 0.696882]
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240 [D loss: 0.683280, acc.: 62.30%] [G loss: 0.698106]
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241 [D loss: 0.683250, acc.: 64.65%] [G loss: 0.702810]
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242 [D loss: 0.683325, acc.: 62.11%] [G loss: 0.703294]
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243 [D loss: 0.684514, acc.: 61.91%] [G loss: 0.703643]
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244 [D loss: 0.684000, acc.: 59.77%] [G loss: 0.707348]
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245 [D loss: 0.681700, acc.: 64.26%] [G loss: 0.700408]
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246 [D loss: 0.686092, acc.: 58.01%] [G loss: 0.700826]
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247 [D loss: 0.686693, acc.: 59.57%] [G loss: 0.690281]
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248 [D loss: 0.693985, acc.: 52.93%] [G loss: 0.687991]
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249 [D loss: 0.697747, acc.: 48.24%] [G loss: 0.685583]
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250 [D loss: 0.701818, acc.: 45.12%] [G loss: 0.680641]
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251 [D loss: 0.707949, acc.: 39.45%] [G loss: 0.678970]
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252 [D loss: 0.706573, acc.: 40.62%] [G loss: 0.671680]
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253 [D loss: 0.710360, acc.: 40.82%] [G loss: 0.668735]
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254 [D loss: 0.711493, acc.: 36.72%] [G loss: 0.668752]
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255 [D loss: 0.713172, acc.: 33.79%] [G loss: 0.671282]
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256 [D loss: 0.714549, acc.: 30.08%] [G loss: 0.676105]
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257 [D loss: 0.708173, acc.: 32.42%] [G loss: 0.684339]
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258 [D loss: 0.708930, acc.: 31.64%] [G loss: 0.686017]
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259 [D loss: 0.706067, acc.: 35.55%] [G loss: 0.694955]
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260 [D loss: 0.703663, acc.: 36.52%] [G loss: 0.701177]
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261 [D loss: 0.697351, acc.: 47.07%] [G loss: 0.709900]
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262 [D loss: 0.696161, acc.: 46.29%] [G loss: 0.711504]
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263 [D loss: 0.694561, acc.: 48.05%] [G loss: 0.713673]
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264 [D loss: 0.694335, acc.: 50.59%] [G loss: 0.716493]
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265 [D loss: 0.692536, acc.: 52.54%] [G loss: 0.713368]
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266 [D loss: 0.692664, acc.: 55.08%] [G loss: 0.709638]
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267 [D loss: 0.690528, acc.: 56.25%] [G loss: 0.709128]
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268 [D loss: 0.691839, acc.: 53.32%] [G loss: 0.704342]
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269 [D loss: 0.690495, acc.: 53.52%] [G loss: 0.703794]
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270 [D loss: 0.689200, acc.: 56.45%] [G loss: 0.702563]
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271 [D loss: 0.687215, acc.: 61.91%] [G loss: 0.700582]
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272 [D loss: 0.688469, acc.: 57.62%] [G loss: 0.697711]
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273 [D loss: 0.689616, acc.: 56.25%] [G loss: 0.692362]
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274 [D loss: 0.691385, acc.: 53.52%] [G loss: 0.693896]
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275 [D loss: 0.690471, acc.: 52.15%] [G loss: 0.688004]
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276 [D loss: 0.693486, acc.: 50.59%] [G loss: 0.690559]
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277 [D loss: 0.692972, acc.: 51.56%] [G loss: 0.687783]
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278 [D loss: 0.699930, acc.: 43.16%] [G loss: 0.687646]
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279 [D loss: 0.697158, acc.: 46.88%] [G loss: 0.686492]
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280 [D loss: 0.699222, acc.: 41.41%] [G loss: 0.681271]
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281 [D loss: 0.702353, acc.: 42.77%] [G loss: 0.681293]
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282 [D loss: 0.706441, acc.: 32.23%] [G loss: 0.682054]
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283 [D loss: 0.707725, acc.: 31.84%] [G loss: 0.678043]
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284 [D loss: 0.706953, acc.: 31.64%] [G loss: 0.678660]
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285 [D loss: 0.705598, acc.: 34.57%] [G loss: 0.674816]
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286 [D loss: 0.706114, acc.: 33.40%] [G loss: 0.676393]
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287 [D loss: 0.704102, acc.: 36.72%] [G loss: 0.675030]
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288 [D loss: 0.703987, acc.: 36.52%] [G loss: 0.677200]
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289 [D loss: 0.699139, acc.: 42.77%] [G loss: 0.681094]
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290 [D loss: 0.699684, acc.: 42.97%] [G loss: 0.688790]
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291 [D loss: 0.696474, acc.: 46.29%] [G loss: 0.692066]
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292 [D loss: 0.695093, acc.: 49.61%] [G loss: 0.696417]
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293 [D loss: 0.693690, acc.: 50.39%] [G loss: 0.700144]
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294 [D loss: 0.690766, acc.: 57.81%] [G loss: 0.705126]
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295 [D loss: 0.688295, acc.: 60.55%] [G loss: 0.706449]
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296 [D loss: 0.685550, acc.: 60.16%] [G loss: 0.706916]
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297 [D loss: 0.685236, acc.: 62.70%] [G loss: 0.709750]
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298 [D loss: 0.685114, acc.: 62.50%] [G loss: 0.710092]
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299 [D loss: 0.682175, acc.: 66.21%] [G loss: 0.705754]
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301 [D loss: 0.686145, acc.: 61.13%] [G loss: 0.702454]
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302 [D loss: 0.686767, acc.: 62.11%] [G loss: 0.698770]
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303 [D loss: 0.690634, acc.: 56.64%] [G loss: 0.704454]
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304 [D loss: 0.691419, acc.: 52.93%] [G loss: 0.699995]
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305 [D loss: 0.694170, acc.: 51.76%] [G loss: 0.702674]
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306 [D loss: 0.695108, acc.: 52.34%] [G loss: 0.698610]
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307 [D loss: 0.698293, acc.: 45.70%] [G loss: 0.697600]
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308 [D loss: 0.697994, acc.: 49.02%] [G loss: 0.697319]
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309 [D loss: 0.702934, acc.: 40.62%] [G loss: 0.695145]
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310 [D loss: 0.704457, acc.: 39.65%] [G loss: 0.696801]
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311 [D loss: 0.707713, acc.: 35.94%] [G loss: 0.694407]
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312 [D loss: 0.706238, acc.: 35.35%] [G loss: 0.697505]
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313 [D loss: 0.707430, acc.: 34.96%] [G loss: 0.694687]
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314 [D loss: 0.712504, acc.: 27.73%] [G loss: 0.689738]
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315 [D loss: 0.708389, acc.: 32.81%] [G loss: 0.694563]
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316 [D loss: 0.706693, acc.: 30.66%] [G loss: 0.693824]
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317 [D loss: 0.706205, acc.: 31.45%] [G loss: 0.697027]
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318 [D loss: 0.706243, acc.: 33.79%] [G loss: 0.692636]
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319 [D loss: 0.702933, acc.: 36.13%] [G loss: 0.694850]
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320 [D loss: 0.703055, acc.: 35.35%] [G loss: 0.692378]
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321 [D loss: 0.700946, acc.: 39.45%] [G loss: 0.697096]
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322 [D loss: 0.700429, acc.: 38.87%] [G loss: 0.697867]
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323 [D loss: 0.699313, acc.: 41.21%] [G loss: 0.699101]
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324 [D loss: 0.697459, acc.: 43.95%] [G loss: 0.701558]
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325 [D loss: 0.696370, acc.: 44.34%] [G loss: 0.701578]
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326 [D loss: 0.698129, acc.: 44.34%] [G loss: 0.705307]
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327 [D loss: 0.695376, acc.: 47.27%] [G loss: 0.703673]
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328 [D loss: 0.696372, acc.: 45.31%] [G loss: 0.705996]
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329 [D loss: 0.693803, acc.: 51.17%] [G loss: 0.703131]
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330 [D loss: 0.692961, acc.: 50.39%] [G loss: 0.704068]
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331 [D loss: 0.696198, acc.: 46.48%] [G loss: 0.701759]
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332 [D loss: 0.695339, acc.: 47.85%] [G loss: 0.700559]
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333 [D loss: 0.694520, acc.: 49.02%] [G loss: 0.703925]
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334 [D loss: 0.695102, acc.: 48.83%] [G loss: 0.700541]
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335 [D loss: 0.696840, acc.: 44.34%] [G loss: 0.702496]
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336 [D loss: 0.696589, acc.: 48.24%] [G loss: 0.703837]
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337 [D loss: 0.697282, acc.: 45.31%] [G loss: 0.699159]
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338 [D loss: 0.699646, acc.: 41.41%] [G loss: 0.700271]
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339 [D loss: 0.698058, acc.: 43.16%] [G loss: 0.698491]
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340 [D loss: 0.695168, acc.: 47.46%] [G loss: 0.701482]
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341 [D loss: 0.698334, acc.: 42.19%] [G loss: 0.700378]
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342 [D loss: 0.699253, acc.: 40.82%] [G loss: 0.700427]
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343 [D loss: 0.697174, acc.: 42.77%] [G loss: 0.699433]
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344 [D loss: 0.697511, acc.: 43.95%] [G loss: 0.701356]
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345 [D loss: 0.697583, acc.: 41.60%] [G loss: 0.703360]
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346 [D loss: 0.697485, acc.: 45.31%] [G loss: 0.702043]
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347 [D loss: 0.697963, acc.: 44.53%] [G loss: 0.706065]
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348 [D loss: 0.698891, acc.: 41.02%] [G loss: 0.705508]
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349 [D loss: 0.696870, acc.: 44.73%] [G loss: 0.707293]
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350 [D loss: 0.697679, acc.: 41.41%] [G loss: 0.706370]
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351 [D loss: 0.698327, acc.: 42.19%] [G loss: 0.709218]
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352 [D loss: 0.694551, acc.: 47.07%] [G loss: 0.709047]
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353 [D loss: 0.695903, acc.: 49.41%] [G loss: 0.708927]
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354 [D loss: 0.695973, acc.: 47.46%] [G loss: 0.709947]
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355 [D loss: 0.693723, acc.: 49.22%] [G loss: 0.712906]
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356 [D loss: 0.691335, acc.: 53.32%] [G loss: 0.715885]
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357 [D loss: 0.691011, acc.: 54.30%] [G loss: 0.718593]
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358 [D loss: 0.692726, acc.: 51.56%] [G loss: 0.717307]
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359 [D loss: 0.690315, acc.: 56.64%] [G loss: 0.719389]
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360 [D loss: 0.693089, acc.: 51.17%] [G loss: 0.719988]
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361 [D loss: 0.689920, acc.: 53.52%] [G loss: 0.720901]
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362 [D loss: 0.692295, acc.: 53.12%] [G loss: 0.716817]
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363 [D loss: 0.693245, acc.: 49.61%] [G loss: 0.714360]
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364 [D loss: 0.694633, acc.: 51.76%] [G loss: 0.715532]
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365 [D loss: 0.695516, acc.: 48.63%] [G loss: 0.708477]
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366 [D loss: 0.698965, acc.: 45.70%] [G loss: 0.700374]
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367 [D loss: 0.696387, acc.: 46.09%] [G loss: 0.694291]
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368 [D loss: 0.703253, acc.: 38.67%] [G loss: 0.692881]
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369 [D loss: 0.701504, acc.: 40.82%] [G loss: 0.687406]
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370 [D loss: 0.701897, acc.: 42.77%] [G loss: 0.690127]
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371 [D loss: 0.701801, acc.: 41.41%] [G loss: 0.690956]
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372 [D loss: 0.703363, acc.: 37.89%] [G loss: 0.695083]
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373 [D loss: 0.700433, acc.: 41.21%] [G loss: 0.702918]
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374 [D loss: 0.695993, acc.: 43.95%] [G loss: 0.703245]
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375 [D loss: 0.691951, acc.: 51.76%] [G loss: 0.710303]
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376 [D loss: 0.691473, acc.: 54.49%] [G loss: 0.714109]
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377 [D loss: 0.689337, acc.: 59.38%] [G loss: 0.717160]
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378 [D loss: 0.685794, acc.: 62.11%] [G loss: 0.721263]
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379 [D loss: 0.682945, acc.: 64.65%] [G loss: 0.720402]
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380 [D loss: 0.682805, acc.: 63.28%] [G loss: 0.720556]
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381 [D loss: 0.681848, acc.: 63.67%] [G loss: 0.724799]
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382 [D loss: 0.680606, acc.: 65.62%] [G loss: 0.717901]
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383 [D loss: 0.683587, acc.: 61.13%] [G loss: 0.710628]
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384 [D loss: 0.688506, acc.: 56.45%] [G loss: 0.704740]
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385 [D loss: 0.689358, acc.: 53.91%] [G loss: 0.697487]
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386 [D loss: 0.691176, acc.: 50.39%] [G loss: 0.691200]
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387 [D loss: 0.693951, acc.: 48.24%] [G loss: 0.684427]
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388 [D loss: 0.694439, acc.: 46.48%] [G loss: 0.677038]
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389 [D loss: 0.696269, acc.: 48.44%] [G loss: 0.668210]
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390 [D loss: 0.697869, acc.: 45.31%] [G loss: 0.667390]
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391 [D loss: 0.703240, acc.: 45.70%] [G loss: 0.666178]
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392 [D loss: 0.705036, acc.: 41.99%] [G loss: 0.665168]
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393 [D loss: 0.705961, acc.: 40.82%] [G loss: 0.662083]
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394 [D loss: 0.707012, acc.: 40.23%] [G loss: 0.662721]
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395 [D loss: 0.710070, acc.: 35.74%] [G loss: 0.663850]
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396 [D loss: 0.705628, acc.: 40.23%] [G loss: 0.666260]
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397 [D loss: 0.709074, acc.: 33.20%] [G loss: 0.669324]
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398 [D loss: 0.707143, acc.: 36.72%] [G loss: 0.671235]
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399 [D loss: 0.706586, acc.: 35.94%] [G loss: 0.672183]
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402 [D loss: 0.705479, acc.: 32.81%] [G loss: 0.683560]
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403 [D loss: 0.705093, acc.: 31.05%] [G loss: 0.686830]
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404 [D loss: 0.701307, acc.: 35.35%] [G loss: 0.691290]
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405 [D loss: 0.701082, acc.: 35.35%] [G loss: 0.695885]
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406 [D loss: 0.698321, acc.: 39.84%] [G loss: 0.703041]
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407 [D loss: 0.697310, acc.: 45.12%] [G loss: 0.704281]
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408 [D loss: 0.697099, acc.: 42.77%] [G loss: 0.709262]
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409 [D loss: 0.695104, acc.: 46.29%] [G loss: 0.714391]
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410 [D loss: 0.694807, acc.: 47.46%] [G loss: 0.718346]
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411 [D loss: 0.691309, acc.: 52.15%] [G loss: 0.719188]
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414 [D loss: 0.689981, acc.: 53.32%] [G loss: 0.726405]
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415 [D loss: 0.686695, acc.: 57.62%] [G loss: 0.726127]
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417 [D loss: 0.688324, acc.: 53.12%] [G loss: 0.729867]
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418 [D loss: 0.685572, acc.: 58.40%] [G loss: 0.734200]
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419 [D loss: 0.687881, acc.: 55.47%] [G loss: 0.731481]
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420 [D loss: 0.686381, acc.: 57.03%] [G loss: 0.732077]
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421 [D loss: 0.689602, acc.: 53.52%] [G loss: 0.723901]
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422 [D loss: 0.687957, acc.: 58.01%] [G loss: 0.726343]
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423 [D loss: 0.685669, acc.: 58.20%] [G loss: 0.725965]
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424 [D loss: 0.690014, acc.: 54.49%] [G loss: 0.721411]
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425 [D loss: 0.692987, acc.: 52.54%] [G loss: 0.717927]
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426 [D loss: 0.690592, acc.: 52.73%] [G loss: 0.719693]
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427 [D loss: 0.696561, acc.: 46.09%] [G loss: 0.719323]
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428 [D loss: 0.696400, acc.: 47.85%] [G loss: 0.713959]
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429 [D loss: 0.698627, acc.: 45.12%] [G loss: 0.709959]
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430 [D loss: 0.696748, acc.: 46.29%] [G loss: 0.707170]
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431 [D loss: 0.699180, acc.: 44.53%] [G loss: 0.706259]
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432 [D loss: 0.698264, acc.: 46.09%] [G loss: 0.704104]
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434 [D loss: 0.699392, acc.: 43.95%] [G loss: 0.702927]
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435 [D loss: 0.700367, acc.: 41.99%] [G loss: 0.703248]
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436 [D loss: 0.700595, acc.: 39.84%] [G loss: 0.703695]
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437 [D loss: 0.698106, acc.: 44.14%] [G loss: 0.701334]
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438 [D loss: 0.698525, acc.: 41.99%] [G loss: 0.701636]
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439 [D loss: 0.700730, acc.: 38.28%] [G loss: 0.700776]
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440 [D loss: 0.697478, acc.: 46.29%] [G loss: 0.700120]
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441 [D loss: 0.698863, acc.: 43.55%] [G loss: 0.699678]
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442 [D loss: 0.696820, acc.: 45.70%] [G loss: 0.698336]
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443 [D loss: 0.695933, acc.: 43.16%] [G loss: 0.701480]
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444 [D loss: 0.696195, acc.: 45.51%] [G loss: 0.698516]
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445 [D loss: 0.695474, acc.: 49.80%] [G loss: 0.697039]
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446 [D loss: 0.695747, acc.: 47.07%] [G loss: 0.697249]
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447 [D loss: 0.695953, acc.: 46.48%] [G loss: 0.698413]
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448 [D loss: 0.695608, acc.: 47.66%] [G loss: 0.698244]
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449 [D loss: 0.696683, acc.: 45.90%] [G loss: 0.696867]
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450 [D loss: 0.694323, acc.: 47.85%] [G loss: 0.696337]
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451 [D loss: 0.696012, acc.: 44.14%] [G loss: 0.696007]
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452 [D loss: 0.695760, acc.: 47.27%] [G loss: 0.697433]
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453 [D loss: 0.694808, acc.: 47.07%] [G loss: 0.692407]
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454 [D loss: 0.693821, acc.: 48.83%] [G loss: 0.689662]
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455 [D loss: 0.697025, acc.: 43.55%] [G loss: 0.691339]
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456 [D loss: 0.695131, acc.: 46.29%] [G loss: 0.687871]
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457 [D loss: 0.696776, acc.: 43.16%] [G loss: 0.690239]
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458 [D loss: 0.695172, acc.: 46.48%] [G loss: 0.683657]
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459 [D loss: 0.696656, acc.: 42.19%] [G loss: 0.687471]
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460 [D loss: 0.694938, acc.: 45.70%] [G loss: 0.686922]
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461 [D loss: 0.695250, acc.: 46.48%] [G loss: 0.686865]
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462 [D loss: 0.695583, acc.: 46.88%] [G loss: 0.688530]
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463 [D loss: 0.693289, acc.: 50.39%] [G loss: 0.691744]
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464 [D loss: 0.694954, acc.: 47.66%] [G loss: 0.693627]
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465 [D loss: 0.693987, acc.: 50.00%] [G loss: 0.695134]
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466 [D loss: 0.692588, acc.: 50.78%] [G loss: 0.696043]
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467 [D loss: 0.694072, acc.: 48.63%] [G loss: 0.699351]
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468 [D loss: 0.691507, acc.: 51.95%] [G loss: 0.695986]
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469 [D loss: 0.693704, acc.: 46.48%] [G loss: 0.698608]
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470 [D loss: 0.691977, acc.: 52.34%] [G loss: 0.702670]
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471 [D loss: 0.692668, acc.: 52.15%] [G loss: 0.701529]
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472 [D loss: 0.693023, acc.: 49.80%] [G loss: 0.703087]
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473 [D loss: 0.694361, acc.: 48.05%] [G loss: 0.701445]
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474 [D loss: 0.695823, acc.: 46.68%] [G loss: 0.704370]
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475 [D loss: 0.697050, acc.: 45.51%] [G loss: 0.703317]
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476 [D loss: 0.695582, acc.: 44.92%] [G loss: 0.698727]
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477 [D loss: 0.696446, acc.: 45.90%] [G loss: 0.700173]
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478 [D loss: 0.697416, acc.: 41.99%] [G loss: 0.701144]
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479 [D loss: 0.696964, acc.: 43.16%] [G loss: 0.696472]
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480 [D loss: 0.696390, acc.: 44.53%] [G loss: 0.698519]
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481 [D loss: 0.694942, acc.: 49.80%] [G loss: 0.697031]
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482 [D loss: 0.699609, acc.: 39.45%] [G loss: 0.697467]
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483 [D loss: 0.695044, acc.: 48.24%] [G loss: 0.699689]
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484 [D loss: 0.696961, acc.: 45.12%] [G loss: 0.696332]
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485 [D loss: 0.698152, acc.: 40.04%] [G loss: 0.698763]
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486 [D loss: 0.698686, acc.: 44.34%] [G loss: 0.700214]
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487 [D loss: 0.699071, acc.: 41.02%] [G loss: 0.699634]
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488 [D loss: 0.697854, acc.: 43.55%] [G loss: 0.700979]
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489 [D loss: 0.696766, acc.: 43.75%] [G loss: 0.701105]
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490 [D loss: 0.697043, acc.: 45.31%] [G loss: 0.701879]
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491 [D loss: 0.697780, acc.: 44.14%] [G loss: 0.704626]
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492 [D loss: 0.695926, acc.: 44.14%] [G loss: 0.702789]
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493 [D loss: 0.695785, acc.: 47.46%] [G loss: 0.703296]
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494 [D loss: 0.694061, acc.: 50.20%] [G loss: 0.706306]
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495 [D loss: 0.694921, acc.: 48.05%] [G loss: 0.707607]
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496 [D loss: 0.694484, acc.: 50.39%] [G loss: 0.708457]
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497 [D loss: 0.690940, acc.: 55.08%] [G loss: 0.709198]
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498 [D loss: 0.692093, acc.: 52.54%] [G loss: 0.711464]
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499 [D loss: 0.691711, acc.: 54.49%] [G loss: 0.709183]
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500 [D loss: 0.690530, acc.: 55.27%] [G loss: 0.709735]
1/1 [==============================] - 0s 18ms/step
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501 [D loss: 0.691371, acc.: 55.08%] [G loss: 0.707658]
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502 [D loss: 0.690887, acc.: 55.27%] [G loss: 0.708714]
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503 [D loss: 0.690413, acc.: 58.40%] [G loss: 0.708590]
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504 [D loss: 0.691877, acc.: 52.93%] [G loss: 0.706813]
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505 [D loss: 0.689638, acc.: 57.81%] [G loss: 0.707611]
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506 [D loss: 0.690515, acc.: 56.05%] [G loss: 0.707712]
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507 [D loss: 0.691729, acc.: 56.05%] [G loss: 0.700260]
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508 [D loss: 0.692694, acc.: 51.56%] [G loss: 0.703162]
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509 [D loss: 0.692025, acc.: 53.12%] [G loss: 0.698660]
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510 [D loss: 0.693444, acc.: 52.34%] [G loss: 0.697747]
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511 [D loss: 0.695393, acc.: 47.27%] [G loss: 0.694443]
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512 [D loss: 0.694812, acc.: 50.98%] [G loss: 0.689765]
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513 [D loss: 0.696192, acc.: 45.31%] [G loss: 0.690830]
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514 [D loss: 0.694214, acc.: 48.83%] [G loss: 0.688373]
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515 [D loss: 0.694200, acc.: 48.83%] [G loss: 0.684101]
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516 [D loss: 0.697101, acc.: 46.68%] [G loss: 0.681757]
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517 [D loss: 0.700723, acc.: 43.95%] [G loss: 0.682154]
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518 [D loss: 0.702302, acc.: 40.43%] [G loss: 0.685312]
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519 [D loss: 0.700896, acc.: 42.77%] [G loss: 0.684217]
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520 [D loss: 0.700485, acc.: 42.58%] [G loss: 0.684811]
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521 [D loss: 0.700552, acc.: 39.84%] [G loss: 0.683217]
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522 [D loss: 0.701210, acc.: 38.87%] [G loss: 0.685386]
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523 [D loss: 0.698999, acc.: 40.43%] [G loss: 0.689711]
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524 [D loss: 0.699572, acc.: 43.16%] [G loss: 0.688298]
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525 [D loss: 0.701031, acc.: 37.30%] [G loss: 0.687816]
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526 [D loss: 0.698812, acc.: 40.43%] [G loss: 0.690902]
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527 [D loss: 0.697631, acc.: 42.58%] [G loss: 0.692518]
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528 [D loss: 0.700307, acc.: 38.48%] [G loss: 0.696976]
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529 [D loss: 0.697165, acc.: 41.99%] [G loss: 0.693405]
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530 [D loss: 0.696181, acc.: 45.12%] [G loss: 0.698420]
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531 [D loss: 0.695486, acc.: 45.51%] [G loss: 0.700508]
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532 [D loss: 0.695574, acc.: 46.88%] [G loss: 0.703164]
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533 [D loss: 0.692597, acc.: 51.76%] [G loss: 0.705516]
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534 [D loss: 0.692732, acc.: 50.20%] [G loss: 0.707415]
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535 [D loss: 0.691274, acc.: 52.93%] [G loss: 0.707004]
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536 [D loss: 0.690793, acc.: 54.10%] [G loss: 0.711506]
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537 [D loss: 0.688654, acc.: 58.20%] [G loss: 0.711837]
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538 [D loss: 0.689700, acc.: 55.66%] [G loss: 0.713789]
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539 [D loss: 0.686815, acc.: 59.57%] [G loss: 0.714599]
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540 [D loss: 0.688720, acc.: 58.59%] [G loss: 0.717751]
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541 [D loss: 0.688379, acc.: 57.23%] [G loss: 0.714304]
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542 [D loss: 0.688442, acc.: 54.30%] [G loss: 0.717485]
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543 [D loss: 0.686853, acc.: 59.96%] [G loss: 0.714867]
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544 [D loss: 0.687595, acc.: 57.23%] [G loss: 0.719387]
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545 [D loss: 0.691445, acc.: 53.12%] [G loss: 0.715734]
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546 [D loss: 0.690444, acc.: 52.54%] [G loss: 0.717151]
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547 [D loss: 0.693406, acc.: 49.80%] [G loss: 0.712927]
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548 [D loss: 0.691633, acc.: 50.78%] [G loss: 0.716675]
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549 [D loss: 0.691287, acc.: 52.34%] [G loss: 0.715792]
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550 [D loss: 0.691813, acc.: 52.54%] [G loss: 0.714347]
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551 [D loss: 0.692609, acc.: 50.98%] [G loss: 0.709450]
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552 [D loss: 0.693014, acc.: 50.39%] [G loss: 0.710330]
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553 [D loss: 0.696722, acc.: 46.09%] [G loss: 0.709036]
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554 [D loss: 0.695180, acc.: 50.78%] [G loss: 0.705314]
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555 [D loss: 0.696978, acc.: 44.53%] [G loss: 0.706455]
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556 [D loss: 0.699733, acc.: 38.87%] [G loss: 0.703359]
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557 [D loss: 0.697508, acc.: 43.95%] [G loss: 0.700910]
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558 [D loss: 0.695925, acc.: 47.07%] [G loss: 0.699106]
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559 [D loss: 0.699276, acc.: 40.23%] [G loss: 0.700344]
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560 [D loss: 0.699704, acc.: 40.62%] [G loss: 0.697318]
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561 [D loss: 0.698403, acc.: 40.23%] [G loss: 0.698490]
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562 [D loss: 0.701166, acc.: 35.94%] [G loss: 0.696724]
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563 [D loss: 0.701014, acc.: 36.72%] [G loss: 0.696323]
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564 [D loss: 0.699869, acc.: 40.43%] [G loss: 0.696607]
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565 [D loss: 0.701901, acc.: 37.30%] [G loss: 0.697941]
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566 [D loss: 0.699675, acc.: 38.28%] [G loss: 0.695791]
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567 [D loss: 0.699407, acc.: 39.65%] [G loss: 0.700969]
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568 [D loss: 0.699099, acc.: 40.82%] [G loss: 0.698857]
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569 [D loss: 0.696416, acc.: 43.16%] [G loss: 0.700318]
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570 [D loss: 0.699497, acc.: 37.30%] [G loss: 0.699047]
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571 [D loss: 0.697307, acc.: 40.43%] [G loss: 0.702352]
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572 [D loss: 0.696975, acc.: 43.55%] [G loss: 0.699012]
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573 [D loss: 0.697675, acc.: 42.38%] [G loss: 0.701004]
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574 [D loss: 0.695095, acc.: 45.31%] [G loss: 0.701999]
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575 [D loss: 0.697952, acc.: 41.21%] [G loss: 0.703771]
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576 [D loss: 0.696094, acc.: 42.58%] [G loss: 0.700906]
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577 [D loss: 0.696490, acc.: 44.14%] [G loss: 0.701614]
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578 [D loss: 0.695343, acc.: 45.51%] [G loss: 0.702302]
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579 [D loss: 0.696161, acc.: 45.12%] [G loss: 0.703101]
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580 [D loss: 0.695224, acc.: 44.14%] [G loss: 0.705382]
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581 [D loss: 0.694773, acc.: 46.09%] [G loss: 0.704952]
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582 [D loss: 0.694534, acc.: 47.27%] [G loss: 0.708832]
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583 [D loss: 0.693362, acc.: 48.83%] [G loss: 0.710644]
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584 [D loss: 0.691925, acc.: 53.12%] [G loss: 0.708225]
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585 [D loss: 0.692262, acc.: 53.12%] [G loss: 0.709099]
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586 [D loss: 0.693653, acc.: 50.20%] [G loss: 0.709407]
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587 [D loss: 0.691341, acc.: 53.91%] [G loss: 0.708304]
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588 [D loss: 0.690710, acc.: 54.69%] [G loss: 0.709732]
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589 [D loss: 0.690740, acc.: 54.88%] [G loss: 0.710412]
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590 [D loss: 0.689983, acc.: 55.66%] [G loss: 0.709804]
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591 [D loss: 0.689565, acc.: 55.66%] [G loss: 0.709903]
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592 [D loss: 0.689938, acc.: 54.49%] [G loss: 0.710762]
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593 [D loss: 0.691243, acc.: 54.30%] [G loss: 0.711584]
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594 [D loss: 0.689421, acc.: 55.08%] [G loss: 0.711028]
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595 [D loss: 0.691050, acc.: 56.05%] [G loss: 0.708253]
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596 [D loss: 0.689713, acc.: 55.86%] [G loss: 0.706053]
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597 [D loss: 0.692313, acc.: 50.98%] [G loss: 0.705033]
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598 [D loss: 0.691366, acc.: 53.91%] [G loss: 0.704693]
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599 [D loss: 0.694390, acc.: 51.17%] [G loss: 0.700915]
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600 [D loss: 0.692788, acc.: 53.91%] [G loss: 0.702301]
1/1 [==============================] - 0s 14ms/step
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601 [D loss: 0.695662, acc.: 47.27%] [G loss: 0.701122]
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602 [D loss: 0.696193, acc.: 45.70%] [G loss: 0.698328]
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603 [D loss: 0.695209, acc.: 47.66%] [G loss: 0.695073]
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604 [D loss: 0.696966, acc.: 43.55%] [G loss: 0.692608]
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605 [D loss: 0.697218, acc.: 43.36%] [G loss: 0.690865]
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606 [D loss: 0.699605, acc.: 41.02%] [G loss: 0.690558]
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607 [D loss: 0.700024, acc.: 38.48%] [G loss: 0.690276]
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608 [D loss: 0.698697, acc.: 44.53%] [G loss: 0.687863]
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609 [D loss: 0.698578, acc.: 41.21%] [G loss: 0.685628]
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610 [D loss: 0.700116, acc.: 36.52%] [G loss: 0.685084]
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611 [D loss: 0.698119, acc.: 42.58%] [G loss: 0.688384]
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612 [D loss: 0.698372, acc.: 40.43%] [G loss: 0.689586]
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613 [D loss: 0.697400, acc.: 41.21%] [G loss: 0.691749]
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614 [D loss: 0.695679, acc.: 47.07%] [G loss: 0.694034]
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615 [D loss: 0.697205, acc.: 43.16%] [G loss: 0.693456]
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616 [D loss: 0.697856, acc.: 42.77%] [G loss: 0.695489]
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617 [D loss: 0.694617, acc.: 48.24%] [G loss: 0.700279]
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618 [D loss: 0.695789, acc.: 45.31%] [G loss: 0.700719]
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619 [D loss: 0.693776, acc.: 50.59%] [G loss: 0.703609]
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620 [D loss: 0.691842, acc.: 53.91%] [G loss: 0.704295]
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621 [D loss: 0.692805, acc.: 49.22%] [G loss: 0.704026]
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622 [D loss: 0.691798, acc.: 52.93%] [G loss: 0.707295]
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623 [D loss: 0.692169, acc.: 50.59%] [G loss: 0.706455]
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624 [D loss: 0.690088, acc.: 55.47%] [G loss: 0.711433]
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625 [D loss: 0.691655, acc.: 52.93%] [G loss: 0.711732]
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626 [D loss: 0.689726, acc.: 56.84%] [G loss: 0.711923]
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627 [D loss: 0.689964, acc.: 53.71%] [G loss: 0.711389]
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628 [D loss: 0.687780, acc.: 57.81%] [G loss: 0.713679]
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629 [D loss: 0.690091, acc.: 53.52%] [G loss: 0.711131]
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630 [D loss: 0.688984, acc.: 54.10%] [G loss: 0.713243]
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631 [D loss: 0.690856, acc.: 53.91%] [G loss: 0.710866]
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632 [D loss: 0.693364, acc.: 49.61%] [G loss: 0.710424]
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633 [D loss: 0.692419, acc.: 51.37%] [G loss: 0.707691]
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634 [D loss: 0.692818, acc.: 49.61%] [G loss: 0.704065]
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635 [D loss: 0.693000, acc.: 50.78%] [G loss: 0.700667]
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636 [D loss: 0.693361, acc.: 50.98%] [G loss: 0.695258]
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637 [D loss: 0.695083, acc.: 49.22%] [G loss: 0.699198]
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638 [D loss: 0.693950, acc.: 49.61%] [G loss: 0.694919]
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639 [D loss: 0.693513, acc.: 47.27%] [G loss: 0.692212]
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640 [D loss: 0.693880, acc.: 48.05%] [G loss: 0.693746]
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641 [D loss: 0.692507, acc.: 50.20%] [G loss: 0.692308]
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642 [D loss: 0.693016, acc.: 51.76%] [G loss: 0.690324]
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643 [D loss: 0.695299, acc.: 47.46%] [G loss: 0.691797]
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644 [D loss: 0.695977, acc.: 43.95%] [G loss: 0.694121]
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645 [D loss: 0.695445, acc.: 46.29%] [G loss: 0.692598]
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646 [D loss: 0.698682, acc.: 40.23%] [G loss: 0.695164]
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647 [D loss: 0.695194, acc.: 47.27%] [G loss: 0.695267]
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648 [D loss: 0.696280, acc.: 44.73%] [G loss: 0.691021]
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649 [D loss: 0.697734, acc.: 43.55%] [G loss: 0.690818]
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650 [D loss: 0.697331, acc.: 43.95%] [G loss: 0.683304]
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651 [D loss: 0.698808, acc.: 43.55%] [G loss: 0.683165]
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652 [D loss: 0.699696, acc.: 39.45%] [G loss: 0.687162]
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653 [D loss: 0.697160, acc.: 45.51%] [G loss: 0.686309]
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654 [D loss: 0.696453, acc.: 46.68%] [G loss: 0.683953]
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655 [D loss: 0.697602, acc.: 48.05%] [G loss: 0.684174]
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656 [D loss: 0.697009, acc.: 46.88%] [G loss: 0.684272]
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657 [D loss: 0.698070, acc.: 46.29%] [G loss: 0.685904]
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658 [D loss: 0.697973, acc.: 43.36%] [G loss: 0.685129]
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659 [D loss: 0.696640, acc.: 46.09%] [G loss: 0.688611]
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660 [D loss: 0.697609, acc.: 42.77%] [G loss: 0.686609]
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661 [D loss: 0.696362, acc.: 43.95%] [G loss: 0.691630]
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662 [D loss: 0.696773, acc.: 43.95%] [G loss: 0.692759]
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663 [D loss: 0.696027, acc.: 45.90%] [G loss: 0.694626]
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664 [D loss: 0.696434, acc.: 45.70%] [G loss: 0.695599]
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665 [D loss: 0.694821, acc.: 47.07%] [G loss: 0.698145]
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666 [D loss: 0.696323, acc.: 44.34%] [G loss: 0.699871]
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667 [D loss: 0.695171, acc.: 48.24%] [G loss: 0.701575]
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668 [D loss: 0.695466, acc.: 44.34%] [G loss: 0.704853]
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669 [D loss: 0.694318, acc.: 49.22%] [G loss: 0.705145]
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670 [D loss: 0.693433, acc.: 49.02%] [G loss: 0.705617]
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671 [D loss: 0.693461, acc.: 50.59%] [G loss: 0.707514]
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672 [D loss: 0.693289, acc.: 49.80%] [G loss: 0.705590]
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673 [D loss: 0.693318, acc.: 47.66%] [G loss: 0.707906]
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674 [D loss: 0.692554, acc.: 52.54%] [G loss: 0.708705]
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675 [D loss: 0.692398, acc.: 51.95%] [G loss: 0.711481]
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676 [D loss: 0.690292, acc.: 56.05%] [G loss: 0.711410]
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677 [D loss: 0.690200, acc.: 56.64%] [G loss: 0.714005]
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678 [D loss: 0.689379, acc.: 55.27%] [G loss: 0.712388]
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679 [D loss: 0.689772, acc.: 57.03%] [G loss: 0.714759]
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680 [D loss: 0.690158, acc.: 54.69%] [G loss: 0.715470]
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681 [D loss: 0.689786, acc.: 54.10%] [G loss: 0.715612]
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682 [D loss: 0.690981, acc.: 54.69%] [G loss: 0.716397]
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683 [D loss: 0.691483, acc.: 50.59%] [G loss: 0.716985]
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684 [D loss: 0.692046, acc.: 53.32%] [G loss: 0.717656]
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685 [D loss: 0.690148, acc.: 56.05%] [G loss: 0.716116]
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686 [D loss: 0.689775, acc.: 56.05%] [G loss: 0.717747]
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687 [D loss: 0.690726, acc.: 52.93%] [G loss: 0.715161]
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688 [D loss: 0.694219, acc.: 49.02%] [G loss: 0.716340]
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689 [D loss: 0.693950, acc.: 51.56%] [G loss: 0.714633]
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690 [D loss: 0.692997, acc.: 49.80%] [G loss: 0.707803]
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691 [D loss: 0.698070, acc.: 42.58%] [G loss: 0.708789]
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692 [D loss: 0.698032, acc.: 41.21%] [G loss: 0.706211]
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693 [D loss: 0.699019, acc.: 41.60%] [G loss: 0.705199]
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694 [D loss: 0.698817, acc.: 41.60%] [G loss: 0.701404]
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695 [D loss: 0.699282, acc.: 40.82%] [G loss: 0.702674]
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696 [D loss: 0.702207, acc.: 34.18%] [G loss: 0.701178]
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697 [D loss: 0.699385, acc.: 38.67%] [G loss: 0.700141]
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698 [D loss: 0.701307, acc.: 37.30%] [G loss: 0.700734]
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699 [D loss: 0.700445, acc.: 35.74%] [G loss: 0.701640]
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700 [D loss: 0.699700, acc.: 38.48%] [G loss: 0.699766]
1/1 [==============================] - 0s 16ms/step
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701 [D loss: 0.699084, acc.: 38.28%] [G loss: 0.704460]
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702 [D loss: 0.697739, acc.: 41.02%] [G loss: 0.703517]
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703 [D loss: 0.696991, acc.: 44.34%] [G loss: 0.704805]
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704 [D loss: 0.693239, acc.: 49.61%] [G loss: 0.707919]
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705 [D loss: 0.693303, acc.: 48.24%] [G loss: 0.705918]
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706 [D loss: 0.692294, acc.: 50.00%] [G loss: 0.710554]
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707 [D loss: 0.691038, acc.: 52.54%] [G loss: 0.709245]
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708 [D loss: 0.689507, acc.: 56.25%] [G loss: 0.712689]
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709 [D loss: 0.691621, acc.: 50.98%] [G loss: 0.713975]
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710 [D loss: 0.690229, acc.: 52.34%] [G loss: 0.713078]
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711 [D loss: 0.689003, acc.: 54.69%] [G loss: 0.712321]
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712 [D loss: 0.690258, acc.: 53.71%] [G loss: 0.712178]
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713 [D loss: 0.690975, acc.: 52.54%] [G loss: 0.706654]
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714 [D loss: 0.692071, acc.: 52.73%] [G loss: 0.708137]
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715 [D loss: 0.692343, acc.: 51.17%] [G loss: 0.703804]
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716 [D loss: 0.691472, acc.: 55.66%] [G loss: 0.700443]
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717 [D loss: 0.693377, acc.: 50.00%] [G loss: 0.699958]
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718 [D loss: 0.692315, acc.: 53.91%] [G loss: 0.697678]
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719 [D loss: 0.694937, acc.: 48.05%] [G loss: 0.699116]
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720 [D loss: 0.694662, acc.: 49.80%] [G loss: 0.695390]
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721 [D loss: 0.695113, acc.: 49.22%] [G loss: 0.694018]
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722 [D loss: 0.694259, acc.: 46.88%] [G loss: 0.693801]
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723 [D loss: 0.694682, acc.: 47.66%] [G loss: 0.694386]
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724 [D loss: 0.695879, acc.: 46.88%] [G loss: 0.693301]
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725 [D loss: 0.695275, acc.: 45.70%] [G loss: 0.692296]
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726 [D loss: 0.695811, acc.: 44.92%] [G loss: 0.690274]
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727 [D loss: 0.696692, acc.: 43.55%] [G loss: 0.691767]
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728 [D loss: 0.694833, acc.: 46.68%] [G loss: 0.691672]
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729 [D loss: 0.694941, acc.: 49.22%] [G loss: 0.696152]
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730 [D loss: 0.694514, acc.: 49.61%] [G loss: 0.694104]
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731 [D loss: 0.694492, acc.: 45.90%] [G loss: 0.692306]
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732 [D loss: 0.693308, acc.: 50.98%] [G loss: 0.694080]
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733 [D loss: 0.694126, acc.: 49.02%] [G loss: 0.696257]
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734 [D loss: 0.694493, acc.: 49.41%] [G loss: 0.693829]
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735 [D loss: 0.694538, acc.: 47.85%] [G loss: 0.696703]
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736 [D loss: 0.695167, acc.: 44.92%] [G loss: 0.694966]
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737 [D loss: 0.693932, acc.: 49.80%] [G loss: 0.695437]
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738 [D loss: 0.695389, acc.: 44.92%] [G loss: 0.695877]
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739 [D loss: 0.695248, acc.: 48.05%] [G loss: 0.696665]
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740 [D loss: 0.695419, acc.: 45.12%] [G loss: 0.696562]
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741 [D loss: 0.693486, acc.: 48.05%] [G loss: 0.695091]
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742 [D loss: 0.693675, acc.: 51.76%] [G loss: 0.695459]
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743 [D loss: 0.694097, acc.: 48.63%] [G loss: 0.698719]
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744 [D loss: 0.695714, acc.: 44.53%] [G loss: 0.699942]
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745 [D loss: 0.694152, acc.: 47.85%] [G loss: 0.697619]
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746 [D loss: 0.695159, acc.: 46.88%] [G loss: 0.698053]
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747 [D loss: 0.694586, acc.: 46.09%] [G loss: 0.701121]
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748 [D loss: 0.695597, acc.: 45.70%] [G loss: 0.699537]
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749 [D loss: 0.695975, acc.: 43.75%] [G loss: 0.699333]
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750 [D loss: 0.693990, acc.: 48.44%] [G loss: 0.701963]
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751 [D loss: 0.695205, acc.: 46.48%] [G loss: 0.699750]
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752 [D loss: 0.694585, acc.: 45.31%] [G loss: 0.701361]
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753 [D loss: 0.695787, acc.: 43.16%] [G loss: 0.702770]
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754 [D loss: 0.695258, acc.: 45.70%] [G loss: 0.700659]
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755 [D loss: 0.696226, acc.: 43.16%] [G loss: 0.704201]
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756 [D loss: 0.696087, acc.: 42.77%] [G loss: 0.703014]
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757 [D loss: 0.696147, acc.: 44.73%] [G loss: 0.704246]
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758 [D loss: 0.695432, acc.: 43.75%] [G loss: 0.703680]
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759 [D loss: 0.694573, acc.: 46.29%] [G loss: 0.706895]
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760 [D loss: 0.695708, acc.: 43.75%] [G loss: 0.708028]
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761 [D loss: 0.694241, acc.: 48.05%] [G loss: 0.708319]
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762 [D loss: 0.693428, acc.: 47.27%] [G loss: 0.709537]
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763 [D loss: 0.692934, acc.: 52.15%] [G loss: 0.709325]
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764 [D loss: 0.691726, acc.: 54.49%] [G loss: 0.710385]
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765 [D loss: 0.692135, acc.: 53.12%] [G loss: 0.711869]
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766 [D loss: 0.691314, acc.: 51.76%] [G loss: 0.712499]
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767 [D loss: 0.691656, acc.: 56.45%] [G loss: 0.712038]
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768 [D loss: 0.690953, acc.: 57.03%] [G loss: 0.711523]
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769 [D loss: 0.690329, acc.: 56.05%] [G loss: 0.712916]
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770 [D loss: 0.690732, acc.: 57.23%] [G loss: 0.711429]
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771 [D loss: 0.691517, acc.: 51.76%] [G loss: 0.710192]
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772 [D loss: 0.691031, acc.: 54.69%] [G loss: 0.709208]
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773 [D loss: 0.692763, acc.: 48.24%] [G loss: 0.710291]
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774 [D loss: 0.692117, acc.: 50.20%] [G loss: 0.708020]
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775 [D loss: 0.692691, acc.: 50.98%] [G loss: 0.704524]
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776 [D loss: 0.693080, acc.: 49.41%] [G loss: 0.706002]
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777 [D loss: 0.694670, acc.: 44.73%] [G loss: 0.703443]
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778 [D loss: 0.694289, acc.: 49.02%] [G loss: 0.702931]
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779 [D loss: 0.693412, acc.: 50.59%] [G loss: 0.701999]
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780 [D loss: 0.693488, acc.: 47.85%] [G loss: 0.698679]
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781 [D loss: 0.693372, acc.: 47.66%] [G loss: 0.698688]
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782 [D loss: 0.695952, acc.: 44.73%] [G loss: 0.696118]
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783 [D loss: 0.694172, acc.: 47.66%] [G loss: 0.696864]
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784 [D loss: 0.696080, acc.: 45.51%] [G loss: 0.694944]
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785 [D loss: 0.695366, acc.: 46.29%] [G loss: 0.693105]
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786 [D loss: 0.695517, acc.: 45.51%] [G loss: 0.693754]
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787 [D loss: 0.693632, acc.: 50.20%] [G loss: 0.695059]
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788 [D loss: 0.695363, acc.: 44.34%] [G loss: 0.694007]
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789 [D loss: 0.695009, acc.: 46.09%] [G loss: 0.693585]
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790 [D loss: 0.695382, acc.: 45.31%] [G loss: 0.695189]
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791 [D loss: 0.695527, acc.: 44.92%] [G loss: 0.693879]
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792 [D loss: 0.693269, acc.: 51.95%] [G loss: 0.695190]
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793 [D loss: 0.694809, acc.: 45.31%] [G loss: 0.696498]
8/8 [==============================] - 0s 2ms/step
794 [D loss: 0.694186, acc.: 49.22%] [G loss: 0.698314]
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795 [D loss: 0.694912, acc.: 44.92%] [G loss: 0.698372]
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796 [D loss: 0.695225, acc.: 44.73%] [G loss: 0.698652]
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797 [D loss: 0.693809, acc.: 49.80%] [G loss: 0.699917]
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798 [D loss: 0.692948, acc.: 50.98%] [G loss: 0.699621]
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799 [D loss: 0.692621, acc.: 50.20%] [G loss: 0.701628]
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800 [D loss: 0.692551, acc.: 53.12%] [G loss: 0.701590]
1/1 [==============================] - 0s 14ms/step
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801 [D loss: 0.693104, acc.: 51.95%] [G loss: 0.701940]
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802 [D loss: 0.692271, acc.: 56.25%] [G loss: 0.703327]
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803 [D loss: 0.690719, acc.: 56.05%] [G loss: 0.703847]
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804 [D loss: 0.692461, acc.: 52.93%] [G loss: 0.704274]
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805 [D loss: 0.692908, acc.: 52.73%] [G loss: 0.707184]
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806 [D loss: 0.693401, acc.: 51.17%] [G loss: 0.706209]
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807 [D loss: 0.693380, acc.: 52.93%] [G loss: 0.704344]
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808 [D loss: 0.691678, acc.: 52.54%] [G loss: 0.705186]
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809 [D loss: 0.691947, acc.: 55.47%] [G loss: 0.706233]
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810 [D loss: 0.692826, acc.: 53.32%] [G loss: 0.705535]
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811 [D loss: 0.690686, acc.: 57.81%] [G loss: 0.706516]
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812 [D loss: 0.693070, acc.: 49.61%] [G loss: 0.707173]
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813 [D loss: 0.693214, acc.: 48.63%] [G loss: 0.707747]
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814 [D loss: 0.690800, acc.: 55.66%] [G loss: 0.705975]
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815 [D loss: 0.690222, acc.: 56.05%] [G loss: 0.709429]
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816 [D loss: 0.691048, acc.: 52.93%] [G loss: 0.707177]
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817 [D loss: 0.692826, acc.: 54.30%] [G loss: 0.709673]
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818 [D loss: 0.691008, acc.: 53.12%] [G loss: 0.711272]
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819 [D loss: 0.691828, acc.: 54.30%] [G loss: 0.709701]
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820 [D loss: 0.692476, acc.: 50.39%] [G loss: 0.708736]
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821 [D loss: 0.692043, acc.: 54.49%] [G loss: 0.707386]
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822 [D loss: 0.693481, acc.: 50.78%] [G loss: 0.705954]
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823 [D loss: 0.695028, acc.: 46.88%] [G loss: 0.703620]
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824 [D loss: 0.695753, acc.: 43.75%] [G loss: 0.702280]
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825 [D loss: 0.695695, acc.: 46.48%] [G loss: 0.702555]
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826 [D loss: 0.695552, acc.: 46.68%] [G loss: 0.702941]
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827 [D loss: 0.695426, acc.: 47.66%] [G loss: 0.701835]
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828 [D loss: 0.696151, acc.: 41.02%] [G loss: 0.701664]
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829 [D loss: 0.695069, acc.: 43.16%] [G loss: 0.702666]
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830 [D loss: 0.694653, acc.: 46.88%] [G loss: 0.703004]
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831 [D loss: 0.691690, acc.: 53.32%] [G loss: 0.705308]
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832 [D loss: 0.691095, acc.: 54.69%] [G loss: 0.706333]
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833 [D loss: 0.690974, acc.: 55.08%] [G loss: 0.706949]
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834 [D loss: 0.690667, acc.: 54.49%] [G loss: 0.707015]
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835 [D loss: 0.688881, acc.: 60.94%] [G loss: 0.709963]
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836 [D loss: 0.688908, acc.: 58.98%] [G loss: 0.713091]
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837 [D loss: 0.687567, acc.: 59.77%] [G loss: 0.713987]
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838 [D loss: 0.687986, acc.: 58.01%] [G loss: 0.713131]
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839 [D loss: 0.687976, acc.: 58.40%] [G loss: 0.714423]
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840 [D loss: 0.687050, acc.: 61.13%] [G loss: 0.713133]
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841 [D loss: 0.687413, acc.: 60.74%] [G loss: 0.713437]
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842 [D loss: 0.688468, acc.: 61.72%] [G loss: 0.709938]
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843 [D loss: 0.690898, acc.: 54.49%] [G loss: 0.708122]
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844 [D loss: 0.691109, acc.: 57.23%] [G loss: 0.704379]
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845 [D loss: 0.692892, acc.: 50.98%] [G loss: 0.701596]
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846 [D loss: 0.692903, acc.: 51.17%] [G loss: 0.702378]
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847 [D loss: 0.694116, acc.: 49.61%] [G loss: 0.700513]
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848 [D loss: 0.694913, acc.: 46.29%] [G loss: 0.698002]
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849 [D loss: 0.695535, acc.: 47.46%] [G loss: 0.695068]
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850 [D loss: 0.695593, acc.: 46.68%] [G loss: 0.693118]
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851 [D loss: 0.696624, acc.: 43.75%] [G loss: 0.694999]
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852 [D loss: 0.696700, acc.: 44.34%] [G loss: 0.693516]
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853 [D loss: 0.696288, acc.: 46.48%] [G loss: 0.689967]
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854 [D loss: 0.696728, acc.: 42.58%] [G loss: 0.694087]
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855 [D loss: 0.697297, acc.: 41.02%] [G loss: 0.693203]
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856 [D loss: 0.696272, acc.: 44.34%] [G loss: 0.692513]
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857 [D loss: 0.697336, acc.: 40.23%] [G loss: 0.693226]
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858 [D loss: 0.697464, acc.: 42.58%] [G loss: 0.692432]
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859 [D loss: 0.696846, acc.: 41.99%] [G loss: 0.694406]
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860 [D loss: 0.697681, acc.: 38.87%] [G loss: 0.694969]
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861 [D loss: 0.696379, acc.: 43.36%] [G loss: 0.695614]
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862 [D loss: 0.695200, acc.: 46.09%] [G loss: 0.697039]
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863 [D loss: 0.696096, acc.: 46.68%] [G loss: 0.696418]
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864 [D loss: 0.694101, acc.: 47.07%] [G loss: 0.696887]
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865 [D loss: 0.694166, acc.: 48.24%] [G loss: 0.699522]
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866 [D loss: 0.693853, acc.: 49.80%] [G loss: 0.700785]
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867 [D loss: 0.693042, acc.: 48.24%] [G loss: 0.700607]
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868 [D loss: 0.691554, acc.: 53.52%] [G loss: 0.702218]
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869 [D loss: 0.690919, acc.: 57.62%] [G loss: 0.702412]
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870 [D loss: 0.692783, acc.: 54.88%] [G loss: 0.704720]
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871 [D loss: 0.689886, acc.: 58.01%] [G loss: 0.702776]
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872 [D loss: 0.690877, acc.: 55.08%] [G loss: 0.702572]
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873 [D loss: 0.691416, acc.: 54.49%] [G loss: 0.705766]
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874 [D loss: 0.690774, acc.: 54.88%] [G loss: 0.701238]
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875 [D loss: 0.691070, acc.: 52.34%] [G loss: 0.702834]
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876 [D loss: 0.691130, acc.: 53.91%] [G loss: 0.704085]
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877 [D loss: 0.689680, acc.: 57.42%] [G loss: 0.701762]
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878 [D loss: 0.692132, acc.: 51.56%] [G loss: 0.702567]
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879 [D loss: 0.691726, acc.: 53.52%] [G loss: 0.699785]
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880 [D loss: 0.691240, acc.: 54.69%] [G loss: 0.699661]
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881 [D loss: 0.692089, acc.: 54.30%] [G loss: 0.700388]
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882 [D loss: 0.691258, acc.: 51.95%] [G loss: 0.699463]
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883 [D loss: 0.693254, acc.: 50.59%] [G loss: 0.699633]
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884 [D loss: 0.693827, acc.: 46.29%] [G loss: 0.700050]
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885 [D loss: 0.695031, acc.: 46.88%] [G loss: 0.697893]
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886 [D loss: 0.696738, acc.: 41.02%] [G loss: 0.694003]
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887 [D loss: 0.695474, acc.: 45.70%] [G loss: 0.693176]
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888 [D loss: 0.695490, acc.: 46.09%] [G loss: 0.691494]
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889 [D loss: 0.696340, acc.: 45.31%] [G loss: 0.691679]
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890 [D loss: 0.695300, acc.: 47.07%] [G loss: 0.690081]
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891 [D loss: 0.697440, acc.: 39.26%] [G loss: 0.690036]
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892 [D loss: 0.695326, acc.: 44.14%] [G loss: 0.688484]
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893 [D loss: 0.695970, acc.: 44.73%] [G loss: 0.689215]
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894 [D loss: 0.694990, acc.: 48.44%] [G loss: 0.689517]
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895 [D loss: 0.695716, acc.: 44.92%] [G loss: 0.691485]
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896 [D loss: 0.694397, acc.: 46.48%] [G loss: 0.690210]
8/8 [==============================] - 0s 2ms/step
897 [D loss: 0.695205, acc.: 45.12%] [G loss: 0.691377]
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898 [D loss: 0.693969, acc.: 47.85%] [G loss: 0.690634]
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899 [D loss: 0.692384, acc.: 49.61%] [G loss: 0.695930]
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900 [D loss: 0.692198, acc.: 53.52%] [G loss: 0.696556]
1/1 [==============================] - 0s 15ms/step
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901 [D loss: 0.691589, acc.: 54.69%] [G loss: 0.696666]
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902 [D loss: 0.689699, acc.: 59.18%] [G loss: 0.700186]
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903 [D loss: 0.689741, acc.: 57.81%] [G loss: 0.702165]
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904 [D loss: 0.689719, acc.: 57.81%] [G loss: 0.701399]
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905 [D loss: 0.689249, acc.: 60.35%] [G loss: 0.700675]
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906 [D loss: 0.690647, acc.: 57.03%] [G loss: 0.702647]
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907 [D loss: 0.689090, acc.: 57.23%] [G loss: 0.700575]
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908 [D loss: 0.688973, acc.: 58.79%] [G loss: 0.700540]
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909 [D loss: 0.689101, acc.: 55.08%] [G loss: 0.700634]
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910 [D loss: 0.691948, acc.: 55.66%] [G loss: 0.697641]
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911 [D loss: 0.690835, acc.: 50.20%] [G loss: 0.693948]
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912 [D loss: 0.691771, acc.: 53.91%] [G loss: 0.692237]
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913 [D loss: 0.693266, acc.: 50.20%] [G loss: 0.692277]
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914 [D loss: 0.693790, acc.: 48.63%] [G loss: 0.692242]
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915 [D loss: 0.693777, acc.: 50.00%] [G loss: 0.690724]
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916 [D loss: 0.694195, acc.: 47.46%] [G loss: 0.692597]
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917 [D loss: 0.693464, acc.: 51.17%] [G loss: 0.689095]
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918 [D loss: 0.695627, acc.: 43.95%] [G loss: 0.690804]
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919 [D loss: 0.696013, acc.: 46.68%] [G loss: 0.689708]
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920 [D loss: 0.695653, acc.: 46.68%] [G loss: 0.691867]
8/8 [==============================] - 0s 2ms/step
921 [D loss: 0.694666, acc.: 48.44%] [G loss: 0.692521]
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922 [D loss: 0.697059, acc.: 43.16%] [G loss: 0.695081]
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923 [D loss: 0.694645, acc.: 48.24%] [G loss: 0.694815]
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924 [D loss: 0.694752, acc.: 46.29%] [G loss: 0.696471]
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925 [D loss: 0.695470, acc.: 46.09%] [G loss: 0.696973]
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926 [D loss: 0.695599, acc.: 47.27%] [G loss: 0.699085]
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927 [D loss: 0.692613, acc.: 51.17%] [G loss: 0.698329]
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928 [D loss: 0.693843, acc.: 49.22%] [G loss: 0.701207]
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929 [D loss: 0.693610, acc.: 49.41%] [G loss: 0.699170]
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930 [D loss: 0.695280, acc.: 46.88%] [G loss: 0.699673]
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931 [D loss: 0.692897, acc.: 52.15%] [G loss: 0.702134]
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932 [D loss: 0.691854, acc.: 53.91%] [G loss: 0.702054]
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933 [D loss: 0.693094, acc.: 49.02%] [G loss: 0.702553]
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934 [D loss: 0.692526, acc.: 51.76%] [G loss: 0.702003]
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935 [D loss: 0.693171, acc.: 48.63%] [G loss: 0.704063]
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936 [D loss: 0.691805, acc.: 54.69%] [G loss: 0.704128]
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937 [D loss: 0.691467, acc.: 49.61%] [G loss: 0.704131]
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938 [D loss: 0.691498, acc.: 53.71%] [G loss: 0.707779]
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939 [D loss: 0.691697, acc.: 52.73%] [G loss: 0.705414]
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940 [D loss: 0.689828, acc.: 54.49%] [G loss: 0.704950]
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941 [D loss: 0.691777, acc.: 50.98%] [G loss: 0.707038]
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942 [D loss: 0.690776, acc.: 56.05%] [G loss: 0.709292]
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943 [D loss: 0.691285, acc.: 52.54%] [G loss: 0.708892]
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944 [D loss: 0.691915, acc.: 51.76%] [G loss: 0.708394]
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945 [D loss: 0.691362, acc.: 54.30%] [G loss: 0.711102]
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946 [D loss: 0.691370, acc.: 53.71%] [G loss: 0.706136]
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947 [D loss: 0.691467, acc.: 54.30%] [G loss: 0.707995]
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948 [D loss: 0.691565, acc.: 53.91%] [G loss: 0.702530]
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949 [D loss: 0.693502, acc.: 50.20%] [G loss: 0.703796]
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950 [D loss: 0.693777, acc.: 47.07%] [G loss: 0.701930]
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951 [D loss: 0.693352, acc.: 49.80%] [G loss: 0.698627]
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952 [D loss: 0.695095, acc.: 46.09%] [G loss: 0.696431]
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953 [D loss: 0.694805, acc.: 44.14%] [G loss: 0.695440]
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954 [D loss: 0.693084, acc.: 50.00%] [G loss: 0.694493]
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955 [D loss: 0.694848, acc.: 45.12%] [G loss: 0.692914]
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956 [D loss: 0.695682, acc.: 45.12%] [G loss: 0.693602]
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957 [D loss: 0.694480, acc.: 47.46%] [G loss: 0.691358]
8/8 [==============================] - 0s 2ms/step
958 [D loss: 0.695953, acc.: 45.51%] [G loss: 0.691327]
8/8 [==============================] - 0s 2ms/step
959 [D loss: 0.694682, acc.: 49.80%] [G loss: 0.690103]
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960 [D loss: 0.695627, acc.: 45.70%] [G loss: 0.690942]
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961 [D loss: 0.695142, acc.: 47.66%] [G loss: 0.690740]
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962 [D loss: 0.694068, acc.: 50.20%] [G loss: 0.693949]
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963 [D loss: 0.694933, acc.: 46.48%] [G loss: 0.693015]
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964 [D loss: 0.694769, acc.: 45.70%] [G loss: 0.693917]
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965 [D loss: 0.692281, acc.: 53.91%] [G loss: 0.695609]
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966 [D loss: 0.694049, acc.: 46.68%] [G loss: 0.694821]
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967 [D loss: 0.692688, acc.: 53.52%] [G loss: 0.693922]
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968 [D loss: 0.693520, acc.: 50.39%] [G loss: 0.696708]
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969 [D loss: 0.691891, acc.: 52.54%] [G loss: 0.695897]
8/8 [==============================] - 0s 2ms/step
970 [D loss: 0.691546, acc.: 54.10%] [G loss: 0.698717]
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971 [D loss: 0.691979, acc.: 54.49%] [G loss: 0.698069]
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972 [D loss: 0.691319, acc.: 55.08%] [G loss: 0.695810]
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973 [D loss: 0.691423, acc.: 55.27%] [G loss: 0.695579]
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974 [D loss: 0.691911, acc.: 53.52%] [G loss: 0.697878]
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975 [D loss: 0.691085, acc.: 58.01%] [G loss: 0.696976]
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976 [D loss: 0.692969, acc.: 51.56%] [G loss: 0.697928]
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977 [D loss: 0.692406, acc.: 48.63%] [G loss: 0.697254]
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978 [D loss: 0.692071, acc.: 54.88%] [G loss: 0.697596]
8/8 [==============================] - 0s 2ms/step
979 [D loss: 0.692295, acc.: 51.95%] [G loss: 0.698700]
8/8 [==============================] - 0s 2ms/step
980 [D loss: 0.692896, acc.: 51.37%] [G loss: 0.697443]
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981 [D loss: 0.692297, acc.: 54.30%] [G loss: 0.695523]
8/8 [==============================] - 0s 2ms/step
982 [D loss: 0.692617, acc.: 53.52%] [G loss: 0.697536]
8/8 [==============================] - 0s 2ms/step
983 [D loss: 0.693205, acc.: 49.02%] [G loss: 0.695361]
8/8 [==============================] - 0s 2ms/step
984 [D loss: 0.693712, acc.: 47.66%] [G loss: 0.696424]
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985 [D loss: 0.692856, acc.: 50.39%] [G loss: 0.696586]
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986 [D loss: 0.692349, acc.: 51.17%] [G loss: 0.697249]
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987 [D loss: 0.692491, acc.: 51.17%] [G loss: 0.696233]
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988 [D loss: 0.692796, acc.: 52.15%] [G loss: 0.695407]
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989 [D loss: 0.691145, acc.: 52.34%] [G loss: 0.696739]
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990 [D loss: 0.690334, acc.: 56.45%] [G loss: 0.698902]
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991 [D loss: 0.692095, acc.: 51.95%] [G loss: 0.699557]
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992 [D loss: 0.691532, acc.: 53.71%] [G loss: 0.698184]
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993 [D loss: 0.691099, acc.: 56.64%] [G loss: 0.698201]
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994 [D loss: 0.691994, acc.: 53.71%] [G loss: 0.699854]
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995 [D loss: 0.690397, acc.: 55.27%] [G loss: 0.699889]
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996 [D loss: 0.690055, acc.: 57.23%] [G loss: 0.701542]
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997 [D loss: 0.689425, acc.: 58.79%] [G loss: 0.701075]
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998 [D loss: 0.691671, acc.: 57.23%] [G loss: 0.701950]
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999 [D loss: 0.690424, acc.: 56.84%] [G loss: 0.701717]
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1000 [D loss: 0.691340, acc.: 55.66%] [G loss: 0.701753]
1/1 [==============================] - 0s 16ms/step
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1001 [D loss: 0.691189, acc.: 55.66%] [G loss: 0.699358]
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1002 [D loss: 0.693630, acc.: 48.24%] [G loss: 0.699901]
8/8 [==============================] - 0s 2ms/step
1003 [D loss: 0.690380, acc.: 54.49%] [G loss: 0.700013]
8/8 [==============================] - 0s 2ms/step
1004 [D loss: 0.691734, acc.: 52.54%] [G loss: 0.697352]
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1005 [D loss: 0.692243, acc.: 52.15%] [G loss: 0.699043]
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1006 [D loss: 0.693051, acc.: 50.78%] [G loss: 0.697102]
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1007 [D loss: 0.692230, acc.: 50.00%] [G loss: 0.697040]
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1008 [D loss: 0.691196, acc.: 51.95%] [G loss: 0.694627]
8/8 [==============================] - 0s 2ms/step
1009 [D loss: 0.692746, acc.: 53.71%] [G loss: 0.692861]
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1010 [D loss: 0.693350, acc.: 49.41%] [G loss: 0.695358]
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1011 [D loss: 0.691458, acc.: 53.52%] [G loss: 0.692136]
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1012 [D loss: 0.694920, acc.: 47.46%] [G loss: 0.690808]
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1013 [D loss: 0.695891, acc.: 45.70%] [G loss: 0.690998]
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1014 [D loss: 0.695026, acc.: 50.78%] [G loss: 0.692255]
8/8 [==============================] - 0s 2ms/step
1015 [D loss: 0.695269, acc.: 47.66%] [G loss: 0.691865]
8/8 [==============================] - 0s 3ms/step
1016 [D loss: 0.696566, acc.: 44.34%] [G loss: 0.691015]
8/8 [==============================] - 0s 2ms/step
1017 [D loss: 0.695174, acc.: 46.29%] [G loss: 0.691645]
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1018 [D loss: 0.696788, acc.: 44.53%] [G loss: 0.691334]
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1019 [D loss: 0.696560, acc.: 43.95%] [G loss: 0.695432]
8/8 [==============================] - 0s 2ms/step
1020 [D loss: 0.696351, acc.: 45.70%] [G loss: 0.693296]
8/8 [==============================] - 0s 2ms/step
1021 [D loss: 0.695099, acc.: 47.07%] [G loss: 0.691395]
8/8 [==============================] - 0s 2ms/step
1022 [D loss: 0.694735, acc.: 47.27%] [G loss: 0.695145]
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1023 [D loss: 0.693922, acc.: 49.80%] [G loss: 0.695474]
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1024 [D loss: 0.696512, acc.: 45.51%] [G loss: 0.696569]
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1025 [D loss: 0.695160, acc.: 48.63%] [G loss: 0.695321]
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1026 [D loss: 0.696744, acc.: 40.43%] [G loss: 0.695964]
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1027 [D loss: 0.693840, acc.: 48.63%] [G loss: 0.696765]
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1028 [D loss: 0.693267, acc.: 48.63%] [G loss: 0.698129]
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1029 [D loss: 0.692840, acc.: 51.17%] [G loss: 0.698782]
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1030 [D loss: 0.691883, acc.: 53.32%] [G loss: 0.698851]
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1031 [D loss: 0.691418, acc.: 53.91%] [G loss: 0.698501]
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1032 [D loss: 0.690285, acc.: 58.79%] [G loss: 0.698048]
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1033 [D loss: 0.689556, acc.: 61.91%] [G loss: 0.699819]
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1034 [D loss: 0.690366, acc.: 56.84%] [G loss: 0.699367]
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1035 [D loss: 0.690026, acc.: 58.01%] [G loss: 0.699107]
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1036 [D loss: 0.688081, acc.: 61.72%] [G loss: 0.699940]
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1037 [D loss: 0.689115, acc.: 58.01%] [G loss: 0.700669]
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1038 [D loss: 0.690522, acc.: 56.25%] [G loss: 0.698034]
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1039 [D loss: 0.689803, acc.: 57.23%] [G loss: 0.696591]
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1040 [D loss: 0.689622, acc.: 59.38%] [G loss: 0.696925]
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1041 [D loss: 0.691620, acc.: 52.34%] [G loss: 0.694489]
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1042 [D loss: 0.690004, acc.: 53.12%] [G loss: 0.694115]
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1043 [D loss: 0.691663, acc.: 52.93%] [G loss: 0.690991]
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1044 [D loss: 0.691348, acc.: 53.32%] [G loss: 0.693588]
8/8 [==============================] - 0s 2ms/step
1045 [D loss: 0.691636, acc.: 55.86%] [G loss: 0.694592]
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1046 [D loss: 0.692680, acc.: 53.12%] [G loss: 0.692105]
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1047 [D loss: 0.692956, acc.: 53.71%] [G loss: 0.694343]
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1048 [D loss: 0.691270, acc.: 53.71%] [G loss: 0.691854]
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1049 [D loss: 0.692316, acc.: 54.88%] [G loss: 0.689393]
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1050 [D loss: 0.693181, acc.: 49.02%] [G loss: 0.691049]
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1051 [D loss: 0.691590, acc.: 54.88%] [G loss: 0.692406]
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1052 [D loss: 0.693906, acc.: 50.59%] [G loss: 0.691164]
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1053 [D loss: 0.693850, acc.: 47.46%] [G loss: 0.690648]
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1054 [D loss: 0.692724, acc.: 54.30%] [G loss: 0.691056]
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1055 [D loss: 0.693254, acc.: 48.83%] [G loss: 0.690349]
8/8 [==============================] - 0s 2ms/step
1056 [D loss: 0.694805, acc.: 43.95%] [G loss: 0.689105]
8/8 [==============================] - 0s 2ms/step
1057 [D loss: 0.693766, acc.: 49.80%] [G loss: 0.690840]
8/8 [==============================] - 0s 2ms/step
1058 [D loss: 0.692842, acc.: 50.98%] [G loss: 0.688916]
8/8 [==============================] - 0s 2ms/step
1059 [D loss: 0.694346, acc.: 46.68%] [G loss: 0.688203]
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1060 [D loss: 0.696365, acc.: 44.34%] [G loss: 0.686567]
8/8 [==============================] - 0s 2ms/step
1061 [D loss: 0.695103, acc.: 47.07%] [G loss: 0.687209]
8/8 [==============================] - 0s 2ms/step
1062 [D loss: 0.694288, acc.: 49.61%] [G loss: 0.690488]
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1063 [D loss: 0.694138, acc.: 47.66%] [G loss: 0.690136]
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1064 [D loss: 0.692875, acc.: 50.59%] [G loss: 0.692800]
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1065 [D loss: 0.692843, acc.: 52.15%] [G loss: 0.691349]
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1066 [D loss: 0.692409, acc.: 51.76%] [G loss: 0.692976]
8/8 [==============================] - 0s 2ms/step
1067 [D loss: 0.693500, acc.: 50.00%] [G loss: 0.694321]
8/8 [==============================] - 0s 2ms/step
1068 [D loss: 0.693851, acc.: 47.85%] [G loss: 0.693373]
8/8 [==============================] - 0s 2ms/step
1069 [D loss: 0.692487, acc.: 52.34%] [G loss: 0.692320]
8/8 [==============================] - 0s 2ms/step
1070 [D loss: 0.691631, acc.: 56.64%] [G loss: 0.693986]
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1071 [D loss: 0.692477, acc.: 49.80%] [G loss: 0.693901]
8/8 [==============================] - 0s 2ms/step
1072 [D loss: 0.692519, acc.: 52.54%] [G loss: 0.694256]
8/8 [==============================] - 0s 2ms/step
1073 [D loss: 0.692174, acc.: 53.12%] [G loss: 0.695948]
8/8 [==============================] - 0s 2ms/step
1074 [D loss: 0.691751, acc.: 53.52%] [G loss: 0.696646]
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1075 [D loss: 0.691339, acc.: 55.47%] [G loss: 0.697808]
8/8 [==============================] - 0s 2ms/step
1076 [D loss: 0.690660, acc.: 57.81%] [G loss: 0.695577]
8/8 [==============================] - 0s 2ms/step
1077 [D loss: 0.691106, acc.: 55.86%] [G loss: 0.698002]
8/8 [==============================] - 0s 2ms/step
1078 [D loss: 0.689944, acc.: 58.20%] [G loss: 0.698370]
8/8 [==============================] - 0s 2ms/step
1079 [D loss: 0.691571, acc.: 54.30%] [G loss: 0.696460]
8/8 [==============================] - 0s 2ms/step
1080 [D loss: 0.691721, acc.: 53.12%] [G loss: 0.695646]
8/8 [==============================] - 0s 2ms/step
1081 [D loss: 0.692056, acc.: 53.32%] [G loss: 0.698443]
8/8 [==============================] - 0s 2ms/step
1082 [D loss: 0.692476, acc.: 51.76%] [G loss: 0.698620]
8/8 [==============================] - 0s 2ms/step
1083 [D loss: 0.692358, acc.: 52.73%] [G loss: 0.700854]
8/8 [==============================] - 0s 2ms/step
1084 [D loss: 0.693801, acc.: 49.02%] [G loss: 0.700773]
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1085 [D loss: 0.693055, acc.: 48.83%] [G loss: 0.699152]
8/8 [==============================] - 0s 2ms/step
1086 [D loss: 0.695027, acc.: 47.66%] [G loss: 0.695595]
8/8 [==============================] - 0s 2ms/step
1087 [D loss: 0.695275, acc.: 46.88%] [G loss: 0.694894]
8/8 [==============================] - 0s 2ms/step
1088 [D loss: 0.695585, acc.: 46.68%] [G loss: 0.695171]
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1089 [D loss: 0.694812, acc.: 48.63%] [G loss: 0.692798]
8/8 [==============================] - 0s 2ms/step
1090 [D loss: 0.695286, acc.: 47.27%] [G loss: 0.685391]
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1091 [D loss: 0.695796, acc.: 45.51%] [G loss: 0.688394]
8/8 [==============================] - 0s 2ms/step
1092 [D loss: 0.696003, acc.: 46.29%] [G loss: 0.690303]
8/8 [==============================] - 0s 2ms/step
1093 [D loss: 0.695854, acc.: 47.46%] [G loss: 0.687290]
8/8 [==============================] - 0s 2ms/step
1094 [D loss: 0.695171, acc.: 46.09%] [G loss: 0.689319]
8/8 [==============================] - 0s 2ms/step
1095 [D loss: 0.694085, acc.: 48.83%] [G loss: 0.688904]
8/8 [==============================] - 0s 2ms/step
1096 [D loss: 0.693484, acc.: 51.95%] [G loss: 0.694288]
8/8 [==============================] - 0s 2ms/step
1097 [D loss: 0.693509, acc.: 49.41%] [G loss: 0.694763]
8/8 [==============================] - 0s 2ms/step
1098 [D loss: 0.693011, acc.: 52.73%] [G loss: 0.694285]
8/8 [==============================] - 0s 2ms/step
1099 [D loss: 0.692250, acc.: 51.17%] [G loss: 0.693763]
8/8 [==============================] - 0s 2ms/step
1100 [D loss: 0.691070, acc.: 54.88%] [G loss: 0.694315]
1/1 [==============================] - 0s 15ms/step
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1101 [D loss: 0.690931, acc.: 57.23%] [G loss: 0.694348]
8/8 [==============================] - 0s 2ms/step
1102 [D loss: 0.691887, acc.: 53.52%] [G loss: 0.694343]
8/8 [==============================] - 0s 2ms/step
1103 [D loss: 0.689899, acc.: 58.98%] [G loss: 0.693954]
8/8 [==============================] - 0s 2ms/step
1104 [D loss: 0.692361, acc.: 51.95%] [G loss: 0.693963]
8/8 [==============================] - 0s 2ms/step
1105 [D loss: 0.691647, acc.: 52.73%] [G loss: 0.693268]
8/8 [==============================] - 0s 2ms/step
1106 [D loss: 0.692057, acc.: 54.10%] [G loss: 0.694655]
8/8 [==============================] - 0s 2ms/step
1107 [D loss: 0.690623, acc.: 55.08%] [G loss: 0.694965]
8/8 [==============================] - 0s 2ms/step
1108 [D loss: 0.691909, acc.: 54.69%] [G loss: 0.694097]
8/8 [==============================] - 0s 2ms/step
1109 [D loss: 0.691314, acc.: 54.88%] [G loss: 0.693297]
8/8 [==============================] - 0s 2ms/step
1110 [D loss: 0.690559, acc.: 57.23%] [G loss: 0.694581]
8/8 [==============================] - 0s 2ms/step
1111 [D loss: 0.693316, acc.: 51.95%] [G loss: 0.694627]
8/8 [==============================] - 0s 3ms/step
1112 [D loss: 0.692099, acc.: 55.47%] [G loss: 0.695395]
8/8 [==============================] - 0s 2ms/step
1113 [D loss: 0.691739, acc.: 54.10%] [G loss: 0.692805]
8/8 [==============================] - 0s 2ms/step
1114 [D loss: 0.692672, acc.: 52.34%] [G loss: 0.689455]
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1115 [D loss: 0.693185, acc.: 50.78%] [G loss: 0.690951]
8/8 [==============================] - 0s 2ms/step
1116 [D loss: 0.692127, acc.: 52.34%] [G loss: 0.687673]
8/8 [==============================] - 0s 2ms/step
1117 [D loss: 0.693829, acc.: 47.85%] [G loss: 0.690246]
8/8 [==============================] - 0s 2ms/step
1118 [D loss: 0.693895, acc.: 49.22%] [G loss: 0.688130]
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1119 [D loss: 0.695219, acc.: 45.51%] [G loss: 0.689248]
8/8 [==============================] - 0s 2ms/step
1120 [D loss: 0.692708, acc.: 51.17%] [G loss: 0.687623]
8/8 [==============================] - 0s 2ms/step
1121 [D loss: 0.692446, acc.: 52.93%] [G loss: 0.690831]
8/8 [==============================] - 0s 2ms/step
1122 [D loss: 0.693694, acc.: 46.09%] [G loss: 0.689137]
8/8 [==============================] - 0s 2ms/step
1123 [D loss: 0.692138, acc.: 50.00%] [G loss: 0.689518]
8/8 [==============================] - 0s 2ms/step
1124 [D loss: 0.693572, acc.: 46.68%] [G loss: 0.690156]
8/8 [==============================] - 0s 2ms/step
1125 [D loss: 0.693513, acc.: 49.22%] [G loss: 0.690701]
8/8 [==============================] - 0s 2ms/step
1126 [D loss: 0.691954, acc.: 52.15%] [G loss: 0.690484]
8/8 [==============================] - 0s 2ms/step
1127 [D loss: 0.690756, acc.: 53.32%] [G loss: 0.689552]
8/8 [==============================] - 0s 2ms/step
1128 [D loss: 0.691528, acc.: 55.08%] [G loss: 0.692985]
8/8 [==============================] - 0s 2ms/step
1129 [D loss: 0.691961, acc.: 51.37%] [G loss: 0.691841]
8/8 [==============================] - 0s 2ms/step
1130 [D loss: 0.690999, acc.: 55.47%] [G loss: 0.691244]
8/8 [==============================] - 0s 2ms/step
1131 [D loss: 0.691296, acc.: 56.45%] [G loss: 0.694256]
8/8 [==============================] - 0s 2ms/step
1132 [D loss: 0.690761, acc.: 53.71%] [G loss: 0.693886]
8/8 [==============================] - 0s 2ms/step
1133 [D loss: 0.690572, acc.: 56.64%] [G loss: 0.695181]
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1134 [D loss: 0.690607, acc.: 55.08%] [G loss: 0.694722]
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1135 [D loss: 0.691800, acc.: 53.12%] [G loss: 0.696056]
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1136 [D loss: 0.691268, acc.: 53.12%] [G loss: 0.695491]
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1137 [D loss: 0.690845, acc.: 55.47%] [G loss: 0.694687]
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1138 [D loss: 0.691280, acc.: 54.88%] [G loss: 0.696001]
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1139 [D loss: 0.692398, acc.: 52.34%] [G loss: 0.694152]
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1140 [D loss: 0.690979, acc.: 57.03%] [G loss: 0.694197]
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1141 [D loss: 0.691363, acc.: 55.08%] [G loss: 0.692603]
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1142 [D loss: 0.692945, acc.: 50.78%] [G loss: 0.692007]
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1143 [D loss: 0.693178, acc.: 49.41%] [G loss: 0.694674]
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1144 [D loss: 0.693546, acc.: 53.12%] [G loss: 0.693123]
8/8 [==============================] - 0s 2ms/step
1145 [D loss: 0.692767, acc.: 53.32%] [G loss: 0.694802]
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1146 [D loss: 0.693811, acc.: 49.22%] [G loss: 0.692829]
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1147 [D loss: 0.693841, acc.: 50.98%] [G loss: 0.691315]
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1148 [D loss: 0.692857, acc.: 51.95%] [G loss: 0.693963]
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1149 [D loss: 0.693419, acc.: 49.41%] [G loss: 0.694496]
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1150 [D loss: 0.692735, acc.: 49.61%] [G loss: 0.694963]
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1151 [D loss: 0.694252, acc.: 43.36%] [G loss: 0.695801]
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1152 [D loss: 0.692081, acc.: 52.15%] [G loss: 0.693404]
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1153 [D loss: 0.691777, acc.: 52.54%] [G loss: 0.693691]
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1154 [D loss: 0.693139, acc.: 51.17%] [G loss: 0.696227]
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1155 [D loss: 0.693263, acc.: 51.76%] [G loss: 0.694866]
8/8 [==============================] - 0s 2ms/step
1156 [D loss: 0.692110, acc.: 52.15%] [G loss: 0.696437]
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1157 [D loss: 0.690869, acc.: 56.45%] [G loss: 0.696326]
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1158 [D loss: 0.692243, acc.: 53.12%] [G loss: 0.695048]
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1159 [D loss: 0.693682, acc.: 47.85%] [G loss: 0.694719]
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1160 [D loss: 0.692663, acc.: 50.00%] [G loss: 0.697640]
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1161 [D loss: 0.694206, acc.: 50.78%] [G loss: 0.696447]
8/8 [==============================] - 0s 2ms/step
1162 [D loss: 0.694007, acc.: 48.44%] [G loss: 0.695498]
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1163 [D loss: 0.693400, acc.: 49.41%] [G loss: 0.696063]
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1164 [D loss: 0.694575, acc.: 46.29%] [G loss: 0.695575]
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1165 [D loss: 0.694912, acc.: 47.46%] [G loss: 0.693205]
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1166 [D loss: 0.695096, acc.: 46.68%] [G loss: 0.692603]
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1167 [D loss: 0.694919, acc.: 46.48%] [G loss: 0.691800]
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1168 [D loss: 0.696926, acc.: 44.14%] [G loss: 0.693983]
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1169 [D loss: 0.695718, acc.: 42.58%] [G loss: 0.693020]
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1170 [D loss: 0.696367, acc.: 42.38%] [G loss: 0.691046]
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1171 [D loss: 0.695890, acc.: 45.90%] [G loss: 0.691175]
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1172 [D loss: 0.695188, acc.: 46.68%] [G loss: 0.691555]
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1173 [D loss: 0.695125, acc.: 46.29%] [G loss: 0.691210]
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1174 [D loss: 0.694299, acc.: 48.63%] [G loss: 0.690809]
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1175 [D loss: 0.694695, acc.: 47.07%] [G loss: 0.693200]
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1176 [D loss: 0.695495, acc.: 42.19%] [G loss: 0.692584]
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1177 [D loss: 0.693961, acc.: 49.02%] [G loss: 0.695284]
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1178 [D loss: 0.693760, acc.: 49.80%] [G loss: 0.694612]
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1179 [D loss: 0.693652, acc.: 47.85%] [G loss: 0.696188]
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1180 [D loss: 0.692546, acc.: 50.98%] [G loss: 0.698560]
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1181 [D loss: 0.693532, acc.: 50.00%] [G loss: 0.697715]
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1182 [D loss: 0.693178, acc.: 50.98%] [G loss: 0.696897]
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1183 [D loss: 0.692911, acc.: 50.78%] [G loss: 0.698127]
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1184 [D loss: 0.692846, acc.: 53.12%] [G loss: 0.696549]
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1185 [D loss: 0.691193, acc.: 53.71%] [G loss: 0.695043]
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1186 [D loss: 0.693049, acc.: 50.98%] [G loss: 0.694641]
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1187 [D loss: 0.692518, acc.: 49.80%] [G loss: 0.694265]
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1188 [D loss: 0.692600, acc.: 50.78%] [G loss: 0.692093]
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1189 [D loss: 0.692190, acc.: 52.54%] [G loss: 0.694831]
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1190 [D loss: 0.693683, acc.: 49.41%] [G loss: 0.692520]
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1191 [D loss: 0.692370, acc.: 53.12%] [G loss: 0.695371]
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1192 [D loss: 0.692713, acc.: 50.78%] [G loss: 0.694186]
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1193 [D loss: 0.692314, acc.: 50.39%] [G loss: 0.690946]
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1194 [D loss: 0.692092, acc.: 52.73%] [G loss: 0.693396]
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1195 [D loss: 0.693436, acc.: 50.78%] [G loss: 0.695977]
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1196 [D loss: 0.693523, acc.: 45.51%] [G loss: 0.693828]
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1197 [D loss: 0.692205, acc.: 52.93%] [G loss: 0.691243]
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1198 [D loss: 0.693162, acc.: 50.00%] [G loss: 0.691069]
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1199 [D loss: 0.694163, acc.: 47.85%] [G loss: 0.692819]
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1200 [D loss: 0.692955, acc.: 50.98%] [G loss: 0.690965]
1/1 [==============================] - 0s 16ms/step
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1201 [D loss: 0.693800, acc.: 48.83%] [G loss: 0.691085]
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1202 [D loss: 0.694162, acc.: 50.00%] [G loss: 0.689326]
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1203 [D loss: 0.693114, acc.: 50.39%] [G loss: 0.691201]
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1204 [D loss: 0.693083, acc.: 47.46%] [G loss: 0.689517]
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1205 [D loss: 0.693359, acc.: 51.95%] [G loss: 0.690080]
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1206 [D loss: 0.691904, acc.: 53.32%] [G loss: 0.692029]
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1207 [D loss: 0.693350, acc.: 51.37%] [G loss: 0.693378]
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1208 [D loss: 0.693396, acc.: 48.44%] [G loss: 0.693655]
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1209 [D loss: 0.692426, acc.: 51.37%] [G loss: 0.693613]
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1210 [D loss: 0.691555, acc.: 52.73%] [G loss: 0.693053]
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1211 [D loss: 0.692010, acc.: 52.15%] [G loss: 0.691121]
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1212 [D loss: 0.691001, acc.: 53.32%] [G loss: 0.691487]
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1213 [D loss: 0.691301, acc.: 51.95%] [G loss: 0.692309]
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1214 [D loss: 0.691927, acc.: 52.54%] [G loss: 0.692537]
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1215 [D loss: 0.692561, acc.: 48.83%] [G loss: 0.690858]
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1216 [D loss: 0.692554, acc.: 49.41%] [G loss: 0.691473]
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1217 [D loss: 0.692771, acc.: 52.93%] [G loss: 0.690294]
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1218 [D loss: 0.693270, acc.: 50.00%] [G loss: 0.691405]
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1219 [D loss: 0.691121, acc.: 51.56%] [G loss: 0.691424]
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1220 [D loss: 0.692555, acc.: 52.54%] [G loss: 0.691778]
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1221 [D loss: 0.692746, acc.: 51.76%] [G loss: 0.688595]
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1222 [D loss: 0.691943, acc.: 52.15%] [G loss: 0.688207]
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1223 [D loss: 0.693976, acc.: 48.44%] [G loss: 0.689338]
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1224 [D loss: 0.693502, acc.: 49.80%] [G loss: 0.689156]
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1225 [D loss: 0.693784, acc.: 47.85%] [G loss: 0.687530]
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1226 [D loss: 0.693630, acc.: 50.59%] [G loss: 0.691679]
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1227 [D loss: 0.694912, acc.: 45.12%] [G loss: 0.691254]
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1228 [D loss: 0.693234, acc.: 50.20%] [G loss: 0.690899]
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1229 [D loss: 0.693296, acc.: 50.39%] [G loss: 0.690310]
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1230 [D loss: 0.693817, acc.: 49.02%] [G loss: 0.692177]
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1231 [D loss: 0.695293, acc.: 45.70%] [G loss: 0.689533]
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1232 [D loss: 0.694063, acc.: 49.80%] [G loss: 0.690462]
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1233 [D loss: 0.695092, acc.: 45.90%] [G loss: 0.691401]
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1234 [D loss: 0.694167, acc.: 47.27%] [G loss: 0.692867]
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1235 [D loss: 0.693187, acc.: 51.37%] [G loss: 0.692671]
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1236 [D loss: 0.694357, acc.: 47.07%] [G loss: 0.692440]
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1237 [D loss: 0.692681, acc.: 50.00%] [G loss: 0.692995]
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1238 [D loss: 0.693389, acc.: 49.22%] [G loss: 0.692986]
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1239 [D loss: 0.693005, acc.: 51.76%] [G loss: 0.691688]
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1240 [D loss: 0.693770, acc.: 47.27%] [G loss: 0.692502]
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1241 [D loss: 0.692714, acc.: 50.20%] [G loss: 0.693990]
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1242 [D loss: 0.693023, acc.: 50.98%] [G loss: 0.695550]
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1243 [D loss: 0.692910, acc.: 50.20%] [G loss: 0.693015]
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1244 [D loss: 0.693848, acc.: 49.61%] [G loss: 0.695754]
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1245 [D loss: 0.694128, acc.: 47.46%] [G loss: 0.695564]
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1246 [D loss: 0.691579, acc.: 55.66%] [G loss: 0.695440]
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1247 [D loss: 0.693848, acc.: 50.78%] [G loss: 0.695464]
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1248 [D loss: 0.692655, acc.: 51.76%] [G loss: 0.695118]
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1249 [D loss: 0.693256, acc.: 48.83%] [G loss: 0.696763]
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1250 [D loss: 0.690944, acc.: 55.27%] [G loss: 0.695554]
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1251 [D loss: 0.692590, acc.: 52.34%] [G loss: 0.696930]
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1252 [D loss: 0.692732, acc.: 52.54%] [G loss: 0.694480]
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1253 [D loss: 0.692447, acc.: 52.15%] [G loss: 0.693948]
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1254 [D loss: 0.692187, acc.: 53.32%] [G loss: 0.695211]
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1255 [D loss: 0.691561, acc.: 52.73%] [G loss: 0.695015]
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1256 [D loss: 0.693763, acc.: 49.22%] [G loss: 0.694522]
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1257 [D loss: 0.693518, acc.: 50.39%] [G loss: 0.695514]
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1258 [D loss: 0.692661, acc.: 50.98%] [G loss: 0.693608]
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1259 [D loss: 0.692944, acc.: 50.39%] [G loss: 0.693594]
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1260 [D loss: 0.693192, acc.: 48.24%] [G loss: 0.693045]
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1261 [D loss: 0.693291, acc.: 48.83%] [G loss: 0.694703]
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1262 [D loss: 0.693319, acc.: 49.80%] [G loss: 0.693037]
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1263 [D loss: 0.694173, acc.: 50.39%] [G loss: 0.692498]
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1264 [D loss: 0.693321, acc.: 50.39%] [G loss: 0.693803]
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1265 [D loss: 0.693185, acc.: 51.37%] [G loss: 0.693171]
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1266 [D loss: 0.692539, acc.: 52.93%] [G loss: 0.694538]
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1267 [D loss: 0.693073, acc.: 50.20%] [G loss: 0.694600]
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1268 [D loss: 0.692901, acc.: 52.34%] [G loss: 0.693886]
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1269 [D loss: 0.693588, acc.: 49.22%] [G loss: 0.694999]
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1270 [D loss: 0.692617, acc.: 50.00%] [G loss: 0.693519]
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1271 [D loss: 0.692615, acc.: 51.76%] [G loss: 0.692950]
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1272 [D loss: 0.693145, acc.: 50.00%] [G loss: 0.694520]
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1273 [D loss: 0.694363, acc.: 46.09%] [G loss: 0.694667]
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1274 [D loss: 0.692000, acc.: 53.52%] [G loss: 0.695141]
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1275 [D loss: 0.693042, acc.: 49.22%] [G loss: 0.695252]
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1276 [D loss: 0.692120, acc.: 53.32%] [G loss: 0.694535]
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1277 [D loss: 0.693922, acc.: 49.61%] [G loss: 0.692717]
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1278 [D loss: 0.691621, acc.: 55.47%] [G loss: 0.693712]
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1279 [D loss: 0.691643, acc.: 55.66%] [G loss: 0.692994]
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1280 [D loss: 0.692706, acc.: 51.56%] [G loss: 0.693920]
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1281 [D loss: 0.693465, acc.: 49.41%] [G loss: 0.695889]
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1282 [D loss: 0.693038, acc.: 52.15%] [G loss: 0.695254]
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1283 [D loss: 0.691599, acc.: 56.05%] [G loss: 0.695106]
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1284 [D loss: 0.693039, acc.: 49.80%] [G loss: 0.695703]
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1285 [D loss: 0.692953, acc.: 51.76%] [G loss: 0.697736]
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1286 [D loss: 0.692549, acc.: 51.76%] [G loss: 0.696029]
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1287 [D loss: 0.693453, acc.: 47.85%] [G loss: 0.695057]
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1288 [D loss: 0.693410, acc.: 48.24%] [G loss: 0.693257]
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1289 [D loss: 0.693564, acc.: 50.78%] [G loss: 0.693086]
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1290 [D loss: 0.694065, acc.: 47.66%] [G loss: 0.694810]
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1291 [D loss: 0.692871, acc.: 49.61%] [G loss: 0.692539]
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1292 [D loss: 0.694245, acc.: 46.29%] [G loss: 0.692716]
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1293 [D loss: 0.693339, acc.: 50.39%] [G loss: 0.691633]
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1294 [D loss: 0.693234, acc.: 49.02%] [G loss: 0.694698]
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1295 [D loss: 0.693670, acc.: 49.80%] [G loss: 0.693272]
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1296 [D loss: 0.693203, acc.: 51.37%] [G loss: 0.694102]
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1297 [D loss: 0.692670, acc.: 53.32%] [G loss: 0.694445]
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1298 [D loss: 0.693527, acc.: 47.07%] [G loss: 0.694311]
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1299 [D loss: 0.693758, acc.: 48.83%] [G loss: 0.693668]
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1300 [D loss: 0.692961, acc.: 52.15%] [G loss: 0.694797]
1/1 [==============================] - 0s 15ms/step
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1301 [D loss: 0.692960, acc.: 49.22%] [G loss: 0.693426]
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1302 [D loss: 0.692517, acc.: 53.32%] [G loss: 0.692768]
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1303 [D loss: 0.693870, acc.: 47.66%] [G loss: 0.694279]
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1304 [D loss: 0.691968, acc.: 54.10%] [G loss: 0.696466]
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1305 [D loss: 0.691606, acc.: 52.73%] [G loss: 0.697144]
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1306 [D loss: 0.692373, acc.: 55.66%] [G loss: 0.696426]
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1307 [D loss: 0.692412, acc.: 52.34%] [G loss: 0.697867]
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1308 [D loss: 0.693926, acc.: 47.85%] [G loss: 0.697066]
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1309 [D loss: 0.692904, acc.: 50.98%] [G loss: 0.696602]
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1310 [D loss: 0.693678, acc.: 50.98%] [G loss: 0.696470]
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1311 [D loss: 0.693182, acc.: 49.41%] [G loss: 0.696106]
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1312 [D loss: 0.693444, acc.: 47.85%] [G loss: 0.696848]
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1313 [D loss: 0.692098, acc.: 52.73%] [G loss: 0.697105]
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1314 [D loss: 0.692153, acc.: 53.71%] [G loss: 0.694660]
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1315 [D loss: 0.693209, acc.: 48.63%] [G loss: 0.696328]
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1316 [D loss: 0.692636, acc.: 51.76%] [G loss: 0.697443]
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1317 [D loss: 0.693483, acc.: 47.66%] [G loss: 0.695369]
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1318 [D loss: 0.694417, acc.: 48.05%] [G loss: 0.695776]
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1319 [D loss: 0.693100, acc.: 50.78%] [G loss: 0.695333]
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1320 [D loss: 0.693992, acc.: 48.63%] [G loss: 0.695756]
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1321 [D loss: 0.692891, acc.: 50.00%] [G loss: 0.693703]
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1322 [D loss: 0.692407, acc.: 53.52%] [G loss: 0.695139]
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1323 [D loss: 0.691980, acc.: 52.93%] [G loss: 0.694886]
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1324 [D loss: 0.692458, acc.: 50.98%] [G loss: 0.692519]
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1325 [D loss: 0.691704, acc.: 54.30%] [G loss: 0.694644]
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1326 [D loss: 0.693059, acc.: 47.85%] [G loss: 0.693507]
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1327 [D loss: 0.694189, acc.: 45.90%] [G loss: 0.693271]
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1328 [D loss: 0.693157, acc.: 50.78%] [G loss: 0.694436]
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1329 [D loss: 0.692788, acc.: 51.37%] [G loss: 0.692606]
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1330 [D loss: 0.693407, acc.: 48.83%] [G loss: 0.694245]
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1331 [D loss: 0.693469, acc.: 51.37%] [G loss: 0.693580]
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1332 [D loss: 0.693213, acc.: 51.17%] [G loss: 0.692249]
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1333 [D loss: 0.693029, acc.: 50.39%] [G loss: 0.692958]
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1334 [D loss: 0.692677, acc.: 52.34%] [G loss: 0.693727]
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1335 [D loss: 0.692154, acc.: 52.54%] [G loss: 0.693177]
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1336 [D loss: 0.693126, acc.: 47.85%] [G loss: 0.691148]
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1337 [D loss: 0.693280, acc.: 49.61%] [G loss: 0.692815]
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1338 [D loss: 0.692639, acc.: 53.12%] [G loss: 0.693526]
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1339 [D loss: 0.693852, acc.: 47.07%] [G loss: 0.691632]
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1340 [D loss: 0.693803, acc.: 48.05%] [G loss: 0.693996]
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1341 [D loss: 0.693116, acc.: 49.02%] [G loss: 0.693220]
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1342 [D loss: 0.692304, acc.: 51.76%] [G loss: 0.692658]
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1343 [D loss: 0.693269, acc.: 50.59%] [G loss: 0.694128]
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1344 [D loss: 0.692317, acc.: 54.88%] [G loss: 0.693298]
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1345 [D loss: 0.693914, acc.: 48.83%] [G loss: 0.692814]
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1346 [D loss: 0.692569, acc.: 53.12%] [G loss: 0.692347]
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1347 [D loss: 0.692263, acc.: 54.30%] [G loss: 0.692424]
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1348 [D loss: 0.691874, acc.: 51.17%] [G loss: 0.692926]
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1349 [D loss: 0.692427, acc.: 54.88%] [G loss: 0.694001]
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1350 [D loss: 0.693446, acc.: 49.41%] [G loss: 0.692638]
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1351 [D loss: 0.692014, acc.: 52.93%] [G loss: 0.691361]
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1352 [D loss: 0.692433, acc.: 51.37%] [G loss: 0.692624]
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1353 [D loss: 0.693605, acc.: 47.85%] [G loss: 0.693056]
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1354 [D loss: 0.693028, acc.: 50.20%] [G loss: 0.691805]
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1355 [D loss: 0.692275, acc.: 55.27%] [G loss: 0.692069]
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1356 [D loss: 0.692442, acc.: 50.20%] [G loss: 0.688256]
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1357 [D loss: 0.694672, acc.: 46.68%] [G loss: 0.690418]
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1358 [D loss: 0.694048, acc.: 49.41%] [G loss: 0.691074]
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1359 [D loss: 0.692704, acc.: 51.37%] [G loss: 0.689144]
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1360 [D loss: 0.693507, acc.: 47.66%] [G loss: 0.691198]
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1361 [D loss: 0.693970, acc.: 48.63%] [G loss: 0.691117]
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1362 [D loss: 0.693564, acc.: 48.05%] [G loss: 0.690984]
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1363 [D loss: 0.692949, acc.: 51.95%] [G loss: 0.691700]
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1364 [D loss: 0.693295, acc.: 50.59%] [G loss: 0.688700]
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1365 [D loss: 0.693268, acc.: 49.80%] [G loss: 0.691621]
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1366 [D loss: 0.693747, acc.: 50.98%] [G loss: 0.690164]
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1367 [D loss: 0.694027, acc.: 45.31%] [G loss: 0.689064]
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1368 [D loss: 0.694057, acc.: 48.83%] [G loss: 0.690777]
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1369 [D loss: 0.692558, acc.: 50.20%] [G loss: 0.688935]
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1370 [D loss: 0.694359, acc.: 44.53%] [G loss: 0.690502]
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1371 [D loss: 0.693248, acc.: 51.17%] [G loss: 0.690221]
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1372 [D loss: 0.692724, acc.: 51.76%] [G loss: 0.690401]
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1373 [D loss: 0.693395, acc.: 49.80%] [G loss: 0.689823]
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1374 [D loss: 0.693493, acc.: 48.44%] [G loss: 0.689973]
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1375 [D loss: 0.693181, acc.: 50.98%] [G loss: 0.692387]
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1376 [D loss: 0.693616, acc.: 48.83%] [G loss: 0.691542]
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1377 [D loss: 0.693214, acc.: 50.98%] [G loss: 0.690484]
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1378 [D loss: 0.693340, acc.: 48.44%] [G loss: 0.690806]
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1379 [D loss: 0.693369, acc.: 49.41%] [G loss: 0.688930]
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1380 [D loss: 0.691809, acc.: 54.49%] [G loss: 0.691294]
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1381 [D loss: 0.692223, acc.: 54.49%] [G loss: 0.690771]
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1382 [D loss: 0.693393, acc.: 49.80%] [G loss: 0.691869]
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1383 [D loss: 0.692352, acc.: 54.69%] [G loss: 0.692720]
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1384 [D loss: 0.692809, acc.: 50.20%] [G loss: 0.692573]
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1385 [D loss: 0.691650, acc.: 53.52%] [G loss: 0.691982]
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1386 [D loss: 0.691640, acc.: 54.69%] [G loss: 0.692846]
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1387 [D loss: 0.691781, acc.: 53.71%] [G loss: 0.692409]
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1388 [D loss: 0.691705, acc.: 54.30%] [G loss: 0.693668]
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1389 [D loss: 0.692778, acc.: 52.15%] [G loss: 0.693351]
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1390 [D loss: 0.692293, acc.: 52.54%] [G loss: 0.693518]
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1391 [D loss: 0.691196, acc.: 55.47%] [G loss: 0.694152]
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1392 [D loss: 0.692448, acc.: 53.71%] [G loss: 0.693438]
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1393 [D loss: 0.691203, acc.: 52.93%] [G loss: 0.694567]
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1394 [D loss: 0.690649, acc.: 58.20%] [G loss: 0.694143]
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1395 [D loss: 0.692868, acc.: 51.37%] [G loss: 0.695655]
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1396 [D loss: 0.691985, acc.: 53.32%] [G loss: 0.694020]
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1397 [D loss: 0.691924, acc.: 54.69%] [G loss: 0.693426]
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1398 [D loss: 0.692738, acc.: 50.59%] [G loss: 0.694376]
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1399 [D loss: 0.692402, acc.: 53.71%] [G loss: 0.693733]
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1400 [D loss: 0.691814, acc.: 54.88%] [G loss: 0.695594]
1/1 [==============================] - 0s 14ms/step
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1401 [D loss: 0.692728, acc.: 50.78%] [G loss: 0.695703]
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1402 [D loss: 0.693789, acc.: 49.80%] [G loss: 0.692989]
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1403 [D loss: 0.692321, acc.: 52.54%] [G loss: 0.694519]
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1404 [D loss: 0.693095, acc.: 49.41%] [G loss: 0.693127]
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1405 [D loss: 0.692282, acc.: 50.20%] [G loss: 0.693018]
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1406 [D loss: 0.692771, acc.: 51.17%] [G loss: 0.692453]
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1407 [D loss: 0.691905, acc.: 56.64%] [G loss: 0.692938]
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1408 [D loss: 0.692699, acc.: 51.76%] [G loss: 0.692341]
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1409 [D loss: 0.692982, acc.: 53.71%] [G loss: 0.693094]
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1410 [D loss: 0.691980, acc.: 55.27%] [G loss: 0.694902]
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1411 [D loss: 0.693083, acc.: 50.78%] [G loss: 0.695730]
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1412 [D loss: 0.694101, acc.: 49.02%] [G loss: 0.692248]
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1413 [D loss: 0.693268, acc.: 48.05%] [G loss: 0.695000]
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1414 [D loss: 0.692581, acc.: 49.61%] [G loss: 0.694060]
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1415 [D loss: 0.692719, acc.: 51.37%] [G loss: 0.696383]
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1416 [D loss: 0.692632, acc.: 54.10%] [G loss: 0.693660]
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1417 [D loss: 0.692687, acc.: 51.56%] [G loss: 0.693264]
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1418 [D loss: 0.693370, acc.: 49.02%] [G loss: 0.692708]
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1419 [D loss: 0.693442, acc.: 49.22%] [G loss: 0.691754]
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1420 [D loss: 0.694510, acc.: 47.85%] [G loss: 0.692753]
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1421 [D loss: 0.692904, acc.: 51.56%] [G loss: 0.693164]
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1422 [D loss: 0.694158, acc.: 47.85%] [G loss: 0.692037]
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1423 [D loss: 0.693557, acc.: 47.07%] [G loss: 0.694052]
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1424 [D loss: 0.692260, acc.: 52.34%] [G loss: 0.693190]
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1425 [D loss: 0.692801, acc.: 52.15%] [G loss: 0.693936]
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1426 [D loss: 0.693507, acc.: 51.37%] [G loss: 0.693049]
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1427 [D loss: 0.693145, acc.: 50.78%] [G loss: 0.692971]
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1428 [D loss: 0.693335, acc.: 49.02%] [G loss: 0.692716]
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1429 [D loss: 0.693755, acc.: 50.20%] [G loss: 0.692909]
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1430 [D loss: 0.693534, acc.: 49.41%] [G loss: 0.693171]
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1431 [D loss: 0.693179, acc.: 51.76%] [G loss: 0.694896]
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1432 [D loss: 0.692572, acc.: 49.61%] [G loss: 0.693381]
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1433 [D loss: 0.693065, acc.: 51.56%] [G loss: 0.693109]
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1434 [D loss: 0.693575, acc.: 48.83%] [G loss: 0.692560]
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1435 [D loss: 0.693731, acc.: 47.27%] [G loss: 0.691559]
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1436 [D loss: 0.693988, acc.: 49.02%] [G loss: 0.690449]
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1437 [D loss: 0.693209, acc.: 48.63%] [G loss: 0.691397]
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1438 [D loss: 0.693292, acc.: 52.93%] [G loss: 0.691309]
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1439 [D loss: 0.693721, acc.: 49.22%] [G loss: 0.691039]
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1440 [D loss: 0.693450, acc.: 50.00%] [G loss: 0.690657]
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1441 [D loss: 0.693165, acc.: 53.32%] [G loss: 0.690316]
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1442 [D loss: 0.693686, acc.: 48.44%] [G loss: 0.690766]
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1443 [D loss: 0.694173, acc.: 48.05%] [G loss: 0.689929]
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1444 [D loss: 0.694861, acc.: 43.95%] [G loss: 0.691659]
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1445 [D loss: 0.693559, acc.: 46.68%] [G loss: 0.691473]
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1446 [D loss: 0.693871, acc.: 46.88%] [G loss: 0.690175]
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1447 [D loss: 0.693428, acc.: 50.20%] [G loss: 0.692501]
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1448 [D loss: 0.693049, acc.: 49.41%] [G loss: 0.691558]
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1449 [D loss: 0.693781, acc.: 49.02%] [G loss: 0.692999]
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1450 [D loss: 0.693833, acc.: 49.61%] [G loss: 0.692080]
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1451 [D loss: 0.692504, acc.: 51.95%] [G loss: 0.694137]
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1452 [D loss: 0.691734, acc.: 55.08%] [G loss: 0.694597]
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1453 [D loss: 0.692400, acc.: 52.15%] [G loss: 0.692182]
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1454 [D loss: 0.692116, acc.: 52.34%] [G loss: 0.694565]
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1455 [D loss: 0.692228, acc.: 53.52%] [G loss: 0.694914]
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1456 [D loss: 0.691837, acc.: 52.15%] [G loss: 0.693655]
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1457 [D loss: 0.692991, acc.: 50.98%] [G loss: 0.694799]
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1458 [D loss: 0.691643, acc.: 56.05%] [G loss: 0.694982]
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1459 [D loss: 0.692354, acc.: 51.76%] [G loss: 0.695972]
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1460 [D loss: 0.692565, acc.: 51.37%] [G loss: 0.695716]
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1461 [D loss: 0.693027, acc.: 51.37%] [G loss: 0.696465]
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1462 [D loss: 0.691937, acc.: 54.30%] [G loss: 0.696983]
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1463 [D loss: 0.692590, acc.: 50.78%] [G loss: 0.695397]
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1464 [D loss: 0.692662, acc.: 53.52%] [G loss: 0.695950]
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1465 [D loss: 0.692283, acc.: 52.34%] [G loss: 0.695239]
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1466 [D loss: 0.692195, acc.: 53.71%] [G loss: 0.694439]
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1467 [D loss: 0.692987, acc.: 49.41%] [G loss: 0.695852]
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1468 [D loss: 0.692559, acc.: 52.54%] [G loss: 0.693153]
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1469 [D loss: 0.692896, acc.: 49.22%] [G loss: 0.695857]
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1470 [D loss: 0.694088, acc.: 47.07%] [G loss: 0.695286]
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1471 [D loss: 0.693106, acc.: 48.63%] [G loss: 0.693572]
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1472 [D loss: 0.692632, acc.: 51.37%] [G loss: 0.696849]
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1473 [D loss: 0.692934, acc.: 50.59%] [G loss: 0.692484]
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1474 [D loss: 0.693855, acc.: 48.83%] [G loss: 0.692748]
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1475 [D loss: 0.694131, acc.: 48.44%] [G loss: 0.694479]
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1476 [D loss: 0.693170, acc.: 50.20%] [G loss: 0.694491]
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1477 [D loss: 0.693671, acc.: 47.46%] [G loss: 0.694003]
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1478 [D loss: 0.693091, acc.: 50.00%] [G loss: 0.694210]
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1479 [D loss: 0.692315, acc.: 54.49%] [G loss: 0.693589]
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1480 [D loss: 0.693912, acc.: 47.07%] [G loss: 0.694156]
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1481 [D loss: 0.692695, acc.: 51.76%] [G loss: 0.691595]
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1482 [D loss: 0.692533, acc.: 48.44%] [G loss: 0.693299]
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1483 [D loss: 0.693785, acc.: 50.59%] [G loss: 0.694338]
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1484 [D loss: 0.693361, acc.: 50.98%] [G loss: 0.694252]
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1485 [D loss: 0.693820, acc.: 47.46%] [G loss: 0.693274]
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1486 [D loss: 0.693106, acc.: 50.39%] [G loss: 0.693438]
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1487 [D loss: 0.693338, acc.: 49.02%] [G loss: 0.694039]
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1488 [D loss: 0.693409, acc.: 47.07%] [G loss: 0.692907]
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1489 [D loss: 0.693944, acc.: 46.48%] [G loss: 0.692849]
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1490 [D loss: 0.693097, acc.: 51.17%] [G loss: 0.694154]
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1491 [D loss: 0.694640, acc.: 45.12%] [G loss: 0.693573]
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1492 [D loss: 0.694685, acc.: 47.46%] [G loss: 0.694505]
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1493 [D loss: 0.693514, acc.: 51.95%] [G loss: 0.695811]
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1494 [D loss: 0.693493, acc.: 47.07%] [G loss: 0.693143]
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1495 [D loss: 0.693034, acc.: 51.37%] [G loss: 0.694644]
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1496 [D loss: 0.693507, acc.: 49.22%] [G loss: 0.694029]
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1497 [D loss: 0.692695, acc.: 53.91%] [G loss: 0.694995]
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1498 [D loss: 0.693203, acc.: 50.98%] [G loss: 0.693710]
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1499 [D loss: 0.693191, acc.: 52.15%] [G loss: 0.694051]
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1500 [D loss: 0.693618, acc.: 48.44%] [G loss: 0.694366]
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1501 [D loss: 0.693263, acc.: 50.00%] [G loss: 0.693453]
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1502 [D loss: 0.693648, acc.: 48.44%] [G loss: 0.695597]
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1503 [D loss: 0.693311, acc.: 50.39%] [G loss: 0.696302]
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1504 [D loss: 0.693268, acc.: 49.80%] [G loss: 0.694629]
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1505 [D loss: 0.693414, acc.: 50.00%] [G loss: 0.696045]
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1506 [D loss: 0.694557, acc.: 46.09%] [G loss: 0.697200]
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1507 [D loss: 0.693185, acc.: 49.02%] [G loss: 0.694633]
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1508 [D loss: 0.693482, acc.: 48.83%] [G loss: 0.696913]
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1509 [D loss: 0.692524, acc.: 51.76%] [G loss: 0.695214]
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1510 [D loss: 0.692904, acc.: 49.02%] [G loss: 0.695968]
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1511 [D loss: 0.691794, acc.: 53.12%] [G loss: 0.696802]
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1512 [D loss: 0.692674, acc.: 53.52%] [G loss: 0.696451]
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1513 [D loss: 0.692406, acc.: 52.54%] [G loss: 0.697295]
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1514 [D loss: 0.692929, acc.: 50.00%] [G loss: 0.695667]
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1515 [D loss: 0.692153, acc.: 51.37%] [G loss: 0.697253]
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1516 [D loss: 0.692023, acc.: 53.32%] [G loss: 0.696882]
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1517 [D loss: 0.692628, acc.: 51.56%] [G loss: 0.696360]
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1518 [D loss: 0.692081, acc.: 50.98%] [G loss: 0.697282]
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1519 [D loss: 0.692144, acc.: 53.32%] [G loss: 0.696955]
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1520 [D loss: 0.691982, acc.: 51.17%] [G loss: 0.695633]
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1521 [D loss: 0.692054, acc.: 53.12%] [G loss: 0.696309]
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1522 [D loss: 0.692438, acc.: 54.88%] [G loss: 0.694352]
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1523 [D loss: 0.692782, acc.: 52.73%] [G loss: 0.693310]
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1524 [D loss: 0.692388, acc.: 51.17%] [G loss: 0.694828]
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1525 [D loss: 0.692277, acc.: 53.71%] [G loss: 0.693525]
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1526 [D loss: 0.692965, acc.: 51.56%] [G loss: 0.692440]
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1527 [D loss: 0.692432, acc.: 51.95%] [G loss: 0.693231]
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1528 [D loss: 0.693168, acc.: 50.59%] [G loss: 0.690899]
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1529 [D loss: 0.692692, acc.: 50.59%] [G loss: 0.691685]
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1530 [D loss: 0.693629, acc.: 50.98%] [G loss: 0.690523]
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1531 [D loss: 0.693660, acc.: 49.61%] [G loss: 0.690714]
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1532 [D loss: 0.693222, acc.: 48.05%] [G loss: 0.689779]
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1533 [D loss: 0.693713, acc.: 49.22%] [G loss: 0.689962]
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1534 [D loss: 0.693078, acc.: 51.56%] [G loss: 0.691424]
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1535 [D loss: 0.694263, acc.: 47.66%] [G loss: 0.692610]
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1536 [D loss: 0.692837, acc.: 52.73%] [G loss: 0.692088]
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1537 [D loss: 0.694665, acc.: 46.68%] [G loss: 0.692840]
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1538 [D loss: 0.693572, acc.: 51.17%] [G loss: 0.691815]
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1539 [D loss: 0.693822, acc.: 48.83%] [G loss: 0.691807]
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1540 [D loss: 0.694193, acc.: 45.90%] [G loss: 0.694961]
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1541 [D loss: 0.693791, acc.: 50.00%] [G loss: 0.691934]
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1542 [D loss: 0.694946, acc.: 45.31%] [G loss: 0.692068]
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1543 [D loss: 0.692922, acc.: 49.22%] [G loss: 0.692645]
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1544 [D loss: 0.693620, acc.: 49.02%] [G loss: 0.693918]
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1545 [D loss: 0.693293, acc.: 50.78%] [G loss: 0.694519]
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1546 [D loss: 0.693842, acc.: 46.48%] [G loss: 0.696668]
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1547 [D loss: 0.693515, acc.: 49.41%] [G loss: 0.695117]
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1548 [D loss: 0.694192, acc.: 47.07%] [G loss: 0.693858]
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1549 [D loss: 0.692652, acc.: 49.61%] [G loss: 0.691690]
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1550 [D loss: 0.692829, acc.: 50.59%] [G loss: 0.692296]
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1551 [D loss: 0.694093, acc.: 47.46%] [G loss: 0.691429]
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1552 [D loss: 0.693271, acc.: 49.41%] [G loss: 0.692616]
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1553 [D loss: 0.694310, acc.: 46.29%] [G loss: 0.693187]
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1554 [D loss: 0.691833, acc.: 55.66%] [G loss: 0.692743]
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1555 [D loss: 0.693647, acc.: 51.17%] [G loss: 0.695123]
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1556 [D loss: 0.691280, acc.: 55.47%] [G loss: 0.694911]
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1557 [D loss: 0.692852, acc.: 50.59%] [G loss: 0.695210]
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1558 [D loss: 0.692706, acc.: 52.15%] [G loss: 0.694474]
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1559 [D loss: 0.692870, acc.: 52.93%] [G loss: 0.694473]
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1560 [D loss: 0.691752, acc.: 54.88%] [G loss: 0.692033]
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1561 [D loss: 0.692302, acc.: 54.10%] [G loss: 0.694586]
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1562 [D loss: 0.691179, acc.: 54.69%] [G loss: 0.694174]
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1563 [D loss: 0.692237, acc.: 53.91%] [G loss: 0.696399]
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1564 [D loss: 0.691652, acc.: 54.88%] [G loss: 0.696890]
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1565 [D loss: 0.691161, acc.: 53.52%] [G loss: 0.696054]
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1566 [D loss: 0.691177, acc.: 57.23%] [G loss: 0.695799]
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1567 [D loss: 0.692249, acc.: 49.22%] [G loss: 0.695260]
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1568 [D loss: 0.692972, acc.: 50.00%] [G loss: 0.696501]
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1569 [D loss: 0.691505, acc.: 52.93%] [G loss: 0.695537]
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1570 [D loss: 0.691849, acc.: 52.73%] [G loss: 0.694139]
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1571 [D loss: 0.693424, acc.: 48.24%] [G loss: 0.694578]
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1572 [D loss: 0.692870, acc.: 50.20%] [G loss: 0.694640]
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1573 [D loss: 0.693549, acc.: 49.61%] [G loss: 0.694028]
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1574 [D loss: 0.691498, acc.: 55.86%] [G loss: 0.693751]
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1575 [D loss: 0.692804, acc.: 51.17%] [G loss: 0.694993]
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1576 [D loss: 0.693707, acc.: 49.22%] [G loss: 0.694196]
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1577 [D loss: 0.693247, acc.: 51.17%] [G loss: 0.693590]
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1578 [D loss: 0.691767, acc.: 54.49%] [G loss: 0.693896]
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1579 [D loss: 0.693698, acc.: 50.20%] [G loss: 0.693554]
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1580 [D loss: 0.693807, acc.: 48.44%] [G loss: 0.692052]
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1581 [D loss: 0.694360, acc.: 47.27%] [G loss: 0.693878]
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1582 [D loss: 0.693697, acc.: 48.24%] [G loss: 0.695601]
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1583 [D loss: 0.692385, acc.: 51.95%] [G loss: 0.692986]
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1584 [D loss: 0.692232, acc.: 54.10%] [G loss: 0.695600]
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1585 [D loss: 0.693233, acc.: 49.22%] [G loss: 0.694129]
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1586 [D loss: 0.691958, acc.: 53.52%] [G loss: 0.692699]
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1587 [D loss: 0.693059, acc.: 52.15%] [G loss: 0.695464]
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1588 [D loss: 0.693410, acc.: 48.24%] [G loss: 0.695405]
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1589 [D loss: 0.693692, acc.: 47.27%] [G loss: 0.692005]
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1590 [D loss: 0.693543, acc.: 47.46%] [G loss: 0.691767]
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1591 [D loss: 0.693049, acc.: 54.30%] [G loss: 0.693509]
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1592 [D loss: 0.691204, acc.: 57.23%] [G loss: 0.695898]
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1593 [D loss: 0.692884, acc.: 50.20%] [G loss: 0.692899]
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1594 [D loss: 0.693830, acc.: 48.63%] [G loss: 0.693860]
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1595 [D loss: 0.694164, acc.: 47.27%] [G loss: 0.695138]
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1596 [D loss: 0.692956, acc.: 53.52%] [G loss: 0.694074]
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1597 [D loss: 0.692957, acc.: 52.15%] [G loss: 0.694049]
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1598 [D loss: 0.691482, acc.: 54.69%] [G loss: 0.694115]
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1599 [D loss: 0.692748, acc.: 51.37%] [G loss: 0.693661]
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1600 [D loss: 0.692170, acc.: 53.52%] [G loss: 0.693267]
1/1 [==============================] - 0s 15ms/step
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1601 [D loss: 0.695271, acc.: 45.90%] [G loss: 0.695077]
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1602 [D loss: 0.693043, acc.: 50.78%] [G loss: 0.696142]
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1603 [D loss: 0.693617, acc.: 47.27%] [G loss: 0.692569]
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1604 [D loss: 0.692789, acc.: 51.17%] [G loss: 0.693769]
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1605 [D loss: 0.694141, acc.: 46.48%] [G loss: 0.694342]
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1606 [D loss: 0.692808, acc.: 50.78%] [G loss: 0.693068]
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1607 [D loss: 0.692651, acc.: 51.17%] [G loss: 0.694198]
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1608 [D loss: 0.692214, acc.: 55.08%] [G loss: 0.693742]
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1609 [D loss: 0.693262, acc.: 49.61%] [G loss: 0.692326]
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1610 [D loss: 0.693046, acc.: 50.78%] [G loss: 0.694061]
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1611 [D loss: 0.693257, acc.: 50.00%] [G loss: 0.694091]
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1612 [D loss: 0.692049, acc.: 52.93%] [G loss: 0.692461]
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1613 [D loss: 0.693575, acc.: 50.00%] [G loss: 0.694615]
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1614 [D loss: 0.693639, acc.: 50.00%] [G loss: 0.692675]
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1615 [D loss: 0.692964, acc.: 52.93%] [G loss: 0.694907]
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1616 [D loss: 0.693611, acc.: 49.80%] [G loss: 0.693343]
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1617 [D loss: 0.692904, acc.: 50.59%] [G loss: 0.695125]
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1618 [D loss: 0.693254, acc.: 48.44%] [G loss: 0.695906]
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1619 [D loss: 0.692306, acc.: 51.95%] [G loss: 0.693524]
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1620 [D loss: 0.693313, acc.: 51.17%] [G loss: 0.694457]
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1621 [D loss: 0.693733, acc.: 48.83%] [G loss: 0.694775]
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1622 [D loss: 0.692273, acc.: 53.71%] [G loss: 0.694819]
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1623 [D loss: 0.692813, acc.: 51.95%] [G loss: 0.695014]
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1624 [D loss: 0.692509, acc.: 48.83%] [G loss: 0.693868]
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1625 [D loss: 0.692709, acc.: 50.98%] [G loss: 0.693177]
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1626 [D loss: 0.693088, acc.: 52.34%] [G loss: 0.693400]
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1627 [D loss: 0.692495, acc.: 50.78%] [G loss: 0.694043]
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1628 [D loss: 0.692300, acc.: 53.91%] [G loss: 0.692694]
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1629 [D loss: 0.694222, acc.: 47.46%] [G loss: 0.694113]
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1630 [D loss: 0.692655, acc.: 51.76%] [G loss: 0.694270]
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1631 [D loss: 0.693430, acc.: 48.63%] [G loss: 0.693352]
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1632 [D loss: 0.691868, acc.: 52.93%] [G loss: 0.693660]
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1633 [D loss: 0.694347, acc.: 47.07%] [G loss: 0.691069]
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1634 [D loss: 0.692092, acc.: 51.56%] [G loss: 0.692180]
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1635 [D loss: 0.693092, acc.: 51.76%] [G loss: 0.691163]
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1636 [D loss: 0.692167, acc.: 53.12%] [G loss: 0.693052]
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1637 [D loss: 0.692846, acc.: 52.15%] [G loss: 0.691804]
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1638 [D loss: 0.692988, acc.: 50.00%] [G loss: 0.691435]
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1639 [D loss: 0.692977, acc.: 50.59%] [G loss: 0.692778]
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1640 [D loss: 0.693396, acc.: 50.78%] [G loss: 0.691445]
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1641 [D loss: 0.693292, acc.: 52.93%] [G loss: 0.692382]
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1642 [D loss: 0.693419, acc.: 50.20%] [G loss: 0.692399]
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1643 [D loss: 0.693224, acc.: 49.02%] [G loss: 0.692751]
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1644 [D loss: 0.692988, acc.: 49.41%] [G loss: 0.692394]
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1645 [D loss: 0.692592, acc.: 51.76%] [G loss: 0.694793]
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1646 [D loss: 0.693997, acc.: 47.66%] [G loss: 0.693314]
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1647 [D loss: 0.693095, acc.: 49.80%] [G loss: 0.694535]
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1648 [D loss: 0.693232, acc.: 49.61%] [G loss: 0.692933]
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1649 [D loss: 0.692176, acc.: 50.59%] [G loss: 0.694152]
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1650 [D loss: 0.692873, acc.: 51.17%] [G loss: 0.695143]
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1651 [D loss: 0.692666, acc.: 51.37%] [G loss: 0.695046]
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1652 [D loss: 0.691799, acc.: 53.91%] [G loss: 0.694013]
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1653 [D loss: 0.693308, acc.: 50.20%] [G loss: 0.694466]
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1654 [D loss: 0.693594, acc.: 49.80%] [G loss: 0.694211]
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1655 [D loss: 0.692800, acc.: 52.15%] [G loss: 0.694357]
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1656 [D loss: 0.692681, acc.: 51.56%] [G loss: 0.694118]
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1657 [D loss: 0.692529, acc.: 51.37%] [G loss: 0.694370]
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1658 [D loss: 0.692863, acc.: 49.80%] [G loss: 0.693632]
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1659 [D loss: 0.692947, acc.: 50.59%] [G loss: 0.694760]
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1660 [D loss: 0.694960, acc.: 46.09%] [G loss: 0.694014]
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1661 [D loss: 0.693364, acc.: 47.46%] [G loss: 0.692450]
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1662 [D loss: 0.692669, acc.: 51.76%] [G loss: 0.693538]
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1663 [D loss: 0.693159, acc.: 53.71%] [G loss: 0.691623]
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1664 [D loss: 0.692566, acc.: 51.95%] [G loss: 0.693790]
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1665 [D loss: 0.693462, acc.: 49.41%] [G loss: 0.692339]
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1666 [D loss: 0.694284, acc.: 48.05%] [G loss: 0.693274]
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1667 [D loss: 0.693289, acc.: 50.39%] [G loss: 0.693706]
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1668 [D loss: 0.693152, acc.: 49.61%] [G loss: 0.691786]
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1669 [D loss: 0.692760, acc.: 51.37%] [G loss: 0.694295]
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1670 [D loss: 0.692617, acc.: 49.80%] [G loss: 0.694763]
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1671 [D loss: 0.693697, acc.: 51.76%] [G loss: 0.693599]
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1672 [D loss: 0.692593, acc.: 52.54%] [G loss: 0.695576]
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1673 [D loss: 0.692607, acc.: 50.59%] [G loss: 0.695985]
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1674 [D loss: 0.693136, acc.: 48.44%] [G loss: 0.694794]
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1675 [D loss: 0.693716, acc.: 49.61%] [G loss: 0.694655]
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1676 [D loss: 0.693258, acc.: 50.98%] [G loss: 0.694897]
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1677 [D loss: 0.692629, acc.: 50.98%] [G loss: 0.694549]
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1678 [D loss: 0.693089, acc.: 50.00%] [G loss: 0.693129]
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1679 [D loss: 0.692359, acc.: 55.86%] [G loss: 0.695322]
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1680 [D loss: 0.692060, acc.: 52.73%] [G loss: 0.695917]
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1681 [D loss: 0.693414, acc.: 50.59%] [G loss: 0.696191]
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1682 [D loss: 0.692516, acc.: 49.80%] [G loss: 0.695775]
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1683 [D loss: 0.692678, acc.: 55.66%] [G loss: 0.695944]
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1684 [D loss: 0.693659, acc.: 48.24%] [G loss: 0.694595]
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1685 [D loss: 0.691261, acc.: 55.08%] [G loss: 0.696636]
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1686 [D loss: 0.692854, acc.: 51.76%] [G loss: 0.692821]
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1687 [D loss: 0.692397, acc.: 52.54%] [G loss: 0.692752]
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1688 [D loss: 0.692991, acc.: 51.76%] [G loss: 0.694893]
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1689 [D loss: 0.693422, acc.: 50.59%] [G loss: 0.693997]
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1690 [D loss: 0.692667, acc.: 49.80%] [G loss: 0.693597]
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1691 [D loss: 0.694020, acc.: 49.02%] [G loss: 0.694350]
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1692 [D loss: 0.693163, acc.: 49.22%] [G loss: 0.695485]
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1693 [D loss: 0.694477, acc.: 48.63%] [G loss: 0.694742]
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1694 [D loss: 0.693318, acc.: 49.22%] [G loss: 0.694234]
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1695 [D loss: 0.693694, acc.: 49.02%] [G loss: 0.695322]
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1696 [D loss: 0.692705, acc.: 50.20%] [G loss: 0.693262]
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1697 [D loss: 0.693783, acc.: 49.02%] [G loss: 0.694267]
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1698 [D loss: 0.694280, acc.: 47.27%] [G loss: 0.694520]
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1699 [D loss: 0.692294, acc.: 54.88%] [G loss: 0.694253]
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1700 [D loss: 0.692864, acc.: 48.24%] [G loss: 0.695324]
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1701 [D loss: 0.693332, acc.: 50.78%] [G loss: 0.694887]
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1702 [D loss: 0.692872, acc.: 51.56%] [G loss: 0.697250]
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1703 [D loss: 0.692886, acc.: 49.22%] [G loss: 0.695948]
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1704 [D loss: 0.692648, acc.: 50.39%] [G loss: 0.696260]
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1705 [D loss: 0.692455, acc.: 54.10%] [G loss: 0.694859]
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1706 [D loss: 0.694174, acc.: 48.83%] [G loss: 0.695005]
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1707 [D loss: 0.694434, acc.: 46.48%] [G loss: 0.696291]
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1708 [D loss: 0.693762, acc.: 48.83%] [G loss: 0.695576]
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1709 [D loss: 0.692930, acc.: 49.61%] [G loss: 0.695921]
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1710 [D loss: 0.693023, acc.: 52.73%] [G loss: 0.695443]
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1711 [D loss: 0.693027, acc.: 49.80%] [G loss: 0.696211]
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1712 [D loss: 0.693440, acc.: 49.22%] [G loss: 0.694498]
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1713 [D loss: 0.692689, acc.: 50.20%] [G loss: 0.694527]
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1714 [D loss: 0.693072, acc.: 50.98%] [G loss: 0.695202]
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1715 [D loss: 0.692122, acc.: 53.71%] [G loss: 0.693866]
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1716 [D loss: 0.692922, acc.: 49.22%] [G loss: 0.695764]
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1717 [D loss: 0.692908, acc.: 51.37%] [G loss: 0.694339]
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1718 [D loss: 0.691928, acc.: 55.08%] [G loss: 0.693318]
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1719 [D loss: 0.692378, acc.: 53.91%] [G loss: 0.694342]
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1720 [D loss: 0.692538, acc.: 52.15%] [G loss: 0.694407]
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1721 [D loss: 0.693120, acc.: 51.17%] [G loss: 0.694393]
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1722 [D loss: 0.692344, acc.: 54.69%] [G loss: 0.694706]
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1723 [D loss: 0.692609, acc.: 52.15%] [G loss: 0.692093]
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1724 [D loss: 0.693862, acc.: 48.44%] [G loss: 0.693813]
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1725 [D loss: 0.693084, acc.: 50.59%] [G loss: 0.694316]
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1726 [D loss: 0.693000, acc.: 51.17%] [G loss: 0.692903]
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1727 [D loss: 0.692144, acc.: 53.71%] [G loss: 0.693951]
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1728 [D loss: 0.693504, acc.: 50.20%] [G loss: 0.692590]
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1729 [D loss: 0.693341, acc.: 51.37%] [G loss: 0.694777]
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1730 [D loss: 0.692563, acc.: 52.34%] [G loss: 0.693086]
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1731 [D loss: 0.692116, acc.: 51.95%] [G loss: 0.691871]
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1732 [D loss: 0.693459, acc.: 47.66%] [G loss: 0.692777]
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1733 [D loss: 0.692359, acc.: 50.78%] [G loss: 0.692334]
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1734 [D loss: 0.694481, acc.: 45.31%] [G loss: 0.692956]
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1735 [D loss: 0.693327, acc.: 49.80%] [G loss: 0.692803]
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1736 [D loss: 0.692975, acc.: 52.15%] [G loss: 0.691365]
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1737 [D loss: 0.692934, acc.: 50.00%] [G loss: 0.693441]
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1738 [D loss: 0.692024, acc.: 51.76%] [G loss: 0.691673]
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1739 [D loss: 0.692454, acc.: 53.12%] [G loss: 0.691565]
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1740 [D loss: 0.693537, acc.: 49.61%] [G loss: 0.692476]
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1741 [D loss: 0.693260, acc.: 51.17%] [G loss: 0.691033]
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1742 [D loss: 0.693369, acc.: 49.02%] [G loss: 0.691588]
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1743 [D loss: 0.693165, acc.: 49.61%] [G loss: 0.691605]
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1744 [D loss: 0.694802, acc.: 44.34%] [G loss: 0.691272]
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1745 [D loss: 0.693754, acc.: 50.59%] [G loss: 0.692675]
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1746 [D loss: 0.693564, acc.: 49.41%] [G loss: 0.690313]
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1747 [D loss: 0.693561, acc.: 48.24%] [G loss: 0.691696]
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1748 [D loss: 0.694116, acc.: 47.27%] [G loss: 0.691523]
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1749 [D loss: 0.694086, acc.: 48.44%] [G loss: 0.691497]
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1750 [D loss: 0.692980, acc.: 49.02%] [G loss: 0.692730]
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1751 [D loss: 0.693708, acc.: 49.80%] [G loss: 0.693146]
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1752 [D loss: 0.693152, acc.: 51.37%] [G loss: 0.692943]
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1753 [D loss: 0.691841, acc.: 53.52%] [G loss: 0.692691]
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1754 [D loss: 0.693805, acc.: 48.24%] [G loss: 0.695066]
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1755 [D loss: 0.692412, acc.: 52.73%] [G loss: 0.694166]
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1756 [D loss: 0.693485, acc.: 51.17%] [G loss: 0.693653]
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1757 [D loss: 0.693947, acc.: 48.44%] [G loss: 0.692552]
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1758 [D loss: 0.692862, acc.: 50.98%] [G loss: 0.693953]
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1759 [D loss: 0.692471, acc.: 50.59%] [G loss: 0.694181]
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1760 [D loss: 0.691837, acc.: 54.49%] [G loss: 0.693769]
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1761 [D loss: 0.693013, acc.: 51.17%] [G loss: 0.693527]
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1762 [D loss: 0.694228, acc.: 46.88%] [G loss: 0.693493]
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1763 [D loss: 0.694201, acc.: 48.24%] [G loss: 0.695397]
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1764 [D loss: 0.693533, acc.: 50.98%] [G loss: 0.694470]
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1765 [D loss: 0.693545, acc.: 50.78%] [G loss: 0.695762]
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1766 [D loss: 0.692895, acc.: 52.15%] [G loss: 0.695516]
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1767 [D loss: 0.692436, acc.: 53.91%] [G loss: 0.696445]
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1768 [D loss: 0.692987, acc.: 52.93%] [G loss: 0.696327]
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1769 [D loss: 0.692971, acc.: 50.78%] [G loss: 0.697517]
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1770 [D loss: 0.692815, acc.: 50.59%] [G loss: 0.696143]
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1771 [D loss: 0.692734, acc.: 49.61%] [G loss: 0.697977]
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1772 [D loss: 0.692937, acc.: 53.32%] [G loss: 0.697318]
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1773 [D loss: 0.692387, acc.: 50.39%] [G loss: 0.696372]
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1774 [D loss: 0.693401, acc.: 51.17%] [G loss: 0.698246]
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1775 [D loss: 0.692838, acc.: 54.49%] [G loss: 0.696677]
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1776 [D loss: 0.693224, acc.: 51.56%] [G loss: 0.697512]
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1777 [D loss: 0.693075, acc.: 49.80%] [G loss: 0.695688]
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1778 [D loss: 0.692778, acc.: 52.15%] [G loss: 0.696503]
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1779 [D loss: 0.693091, acc.: 50.78%] [G loss: 0.696181]
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1780 [D loss: 0.693121, acc.: 52.15%] [G loss: 0.696606]
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1781 [D loss: 0.692679, acc.: 52.54%] [G loss: 0.694673]
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1782 [D loss: 0.692944, acc.: 50.59%] [G loss: 0.695163]
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1783 [D loss: 0.693039, acc.: 52.73%] [G loss: 0.695999]
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1784 [D loss: 0.693637, acc.: 49.02%] [G loss: 0.694703]
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1785 [D loss: 0.692764, acc.: 50.78%] [G loss: 0.694188]
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1786 [D loss: 0.693746, acc.: 48.24%] [G loss: 0.695158]
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1787 [D loss: 0.694344, acc.: 48.83%] [G loss: 0.693853]
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1788 [D loss: 0.694099, acc.: 46.29%] [G loss: 0.694438]
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1789 [D loss: 0.693791, acc.: 49.61%] [G loss: 0.694881]
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1790 [D loss: 0.693477, acc.: 51.56%] [G loss: 0.694056]
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1791 [D loss: 0.694458, acc.: 49.02%] [G loss: 0.694909]
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1792 [D loss: 0.693856, acc.: 50.39%] [G loss: 0.695084]
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1793 [D loss: 0.693365, acc.: 50.00%] [G loss: 0.694595]
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1794 [D loss: 0.693036, acc.: 51.95%] [G loss: 0.694387]
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1795 [D loss: 0.692985, acc.: 51.17%] [G loss: 0.695911]
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1796 [D loss: 0.694089, acc.: 46.88%] [G loss: 0.695945]
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1797 [D loss: 0.693287, acc.: 48.44%] [G loss: 0.696631]
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1798 [D loss: 0.693847, acc.: 47.27%] [G loss: 0.694565]
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1799 [D loss: 0.693474, acc.: 50.20%] [G loss: 0.694544]
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1800 [D loss: 0.693558, acc.: 49.41%] [G loss: 0.695026]
1/1 [==============================] - 0s 15ms/step
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1801 [D loss: 0.694474, acc.: 47.46%] [G loss: 0.695597]
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1802 [D loss: 0.692154, acc.: 52.54%] [G loss: 0.693943]
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1803 [D loss: 0.692360, acc.: 52.93%] [G loss: 0.695105]
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1804 [D loss: 0.692023, acc.: 53.32%] [G loss: 0.695362]
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1805 [D loss: 0.694272, acc.: 47.66%] [G loss: 0.697133]
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1806 [D loss: 0.692743, acc.: 51.76%] [G loss: 0.694041]
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1807 [D loss: 0.692805, acc.: 52.34%] [G loss: 0.693348]
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1808 [D loss: 0.693519, acc.: 49.61%] [G loss: 0.694159]
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1809 [D loss: 0.693172, acc.: 48.63%] [G loss: 0.693309]
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1810 [D loss: 0.692743, acc.: 50.39%] [G loss: 0.693574]
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1811 [D loss: 0.693177, acc.: 48.44%] [G loss: 0.694778]
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1812 [D loss: 0.693373, acc.: 52.15%] [G loss: 0.693823]
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1813 [D loss: 0.693916, acc.: 49.41%] [G loss: 0.695081]
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1814 [D loss: 0.694263, acc.: 49.22%] [G loss: 0.695661]
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1815 [D loss: 0.693392, acc.: 51.76%] [G loss: 0.692737]
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1816 [D loss: 0.693548, acc.: 50.59%] [G loss: 0.694049]
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1817 [D loss: 0.693252, acc.: 52.34%] [G loss: 0.696060]
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1818 [D loss: 0.693856, acc.: 49.41%] [G loss: 0.695300]
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1819 [D loss: 0.693558, acc.: 48.44%] [G loss: 0.694890]
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1820 [D loss: 0.692413, acc.: 52.15%] [G loss: 0.695217]
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1821 [D loss: 0.693072, acc.: 51.37%] [G loss: 0.695800]
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1822 [D loss: 0.693140, acc.: 52.73%] [G loss: 0.696647]
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1823 [D loss: 0.694015, acc.: 48.63%] [G loss: 0.696067]
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1824 [D loss: 0.693697, acc.: 48.05%] [G loss: 0.696883]
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1825 [D loss: 0.693290, acc.: 49.02%] [G loss: 0.696105]
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1826 [D loss: 0.693970, acc.: 48.24%] [G loss: 0.696004]
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1827 [D loss: 0.691981, acc.: 52.54%] [G loss: 0.698023]
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1828 [D loss: 0.693339, acc.: 48.24%] [G loss: 0.697631]
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1829 [D loss: 0.693002, acc.: 49.22%] [G loss: 0.695646]
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1830 [D loss: 0.693132, acc.: 47.66%] [G loss: 0.694066]
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1831 [D loss: 0.693192, acc.: 48.44%] [G loss: 0.694139]
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1832 [D loss: 0.693199, acc.: 49.61%] [G loss: 0.695528]
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1833 [D loss: 0.692269, acc.: 53.12%] [G loss: 0.695145]
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1834 [D loss: 0.693569, acc.: 50.39%] [G loss: 0.694883]
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1835 [D loss: 0.694561, acc.: 45.90%] [G loss: 0.695489]
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1836 [D loss: 0.693397, acc.: 50.98%] [G loss: 0.695066]
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1837 [D loss: 0.692299, acc.: 51.56%] [G loss: 0.695141]
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1838 [D loss: 0.693538, acc.: 48.63%] [G loss: 0.694487]
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1839 [D loss: 0.692903, acc.: 49.80%] [G loss: 0.693633]
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1840 [D loss: 0.693525, acc.: 51.37%] [G loss: 0.694712]
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1841 [D loss: 0.693191, acc.: 51.37%] [G loss: 0.696054]
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1842 [D loss: 0.693574, acc.: 48.44%] [G loss: 0.694605]
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1843 [D loss: 0.693203, acc.: 50.59%] [G loss: 0.696817]
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1844 [D loss: 0.691309, acc.: 57.23%] [G loss: 0.696283]
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1845 [D loss: 0.693837, acc.: 48.05%] [G loss: 0.695366]
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1846 [D loss: 0.692858, acc.: 50.00%] [G loss: 0.696638]
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1847 [D loss: 0.692113, acc.: 50.98%] [G loss: 0.695189]
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1848 [D loss: 0.692984, acc.: 50.39%] [G loss: 0.696228]
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1849 [D loss: 0.694179, acc.: 46.68%] [G loss: 0.693782]
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1850 [D loss: 0.692587, acc.: 48.83%] [G loss: 0.695327]
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1851 [D loss: 0.692523, acc.: 50.39%] [G loss: 0.695722]
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1852 [D loss: 0.693714, acc.: 49.22%] [G loss: 0.697165]
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1853 [D loss: 0.693817, acc.: 46.88%] [G loss: 0.695658]
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1854 [D loss: 0.693756, acc.: 47.66%] [G loss: 0.697003]
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1855 [D loss: 0.692983, acc.: 50.59%] [G loss: 0.694592]
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1856 [D loss: 0.692678, acc.: 52.93%] [G loss: 0.695994]
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1857 [D loss: 0.693220, acc.: 48.24%] [G loss: 0.694139]
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1858 [D loss: 0.694126, acc.: 50.20%] [G loss: 0.695282]
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1859 [D loss: 0.693392, acc.: 51.56%] [G loss: 0.695619]
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1860 [D loss: 0.693391, acc.: 49.41%] [G loss: 0.694900]
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1861 [D loss: 0.694551, acc.: 45.51%] [G loss: 0.695442]
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1862 [D loss: 0.693498, acc.: 48.83%] [G loss: 0.694747]
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1863 [D loss: 0.693840, acc.: 46.29%] [G loss: 0.694342]
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1864 [D loss: 0.692787, acc.: 48.83%] [G loss: 0.695269]
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1865 [D loss: 0.694109, acc.: 45.90%] [G loss: 0.693379]
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1866 [D loss: 0.694199, acc.: 47.66%] [G loss: 0.693472]
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1867 [D loss: 0.694258, acc.: 46.68%] [G loss: 0.693005]
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1868 [D loss: 0.692913, acc.: 50.78%] [G loss: 0.696203]
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1869 [D loss: 0.693324, acc.: 48.24%] [G loss: 0.695013]
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1870 [D loss: 0.692397, acc.: 51.56%] [G loss: 0.693118]
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1871 [D loss: 0.694163, acc.: 46.88%] [G loss: 0.692318]
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1872 [D loss: 0.693636, acc.: 50.00%] [G loss: 0.690978]
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1873 [D loss: 0.692400, acc.: 50.98%] [G loss: 0.692359]
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1874 [D loss: 0.693998, acc.: 48.44%] [G loss: 0.693302]
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1875 [D loss: 0.693760, acc.: 50.39%] [G loss: 0.695188]
8/8 [==============================] - 0s 2ms/step
1876 [D loss: 0.693161, acc.: 49.80%] [G loss: 0.694139]
8/8 [==============================] - 0s 2ms/step
1877 [D loss: 0.692846, acc.: 53.71%] [G loss: 0.695848]
8/8 [==============================] - 0s 2ms/step
1878 [D loss: 0.692610, acc.: 49.61%] [G loss: 0.693928]
8/8 [==============================] - 0s 2ms/step
1879 [D loss: 0.692871, acc.: 52.54%] [G loss: 0.694016]
8/8 [==============================] - 0s 2ms/step
1880 [D loss: 0.691635, acc.: 53.52%] [G loss: 0.694347]
8/8 [==============================] - 0s 2ms/step
1881 [D loss: 0.693030, acc.: 50.20%] [G loss: 0.693159]
8/8 [==============================] - 0s 2ms/step
1882 [D loss: 0.692212, acc.: 53.32%] [G loss: 0.694351]
8/8 [==============================] - 0s 2ms/step
1883 [D loss: 0.692898, acc.: 49.80%] [G loss: 0.693585]
8/8 [==============================] - 0s 2ms/step
1884 [D loss: 0.692784, acc.: 51.17%] [G loss: 0.695269]
8/8 [==============================] - 0s 2ms/step
1885 [D loss: 0.694060, acc.: 49.61%] [G loss: 0.695093]
8/8 [==============================] - 0s 2ms/step
1886 [D loss: 0.692910, acc.: 51.17%] [G loss: 0.694368]
8/8 [==============================] - 0s 2ms/step
1887 [D loss: 0.693009, acc.: 51.17%] [G loss: 0.694487]
8/8 [==============================] - 0s 2ms/step
1888 [D loss: 0.693265, acc.: 51.17%] [G loss: 0.694195]
8/8 [==============================] - 0s 2ms/step
1889 [D loss: 0.692553, acc.: 50.78%] [G loss: 0.696002]
8/8 [==============================] - 0s 2ms/step
1890 [D loss: 0.694115, acc.: 51.17%] [G loss: 0.694798]
8/8 [==============================] - 0s 2ms/step
1891 [D loss: 0.693255, acc.: 51.17%] [G loss: 0.696437]
8/8 [==============================] - 0s 2ms/step
1892 [D loss: 0.693050, acc.: 49.80%] [G loss: 0.694545]
8/8 [==============================] - 0s 2ms/step
1893 [D loss: 0.693634, acc.: 48.83%] [G loss: 0.695469]
8/8 [==============================] - 0s 2ms/step
1894 [D loss: 0.694046, acc.: 48.24%] [G loss: 0.694515]
8/8 [==============================] - 0s 2ms/step
1895 [D loss: 0.692816, acc.: 48.63%] [G loss: 0.694328]
8/8 [==============================] - 0s 2ms/step
1896 [D loss: 0.694999, acc.: 44.92%] [G loss: 0.693771]
8/8 [==============================] - 0s 2ms/step
1897 [D loss: 0.692279, acc.: 53.52%] [G loss: 0.694003]
8/8 [==============================] - 0s 2ms/step
1898 [D loss: 0.693773, acc.: 50.20%] [G loss: 0.694539]
8/8 [==============================] - 0s 2ms/step
1899 [D loss: 0.694224, acc.: 47.85%] [G loss: 0.694219]
8/8 [==============================] - 0s 2ms/step
1900 [D loss: 0.694040, acc.: 49.61%] [G loss: 0.694050]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
1901 [D loss: 0.693017, acc.: 48.44%] [G loss: 0.696027]
8/8 [==============================] - 0s 2ms/step
1902 [D loss: 0.692382, acc.: 51.17%] [G loss: 0.693173]
8/8 [==============================] - 0s 2ms/step
1903 [D loss: 0.694175, acc.: 49.61%] [G loss: 0.695369]
8/8 [==============================] - 0s 2ms/step
1904 [D loss: 0.693013, acc.: 50.20%] [G loss: 0.695469]
8/8 [==============================] - 0s 2ms/step
1905 [D loss: 0.692550, acc.: 50.98%] [G loss: 0.694826]
8/8 [==============================] - 0s 2ms/step
1906 [D loss: 0.693225, acc.: 49.41%] [G loss: 0.694871]
8/8 [==============================] - 0s 2ms/step
1907 [D loss: 0.693880, acc.: 46.68%] [G loss: 0.695362]
8/8 [==============================] - 0s 2ms/step
1908 [D loss: 0.693096, acc.: 50.39%] [G loss: 0.696047]
8/8 [==============================] - 0s 2ms/step
1909 [D loss: 0.694486, acc.: 45.90%] [G loss: 0.694183]
8/8 [==============================] - 0s 2ms/step
1910 [D loss: 0.693923, acc.: 47.85%] [G loss: 0.696016]
8/8 [==============================] - 0s 2ms/step
1911 [D loss: 0.694507, acc.: 48.44%] [G loss: 0.695966]
8/8 [==============================] - 0s 2ms/step
1912 [D loss: 0.695005, acc.: 44.14%] [G loss: 0.692760]
8/8 [==============================] - 0s 2ms/step
1913 [D loss: 0.694045, acc.: 47.66%] [G loss: 0.697698]
8/8 [==============================] - 0s 2ms/step
1914 [D loss: 0.693283, acc.: 50.78%] [G loss: 0.695468]
8/8 [==============================] - 0s 2ms/step
1915 [D loss: 0.693640, acc.: 48.83%] [G loss: 0.695212]
8/8 [==============================] - 0s 2ms/step
1916 [D loss: 0.693363, acc.: 49.22%] [G loss: 0.694647]
8/8 [==============================] - 0s 2ms/step
1917 [D loss: 0.693494, acc.: 50.59%] [G loss: 0.694404]
8/8 [==============================] - 0s 2ms/step
1918 [D loss: 0.693661, acc.: 50.39%] [G loss: 0.693972]
8/8 [==============================] - 0s 2ms/step
1919 [D loss: 0.693658, acc.: 48.05%] [G loss: 0.695140]
8/8 [==============================] - 0s 2ms/step
1920 [D loss: 0.692538, acc.: 51.95%] [G loss: 0.693923]
8/8 [==============================] - 0s 2ms/step
1921 [D loss: 0.693419, acc.: 47.66%] [G loss: 0.692660]
8/8 [==============================] - 0s 2ms/step
1922 [D loss: 0.692681, acc.: 50.39%] [G loss: 0.694689]
8/8 [==============================] - 0s 2ms/step
1923 [D loss: 0.693883, acc.: 46.88%] [G loss: 0.695518]
8/8 [==============================] - 0s 2ms/step
1924 [D loss: 0.692722, acc.: 53.91%] [G loss: 0.694843]
8/8 [==============================] - 0s 2ms/step
1925 [D loss: 0.693322, acc.: 52.93%] [G loss: 0.695361]
8/8 [==============================] - 0s 2ms/step
1926 [D loss: 0.694677, acc.: 43.95%] [G loss: 0.694409]
8/8 [==============================] - 0s 2ms/step
1927 [D loss: 0.693340, acc.: 51.76%] [G loss: 0.695093]
8/8 [==============================] - 0s 2ms/step
1928 [D loss: 0.692785, acc.: 54.10%] [G loss: 0.695957]
8/8 [==============================] - 0s 2ms/step
1929 [D loss: 0.694188, acc.: 47.85%] [G loss: 0.695118]
8/8 [==============================] - 0s 2ms/step
1930 [D loss: 0.693140, acc.: 47.07%] [G loss: 0.694849]
8/8 [==============================] - 0s 2ms/step
1931 [D loss: 0.693195, acc.: 51.37%] [G loss: 0.695052]
8/8 [==============================] - 0s 2ms/step
1932 [D loss: 0.692246, acc.: 53.52%] [G loss: 0.693225]
8/8 [==============================] - 0s 2ms/step
1933 [D loss: 0.692535, acc.: 52.73%] [G loss: 0.694348]
8/8 [==============================] - 0s 2ms/step
1934 [D loss: 0.693936, acc.: 49.80%] [G loss: 0.693652]
8/8 [==============================] - 0s 2ms/step
1935 [D loss: 0.693258, acc.: 49.61%] [G loss: 0.694244]
8/8 [==============================] - 0s 2ms/step
1936 [D loss: 0.693229, acc.: 49.22%] [G loss: 0.692546]
8/8 [==============================] - 0s 2ms/step
1937 [D loss: 0.694946, acc.: 45.31%] [G loss: 0.695650]
8/8 [==============================] - 0s 2ms/step
1938 [D loss: 0.692861, acc.: 50.59%] [G loss: 0.694227]
8/8 [==============================] - 0s 2ms/step
1939 [D loss: 0.694082, acc.: 49.80%] [G loss: 0.695736]
8/8 [==============================] - 0s 2ms/step
1940 [D loss: 0.694397, acc.: 48.83%] [G loss: 0.695640]
8/8 [==============================] - 0s 2ms/step
1941 [D loss: 0.694182, acc.: 47.66%] [G loss: 0.695615]
8/8 [==============================] - 0s 3ms/step
1942 [D loss: 0.693195, acc.: 48.44%] [G loss: 0.694264]
8/8 [==============================] - 0s 2ms/step
1943 [D loss: 0.693766, acc.: 48.63%] [G loss: 0.692868]
8/8 [==============================] - 0s 2ms/step
1944 [D loss: 0.693621, acc.: 49.41%] [G loss: 0.693849]
8/8 [==============================] - 0s 2ms/step
1945 [D loss: 0.692473, acc.: 50.78%] [G loss: 0.694631]
8/8 [==============================] - 0s 2ms/step
1946 [D loss: 0.693267, acc.: 47.85%] [G loss: 0.695518]
8/8 [==============================] - 0s 2ms/step
1947 [D loss: 0.693649, acc.: 50.59%] [G loss: 0.695263]
8/8 [==============================] - 0s 2ms/step
1948 [D loss: 0.693204, acc.: 49.41%] [G loss: 0.694742]
8/8 [==============================] - 0s 2ms/step
1949 [D loss: 0.694109, acc.: 46.48%] [G loss: 0.694635]
8/8 [==============================] - 0s 2ms/step
1950 [D loss: 0.692954, acc.: 54.10%] [G loss: 0.695986]
8/8 [==============================] - 0s 2ms/step
1951 [D loss: 0.691640, acc.: 55.08%] [G loss: 0.693680]
8/8 [==============================] - 0s 2ms/step
1952 [D loss: 0.693782, acc.: 48.24%] [G loss: 0.693496]
8/8 [==============================] - 0s 2ms/step
1953 [D loss: 0.694222, acc.: 48.83%] [G loss: 0.695472]
8/8 [==============================] - 0s 2ms/step
1954 [D loss: 0.693643, acc.: 49.02%] [G loss: 0.694517]
8/8 [==============================] - 0s 2ms/step
1955 [D loss: 0.692644, acc.: 53.52%] [G loss: 0.694517]
8/8 [==============================] - 0s 2ms/step
1956 [D loss: 0.694113, acc.: 49.80%] [G loss: 0.695559]
8/8 [==============================] - 0s 2ms/step
1957 [D loss: 0.692563, acc.: 50.59%] [G loss: 0.695156]
8/8 [==============================] - 0s 2ms/step
1958 [D loss: 0.692687, acc.: 52.34%] [G loss: 0.695259]
8/8 [==============================] - 0s 2ms/step
1959 [D loss: 0.693415, acc.: 48.63%] [G loss: 0.693414]
8/8 [==============================] - 0s 2ms/step
1960 [D loss: 0.694089, acc.: 48.63%] [G loss: 0.695084]
8/8 [==============================] - 0s 2ms/step
1961 [D loss: 0.693639, acc.: 48.05%] [G loss: 0.693442]
8/8 [==============================] - 0s 2ms/step
1962 [D loss: 0.692233, acc.: 50.78%] [G loss: 0.695625]
8/8 [==============================] - 0s 2ms/step
1963 [D loss: 0.693213, acc.: 51.76%] [G loss: 0.694450]
8/8 [==============================] - 0s 2ms/step
1964 [D loss: 0.692959, acc.: 50.78%] [G loss: 0.695152]
8/8 [==============================] - 0s 2ms/step
1965 [D loss: 0.693408, acc.: 49.41%] [G loss: 0.694573]
8/8 [==============================] - 0s 2ms/step
1966 [D loss: 0.693678, acc.: 49.41%] [G loss: 0.694363]
8/8 [==============================] - 0s 2ms/step
1967 [D loss: 0.693316, acc.: 49.22%] [G loss: 0.694301]
8/8 [==============================] - 0s 2ms/step
1968 [D loss: 0.692855, acc.: 51.95%] [G loss: 0.695479]
8/8 [==============================] - 0s 2ms/step
1969 [D loss: 0.693639, acc.: 51.17%] [G loss: 0.694284]
8/8 [==============================] - 0s 2ms/step
1970 [D loss: 0.694209, acc.: 48.44%] [G loss: 0.695464]
8/8 [==============================] - 0s 2ms/step
1971 [D loss: 0.692304, acc.: 53.52%] [G loss: 0.694475]
8/8 [==============================] - 0s 2ms/step
1972 [D loss: 0.692950, acc.: 49.61%] [G loss: 0.692764]
8/8 [==============================] - 0s 2ms/step
1973 [D loss: 0.694645, acc.: 45.90%] [G loss: 0.693923]
8/8 [==============================] - 0s 2ms/step
1974 [D loss: 0.693101, acc.: 51.37%] [G loss: 0.696204]
8/8 [==============================] - 0s 2ms/step
1975 [D loss: 0.693652, acc.: 49.22%] [G loss: 0.693067]
8/8 [==============================] - 0s 2ms/step
1976 [D loss: 0.693404, acc.: 50.98%] [G loss: 0.693459]
8/8 [==============================] - 0s 2ms/step
1977 [D loss: 0.693952, acc.: 48.83%] [G loss: 0.692450]
8/8 [==============================] - 0s 2ms/step
1978 [D loss: 0.693937, acc.: 49.22%] [G loss: 0.694126]
8/8 [==============================] - 0s 2ms/step
1979 [D loss: 0.692957, acc.: 51.37%] [G loss: 0.693667]
8/8 [==============================] - 0s 2ms/step
1980 [D loss: 0.693215, acc.: 49.02%] [G loss: 0.691903]
8/8 [==============================] - 0s 2ms/step
1981 [D loss: 0.693511, acc.: 50.78%] [G loss: 0.693241]
8/8 [==============================] - 0s 2ms/step
1982 [D loss: 0.693571, acc.: 49.22%] [G loss: 0.693839]
8/8 [==============================] - 0s 2ms/step
1983 [D loss: 0.693491, acc.: 50.98%] [G loss: 0.692883]
8/8 [==============================] - 0s 2ms/step
1984 [D loss: 0.693515, acc.: 48.83%] [G loss: 0.693348]
8/8 [==============================] - 0s 2ms/step
1985 [D loss: 0.693220, acc.: 48.44%] [G loss: 0.692345]
8/8 [==============================] - 0s 2ms/step
1986 [D loss: 0.694805, acc.: 44.34%] [G loss: 0.693706]
8/8 [==============================] - 0s 2ms/step
1987 [D loss: 0.693465, acc.: 50.59%] [G loss: 0.692838]
8/8 [==============================] - 0s 2ms/step
1988 [D loss: 0.693059, acc.: 51.95%] [G loss: 0.694524]
8/8 [==============================] - 0s 2ms/step
1989 [D loss: 0.692867, acc.: 50.39%] [G loss: 0.692505]
8/8 [==============================] - 0s 2ms/step
1990 [D loss: 0.693618, acc.: 49.02%] [G loss: 0.693308]
8/8 [==============================] - 0s 2ms/step
1991 [D loss: 0.692209, acc.: 52.15%] [G loss: 0.693283]
8/8 [==============================] - 0s 2ms/step
1992 [D loss: 0.693135, acc.: 50.39%] [G loss: 0.694204]
8/8 [==============================] - 0s 2ms/step
1993 [D loss: 0.693307, acc.: 49.61%] [G loss: 0.694665]
8/8 [==============================] - 0s 2ms/step
1994 [D loss: 0.693168, acc.: 51.17%] [G loss: 0.695022]
8/8 [==============================] - 0s 2ms/step
1995 [D loss: 0.693251, acc.: 50.39%] [G loss: 0.692745]
8/8 [==============================] - 0s 2ms/step
1996 [D loss: 0.694288, acc.: 45.70%] [G loss: 0.692746]
8/8 [==============================] - 0s 2ms/step
1997 [D loss: 0.693657, acc.: 50.00%] [G loss: 0.693599]
8/8 [==============================] - 0s 2ms/step
1998 [D loss: 0.692507, acc.: 54.30%] [G loss: 0.694557]
8/8 [==============================] - 0s 2ms/step
1999 [D loss: 0.694850, acc.: 46.09%] [G loss: 0.692736]
8/8 [==============================] - 0s 2ms/step
2000 [D loss: 0.694191, acc.: 47.07%] [G loss: 0.692414]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
2001 [D loss: 0.693245, acc.: 50.98%] [G loss: 0.693832]
8/8 [==============================] - 0s 2ms/step
2002 [D loss: 0.693364, acc.: 50.20%] [G loss: 0.691801]
8/8 [==============================] - 0s 2ms/step
2003 [D loss: 0.694144, acc.: 47.85%] [G loss: 0.692412]
8/8 [==============================] - 0s 2ms/step
2004 [D loss: 0.693602, acc.: 47.46%] [G loss: 0.694327]
8/8 [==============================] - 0s 2ms/step
2005 [D loss: 0.693653, acc.: 48.24%] [G loss: 0.695620]
8/8 [==============================] - 0s 2ms/step
2006 [D loss: 0.693700, acc.: 48.63%] [G loss: 0.694861]
8/8 [==============================] - 0s 2ms/step
2007 [D loss: 0.694522, acc.: 46.68%] [G loss: 0.695875]
8/8 [==============================] - 0s 2ms/step
2008 [D loss: 0.695079, acc.: 44.92%] [G loss: 0.693774]
8/8 [==============================] - 0s 2ms/step
2009 [D loss: 0.693349, acc.: 49.22%] [G loss: 0.693692]
8/8 [==============================] - 0s 2ms/step
2010 [D loss: 0.692757, acc.: 49.61%] [G loss: 0.696553]
8/8 [==============================] - 0s 2ms/step
2011 [D loss: 0.693567, acc.: 51.17%] [G loss: 0.694777]
8/8 [==============================] - 0s 2ms/step
2012 [D loss: 0.692930, acc.: 50.98%] [G loss: 0.695598]
8/8 [==============================] - 0s 2ms/step
2013 [D loss: 0.693629, acc.: 48.05%] [G loss: 0.696183]
8/8 [==============================] - 0s 2ms/step
2014 [D loss: 0.692749, acc.: 52.54%] [G loss: 0.696267]
8/8 [==============================] - 0s 2ms/step
2015 [D loss: 0.693821, acc.: 47.46%] [G loss: 0.694613]
8/8 [==============================] - 0s 2ms/step
2016 [D loss: 0.693122, acc.: 50.00%] [G loss: 0.696542]
8/8 [==============================] - 0s 3ms/step
2017 [D loss: 0.692811, acc.: 52.34%] [G loss: 0.696264]
8/8 [==============================] - 0s 2ms/step
2018 [D loss: 0.694099, acc.: 49.02%] [G loss: 0.694143]
8/8 [==============================] - 0s 2ms/step
2019 [D loss: 0.692678, acc.: 51.56%] [G loss: 0.694427]
8/8 [==============================] - 0s 2ms/step
2020 [D loss: 0.693798, acc.: 46.68%] [G loss: 0.696174]
8/8 [==============================] - 0s 2ms/step
2021 [D loss: 0.693446, acc.: 48.63%] [G loss: 0.696079]
8/8 [==============================] - 0s 2ms/step
2022 [D loss: 0.693514, acc.: 48.83%] [G loss: 0.694894]
8/8 [==============================] - 0s 2ms/step
2023 [D loss: 0.694260, acc.: 45.70%] [G loss: 0.695665]
8/8 [==============================] - 0s 2ms/step
2024 [D loss: 0.693071, acc.: 52.54%] [G loss: 0.695116]
8/8 [==============================] - 0s 2ms/step
2025 [D loss: 0.692643, acc.: 52.34%] [G loss: 0.696139]
8/8 [==============================] - 0s 2ms/step
2026 [D loss: 0.693187, acc.: 50.20%] [G loss: 0.694644]
8/8 [==============================] - 0s 2ms/step
2027 [D loss: 0.692992, acc.: 50.20%] [G loss: 0.694201]
8/8 [==============================] - 0s 2ms/step
2028 [D loss: 0.692700, acc.: 49.41%] [G loss: 0.695331]
8/8 [==============================] - 0s 2ms/step
2029 [D loss: 0.693231, acc.: 50.59%] [G loss: 0.693487]
8/8 [==============================] - 0s 2ms/step
2030 [D loss: 0.693552, acc.: 49.22%] [G loss: 0.694416]
8/8 [==============================] - 0s 2ms/step
2031 [D loss: 0.693607, acc.: 50.00%] [G loss: 0.692748]
8/8 [==============================] - 0s 2ms/step
2032 [D loss: 0.693863, acc.: 48.83%] [G loss: 0.694057]
8/8 [==============================] - 0s 2ms/step
2033 [D loss: 0.692376, acc.: 50.39%] [G loss: 0.694878]
8/8 [==============================] - 0s 2ms/step
2034 [D loss: 0.693282, acc.: 49.41%] [G loss: 0.694873]
8/8 [==============================] - 0s 2ms/step
2035 [D loss: 0.693608, acc.: 46.68%] [G loss: 0.693957]
8/8 [==============================] - 0s 2ms/step
2036 [D loss: 0.691951, acc.: 55.47%] [G loss: 0.694556]
8/8 [==============================] - 0s 2ms/step
2037 [D loss: 0.693834, acc.: 48.83%] [G loss: 0.693212]
8/8 [==============================] - 0s 2ms/step
2038 [D loss: 0.693307, acc.: 50.20%] [G loss: 0.694234]
8/8 [==============================] - 0s 2ms/step
2039 [D loss: 0.694300, acc.: 48.05%] [G loss: 0.693421]
8/8 [==============================] - 0s 2ms/step
2040 [D loss: 0.693119, acc.: 49.80%] [G loss: 0.692341]
8/8 [==============================] - 0s 2ms/step
2041 [D loss: 0.693343, acc.: 49.02%] [G loss: 0.694025]
8/8 [==============================] - 0s 2ms/step
2042 [D loss: 0.692642, acc.: 50.78%] [G loss: 0.692977]
8/8 [==============================] - 0s 2ms/step
2043 [D loss: 0.693424, acc.: 47.85%] [G loss: 0.694276]
8/8 [==============================] - 0s 2ms/step
2044 [D loss: 0.693226, acc.: 49.41%] [G loss: 0.693723]
8/8 [==============================] - 0s 2ms/step
2045 [D loss: 0.694171, acc.: 47.07%] [G loss: 0.694313]
8/8 [==============================] - 0s 2ms/step
2046 [D loss: 0.694170, acc.: 47.27%] [G loss: 0.692595]
8/8 [==============================] - 0s 2ms/step
2047 [D loss: 0.692245, acc.: 53.52%] [G loss: 0.692911]
8/8 [==============================] - 0s 2ms/step
2048 [D loss: 0.693286, acc.: 48.24%] [G loss: 0.693994]
8/8 [==============================] - 0s 2ms/step
2049 [D loss: 0.694258, acc.: 48.83%] [G loss: 0.694409]
8/8 [==============================] - 0s 2ms/step
2050 [D loss: 0.692960, acc.: 48.83%] [G loss: 0.693090]
8/8 [==============================] - 0s 2ms/step
2051 [D loss: 0.692610, acc.: 50.78%] [G loss: 0.693815]
8/8 [==============================] - 0s 2ms/step
2052 [D loss: 0.693273, acc.: 50.00%] [G loss: 0.693099]
8/8 [==============================] - 0s 2ms/step
2053 [D loss: 0.693808, acc.: 48.44%] [G loss: 0.694598]
8/8 [==============================] - 0s 2ms/step
2054 [D loss: 0.693866, acc.: 49.80%] [G loss: 0.694505]
8/8 [==============================] - 0s 2ms/step
2055 [D loss: 0.691638, acc.: 54.88%] [G loss: 0.692853]
8/8 [==============================] - 0s 2ms/step
2056 [D loss: 0.693448, acc.: 50.98%] [G loss: 0.695038]
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2057 [D loss: 0.692553, acc.: 51.56%] [G loss: 0.692536]
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2058 [D loss: 0.693161, acc.: 50.98%] [G loss: 0.693784]
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2059 [D loss: 0.694007, acc.: 47.85%] [G loss: 0.693824]
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2060 [D loss: 0.693067, acc.: 50.20%] [G loss: 0.695419]
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2061 [D loss: 0.692747, acc.: 54.49%] [G loss: 0.693937]
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2062 [D loss: 0.692929, acc.: 49.02%] [G loss: 0.696407]
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2063 [D loss: 0.691844, acc.: 55.86%] [G loss: 0.692784]
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2064 [D loss: 0.693719, acc.: 47.85%] [G loss: 0.693431]
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2065 [D loss: 0.693778, acc.: 50.20%] [G loss: 0.693553]
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2066 [D loss: 0.693861, acc.: 50.39%] [G loss: 0.695059]
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2067 [D loss: 0.692945, acc.: 47.46%] [G loss: 0.695317]
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2068 [D loss: 0.693481, acc.: 48.05%] [G loss: 0.693996]
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2069 [D loss: 0.693109, acc.: 51.56%] [G loss: 0.695035]
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2070 [D loss: 0.693207, acc.: 51.37%] [G loss: 0.694644]
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2071 [D loss: 0.693432, acc.: 50.39%] [G loss: 0.694543]
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2072 [D loss: 0.693123, acc.: 48.83%] [G loss: 0.694692]
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2073 [D loss: 0.693678, acc.: 49.22%] [G loss: 0.694564]
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2074 [D loss: 0.693425, acc.: 50.20%] [G loss: 0.694193]
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2075 [D loss: 0.693550, acc.: 49.22%] [G loss: 0.695770]
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2076 [D loss: 0.692683, acc.: 50.20%] [G loss: 0.695053]
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2077 [D loss: 0.691450, acc.: 53.91%] [G loss: 0.694669]
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2078 [D loss: 0.694119, acc.: 49.02%] [G loss: 0.694038]
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2079 [D loss: 0.694363, acc.: 45.70%] [G loss: 0.693976]
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2080 [D loss: 0.693063, acc.: 50.39%] [G loss: 0.692557]
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2081 [D loss: 0.692975, acc.: 50.98%] [G loss: 0.691787]
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2082 [D loss: 0.693608, acc.: 48.83%] [G loss: 0.692859]
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2083 [D loss: 0.693455, acc.: 46.68%] [G loss: 0.691997]
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2084 [D loss: 0.694095, acc.: 46.09%] [G loss: 0.693544]
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2085 [D loss: 0.693084, acc.: 49.80%] [G loss: 0.691115]
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2086 [D loss: 0.693825, acc.: 49.61%] [G loss: 0.691507]
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2087 [D loss: 0.693249, acc.: 49.61%] [G loss: 0.691054]
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2088 [D loss: 0.694907, acc.: 45.12%] [G loss: 0.691049]
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2089 [D loss: 0.693284, acc.: 50.20%] [G loss: 0.693277]
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2090 [D loss: 0.693240, acc.: 50.00%] [G loss: 0.693516]
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2091 [D loss: 0.693107, acc.: 50.59%] [G loss: 0.691418]
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2092 [D loss: 0.693160, acc.: 50.78%] [G loss: 0.692582]
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2093 [D loss: 0.693796, acc.: 48.05%] [G loss: 0.693703]
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2094 [D loss: 0.693294, acc.: 51.37%] [G loss: 0.692069]
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2095 [D loss: 0.692865, acc.: 51.17%] [G loss: 0.691914]
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2096 [D loss: 0.693277, acc.: 49.41%] [G loss: 0.694808]
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2097 [D loss: 0.693304, acc.: 49.41%] [G loss: 0.693085]
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2098 [D loss: 0.694348, acc.: 45.51%] [G loss: 0.694059]
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2099 [D loss: 0.693360, acc.: 50.20%] [G loss: 0.693402]
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2100 [D loss: 0.693030, acc.: 51.17%] [G loss: 0.693447]
1/1 [==============================] - 0s 15ms/step
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2101 [D loss: 0.694364, acc.: 46.48%] [G loss: 0.693612]
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2102 [D loss: 0.692912, acc.: 52.15%] [G loss: 0.694369]
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2103 [D loss: 0.692666, acc.: 51.17%] [G loss: 0.693272]
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2104 [D loss: 0.692578, acc.: 53.71%] [G loss: 0.694521]
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2105 [D loss: 0.693537, acc.: 46.48%] [G loss: 0.695122]
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2106 [D loss: 0.693702, acc.: 48.44%] [G loss: 0.693651]
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2107 [D loss: 0.693283, acc.: 50.98%] [G loss: 0.691839]
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2108 [D loss: 0.692951, acc.: 50.39%] [G loss: 0.693984]
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2109 [D loss: 0.694199, acc.: 47.27%] [G loss: 0.692429]
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2110 [D loss: 0.693002, acc.: 51.37%] [G loss: 0.692979]
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2111 [D loss: 0.693451, acc.: 50.00%] [G loss: 0.692262]
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2112 [D loss: 0.693261, acc.: 50.20%] [G loss: 0.691495]
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2113 [D loss: 0.693379, acc.: 49.80%] [G loss: 0.692902]
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2114 [D loss: 0.693649, acc.: 49.02%] [G loss: 0.692248]
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2115 [D loss: 0.693000, acc.: 50.78%] [G loss: 0.694693]
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2116 [D loss: 0.693961, acc.: 48.83%] [G loss: 0.690215]
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2117 [D loss: 0.692888, acc.: 56.64%] [G loss: 0.692666]
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2118 [D loss: 0.693207, acc.: 50.98%] [G loss: 0.692458]
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2119 [D loss: 0.693464, acc.: 50.39%] [G loss: 0.693393]
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2120 [D loss: 0.693091, acc.: 51.95%] [G loss: 0.692715]
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2121 [D loss: 0.693390, acc.: 51.56%] [G loss: 0.693200]
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2122 [D loss: 0.694092, acc.: 47.46%] [G loss: 0.693795]
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2123 [D loss: 0.694415, acc.: 46.68%] [G loss: 0.694907]
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2124 [D loss: 0.692943, acc.: 51.56%] [G loss: 0.693928]
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2125 [D loss: 0.694449, acc.: 46.48%] [G loss: 0.694397]
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2126 [D loss: 0.694208, acc.: 49.61%] [G loss: 0.694206]
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2127 [D loss: 0.693801, acc.: 49.80%] [G loss: 0.694626]
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2128 [D loss: 0.693025, acc.: 50.78%] [G loss: 0.694193]
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2129 [D loss: 0.692924, acc.: 51.37%] [G loss: 0.693967]
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2130 [D loss: 0.693238, acc.: 50.20%] [G loss: 0.694631]
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2131 [D loss: 0.694415, acc.: 46.48%] [G loss: 0.693888]
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2132 [D loss: 0.693719, acc.: 47.85%] [G loss: 0.695086]
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2133 [D loss: 0.692894, acc.: 52.54%] [G loss: 0.693950]
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2134 [D loss: 0.692623, acc.: 50.98%] [G loss: 0.693080]
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2135 [D loss: 0.693026, acc.: 52.54%] [G loss: 0.694456]
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2136 [D loss: 0.692611, acc.: 50.59%] [G loss: 0.693564]
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2137 [D loss: 0.693538, acc.: 51.17%] [G loss: 0.694456]
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2138 [D loss: 0.694110, acc.: 47.27%] [G loss: 0.694845]
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2139 [D loss: 0.692698, acc.: 53.32%] [G loss: 0.695468]
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2140 [D loss: 0.691956, acc.: 51.17%] [G loss: 0.694840]
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2141 [D loss: 0.693411, acc.: 50.59%] [G loss: 0.693787]
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2142 [D loss: 0.693293, acc.: 50.20%] [G loss: 0.694707]
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2143 [D loss: 0.694867, acc.: 45.12%] [G loss: 0.694300]
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2144 [D loss: 0.692770, acc.: 50.98%] [G loss: 0.694819]
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2145 [D loss: 0.692864, acc.: 49.41%] [G loss: 0.695211]
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2146 [D loss: 0.693364, acc.: 49.80%] [G loss: 0.696005]
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2147 [D loss: 0.693589, acc.: 49.80%] [G loss: 0.695693]
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2148 [D loss: 0.693190, acc.: 50.98%] [G loss: 0.696363]
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2149 [D loss: 0.691942, acc.: 52.54%] [G loss: 0.696709]
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2150 [D loss: 0.693827, acc.: 49.02%] [G loss: 0.695751]
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2151 [D loss: 0.693778, acc.: 46.68%] [G loss: 0.695874]
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2152 [D loss: 0.692989, acc.: 50.39%] [G loss: 0.695960]
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2153 [D loss: 0.691990, acc.: 53.52%] [G loss: 0.695764]
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2154 [D loss: 0.692858, acc.: 51.56%] [G loss: 0.694416]
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2155 [D loss: 0.693864, acc.: 49.61%] [G loss: 0.696316]
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2156 [D loss: 0.692960, acc.: 51.17%] [G loss: 0.696296]
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2157 [D loss: 0.693962, acc.: 46.48%] [G loss: 0.694469]
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2158 [D loss: 0.692601, acc.: 51.95%] [G loss: 0.695686]
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2159 [D loss: 0.694805, acc.: 46.88%] [G loss: 0.694348]
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2160 [D loss: 0.693822, acc.: 49.61%] [G loss: 0.694335]
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2161 [D loss: 0.693140, acc.: 50.20%] [G loss: 0.695291]
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2162 [D loss: 0.692813, acc.: 49.02%] [G loss: 0.692314]
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2163 [D loss: 0.693903, acc.: 47.46%] [G loss: 0.695939]
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2164 [D loss: 0.693846, acc.: 49.02%] [G loss: 0.694660]
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2165 [D loss: 0.693387, acc.: 49.41%] [G loss: 0.693322]
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2166 [D loss: 0.692669, acc.: 52.93%] [G loss: 0.694410]
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2167 [D loss: 0.693424, acc.: 50.39%] [G loss: 0.694348]
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2168 [D loss: 0.693683, acc.: 49.61%] [G loss: 0.696984]
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2169 [D loss: 0.693704, acc.: 49.22%] [G loss: 0.694138]
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2170 [D loss: 0.693334, acc.: 50.00%] [G loss: 0.694464]
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2171 [D loss: 0.693991, acc.: 51.95%] [G loss: 0.694458]
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2172 [D loss: 0.693740, acc.: 48.83%] [G loss: 0.695050]
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2173 [D loss: 0.693704, acc.: 47.66%] [G loss: 0.696367]
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2174 [D loss: 0.693674, acc.: 47.85%] [G loss: 0.694965]
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2175 [D loss: 0.693221, acc.: 52.34%] [G loss: 0.694268]
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2176 [D loss: 0.692851, acc.: 48.24%] [G loss: 0.695197]
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2177 [D loss: 0.693505, acc.: 51.17%] [G loss: 0.695403]
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2178 [D loss: 0.693975, acc.: 48.44%] [G loss: 0.694542]
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2179 [D loss: 0.693268, acc.: 48.05%] [G loss: 0.695639]
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2180 [D loss: 0.693821, acc.: 49.02%] [G loss: 0.692557]
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2181 [D loss: 0.692077, acc.: 52.54%] [G loss: 0.693288]
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2182 [D loss: 0.693568, acc.: 49.22%] [G loss: 0.694876]
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2183 [D loss: 0.693684, acc.: 50.59%] [G loss: 0.693047]
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2184 [D loss: 0.693393, acc.: 48.63%] [G loss: 0.694878]
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2185 [D loss: 0.693151, acc.: 48.63%] [G loss: 0.691854]
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2186 [D loss: 0.692112, acc.: 53.52%] [G loss: 0.693228]
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2187 [D loss: 0.694076, acc.: 47.46%] [G loss: 0.693431]
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2188 [D loss: 0.693212, acc.: 50.59%] [G loss: 0.692717]
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2189 [D loss: 0.693075, acc.: 51.17%] [G loss: 0.691870]
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2190 [D loss: 0.693587, acc.: 48.83%] [G loss: 0.693562]
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2191 [D loss: 0.692965, acc.: 53.52%] [G loss: 0.693954]
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2192 [D loss: 0.693400, acc.: 48.05%] [G loss: 0.693291]
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2193 [D loss: 0.692616, acc.: 50.98%] [G loss: 0.693364]
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2194 [D loss: 0.692573, acc.: 50.20%] [G loss: 0.693384]
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2195 [D loss: 0.694248, acc.: 45.70%] [G loss: 0.693343]
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2196 [D loss: 0.693307, acc.: 47.66%] [G loss: 0.692179]
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2197 [D loss: 0.693089, acc.: 48.44%] [G loss: 0.691850]
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2198 [D loss: 0.692622, acc.: 54.49%] [G loss: 0.692821]
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2199 [D loss: 0.693241, acc.: 51.95%] [G loss: 0.691735]
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2200 [D loss: 0.693960, acc.: 49.41%] [G loss: 0.692229]
1/1 [==============================] - 0s 15ms/step
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2201 [D loss: 0.693306, acc.: 53.32%] [G loss: 0.692285]
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2202 [D loss: 0.693270, acc.: 49.80%] [G loss: 0.692225]
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2203 [D loss: 0.694211, acc.: 49.80%] [G loss: 0.691702]
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2204 [D loss: 0.692698, acc.: 51.76%] [G loss: 0.692175]
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2205 [D loss: 0.693077, acc.: 49.61%] [G loss: 0.690105]
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2206 [D loss: 0.694452, acc.: 45.31%] [G loss: 0.692435]
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2207 [D loss: 0.692933, acc.: 50.39%] [G loss: 0.691389]
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2208 [D loss: 0.693406, acc.: 51.56%] [G loss: 0.692948]
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2209 [D loss: 0.693416, acc.: 49.22%] [G loss: 0.689692]
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2210 [D loss: 0.693385, acc.: 50.00%] [G loss: 0.691749]
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2211 [D loss: 0.693727, acc.: 47.07%] [G loss: 0.690446]
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2212 [D loss: 0.693803, acc.: 49.22%] [G loss: 0.692582]
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2213 [D loss: 0.693734, acc.: 48.24%] [G loss: 0.692772]
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2214 [D loss: 0.694138, acc.: 47.46%] [G loss: 0.690841]
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2215 [D loss: 0.693724, acc.: 51.76%] [G loss: 0.691381]
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2216 [D loss: 0.694083, acc.: 44.73%] [G loss: 0.693471]
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2217 [D loss: 0.695027, acc.: 46.29%] [G loss: 0.692165]
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2218 [D loss: 0.694291, acc.: 46.48%] [G loss: 0.691089]
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2219 [D loss: 0.694931, acc.: 45.51%] [G loss: 0.691440]
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2220 [D loss: 0.694351, acc.: 48.83%] [G loss: 0.695121]
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2221 [D loss: 0.693307, acc.: 47.66%] [G loss: 0.693564]
8/8 [==============================] - 0s 2ms/step
2222 [D loss: 0.692965, acc.: 51.17%] [G loss: 0.693249]
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2223 [D loss: 0.692349, acc.: 51.76%] [G loss: 0.693027]
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2224 [D loss: 0.693310, acc.: 46.88%] [G loss: 0.692839]
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2225 [D loss: 0.691914, acc.: 53.71%] [G loss: 0.693893]
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2226 [D loss: 0.693363, acc.: 49.61%] [G loss: 0.694447]
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2227 [D loss: 0.694245, acc.: 48.63%] [G loss: 0.695496]
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2228 [D loss: 0.693855, acc.: 46.68%] [G loss: 0.693219]
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2229 [D loss: 0.692275, acc.: 52.73%] [G loss: 0.694301]
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2230 [D loss: 0.694040, acc.: 50.59%] [G loss: 0.695908]
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2231 [D loss: 0.693670, acc.: 49.41%] [G loss: 0.695407]
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2232 [D loss: 0.692735, acc.: 52.34%] [G loss: 0.694700]
8/8 [==============================] - 0s 2ms/step
2233 [D loss: 0.693840, acc.: 47.27%] [G loss: 0.694890]
8/8 [==============================] - 0s 2ms/step
2234 [D loss: 0.693151, acc.: 50.00%] [G loss: 0.694438]
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2235 [D loss: 0.694166, acc.: 47.27%] [G loss: 0.695275]
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2236 [D loss: 0.692950, acc.: 50.59%] [G loss: 0.696158]
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2237 [D loss: 0.692317, acc.: 54.10%] [G loss: 0.695579]
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2238 [D loss: 0.693690, acc.: 47.66%] [G loss: 0.694875]
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2239 [D loss: 0.694201, acc.: 47.66%] [G loss: 0.696212]
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2240 [D loss: 0.692476, acc.: 53.32%] [G loss: 0.694349]
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2241 [D loss: 0.693640, acc.: 47.85%] [G loss: 0.693896]
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2242 [D loss: 0.692789, acc.: 51.76%] [G loss: 0.693131]
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2243 [D loss: 0.692063, acc.: 53.91%] [G loss: 0.694265]
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2244 [D loss: 0.693109, acc.: 49.61%] [G loss: 0.695570]
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2245 [D loss: 0.693324, acc.: 46.88%] [G loss: 0.694819]
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2246 [D loss: 0.693938, acc.: 47.27%] [G loss: 0.694180]
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2247 [D loss: 0.693668, acc.: 47.07%] [G loss: 0.695167]
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2248 [D loss: 0.693884, acc.: 47.66%] [G loss: 0.693323]
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2249 [D loss: 0.693947, acc.: 48.44%] [G loss: 0.693567]
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2250 [D loss: 0.693791, acc.: 47.66%] [G loss: 0.694143]
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2251 [D loss: 0.694602, acc.: 46.68%] [G loss: 0.694987]
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2252 [D loss: 0.693850, acc.: 50.20%] [G loss: 0.695215]
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2253 [D loss: 0.693383, acc.: 47.07%] [G loss: 0.695986]
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2254 [D loss: 0.694587, acc.: 48.63%] [G loss: 0.694831]
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2255 [D loss: 0.694656, acc.: 47.85%] [G loss: 0.694599]
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2256 [D loss: 0.693706, acc.: 49.41%] [G loss: 0.695500]
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2257 [D loss: 0.694265, acc.: 46.68%] [G loss: 0.693822]
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2258 [D loss: 0.694709, acc.: 47.07%] [G loss: 0.694425]
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2259 [D loss: 0.693710, acc.: 47.27%] [G loss: 0.694341]
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2260 [D loss: 0.693779, acc.: 47.85%] [G loss: 0.696037]
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2261 [D loss: 0.693365, acc.: 50.20%] [G loss: 0.694867]
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2262 [D loss: 0.692922, acc.: 49.80%] [G loss: 0.695249]
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2263 [D loss: 0.693898, acc.: 48.05%] [G loss: 0.695018]
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2264 [D loss: 0.693608, acc.: 46.29%] [G loss: 0.693916]
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2265 [D loss: 0.692169, acc.: 53.91%] [G loss: 0.695711]
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2266 [D loss: 0.693754, acc.: 51.17%] [G loss: 0.694740]
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2267 [D loss: 0.693779, acc.: 46.48%] [G loss: 0.695338]
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2268 [D loss: 0.692987, acc.: 50.00%] [G loss: 0.694240]
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2269 [D loss: 0.693189, acc.: 49.02%] [G loss: 0.694505]
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2270 [D loss: 0.693921, acc.: 49.41%] [G loss: 0.693927]
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2271 [D loss: 0.693301, acc.: 51.76%] [G loss: 0.694410]
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2272 [D loss: 0.692883, acc.: 51.56%] [G loss: 0.694804]
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2273 [D loss: 0.693547, acc.: 49.22%] [G loss: 0.694941]
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2274 [D loss: 0.692380, acc.: 51.95%] [G loss: 0.693624]
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2275 [D loss: 0.693504, acc.: 50.78%] [G loss: 0.693949]
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2276 [D loss: 0.693565, acc.: 49.41%] [G loss: 0.694599]
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2277 [D loss: 0.694094, acc.: 46.29%] [G loss: 0.694333]
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2278 [D loss: 0.693555, acc.: 49.22%] [G loss: 0.695122]
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2279 [D loss: 0.693587, acc.: 50.20%] [G loss: 0.694049]
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2280 [D loss: 0.695007, acc.: 45.51%] [G loss: 0.694214]
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2281 [D loss: 0.693575, acc.: 47.66%] [G loss: 0.694818]
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2282 [D loss: 0.691916, acc.: 54.30%] [G loss: 0.696388]
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2283 [D loss: 0.693074, acc.: 50.59%] [G loss: 0.696641]
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2284 [D loss: 0.692701, acc.: 47.46%] [G loss: 0.695628]
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2285 [D loss: 0.692980, acc.: 49.61%] [G loss: 0.695274]
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2286 [D loss: 0.692885, acc.: 51.56%] [G loss: 0.694008]
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2287 [D loss: 0.691988, acc.: 53.12%] [G loss: 0.695223]
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2288 [D loss: 0.693141, acc.: 49.41%] [G loss: 0.694984]
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2289 [D loss: 0.694250, acc.: 45.70%] [G loss: 0.694911]
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2290 [D loss: 0.694155, acc.: 47.27%] [G loss: 0.694934]
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2291 [D loss: 0.692099, acc.: 53.12%] [G loss: 0.693339]
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2292 [D loss: 0.692507, acc.: 51.17%] [G loss: 0.694404]
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2293 [D loss: 0.693225, acc.: 51.37%] [G loss: 0.694676]
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2294 [D loss: 0.693190, acc.: 51.37%] [G loss: 0.693181]
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2295 [D loss: 0.693729, acc.: 49.22%] [G loss: 0.692725]
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2296 [D loss: 0.693181, acc.: 49.61%] [G loss: 0.693661]
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2297 [D loss: 0.692667, acc.: 51.37%] [G loss: 0.692689]
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2298 [D loss: 0.692924, acc.: 51.17%] [G loss: 0.692226]
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2299 [D loss: 0.693377, acc.: 49.02%] [G loss: 0.692121]
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2300 [D loss: 0.694079, acc.: 48.83%] [G loss: 0.693581]
1/1 [==============================] - 0s 14ms/step
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2301 [D loss: 0.693720, acc.: 48.83%] [G loss: 0.693664]
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2302 [D loss: 0.693344, acc.: 48.44%] [G loss: 0.693306]
8/8 [==============================] - 0s 2ms/step
2303 [D loss: 0.693162, acc.: 52.54%] [G loss: 0.693266]
8/8 [==============================] - 0s 2ms/step
2304 [D loss: 0.693281, acc.: 49.22%] [G loss: 0.692088]
8/8 [==============================] - 0s 2ms/step
2305 [D loss: 0.693875, acc.: 50.39%] [G loss: 0.691231]
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2306 [D loss: 0.693561, acc.: 50.98%] [G loss: 0.693043]
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2307 [D loss: 0.694144, acc.: 48.24%] [G loss: 0.694024]
8/8 [==============================] - 0s 2ms/step
2308 [D loss: 0.692864, acc.: 52.34%] [G loss: 0.692901]
8/8 [==============================] - 0s 2ms/step
2309 [D loss: 0.693640, acc.: 46.68%] [G loss: 0.692709]
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2310 [D loss: 0.693723, acc.: 49.61%] [G loss: 0.692393]
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2311 [D loss: 0.693812, acc.: 48.24%] [G loss: 0.693066]
8/8 [==============================] - 0s 2ms/step
2312 [D loss: 0.693689, acc.: 47.66%] [G loss: 0.691518]
8/8 [==============================] - 0s 2ms/step
2313 [D loss: 0.693923, acc.: 50.20%] [G loss: 0.692534]
8/8 [==============================] - 0s 2ms/step
2314 [D loss: 0.694153, acc.: 45.51%] [G loss: 0.692209]
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2315 [D loss: 0.693354, acc.: 50.39%] [G loss: 0.694300]
8/8 [==============================] - 0s 2ms/step
2316 [D loss: 0.694581, acc.: 45.31%] [G loss: 0.692935]
8/8 [==============================] - 0s 2ms/step
2317 [D loss: 0.694229, acc.: 47.85%] [G loss: 0.693173]
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2318 [D loss: 0.693636, acc.: 51.76%] [G loss: 0.693184]
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2319 [D loss: 0.692195, acc.: 53.52%] [G loss: 0.692608]
8/8 [==============================] - 0s 2ms/step
2320 [D loss: 0.694427, acc.: 47.66%] [G loss: 0.693286]
8/8 [==============================] - 0s 2ms/step
2321 [D loss: 0.693833, acc.: 46.09%] [G loss: 0.692825]
8/8 [==============================] - 0s 2ms/step
2322 [D loss: 0.693829, acc.: 48.24%] [G loss: 0.694093]
8/8 [==============================] - 0s 2ms/step
2323 [D loss: 0.693931, acc.: 51.37%] [G loss: 0.693233]
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2324 [D loss: 0.692908, acc.: 52.73%] [G loss: 0.693169]
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2325 [D loss: 0.693806, acc.: 48.83%] [G loss: 0.694324]
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2326 [D loss: 0.694585, acc.: 45.70%] [G loss: 0.694731]
8/8 [==============================] - 0s 2ms/step
2327 [D loss: 0.693453, acc.: 45.70%] [G loss: 0.694699]
8/8 [==============================] - 0s 2ms/step
2328 [D loss: 0.693300, acc.: 50.39%] [G loss: 0.696501]
8/8 [==============================] - 0s 2ms/step
2329 [D loss: 0.693619, acc.: 50.39%] [G loss: 0.694503]
8/8 [==============================] - 0s 2ms/step
2330 [D loss: 0.692794, acc.: 52.34%] [G loss: 0.694433]
8/8 [==============================] - 0s 2ms/step
2331 [D loss: 0.693928, acc.: 49.80%] [G loss: 0.694304]
8/8 [==============================] - 0s 2ms/step
2332 [D loss: 0.694050, acc.: 45.70%] [G loss: 0.694770]
8/8 [==============================] - 0s 2ms/step
2333 [D loss: 0.693784, acc.: 50.20%] [G loss: 0.695145]
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2334 [D loss: 0.693390, acc.: 50.39%] [G loss: 0.695055]
8/8 [==============================] - 0s 2ms/step
2335 [D loss: 0.693897, acc.: 48.05%] [G loss: 0.694512]
8/8 [==============================] - 0s 2ms/step
2336 [D loss: 0.693507, acc.: 49.61%] [G loss: 0.694800]
8/8 [==============================] - 0s 2ms/step
2337 [D loss: 0.693081, acc.: 53.32%] [G loss: 0.694579]
8/8 [==============================] - 0s 2ms/step
2338 [D loss: 0.694043, acc.: 46.48%] [G loss: 0.695180]
8/8 [==============================] - 0s 2ms/step
2339 [D loss: 0.693268, acc.: 49.80%] [G loss: 0.694805]
8/8 [==============================] - 0s 2ms/step
2340 [D loss: 0.694201, acc.: 46.29%] [G loss: 0.694246]
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2341 [D loss: 0.693567, acc.: 50.39%] [G loss: 0.695725]
8/8 [==============================] - 0s 2ms/step
2342 [D loss: 0.694126, acc.: 48.44%] [G loss: 0.693712]
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2343 [D loss: 0.693071, acc.: 51.17%] [G loss: 0.695293]
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2344 [D loss: 0.693635, acc.: 49.80%] [G loss: 0.694392]
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2345 [D loss: 0.694241, acc.: 47.07%] [G loss: 0.695705]
8/8 [==============================] - 0s 2ms/step
2346 [D loss: 0.693775, acc.: 49.61%] [G loss: 0.696062]
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2347 [D loss: 0.693612, acc.: 50.20%] [G loss: 0.696006]
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2348 [D loss: 0.694157, acc.: 46.48%] [G loss: 0.694843]
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2349 [D loss: 0.692907, acc.: 51.56%] [G loss: 0.696062]
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2350 [D loss: 0.693549, acc.: 49.61%] [G loss: 0.694142]
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2351 [D loss: 0.693902, acc.: 48.83%] [G loss: 0.694201]
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2352 [D loss: 0.692813, acc.: 49.61%] [G loss: 0.693643]
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2353 [D loss: 0.692854, acc.: 50.20%] [G loss: 0.693982]
8/8 [==============================] - 0s 2ms/step
2354 [D loss: 0.693291, acc.: 48.24%] [G loss: 0.692824]
8/8 [==============================] - 0s 2ms/step
2355 [D loss: 0.694408, acc.: 47.27%] [G loss: 0.692785]
8/8 [==============================] - 0s 2ms/step
2356 [D loss: 0.693259, acc.: 49.80%] [G loss: 0.693510]
8/8 [==============================] - 0s 2ms/step
2357 [D loss: 0.692915, acc.: 51.76%] [G loss: 0.693438]
8/8 [==============================] - 0s 2ms/step
2358 [D loss: 0.692477, acc.: 51.56%] [G loss: 0.694644]
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2359 [D loss: 0.692576, acc.: 51.37%] [G loss: 0.693395]
8/8 [==============================] - 0s 2ms/step
2360 [D loss: 0.693685, acc.: 47.27%] [G loss: 0.693534]
8/8 [==============================] - 0s 2ms/step
2361 [D loss: 0.693812, acc.: 47.27%] [G loss: 0.695036]
8/8 [==============================] - 0s 2ms/step
2362 [D loss: 0.694662, acc.: 45.90%] [G loss: 0.694582]
8/8 [==============================] - 0s 2ms/step
2363 [D loss: 0.693439, acc.: 50.59%] [G loss: 0.694492]
8/8 [==============================] - 0s 2ms/step
2364 [D loss: 0.695230, acc.: 45.12%] [G loss: 0.694449]
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2365 [D loss: 0.694102, acc.: 47.27%] [G loss: 0.693204]
8/8 [==============================] - 0s 2ms/step
2366 [D loss: 0.694516, acc.: 44.53%] [G loss: 0.695620]
8/8 [==============================] - 0s 2ms/step
2367 [D loss: 0.693534, acc.: 48.83%] [G loss: 0.693948]
8/8 [==============================] - 0s 2ms/step
2368 [D loss: 0.692514, acc.: 52.93%] [G loss: 0.694101]
8/8 [==============================] - 0s 2ms/step
2369 [D loss: 0.694168, acc.: 47.46%] [G loss: 0.693736]
8/8 [==============================] - 0s 2ms/step
2370 [D loss: 0.693803, acc.: 48.63%] [G loss: 0.693671]
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2371 [D loss: 0.693411, acc.: 49.02%] [G loss: 0.694200]
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2372 [D loss: 0.693568, acc.: 50.00%] [G loss: 0.694045]
8/8 [==============================] - 0s 2ms/step
2373 [D loss: 0.693068, acc.: 49.80%] [G loss: 0.694758]
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2374 [D loss: 0.693845, acc.: 48.05%] [G loss: 0.694505]
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2375 [D loss: 0.694150, acc.: 48.24%] [G loss: 0.694388]
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2376 [D loss: 0.693899, acc.: 49.02%] [G loss: 0.694616]
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2377 [D loss: 0.692573, acc.: 51.37%] [G loss: 0.694307]
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2378 [D loss: 0.692433, acc.: 50.59%] [G loss: 0.694761]
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2379 [D loss: 0.693994, acc.: 46.88%] [G loss: 0.696126]
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2380 [D loss: 0.692445, acc.: 51.76%] [G loss: 0.697250]
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2381 [D loss: 0.693478, acc.: 48.24%] [G loss: 0.694967]
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2382 [D loss: 0.692405, acc.: 51.76%] [G loss: 0.696501]
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2383 [D loss: 0.693726, acc.: 48.24%] [G loss: 0.696533]
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2384 [D loss: 0.692542, acc.: 50.59%] [G loss: 0.694057]
8/8 [==============================] - 0s 2ms/step
2385 [D loss: 0.694046, acc.: 46.29%] [G loss: 0.693421]
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2386 [D loss: 0.693695, acc.: 48.24%] [G loss: 0.695114]
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2387 [D loss: 0.693253, acc.: 50.20%] [G loss: 0.695009]
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2388 [D loss: 0.691475, acc.: 55.27%] [G loss: 0.693664]
8/8 [==============================] - 0s 2ms/step
2389 [D loss: 0.694203, acc.: 44.53%] [G loss: 0.694942]
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2390 [D loss: 0.693696, acc.: 45.70%] [G loss: 0.694408]
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2391 [D loss: 0.693972, acc.: 51.56%] [G loss: 0.694045]
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2392 [D loss: 0.693161, acc.: 52.15%] [G loss: 0.695285]
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2393 [D loss: 0.694085, acc.: 48.83%] [G loss: 0.692811]
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2394 [D loss: 0.694303, acc.: 47.07%] [G loss: 0.692419]
8/8 [==============================] - 0s 2ms/step
2395 [D loss: 0.693449, acc.: 51.17%] [G loss: 0.693709]
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2396 [D loss: 0.694866, acc.: 43.95%] [G loss: 0.693938]
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2397 [D loss: 0.693846, acc.: 48.44%] [G loss: 0.692519]
8/8 [==============================] - 0s 2ms/step
2398 [D loss: 0.694355, acc.: 47.46%] [G loss: 0.694328]
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2399 [D loss: 0.693365, acc.: 50.00%] [G loss: 0.693771]
8/8 [==============================] - 0s 2ms/step
2400 [D loss: 0.693853, acc.: 50.59%] [G loss: 0.693336]
1/1 [==============================] - 0s 16ms/step
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2401 [D loss: 0.692895, acc.: 49.41%] [G loss: 0.694420]
8/8 [==============================] - 0s 2ms/step
2402 [D loss: 0.693437, acc.: 51.56%] [G loss: 0.693630]
8/8 [==============================] - 0s 2ms/step
2403 [D loss: 0.693266, acc.: 48.83%] [G loss: 0.695137]
8/8 [==============================] - 0s 2ms/step
2404 [D loss: 0.694442, acc.: 45.90%] [G loss: 0.694393]
8/8 [==============================] - 0s 2ms/step
2405 [D loss: 0.693275, acc.: 49.80%] [G loss: 0.693390]
8/8 [==============================] - 0s 2ms/step
2406 [D loss: 0.692979, acc.: 51.95%] [G loss: 0.695110]
8/8 [==============================] - 0s 2ms/step
2407 [D loss: 0.693910, acc.: 46.29%] [G loss: 0.694286]
8/8 [==============================] - 0s 2ms/step
2408 [D loss: 0.694023, acc.: 49.80%] [G loss: 0.694402]
8/8 [==============================] - 0s 2ms/step
2409 [D loss: 0.693973, acc.: 48.63%] [G loss: 0.694683]
8/8 [==============================] - 0s 2ms/step
2410 [D loss: 0.694099, acc.: 45.31%] [G loss: 0.696294]
8/8 [==============================] - 0s 2ms/step
2411 [D loss: 0.693255, acc.: 49.80%] [G loss: 0.695184]
8/8 [==============================] - 0s 3ms/step
2412 [D loss: 0.694457, acc.: 47.46%] [G loss: 0.694656]
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2413 [D loss: 0.694165, acc.: 48.05%] [G loss: 0.694468]
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2414 [D loss: 0.693449, acc.: 50.98%] [G loss: 0.694710]
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2415 [D loss: 0.693558, acc.: 48.44%] [G loss: 0.694756]
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2416 [D loss: 0.693396, acc.: 48.83%] [G loss: 0.693772]
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2417 [D loss: 0.692952, acc.: 50.78%] [G loss: 0.695375]
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2418 [D loss: 0.694023, acc.: 48.44%] [G loss: 0.694142]
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2419 [D loss: 0.694970, acc.: 42.38%] [G loss: 0.694979]
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2420 [D loss: 0.694810, acc.: 46.09%] [G loss: 0.693357]
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2421 [D loss: 0.693705, acc.: 50.59%] [G loss: 0.693443]
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2422 [D loss: 0.693429, acc.: 48.63%] [G loss: 0.694987]
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2423 [D loss: 0.693505, acc.: 50.98%] [G loss: 0.694911]
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2424 [D loss: 0.692573, acc.: 53.12%] [G loss: 0.694059]
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2425 [D loss: 0.694209, acc.: 49.22%] [G loss: 0.692950]
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2426 [D loss: 0.692831, acc.: 51.76%] [G loss: 0.693826]
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2427 [D loss: 0.693161, acc.: 50.59%] [G loss: 0.693143]
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2428 [D loss: 0.693501, acc.: 48.83%] [G loss: 0.693876]
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2429 [D loss: 0.692920, acc.: 52.15%] [G loss: 0.693828]
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2430 [D loss: 0.694493, acc.: 46.68%] [G loss: 0.695471]
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2431 [D loss: 0.692633, acc.: 50.20%] [G loss: 0.694589]
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2432 [D loss: 0.693693, acc.: 46.68%] [G loss: 0.696635]
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2433 [D loss: 0.691884, acc.: 54.49%] [G loss: 0.694506]
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2434 [D loss: 0.693129, acc.: 51.95%] [G loss: 0.693369]
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2435 [D loss: 0.693975, acc.: 49.41%] [G loss: 0.694763]
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2436 [D loss: 0.692236, acc.: 52.73%] [G loss: 0.694864]
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2437 [D loss: 0.693557, acc.: 49.61%] [G loss: 0.695378]
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2438 [D loss: 0.693319, acc.: 51.37%] [G loss: 0.694893]
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2439 [D loss: 0.694137, acc.: 48.44%] [G loss: 0.695020]
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2440 [D loss: 0.693093, acc.: 50.78%] [G loss: 0.695342]
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2441 [D loss: 0.693916, acc.: 50.00%] [G loss: 0.694126]
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2442 [D loss: 0.692906, acc.: 51.37%] [G loss: 0.694520]
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2443 [D loss: 0.693129, acc.: 50.98%] [G loss: 0.696503]
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2444 [D loss: 0.694018, acc.: 47.46%] [G loss: 0.694588]
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2445 [D loss: 0.693816, acc.: 47.85%] [G loss: 0.694600]
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2446 [D loss: 0.693462, acc.: 50.00%] [G loss: 0.695126]
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2447 [D loss: 0.692916, acc.: 51.17%] [G loss: 0.695401]
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2448 [D loss: 0.694232, acc.: 46.68%] [G loss: 0.694995]
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2449 [D loss: 0.694450, acc.: 46.88%] [G loss: 0.695620]
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2450 [D loss: 0.693337, acc.: 50.59%] [G loss: 0.695462]
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2451 [D loss: 0.693541, acc.: 48.24%] [G loss: 0.696348]
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2452 [D loss: 0.693053, acc.: 50.39%] [G loss: 0.693225]
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2453 [D loss: 0.694074, acc.: 48.63%] [G loss: 0.696243]
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2454 [D loss: 0.693569, acc.: 47.85%] [G loss: 0.695177]
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2455 [D loss: 0.693541, acc.: 49.61%] [G loss: 0.695236]
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2456 [D loss: 0.693639, acc.: 49.22%] [G loss: 0.695210]
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2457 [D loss: 0.693960, acc.: 49.41%] [G loss: 0.695807]
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2458 [D loss: 0.693047, acc.: 51.37%] [G loss: 0.695833]
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2459 [D loss: 0.692777, acc.: 51.37%] [G loss: 0.696846]
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2460 [D loss: 0.693273, acc.: 47.66%] [G loss: 0.694514]
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2461 [D loss: 0.692434, acc.: 51.37%] [G loss: 0.693971]
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2462 [D loss: 0.694623, acc.: 44.92%] [G loss: 0.693777]
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2463 [D loss: 0.693321, acc.: 50.00%] [G loss: 0.695793]
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2464 [D loss: 0.693547, acc.: 51.76%] [G loss: 0.695086]
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2465 [D loss: 0.692435, acc.: 53.32%] [G loss: 0.695904]
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2466 [D loss: 0.692824, acc.: 53.91%] [G loss: 0.693457]
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2467 [D loss: 0.693090, acc.: 51.76%] [G loss: 0.694891]
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2468 [D loss: 0.694194, acc.: 48.63%] [G loss: 0.694718]
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2469 [D loss: 0.693006, acc.: 49.22%] [G loss: 0.695819]
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2470 [D loss: 0.693365, acc.: 50.20%] [G loss: 0.694041]
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2471 [D loss: 0.693472, acc.: 50.98%] [G loss: 0.694878]
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2472 [D loss: 0.693298, acc.: 50.39%] [G loss: 0.694658]
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2473 [D loss: 0.693968, acc.: 48.24%] [G loss: 0.694920]
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2474 [D loss: 0.693209, acc.: 50.00%] [G loss: 0.695201]
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2475 [D loss: 0.693745, acc.: 47.46%] [G loss: 0.695913]
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2476 [D loss: 0.693060, acc.: 49.61%] [G loss: 0.694492]
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2477 [D loss: 0.694234, acc.: 45.51%] [G loss: 0.694994]
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2478 [D loss: 0.693631, acc.: 49.02%] [G loss: 0.695736]
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2479 [D loss: 0.693755, acc.: 49.02%] [G loss: 0.693951]
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2480 [D loss: 0.694035, acc.: 45.51%] [G loss: 0.693818]
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2481 [D loss: 0.694550, acc.: 45.31%] [G loss: 0.695640]
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2482 [D loss: 0.693029, acc.: 50.78%] [G loss: 0.696146]
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2483 [D loss: 0.693286, acc.: 49.02%] [G loss: 0.695393]
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2484 [D loss: 0.694299, acc.: 47.07%] [G loss: 0.694625]
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2485 [D loss: 0.693390, acc.: 50.20%] [G loss: 0.695702]
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2486 [D loss: 0.694136, acc.: 49.22%] [G loss: 0.694686]
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2487 [D loss: 0.694171, acc.: 47.66%] [G loss: 0.695076]
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2488 [D loss: 0.694126, acc.: 46.68%] [G loss: 0.694632]
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2489 [D loss: 0.693978, acc.: 49.22%] [G loss: 0.695163]
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2490 [D loss: 0.692468, acc.: 57.03%] [G loss: 0.692852]
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2491 [D loss: 0.693260, acc.: 50.59%] [G loss: 0.693177]
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2492 [D loss: 0.693951, acc.: 48.63%] [G loss: 0.693160]
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2493 [D loss: 0.694324, acc.: 46.09%] [G loss: 0.693485]
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2494 [D loss: 0.693941, acc.: 48.83%] [G loss: 0.693931]
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2495 [D loss: 0.694054, acc.: 47.85%] [G loss: 0.694365]
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2496 [D loss: 0.693339, acc.: 51.17%] [G loss: 0.693986]
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2497 [D loss: 0.693410, acc.: 49.80%] [G loss: 0.694193]
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2498 [D loss: 0.693760, acc.: 45.70%] [G loss: 0.693679]
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2499 [D loss: 0.694348, acc.: 46.09%] [G loss: 0.692804]
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2500 [D loss: 0.693092, acc.: 50.98%] [G loss: 0.694501]
1/1 [==============================] - 0s 16ms/step
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2501 [D loss: 0.692307, acc.: 53.71%] [G loss: 0.695280]
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2502 [D loss: 0.692643, acc.: 52.34%] [G loss: 0.693928]
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2503 [D loss: 0.693231, acc.: 51.17%] [G loss: 0.693282]
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2504 [D loss: 0.692970, acc.: 51.17%] [G loss: 0.694311]
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2505 [D loss: 0.693471, acc.: 51.17%] [G loss: 0.694689]
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2506 [D loss: 0.693104, acc.: 48.63%] [G loss: 0.693370]
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2507 [D loss: 0.693095, acc.: 49.80%] [G loss: 0.693363]
8/8 [==============================] - 0s 2ms/step
2508 [D loss: 0.694304, acc.: 47.66%] [G loss: 0.693562]
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2509 [D loss: 0.693363, acc.: 51.76%] [G loss: 0.693236]
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2510 [D loss: 0.693239, acc.: 49.61%] [G loss: 0.693534]
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2511 [D loss: 0.692784, acc.: 52.54%] [G loss: 0.693058]
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2512 [D loss: 0.692784, acc.: 52.34%] [G loss: 0.694027]
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2513 [D loss: 0.694277, acc.: 44.34%] [G loss: 0.694000]
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2514 [D loss: 0.692955, acc.: 48.83%] [G loss: 0.695039]
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2515 [D loss: 0.693805, acc.: 48.63%] [G loss: 0.693249]
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2516 [D loss: 0.691825, acc.: 56.05%] [G loss: 0.693261]
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2517 [D loss: 0.693005, acc.: 48.63%] [G loss: 0.694073]
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2518 [D loss: 0.693210, acc.: 50.39%] [G loss: 0.694320]
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2519 [D loss: 0.693110, acc.: 50.78%] [G loss: 0.693659]
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2520 [D loss: 0.693164, acc.: 49.80%] [G loss: 0.693458]
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2521 [D loss: 0.692796, acc.: 51.56%] [G loss: 0.694474]
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2522 [D loss: 0.692660, acc.: 49.22%] [G loss: 0.693409]
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2523 [D loss: 0.693224, acc.: 48.83%] [G loss: 0.693014]
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2524 [D loss: 0.692868, acc.: 49.02%] [G loss: 0.695196]
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2525 [D loss: 0.693632, acc.: 48.83%] [G loss: 0.692843]
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2526 [D loss: 0.694267, acc.: 46.48%] [G loss: 0.692173]
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2527 [D loss: 0.694752, acc.: 47.27%] [G loss: 0.693163]
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2528 [D loss: 0.693455, acc.: 50.00%] [G loss: 0.694092]
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2529 [D loss: 0.694532, acc.: 46.68%] [G loss: 0.692457]
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2530 [D loss: 0.694044, acc.: 46.29%] [G loss: 0.693625]
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2531 [D loss: 0.694488, acc.: 45.70%] [G loss: 0.691669]
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2532 [D loss: 0.693474, acc.: 48.83%] [G loss: 0.691354]
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2533 [D loss: 0.694814, acc.: 46.09%] [G loss: 0.692551]
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2534 [D loss: 0.694029, acc.: 48.24%] [G loss: 0.692051]
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2535 [D loss: 0.693521, acc.: 48.24%] [G loss: 0.695269]
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2536 [D loss: 0.693134, acc.: 51.37%] [G loss: 0.694978]
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2537 [D loss: 0.693201, acc.: 52.54%] [G loss: 0.694081]
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2538 [D loss: 0.692973, acc.: 50.59%] [G loss: 0.694225]
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2539 [D loss: 0.693671, acc.: 48.63%] [G loss: 0.694344]
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2540 [D loss: 0.694087, acc.: 46.88%] [G loss: 0.694717]
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2541 [D loss: 0.692998, acc.: 51.37%] [G loss: 0.695103]
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2542 [D loss: 0.693635, acc.: 49.02%] [G loss: 0.695355]
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2543 [D loss: 0.692824, acc.: 51.37%] [G loss: 0.694155]
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2544 [D loss: 0.693413, acc.: 49.41%] [G loss: 0.694328]
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2545 [D loss: 0.694100, acc.: 45.12%] [G loss: 0.694045]
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2546 [D loss: 0.694274, acc.: 47.66%] [G loss: 0.695299]
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2547 [D loss: 0.694601, acc.: 45.12%] [G loss: 0.696048]
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2548 [D loss: 0.692740, acc.: 50.20%] [G loss: 0.695847]
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2549 [D loss: 0.693384, acc.: 50.00%] [G loss: 0.694411]
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2550 [D loss: 0.693577, acc.: 47.27%] [G loss: 0.695149]
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2551 [D loss: 0.693910, acc.: 48.05%] [G loss: 0.694309]
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2552 [D loss: 0.693188, acc.: 52.54%] [G loss: 0.694617]
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2553 [D loss: 0.693536, acc.: 48.05%] [G loss: 0.694583]
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2554 [D loss: 0.693285, acc.: 51.17%] [G loss: 0.695887]
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2555 [D loss: 0.693018, acc.: 51.56%] [G loss: 0.694553]
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2556 [D loss: 0.694139, acc.: 48.24%] [G loss: 0.696017]
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2557 [D loss: 0.693417, acc.: 49.80%] [G loss: 0.695876]
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2558 [D loss: 0.693192, acc.: 48.05%] [G loss: 0.695780]
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2559 [D loss: 0.692566, acc.: 54.10%] [G loss: 0.694255]
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2560 [D loss: 0.693515, acc.: 50.00%] [G loss: 0.694056]
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2561 [D loss: 0.694422, acc.: 46.48%] [G loss: 0.694238]
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2562 [D loss: 0.693298, acc.: 49.22%] [G loss: 0.693997]
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2563 [D loss: 0.693339, acc.: 47.85%] [G loss: 0.693939]
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2564 [D loss: 0.693820, acc.: 46.88%] [G loss: 0.694538]
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2565 [D loss: 0.693001, acc.: 51.95%] [G loss: 0.693860]
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2566 [D loss: 0.693374, acc.: 51.37%] [G loss: 0.693771]
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2567 [D loss: 0.693140, acc.: 51.56%] [G loss: 0.691944]
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2568 [D loss: 0.693110, acc.: 50.00%] [G loss: 0.693125]
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2569 [D loss: 0.692676, acc.: 52.15%] [G loss: 0.693085]
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2570 [D loss: 0.692624, acc.: 50.78%] [G loss: 0.693701]
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2571 [D loss: 0.693547, acc.: 51.76%] [G loss: 0.692310]
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2572 [D loss: 0.694752, acc.: 45.90%] [G loss: 0.693471]
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2573 [D loss: 0.693406, acc.: 48.83%] [G loss: 0.692543]
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2574 [D loss: 0.694368, acc.: 46.29%] [G loss: 0.694423]
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2575 [D loss: 0.693914, acc.: 48.24%] [G loss: 0.694753]
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2576 [D loss: 0.692751, acc.: 50.98%] [G loss: 0.694429]
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2577 [D loss: 0.692891, acc.: 52.93%] [G loss: 0.695220]
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2578 [D loss: 0.692374, acc.: 54.30%] [G loss: 0.693476]
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2579 [D loss: 0.692109, acc.: 54.88%] [G loss: 0.694679]
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2580 [D loss: 0.694700, acc.: 45.70%] [G loss: 0.693891]
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2581 [D loss: 0.693140, acc.: 49.41%] [G loss: 0.694360]
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2582 [D loss: 0.694325, acc.: 48.44%] [G loss: 0.693775]
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2583 [D loss: 0.693728, acc.: 47.27%] [G loss: 0.696188]
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2584 [D loss: 0.693196, acc.: 48.63%] [G loss: 0.694223]
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2585 [D loss: 0.692060, acc.: 51.95%] [G loss: 0.694697]
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2586 [D loss: 0.693642, acc.: 50.39%] [G loss: 0.696806]
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2587 [D loss: 0.693594, acc.: 49.02%] [G loss: 0.695494]
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2588 [D loss: 0.693473, acc.: 50.20%] [G loss: 0.694336]
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2589 [D loss: 0.693762, acc.: 47.27%] [G loss: 0.695895]
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2590 [D loss: 0.693118, acc.: 48.83%] [G loss: 0.695359]
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2591 [D loss: 0.692894, acc.: 50.20%] [G loss: 0.694911]
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2592 [D loss: 0.693529, acc.: 50.20%] [G loss: 0.693254]
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2593 [D loss: 0.693265, acc.: 49.41%] [G loss: 0.696324]
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2594 [D loss: 0.693807, acc.: 45.90%] [G loss: 0.694173]
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2595 [D loss: 0.693199, acc.: 51.76%] [G loss: 0.694892]
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2596 [D loss: 0.692450, acc.: 50.78%] [G loss: 0.694489]
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2597 [D loss: 0.693586, acc.: 51.17%] [G loss: 0.695180]
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2598 [D loss: 0.693529, acc.: 50.98%] [G loss: 0.696949]
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2599 [D loss: 0.693525, acc.: 50.20%] [G loss: 0.697809]
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2600 [D loss: 0.693702, acc.: 49.41%] [G loss: 0.696842]
1/1 [==============================] - 0s 16ms/step
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2601 [D loss: 0.693055, acc.: 51.37%] [G loss: 0.695554]
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2602 [D loss: 0.694492, acc.: 44.53%] [G loss: 0.694412]
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2603 [D loss: 0.694945, acc.: 44.53%] [G loss: 0.693564]
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2604 [D loss: 0.694312, acc.: 47.66%] [G loss: 0.695361]
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2605 [D loss: 0.693030, acc.: 50.00%] [G loss: 0.694388]
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2606 [D loss: 0.692925, acc.: 49.61%] [G loss: 0.694477]
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2607 [D loss: 0.692860, acc.: 52.93%] [G loss: 0.695335]
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2608 [D loss: 0.693576, acc.: 51.17%] [G loss: 0.692958]
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2609 [D loss: 0.694041, acc.: 47.66%] [G loss: 0.694519]
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2610 [D loss: 0.693851, acc.: 47.46%] [G loss: 0.693333]
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2611 [D loss: 0.693916, acc.: 50.39%] [G loss: 0.694261]
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2612 [D loss: 0.693385, acc.: 49.41%] [G loss: 0.694113]
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2613 [D loss: 0.692873, acc.: 52.15%] [G loss: 0.694821]
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2614 [D loss: 0.692886, acc.: 49.80%] [G loss: 0.693756]
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2615 [D loss: 0.693918, acc.: 46.88%] [G loss: 0.692839]
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2616 [D loss: 0.693547, acc.: 47.85%] [G loss: 0.692754]
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2617 [D loss: 0.693967, acc.: 47.85%] [G loss: 0.693309]
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2618 [D loss: 0.693367, acc.: 48.63%] [G loss: 0.693002]
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2619 [D loss: 0.693386, acc.: 50.59%] [G loss: 0.691928]
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2620 [D loss: 0.693099, acc.: 49.80%] [G loss: 0.692660]
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2621 [D loss: 0.693440, acc.: 49.22%] [G loss: 0.693281]
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2622 [D loss: 0.694572, acc.: 46.88%] [G loss: 0.692406]
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2623 [D loss: 0.692634, acc.: 50.78%] [G loss: 0.694600]
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2624 [D loss: 0.694189, acc.: 47.27%] [G loss: 0.692633]
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2625 [D loss: 0.692928, acc.: 50.20%] [G loss: 0.693424]
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2626 [D loss: 0.693273, acc.: 51.95%] [G loss: 0.692719]
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2627 [D loss: 0.693015, acc.: 50.00%] [G loss: 0.694450]
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2628 [D loss: 0.693347, acc.: 50.00%] [G loss: 0.692928]
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2629 [D loss: 0.694176, acc.: 47.27%] [G loss: 0.692448]
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2630 [D loss: 0.693030, acc.: 50.39%] [G loss: 0.693108]
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2631 [D loss: 0.693983, acc.: 48.63%] [G loss: 0.694925]
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2632 [D loss: 0.694005, acc.: 47.85%] [G loss: 0.694875]
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2633 [D loss: 0.692907, acc.: 50.00%] [G loss: 0.694184]
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2634 [D loss: 0.692316, acc.: 52.93%] [G loss: 0.693396]
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2635 [D loss: 0.693995, acc.: 47.46%] [G loss: 0.692699]
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2636 [D loss: 0.692514, acc.: 50.98%] [G loss: 0.694076]
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2637 [D loss: 0.693060, acc.: 51.95%] [G loss: 0.693814]
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2638 [D loss: 0.692696, acc.: 52.93%] [G loss: 0.693046]
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2639 [D loss: 0.693899, acc.: 50.20%] [G loss: 0.692262]
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2640 [D loss: 0.694332, acc.: 49.80%] [G loss: 0.695032]
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2641 [D loss: 0.693296, acc.: 47.66%] [G loss: 0.694463]
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2642 [D loss: 0.692539, acc.: 52.34%] [G loss: 0.694596]
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2643 [D loss: 0.692347, acc.: 53.32%] [G loss: 0.693807]
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2644 [D loss: 0.692618, acc.: 52.73%] [G loss: 0.694297]
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2645 [D loss: 0.693224, acc.: 51.17%] [G loss: 0.694714]
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2646 [D loss: 0.692565, acc.: 52.15%] [G loss: 0.695220]
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2647 [D loss: 0.693292, acc.: 50.59%] [G loss: 0.694212]
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2648 [D loss: 0.693678, acc.: 47.46%] [G loss: 0.695111]
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2649 [D loss: 0.692846, acc.: 52.15%] [G loss: 0.693929]
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2650 [D loss: 0.693987, acc.: 47.46%] [G loss: 0.694451]
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2651 [D loss: 0.693558, acc.: 47.27%] [G loss: 0.695140]
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2652 [D loss: 0.693107, acc.: 53.71%] [G loss: 0.695347]
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2653 [D loss: 0.692632, acc.: 52.34%] [G loss: 0.694224]
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2654 [D loss: 0.693715, acc.: 48.05%] [G loss: 0.695679]
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2655 [D loss: 0.692757, acc.: 50.59%] [G loss: 0.695261]
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2656 [D loss: 0.693562, acc.: 48.24%] [G loss: 0.695550]
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2657 [D loss: 0.692970, acc.: 53.12%] [G loss: 0.695111]
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2658 [D loss: 0.693103, acc.: 47.27%] [G loss: 0.694540]
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2659 [D loss: 0.693726, acc.: 48.24%] [G loss: 0.694068]
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2660 [D loss: 0.693185, acc.: 49.61%] [G loss: 0.693206]
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2661 [D loss: 0.692994, acc.: 48.83%] [G loss: 0.693094]
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2662 [D loss: 0.692657, acc.: 50.78%] [G loss: 0.694002]
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2663 [D loss: 0.692803, acc.: 52.93%] [G loss: 0.692789]
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2664 [D loss: 0.693917, acc.: 47.66%] [G loss: 0.694911]
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2665 [D loss: 0.693081, acc.: 50.39%] [G loss: 0.694056]
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2666 [D loss: 0.693059, acc.: 50.00%] [G loss: 0.694217]
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2667 [D loss: 0.693267, acc.: 48.44%] [G loss: 0.695751]
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2668 [D loss: 0.693458, acc.: 47.85%] [G loss: 0.694711]
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2669 [D loss: 0.693314, acc.: 50.39%] [G loss: 0.694718]
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2670 [D loss: 0.693563, acc.: 49.41%] [G loss: 0.695251]
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2671 [D loss: 0.693416, acc.: 47.85%] [G loss: 0.694770]
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2672 [D loss: 0.694105, acc.: 47.66%] [G loss: 0.696661]
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2673 [D loss: 0.693376, acc.: 50.78%] [G loss: 0.694035]
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2674 [D loss: 0.692727, acc.: 53.71%] [G loss: 0.694487]
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2675 [D loss: 0.692647, acc.: 53.12%] [G loss: 0.693948]
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2676 [D loss: 0.693792, acc.: 50.00%] [G loss: 0.693642]
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2677 [D loss: 0.692186, acc.: 53.71%] [G loss: 0.692671]
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2678 [D loss: 0.693746, acc.: 46.68%] [G loss: 0.692422]
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2679 [D loss: 0.693702, acc.: 47.46%] [G loss: 0.693979]
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2680 [D loss: 0.693520, acc.: 46.29%] [G loss: 0.693502]
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2681 [D loss: 0.692521, acc.: 51.95%] [G loss: 0.692596]
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2682 [D loss: 0.694396, acc.: 45.90%] [G loss: 0.692523]
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2683 [D loss: 0.693753, acc.: 48.44%] [G loss: 0.692478]
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2684 [D loss: 0.694797, acc.: 45.90%] [G loss: 0.694466]
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2685 [D loss: 0.694252, acc.: 50.20%] [G loss: 0.693342]
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2686 [D loss: 0.694767, acc.: 45.70%] [G loss: 0.693782]
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2687 [D loss: 0.692760, acc.: 50.00%] [G loss: 0.693486]
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2688 [D loss: 0.693954, acc.: 48.63%] [G loss: 0.693000]
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2689 [D loss: 0.693474, acc.: 50.39%] [G loss: 0.693558]
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2690 [D loss: 0.692966, acc.: 51.17%] [G loss: 0.693475]
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2691 [D loss: 0.691850, acc.: 52.73%] [G loss: 0.694071]
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2692 [D loss: 0.693693, acc.: 46.88%] [G loss: 0.693853]
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2693 [D loss: 0.693472, acc.: 50.39%] [G loss: 0.693837]
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2694 [D loss: 0.693609, acc.: 49.02%] [G loss: 0.693306]
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2695 [D loss: 0.695091, acc.: 43.16%] [G loss: 0.693815]
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2696 [D loss: 0.694129, acc.: 47.66%] [G loss: 0.694120]
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2697 [D loss: 0.693770, acc.: 49.02%] [G loss: 0.693906]
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2698 [D loss: 0.693556, acc.: 50.39%] [G loss: 0.694159]
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2699 [D loss: 0.694767, acc.: 46.48%] [G loss: 0.693184]
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2700 [D loss: 0.692873, acc.: 50.78%] [G loss: 0.694320]
1/1 [==============================] - 0s 15ms/step
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2701 [D loss: 0.693927, acc.: 47.46%] [G loss: 0.695297]
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2702 [D loss: 0.692668, acc.: 51.17%] [G loss: 0.695667]
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2703 [D loss: 0.693662, acc.: 49.22%] [G loss: 0.697575]
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2704 [D loss: 0.692084, acc.: 54.30%] [G loss: 0.696247]
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2705 [D loss: 0.692135, acc.: 51.95%] [G loss: 0.692994]
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2706 [D loss: 0.692764, acc.: 49.41%] [G loss: 0.693266]
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2707 [D loss: 0.692701, acc.: 51.76%] [G loss: 0.694253]
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2708 [D loss: 0.694187, acc.: 46.48%] [G loss: 0.693847]
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2709 [D loss: 0.691988, acc.: 55.27%] [G loss: 0.694818]
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2710 [D loss: 0.693406, acc.: 49.02%] [G loss: 0.694944]
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2711 [D loss: 0.693940, acc.: 48.63%] [G loss: 0.695634]
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2712 [D loss: 0.692472, acc.: 53.32%] [G loss: 0.695569]
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2713 [D loss: 0.693554, acc.: 47.85%] [G loss: 0.696770]
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2714 [D loss: 0.693934, acc.: 49.41%] [G loss: 0.693646]
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2715 [D loss: 0.693233, acc.: 49.61%] [G loss: 0.693817]
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2716 [D loss: 0.694208, acc.: 48.24%] [G loss: 0.693347]
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2717 [D loss: 0.693506, acc.: 51.56%] [G loss: 0.694415]
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2718 [D loss: 0.693636, acc.: 49.61%] [G loss: 0.693289]
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2719 [D loss: 0.693486, acc.: 45.51%] [G loss: 0.693932]
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2720 [D loss: 0.693285, acc.: 49.22%] [G loss: 0.692428]
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2721 [D loss: 0.693275, acc.: 51.56%] [G loss: 0.693655]
8/8 [==============================] - 0s 2ms/step
2722 [D loss: 0.693523, acc.: 49.22%] [G loss: 0.694418]
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2723 [D loss: 0.694170, acc.: 48.44%] [G loss: 0.694296]
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2724 [D loss: 0.693521, acc.: 50.00%] [G loss: 0.693069]
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2725 [D loss: 0.694301, acc.: 45.31%] [G loss: 0.695060]
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2726 [D loss: 0.693458, acc.: 51.76%] [G loss: 0.693517]
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2727 [D loss: 0.694335, acc.: 47.27%] [G loss: 0.694044]
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2728 [D loss: 0.693563, acc.: 51.56%] [G loss: 0.694159]
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2729 [D loss: 0.693734, acc.: 48.83%] [G loss: 0.694573]
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2730 [D loss: 0.693676, acc.: 51.17%] [G loss: 0.693201]
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2731 [D loss: 0.692912, acc.: 49.41%] [G loss: 0.693930]
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2732 [D loss: 0.694075, acc.: 47.46%] [G loss: 0.694086]
8/8 [==============================] - 0s 2ms/step
2733 [D loss: 0.692546, acc.: 51.17%] [G loss: 0.693343]
8/8 [==============================] - 0s 2ms/step
2734 [D loss: 0.693031, acc.: 50.20%] [G loss: 0.693781]
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2735 [D loss: 0.694337, acc.: 48.05%] [G loss: 0.694117]
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2736 [D loss: 0.693387, acc.: 48.24%] [G loss: 0.693222]
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2737 [D loss: 0.692836, acc.: 50.00%] [G loss: 0.692804]
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2738 [D loss: 0.693310, acc.: 50.00%] [G loss: 0.692156]
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2739 [D loss: 0.692823, acc.: 52.54%] [G loss: 0.691625]
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2740 [D loss: 0.692894, acc.: 51.37%] [G loss: 0.692809]
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2741 [D loss: 0.693656, acc.: 48.63%] [G loss: 0.693103]
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2742 [D loss: 0.692792, acc.: 50.39%] [G loss: 0.692865]
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2743 [D loss: 0.692427, acc.: 51.95%] [G loss: 0.692945]
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2744 [D loss: 0.693544, acc.: 51.56%] [G loss: 0.693481]
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2745 [D loss: 0.693191, acc.: 49.02%] [G loss: 0.695436]
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2746 [D loss: 0.693523, acc.: 46.88%] [G loss: 0.695743]
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2747 [D loss: 0.692854, acc.: 50.98%] [G loss: 0.694317]
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2748 [D loss: 0.693315, acc.: 46.09%] [G loss: 0.694026]
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2749 [D loss: 0.692798, acc.: 51.76%] [G loss: 0.694177]
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2750 [D loss: 0.693132, acc.: 48.63%] [G loss: 0.695419]
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2751 [D loss: 0.693011, acc.: 49.61%] [G loss: 0.693355]
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2752 [D loss: 0.693623, acc.: 49.61%] [G loss: 0.693368]
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2753 [D loss: 0.693807, acc.: 49.80%] [G loss: 0.693647]
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2754 [D loss: 0.694049, acc.: 47.66%] [G loss: 0.694049]
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2755 [D loss: 0.694114, acc.: 44.73%] [G loss: 0.694102]
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2756 [D loss: 0.693848, acc.: 49.02%] [G loss: 0.694126]
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2757 [D loss: 0.693387, acc.: 49.80%] [G loss: 0.694770]
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2758 [D loss: 0.693865, acc.: 48.44%] [G loss: 0.694021]
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2759 [D loss: 0.694115, acc.: 45.70%] [G loss: 0.694411]
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2760 [D loss: 0.693339, acc.: 49.41%] [G loss: 0.692241]
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2761 [D loss: 0.693672, acc.: 49.41%] [G loss: 0.695550]
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2762 [D loss: 0.692623, acc.: 54.10%] [G loss: 0.694942]
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2763 [D loss: 0.692740, acc.: 51.17%] [G loss: 0.692794]
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2764 [D loss: 0.693926, acc.: 49.22%] [G loss: 0.694011]
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2765 [D loss: 0.692812, acc.: 51.37%] [G loss: 0.691626]
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2766 [D loss: 0.694945, acc.: 46.88%] [G loss: 0.694797]
8/8 [==============================] - 0s 2ms/step
2767 [D loss: 0.694172, acc.: 48.24%] [G loss: 0.694124]
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2768 [D loss: 0.694267, acc.: 46.29%] [G loss: 0.692003]
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2769 [D loss: 0.693318, acc.: 50.78%] [G loss: 0.694294]
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2770 [D loss: 0.695199, acc.: 44.14%] [G loss: 0.691663]
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2771 [D loss: 0.694011, acc.: 47.07%] [G loss: 0.693760]
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2772 [D loss: 0.693649, acc.: 48.05%] [G loss: 0.693267]
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2773 [D loss: 0.693842, acc.: 49.02%] [G loss: 0.693646]
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2774 [D loss: 0.693041, acc.: 51.17%] [G loss: 0.693388]
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2775 [D loss: 0.693060, acc.: 49.61%] [G loss: 0.694360]
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2776 [D loss: 0.692883, acc.: 49.02%] [G loss: 0.694960]
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2777 [D loss: 0.693122, acc.: 49.80%] [G loss: 0.694829]
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2778 [D loss: 0.694451, acc.: 45.51%] [G loss: 0.695460]
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2779 [D loss: 0.692829, acc.: 52.93%] [G loss: 0.695945]
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2780 [D loss: 0.694663, acc.: 45.12%] [G loss: 0.695921]
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2781 [D loss: 0.693359, acc.: 50.00%] [G loss: 0.695232]
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2782 [D loss: 0.693909, acc.: 47.66%] [G loss: 0.695054]
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2783 [D loss: 0.693727, acc.: 49.22%] [G loss: 0.694825]
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2784 [D loss: 0.693446, acc.: 51.56%] [G loss: 0.695558]
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2785 [D loss: 0.693632, acc.: 46.68%] [G loss: 0.696043]
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2786 [D loss: 0.692888, acc.: 50.59%] [G loss: 0.695142]
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2787 [D loss: 0.692465, acc.: 52.15%] [G loss: 0.697332]
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2788 [D loss: 0.693362, acc.: 51.17%] [G loss: 0.695274]
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2789 [D loss: 0.691795, acc.: 52.34%] [G loss: 0.695361]
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2790 [D loss: 0.692883, acc.: 50.20%] [G loss: 0.694762]
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2791 [D loss: 0.693000, acc.: 50.78%] [G loss: 0.693932]
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2792 [D loss: 0.693375, acc.: 47.27%] [G loss: 0.693968]
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2793 [D loss: 0.694085, acc.: 49.22%] [G loss: 0.694794]
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2794 [D loss: 0.693944, acc.: 46.09%] [G loss: 0.694653]
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2795 [D loss: 0.693459, acc.: 50.78%] [G loss: 0.693884]
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2796 [D loss: 0.693409, acc.: 48.63%] [G loss: 0.695094]
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2797 [D loss: 0.692719, acc.: 52.73%] [G loss: 0.695097]
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2798 [D loss: 0.693270, acc.: 49.61%] [G loss: 0.695728]
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2799 [D loss: 0.693524, acc.: 48.24%] [G loss: 0.693066]
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2800 [D loss: 0.693572, acc.: 49.02%] [G loss: 0.692453]
1/1 [==============================] - 0s 15ms/step
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2801 [D loss: 0.693288, acc.: 50.59%] [G loss: 0.694338]
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2802 [D loss: 0.693808, acc.: 50.00%] [G loss: 0.695178]
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2803 [D loss: 0.693678, acc.: 47.66%] [G loss: 0.694988]
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2804 [D loss: 0.693132, acc.: 49.02%] [G loss: 0.696183]
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2805 [D loss: 0.693030, acc.: 51.37%] [G loss: 0.694490]
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2806 [D loss: 0.693750, acc.: 49.02%] [G loss: 0.694399]
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2807 [D loss: 0.693540, acc.: 47.27%] [G loss: 0.695585]
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2808 [D loss: 0.694315, acc.: 46.88%] [G loss: 0.693400]
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2809 [D loss: 0.692940, acc.: 48.44%] [G loss: 0.693458]
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2810 [D loss: 0.693632, acc.: 50.98%] [G loss: 0.694290]
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2811 [D loss: 0.693337, acc.: 50.78%] [G loss: 0.693658]
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2812 [D loss: 0.693294, acc.: 49.41%] [G loss: 0.694763]
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2813 [D loss: 0.692804, acc.: 52.34%] [G loss: 0.694220]
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2814 [D loss: 0.693330, acc.: 49.61%] [G loss: 0.694556]
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2815 [D loss: 0.693262, acc.: 50.39%] [G loss: 0.694190]
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2816 [D loss: 0.693245, acc.: 48.44%] [G loss: 0.694302]
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2817 [D loss: 0.693645, acc.: 48.83%] [G loss: 0.695908]
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2818 [D loss: 0.693186, acc.: 49.22%] [G loss: 0.694145]
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2819 [D loss: 0.693542, acc.: 50.00%] [G loss: 0.695834]
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2820 [D loss: 0.693150, acc.: 48.63%] [G loss: 0.693809]
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2821 [D loss: 0.692951, acc.: 50.59%] [G loss: 0.693596]
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2822 [D loss: 0.693145, acc.: 51.95%] [G loss: 0.693081]
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2823 [D loss: 0.692681, acc.: 51.17%] [G loss: 0.694120]
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2824 [D loss: 0.693522, acc.: 50.98%] [G loss: 0.693595]
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2825 [D loss: 0.693627, acc.: 48.05%] [G loss: 0.693662]
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2826 [D loss: 0.694945, acc.: 45.90%] [G loss: 0.692862]
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2827 [D loss: 0.693681, acc.: 48.05%] [G loss: 0.692871]
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2828 [D loss: 0.693649, acc.: 48.83%] [G loss: 0.692392]
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2829 [D loss: 0.692934, acc.: 49.61%] [G loss: 0.693156]
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2830 [D loss: 0.694266, acc.: 46.68%] [G loss: 0.692353]
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2831 [D loss: 0.693101, acc.: 52.73%] [G loss: 0.694994]
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2832 [D loss: 0.692917, acc.: 52.93%] [G loss: 0.693566]
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2833 [D loss: 0.694408, acc.: 43.95%] [G loss: 0.694731]
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2834 [D loss: 0.692928, acc.: 50.78%] [G loss: 0.693896]
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2835 [D loss: 0.693766, acc.: 51.37%] [G loss: 0.692873]
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2836 [D loss: 0.692581, acc.: 52.34%] [G loss: 0.693214]
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2837 [D loss: 0.693800, acc.: 50.00%] [G loss: 0.694561]
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2838 [D loss: 0.693359, acc.: 51.95%] [G loss: 0.693967]
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2839 [D loss: 0.693358, acc.: 48.24%] [G loss: 0.694999]
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2840 [D loss: 0.693823, acc.: 47.85%] [G loss: 0.694898]
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2841 [D loss: 0.693723, acc.: 47.66%] [G loss: 0.693646]
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2842 [D loss: 0.693373, acc.: 49.80%] [G loss: 0.694262]
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2843 [D loss: 0.692231, acc.: 52.93%] [G loss: 0.695218]
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2844 [D loss: 0.693973, acc.: 47.85%] [G loss: 0.695463]
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2845 [D loss: 0.693296, acc.: 48.63%] [G loss: 0.694087]
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2846 [D loss: 0.694762, acc.: 44.14%] [G loss: 0.695017]
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2847 [D loss: 0.693936, acc.: 45.70%] [G loss: 0.694561]
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2848 [D loss: 0.694025, acc.: 47.27%] [G loss: 0.693091]
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2849 [D loss: 0.693114, acc.: 52.15%] [G loss: 0.696672]
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2850 [D loss: 0.693679, acc.: 49.80%] [G loss: 0.694914]
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2851 [D loss: 0.693722, acc.: 46.09%] [G loss: 0.693636]
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2852 [D loss: 0.693765, acc.: 50.39%] [G loss: 0.694081]
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2853 [D loss: 0.693071, acc.: 53.12%] [G loss: 0.695116]
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2854 [D loss: 0.694280, acc.: 48.05%] [G loss: 0.694012]
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2855 [D loss: 0.694288, acc.: 43.55%] [G loss: 0.694581]
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2856 [D loss: 0.693229, acc.: 48.05%] [G loss: 0.694491]
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2857 [D loss: 0.692361, acc.: 53.71%] [G loss: 0.695241]
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2858 [D loss: 0.693270, acc.: 50.00%] [G loss: 0.695414]
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2859 [D loss: 0.692650, acc.: 53.52%] [G loss: 0.694621]
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2860 [D loss: 0.692969, acc.: 52.73%] [G loss: 0.694927]
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2861 [D loss: 0.692653, acc.: 52.54%] [G loss: 0.695085]
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2862 [D loss: 0.693544, acc.: 48.24%] [G loss: 0.694634]
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2863 [D loss: 0.692908, acc.: 50.00%] [G loss: 0.695125]
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2864 [D loss: 0.692901, acc.: 49.41%] [G loss: 0.696323]
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2865 [D loss: 0.691953, acc.: 55.27%] [G loss: 0.695189]
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2866 [D loss: 0.691991, acc.: 54.10%] [G loss: 0.695272]
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2867 [D loss: 0.693018, acc.: 49.80%] [G loss: 0.695451]
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2868 [D loss: 0.692373, acc.: 51.56%] [G loss: 0.693604]
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2869 [D loss: 0.692802, acc.: 50.78%] [G loss: 0.693997]
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2870 [D loss: 0.692714, acc.: 53.32%] [G loss: 0.691786]
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2871 [D loss: 0.693638, acc.: 50.00%] [G loss: 0.692485]
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2872 [D loss: 0.692548, acc.: 51.95%] [G loss: 0.691802]
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2873 [D loss: 0.692870, acc.: 54.10%] [G loss: 0.693782]
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2874 [D loss: 0.693425, acc.: 51.56%] [G loss: 0.691042]
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2875 [D loss: 0.693833, acc.: 50.98%] [G loss: 0.694263]
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2876 [D loss: 0.694820, acc.: 42.97%] [G loss: 0.693526]
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2877 [D loss: 0.693745, acc.: 50.98%] [G loss: 0.690395]
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2878 [D loss: 0.693827, acc.: 46.48%] [G loss: 0.692331]
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2879 [D loss: 0.693030, acc.: 51.95%] [G loss: 0.691618]
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2880 [D loss: 0.694387, acc.: 48.63%] [G loss: 0.691411]
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2881 [D loss: 0.694679, acc.: 46.29%] [G loss: 0.692008]
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2882 [D loss: 0.694194, acc.: 50.39%] [G loss: 0.691490]
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2883 [D loss: 0.694698, acc.: 46.48%] [G loss: 0.691952]
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2884 [D loss: 0.694510, acc.: 45.12%] [G loss: 0.692628]
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2885 [D loss: 0.693652, acc.: 48.83%] [G loss: 0.692408]
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2886 [D loss: 0.694713, acc.: 46.29%] [G loss: 0.692280]
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2887 [D loss: 0.693958, acc.: 47.07%] [G loss: 0.692206]
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2888 [D loss: 0.693537, acc.: 49.02%] [G loss: 0.692089]
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2889 [D loss: 0.692698, acc.: 51.17%] [G loss: 0.692276]
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2890 [D loss: 0.693911, acc.: 47.66%] [G loss: 0.691084]
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2891 [D loss: 0.693292, acc.: 49.02%] [G loss: 0.692766]
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2892 [D loss: 0.693607, acc.: 49.02%] [G loss: 0.693065]
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2893 [D loss: 0.693798, acc.: 47.66%] [G loss: 0.694606]
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2894 [D loss: 0.693140, acc.: 52.54%] [G loss: 0.692902]
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2895 [D loss: 0.692725, acc.: 49.41%] [G loss: 0.694065]
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2896 [D loss: 0.692632, acc.: 53.71%] [G loss: 0.694955]
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2897 [D loss: 0.692555, acc.: 51.76%] [G loss: 0.694845]
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2898 [D loss: 0.691351, acc.: 57.03%] [G loss: 0.694077]
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2899 [D loss: 0.692720, acc.: 51.76%] [G loss: 0.695041]
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2900 [D loss: 0.692576, acc.: 52.15%] [G loss: 0.693807]
1/1 [==============================] - 0s 15ms/step
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2901 [D loss: 0.691397, acc.: 53.32%] [G loss: 0.694442]
8/8 [==============================] - 0s 2ms/step
2902 [D loss: 0.692109, acc.: 51.37%] [G loss: 0.692731]
8/8 [==============================] - 0s 2ms/step
2903 [D loss: 0.694120, acc.: 50.00%] [G loss: 0.693345]
8/8 [==============================] - 0s 2ms/step
2904 [D loss: 0.693478, acc.: 48.83%] [G loss: 0.691904]
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2905 [D loss: 0.692672, acc.: 51.56%] [G loss: 0.693337]
8/8 [==============================] - 0s 2ms/step
2906 [D loss: 0.694371, acc.: 45.70%] [G loss: 0.693771]
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2907 [D loss: 0.694460, acc.: 46.68%] [G loss: 0.694135]
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2908 [D loss: 0.693616, acc.: 50.20%] [G loss: 0.692396]
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2909 [D loss: 0.694074, acc.: 45.90%] [G loss: 0.692347]
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2910 [D loss: 0.694275, acc.: 45.12%] [G loss: 0.692015]
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2911 [D loss: 0.694354, acc.: 46.88%] [G loss: 0.693781]
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2912 [D loss: 0.692529, acc.: 50.98%] [G loss: 0.695129]
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2913 [D loss: 0.694376, acc.: 43.95%] [G loss: 0.695091]
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2914 [D loss: 0.692376, acc.: 55.08%] [G loss: 0.693919]
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2915 [D loss: 0.694495, acc.: 45.51%] [G loss: 0.693202]
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2916 [D loss: 0.692538, acc.: 51.37%] [G loss: 0.695318]
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2917 [D loss: 0.692757, acc.: 50.39%] [G loss: 0.695323]
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2918 [D loss: 0.693330, acc.: 50.20%] [G loss: 0.694086]
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2919 [D loss: 0.693483, acc.: 48.44%] [G loss: 0.695454]
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2920 [D loss: 0.693802, acc.: 47.66%] [G loss: 0.693595]
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2921 [D loss: 0.693484, acc.: 51.95%] [G loss: 0.694495]
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2922 [D loss: 0.693585, acc.: 51.37%] [G loss: 0.695388]
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2923 [D loss: 0.694197, acc.: 44.92%] [G loss: 0.694508]
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2924 [D loss: 0.694146, acc.: 49.41%] [G loss: 0.693980]
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2925 [D loss: 0.694051, acc.: 49.80%] [G loss: 0.695199]
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2926 [D loss: 0.692353, acc.: 52.34%] [G loss: 0.695269]
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2927 [D loss: 0.693118, acc.: 51.76%] [G loss: 0.693634]
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2928 [D loss: 0.693779, acc.: 49.61%] [G loss: 0.693564]
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2929 [D loss: 0.693864, acc.: 47.85%] [G loss: 0.695640]
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2930 [D loss: 0.694079, acc.: 47.46%] [G loss: 0.695791]
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2931 [D loss: 0.693576, acc.: 51.56%] [G loss: 0.693189]
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2932 [D loss: 0.694093, acc.: 48.44%] [G loss: 0.694295]
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2933 [D loss: 0.692957, acc.: 52.34%] [G loss: 0.694108]
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2934 [D loss: 0.694605, acc.: 45.12%] [G loss: 0.693362]
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2935 [D loss: 0.693703, acc.: 48.63%] [G loss: 0.693271]
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2936 [D loss: 0.693650, acc.: 49.22%] [G loss: 0.691466]
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2937 [D loss: 0.694114, acc.: 47.07%] [G loss: 0.693359]
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2938 [D loss: 0.693999, acc.: 47.46%] [G loss: 0.694130]
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2939 [D loss: 0.694629, acc.: 48.24%] [G loss: 0.693165]
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2940 [D loss: 0.693458, acc.: 47.46%] [G loss: 0.695361]
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2941 [D loss: 0.692937, acc.: 52.54%] [G loss: 0.694616]
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2942 [D loss: 0.693052, acc.: 50.39%] [G loss: 0.694845]
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2943 [D loss: 0.693230, acc.: 47.46%] [G loss: 0.694211]
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2944 [D loss: 0.693245, acc.: 49.22%] [G loss: 0.694095]
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2945 [D loss: 0.692281, acc.: 51.37%] [G loss: 0.694541]
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2946 [D loss: 0.693526, acc.: 50.39%] [G loss: 0.694352]
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2947 [D loss: 0.692822, acc.: 51.17%] [G loss: 0.694571]
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2948 [D loss: 0.692790, acc.: 51.56%] [G loss: 0.694181]
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2949 [D loss: 0.693252, acc.: 48.83%] [G loss: 0.694917]
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2950 [D loss: 0.692824, acc.: 51.37%] [G loss: 0.696033]
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2951 [D loss: 0.692986, acc.: 53.71%] [G loss: 0.694969]
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2952 [D loss: 0.693023, acc.: 51.37%] [G loss: 0.695576]
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2953 [D loss: 0.693217, acc.: 49.22%] [G loss: 0.694582]
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2954 [D loss: 0.693034, acc.: 51.37%] [G loss: 0.694584]
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2955 [D loss: 0.692986, acc.: 52.34%] [G loss: 0.693816]
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2956 [D loss: 0.694219, acc.: 47.46%] [G loss: 0.693666]
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2957 [D loss: 0.692504, acc.: 51.17%] [G loss: 0.693345]
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2958 [D loss: 0.692712, acc.: 52.73%] [G loss: 0.694439]
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2959 [D loss: 0.693900, acc.: 48.44%] [G loss: 0.692752]
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2960 [D loss: 0.693400, acc.: 47.46%] [G loss: 0.692053]
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2961 [D loss: 0.693394, acc.: 50.78%] [G loss: 0.691400]
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2962 [D loss: 0.693075, acc.: 49.22%] [G loss: 0.693778]
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2963 [D loss: 0.693774, acc.: 50.78%] [G loss: 0.693399]
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2964 [D loss: 0.692522, acc.: 51.56%] [G loss: 0.691985]
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2965 [D loss: 0.693449, acc.: 48.63%] [G loss: 0.691943]
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2966 [D loss: 0.694333, acc.: 48.05%] [G loss: 0.692740]
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2967 [D loss: 0.694307, acc.: 49.02%] [G loss: 0.692954]
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2968 [D loss: 0.693035, acc.: 51.17%] [G loss: 0.693061]
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2969 [D loss: 0.694903, acc.: 43.36%] [G loss: 0.692092]
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2970 [D loss: 0.693310, acc.: 49.22%] [G loss: 0.692031]
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2971 [D loss: 0.692749, acc.: 51.76%] [G loss: 0.691552]
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2972 [D loss: 0.693141, acc.: 51.76%] [G loss: 0.690607]
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2973 [D loss: 0.693492, acc.: 47.46%] [G loss: 0.691020]
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2974 [D loss: 0.693953, acc.: 48.05%] [G loss: 0.692396]
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2975 [D loss: 0.693979, acc.: 49.22%] [G loss: 0.693221]
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2976 [D loss: 0.694229, acc.: 45.90%] [G loss: 0.693717]
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2977 [D loss: 0.693162, acc.: 52.54%] [G loss: 0.692508]
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2978 [D loss: 0.693697, acc.: 48.05%] [G loss: 0.693769]
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2979 [D loss: 0.693252, acc.: 51.95%] [G loss: 0.694115]
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2980 [D loss: 0.692778, acc.: 52.34%] [G loss: 0.692899]
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2981 [D loss: 0.693496, acc.: 48.24%] [G loss: 0.693408]
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2982 [D loss: 0.691683, acc.: 54.88%] [G loss: 0.693617]
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2983 [D loss: 0.692613, acc.: 52.54%] [G loss: 0.692262]
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2984 [D loss: 0.693233, acc.: 51.56%] [G loss: 0.691857]
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2985 [D loss: 0.692173, acc.: 53.91%] [G loss: 0.692467]
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2986 [D loss: 0.693055, acc.: 50.78%] [G loss: 0.692923]
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2987 [D loss: 0.692814, acc.: 51.37%] [G loss: 0.695005]
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2988 [D loss: 0.693666, acc.: 47.27%] [G loss: 0.692706]
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2989 [D loss: 0.692846, acc.: 51.95%] [G loss: 0.693418]
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2990 [D loss: 0.693933, acc.: 48.05%] [G loss: 0.695743]
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2991 [D loss: 0.693074, acc.: 51.37%] [G loss: 0.693028]
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2992 [D loss: 0.692625, acc.: 50.39%] [G loss: 0.693378]
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2993 [D loss: 0.693230, acc.: 50.98%] [G loss: 0.694540]
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2994 [D loss: 0.693317, acc.: 51.95%] [G loss: 0.692828]
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2995 [D loss: 0.692864, acc.: 51.17%] [G loss: 0.693279]
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2996 [D loss: 0.693659, acc.: 51.17%] [G loss: 0.694645]
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2997 [D loss: 0.694773, acc.: 46.48%] [G loss: 0.693190]
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2998 [D loss: 0.693927, acc.: 48.44%] [G loss: 0.692283]
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2999 [D loss: 0.694701, acc.: 46.48%] [G loss: 0.693583]
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3000 [D loss: 0.694006, acc.: 48.05%] [G loss: 0.692644]
1/1 [==============================] - 0s 15ms/step
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3001 [D loss: 0.694095, acc.: 48.05%] [G loss: 0.692296]
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3002 [D loss: 0.694354, acc.: 46.29%] [G loss: 0.691298]
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3003 [D loss: 0.694387, acc.: 47.46%] [G loss: 0.692843]
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3004 [D loss: 0.693516, acc.: 49.41%] [G loss: 0.692878]
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3005 [D loss: 0.694367, acc.: 44.53%] [G loss: 0.694780]
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3006 [D loss: 0.694078, acc.: 46.29%] [G loss: 0.694842]
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3007 [D loss: 0.692984, acc.: 51.17%] [G loss: 0.694508]
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3008 [D loss: 0.693934, acc.: 48.05%] [G loss: 0.696468]
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3009 [D loss: 0.692648, acc.: 52.54%] [G loss: 0.696254]
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3010 [D loss: 0.693210, acc.: 50.59%] [G loss: 0.694606]
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3011 [D loss: 0.693583, acc.: 49.61%] [G loss: 0.694490]
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3012 [D loss: 0.694024, acc.: 48.05%] [G loss: 0.696402]
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3013 [D loss: 0.692890, acc.: 50.39%] [G loss: 0.694587]
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3014 [D loss: 0.693245, acc.: 50.39%] [G loss: 0.696097]
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3015 [D loss: 0.693922, acc.: 49.22%] [G loss: 0.696779]
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3016 [D loss: 0.693449, acc.: 49.02%] [G loss: 0.695471]
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3017 [D loss: 0.693457, acc.: 48.63%] [G loss: 0.693946]
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3018 [D loss: 0.693421, acc.: 49.80%] [G loss: 0.695564]
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3019 [D loss: 0.694304, acc.: 45.70%] [G loss: 0.696609]
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3020 [D loss: 0.694575, acc.: 47.07%] [G loss: 0.696438]
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3021 [D loss: 0.693932, acc.: 47.66%] [G loss: 0.695919]
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3022 [D loss: 0.692651, acc.: 54.69%] [G loss: 0.696904]
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3023 [D loss: 0.693081, acc.: 50.39%] [G loss: 0.697004]
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3024 [D loss: 0.692944, acc.: 50.78%] [G loss: 0.696838]
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3025 [D loss: 0.693448, acc.: 48.44%] [G loss: 0.695546]
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3026 [D loss: 0.692429, acc.: 52.15%] [G loss: 0.695146]
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3027 [D loss: 0.692893, acc.: 49.02%] [G loss: 0.694802]
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3028 [D loss: 0.693858, acc.: 49.02%] [G loss: 0.694893]
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3029 [D loss: 0.692708, acc.: 51.17%] [G loss: 0.694720]
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3030 [D loss: 0.693508, acc.: 51.17%] [G loss: 0.694717]
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3031 [D loss: 0.691923, acc.: 56.25%] [G loss: 0.695790]
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3032 [D loss: 0.692651, acc.: 50.98%] [G loss: 0.694979]
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3033 [D loss: 0.693166, acc.: 50.20%] [G loss: 0.695661]
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3034 [D loss: 0.693387, acc.: 49.41%] [G loss: 0.695379]
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3035 [D loss: 0.693077, acc.: 49.41%] [G loss: 0.694154]
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3036 [D loss: 0.692916, acc.: 49.41%] [G loss: 0.693812]
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3037 [D loss: 0.692966, acc.: 50.78%] [G loss: 0.692420]
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3038 [D loss: 0.693817, acc.: 48.44%] [G loss: 0.692886]
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3039 [D loss: 0.692925, acc.: 49.22%] [G loss: 0.693367]
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3040 [D loss: 0.692798, acc.: 52.15%] [G loss: 0.693578]
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3041 [D loss: 0.692593, acc.: 52.73%] [G loss: 0.692395]
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3042 [D loss: 0.693263, acc.: 50.39%] [G loss: 0.693215]
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3043 [D loss: 0.694080, acc.: 45.31%] [G loss: 0.693212]
8/8 [==============================] - 0s 2ms/step
3044 [D loss: 0.693370, acc.: 49.41%] [G loss: 0.694145]
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3045 [D loss: 0.694127, acc.: 46.09%] [G loss: 0.693772]
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3046 [D loss: 0.693582, acc.: 49.61%] [G loss: 0.692632]
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3047 [D loss: 0.693772, acc.: 48.44%] [G loss: 0.692071]
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3048 [D loss: 0.693775, acc.: 49.41%] [G loss: 0.692280]
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3049 [D loss: 0.692796, acc.: 54.88%] [G loss: 0.691853]
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3050 [D loss: 0.694487, acc.: 45.90%] [G loss: 0.692647]
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3051 [D loss: 0.694494, acc.: 47.27%] [G loss: 0.690990]
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3052 [D loss: 0.693074, acc.: 48.63%] [G loss: 0.691468]
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3053 [D loss: 0.693542, acc.: 48.63%] [G loss: 0.691423]
8/8 [==============================] - 0s 2ms/step
3054 [D loss: 0.693145, acc.: 51.56%] [G loss: 0.689910]
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3055 [D loss: 0.693648, acc.: 51.56%] [G loss: 0.691199]
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3056 [D loss: 0.693366, acc.: 51.37%] [G loss: 0.693359]
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3057 [D loss: 0.692976, acc.: 51.17%] [G loss: 0.690996]
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3058 [D loss: 0.694054, acc.: 47.85%] [G loss: 0.691596]
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3059 [D loss: 0.693978, acc.: 47.66%] [G loss: 0.692575]
8/8 [==============================] - 0s 2ms/step
3060 [D loss: 0.694301, acc.: 50.39%] [G loss: 0.691675]
8/8 [==============================] - 0s 2ms/step
3061 [D loss: 0.693731, acc.: 48.44%] [G loss: 0.690566]
8/8 [==============================] - 0s 2ms/step
3062 [D loss: 0.694498, acc.: 46.29%] [G loss: 0.692113]
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3063 [D loss: 0.693071, acc.: 49.22%] [G loss: 0.693614]
8/8 [==============================] - 0s 2ms/step
3064 [D loss: 0.693652, acc.: 47.66%] [G loss: 0.693177]
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3065 [D loss: 0.693053, acc.: 48.63%] [G loss: 0.694293]
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3066 [D loss: 0.693167, acc.: 49.61%] [G loss: 0.695081]
8/8 [==============================] - 0s 2ms/step
3067 [D loss: 0.692424, acc.: 50.78%] [G loss: 0.695345]
8/8 [==============================] - 0s 2ms/step
3068 [D loss: 0.692780, acc.: 52.73%] [G loss: 0.694083]
8/8 [==============================] - 0s 2ms/step
3069 [D loss: 0.692924, acc.: 52.15%] [G loss: 0.693403]
8/8 [==============================] - 0s 2ms/step
3070 [D loss: 0.692800, acc.: 53.32%] [G loss: 0.693203]
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3071 [D loss: 0.692627, acc.: 52.34%] [G loss: 0.692769]
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3072 [D loss: 0.693938, acc.: 44.73%] [G loss: 0.693383]
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3073 [D loss: 0.692796, acc.: 52.34%] [G loss: 0.695783]
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3074 [D loss: 0.692426, acc.: 53.91%] [G loss: 0.693383]
8/8 [==============================] - 0s 2ms/step
3075 [D loss: 0.692612, acc.: 52.54%] [G loss: 0.693483]
8/8 [==============================] - 0s 2ms/step
3076 [D loss: 0.692448, acc.: 51.17%] [G loss: 0.694400]
8/8 [==============================] - 0s 2ms/step
3077 [D loss: 0.693181, acc.: 50.00%] [G loss: 0.694534]
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3078 [D loss: 0.693963, acc.: 46.09%] [G loss: 0.694320]
8/8 [==============================] - 0s 2ms/step
3079 [D loss: 0.693221, acc.: 47.07%] [G loss: 0.695166]
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3080 [D loss: 0.694136, acc.: 47.07%] [G loss: 0.694350]
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3081 [D loss: 0.694265, acc.: 47.07%] [G loss: 0.694506]
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3082 [D loss: 0.693031, acc.: 51.37%] [G loss: 0.693852]
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3083 [D loss: 0.693264, acc.: 47.66%] [G loss: 0.695411]
8/8 [==============================] - 0s 2ms/step
3084 [D loss: 0.693243, acc.: 48.44%] [G loss: 0.695723]
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3085 [D loss: 0.692747, acc.: 50.98%] [G loss: 0.696779]
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3086 [D loss: 0.693714, acc.: 50.78%] [G loss: 0.697515]
8/8 [==============================] - 0s 2ms/step
3087 [D loss: 0.692800, acc.: 52.54%] [G loss: 0.694476]
8/8 [==============================] - 0s 2ms/step
3088 [D loss: 0.694274, acc.: 49.41%] [G loss: 0.696316]
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3089 [D loss: 0.693846, acc.: 48.44%] [G loss: 0.695342]
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3090 [D loss: 0.692540, acc.: 51.56%] [G loss: 0.694809]
8/8 [==============================] - 0s 2ms/step
3091 [D loss: 0.693161, acc.: 48.83%] [G loss: 0.694663]
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3092 [D loss: 0.693882, acc.: 47.46%] [G loss: 0.694598]
8/8 [==============================] - 0s 2ms/step
3093 [D loss: 0.694182, acc.: 47.27%] [G loss: 0.694343]
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3094 [D loss: 0.693228, acc.: 49.02%] [G loss: 0.693276]
8/8 [==============================] - 0s 2ms/step
3095 [D loss: 0.693404, acc.: 49.80%] [G loss: 0.693283]
8/8 [==============================] - 0s 2ms/step
3096 [D loss: 0.694150, acc.: 47.85%] [G loss: 0.691458]
8/8 [==============================] - 0s 2ms/step
3097 [D loss: 0.693815, acc.: 47.27%] [G loss: 0.692475]
8/8 [==============================] - 0s 2ms/step
3098 [D loss: 0.693762, acc.: 48.24%] [G loss: 0.693511]
8/8 [==============================] - 0s 2ms/step
3099 [D loss: 0.693781, acc.: 47.66%] [G loss: 0.693330]
8/8 [==============================] - 0s 2ms/step
3100 [D loss: 0.692323, acc.: 53.12%] [G loss: 0.694362]
1/1 [==============================] - 0s 16ms/step
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3101 [D loss: 0.693410, acc.: 50.39%] [G loss: 0.693695]
8/8 [==============================] - 0s 2ms/step
3102 [D loss: 0.693128, acc.: 49.02%] [G loss: 0.694792]
8/8 [==============================] - 0s 2ms/step
3103 [D loss: 0.694004, acc.: 46.09%] [G loss: 0.693354]
8/8 [==============================] - 0s 2ms/step
3104 [D loss: 0.693182, acc.: 50.20%] [G loss: 0.692638]
8/8 [==============================] - 0s 2ms/step
3105 [D loss: 0.694277, acc.: 47.07%] [G loss: 0.693287]
8/8 [==============================] - 0s 2ms/step
3106 [D loss: 0.692424, acc.: 52.34%] [G loss: 0.694183]
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3107 [D loss: 0.694332, acc.: 48.05%] [G loss: 0.693935]
8/8 [==============================] - 0s 2ms/step
3108 [D loss: 0.693285, acc.: 49.02%] [G loss: 0.692311]
8/8 [==============================] - 0s 2ms/step
3109 [D loss: 0.692308, acc.: 52.15%] [G loss: 0.692700]
8/8 [==============================] - 0s 2ms/step
3110 [D loss: 0.693906, acc.: 49.02%] [G loss: 0.694219]
8/8 [==============================] - 0s 2ms/step
3111 [D loss: 0.693549, acc.: 50.78%] [G loss: 0.694338]
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3112 [D loss: 0.692746, acc.: 51.17%] [G loss: 0.693755]
8/8 [==============================] - 0s 2ms/step
3113 [D loss: 0.693305, acc.: 52.15%] [G loss: 0.692660]
8/8 [==============================] - 0s 2ms/step
3114 [D loss: 0.692974, acc.: 49.02%] [G loss: 0.694792]
8/8 [==============================] - 0s 2ms/step
3115 [D loss: 0.694151, acc.: 48.44%] [G loss: 0.693089]
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3116 [D loss: 0.692994, acc.: 48.63%] [G loss: 0.693663]
8/8 [==============================] - 0s 2ms/step
3117 [D loss: 0.694158, acc.: 46.88%] [G loss: 0.693454]
8/8 [==============================] - 0s 2ms/step
3118 [D loss: 0.693530, acc.: 47.66%] [G loss: 0.693815]
8/8 [==============================] - 0s 2ms/step
3119 [D loss: 0.692717, acc.: 48.83%] [G loss: 0.694807]
8/8 [==============================] - 0s 2ms/step
3120 [D loss: 0.692308, acc.: 53.91%] [G loss: 0.694994]
8/8 [==============================] - 0s 2ms/step
3121 [D loss: 0.693526, acc.: 50.39%] [G loss: 0.695387]
8/8 [==============================] - 0s 2ms/step
3122 [D loss: 0.692151, acc.: 53.71%] [G loss: 0.696146]
8/8 [==============================] - 0s 2ms/step
3123 [D loss: 0.692692, acc.: 53.32%] [G loss: 0.694580]
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3124 [D loss: 0.693287, acc.: 50.00%] [G loss: 0.693628]
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3125 [D loss: 0.693447, acc.: 48.63%] [G loss: 0.694209]
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3126 [D loss: 0.692788, acc.: 52.54%] [G loss: 0.695112]
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3127 [D loss: 0.693069, acc.: 50.39%] [G loss: 0.694046]
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3128 [D loss: 0.692857, acc.: 53.32%] [G loss: 0.694559]
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3129 [D loss: 0.692922, acc.: 51.17%] [G loss: 0.692736]
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3130 [D loss: 0.693270, acc.: 50.20%] [G loss: 0.692996]
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3131 [D loss: 0.693497, acc.: 50.00%] [G loss: 0.691450]
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3132 [D loss: 0.693603, acc.: 48.83%] [G loss: 0.692816]
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3133 [D loss: 0.694328, acc.: 46.88%] [G loss: 0.692835]
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3134 [D loss: 0.693411, acc.: 50.78%] [G loss: 0.694557]
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3135 [D loss: 0.693563, acc.: 48.83%] [G loss: 0.695358]
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3136 [D loss: 0.694246, acc.: 44.73%] [G loss: 0.695196]
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3137 [D loss: 0.693128, acc.: 50.98%] [G loss: 0.694757]
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3138 [D loss: 0.693256, acc.: 49.02%] [G loss: 0.694554]
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3139 [D loss: 0.694167, acc.: 47.07%] [G loss: 0.693938]
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3140 [D loss: 0.693643, acc.: 50.39%] [G loss: 0.695380]
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3141 [D loss: 0.694076, acc.: 48.24%] [G loss: 0.694546]
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3142 [D loss: 0.693539, acc.: 47.66%] [G loss: 0.694226]
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3143 [D loss: 0.694481, acc.: 46.68%] [G loss: 0.694352]
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3144 [D loss: 0.692679, acc.: 50.00%] [G loss: 0.695136]
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3145 [D loss: 0.692959, acc.: 50.00%] [G loss: 0.694621]
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3146 [D loss: 0.693697, acc.: 49.80%] [G loss: 0.694739]
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3147 [D loss: 0.693461, acc.: 50.20%] [G loss: 0.696203]
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3148 [D loss: 0.693339, acc.: 52.15%] [G loss: 0.694758]
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3149 [D loss: 0.692558, acc.: 51.37%] [G loss: 0.694157]
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3150 [D loss: 0.693733, acc.: 47.85%] [G loss: 0.694595]
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3151 [D loss: 0.693740, acc.: 49.41%] [G loss: 0.694286]
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3152 [D loss: 0.693787, acc.: 47.46%] [G loss: 0.692828]
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3153 [D loss: 0.693637, acc.: 48.44%] [G loss: 0.694784]
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3154 [D loss: 0.693365, acc.: 49.02%] [G loss: 0.693658]
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3155 [D loss: 0.693854, acc.: 49.22%] [G loss: 0.693689]
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3156 [D loss: 0.693638, acc.: 49.41%] [G loss: 0.693250]
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3157 [D loss: 0.692964, acc.: 52.54%] [G loss: 0.693708]
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3158 [D loss: 0.693328, acc.: 46.68%] [G loss: 0.693454]
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3159 [D loss: 0.691872, acc.: 53.32%] [G loss: 0.694466]
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3160 [D loss: 0.694182, acc.: 47.46%] [G loss: 0.694080]
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3161 [D loss: 0.692591, acc.: 50.00%] [G loss: 0.693383]
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3162 [D loss: 0.693651, acc.: 46.88%] [G loss: 0.693731]
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3163 [D loss: 0.692437, acc.: 54.49%] [G loss: 0.694477]
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3164 [D loss: 0.692965, acc.: 50.59%] [G loss: 0.692791]
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3165 [D loss: 0.692638, acc.: 48.44%] [G loss: 0.693805]
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3166 [D loss: 0.692962, acc.: 52.34%] [G loss: 0.695704]
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3167 [D loss: 0.693616, acc.: 46.88%] [G loss: 0.693954]
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3168 [D loss: 0.693481, acc.: 51.56%] [G loss: 0.695540]
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3169 [D loss: 0.693073, acc.: 49.80%] [G loss: 0.694119]
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3170 [D loss: 0.692856, acc.: 52.34%] [G loss: 0.694161]
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3171 [D loss: 0.692716, acc.: 51.76%] [G loss: 0.694856]
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3172 [D loss: 0.693431, acc.: 49.61%] [G loss: 0.693287]
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3173 [D loss: 0.692908, acc.: 51.37%] [G loss: 0.694365]
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3174 [D loss: 0.692797, acc.: 50.98%] [G loss: 0.692501]
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3175 [D loss: 0.692977, acc.: 51.95%] [G loss: 0.694605]
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3176 [D loss: 0.693341, acc.: 49.80%] [G loss: 0.695279]
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3177 [D loss: 0.693856, acc.: 47.66%] [G loss: 0.694760]
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3178 [D loss: 0.692407, acc.: 54.10%] [G loss: 0.695336]
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3179 [D loss: 0.691288, acc.: 59.77%] [G loss: 0.695143]
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3180 [D loss: 0.692519, acc.: 50.59%] [G loss: 0.694009]
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3181 [D loss: 0.692697, acc.: 53.12%] [G loss: 0.695072]
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3182 [D loss: 0.693453, acc.: 47.46%] [G loss: 0.693294]
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3183 [D loss: 0.694002, acc.: 46.68%] [G loss: 0.693360]
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3184 [D loss: 0.692869, acc.: 51.56%] [G loss: 0.693051]
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3185 [D loss: 0.693943, acc.: 47.27%] [G loss: 0.691906]
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3186 [D loss: 0.694810, acc.: 43.16%] [G loss: 0.693537]
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3187 [D loss: 0.693594, acc.: 50.98%] [G loss: 0.693027]
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3188 [D loss: 0.694399, acc.: 46.29%] [G loss: 0.693755]
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3189 [D loss: 0.693149, acc.: 50.39%] [G loss: 0.691823]
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3190 [D loss: 0.694538, acc.: 48.44%] [G loss: 0.694525]
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3191 [D loss: 0.693608, acc.: 46.48%] [G loss: 0.693140]
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3192 [D loss: 0.693776, acc.: 49.02%] [G loss: 0.692959]
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3193 [D loss: 0.692848, acc.: 51.37%] [G loss: 0.695253]
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3194 [D loss: 0.693084, acc.: 49.41%] [G loss: 0.695584]
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3195 [D loss: 0.692859, acc.: 50.59%] [G loss: 0.696509]
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3196 [D loss: 0.693120, acc.: 50.20%] [G loss: 0.695370]
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3197 [D loss: 0.692887, acc.: 49.41%] [G loss: 0.695831]
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3198 [D loss: 0.692677, acc.: 49.80%] [G loss: 0.696485]
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3199 [D loss: 0.692769, acc.: 51.17%] [G loss: 0.695161]
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3200 [D loss: 0.693731, acc.: 48.83%] [G loss: 0.695270]
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3201 [D loss: 0.692990, acc.: 49.22%] [G loss: 0.696193]
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3202 [D loss: 0.694186, acc.: 46.48%] [G loss: 0.693429]
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3203 [D loss: 0.693441, acc.: 51.17%] [G loss: 0.694215]
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3204 [D loss: 0.693635, acc.: 49.22%] [G loss: 0.693908]
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3205 [D loss: 0.693556, acc.: 47.85%] [G loss: 0.694621]
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3206 [D loss: 0.694416, acc.: 45.90%] [G loss: 0.692809]
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3207 [D loss: 0.693015, acc.: 51.37%] [G loss: 0.694812]
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3208 [D loss: 0.693754, acc.: 50.78%] [G loss: 0.694350]
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3209 [D loss: 0.694094, acc.: 48.05%] [G loss: 0.694535]
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3210 [D loss: 0.693108, acc.: 48.63%] [G loss: 0.695197]
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3211 [D loss: 0.693026, acc.: 50.20%] [G loss: 0.694142]
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3212 [D loss: 0.693272, acc.: 49.02%] [G loss: 0.695217]
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3213 [D loss: 0.693279, acc.: 49.80%] [G loss: 0.694504]
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3214 [D loss: 0.693627, acc.: 49.22%] [G loss: 0.695463]
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3215 [D loss: 0.692954, acc.: 50.78%] [G loss: 0.695246]
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3216 [D loss: 0.692337, acc.: 53.52%] [G loss: 0.694872]
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3217 [D loss: 0.692817, acc.: 51.56%] [G loss: 0.695222]
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3218 [D loss: 0.692957, acc.: 50.20%] [G loss: 0.695031]
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3219 [D loss: 0.693248, acc.: 48.44%] [G loss: 0.695669]
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3220 [D loss: 0.692865, acc.: 49.41%] [G loss: 0.693464]
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3221 [D loss: 0.693010, acc.: 52.93%] [G loss: 0.695831]
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3222 [D loss: 0.692915, acc.: 50.78%] [G loss: 0.695032]
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3223 [D loss: 0.692500, acc.: 53.71%] [G loss: 0.694841]
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3224 [D loss: 0.693309, acc.: 51.56%] [G loss: 0.693971]
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3225 [D loss: 0.691555, acc.: 56.84%] [G loss: 0.693642]
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3226 [D loss: 0.693747, acc.: 50.39%] [G loss: 0.693126]
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3227 [D loss: 0.693051, acc.: 51.95%] [G loss: 0.694134]
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3228 [D loss: 0.692942, acc.: 49.80%] [G loss: 0.693958]
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3229 [D loss: 0.692603, acc.: 53.71%] [G loss: 0.695008]
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3230 [D loss: 0.692934, acc.: 53.52%] [G loss: 0.693421]
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3231 [D loss: 0.693060, acc.: 49.22%] [G loss: 0.694556]
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3232 [D loss: 0.692443, acc.: 52.54%] [G loss: 0.695260]
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3233 [D loss: 0.692521, acc.: 53.52%] [G loss: 0.693493]
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3234 [D loss: 0.692841, acc.: 53.12%] [G loss: 0.692506]
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3235 [D loss: 0.693103, acc.: 50.78%] [G loss: 0.692444]
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3236 [D loss: 0.693948, acc.: 46.88%] [G loss: 0.693592]
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3237 [D loss: 0.693400, acc.: 50.78%] [G loss: 0.694159]
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3238 [D loss: 0.694814, acc.: 44.92%] [G loss: 0.693262]
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3239 [D loss: 0.693485, acc.: 49.41%] [G loss: 0.692933]
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3240 [D loss: 0.693212, acc.: 50.98%] [G loss: 0.692943]
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3241 [D loss: 0.693083, acc.: 50.59%] [G loss: 0.692552]
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3242 [D loss: 0.693913, acc.: 48.05%] [G loss: 0.693940]
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3243 [D loss: 0.692876, acc.: 51.56%] [G loss: 0.693785]
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3244 [D loss: 0.693317, acc.: 52.93%] [G loss: 0.692477]
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3245 [D loss: 0.694792, acc.: 45.51%] [G loss: 0.692632]
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3246 [D loss: 0.693818, acc.: 48.44%] [G loss: 0.691864]
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3247 [D loss: 0.693523, acc.: 49.80%] [G loss: 0.692263]
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3248 [D loss: 0.693888, acc.: 48.63%] [G loss: 0.693063]
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3249 [D loss: 0.692933, acc.: 49.61%] [G loss: 0.694534]
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3250 [D loss: 0.693539, acc.: 49.41%] [G loss: 0.694174]
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3251 [D loss: 0.692506, acc.: 51.56%] [G loss: 0.694174]
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3252 [D loss: 0.692729, acc.: 51.37%] [G loss: 0.693765]
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3253 [D loss: 0.693475, acc.: 50.59%] [G loss: 0.693401]
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3254 [D loss: 0.692080, acc.: 53.12%] [G loss: 0.693765]
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3255 [D loss: 0.692757, acc.: 50.00%] [G loss: 0.694788]
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3256 [D loss: 0.692406, acc.: 53.52%] [G loss: 0.693858]
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3257 [D loss: 0.692844, acc.: 51.56%] [G loss: 0.694018]
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3258 [D loss: 0.693627, acc.: 49.41%] [G loss: 0.693414]
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3259 [D loss: 0.693466, acc.: 50.39%] [G loss: 0.694286]
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3260 [D loss: 0.693248, acc.: 48.24%] [G loss: 0.694647]
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3261 [D loss: 0.694291, acc.: 46.29%] [G loss: 0.693795]
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3262 [D loss: 0.692286, acc.: 54.10%] [G loss: 0.693876]
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3263 [D loss: 0.693472, acc.: 49.80%] [G loss: 0.694751]
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3264 [D loss: 0.693697, acc.: 49.41%] [G loss: 0.693930]
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3265 [D loss: 0.693984, acc.: 47.66%] [G loss: 0.693569]
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3266 [D loss: 0.694081, acc.: 44.92%] [G loss: 0.694380]
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3267 [D loss: 0.692480, acc.: 51.17%] [G loss: 0.695745]
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3268 [D loss: 0.693084, acc.: 52.93%] [G loss: 0.696185]
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3269 [D loss: 0.693551, acc.: 48.83%] [G loss: 0.696208]
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3270 [D loss: 0.693270, acc.: 49.41%] [G loss: 0.694925]
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3271 [D loss: 0.694006, acc.: 48.24%] [G loss: 0.696352]
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3272 [D loss: 0.692559, acc.: 53.32%] [G loss: 0.694227]
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3273 [D loss: 0.692831, acc.: 50.78%] [G loss: 0.696092]
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3274 [D loss: 0.693160, acc.: 50.78%] [G loss: 0.694801]
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3275 [D loss: 0.693434, acc.: 50.98%] [G loss: 0.695203]
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3276 [D loss: 0.693206, acc.: 51.17%] [G loss: 0.696276]
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3277 [D loss: 0.693913, acc.: 47.85%] [G loss: 0.693775]
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3278 [D loss: 0.692655, acc.: 50.39%] [G loss: 0.696024]
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3279 [D loss: 0.692544, acc.: 50.00%] [G loss: 0.695558]
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3280 [D loss: 0.693901, acc.: 49.02%] [G loss: 0.696579]
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3281 [D loss: 0.693456, acc.: 48.83%] [G loss: 0.694972]
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3282 [D loss: 0.693627, acc.: 49.02%] [G loss: 0.694594]
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3283 [D loss: 0.692474, acc.: 52.54%] [G loss: 0.695900]
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3284 [D loss: 0.692773, acc.: 48.44%] [G loss: 0.695114]
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3285 [D loss: 0.692102, acc.: 54.10%] [G loss: 0.694527]
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3286 [D loss: 0.692474, acc.: 51.56%] [G loss: 0.694984]
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3287 [D loss: 0.691063, acc.: 56.25%] [G loss: 0.696184]
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3288 [D loss: 0.693633, acc.: 47.85%] [G loss: 0.693515]
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3289 [D loss: 0.692163, acc.: 53.71%] [G loss: 0.695862]
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3290 [D loss: 0.693440, acc.: 48.05%] [G loss: 0.695582]
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3291 [D loss: 0.692108, acc.: 52.73%] [G loss: 0.694819]
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3292 [D loss: 0.691692, acc.: 54.10%] [G loss: 0.695470]
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3293 [D loss: 0.693850, acc.: 46.68%] [G loss: 0.693529]
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3294 [D loss: 0.693785, acc.: 49.61%] [G loss: 0.693431]
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3295 [D loss: 0.693970, acc.: 47.27%] [G loss: 0.692785]
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3296 [D loss: 0.695136, acc.: 45.70%] [G loss: 0.692575]
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3297 [D loss: 0.693071, acc.: 53.52%] [G loss: 0.692224]
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3298 [D loss: 0.694644, acc.: 45.31%] [G loss: 0.693625]
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3299 [D loss: 0.694834, acc.: 45.31%] [G loss: 0.693213]
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3300 [D loss: 0.694011, acc.: 45.31%] [G loss: 0.692146]
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3301 [D loss: 0.694135, acc.: 49.80%] [G loss: 0.692118]
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3302 [D loss: 0.694368, acc.: 45.90%] [G loss: 0.692851]
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3303 [D loss: 0.694457, acc.: 46.48%] [G loss: 0.694405]
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3304 [D loss: 0.693534, acc.: 48.05%] [G loss: 0.694595]
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3305 [D loss: 0.694322, acc.: 46.48%] [G loss: 0.694253]
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3306 [D loss: 0.694656, acc.: 43.95%] [G loss: 0.693149]
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3307 [D loss: 0.692763, acc.: 50.78%] [G loss: 0.694057]
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3308 [D loss: 0.694147, acc.: 47.85%] [G loss: 0.694404]
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3309 [D loss: 0.693945, acc.: 49.41%] [G loss: 0.694083]
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3310 [D loss: 0.693503, acc.: 49.02%] [G loss: 0.693335]
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3311 [D loss: 0.694028, acc.: 48.05%] [G loss: 0.694753]
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3312 [D loss: 0.693115, acc.: 51.56%] [G loss: 0.696386]
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3313 [D loss: 0.693442, acc.: 48.44%] [G loss: 0.696369]
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3314 [D loss: 0.692572, acc.: 52.34%] [G loss: 0.696817]
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3315 [D loss: 0.693264, acc.: 49.02%] [G loss: 0.696279]
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3316 [D loss: 0.692642, acc.: 53.91%] [G loss: 0.695964]
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3317 [D loss: 0.692613, acc.: 53.12%] [G loss: 0.693236]
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3318 [D loss: 0.693979, acc.: 47.66%] [G loss: 0.693208]
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3319 [D loss: 0.694136, acc.: 49.80%] [G loss: 0.692889]
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3320 [D loss: 0.693365, acc.: 52.34%] [G loss: 0.693941]
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3321 [D loss: 0.692866, acc.: 51.37%] [G loss: 0.693658]
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3322 [D loss: 0.694166, acc.: 48.63%] [G loss: 0.692912]
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3323 [D loss: 0.693352, acc.: 48.44%] [G loss: 0.693087]
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3324 [D loss: 0.693509, acc.: 47.07%] [G loss: 0.691819]
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3325 [D loss: 0.693154, acc.: 50.98%] [G loss: 0.693978]
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3326 [D loss: 0.692559, acc.: 53.12%] [G loss: 0.694070]
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3327 [D loss: 0.692662, acc.: 53.52%] [G loss: 0.694339]
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3328 [D loss: 0.692343, acc.: 51.95%] [G loss: 0.694173]
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3329 [D loss: 0.693855, acc.: 49.02%] [G loss: 0.694134]
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3330 [D loss: 0.693045, acc.: 50.59%] [G loss: 0.694578]
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3331 [D loss: 0.693610, acc.: 47.46%] [G loss: 0.694161]
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3332 [D loss: 0.692221, acc.: 52.34%] [G loss: 0.693150]
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3333 [D loss: 0.692375, acc.: 51.56%] [G loss: 0.693692]
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3334 [D loss: 0.692019, acc.: 53.91%] [G loss: 0.693545]
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3335 [D loss: 0.693120, acc.: 50.00%] [G loss: 0.693438]
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3336 [D loss: 0.693704, acc.: 49.02%] [G loss: 0.693599]
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3337 [D loss: 0.692682, acc.: 52.93%] [G loss: 0.694209]
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3338 [D loss: 0.693291, acc.: 49.80%] [G loss: 0.695769]
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3339 [D loss: 0.693606, acc.: 49.02%] [G loss: 0.693299]
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3340 [D loss: 0.693477, acc.: 48.44%] [G loss: 0.693665]
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3341 [D loss: 0.693924, acc.: 48.83%] [G loss: 0.693579]
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3342 [D loss: 0.693548, acc.: 48.05%] [G loss: 0.694604]
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3343 [D loss: 0.693114, acc.: 51.37%] [G loss: 0.693967]
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3344 [D loss: 0.693324, acc.: 50.20%] [G loss: 0.693795]
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3345 [D loss: 0.693975, acc.: 47.66%] [G loss: 0.694675]
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3346 [D loss: 0.693004, acc.: 49.61%] [G loss: 0.696232]
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3347 [D loss: 0.692993, acc.: 50.78%] [G loss: 0.696139]
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3348 [D loss: 0.693488, acc.: 50.78%] [G loss: 0.695750]
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3349 [D loss: 0.691952, acc.: 52.73%] [G loss: 0.694259]
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3350 [D loss: 0.693257, acc.: 49.22%] [G loss: 0.696421]
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3351 [D loss: 0.692837, acc.: 50.20%] [G loss: 0.696499]
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3352 [D loss: 0.693116, acc.: 50.39%] [G loss: 0.694413]
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3353 [D loss: 0.693941, acc.: 46.88%] [G loss: 0.694494]
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3354 [D loss: 0.693810, acc.: 45.31%] [G loss: 0.694927]
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3355 [D loss: 0.693840, acc.: 45.70%] [G loss: 0.694958]
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3356 [D loss: 0.693173, acc.: 50.78%] [G loss: 0.692789]
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3357 [D loss: 0.694489, acc.: 47.85%] [G loss: 0.693485]
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3358 [D loss: 0.693618, acc.: 50.20%] [G loss: 0.693402]
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3359 [D loss: 0.693738, acc.: 48.05%] [G loss: 0.693474]
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3360 [D loss: 0.693393, acc.: 46.88%] [G loss: 0.693534]
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3361 [D loss: 0.694326, acc.: 45.51%] [G loss: 0.695686]
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3362 [D loss: 0.693235, acc.: 48.44%] [G loss: 0.694436]
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3363 [D loss: 0.693386, acc.: 50.20%] [G loss: 0.695249]
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3364 [D loss: 0.692737, acc.: 52.93%] [G loss: 0.695819]
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3365 [D loss: 0.693450, acc.: 51.56%] [G loss: 0.693784]
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3366 [D loss: 0.693088, acc.: 49.22%] [G loss: 0.695026]
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3367 [D loss: 0.693163, acc.: 50.78%] [G loss: 0.695318]
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3368 [D loss: 0.692424, acc.: 51.95%] [G loss: 0.694773]
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3369 [D loss: 0.693977, acc.: 48.44%] [G loss: 0.694449]
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3370 [D loss: 0.693361, acc.: 51.56%] [G loss: 0.694864]
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3371 [D loss: 0.692950, acc.: 48.05%] [G loss: 0.693388]
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3372 [D loss: 0.692806, acc.: 50.98%] [G loss: 0.692961]
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3373 [D loss: 0.693732, acc.: 50.20%] [G loss: 0.693353]
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3374 [D loss: 0.694435, acc.: 47.66%] [G loss: 0.692238]
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3375 [D loss: 0.693619, acc.: 47.46%] [G loss: 0.693524]
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3376 [D loss: 0.692461, acc.: 54.10%] [G loss: 0.692994]
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3377 [D loss: 0.693105, acc.: 52.93%] [G loss: 0.693301]
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3378 [D loss: 0.693879, acc.: 44.92%] [G loss: 0.693422]
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3379 [D loss: 0.693428, acc.: 49.22%] [G loss: 0.693275]
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3380 [D loss: 0.693897, acc.: 48.63%] [G loss: 0.693631]
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3381 [D loss: 0.693797, acc.: 47.46%] [G loss: 0.694708]
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3382 [D loss: 0.692383, acc.: 50.78%] [G loss: 0.695226]
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3383 [D loss: 0.693821, acc.: 46.48%] [G loss: 0.695095]
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3384 [D loss: 0.692665, acc.: 52.54%] [G loss: 0.695120]
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3385 [D loss: 0.692436, acc.: 53.52%] [G loss: 0.697605]
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3386 [D loss: 0.692726, acc.: 51.17%] [G loss: 0.695588]
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3387 [D loss: 0.693041, acc.: 50.98%] [G loss: 0.695799]
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3388 [D loss: 0.692717, acc.: 50.20%] [G loss: 0.696713]
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3389 [D loss: 0.693367, acc.: 47.66%] [G loss: 0.696134]
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3390 [D loss: 0.693877, acc.: 46.29%] [G loss: 0.695138]
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3391 [D loss: 0.692810, acc.: 50.98%] [G loss: 0.695534]
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3392 [D loss: 0.693559, acc.: 51.17%] [G loss: 0.694222]
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3393 [D loss: 0.693663, acc.: 48.44%] [G loss: 0.694806]
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3394 [D loss: 0.692360, acc.: 52.93%] [G loss: 0.693418]
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3395 [D loss: 0.693709, acc.: 47.27%] [G loss: 0.695397]
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3396 [D loss: 0.693299, acc.: 50.20%] [G loss: 0.693516]
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3397 [D loss: 0.694791, acc.: 47.66%] [G loss: 0.693309]
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3398 [D loss: 0.692637, acc.: 54.88%] [G loss: 0.692664]
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3399 [D loss: 0.693538, acc.: 51.37%] [G loss: 0.692886]
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3400 [D loss: 0.694184, acc.: 46.48%] [G loss: 0.692975]
1/1 [==============================] - 0s 15ms/step
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3401 [D loss: 0.693113, acc.: 50.20%] [G loss: 0.694844]
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3402 [D loss: 0.693496, acc.: 49.61%] [G loss: 0.693066]
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3403 [D loss: 0.692207, acc.: 54.10%] [G loss: 0.692988]
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3404 [D loss: 0.693261, acc.: 48.63%] [G loss: 0.694351]
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3405 [D loss: 0.692903, acc.: 49.80%] [G loss: 0.694056]
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3406 [D loss: 0.692514, acc.: 53.71%] [G loss: 0.694870]
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3407 [D loss: 0.692621, acc.: 50.78%] [G loss: 0.694642]
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3408 [D loss: 0.693622, acc.: 47.66%] [G loss: 0.693040]
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3409 [D loss: 0.692142, acc.: 52.93%] [G loss: 0.692907]
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3410 [D loss: 0.694581, acc.: 48.05%] [G loss: 0.694220]
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3411 [D loss: 0.693749, acc.: 46.48%] [G loss: 0.692951]
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3412 [D loss: 0.693307, acc.: 48.44%] [G loss: 0.692642]
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3413 [D loss: 0.693443, acc.: 51.95%] [G loss: 0.693199]
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3414 [D loss: 0.693182, acc.: 51.17%] [G loss: 0.691540]
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3415 [D loss: 0.693561, acc.: 48.63%] [G loss: 0.693089]
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3416 [D loss: 0.692852, acc.: 51.76%] [G loss: 0.690942]
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3417 [D loss: 0.693907, acc.: 46.09%] [G loss: 0.689452]
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3418 [D loss: 0.693596, acc.: 50.39%] [G loss: 0.692572]
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3419 [D loss: 0.694099, acc.: 46.48%] [G loss: 0.693149]
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3420 [D loss: 0.694231, acc.: 48.05%] [G loss: 0.693594]
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3421 [D loss: 0.692320, acc.: 53.12%] [G loss: 0.694593]
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3422 [D loss: 0.692939, acc.: 50.98%] [G loss: 0.693873]
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3423 [D loss: 0.693598, acc.: 50.20%] [G loss: 0.695551]
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3424 [D loss: 0.691945, acc.: 54.10%] [G loss: 0.694745]
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3425 [D loss: 0.693048, acc.: 50.59%] [G loss: 0.694810]
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3426 [D loss: 0.693190, acc.: 51.56%] [G loss: 0.694001]
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3427 [D loss: 0.693909, acc.: 50.20%] [G loss: 0.694851]
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3428 [D loss: 0.693380, acc.: 48.24%] [G loss: 0.692347]
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3429 [D loss: 0.693307, acc.: 47.85%] [G loss: 0.693892]
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3430 [D loss: 0.693903, acc.: 45.70%] [G loss: 0.694311]
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3431 [D loss: 0.693819, acc.: 49.41%] [G loss: 0.695053]
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3432 [D loss: 0.693554, acc.: 50.00%] [G loss: 0.693473]
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3433 [D loss: 0.694443, acc.: 43.95%] [G loss: 0.693999]
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3434 [D loss: 0.693785, acc.: 47.27%] [G loss: 0.694333]
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3435 [D loss: 0.694450, acc.: 43.95%] [G loss: 0.694655]
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3436 [D loss: 0.693132, acc.: 48.83%] [G loss: 0.693068]
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3437 [D loss: 0.693797, acc.: 48.63%] [G loss: 0.693791]
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3438 [D loss: 0.693180, acc.: 50.78%] [G loss: 0.694141]
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3439 [D loss: 0.692061, acc.: 54.88%] [G loss: 0.696173]
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3440 [D loss: 0.693288, acc.: 50.59%] [G loss: 0.694769]
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3441 [D loss: 0.694061, acc.: 47.07%] [G loss: 0.695509]
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3442 [D loss: 0.692595, acc.: 52.34%] [G loss: 0.694603]
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3443 [D loss: 0.694460, acc.: 47.85%] [G loss: 0.694620]
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3444 [D loss: 0.693317, acc.: 50.59%] [G loss: 0.693922]
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3445 [D loss: 0.693484, acc.: 50.98%] [G loss: 0.695193]
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3446 [D loss: 0.692239, acc.: 57.42%] [G loss: 0.693907]
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3447 [D loss: 0.692787, acc.: 50.78%] [G loss: 0.695461]
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3448 [D loss: 0.693023, acc.: 49.61%] [G loss: 0.694256]
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3449 [D loss: 0.692537, acc.: 52.54%] [G loss: 0.694295]
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3450 [D loss: 0.692709, acc.: 50.39%] [G loss: 0.694480]
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3451 [D loss: 0.693239, acc.: 50.00%] [G loss: 0.693819]
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3452 [D loss: 0.692950, acc.: 52.73%] [G loss: 0.693635]
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3453 [D loss: 0.693525, acc.: 50.00%] [G loss: 0.694298]
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3454 [D loss: 0.693872, acc.: 46.48%] [G loss: 0.694848]
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3455 [D loss: 0.693501, acc.: 50.78%] [G loss: 0.694243]
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3456 [D loss: 0.693158, acc.: 50.78%] [G loss: 0.693765]
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3457 [D loss: 0.693380, acc.: 51.95%] [G loss: 0.695773]
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3458 [D loss: 0.692692, acc.: 52.73%] [G loss: 0.696104]
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3459 [D loss: 0.693732, acc.: 50.39%] [G loss: 0.695856]
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3460 [D loss: 0.692632, acc.: 53.91%] [G loss: 0.697123]
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3461 [D loss: 0.692239, acc.: 53.91%] [G loss: 0.695135]
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3462 [D loss: 0.692387, acc.: 53.52%] [G loss: 0.694757]
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3463 [D loss: 0.692970, acc.: 49.80%] [G loss: 0.696243]
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3464 [D loss: 0.692737, acc.: 50.59%] [G loss: 0.695650]
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3465 [D loss: 0.692215, acc.: 52.15%] [G loss: 0.693778]
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3466 [D loss: 0.692583, acc.: 51.37%] [G loss: 0.693391]
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3467 [D loss: 0.693379, acc.: 51.17%] [G loss: 0.693705]
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3468 [D loss: 0.692570, acc.: 54.30%] [G loss: 0.693579]
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3469 [D loss: 0.693434, acc.: 47.85%] [G loss: 0.694109]
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3470 [D loss: 0.693082, acc.: 52.15%] [G loss: 0.693040]
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3471 [D loss: 0.692736, acc.: 50.20%] [G loss: 0.693490]
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3472 [D loss: 0.693166, acc.: 48.63%] [G loss: 0.693531]
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3473 [D loss: 0.693926, acc.: 46.88%] [G loss: 0.693686]
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3474 [D loss: 0.693098, acc.: 50.98%] [G loss: 0.693640]
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3475 [D loss: 0.693516, acc.: 47.27%] [G loss: 0.693219]
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3476 [D loss: 0.694972, acc.: 44.92%] [G loss: 0.693392]
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3477 [D loss: 0.693594, acc.: 49.41%] [G loss: 0.693073]
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3478 [D loss: 0.692716, acc.: 51.56%] [G loss: 0.692215]
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3479 [D loss: 0.693622, acc.: 47.07%] [G loss: 0.694110]
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3480 [D loss: 0.692761, acc.: 51.56%] [G loss: 0.694014]
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3481 [D loss: 0.693821, acc.: 45.51%] [G loss: 0.694504]
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3482 [D loss: 0.692097, acc.: 54.49%] [G loss: 0.694564]
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3483 [D loss: 0.693460, acc.: 49.41%] [G loss: 0.694371]
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3484 [D loss: 0.693806, acc.: 49.41%] [G loss: 0.696361]
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3485 [D loss: 0.693295, acc.: 50.20%] [G loss: 0.694382]
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3486 [D loss: 0.692858, acc.: 51.37%] [G loss: 0.694308]
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3487 [D loss: 0.692793, acc.: 50.98%] [G loss: 0.692551]
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3488 [D loss: 0.692816, acc.: 50.20%] [G loss: 0.692975]
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3489 [D loss: 0.694660, acc.: 45.51%] [G loss: 0.693761]
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3490 [D loss: 0.693826, acc.: 50.78%] [G loss: 0.691951]
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3491 [D loss: 0.691860, acc.: 55.86%] [G loss: 0.691551]
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3492 [D loss: 0.692926, acc.: 48.83%] [G loss: 0.691252]
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3493 [D loss: 0.694160, acc.: 46.88%] [G loss: 0.691091]
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3494 [D loss: 0.693654, acc.: 48.44%] [G loss: 0.690323]
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3495 [D loss: 0.693014, acc.: 49.80%] [G loss: 0.691932]
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3496 [D loss: 0.694245, acc.: 49.02%] [G loss: 0.693267]
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3497 [D loss: 0.693116, acc.: 51.37%] [G loss: 0.694098]
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3498 [D loss: 0.693872, acc.: 47.66%] [G loss: 0.694221]
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3499 [D loss: 0.693518, acc.: 49.80%] [G loss: 0.694715]
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3500 [D loss: 0.694020, acc.: 45.12%] [G loss: 0.693032]
1/1 [==============================] - 0s 15ms/step
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3501 [D loss: 0.693229, acc.: 49.22%] [G loss: 0.694126]
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3502 [D loss: 0.692405, acc.: 51.17%] [G loss: 0.693988]
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3503 [D loss: 0.693248, acc.: 50.39%] [G loss: 0.694056]
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3504 [D loss: 0.692957, acc.: 52.15%] [G loss: 0.696013]
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3505 [D loss: 0.693362, acc.: 48.83%] [G loss: 0.695496]
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3506 [D loss: 0.691874, acc.: 51.76%] [G loss: 0.695331]
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3507 [D loss: 0.693186, acc.: 48.24%] [G loss: 0.694749]
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3508 [D loss: 0.693135, acc.: 52.93%] [G loss: 0.695836]
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3509 [D loss: 0.692968, acc.: 51.95%] [G loss: 0.694163]
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3510 [D loss: 0.692110, acc.: 52.73%] [G loss: 0.696063]
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3511 [D loss: 0.693272, acc.: 50.00%] [G loss: 0.695492]
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3512 [D loss: 0.693577, acc.: 47.07%] [G loss: 0.693348]
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3513 [D loss: 0.693873, acc.: 49.80%] [G loss: 0.694630]
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3514 [D loss: 0.693052, acc.: 52.73%] [G loss: 0.694815]
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3515 [D loss: 0.694042, acc.: 50.20%] [G loss: 0.693268]
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3516 [D loss: 0.694220, acc.: 48.63%] [G loss: 0.692621]
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3517 [D loss: 0.692412, acc.: 53.91%] [G loss: 0.692332]
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3518 [D loss: 0.692775, acc.: 51.76%] [G loss: 0.693531]
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3519 [D loss: 0.694040, acc.: 46.88%] [G loss: 0.694864]
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3520 [D loss: 0.693388, acc.: 48.24%] [G loss: 0.694540]
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3521 [D loss: 0.693806, acc.: 50.20%] [G loss: 0.694132]
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3522 [D loss: 0.694687, acc.: 44.34%] [G loss: 0.692771]
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3523 [D loss: 0.693846, acc.: 46.68%] [G loss: 0.693546]
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3524 [D loss: 0.694207, acc.: 47.27%] [G loss: 0.692730]
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3525 [D loss: 0.693755, acc.: 47.66%] [G loss: 0.693078]
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3526 [D loss: 0.693531, acc.: 49.41%] [G loss: 0.694486]
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3527 [D loss: 0.693109, acc.: 50.98%] [G loss: 0.693494]
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3528 [D loss: 0.693060, acc.: 51.17%] [G loss: 0.694608]
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3529 [D loss: 0.693538, acc.: 48.24%] [G loss: 0.692297]
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3530 [D loss: 0.693601, acc.: 49.41%] [G loss: 0.692960]
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3531 [D loss: 0.693329, acc.: 49.80%] [G loss: 0.694544]
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3532 [D loss: 0.691536, acc.: 55.27%] [G loss: 0.694521]
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3533 [D loss: 0.694006, acc.: 49.02%] [G loss: 0.694343]
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3534 [D loss: 0.693435, acc.: 52.73%] [G loss: 0.694297]
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3535 [D loss: 0.692378, acc.: 52.73%] [G loss: 0.692925]
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3536 [D loss: 0.691985, acc.: 54.30%] [G loss: 0.693685]
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3537 [D loss: 0.692006, acc.: 56.84%] [G loss: 0.695390]
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3538 [D loss: 0.692433, acc.: 51.95%] [G loss: 0.695220]
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3539 [D loss: 0.692633, acc.: 52.54%] [G loss: 0.695699]
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3540 [D loss: 0.691463, acc.: 55.27%] [G loss: 0.693814]
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3541 [D loss: 0.692923, acc.: 48.83%] [G loss: 0.693779]
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3542 [D loss: 0.693164, acc.: 49.80%] [G loss: 0.693470]
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3543 [D loss: 0.693468, acc.: 50.59%] [G loss: 0.693857]
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3544 [D loss: 0.692929, acc.: 51.17%] [G loss: 0.692723]
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3545 [D loss: 0.693212, acc.: 50.59%] [G loss: 0.692696]
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3546 [D loss: 0.693293, acc.: 50.78%] [G loss: 0.693552]
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3547 [D loss: 0.693267, acc.: 49.41%] [G loss: 0.691180]
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3548 [D loss: 0.694620, acc.: 45.90%] [G loss: 0.692739]
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3549 [D loss: 0.693948, acc.: 52.15%] [G loss: 0.694298]
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3550 [D loss: 0.693510, acc.: 50.98%] [G loss: 0.694816]
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3551 [D loss: 0.694163, acc.: 51.56%] [G loss: 0.693929]
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3552 [D loss: 0.693595, acc.: 48.63%] [G loss: 0.693725]
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3553 [D loss: 0.694238, acc.: 48.44%] [G loss: 0.693702]
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3554 [D loss: 0.692192, acc.: 52.73%] [G loss: 0.695481]
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3555 [D loss: 0.692733, acc.: 52.93%] [G loss: 0.694466]
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3556 [D loss: 0.693806, acc.: 50.78%] [G loss: 0.694728]
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3557 [D loss: 0.693958, acc.: 46.88%] [G loss: 0.695083]
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3558 [D loss: 0.692881, acc.: 54.10%] [G loss: 0.695992]
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3559 [D loss: 0.693073, acc.: 52.15%] [G loss: 0.695143]
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3560 [D loss: 0.693369, acc.: 50.78%] [G loss: 0.694596]
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3561 [D loss: 0.692018, acc.: 55.08%] [G loss: 0.695928]
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3562 [D loss: 0.693185, acc.: 50.39%] [G loss: 0.696164]
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3563 [D loss: 0.692151, acc.: 54.49%] [G loss: 0.693429]
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3564 [D loss: 0.693382, acc.: 48.83%] [G loss: 0.694699]
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3565 [D loss: 0.691996, acc.: 54.30%] [G loss: 0.694731]
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3566 [D loss: 0.693475, acc.: 48.24%] [G loss: 0.694581]
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3567 [D loss: 0.692436, acc.: 53.52%] [G loss: 0.694079]
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3568 [D loss: 0.693497, acc.: 48.24%] [G loss: 0.694389]
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3569 [D loss: 0.693105, acc.: 49.41%] [G loss: 0.695808]
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3570 [D loss: 0.693015, acc.: 50.39%] [G loss: 0.695894]
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3571 [D loss: 0.692572, acc.: 51.95%] [G loss: 0.694014]
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3572 [D loss: 0.692409, acc.: 52.54%] [G loss: 0.694236]
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3573 [D loss: 0.693587, acc.: 50.78%] [G loss: 0.694677]
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3574 [D loss: 0.693045, acc.: 48.83%] [G loss: 0.696471]
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3575 [D loss: 0.692875, acc.: 50.78%] [G loss: 0.694164]
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3576 [D loss: 0.692381, acc.: 51.95%] [G loss: 0.694046]
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3577 [D loss: 0.694009, acc.: 47.46%] [G loss: 0.695020]
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3578 [D loss: 0.692899, acc.: 53.52%] [G loss: 0.696104]
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3579 [D loss: 0.693181, acc.: 49.22%] [G loss: 0.695220]
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3580 [D loss: 0.693191, acc.: 49.61%] [G loss: 0.694366]
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3581 [D loss: 0.693017, acc.: 50.59%] [G loss: 0.692976]
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3582 [D loss: 0.693824, acc.: 47.27%] [G loss: 0.693939]
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3583 [D loss: 0.693975, acc.: 46.09%] [G loss: 0.693280]
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3584 [D loss: 0.693269, acc.: 50.59%] [G loss: 0.693211]
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3585 [D loss: 0.694586, acc.: 45.31%] [G loss: 0.692330]
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3586 [D loss: 0.693433, acc.: 50.00%] [G loss: 0.692740]
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3587 [D loss: 0.692908, acc.: 50.39%] [G loss: 0.694357]
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3588 [D loss: 0.693751, acc.: 45.51%] [G loss: 0.694159]
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3589 [D loss: 0.693381, acc.: 47.66%] [G loss: 0.694048]
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3590 [D loss: 0.694105, acc.: 47.85%] [G loss: 0.694131]
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3591 [D loss: 0.692807, acc.: 50.98%] [G loss: 0.694403]
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3592 [D loss: 0.693633, acc.: 45.90%] [G loss: 0.694446]
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3593 [D loss: 0.692223, acc.: 54.88%] [G loss: 0.694829]
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3594 [D loss: 0.692336, acc.: 52.34%] [G loss: 0.694516]
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3595 [D loss: 0.692179, acc.: 53.71%] [G loss: 0.694799]
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3596 [D loss: 0.692853, acc.: 52.34%] [G loss: 0.695033]
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3597 [D loss: 0.692898, acc.: 51.56%] [G loss: 0.694573]
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3598 [D loss: 0.692401, acc.: 53.52%] [G loss: 0.693421]
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3599 [D loss: 0.692927, acc.: 52.15%] [G loss: 0.694369]
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3600 [D loss: 0.693682, acc.: 52.15%] [G loss: 0.694198]
1/1 [==============================] - 0s 15ms/step
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3601 [D loss: 0.694298, acc.: 44.92%] [G loss: 0.694699]
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3602 [D loss: 0.693351, acc.: 48.83%] [G loss: 0.693462]
8/8 [==============================] - 0s 2ms/step
3603 [D loss: 0.693191, acc.: 50.78%] [G loss: 0.692344]
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3604 [D loss: 0.693298, acc.: 48.44%] [G loss: 0.693903]
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3605 [D loss: 0.693179, acc.: 48.24%] [G loss: 0.693679]
8/8 [==============================] - 0s 2ms/step
3606 [D loss: 0.694652, acc.: 45.12%] [G loss: 0.692952]
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3607 [D loss: 0.693992, acc.: 49.41%] [G loss: 0.693810]
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3608 [D loss: 0.691737, acc.: 54.10%] [G loss: 0.693807]
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3609 [D loss: 0.693568, acc.: 49.61%] [G loss: 0.694973]
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3610 [D loss: 0.693008, acc.: 52.34%] [G loss: 0.694640]
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3611 [D loss: 0.692655, acc.: 52.15%] [G loss: 0.694269]
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3612 [D loss: 0.693396, acc.: 50.59%] [G loss: 0.694309]
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3613 [D loss: 0.693376, acc.: 51.95%] [G loss: 0.695104]
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3614 [D loss: 0.692396, acc.: 54.69%] [G loss: 0.695486]
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3615 [D loss: 0.693005, acc.: 50.00%] [G loss: 0.695283]
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3616 [D loss: 0.692672, acc.: 50.59%] [G loss: 0.696221]
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3617 [D loss: 0.692161, acc.: 52.34%] [G loss: 0.694895]
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3618 [D loss: 0.691867, acc.: 55.66%] [G loss: 0.695878]
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3619 [D loss: 0.692623, acc.: 53.32%] [G loss: 0.694595]
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3620 [D loss: 0.692380, acc.: 55.27%] [G loss: 0.692843]
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3621 [D loss: 0.692894, acc.: 50.00%] [G loss: 0.694214]
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3622 [D loss: 0.693930, acc.: 49.41%] [G loss: 0.693421]
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3623 [D loss: 0.692766, acc.: 52.34%] [G loss: 0.694703]
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3624 [D loss: 0.692341, acc.: 52.54%] [G loss: 0.693265]
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3625 [D loss: 0.693290, acc.: 48.83%] [G loss: 0.692832]
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3626 [D loss: 0.693941, acc.: 49.22%] [G loss: 0.693150]
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3627 [D loss: 0.694062, acc.: 50.00%] [G loss: 0.693435]
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3628 [D loss: 0.693744, acc.: 48.24%] [G loss: 0.691477]
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3629 [D loss: 0.693331, acc.: 50.98%] [G loss: 0.693033]
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3630 [D loss: 0.693531, acc.: 48.44%] [G loss: 0.692335]
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3631 [D loss: 0.693554, acc.: 51.76%] [G loss: 0.692752]
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3632 [D loss: 0.692229, acc.: 52.54%] [G loss: 0.694277]
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3633 [D loss: 0.693267, acc.: 53.12%] [G loss: 0.695570]
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3634 [D loss: 0.692781, acc.: 52.73%] [G loss: 0.694191]
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3635 [D loss: 0.692916, acc.: 49.02%] [G loss: 0.693995]
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3636 [D loss: 0.692824, acc.: 51.95%] [G loss: 0.694465]
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3637 [D loss: 0.691370, acc.: 54.10%] [G loss: 0.693908]
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3638 [D loss: 0.692982, acc.: 49.41%] [G loss: 0.694631]
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3639 [D loss: 0.693372, acc.: 47.85%] [G loss: 0.692210]
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3640 [D loss: 0.694466, acc.: 48.24%] [G loss: 0.693385]
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3641 [D loss: 0.693325, acc.: 49.41%] [G loss: 0.692863]
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3642 [D loss: 0.694368, acc.: 46.09%] [G loss: 0.691844]
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3643 [D loss: 0.694300, acc.: 45.12%] [G loss: 0.693489]
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3644 [D loss: 0.694962, acc.: 43.95%] [G loss: 0.692211]
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3645 [D loss: 0.692275, acc.: 54.10%] [G loss: 0.694374]
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3646 [D loss: 0.693443, acc.: 48.83%] [G loss: 0.694345]
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3647 [D loss: 0.692511, acc.: 52.15%] [G loss: 0.695425]
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3648 [D loss: 0.693797, acc.: 48.83%] [G loss: 0.694292]
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3649 [D loss: 0.692171, acc.: 55.47%] [G loss: 0.695620]
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3650 [D loss: 0.693027, acc.: 49.22%] [G loss: 0.695595]
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3651 [D loss: 0.692064, acc.: 51.17%] [G loss: 0.694538]
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3652 [D loss: 0.694038, acc.: 47.46%] [G loss: 0.696802]
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3653 [D loss: 0.692463, acc.: 50.39%] [G loss: 0.695779]
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3654 [D loss: 0.691770, acc.: 53.12%] [G loss: 0.696435]
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3655 [D loss: 0.692925, acc.: 49.80%] [G loss: 0.696900]
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3656 [D loss: 0.693895, acc.: 48.05%] [G loss: 0.695626]
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3657 [D loss: 0.693025, acc.: 49.80%] [G loss: 0.695166]
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3658 [D loss: 0.693181, acc.: 50.59%] [G loss: 0.694290]
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3659 [D loss: 0.693972, acc.: 46.88%] [G loss: 0.692341]
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3660 [D loss: 0.694018, acc.: 48.24%] [G loss: 0.694030]
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3661 [D loss: 0.692733, acc.: 50.78%] [G loss: 0.695307]
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3662 [D loss: 0.693452, acc.: 49.22%] [G loss: 0.695024]
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3663 [D loss: 0.693540, acc.: 49.80%] [G loss: 0.695095]
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3664 [D loss: 0.693083, acc.: 50.59%] [G loss: 0.694049]
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3665 [D loss: 0.693757, acc.: 47.85%] [G loss: 0.693435]
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3666 [D loss: 0.693240, acc.: 48.63%] [G loss: 0.693394]
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3667 [D loss: 0.693414, acc.: 49.41%] [G loss: 0.693824]
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3668 [D loss: 0.692784, acc.: 50.78%] [G loss: 0.695932]
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3669 [D loss: 0.691955, acc.: 54.69%] [G loss: 0.696647]
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3670 [D loss: 0.692906, acc.: 50.78%] [G loss: 0.697129]
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3671 [D loss: 0.693259, acc.: 49.41%] [G loss: 0.696908]
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3672 [D loss: 0.692093, acc.: 53.52%] [G loss: 0.695707]
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3673 [D loss: 0.692861, acc.: 51.56%] [G loss: 0.696355]
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3674 [D loss: 0.692901, acc.: 51.37%] [G loss: 0.695702]
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3675 [D loss: 0.692901, acc.: 48.83%] [G loss: 0.694650]
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3676 [D loss: 0.693224, acc.: 51.95%] [G loss: 0.693396]
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3677 [D loss: 0.694255, acc.: 48.05%] [G loss: 0.693191]
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3678 [D loss: 0.693254, acc.: 48.24%] [G loss: 0.693201]
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3679 [D loss: 0.692857, acc.: 50.78%] [G loss: 0.692364]
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3680 [D loss: 0.694151, acc.: 47.27%] [G loss: 0.692799]
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3681 [D loss: 0.693041, acc.: 49.80%] [G loss: 0.692724]
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3682 [D loss: 0.693036, acc.: 50.20%] [G loss: 0.693079]
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3683 [D loss: 0.694889, acc.: 48.83%] [G loss: 0.691230]
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3684 [D loss: 0.693932, acc.: 47.46%] [G loss: 0.692852]
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3685 [D loss: 0.694127, acc.: 46.68%] [G loss: 0.694408]
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3686 [D loss: 0.693278, acc.: 49.41%] [G loss: 0.692722]
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3687 [D loss: 0.693311, acc.: 49.02%] [G loss: 0.692792]
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3688 [D loss: 0.693655, acc.: 50.39%] [G loss: 0.693789]
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3689 [D loss: 0.693377, acc.: 48.05%] [G loss: 0.695228]
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3690 [D loss: 0.693177, acc.: 50.20%] [G loss: 0.695629]
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3691 [D loss: 0.692717, acc.: 50.20%] [G loss: 0.695854]
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3692 [D loss: 0.692332, acc.: 53.91%] [G loss: 0.694331]
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3693 [D loss: 0.693466, acc.: 48.63%] [G loss: 0.694426]
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3694 [D loss: 0.692767, acc.: 51.37%] [G loss: 0.693117]
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3695 [D loss: 0.693814, acc.: 47.27%] [G loss: 0.693413]
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3696 [D loss: 0.693835, acc.: 48.44%] [G loss: 0.693664]
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3697 [D loss: 0.693299, acc.: 51.17%] [G loss: 0.692039]
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3698 [D loss: 0.693936, acc.: 46.68%] [G loss: 0.691990]
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3699 [D loss: 0.693825, acc.: 48.05%] [G loss: 0.692308]
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3700 [D loss: 0.693753, acc.: 46.68%] [G loss: 0.691888]
1/1 [==============================] - 0s 16ms/step
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3701 [D loss: 0.694513, acc.: 45.70%] [G loss: 0.692658]
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3702 [D loss: 0.693767, acc.: 49.80%] [G loss: 0.692221]
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3703 [D loss: 0.694581, acc.: 47.07%] [G loss: 0.691697]
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3704 [D loss: 0.693496, acc.: 47.27%] [G loss: 0.694034]
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3705 [D loss: 0.693845, acc.: 46.29%] [G loss: 0.695085]
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3706 [D loss: 0.693263, acc.: 49.80%] [G loss: 0.694864]
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3707 [D loss: 0.691719, acc.: 54.69%] [G loss: 0.694647]
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3708 [D loss: 0.692505, acc.: 52.34%] [G loss: 0.696386]
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3709 [D loss: 0.692542, acc.: 52.73%] [G loss: 0.697387]
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3710 [D loss: 0.691028, acc.: 56.64%] [G loss: 0.698252]
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3711 [D loss: 0.692667, acc.: 50.59%] [G loss: 0.697156]
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3712 [D loss: 0.692005, acc.: 53.32%] [G loss: 0.695958]
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3713 [D loss: 0.692445, acc.: 51.37%] [G loss: 0.696338]
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3714 [D loss: 0.692411, acc.: 53.71%] [G loss: 0.694831]
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3715 [D loss: 0.693105, acc.: 49.41%] [G loss: 0.694763]
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3716 [D loss: 0.693454, acc.: 48.05%] [G loss: 0.693834]
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3717 [D loss: 0.692897, acc.: 50.39%] [G loss: 0.695171]
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3718 [D loss: 0.692454, acc.: 54.10%] [G loss: 0.693670]
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3719 [D loss: 0.693460, acc.: 50.00%] [G loss: 0.693478]
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3720 [D loss: 0.693546, acc.: 51.76%] [G loss: 0.691897]
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3721 [D loss: 0.692812, acc.: 49.41%] [G loss: 0.694119]
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3722 [D loss: 0.693756, acc.: 47.85%] [G loss: 0.692294]
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3723 [D loss: 0.694028, acc.: 47.07%] [G loss: 0.693044]
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3724 [D loss: 0.693282, acc.: 49.80%] [G loss: 0.692844]
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3725 [D loss: 0.693619, acc.: 46.48%] [G loss: 0.694862]
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3726 [D loss: 0.693067, acc.: 51.95%] [G loss: 0.691485]
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3727 [D loss: 0.692708, acc.: 49.61%] [G loss: 0.693897]
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3728 [D loss: 0.693249, acc.: 50.98%] [G loss: 0.693232]
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3729 [D loss: 0.694142, acc.: 47.27%] [G loss: 0.693641]
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3730 [D loss: 0.693464, acc.: 47.66%] [G loss: 0.692812]
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3731 [D loss: 0.693114, acc.: 49.41%] [G loss: 0.693260]
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3732 [D loss: 0.693170, acc.: 51.17%] [G loss: 0.694172]
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3733 [D loss: 0.692923, acc.: 48.24%] [G loss: 0.693242]
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3734 [D loss: 0.693122, acc.: 50.39%] [G loss: 0.692377]
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3735 [D loss: 0.693652, acc.: 48.63%] [G loss: 0.692566]
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3736 [D loss: 0.694076, acc.: 47.46%] [G loss: 0.693789]
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3737 [D loss: 0.693614, acc.: 46.48%] [G loss: 0.691208]
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3738 [D loss: 0.694431, acc.: 46.09%] [G loss: 0.692922]
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3739 [D loss: 0.693281, acc.: 47.85%] [G loss: 0.691747]
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3740 [D loss: 0.693412, acc.: 48.24%] [G loss: 0.692514]
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3741 [D loss: 0.694062, acc.: 49.02%] [G loss: 0.693005]
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3742 [D loss: 0.692743, acc.: 51.37%] [G loss: 0.694077]
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3743 [D loss: 0.693557, acc.: 51.76%] [G loss: 0.694440]
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3744 [D loss: 0.693474, acc.: 47.85%] [G loss: 0.694624]
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3745 [D loss: 0.692752, acc.: 51.56%] [G loss: 0.693626]
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3746 [D loss: 0.693697, acc.: 47.46%] [G loss: 0.693145]
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3747 [D loss: 0.692417, acc.: 53.52%] [G loss: 0.695413]
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3748 [D loss: 0.692497, acc.: 50.78%] [G loss: 0.694962]
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3749 [D loss: 0.692483, acc.: 52.54%] [G loss: 0.693711]
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3750 [D loss: 0.692366, acc.: 51.95%] [G loss: 0.693499]
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3751 [D loss: 0.692450, acc.: 52.34%] [G loss: 0.692650]
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3752 [D loss: 0.692744, acc.: 51.95%] [G loss: 0.694192]
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3753 [D loss: 0.692651, acc.: 50.98%] [G loss: 0.692540]
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3754 [D loss: 0.692945, acc.: 50.20%] [G loss: 0.693655]
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3755 [D loss: 0.692961, acc.: 51.95%] [G loss: 0.693185]
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3756 [D loss: 0.692932, acc.: 49.80%] [G loss: 0.693180]
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3757 [D loss: 0.693117, acc.: 48.63%] [G loss: 0.692921]
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3758 [D loss: 0.694088, acc.: 48.05%] [G loss: 0.693349]
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3759 [D loss: 0.693831, acc.: 47.27%] [G loss: 0.693418]
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3760 [D loss: 0.693429, acc.: 47.46%] [G loss: 0.692345]
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3761 [D loss: 0.693026, acc.: 51.76%] [G loss: 0.692363]
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3762 [D loss: 0.694061, acc.: 45.51%] [G loss: 0.692309]
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3763 [D loss: 0.694476, acc.: 48.63%] [G loss: 0.690800]
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3764 [D loss: 0.694122, acc.: 47.85%] [G loss: 0.692434]
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3765 [D loss: 0.693765, acc.: 48.63%] [G loss: 0.693106]
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3766 [D loss: 0.693968, acc.: 48.24%] [G loss: 0.694140]
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3767 [D loss: 0.692858, acc.: 50.59%] [G loss: 0.696261]
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3768 [D loss: 0.693333, acc.: 48.44%] [G loss: 0.694432]
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3769 [D loss: 0.692493, acc.: 52.54%] [G loss: 0.692633]
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3770 [D loss: 0.693583, acc.: 50.20%] [G loss: 0.693968]
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3771 [D loss: 0.693515, acc.: 48.63%] [G loss: 0.692493]
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3772 [D loss: 0.693431, acc.: 50.00%] [G loss: 0.693464]
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3773 [D loss: 0.693724, acc.: 45.90%] [G loss: 0.693615]
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3774 [D loss: 0.693057, acc.: 51.76%] [G loss: 0.693336]
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3775 [D loss: 0.692264, acc.: 53.12%] [G loss: 0.693964]
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3776 [D loss: 0.693093, acc.: 50.00%] [G loss: 0.693987]
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3777 [D loss: 0.692614, acc.: 50.78%] [G loss: 0.693435]
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3778 [D loss: 0.692928, acc.: 50.78%] [G loss: 0.693238]
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3779 [D loss: 0.694397, acc.: 45.31%] [G loss: 0.694896]
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3780 [D loss: 0.693057, acc.: 49.61%] [G loss: 0.694233]
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3781 [D loss: 0.692651, acc.: 50.78%] [G loss: 0.693445]
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3782 [D loss: 0.693021, acc.: 51.17%] [G loss: 0.694119]
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3783 [D loss: 0.693800, acc.: 50.20%] [G loss: 0.692469]
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3784 [D loss: 0.692428, acc.: 51.37%] [G loss: 0.694314]
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3785 [D loss: 0.693248, acc.: 48.63%] [G loss: 0.690996]
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3786 [D loss: 0.692470, acc.: 55.08%] [G loss: 0.693484]
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3787 [D loss: 0.692807, acc.: 50.39%] [G loss: 0.694076]
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3788 [D loss: 0.692758, acc.: 51.37%] [G loss: 0.693871]
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3789 [D loss: 0.692432, acc.: 51.37%] [G loss: 0.696082]
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3790 [D loss: 0.692738, acc.: 50.59%] [G loss: 0.695888]
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3791 [D loss: 0.692929, acc.: 51.95%] [G loss: 0.694692]
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3792 [D loss: 0.692731, acc.: 54.69%] [G loss: 0.694731]
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3793 [D loss: 0.693561, acc.: 52.54%] [G loss: 0.693010]
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3794 [D loss: 0.693190, acc.: 50.98%] [G loss: 0.694051]
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3795 [D loss: 0.692832, acc.: 48.63%] [G loss: 0.694077]
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3796 [D loss: 0.693804, acc.: 49.02%] [G loss: 0.692937]
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3797 [D loss: 0.693749, acc.: 50.00%] [G loss: 0.693895]
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3798 [D loss: 0.692928, acc.: 49.80%] [G loss: 0.692924]
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3799 [D loss: 0.693043, acc.: 51.76%] [G loss: 0.692970]
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3800 [D loss: 0.693869, acc.: 49.41%] [G loss: 0.693540]
1/1 [==============================] - 0s 15ms/step
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3801 [D loss: 0.693520, acc.: 47.66%] [G loss: 0.695498]
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3802 [D loss: 0.694412, acc.: 44.14%] [G loss: 0.693932]
8/8 [==============================] - 0s 2ms/step
3803 [D loss: 0.694363, acc.: 46.88%] [G loss: 0.693107]
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3804 [D loss: 0.693345, acc.: 48.24%] [G loss: 0.693786]
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3805 [D loss: 0.693934, acc.: 46.48%] [G loss: 0.694138]
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3806 [D loss: 0.692792, acc.: 50.39%] [G loss: 0.694730]
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3807 [D loss: 0.693091, acc.: 49.80%] [G loss: 0.693411]
8/8 [==============================] - 0s 2ms/step
3808 [D loss: 0.692800, acc.: 51.76%] [G loss: 0.693707]
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3809 [D loss: 0.692843, acc.: 50.98%] [G loss: 0.695385]
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3810 [D loss: 0.692898, acc.: 48.83%] [G loss: 0.694463]
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3811 [D loss: 0.692706, acc.: 49.41%] [G loss: 0.694277]
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3812 [D loss: 0.694379, acc.: 46.88%] [G loss: 0.694027]
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3813 [D loss: 0.693316, acc.: 52.54%] [G loss: 0.693730]
8/8 [==============================] - 0s 2ms/step
3814 [D loss: 0.693278, acc.: 49.22%] [G loss: 0.692676]
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3815 [D loss: 0.693440, acc.: 49.02%] [G loss: 0.692016]
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3816 [D loss: 0.693658, acc.: 47.85%] [G loss: 0.693563]
8/8 [==============================] - 0s 2ms/step
3817 [D loss: 0.692830, acc.: 51.17%] [G loss: 0.693351]
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3818 [D loss: 0.693259, acc.: 50.39%] [G loss: 0.694995]
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3819 [D loss: 0.693006, acc.: 49.41%] [G loss: 0.694335]
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3820 [D loss: 0.692083, acc.: 53.71%] [G loss: 0.693583]
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3821 [D loss: 0.693152, acc.: 50.98%] [G loss: 0.692922]
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3822 [D loss: 0.693121, acc.: 49.80%] [G loss: 0.691983]
8/8 [==============================] - 0s 2ms/step
3823 [D loss: 0.693140, acc.: 53.71%] [G loss: 0.693614]
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3824 [D loss: 0.693365, acc.: 50.78%] [G loss: 0.692557]
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3825 [D loss: 0.691388, acc.: 53.32%] [G loss: 0.693886]
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3826 [D loss: 0.691809, acc.: 54.10%] [G loss: 0.692849]
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3827 [D loss: 0.692536, acc.: 54.10%] [G loss: 0.694002]
8/8 [==============================] - 0s 2ms/step
3828 [D loss: 0.693989, acc.: 44.92%] [G loss: 0.693517]
8/8 [==============================] - 0s 2ms/step
3829 [D loss: 0.693699, acc.: 49.22%] [G loss: 0.693680]
8/8 [==============================] - 0s 2ms/step
3830 [D loss: 0.692643, acc.: 51.56%] [G loss: 0.692412]
8/8 [==============================] - 0s 2ms/step
3831 [D loss: 0.692619, acc.: 52.73%] [G loss: 0.693868]
8/8 [==============================] - 0s 2ms/step
3832 [D loss: 0.693229, acc.: 50.98%] [G loss: 0.691293]
8/8 [==============================] - 0s 2ms/step
3833 [D loss: 0.692529, acc.: 53.12%] [G loss: 0.692558]
8/8 [==============================] - 0s 2ms/step
3834 [D loss: 0.694110, acc.: 47.66%] [G loss: 0.691741]
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3835 [D loss: 0.693419, acc.: 48.63%] [G loss: 0.691866]
8/8 [==============================] - 0s 2ms/step
3836 [D loss: 0.693520, acc.: 49.22%] [G loss: 0.692396]
8/8 [==============================] - 0s 2ms/step
3837 [D loss: 0.693099, acc.: 49.80%] [G loss: 0.691742]
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3838 [D loss: 0.693079, acc.: 51.17%] [G loss: 0.691769]
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3839 [D loss: 0.692512, acc.: 52.73%] [G loss: 0.693359]
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3840 [D loss: 0.692694, acc.: 50.20%] [G loss: 0.692775]
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3841 [D loss: 0.693389, acc.: 49.22%] [G loss: 0.693528]
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3842 [D loss: 0.692154, acc.: 53.52%] [G loss: 0.693078]
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3843 [D loss: 0.694447, acc.: 47.66%] [G loss: 0.693999]
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3844 [D loss: 0.694186, acc.: 47.85%] [G loss: 0.693738]
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3845 [D loss: 0.691968, acc.: 54.30%] [G loss: 0.694256]
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3846 [D loss: 0.693399, acc.: 49.61%] [G loss: 0.695387]
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3847 [D loss: 0.693161, acc.: 48.83%] [G loss: 0.695251]
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3848 [D loss: 0.693473, acc.: 51.56%] [G loss: 0.694669]
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3849 [D loss: 0.691945, acc.: 54.69%] [G loss: 0.695560]
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3850 [D loss: 0.693199, acc.: 47.66%] [G loss: 0.694879]
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3851 [D loss: 0.693226, acc.: 48.83%] [G loss: 0.695493]
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3852 [D loss: 0.693195, acc.: 47.85%] [G loss: 0.694646]
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3853 [D loss: 0.694059, acc.: 46.68%] [G loss: 0.694011]
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3854 [D loss: 0.692956, acc.: 52.73%] [G loss: 0.695895]
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3855 [D loss: 0.693241, acc.: 49.41%] [G loss: 0.693510]
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3856 [D loss: 0.692993, acc.: 50.20%] [G loss: 0.694634]
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3857 [D loss: 0.692443, acc.: 51.95%] [G loss: 0.693830]
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3858 [D loss: 0.693524, acc.: 49.80%] [G loss: 0.691800]
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3859 [D loss: 0.693224, acc.: 51.56%] [G loss: 0.692527]
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3860 [D loss: 0.692966, acc.: 50.59%] [G loss: 0.693974]
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3861 [D loss: 0.693918, acc.: 50.00%] [G loss: 0.691828]
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3862 [D loss: 0.692498, acc.: 49.02%] [G loss: 0.693697]
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3863 [D loss: 0.693069, acc.: 49.61%] [G loss: 0.694143]
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3864 [D loss: 0.692470, acc.: 51.95%] [G loss: 0.694232]
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3865 [D loss: 0.693691, acc.: 46.48%] [G loss: 0.694282]
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3866 [D loss: 0.693481, acc.: 49.02%] [G loss: 0.694513]
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3867 [D loss: 0.692573, acc.: 55.27%] [G loss: 0.694802]
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3868 [D loss: 0.693468, acc.: 47.85%] [G loss: 0.691928]
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3869 [D loss: 0.693188, acc.: 50.59%] [G loss: 0.692743]
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3870 [D loss: 0.693950, acc.: 49.61%] [G loss: 0.692266]
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3871 [D loss: 0.692815, acc.: 49.22%] [G loss: 0.692459]
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3872 [D loss: 0.692396, acc.: 54.88%] [G loss: 0.692490]
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3873 [D loss: 0.692426, acc.: 52.15%] [G loss: 0.693244]
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3874 [D loss: 0.693430, acc.: 47.27%] [G loss: 0.693602]
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3875 [D loss: 0.694238, acc.: 47.85%] [G loss: 0.693023]
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3876 [D loss: 0.693370, acc.: 49.80%] [G loss: 0.693143]
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3877 [D loss: 0.693903, acc.: 48.63%] [G loss: 0.692374]
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3878 [D loss: 0.693460, acc.: 48.24%] [G loss: 0.692940]
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3879 [D loss: 0.692953, acc.: 51.56%] [G loss: 0.691747]
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3880 [D loss: 0.692582, acc.: 53.91%] [G loss: 0.693243]
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3881 [D loss: 0.693971, acc.: 46.68%] [G loss: 0.691825]
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3882 [D loss: 0.694294, acc.: 47.66%] [G loss: 0.691422]
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3883 [D loss: 0.693282, acc.: 48.44%] [G loss: 0.691790]
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3884 [D loss: 0.693523, acc.: 50.78%] [G loss: 0.692607]
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3885 [D loss: 0.693627, acc.: 49.61%] [G loss: 0.694038]
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3886 [D loss: 0.692584, acc.: 53.71%] [G loss: 0.694017]
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3887 [D loss: 0.692926, acc.: 52.34%] [G loss: 0.694245]
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3888 [D loss: 0.692380, acc.: 53.32%] [G loss: 0.693409]
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3889 [D loss: 0.692763, acc.: 50.00%] [G loss: 0.693905]
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3890 [D loss: 0.693043, acc.: 51.37%] [G loss: 0.694118]
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3891 [D loss: 0.691571, acc.: 54.88%] [G loss: 0.694484]
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3892 [D loss: 0.692575, acc.: 53.71%] [G loss: 0.694757]
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3893 [D loss: 0.692400, acc.: 53.71%] [G loss: 0.694204]
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3894 [D loss: 0.692866, acc.: 51.17%] [G loss: 0.694451]
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3895 [D loss: 0.692102, acc.: 52.93%] [G loss: 0.693645]
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3896 [D loss: 0.693144, acc.: 51.17%] [G loss: 0.693750]
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3897 [D loss: 0.692541, acc.: 51.95%] [G loss: 0.695121]
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3898 [D loss: 0.692941, acc.: 48.83%] [G loss: 0.693826]
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3899 [D loss: 0.693453, acc.: 46.88%] [G loss: 0.695141]
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3900 [D loss: 0.692516, acc.: 50.39%] [G loss: 0.695302]
1/1 [==============================] - 0s 15ms/step
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3901 [D loss: 0.693253, acc.: 49.22%] [G loss: 0.694917]
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3902 [D loss: 0.694085, acc.: 46.88%] [G loss: 0.695534]
8/8 [==============================] - 0s 2ms/step
3903 [D loss: 0.692418, acc.: 55.47%] [G loss: 0.695058]
8/8 [==============================] - 0s 2ms/step
3904 [D loss: 0.692610, acc.: 50.39%] [G loss: 0.693967]
8/8 [==============================] - 0s 2ms/step
3905 [D loss: 0.693680, acc.: 50.39%] [G loss: 0.693574]
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3906 [D loss: 0.693692, acc.: 47.27%] [G loss: 0.695912]
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3907 [D loss: 0.692355, acc.: 49.80%] [G loss: 0.693022]
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3908 [D loss: 0.693246, acc.: 49.61%] [G loss: 0.694389]
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3909 [D loss: 0.692294, acc.: 55.08%] [G loss: 0.693858]
8/8 [==============================] - 0s 2ms/step
3910 [D loss: 0.693583, acc.: 47.27%] [G loss: 0.694495]
8/8 [==============================] - 0s 2ms/step
3911 [D loss: 0.693314, acc.: 49.22%] [G loss: 0.695576]
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3912 [D loss: 0.693430, acc.: 49.80%] [G loss: 0.693563]
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3913 [D loss: 0.693379, acc.: 48.24%] [G loss: 0.694654]
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3914 [D loss: 0.693948, acc.: 47.66%] [G loss: 0.693501]
8/8 [==============================] - 0s 2ms/step
3915 [D loss: 0.694647, acc.: 46.09%] [G loss: 0.692999]
8/8 [==============================] - 0s 2ms/step
3916 [D loss: 0.693248, acc.: 48.83%] [G loss: 0.693628]
8/8 [==============================] - 0s 2ms/step
3917 [D loss: 0.693961, acc.: 50.39%] [G loss: 0.693745]
8/8 [==============================] - 0s 2ms/step
3918 [D loss: 0.693231, acc.: 49.80%] [G loss: 0.692968]
8/8 [==============================] - 0s 2ms/step
3919 [D loss: 0.693029, acc.: 50.78%] [G loss: 0.694665]
8/8 [==============================] - 0s 2ms/step
3920 [D loss: 0.692646, acc.: 51.37%] [G loss: 0.693367]
8/8 [==============================] - 0s 2ms/step
3921 [D loss: 0.693426, acc.: 48.83%] [G loss: 0.692198]
8/8 [==============================] - 0s 2ms/step
3922 [D loss: 0.693339, acc.: 52.73%] [G loss: 0.693280]
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3923 [D loss: 0.693072, acc.: 49.61%] [G loss: 0.693950]
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3924 [D loss: 0.693109, acc.: 49.22%] [G loss: 0.695214]
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3925 [D loss: 0.692293, acc.: 52.34%] [G loss: 0.694532]
8/8 [==============================] - 0s 2ms/step
3926 [D loss: 0.693328, acc.: 47.27%] [G loss: 0.695997]
8/8 [==============================] - 0s 2ms/step
3927 [D loss: 0.692277, acc.: 52.73%] [G loss: 0.696440]
8/8 [==============================] - 0s 2ms/step
3928 [D loss: 0.693302, acc.: 49.22%] [G loss: 0.696418]
8/8 [==============================] - 0s 2ms/step
3929 [D loss: 0.691733, acc.: 55.86%] [G loss: 0.694039]
8/8 [==============================] - 0s 2ms/step
3930 [D loss: 0.692815, acc.: 51.76%] [G loss: 0.692958]
8/8 [==============================] - 0s 2ms/step
3931 [D loss: 0.692311, acc.: 54.10%] [G loss: 0.692212]
8/8 [==============================] - 0s 2ms/step
3932 [D loss: 0.694247, acc.: 47.85%] [G loss: 0.691529]
8/8 [==============================] - 0s 2ms/step
3933 [D loss: 0.693612, acc.: 50.00%] [G loss: 0.691520]
8/8 [==============================] - 0s 2ms/step
3934 [D loss: 0.692865, acc.: 49.61%] [G loss: 0.692418]
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3935 [D loss: 0.693252, acc.: 48.05%] [G loss: 0.694251]
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3936 [D loss: 0.693039, acc.: 53.12%] [G loss: 0.694515]
8/8 [==============================] - 0s 2ms/step
3937 [D loss: 0.692793, acc.: 49.41%] [G loss: 0.695756]
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3938 [D loss: 0.693395, acc.: 49.80%] [G loss: 0.694321]
8/8 [==============================] - 0s 2ms/step
3939 [D loss: 0.692509, acc.: 50.78%] [G loss: 0.695093]
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3940 [D loss: 0.693837, acc.: 49.22%] [G loss: 0.695098]
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3941 [D loss: 0.693478, acc.: 50.59%] [G loss: 0.693693]
8/8 [==============================] - 0s 2ms/step
3942 [D loss: 0.693230, acc.: 50.59%] [G loss: 0.693507]
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3943 [D loss: 0.693638, acc.: 50.00%] [G loss: 0.694078]
8/8 [==============================] - 0s 2ms/step
3944 [D loss: 0.691582, acc.: 52.34%] [G loss: 0.694922]
8/8 [==============================] - 0s 2ms/step
3945 [D loss: 0.692836, acc.: 49.41%] [G loss: 0.696353]
8/8 [==============================] - 0s 2ms/step
3946 [D loss: 0.693113, acc.: 50.98%] [G loss: 0.694729]
8/8 [==============================] - 0s 2ms/step
3947 [D loss: 0.693421, acc.: 51.76%] [G loss: 0.694802]
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3948 [D loss: 0.693689, acc.: 47.66%] [G loss: 0.693415]
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3949 [D loss: 0.693229, acc.: 50.98%] [G loss: 0.694656]
8/8 [==============================] - 0s 2ms/step
3950 [D loss: 0.693042, acc.: 49.61%] [G loss: 0.694161]
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3951 [D loss: 0.692473, acc.: 53.12%] [G loss: 0.693379]
8/8 [==============================] - 0s 2ms/step
3952 [D loss: 0.694006, acc.: 48.63%] [G loss: 0.694481]
8/8 [==============================] - 0s 2ms/step
3953 [D loss: 0.693303, acc.: 50.39%] [G loss: 0.693740]
8/8 [==============================] - 0s 2ms/step
3954 [D loss: 0.694306, acc.: 46.48%] [G loss: 0.693484]
8/8 [==============================] - 0s 2ms/step
3955 [D loss: 0.693315, acc.: 51.37%] [G loss: 0.694387]
8/8 [==============================] - 0s 2ms/step
3956 [D loss: 0.693352, acc.: 50.20%] [G loss: 0.694065]
8/8 [==============================] - 0s 2ms/step
3957 [D loss: 0.693770, acc.: 48.05%] [G loss: 0.696062]
8/8 [==============================] - 0s 2ms/step
3958 [D loss: 0.693185, acc.: 50.59%] [G loss: 0.693565]
8/8 [==============================] - 0s 2ms/step
3959 [D loss: 0.692939, acc.: 49.02%] [G loss: 0.695209]
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3960 [D loss: 0.693096, acc.: 49.61%] [G loss: 0.694382]
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3961 [D loss: 0.693095, acc.: 50.59%] [G loss: 0.693898]
8/8 [==============================] - 0s 2ms/step
3962 [D loss: 0.693221, acc.: 49.41%] [G loss: 0.693709]
8/8 [==============================] - 0s 2ms/step
3963 [D loss: 0.693294, acc.: 51.37%] [G loss: 0.693597]
8/8 [==============================] - 0s 2ms/step
3964 [D loss: 0.693212, acc.: 50.59%] [G loss: 0.692232]
8/8 [==============================] - 0s 2ms/step
3965 [D loss: 0.692799, acc.: 53.32%] [G loss: 0.692000]
8/8 [==============================] - 0s 2ms/step
3966 [D loss: 0.692723, acc.: 52.34%] [G loss: 0.693495]
8/8 [==============================] - 0s 2ms/step
3967 [D loss: 0.692522, acc.: 51.37%] [G loss: 0.693931]
8/8 [==============================] - 0s 2ms/step
3968 [D loss: 0.692808, acc.: 50.59%] [G loss: 0.693331]
8/8 [==============================] - 0s 2ms/step
3969 [D loss: 0.692770, acc.: 51.95%] [G loss: 0.694120]
8/8 [==============================] - 0s 2ms/step
3970 [D loss: 0.693464, acc.: 50.39%] [G loss: 0.693243]
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3971 [D loss: 0.693878, acc.: 48.63%] [G loss: 0.692695]
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3972 [D loss: 0.693047, acc.: 49.02%] [G loss: 0.692662]
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3973 [D loss: 0.692358, acc.: 52.73%] [G loss: 0.694816]
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3974 [D loss: 0.693041, acc.: 49.80%] [G loss: 0.695279]
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3975 [D loss: 0.693919, acc.: 48.24%] [G loss: 0.692048]
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3976 [D loss: 0.693448, acc.: 51.76%] [G loss: 0.692304]
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3977 [D loss: 0.692381, acc.: 54.30%] [G loss: 0.693256]
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3978 [D loss: 0.692965, acc.: 50.20%] [G loss: 0.693525]
8/8 [==============================] - 0s 2ms/step
3979 [D loss: 0.693304, acc.: 46.29%] [G loss: 0.693171]
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3980 [D loss: 0.692387, acc.: 50.78%] [G loss: 0.693677]
8/8 [==============================] - 0s 2ms/step
3981 [D loss: 0.692716, acc.: 52.15%] [G loss: 0.693000]
8/8 [==============================] - 0s 2ms/step
3982 [D loss: 0.692865, acc.: 50.39%] [G loss: 0.691557]
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3983 [D loss: 0.692840, acc.: 51.95%] [G loss: 0.693674]
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3984 [D loss: 0.693045, acc.: 49.80%] [G loss: 0.693893]
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3985 [D loss: 0.693431, acc.: 47.85%] [G loss: 0.693445]
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3986 [D loss: 0.693381, acc.: 46.68%] [G loss: 0.693834]
8/8 [==============================] - 0s 2ms/step
3987 [D loss: 0.693216, acc.: 52.73%] [G loss: 0.692730]
8/8 [==============================] - 0s 2ms/step
3988 [D loss: 0.693933, acc.: 50.59%] [G loss: 0.693310]
8/8 [==============================] - 0s 2ms/step
3989 [D loss: 0.692275, acc.: 52.73%] [G loss: 0.692976]
8/8 [==============================] - 0s 2ms/step
3990 [D loss: 0.693539, acc.: 48.83%] [G loss: 0.694448]
8/8 [==============================] - 0s 2ms/step
3991 [D loss: 0.693546, acc.: 48.83%] [G loss: 0.693316]
8/8 [==============================] - 0s 2ms/step
3992 [D loss: 0.692651, acc.: 52.15%] [G loss: 0.692641]
8/8 [==============================] - 0s 2ms/step
3993 [D loss: 0.693837, acc.: 46.09%] [G loss: 0.693929]
8/8 [==============================] - 0s 2ms/step
3994 [D loss: 0.693793, acc.: 47.66%] [G loss: 0.694068]
8/8 [==============================] - 0s 2ms/step
3995 [D loss: 0.692140, acc.: 52.93%] [G loss: 0.696270]
8/8 [==============================] - 0s 2ms/step
3996 [D loss: 0.692555, acc.: 53.71%] [G loss: 0.695071]
8/8 [==============================] - 0s 2ms/step
3997 [D loss: 0.691971, acc.: 52.73%] [G loss: 0.694696]
8/8 [==============================] - 0s 2ms/step
3998 [D loss: 0.693099, acc.: 50.78%] [G loss: 0.694980]
8/8 [==============================] - 0s 2ms/step
3999 [D loss: 0.692566, acc.: 55.08%] [G loss: 0.695717]
8/8 [==============================] - 0s 2ms/step
4000 [D loss: 0.693801, acc.: 50.20%] [G loss: 0.693852]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
4001 [D loss: 0.694240, acc.: 48.05%] [G loss: 0.694840]
8/8 [==============================] - 0s 2ms/step
4002 [D loss: 0.693483, acc.: 49.61%] [G loss: 0.693950]
8/8 [==============================] - 0s 2ms/step
4003 [D loss: 0.693232, acc.: 50.00%] [G loss: 0.695098]
8/8 [==============================] - 0s 2ms/step
4004 [D loss: 0.693536, acc.: 49.22%] [G loss: 0.694471]
8/8 [==============================] - 0s 2ms/step
4005 [D loss: 0.693354, acc.: 50.78%] [G loss: 0.694954]
8/8 [==============================] - 0s 2ms/step
4006 [D loss: 0.693262, acc.: 47.46%] [G loss: 0.693714]
8/8 [==============================] - 0s 2ms/step
4007 [D loss: 0.693289, acc.: 53.52%] [G loss: 0.694601]
8/8 [==============================] - 0s 2ms/step
4008 [D loss: 0.693392, acc.: 49.41%] [G loss: 0.694257]
8/8 [==============================] - 0s 2ms/step
4009 [D loss: 0.693563, acc.: 47.66%] [G loss: 0.693526]
8/8 [==============================] - 0s 2ms/step
4010 [D loss: 0.693768, acc.: 45.51%] [G loss: 0.695138]
8/8 [==============================] - 0s 2ms/step
4011 [D loss: 0.692770, acc.: 50.39%] [G loss: 0.694432]
8/8 [==============================] - 0s 2ms/step
4012 [D loss: 0.693594, acc.: 47.66%] [G loss: 0.693497]
8/8 [==============================] - 0s 2ms/step
4013 [D loss: 0.692972, acc.: 49.41%] [G loss: 0.692495]
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4014 [D loss: 0.692970, acc.: 49.61%] [G loss: 0.692502]
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4015 [D loss: 0.693422, acc.: 49.02%] [G loss: 0.692540]
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4016 [D loss: 0.692691, acc.: 49.61%] [G loss: 0.691277]
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4017 [D loss: 0.693055, acc.: 50.78%] [G loss: 0.691244]
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4018 [D loss: 0.693644, acc.: 48.44%] [G loss: 0.691321]
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4019 [D loss: 0.694188, acc.: 47.66%] [G loss: 0.690933]
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4020 [D loss: 0.692756, acc.: 51.37%] [G loss: 0.693653]
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4021 [D loss: 0.693625, acc.: 47.07%] [G loss: 0.692730]
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4022 [D loss: 0.693299, acc.: 49.80%] [G loss: 0.692832]
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4023 [D loss: 0.692504, acc.: 50.98%] [G loss: 0.692186]
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4024 [D loss: 0.693111, acc.: 49.22%] [G loss: 0.691946]
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4025 [D loss: 0.693349, acc.: 49.80%] [G loss: 0.693286]
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4026 [D loss: 0.693267, acc.: 49.80%] [G loss: 0.690928]
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4027 [D loss: 0.692664, acc.: 50.98%] [G loss: 0.692336]
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4028 [D loss: 0.693390, acc.: 49.80%] [G loss: 0.693519]
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4029 [D loss: 0.692931, acc.: 53.12%] [G loss: 0.691959]
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4030 [D loss: 0.693024, acc.: 51.56%] [G loss: 0.691073]
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4031 [D loss: 0.693610, acc.: 46.48%] [G loss: 0.692156]
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4032 [D loss: 0.692507, acc.: 51.37%] [G loss: 0.692668]
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4033 [D loss: 0.692725, acc.: 52.15%] [G loss: 0.692767]
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4034 [D loss: 0.692621, acc.: 52.34%] [G loss: 0.693049]
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4035 [D loss: 0.692775, acc.: 50.20%] [G loss: 0.693612]
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4036 [D loss: 0.693573, acc.: 46.48%] [G loss: 0.694932]
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4037 [D loss: 0.692920, acc.: 51.37%] [G loss: 0.694399]
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4038 [D loss: 0.692763, acc.: 51.76%] [G loss: 0.692877]
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4039 [D loss: 0.692457, acc.: 53.12%] [G loss: 0.692959]
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4040 [D loss: 0.693658, acc.: 51.17%] [G loss: 0.693515]
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4041 [D loss: 0.693715, acc.: 49.02%] [G loss: 0.694304]
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4042 [D loss: 0.693123, acc.: 49.61%] [G loss: 0.692782]
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4043 [D loss: 0.694104, acc.: 47.66%] [G loss: 0.694783]
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4044 [D loss: 0.693529, acc.: 51.37%] [G loss: 0.695839]
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4045 [D loss: 0.693573, acc.: 48.83%] [G loss: 0.693556]
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4046 [D loss: 0.693355, acc.: 50.59%] [G loss: 0.694831]
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4047 [D loss: 0.693613, acc.: 48.83%] [G loss: 0.693093]
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4048 [D loss: 0.692720, acc.: 51.37%] [G loss: 0.694912]
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4049 [D loss: 0.692786, acc.: 50.39%] [G loss: 0.694414]
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4050 [D loss: 0.692896, acc.: 49.41%] [G loss: 0.692873]
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4051 [D loss: 0.693899, acc.: 48.24%] [G loss: 0.695401]
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4052 [D loss: 0.692918, acc.: 50.39%] [G loss: 0.696132]
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4053 [D loss: 0.693529, acc.: 46.68%] [G loss: 0.692703]
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4054 [D loss: 0.693140, acc.: 49.80%] [G loss: 0.692664]
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4055 [D loss: 0.691509, acc.: 55.08%] [G loss: 0.692748]
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4056 [D loss: 0.692487, acc.: 50.39%] [G loss: 0.694329]
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4057 [D loss: 0.692758, acc.: 51.17%] [G loss: 0.692899]
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4058 [D loss: 0.692146, acc.: 52.73%] [G loss: 0.691985]
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4059 [D loss: 0.693278, acc.: 48.24%] [G loss: 0.691468]
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4060 [D loss: 0.693308, acc.: 49.02%] [G loss: 0.691400]
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4061 [D loss: 0.693957, acc.: 48.05%] [G loss: 0.691475]
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4062 [D loss: 0.694184, acc.: 46.88%] [G loss: 0.693457]
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4063 [D loss: 0.693575, acc.: 50.39%] [G loss: 0.691825]
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4064 [D loss: 0.693752, acc.: 46.09%] [G loss: 0.693058]
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4065 [D loss: 0.693853, acc.: 49.22%] [G loss: 0.691929]
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4066 [D loss: 0.692244, acc.: 52.54%] [G loss: 0.693785]
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4067 [D loss: 0.693185, acc.: 49.02%] [G loss: 0.694610]
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4068 [D loss: 0.693094, acc.: 51.17%] [G loss: 0.695769]
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4069 [D loss: 0.693679, acc.: 46.09%] [G loss: 0.693676]
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4070 [D loss: 0.692655, acc.: 55.27%] [G loss: 0.693524]
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4071 [D loss: 0.692756, acc.: 50.20%] [G loss: 0.694309]
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4072 [D loss: 0.692428, acc.: 52.15%] [G loss: 0.694254]
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4073 [D loss: 0.693395, acc.: 50.00%] [G loss: 0.695164]
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4074 [D loss: 0.692510, acc.: 50.59%] [G loss: 0.695253]
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4075 [D loss: 0.692134, acc.: 54.88%] [G loss: 0.695922]
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4076 [D loss: 0.693711, acc.: 49.22%] [G loss: 0.695029]
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4077 [D loss: 0.693216, acc.: 51.56%] [G loss: 0.692927]
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4078 [D loss: 0.692325, acc.: 51.17%] [G loss: 0.694126]
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4079 [D loss: 0.693474, acc.: 49.22%] [G loss: 0.692325]
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4080 [D loss: 0.692280, acc.: 52.73%] [G loss: 0.692315]
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4081 [D loss: 0.691950, acc.: 53.91%] [G loss: 0.692151]
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4082 [D loss: 0.693954, acc.: 49.80%] [G loss: 0.693350]
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4083 [D loss: 0.691739, acc.: 53.91%] [G loss: 0.691751]
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4084 [D loss: 0.692208, acc.: 51.37%] [G loss: 0.692935]
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4085 [D loss: 0.693030, acc.: 51.95%] [G loss: 0.692821]
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4086 [D loss: 0.693191, acc.: 49.02%] [G loss: 0.692616]
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4087 [D loss: 0.693549, acc.: 48.83%] [G loss: 0.693172]
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4088 [D loss: 0.693503, acc.: 49.22%] [G loss: 0.691884]
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4089 [D loss: 0.693263, acc.: 49.61%] [G loss: 0.690065]
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4090 [D loss: 0.693966, acc.: 47.85%] [G loss: 0.692156]
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4091 [D loss: 0.693802, acc.: 49.61%] [G loss: 0.691445]
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4092 [D loss: 0.693756, acc.: 49.22%] [G loss: 0.689781]
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4093 [D loss: 0.693280, acc.: 53.12%] [G loss: 0.690921]
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4094 [D loss: 0.693452, acc.: 49.22%] [G loss: 0.692807]
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4095 [D loss: 0.693213, acc.: 51.76%] [G loss: 0.690317]
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4096 [D loss: 0.693784, acc.: 47.85%] [G loss: 0.692541]
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4097 [D loss: 0.693237, acc.: 50.78%] [G loss: 0.694591]
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4098 [D loss: 0.692007, acc.: 54.10%] [G loss: 0.694018]
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4099 [D loss: 0.693245, acc.: 51.95%] [G loss: 0.693179]
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4100 [D loss: 0.693078, acc.: 51.17%] [G loss: 0.694389]
1/1 [==============================] - 0s 20ms/step
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4101 [D loss: 0.692583, acc.: 51.37%] [G loss: 0.693531]
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4102 [D loss: 0.692670, acc.: 51.56%] [G loss: 0.694863]
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4103 [D loss: 0.693199, acc.: 49.22%] [G loss: 0.693874]
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4104 [D loss: 0.692512, acc.: 50.39%] [G loss: 0.695468]
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4105 [D loss: 0.692269, acc.: 51.37%] [G loss: 0.692741]
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4106 [D loss: 0.693067, acc.: 47.66%] [G loss: 0.694132]
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4107 [D loss: 0.693714, acc.: 48.24%] [G loss: 0.693896]
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4108 [D loss: 0.692772, acc.: 51.37%] [G loss: 0.694514]
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4109 [D loss: 0.691950, acc.: 55.66%] [G loss: 0.691954]
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4110 [D loss: 0.693423, acc.: 49.22%] [G loss: 0.694579]
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4111 [D loss: 0.692634, acc.: 52.34%] [G loss: 0.695946]
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4112 [D loss: 0.693082, acc.: 50.59%] [G loss: 0.695106]
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4113 [D loss: 0.692218, acc.: 52.54%] [G loss: 0.695209]
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4114 [D loss: 0.692145, acc.: 54.10%] [G loss: 0.696204]
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4115 [D loss: 0.693802, acc.: 46.48%] [G loss: 0.696340]
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4116 [D loss: 0.691026, acc.: 56.05%] [G loss: 0.695343]
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4117 [D loss: 0.693330, acc.: 47.66%] [G loss: 0.698048]
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4118 [D loss: 0.692198, acc.: 51.95%] [G loss: 0.697935]
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4119 [D loss: 0.692045, acc.: 52.34%] [G loss: 0.697937]
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4120 [D loss: 0.692521, acc.: 50.78%] [G loss: 0.696473]
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4121 [D loss: 0.692126, acc.: 51.95%] [G loss: 0.694082]
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4122 [D loss: 0.692491, acc.: 52.54%] [G loss: 0.693954]
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4123 [D loss: 0.693791, acc.: 47.46%] [G loss: 0.692608]
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4124 [D loss: 0.693905, acc.: 48.24%] [G loss: 0.694080]
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4125 [D loss: 0.693118, acc.: 48.83%] [G loss: 0.693656]
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4126 [D loss: 0.694650, acc.: 45.90%] [G loss: 0.691949]
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4127 [D loss: 0.693159, acc.: 49.61%] [G loss: 0.694200]
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4128 [D loss: 0.693882, acc.: 49.61%] [G loss: 0.693856]
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4129 [D loss: 0.692951, acc.: 48.24%] [G loss: 0.692869]
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4130 [D loss: 0.693470, acc.: 50.20%] [G loss: 0.693555]
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4131 [D loss: 0.692866, acc.: 50.59%] [G loss: 0.693464]
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4132 [D loss: 0.694485, acc.: 47.27%] [G loss: 0.691835]
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4133 [D loss: 0.692595, acc.: 52.15%] [G loss: 0.694674]
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4134 [D loss: 0.692497, acc.: 52.15%] [G loss: 0.693388]
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4135 [D loss: 0.692729, acc.: 53.12%] [G loss: 0.694326]
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4136 [D loss: 0.693241, acc.: 49.61%] [G loss: 0.694669]
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4137 [D loss: 0.692008, acc.: 53.12%] [G loss: 0.695996]
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4138 [D loss: 0.692664, acc.: 53.32%] [G loss: 0.695073]
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4139 [D loss: 0.694410, acc.: 45.90%] [G loss: 0.694183]
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4140 [D loss: 0.692619, acc.: 49.22%] [G loss: 0.694242]
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4141 [D loss: 0.693294, acc.: 48.63%] [G loss: 0.694562]
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4142 [D loss: 0.692706, acc.: 50.00%] [G loss: 0.695233]
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4143 [D loss: 0.692928, acc.: 50.98%] [G loss: 0.696341]
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4144 [D loss: 0.694161, acc.: 49.80%] [G loss: 0.695651]
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4145 [D loss: 0.693815, acc.: 46.88%] [G loss: 0.695117]
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4146 [D loss: 0.692865, acc.: 50.39%] [G loss: 0.696010]
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4147 [D loss: 0.693081, acc.: 50.98%] [G loss: 0.695190]
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4148 [D loss: 0.692978, acc.: 51.17%] [G loss: 0.694642]
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4149 [D loss: 0.692946, acc.: 51.17%] [G loss: 0.694225]
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4150 [D loss: 0.693103, acc.: 48.63%] [G loss: 0.695659]
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4151 [D loss: 0.692924, acc.: 52.54%] [G loss: 0.695357]
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4152 [D loss: 0.692949, acc.: 50.98%] [G loss: 0.694786]
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4153 [D loss: 0.692791, acc.: 52.54%] [G loss: 0.694691]
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4154 [D loss: 0.693324, acc.: 48.83%] [G loss: 0.693679]
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4155 [D loss: 0.692598, acc.: 49.61%] [G loss: 0.694223]
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4156 [D loss: 0.693165, acc.: 49.80%] [G loss: 0.694698]
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4157 [D loss: 0.692633, acc.: 50.59%] [G loss: 0.694170]
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4158 [D loss: 0.694556, acc.: 44.14%] [G loss: 0.692725]
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4159 [D loss: 0.693274, acc.: 49.80%] [G loss: 0.692312]
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4160 [D loss: 0.692710, acc.: 50.20%] [G loss: 0.693067]
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4161 [D loss: 0.693626, acc.: 47.07%] [G loss: 0.692470]
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4162 [D loss: 0.692785, acc.: 49.22%] [G loss: 0.690834]
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4163 [D loss: 0.693322, acc.: 50.59%] [G loss: 0.690200]
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4164 [D loss: 0.693325, acc.: 50.00%] [G loss: 0.691676]
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4165 [D loss: 0.693082, acc.: 50.59%] [G loss: 0.690118]
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4166 [D loss: 0.693011, acc.: 49.22%] [G loss: 0.691360]
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4167 [D loss: 0.693861, acc.: 48.44%] [G loss: 0.691629]
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4168 [D loss: 0.693962, acc.: 47.85%] [G loss: 0.691936]
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4169 [D loss: 0.693542, acc.: 49.61%] [G loss: 0.693714]
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4170 [D loss: 0.693103, acc.: 50.98%] [G loss: 0.696527]
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4171 [D loss: 0.692460, acc.: 50.20%] [G loss: 0.694479]
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4172 [D loss: 0.692935, acc.: 48.83%] [G loss: 0.694227]
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4173 [D loss: 0.693132, acc.: 51.17%] [G loss: 0.694251]
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4174 [D loss: 0.691773, acc.: 53.32%] [G loss: 0.694095]
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4175 [D loss: 0.693506, acc.: 51.76%] [G loss: 0.692198]
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4176 [D loss: 0.692585, acc.: 53.52%] [G loss: 0.692919]
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4177 [D loss: 0.693412, acc.: 49.61%] [G loss: 0.693173]
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4178 [D loss: 0.693478, acc.: 49.41%] [G loss: 0.692529]
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4179 [D loss: 0.692484, acc.: 52.93%] [G loss: 0.691553]
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4180 [D loss: 0.692667, acc.: 51.95%] [G loss: 0.693011]
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4181 [D loss: 0.692638, acc.: 51.56%] [G loss: 0.693328]
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4182 [D loss: 0.693466, acc.: 47.07%] [G loss: 0.693000]
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4183 [D loss: 0.692865, acc.: 48.63%] [G loss: 0.692526]
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4184 [D loss: 0.692555, acc.: 53.52%] [G loss: 0.691993]
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4185 [D loss: 0.692957, acc.: 50.98%] [G loss: 0.693191]
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4186 [D loss: 0.692901, acc.: 49.61%] [G loss: 0.692058]
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4187 [D loss: 0.692776, acc.: 50.78%] [G loss: 0.692544]
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4188 [D loss: 0.692914, acc.: 51.17%] [G loss: 0.692703]
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4189 [D loss: 0.692579, acc.: 52.73%] [G loss: 0.695469]
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4190 [D loss: 0.692815, acc.: 51.17%] [G loss: 0.693067]
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4191 [D loss: 0.691728, acc.: 52.73%] [G loss: 0.693857]
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4192 [D loss: 0.691802, acc.: 54.49%] [G loss: 0.694463]
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4193 [D loss: 0.692967, acc.: 50.98%] [G loss: 0.695021]
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4194 [D loss: 0.691687, acc.: 55.27%] [G loss: 0.691893]
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4195 [D loss: 0.693422, acc.: 50.59%] [G loss: 0.692501]
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4196 [D loss: 0.692885, acc.: 48.83%] [G loss: 0.692497]
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4197 [D loss: 0.693859, acc.: 47.07%] [G loss: 0.692559]
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4198 [D loss: 0.693295, acc.: 49.80%] [G loss: 0.691366]
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4199 [D loss: 0.691953, acc.: 53.32%] [G loss: 0.692687]
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4200 [D loss: 0.692060, acc.: 52.93%] [G loss: 0.692006]
1/1 [==============================] - 0s 16ms/step
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4201 [D loss: 0.693902, acc.: 49.22%] [G loss: 0.691427]
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4202 [D loss: 0.692445, acc.: 51.95%] [G loss: 0.693356]
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4203 [D loss: 0.693787, acc.: 48.05%] [G loss: 0.693462]
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4204 [D loss: 0.694145, acc.: 49.22%] [G loss: 0.693650]
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4205 [D loss: 0.693227, acc.: 52.15%] [G loss: 0.694491]
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4206 [D loss: 0.693291, acc.: 49.41%] [G loss: 0.694267]
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4207 [D loss: 0.693301, acc.: 53.32%] [G loss: 0.693463]
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4208 [D loss: 0.693332, acc.: 51.17%] [G loss: 0.692561]
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4209 [D loss: 0.692673, acc.: 53.12%] [G loss: 0.693926]
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4210 [D loss: 0.692630, acc.: 50.20%] [G loss: 0.695344]
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4211 [D loss: 0.692484, acc.: 49.22%] [G loss: 0.695555]
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4212 [D loss: 0.693409, acc.: 48.44%] [G loss: 0.694438]
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4213 [D loss: 0.693409, acc.: 49.41%] [G loss: 0.695204]
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4214 [D loss: 0.693373, acc.: 50.59%] [G loss: 0.695376]
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4215 [D loss: 0.693609, acc.: 47.27%] [G loss: 0.694649]
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4216 [D loss: 0.694166, acc.: 48.63%] [G loss: 0.694389]
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4217 [D loss: 0.694583, acc.: 43.55%] [G loss: 0.695066]
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4218 [D loss: 0.692818, acc.: 53.52%] [G loss: 0.696152]
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4219 [D loss: 0.693644, acc.: 48.05%] [G loss: 0.694763]
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4220 [D loss: 0.693005, acc.: 51.95%] [G loss: 0.695439]
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4221 [D loss: 0.692058, acc.: 53.71%] [G loss: 0.694574]
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4222 [D loss: 0.693822, acc.: 51.37%] [G loss: 0.694811]
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4223 [D loss: 0.691696, acc.: 53.52%] [G loss: 0.693237]
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4224 [D loss: 0.692010, acc.: 51.56%] [G loss: 0.695144]
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4225 [D loss: 0.693642, acc.: 48.24%] [G loss: 0.695853]
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4226 [D loss: 0.693001, acc.: 51.17%] [G loss: 0.694694]
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4227 [D loss: 0.691844, acc.: 53.12%] [G loss: 0.696978]
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4228 [D loss: 0.692476, acc.: 50.39%] [G loss: 0.696788]
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4229 [D loss: 0.693016, acc.: 49.41%] [G loss: 0.695038]
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4230 [D loss: 0.691403, acc.: 54.88%] [G loss: 0.695340]
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4231 [D loss: 0.691750, acc.: 55.66%] [G loss: 0.694851]
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4232 [D loss: 0.692294, acc.: 51.95%] [G loss: 0.693973]
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4233 [D loss: 0.694197, acc.: 46.68%] [G loss: 0.694112]
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4234 [D loss: 0.692476, acc.: 51.95%] [G loss: 0.692285]
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4235 [D loss: 0.692416, acc.: 53.52%] [G loss: 0.691791]
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4236 [D loss: 0.694260, acc.: 48.44%] [G loss: 0.692209]
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4237 [D loss: 0.692589, acc.: 52.34%] [G loss: 0.692636]
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4238 [D loss: 0.692463, acc.: 51.95%] [G loss: 0.693340]
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4239 [D loss: 0.692150, acc.: 55.08%] [G loss: 0.693077]
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4240 [D loss: 0.692240, acc.: 52.15%] [G loss: 0.693702]
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4241 [D loss: 0.692247, acc.: 50.98%] [G loss: 0.692996]
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4242 [D loss: 0.692538, acc.: 52.15%] [G loss: 0.691825]
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4243 [D loss: 0.693527, acc.: 48.63%] [G loss: 0.692955]
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4244 [D loss: 0.692854, acc.: 51.56%] [G loss: 0.691664]
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4245 [D loss: 0.692935, acc.: 52.73%] [G loss: 0.690263]
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4246 [D loss: 0.692635, acc.: 52.34%] [G loss: 0.692104]
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4247 [D loss: 0.693938, acc.: 47.27%] [G loss: 0.690225]
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4248 [D loss: 0.693566, acc.: 50.39%] [G loss: 0.690550]
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4249 [D loss: 0.692833, acc.: 50.39%] [G loss: 0.692961]
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4250 [D loss: 0.694007, acc.: 49.02%] [G loss: 0.690136]
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4251 [D loss: 0.692434, acc.: 51.95%] [G loss: 0.691669]
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4252 [D loss: 0.693796, acc.: 48.63%] [G loss: 0.691071]
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4253 [D loss: 0.692499, acc.: 50.00%] [G loss: 0.691812]
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4254 [D loss: 0.692256, acc.: 53.52%] [G loss: 0.693232]
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4255 [D loss: 0.692533, acc.: 51.76%] [G loss: 0.692274]
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4256 [D loss: 0.692876, acc.: 53.12%] [G loss: 0.693020]
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4257 [D loss: 0.692871, acc.: 50.78%] [G loss: 0.691861]
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4258 [D loss: 0.694136, acc.: 47.27%] [G loss: 0.691908]
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4259 [D loss: 0.693041, acc.: 50.59%] [G loss: 0.691849]
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4260 [D loss: 0.693022, acc.: 51.56%] [G loss: 0.692715]
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4261 [D loss: 0.693495, acc.: 49.80%] [G loss: 0.692847]
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4262 [D loss: 0.693509, acc.: 48.63%] [G loss: 0.693490]
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4263 [D loss: 0.693161, acc.: 50.78%] [G loss: 0.693811]
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4264 [D loss: 0.691807, acc.: 53.52%] [G loss: 0.694017]
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4265 [D loss: 0.692665, acc.: 52.54%] [G loss: 0.693090]
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4266 [D loss: 0.692917, acc.: 49.41%] [G loss: 0.693437]
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4267 [D loss: 0.693086, acc.: 49.41%] [G loss: 0.694206]
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4268 [D loss: 0.691564, acc.: 53.12%] [G loss: 0.694077]
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4269 [D loss: 0.694076, acc.: 49.02%] [G loss: 0.692954]
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4270 [D loss: 0.693842, acc.: 48.05%] [G loss: 0.693202]
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4271 [D loss: 0.692553, acc.: 51.37%] [G loss: 0.691220]
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4272 [D loss: 0.692741, acc.: 52.15%] [G loss: 0.693337]
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4273 [D loss: 0.693284, acc.: 51.56%] [G loss: 0.690926]
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4274 [D loss: 0.693317, acc.: 48.83%] [G loss: 0.693772]
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4275 [D loss: 0.693809, acc.: 46.48%] [G loss: 0.692678]
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4276 [D loss: 0.693506, acc.: 51.56%] [G loss: 0.695167]
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4277 [D loss: 0.692995, acc.: 49.22%] [G loss: 0.694283]
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4278 [D loss: 0.693360, acc.: 47.85%] [G loss: 0.694611]
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4279 [D loss: 0.692653, acc.: 51.76%] [G loss: 0.692948]
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4280 [D loss: 0.693437, acc.: 51.17%] [G loss: 0.694921]
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4281 [D loss: 0.693029, acc.: 48.24%] [G loss: 0.693633]
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4282 [D loss: 0.692813, acc.: 50.39%] [G loss: 0.694406]
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4283 [D loss: 0.692069, acc.: 54.10%] [G loss: 0.695373]
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4284 [D loss: 0.693732, acc.: 51.17%] [G loss: 0.695984]
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4285 [D loss: 0.691858, acc.: 52.93%] [G loss: 0.693246]
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4286 [D loss: 0.692725, acc.: 51.56%] [G loss: 0.695337]
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4287 [D loss: 0.691562, acc.: 55.47%] [G loss: 0.694983]
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4288 [D loss: 0.692335, acc.: 52.34%] [G loss: 0.696095]
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4289 [D loss: 0.692990, acc.: 49.02%] [G loss: 0.693646]
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4290 [D loss: 0.692681, acc.: 51.76%] [G loss: 0.694116]
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4291 [D loss: 0.692751, acc.: 51.76%] [G loss: 0.691639]
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4292 [D loss: 0.693190, acc.: 49.41%] [G loss: 0.692160]
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4293 [D loss: 0.694616, acc.: 45.51%] [G loss: 0.693494]
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4294 [D loss: 0.693568, acc.: 48.83%] [G loss: 0.692866]
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4295 [D loss: 0.693564, acc.: 51.56%] [G loss: 0.692571]
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4296 [D loss: 0.692747, acc.: 51.17%] [G loss: 0.693200]
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4297 [D loss: 0.693995, acc.: 46.88%] [G loss: 0.693418]
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4298 [D loss: 0.692956, acc.: 50.78%] [G loss: 0.694125]
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4299 [D loss: 0.692602, acc.: 52.54%] [G loss: 0.693094]
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4300 [D loss: 0.692918, acc.: 50.78%] [G loss: 0.693089]
1/1 [==============================] - 0s 15ms/step
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4301 [D loss: 0.692575, acc.: 53.12%] [G loss: 0.694425]
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4302 [D loss: 0.692865, acc.: 51.76%] [G loss: 0.694256]
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4303 [D loss: 0.692325, acc.: 52.34%] [G loss: 0.694477]
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4304 [D loss: 0.692123, acc.: 51.37%] [G loss: 0.694139]
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4305 [D loss: 0.692792, acc.: 50.78%] [G loss: 0.694301]
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4306 [D loss: 0.693166, acc.: 50.98%] [G loss: 0.693904]
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4307 [D loss: 0.692847, acc.: 50.20%] [G loss: 0.695022]
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4308 [D loss: 0.693341, acc.: 48.83%] [G loss: 0.695285]
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4309 [D loss: 0.693662, acc.: 50.20%] [G loss: 0.694995]
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4310 [D loss: 0.693067, acc.: 52.73%] [G loss: 0.695354]
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4311 [D loss: 0.692987, acc.: 51.95%] [G loss: 0.695610]
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4312 [D loss: 0.693016, acc.: 49.41%] [G loss: 0.695953]
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4313 [D loss: 0.693139, acc.: 49.22%] [G loss: 0.693765]
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4314 [D loss: 0.693132, acc.: 51.17%] [G loss: 0.693690]
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4315 [D loss: 0.693133, acc.: 49.22%] [G loss: 0.693870]
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4316 [D loss: 0.691747, acc.: 53.91%] [G loss: 0.693651]
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4317 [D loss: 0.692652, acc.: 51.17%] [G loss: 0.692415]
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4318 [D loss: 0.692671, acc.: 52.54%] [G loss: 0.694956]
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4319 [D loss: 0.692747, acc.: 51.76%] [G loss: 0.695676]
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4320 [D loss: 0.691776, acc.: 53.91%] [G loss: 0.694468]
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4321 [D loss: 0.693355, acc.: 49.02%] [G loss: 0.696436]
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4322 [D loss: 0.693113, acc.: 48.24%] [G loss: 0.694549]
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4323 [D loss: 0.692045, acc.: 52.73%] [G loss: 0.695312]
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4324 [D loss: 0.692054, acc.: 52.93%] [G loss: 0.694436]
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4325 [D loss: 0.694069, acc.: 48.63%] [G loss: 0.692351]
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4326 [D loss: 0.694183, acc.: 48.44%] [G loss: 0.692731]
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4327 [D loss: 0.693039, acc.: 52.73%] [G loss: 0.692053]
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4328 [D loss: 0.693941, acc.: 46.88%] [G loss: 0.693426]
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4329 [D loss: 0.693857, acc.: 47.46%] [G loss: 0.690520]
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4330 [D loss: 0.693979, acc.: 47.85%] [G loss: 0.693502]
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4331 [D loss: 0.693496, acc.: 47.46%] [G loss: 0.694050]
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4332 [D loss: 0.693688, acc.: 46.48%] [G loss: 0.692674]
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4333 [D loss: 0.693062, acc.: 50.39%] [G loss: 0.692067]
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4334 [D loss: 0.694414, acc.: 45.90%] [G loss: 0.692814]
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4335 [D loss: 0.692871, acc.: 53.52%] [G loss: 0.692986]
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4336 [D loss: 0.692686, acc.: 51.37%] [G loss: 0.693829]
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4337 [D loss: 0.692222, acc.: 55.66%] [G loss: 0.693336]
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4338 [D loss: 0.691177, acc.: 56.45%] [G loss: 0.695093]
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4339 [D loss: 0.692138, acc.: 54.10%] [G loss: 0.695032]
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4340 [D loss: 0.693110, acc.: 49.61%] [G loss: 0.693555]
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4341 [D loss: 0.692080, acc.: 54.69%] [G loss: 0.695015]
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4342 [D loss: 0.692508, acc.: 50.59%] [G loss: 0.693046]
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4343 [D loss: 0.692821, acc.: 47.85%] [G loss: 0.694260]
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4344 [D loss: 0.692345, acc.: 52.93%] [G loss: 0.695047]
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4345 [D loss: 0.693315, acc.: 49.22%] [G loss: 0.692870]
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4346 [D loss: 0.693285, acc.: 51.76%] [G loss: 0.692676]
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4347 [D loss: 0.693168, acc.: 49.41%] [G loss: 0.690532]
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4348 [D loss: 0.693339, acc.: 49.61%] [G loss: 0.693635]
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4349 [D loss: 0.692821, acc.: 52.15%] [G loss: 0.693479]
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4350 [D loss: 0.693762, acc.: 49.02%] [G loss: 0.693289]
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4351 [D loss: 0.693519, acc.: 49.80%] [G loss: 0.692860]
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4352 [D loss: 0.692420, acc.: 53.52%] [G loss: 0.692245]
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4353 [D loss: 0.693935, acc.: 48.63%] [G loss: 0.695026]
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4354 [D loss: 0.693443, acc.: 48.44%] [G loss: 0.695470]
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4355 [D loss: 0.692982, acc.: 53.91%] [G loss: 0.695813]
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4356 [D loss: 0.692422, acc.: 52.93%] [G loss: 0.695917]
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4357 [D loss: 0.692210, acc.: 51.17%] [G loss: 0.695996]
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4358 [D loss: 0.691455, acc.: 55.08%] [G loss: 0.695085]
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4359 [D loss: 0.692086, acc.: 52.15%] [G loss: 0.695480]
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4360 [D loss: 0.692610, acc.: 51.56%] [G loss: 0.694678]
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4361 [D loss: 0.692330, acc.: 53.52%] [G loss: 0.693234]
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4362 [D loss: 0.692943, acc.: 48.63%] [G loss: 0.694944]
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4363 [D loss: 0.693767, acc.: 47.27%] [G loss: 0.693967]
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4364 [D loss: 0.692902, acc.: 50.00%] [G loss: 0.693507]
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4365 [D loss: 0.693828, acc.: 47.07%] [G loss: 0.692248]
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4366 [D loss: 0.693300, acc.: 48.05%] [G loss: 0.692118]
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4367 [D loss: 0.693356, acc.: 51.95%] [G loss: 0.692975]
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4368 [D loss: 0.693475, acc.: 47.66%] [G loss: 0.692849]
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4369 [D loss: 0.692684, acc.: 50.39%] [G loss: 0.692891]
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4370 [D loss: 0.692744, acc.: 50.39%] [G loss: 0.693454]
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4371 [D loss: 0.692511, acc.: 51.76%] [G loss: 0.693268]
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4372 [D loss: 0.692473, acc.: 50.59%] [G loss: 0.694655]
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4373 [D loss: 0.692795, acc.: 51.95%] [G loss: 0.694078]
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4374 [D loss: 0.692112, acc.: 52.54%] [G loss: 0.693805]
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4375 [D loss: 0.693318, acc.: 48.63%] [G loss: 0.695760]
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4376 [D loss: 0.691931, acc.: 54.30%] [G loss: 0.694055]
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4377 [D loss: 0.693414, acc.: 49.22%] [G loss: 0.694695]
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4378 [D loss: 0.692313, acc.: 53.91%] [G loss: 0.695085]
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4379 [D loss: 0.692496, acc.: 52.54%] [G loss: 0.695140]
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4380 [D loss: 0.693268, acc.: 48.44%] [G loss: 0.694907]
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4381 [D loss: 0.693459, acc.: 47.66%] [G loss: 0.693317]
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4382 [D loss: 0.694506, acc.: 45.12%] [G loss: 0.691594]
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4383 [D loss: 0.692949, acc.: 49.80%] [G loss: 0.691938]
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4384 [D loss: 0.693336, acc.: 51.37%] [G loss: 0.693092]
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4385 [D loss: 0.693397, acc.: 48.63%] [G loss: 0.691592]
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4386 [D loss: 0.694653, acc.: 45.90%] [G loss: 0.691041]
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4387 [D loss: 0.693058, acc.: 48.63%] [G loss: 0.692557]
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4388 [D loss: 0.692459, acc.: 50.78%] [G loss: 0.693977]
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4389 [D loss: 0.692809, acc.: 52.15%] [G loss: 0.693021]
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4390 [D loss: 0.691435, acc.: 54.30%] [G loss: 0.693619]
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4391 [D loss: 0.692278, acc.: 50.78%] [G loss: 0.694757]
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4392 [D loss: 0.693098, acc.: 51.37%] [G loss: 0.694186]
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4393 [D loss: 0.692682, acc.: 50.00%] [G loss: 0.694458]
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4394 [D loss: 0.691915, acc.: 52.73%] [G loss: 0.694095]
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4395 [D loss: 0.692563, acc.: 49.61%] [G loss: 0.694914]
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4396 [D loss: 0.693195, acc.: 49.61%] [G loss: 0.692437]
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4397 [D loss: 0.693270, acc.: 50.39%] [G loss: 0.691918]
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4398 [D loss: 0.693728, acc.: 45.90%] [G loss: 0.691978]
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4399 [D loss: 0.693732, acc.: 46.68%] [G loss: 0.692397]
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4400 [D loss: 0.693458, acc.: 50.59%] [G loss: 0.693069]
1/1 [==============================] - 0s 15ms/step
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4401 [D loss: 0.693927, acc.: 47.27%] [G loss: 0.690377]
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4402 [D loss: 0.693111, acc.: 48.24%] [G loss: 0.692043]
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4403 [D loss: 0.693534, acc.: 48.05%] [G loss: 0.691177]
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4404 [D loss: 0.693724, acc.: 47.46%] [G loss: 0.692692]
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4405 [D loss: 0.692687, acc.: 51.37%] [G loss: 0.693582]
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4406 [D loss: 0.692824, acc.: 52.93%] [G loss: 0.694165]
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4407 [D loss: 0.692166, acc.: 53.71%] [G loss: 0.693809]
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4408 [D loss: 0.691540, acc.: 55.86%] [G loss: 0.694561]
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4409 [D loss: 0.691289, acc.: 52.93%] [G loss: 0.695197]
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4410 [D loss: 0.692433, acc.: 52.34%] [G loss: 0.694498]
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4411 [D loss: 0.693226, acc.: 48.24%] [G loss: 0.691699]
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4412 [D loss: 0.692317, acc.: 52.54%] [G loss: 0.693751]
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4413 [D loss: 0.692747, acc.: 52.15%] [G loss: 0.694294]
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4414 [D loss: 0.693066, acc.: 48.83%] [G loss: 0.694879]
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4415 [D loss: 0.693483, acc.: 49.02%] [G loss: 0.693620]
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4416 [D loss: 0.692793, acc.: 52.73%] [G loss: 0.694518]
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4417 [D loss: 0.692149, acc.: 54.88%] [G loss: 0.693117]
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4418 [D loss: 0.693468, acc.: 47.85%] [G loss: 0.693223]
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4419 [D loss: 0.693291, acc.: 52.34%] [G loss: 0.692142]
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4420 [D loss: 0.693839, acc.: 50.20%] [G loss: 0.692358]
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4421 [D loss: 0.693734, acc.: 48.44%] [G loss: 0.693357]
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4422 [D loss: 0.693335, acc.: 49.02%] [G loss: 0.693150]
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4423 [D loss: 0.694255, acc.: 49.61%] [G loss: 0.694838]
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4424 [D loss: 0.692494, acc.: 50.98%] [G loss: 0.696134]
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4425 [D loss: 0.691426, acc.: 54.30%] [G loss: 0.696808]
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4426 [D loss: 0.691983, acc.: 52.54%] [G loss: 0.696197]
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4427 [D loss: 0.691781, acc.: 52.73%] [G loss: 0.694234]
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4428 [D loss: 0.692663, acc.: 53.71%] [G loss: 0.695893]
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4429 [D loss: 0.692630, acc.: 53.52%] [G loss: 0.694097]
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4430 [D loss: 0.692866, acc.: 49.80%] [G loss: 0.695059]
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4431 [D loss: 0.693432, acc.: 50.78%] [G loss: 0.695399]
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4432 [D loss: 0.693359, acc.: 49.41%] [G loss: 0.693994]
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4433 [D loss: 0.692423, acc.: 51.37%] [G loss: 0.693228]
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4434 [D loss: 0.692735, acc.: 51.56%] [G loss: 0.694760]
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4435 [D loss: 0.692425, acc.: 51.76%] [G loss: 0.694507]
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4436 [D loss: 0.692607, acc.: 49.22%] [G loss: 0.692445]
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4437 [D loss: 0.693277, acc.: 50.78%] [G loss: 0.691987]
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4438 [D loss: 0.693594, acc.: 46.68%] [G loss: 0.692793]
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4439 [D loss: 0.693651, acc.: 50.59%] [G loss: 0.691496]
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4440 [D loss: 0.693545, acc.: 49.22%] [G loss: 0.693427]
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4441 [D loss: 0.693519, acc.: 48.83%] [G loss: 0.693377]
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4442 [D loss: 0.692497, acc.: 50.98%] [G loss: 0.694372]
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4443 [D loss: 0.694122, acc.: 48.05%] [G loss: 0.693839]
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4444 [D loss: 0.692489, acc.: 53.71%] [G loss: 0.694096]
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4445 [D loss: 0.692524, acc.: 51.56%] [G loss: 0.693879]
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4446 [D loss: 0.693024, acc.: 51.56%] [G loss: 0.694873]
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4447 [D loss: 0.692403, acc.: 50.98%] [G loss: 0.694823]
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4448 [D loss: 0.692362, acc.: 55.27%] [G loss: 0.693648]
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4449 [D loss: 0.691681, acc.: 57.42%] [G loss: 0.694247]
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4450 [D loss: 0.692858, acc.: 50.00%] [G loss: 0.694418]
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4451 [D loss: 0.692751, acc.: 51.76%] [G loss: 0.693649]
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4452 [D loss: 0.691580, acc.: 53.52%] [G loss: 0.692788]
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4453 [D loss: 0.692024, acc.: 53.12%] [G loss: 0.693537]
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4454 [D loss: 0.693900, acc.: 49.61%] [G loss: 0.692232]
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4455 [D loss: 0.694363, acc.: 48.83%] [G loss: 0.691948]
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4456 [D loss: 0.693141, acc.: 51.95%] [G loss: 0.691794]
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4457 [D loss: 0.693747, acc.: 46.68%] [G loss: 0.692908]
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4458 [D loss: 0.693204, acc.: 50.39%] [G loss: 0.694579]
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4459 [D loss: 0.692937, acc.: 51.17%] [G loss: 0.696503]
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4460 [D loss: 0.692566, acc.: 49.41%] [G loss: 0.695728]
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4461 [D loss: 0.691682, acc.: 54.88%] [G loss: 0.694780]
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4462 [D loss: 0.692006, acc.: 52.93%] [G loss: 0.693718]
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4463 [D loss: 0.692635, acc.: 52.54%] [G loss: 0.693528]
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4464 [D loss: 0.691608, acc.: 56.45%] [G loss: 0.694577]
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4465 [D loss: 0.692305, acc.: 52.93%] [G loss: 0.693120]
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4466 [D loss: 0.692504, acc.: 50.78%] [G loss: 0.694853]
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4467 [D loss: 0.692901, acc.: 50.59%] [G loss: 0.696553]
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4468 [D loss: 0.692446, acc.: 53.32%] [G loss: 0.695457]
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4469 [D loss: 0.693766, acc.: 49.80%] [G loss: 0.692949]
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4470 [D loss: 0.693841, acc.: 47.66%] [G loss: 0.694857]
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4471 [D loss: 0.692176, acc.: 48.83%] [G loss: 0.693690]
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4472 [D loss: 0.693600, acc.: 49.61%] [G loss: 0.691167]
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4473 [D loss: 0.694100, acc.: 50.39%] [G loss: 0.692235]
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4474 [D loss: 0.693269, acc.: 51.56%] [G loss: 0.692825]
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4475 [D loss: 0.692788, acc.: 52.73%] [G loss: 0.692242]
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4476 [D loss: 0.694275, acc.: 46.88%] [G loss: 0.693068]
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4477 [D loss: 0.692527, acc.: 51.56%] [G loss: 0.692588]
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4478 [D loss: 0.692836, acc.: 51.17%] [G loss: 0.693598]
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4479 [D loss: 0.693142, acc.: 49.61%] [G loss: 0.692562]
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4480 [D loss: 0.692691, acc.: 50.78%] [G loss: 0.695107]
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4481 [D loss: 0.693892, acc.: 49.02%] [G loss: 0.694792]
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4482 [D loss: 0.692626, acc.: 51.17%] [G loss: 0.694231]
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4483 [D loss: 0.692089, acc.: 52.54%] [G loss: 0.696765]
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4484 [D loss: 0.692344, acc.: 53.71%] [G loss: 0.696668]
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4485 [D loss: 0.692116, acc.: 50.59%] [G loss: 0.694434]
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4486 [D loss: 0.693699, acc.: 50.20%] [G loss: 0.696130]
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4487 [D loss: 0.691755, acc.: 52.73%] [G loss: 0.694624]
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4488 [D loss: 0.691206, acc.: 55.27%] [G loss: 0.692025]
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4489 [D loss: 0.694069, acc.: 47.46%] [G loss: 0.691822]
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4490 [D loss: 0.694752, acc.: 45.51%] [G loss: 0.689596]
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4491 [D loss: 0.693317, acc.: 49.02%] [G loss: 0.693036]
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4492 [D loss: 0.694929, acc.: 42.19%] [G loss: 0.691942]
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4493 [D loss: 0.693470, acc.: 48.44%] [G loss: 0.690886]
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4494 [D loss: 0.693729, acc.: 48.05%] [G loss: 0.693384]
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4495 [D loss: 0.693698, acc.: 49.61%] [G loss: 0.693078]
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4496 [D loss: 0.693668, acc.: 50.00%] [G loss: 0.692743]
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4497 [D loss: 0.692128, acc.: 53.91%] [G loss: 0.693300]
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4498 [D loss: 0.693999, acc.: 47.46%] [G loss: 0.693849]
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4499 [D loss: 0.692626, acc.: 51.76%] [G loss: 0.695716]
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4500 [D loss: 0.692855, acc.: 53.91%] [G loss: 0.695093]
1/1 [==============================] - 0s 18ms/step
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4501 [D loss: 0.691454, acc.: 55.08%] [G loss: 0.695813]
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4502 [D loss: 0.692880, acc.: 48.83%] [G loss: 0.696024]
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4503 [D loss: 0.692151, acc.: 53.52%] [G loss: 0.693549]
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4504 [D loss: 0.692039, acc.: 53.12%] [G loss: 0.693319]
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4505 [D loss: 0.693652, acc.: 49.41%] [G loss: 0.693521]
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4506 [D loss: 0.692028, acc.: 52.93%] [G loss: 0.693253]
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4507 [D loss: 0.694514, acc.: 45.51%] [G loss: 0.693650]
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4508 [D loss: 0.693132, acc.: 49.80%] [G loss: 0.693896]
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4509 [D loss: 0.692907, acc.: 51.37%] [G loss: 0.694428]
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4510 [D loss: 0.693392, acc.: 49.41%] [G loss: 0.693810]
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4511 [D loss: 0.694169, acc.: 47.66%] [G loss: 0.693915]
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4512 [D loss: 0.693069, acc.: 51.76%] [G loss: 0.692705]
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4513 [D loss: 0.692984, acc.: 50.98%] [G loss: 0.692653]
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4514 [D loss: 0.693294, acc.: 48.83%] [G loss: 0.692245]
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4515 [D loss: 0.693377, acc.: 50.20%] [G loss: 0.691660]
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4516 [D loss: 0.692705, acc.: 51.17%] [G loss: 0.693337]
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4517 [D loss: 0.692971, acc.: 51.17%] [G loss: 0.693423]
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4518 [D loss: 0.692666, acc.: 50.00%] [G loss: 0.693630]
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4519 [D loss: 0.692184, acc.: 53.91%] [G loss: 0.693564]
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4520 [D loss: 0.691893, acc.: 55.47%] [G loss: 0.693539]
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4521 [D loss: 0.692195, acc.: 53.32%] [G loss: 0.695216]
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4522 [D loss: 0.692256, acc.: 51.37%] [G loss: 0.693587]
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4523 [D loss: 0.691619, acc.: 55.08%] [G loss: 0.694158]
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4524 [D loss: 0.692348, acc.: 53.91%] [G loss: 0.695051]
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4525 [D loss: 0.691291, acc.: 54.10%] [G loss: 0.694127]
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4526 [D loss: 0.692074, acc.: 53.32%] [G loss: 0.694285]
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4527 [D loss: 0.692575, acc.: 51.17%] [G loss: 0.694641]
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4528 [D loss: 0.693158, acc.: 50.20%] [G loss: 0.691450]
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4529 [D loss: 0.693621, acc.: 48.63%] [G loss: 0.691868]
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4530 [D loss: 0.692179, acc.: 55.08%] [G loss: 0.692861]
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4531 [D loss: 0.692306, acc.: 53.32%] [G loss: 0.691549]
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4532 [D loss: 0.692572, acc.: 52.73%] [G loss: 0.691824]
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4533 [D loss: 0.693848, acc.: 47.66%] [G loss: 0.692549]
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4534 [D loss: 0.693098, acc.: 49.61%] [G loss: 0.692189]
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4535 [D loss: 0.693838, acc.: 49.02%] [G loss: 0.690503]
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4536 [D loss: 0.692852, acc.: 49.22%] [G loss: 0.692104]
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4537 [D loss: 0.692533, acc.: 49.61%] [G loss: 0.692749]
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4538 [D loss: 0.693549, acc.: 49.22%] [G loss: 0.692761]
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4539 [D loss: 0.693660, acc.: 49.22%] [G loss: 0.693676]
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4540 [D loss: 0.693705, acc.: 49.02%] [G loss: 0.694969]
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4541 [D loss: 0.694005, acc.: 46.88%] [G loss: 0.692357]
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4542 [D loss: 0.692257, acc.: 51.17%] [G loss: 0.693397]
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4543 [D loss: 0.691731, acc.: 53.52%] [G loss: 0.691602]
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4544 [D loss: 0.692916, acc.: 49.41%] [G loss: 0.694910]
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4545 [D loss: 0.693351, acc.: 49.61%] [G loss: 0.694592]
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4546 [D loss: 0.692480, acc.: 53.52%] [G loss: 0.694734]
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4547 [D loss: 0.693602, acc.: 47.85%] [G loss: 0.694183]
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4548 [D loss: 0.694284, acc.: 47.66%] [G loss: 0.693985]
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4549 [D loss: 0.692188, acc.: 53.12%] [G loss: 0.692712]
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4550 [D loss: 0.693629, acc.: 47.85%] [G loss: 0.693072]
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4551 [D loss: 0.693800, acc.: 48.44%] [G loss: 0.693739]
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4552 [D loss: 0.693802, acc.: 48.63%] [G loss: 0.693980]
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4553 [D loss: 0.694773, acc.: 44.53%] [G loss: 0.693810]
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4554 [D loss: 0.693970, acc.: 46.68%] [G loss: 0.693966]
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4555 [D loss: 0.693424, acc.: 49.61%] [G loss: 0.694742]
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4556 [D loss: 0.693364, acc.: 48.63%] [G loss: 0.694628]
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4557 [D loss: 0.692177, acc.: 53.52%] [G loss: 0.695994]
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4558 [D loss: 0.691909, acc.: 56.45%] [G loss: 0.695659]
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4559 [D loss: 0.692417, acc.: 51.37%] [G loss: 0.694598]
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4560 [D loss: 0.693356, acc.: 50.00%] [G loss: 0.694252]
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4561 [D loss: 0.692653, acc.: 50.00%] [G loss: 0.696420]
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4562 [D loss: 0.692083, acc.: 53.71%] [G loss: 0.695706]
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4563 [D loss: 0.692926, acc.: 50.78%] [G loss: 0.696989]
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4564 [D loss: 0.691639, acc.: 55.47%] [G loss: 0.695994]
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4565 [D loss: 0.692018, acc.: 53.12%] [G loss: 0.697532]
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4566 [D loss: 0.692724, acc.: 52.15%] [G loss: 0.696632]
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4567 [D loss: 0.692029, acc.: 55.66%] [G loss: 0.696263]
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4568 [D loss: 0.693065, acc.: 50.00%] [G loss: 0.696368]
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4569 [D loss: 0.692707, acc.: 50.59%] [G loss: 0.694747]
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4570 [D loss: 0.693828, acc.: 46.68%] [G loss: 0.692817]
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4571 [D loss: 0.692569, acc.: 52.93%] [G loss: 0.692989]
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4572 [D loss: 0.693163, acc.: 49.61%] [G loss: 0.692736]
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4573 [D loss: 0.692512, acc.: 50.59%] [G loss: 0.690639]
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4574 [D loss: 0.694441, acc.: 48.24%] [G loss: 0.693217]
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4575 [D loss: 0.693199, acc.: 50.20%] [G loss: 0.692033]
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4576 [D loss: 0.692730, acc.: 51.17%] [G loss: 0.690765]
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4577 [D loss: 0.691700, acc.: 56.84%] [G loss: 0.691375]
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4578 [D loss: 0.693025, acc.: 50.98%] [G loss: 0.694033]
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4579 [D loss: 0.692438, acc.: 52.34%] [G loss: 0.694028]
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4580 [D loss: 0.692638, acc.: 51.17%] [G loss: 0.694089]
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4581 [D loss: 0.692598, acc.: 51.37%] [G loss: 0.694630]
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4582 [D loss: 0.692901, acc.: 52.15%] [G loss: 0.695821]
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4583 [D loss: 0.692774, acc.: 52.93%] [G loss: 0.695645]
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4584 [D loss: 0.692389, acc.: 52.54%] [G loss: 0.694863]
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4585 [D loss: 0.692513, acc.: 50.20%] [G loss: 0.695624]
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4586 [D loss: 0.692763, acc.: 50.20%] [G loss: 0.693083]
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4587 [D loss: 0.691686, acc.: 55.08%] [G loss: 0.694237]
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4588 [D loss: 0.692461, acc.: 51.56%] [G loss: 0.693320]
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4589 [D loss: 0.692324, acc.: 50.00%] [G loss: 0.692890]
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4590 [D loss: 0.692960, acc.: 50.00%] [G loss: 0.693913]
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4591 [D loss: 0.694316, acc.: 48.63%] [G loss: 0.692700]
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4592 [D loss: 0.693802, acc.: 47.46%] [G loss: 0.692864]
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4593 [D loss: 0.693419, acc.: 51.56%] [G loss: 0.692093]
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4594 [D loss: 0.693161, acc.: 52.34%] [G loss: 0.691918]
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4595 [D loss: 0.694716, acc.: 47.27%] [G loss: 0.692245]
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4596 [D loss: 0.693970, acc.: 48.63%] [G loss: 0.693750]
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4597 [D loss: 0.694653, acc.: 45.90%] [G loss: 0.695264]
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4598 [D loss: 0.693361, acc.: 48.44%] [G loss: 0.696043]
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4599 [D loss: 0.693989, acc.: 48.63%] [G loss: 0.694377]
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4600 [D loss: 0.692485, acc.: 51.76%] [G loss: 0.694384]
1/1 [==============================] - 0s 16ms/step
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4601 [D loss: 0.692570, acc.: 51.95%] [G loss: 0.695363]
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4602 [D loss: 0.692710, acc.: 53.32%] [G loss: 0.696813]
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4603 [D loss: 0.691928, acc.: 52.93%] [G loss: 0.696453]
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4604 [D loss: 0.691976, acc.: 52.34%] [G loss: 0.695985]
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4605 [D loss: 0.691713, acc.: 56.05%] [G loss: 0.696135]
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4606 [D loss: 0.691819, acc.: 55.47%] [G loss: 0.694050]
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4607 [D loss: 0.691271, acc.: 56.64%] [G loss: 0.696255]
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4608 [D loss: 0.691648, acc.: 53.52%] [G loss: 0.695318]
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4609 [D loss: 0.692677, acc.: 46.68%] [G loss: 0.694810]
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4610 [D loss: 0.692693, acc.: 50.78%] [G loss: 0.697204]
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4611 [D loss: 0.692818, acc.: 51.56%] [G loss: 0.696034]
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4612 [D loss: 0.692534, acc.: 52.54%] [G loss: 0.694465]
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4613 [D loss: 0.693405, acc.: 49.22%] [G loss: 0.693683]
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4614 [D loss: 0.693311, acc.: 50.00%] [G loss: 0.694902]
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4615 [D loss: 0.692521, acc.: 53.32%] [G loss: 0.692543]
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4616 [D loss: 0.692249, acc.: 51.37%] [G loss: 0.692932]
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4617 [D loss: 0.693834, acc.: 44.73%] [G loss: 0.693582]
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4618 [D loss: 0.693170, acc.: 51.17%] [G loss: 0.693853]
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4619 [D loss: 0.692949, acc.: 49.61%] [G loss: 0.693269]
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4620 [D loss: 0.693596, acc.: 50.00%] [G loss: 0.694279]
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4621 [D loss: 0.691701, acc.: 53.71%] [G loss: 0.694225]
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4622 [D loss: 0.693242, acc.: 50.98%] [G loss: 0.697054]
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4623 [D loss: 0.692867, acc.: 51.17%] [G loss: 0.694865]
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4624 [D loss: 0.691224, acc.: 54.69%] [G loss: 0.695890]
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4625 [D loss: 0.692426, acc.: 50.98%] [G loss: 0.697862]
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4626 [D loss: 0.692955, acc.: 50.20%] [G loss: 0.696812]
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4627 [D loss: 0.692887, acc.: 50.20%] [G loss: 0.694699]
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4628 [D loss: 0.692219, acc.: 53.12%] [G loss: 0.695305]
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4629 [D loss: 0.691532, acc.: 54.88%] [G loss: 0.696555]
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4630 [D loss: 0.692311, acc.: 51.56%] [G loss: 0.694963]
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4631 [D loss: 0.693905, acc.: 48.83%] [G loss: 0.693956]
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4632 [D loss: 0.691676, acc.: 54.10%] [G loss: 0.694177]
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4633 [D loss: 0.693896, acc.: 47.27%] [G loss: 0.692323]
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4634 [D loss: 0.693406, acc.: 48.83%] [G loss: 0.692796]
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4635 [D loss: 0.692621, acc.: 50.20%] [G loss: 0.692516]
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4636 [D loss: 0.694742, acc.: 44.73%] [G loss: 0.691839]
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4637 [D loss: 0.693635, acc.: 49.02%] [G loss: 0.691314]
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4638 [D loss: 0.693299, acc.: 48.05%] [G loss: 0.692857]
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4639 [D loss: 0.692393, acc.: 53.71%] [G loss: 0.692580]
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4640 [D loss: 0.692559, acc.: 50.00%] [G loss: 0.692022]
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4641 [D loss: 0.693216, acc.: 52.15%] [G loss: 0.695744]
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4642 [D loss: 0.691826, acc.: 55.08%] [G loss: 0.691679]
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4643 [D loss: 0.693578, acc.: 47.07%] [G loss: 0.694037]
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4644 [D loss: 0.692123, acc.: 54.10%] [G loss: 0.693759]
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4645 [D loss: 0.692495, acc.: 49.61%] [G loss: 0.693018]
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4646 [D loss: 0.693007, acc.: 49.80%] [G loss: 0.694337]
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4647 [D loss: 0.693030, acc.: 49.02%] [G loss: 0.693557]
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4648 [D loss: 0.692546, acc.: 50.00%] [G loss: 0.691968]
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4649 [D loss: 0.692740, acc.: 48.83%] [G loss: 0.692742]
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4650 [D loss: 0.693836, acc.: 48.63%] [G loss: 0.692379]
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4651 [D loss: 0.692585, acc.: 49.02%] [G loss: 0.692571]
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4652 [D loss: 0.692839, acc.: 51.56%] [G loss: 0.692628]
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4653 [D loss: 0.693640, acc.: 48.05%] [G loss: 0.692427]
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4654 [D loss: 0.693478, acc.: 48.05%] [G loss: 0.692310]
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4655 [D loss: 0.693814, acc.: 45.90%] [G loss: 0.693676]
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4656 [D loss: 0.694196, acc.: 45.51%] [G loss: 0.693652]
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4657 [D loss: 0.693988, acc.: 48.44%] [G loss: 0.694583]
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4658 [D loss: 0.693072, acc.: 50.59%] [G loss: 0.694019]
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4659 [D loss: 0.692782, acc.: 53.32%] [G loss: 0.694446]
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4660 [D loss: 0.691679, acc.: 54.88%] [G loss: 0.694533]
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4661 [D loss: 0.692695, acc.: 50.20%] [G loss: 0.696600]
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4662 [D loss: 0.691962, acc.: 52.93%] [G loss: 0.697678]
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4663 [D loss: 0.693815, acc.: 49.41%] [G loss: 0.696036]
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4664 [D loss: 0.693571, acc.: 50.98%] [G loss: 0.695976]
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4665 [D loss: 0.692999, acc.: 50.39%] [G loss: 0.696516]
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4666 [D loss: 0.693851, acc.: 49.41%] [G loss: 0.694737]
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4667 [D loss: 0.691819, acc.: 53.52%] [G loss: 0.694738]
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4668 [D loss: 0.693392, acc.: 50.39%] [G loss: 0.694622]
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4669 [D loss: 0.693049, acc.: 49.61%] [G loss: 0.694331]
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4670 [D loss: 0.693175, acc.: 53.32%] [G loss: 0.694422]
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4671 [D loss: 0.692422, acc.: 52.73%] [G loss: 0.693618]
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4672 [D loss: 0.693576, acc.: 49.02%] [G loss: 0.694704]
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4673 [D loss: 0.693584, acc.: 52.15%] [G loss: 0.693302]
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4674 [D loss: 0.692412, acc.: 52.15%] [G loss: 0.693924]
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4675 [D loss: 0.693233, acc.: 50.98%] [G loss: 0.694141]
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4676 [D loss: 0.691815, acc.: 52.54%] [G loss: 0.693777]
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4677 [D loss: 0.693171, acc.: 50.59%] [G loss: 0.693946]
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4678 [D loss: 0.693706, acc.: 45.31%] [G loss: 0.694391]
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4679 [D loss: 0.692991, acc.: 49.41%] [G loss: 0.693341]
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4680 [D loss: 0.692707, acc.: 52.15%] [G loss: 0.692350]
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4681 [D loss: 0.693238, acc.: 49.61%] [G loss: 0.694064]
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4682 [D loss: 0.693630, acc.: 49.02%] [G loss: 0.693493]
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4683 [D loss: 0.692757, acc.: 53.12%] [G loss: 0.694271]
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4684 [D loss: 0.693078, acc.: 51.76%] [G loss: 0.694351]
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4685 [D loss: 0.693108, acc.: 52.54%] [G loss: 0.692711]
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4686 [D loss: 0.693206, acc.: 49.41%] [G loss: 0.693548]
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4687 [D loss: 0.691886, acc.: 51.95%] [G loss: 0.693975]
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4688 [D loss: 0.693338, acc.: 49.41%] [G loss: 0.695178]
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4689 [D loss: 0.692453, acc.: 50.20%] [G loss: 0.694893]
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4690 [D loss: 0.693788, acc.: 48.44%] [G loss: 0.696714]
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4691 [D loss: 0.691632, acc.: 54.10%] [G loss: 0.696714]
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4692 [D loss: 0.692657, acc.: 49.61%] [G loss: 0.695332]
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4693 [D loss: 0.692930, acc.: 51.76%] [G loss: 0.693868]
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4694 [D loss: 0.693968, acc.: 50.20%] [G loss: 0.696271]
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4695 [D loss: 0.693005, acc.: 50.39%] [G loss: 0.694805]
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4696 [D loss: 0.693934, acc.: 49.02%] [G loss: 0.695269]
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4697 [D loss: 0.692992, acc.: 52.15%] [G loss: 0.696336]
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4698 [D loss: 0.693602, acc.: 50.59%] [G loss: 0.694860]
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4699 [D loss: 0.692530, acc.: 52.15%] [G loss: 0.695552]
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4700 [D loss: 0.692821, acc.: 51.37%] [G loss: 0.694353]
1/1 [==============================] - 0s 15ms/step
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4701 [D loss: 0.693992, acc.: 47.07%] [G loss: 0.693176]
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4702 [D loss: 0.692613, acc.: 51.95%] [G loss: 0.694555]
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4703 [D loss: 0.693403, acc.: 50.98%] [G loss: 0.693571]
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4704 [D loss: 0.692586, acc.: 51.76%] [G loss: 0.692195]
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4705 [D loss: 0.693034, acc.: 48.44%] [G loss: 0.692199]
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4706 [D loss: 0.692819, acc.: 50.20%] [G loss: 0.693371]
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4707 [D loss: 0.691552, acc.: 55.47%] [G loss: 0.691588]
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4708 [D loss: 0.692047, acc.: 51.95%] [G loss: 0.694532]
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4709 [D loss: 0.691863, acc.: 53.32%] [G loss: 0.694276]
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4710 [D loss: 0.693651, acc.: 48.83%] [G loss: 0.692452]
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4711 [D loss: 0.693138, acc.: 51.37%] [G loss: 0.694191]
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4712 [D loss: 0.693138, acc.: 48.05%] [G loss: 0.691880]
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4713 [D loss: 0.692828, acc.: 50.78%] [G loss: 0.692629]
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4714 [D loss: 0.692596, acc.: 53.12%] [G loss: 0.691055]
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4715 [D loss: 0.693316, acc.: 49.41%] [G loss: 0.690861]
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4716 [D loss: 0.693268, acc.: 51.95%] [G loss: 0.690391]
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4717 [D loss: 0.693138, acc.: 48.05%] [G loss: 0.690807]
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4718 [D loss: 0.692818, acc.: 52.34%] [G loss: 0.688677]
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4719 [D loss: 0.692817, acc.: 52.54%] [G loss: 0.690858]
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4720 [D loss: 0.692934, acc.: 50.78%] [G loss: 0.691651]
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4721 [D loss: 0.692283, acc.: 55.27%] [G loss: 0.691447]
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4722 [D loss: 0.691947, acc.: 54.30%] [G loss: 0.691502]
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4723 [D loss: 0.692066, acc.: 54.30%] [G loss: 0.691848]
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4724 [D loss: 0.692485, acc.: 51.17%] [G loss: 0.692042]
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4725 [D loss: 0.691389, acc.: 54.69%] [G loss: 0.694538]
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4726 [D loss: 0.692647, acc.: 51.17%] [G loss: 0.692586]
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4727 [D loss: 0.690622, acc.: 56.05%] [G loss: 0.693986]
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4728 [D loss: 0.692079, acc.: 53.32%] [G loss: 0.695564]
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4729 [D loss: 0.692651, acc.: 50.59%] [G loss: 0.694091]
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4730 [D loss: 0.692291, acc.: 52.93%] [G loss: 0.694701]
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4731 [D loss: 0.692796, acc.: 49.22%] [G loss: 0.694199]
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4732 [D loss: 0.692828, acc.: 49.80%] [G loss: 0.691751]
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4733 [D loss: 0.693497, acc.: 52.34%] [G loss: 0.691416]
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4734 [D loss: 0.693158, acc.: 48.63%] [G loss: 0.691378]
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4735 [D loss: 0.693117, acc.: 50.20%] [G loss: 0.690218]
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4736 [D loss: 0.693423, acc.: 51.17%] [G loss: 0.693063]
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4737 [D loss: 0.693407, acc.: 50.59%] [G loss: 0.692888]
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4738 [D loss: 0.694077, acc.: 47.66%] [G loss: 0.692232]
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4739 [D loss: 0.693901, acc.: 49.80%] [G loss: 0.693840]
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4740 [D loss: 0.694249, acc.: 49.41%] [G loss: 0.695521]
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4741 [D loss: 0.693387, acc.: 48.24%] [G loss: 0.694076]
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4742 [D loss: 0.693861, acc.: 48.83%] [G loss: 0.692357]
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4743 [D loss: 0.692838, acc.: 51.17%] [G loss: 0.693783]
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4744 [D loss: 0.693351, acc.: 48.63%] [G loss: 0.694289]
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4745 [D loss: 0.692921, acc.: 51.95%] [G loss: 0.695733]
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4746 [D loss: 0.693003, acc.: 49.61%] [G loss: 0.694997]
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4747 [D loss: 0.693092, acc.: 50.39%] [G loss: 0.696158]
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4748 [D loss: 0.691486, acc.: 54.10%] [G loss: 0.694660]
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4749 [D loss: 0.692471, acc.: 52.15%] [G loss: 0.695188]
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4750 [D loss: 0.692461, acc.: 52.15%] [G loss: 0.697155]
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4751 [D loss: 0.693861, acc.: 48.05%] [G loss: 0.695116]
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4752 [D loss: 0.693633, acc.: 49.41%] [G loss: 0.695883]
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4753 [D loss: 0.693833, acc.: 46.88%] [G loss: 0.697461]
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4754 [D loss: 0.692474, acc.: 50.39%] [G loss: 0.694550]
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4755 [D loss: 0.693374, acc.: 49.22%] [G loss: 0.693503]
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4756 [D loss: 0.692715, acc.: 50.98%] [G loss: 0.694288]
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4757 [D loss: 0.693736, acc.: 48.24%] [G loss: 0.694401]
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4758 [D loss: 0.692568, acc.: 51.17%] [G loss: 0.693600]
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4759 [D loss: 0.692756, acc.: 48.24%] [G loss: 0.694320]
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4760 [D loss: 0.692736, acc.: 51.37%] [G loss: 0.694989]
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4761 [D loss: 0.692704, acc.: 50.39%] [G loss: 0.693541]
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4762 [D loss: 0.692983, acc.: 48.83%] [G loss: 0.695348]
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4763 [D loss: 0.692418, acc.: 51.76%] [G loss: 0.695192]
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4764 [D loss: 0.692570, acc.: 52.73%] [G loss: 0.693619]
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4765 [D loss: 0.691650, acc.: 54.30%] [G loss: 0.693314]
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4766 [D loss: 0.693602, acc.: 49.02%] [G loss: 0.694506]
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4767 [D loss: 0.693654, acc.: 48.24%] [G loss: 0.692563]
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4768 [D loss: 0.693493, acc.: 49.22%] [G loss: 0.692228]
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4769 [D loss: 0.693305, acc.: 48.05%] [G loss: 0.691758]
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4770 [D loss: 0.694147, acc.: 48.24%] [G loss: 0.693729]
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4771 [D loss: 0.692020, acc.: 55.08%] [G loss: 0.692649]
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4772 [D loss: 0.692513, acc.: 49.80%] [G loss: 0.691904]
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4773 [D loss: 0.692898, acc.: 50.98%] [G loss: 0.692045]
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4774 [D loss: 0.694409, acc.: 46.48%] [G loss: 0.692783]
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4775 [D loss: 0.694557, acc.: 48.44%] [G loss: 0.692264]
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4776 [D loss: 0.693235, acc.: 48.44%] [G loss: 0.691770]
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4777 [D loss: 0.693550, acc.: 50.20%] [G loss: 0.692947]
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4778 [D loss: 0.692946, acc.: 52.34%] [G loss: 0.690486]
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4779 [D loss: 0.693649, acc.: 46.88%] [G loss: 0.691162]
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4780 [D loss: 0.693916, acc.: 47.85%] [G loss: 0.692403]
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4781 [D loss: 0.691996, acc.: 53.91%] [G loss: 0.691634]
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4782 [D loss: 0.691841, acc.: 51.76%] [G loss: 0.693466]
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4783 [D loss: 0.692709, acc.: 50.98%] [G loss: 0.694308]
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4784 [D loss: 0.693531, acc.: 48.05%] [G loss: 0.692864]
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4785 [D loss: 0.692890, acc.: 49.22%] [G loss: 0.694897]
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4786 [D loss: 0.691678, acc.: 54.88%] [G loss: 0.693524]
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4787 [D loss: 0.693584, acc.: 45.51%] [G loss: 0.694568]
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4788 [D loss: 0.692540, acc.: 54.30%] [G loss: 0.694590]
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4789 [D loss: 0.693309, acc.: 47.27%] [G loss: 0.693599]
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4790 [D loss: 0.694039, acc.: 47.27%] [G loss: 0.693969]
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4791 [D loss: 0.693023, acc.: 51.17%] [G loss: 0.695189]
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4792 [D loss: 0.694204, acc.: 48.24%] [G loss: 0.694042]
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4793 [D loss: 0.693484, acc.: 50.98%] [G loss: 0.695593]
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4794 [D loss: 0.693955, acc.: 47.07%] [G loss: 0.696658]
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4795 [D loss: 0.693600, acc.: 50.59%] [G loss: 0.694800]
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4796 [D loss: 0.692540, acc.: 51.76%] [G loss: 0.696155]
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4797 [D loss: 0.692719, acc.: 51.76%] [G loss: 0.694527]
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4798 [D loss: 0.692008, acc.: 52.54%] [G loss: 0.694880]
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4799 [D loss: 0.692663, acc.: 50.20%] [G loss: 0.694530]
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4800 [D loss: 0.692510, acc.: 50.98%] [G loss: 0.696591]
1/1 [==============================] - 0s 16ms/step
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4801 [D loss: 0.693114, acc.: 50.78%] [G loss: 0.695597]
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4802 [D loss: 0.694233, acc.: 45.51%] [G loss: 0.695459]
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4803 [D loss: 0.692319, acc.: 53.12%] [G loss: 0.695306]
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4804 [D loss: 0.693140, acc.: 48.24%] [G loss: 0.695222]
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4805 [D loss: 0.692794, acc.: 49.41%] [G loss: 0.695612]
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4806 [D loss: 0.692555, acc.: 50.98%] [G loss: 0.694315]
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4807 [D loss: 0.693108, acc.: 52.93%] [G loss: 0.695541]
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4808 [D loss: 0.692827, acc.: 50.00%] [G loss: 0.694730]
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4809 [D loss: 0.692801, acc.: 53.91%] [G loss: 0.694880]
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4810 [D loss: 0.694089, acc.: 47.07%] [G loss: 0.693621]
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4811 [D loss: 0.693910, acc.: 48.63%] [G loss: 0.694586]
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4812 [D loss: 0.693340, acc.: 50.00%] [G loss: 0.692693]
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4813 [D loss: 0.692314, acc.: 51.56%] [G loss: 0.693352]
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4814 [D loss: 0.692427, acc.: 50.78%] [G loss: 0.693577]
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4815 [D loss: 0.692994, acc.: 47.85%] [G loss: 0.693680]
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4816 [D loss: 0.693024, acc.: 48.44%] [G loss: 0.693245]
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4817 [D loss: 0.693803, acc.: 49.80%] [G loss: 0.692867]
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4818 [D loss: 0.692748, acc.: 49.41%] [G loss: 0.693085]
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4819 [D loss: 0.693226, acc.: 50.59%] [G loss: 0.690272]
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4820 [D loss: 0.692793, acc.: 50.98%] [G loss: 0.693650]
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4821 [D loss: 0.691031, acc.: 56.64%] [G loss: 0.694575]
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4822 [D loss: 0.692282, acc.: 51.56%] [G loss: 0.695179]
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4823 [D loss: 0.691951, acc.: 51.76%] [G loss: 0.695484]
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4824 [D loss: 0.692407, acc.: 51.76%] [G loss: 0.695982]
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4825 [D loss: 0.692075, acc.: 52.15%] [G loss: 0.696601]
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4826 [D loss: 0.692327, acc.: 52.73%] [G loss: 0.693582]
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4827 [D loss: 0.690644, acc.: 57.62%] [G loss: 0.693115]
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4828 [D loss: 0.693245, acc.: 50.20%] [G loss: 0.692835]
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4829 [D loss: 0.692221, acc.: 53.12%] [G loss: 0.692765]
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4830 [D loss: 0.693086, acc.: 50.98%] [G loss: 0.690571]
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4831 [D loss: 0.692028, acc.: 51.76%] [G loss: 0.691364]
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4832 [D loss: 0.693336, acc.: 49.61%] [G loss: 0.690835]
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4833 [D loss: 0.692459, acc.: 53.12%] [G loss: 0.693475]
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4834 [D loss: 0.694081, acc.: 48.63%] [G loss: 0.690142]
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4835 [D loss: 0.691128, acc.: 55.08%] [G loss: 0.691633]
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4836 [D loss: 0.693706, acc.: 49.61%] [G loss: 0.692905]
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4837 [D loss: 0.693307, acc.: 53.32%] [G loss: 0.691146]
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4838 [D loss: 0.691360, acc.: 55.66%] [G loss: 0.691580]
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4839 [D loss: 0.691663, acc.: 54.49%] [G loss: 0.692366]
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4840 [D loss: 0.692106, acc.: 54.49%] [G loss: 0.692727]
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4841 [D loss: 0.692444, acc.: 50.20%] [G loss: 0.694059]
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4842 [D loss: 0.692685, acc.: 53.32%] [G loss: 0.692031]
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4843 [D loss: 0.694874, acc.: 46.29%] [G loss: 0.692381]
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4844 [D loss: 0.692805, acc.: 48.83%] [G loss: 0.691978]
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4845 [D loss: 0.693516, acc.: 50.20%] [G loss: 0.691672]
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4846 [D loss: 0.693843, acc.: 44.92%] [G loss: 0.692849]
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4847 [D loss: 0.692308, acc.: 50.98%] [G loss: 0.693311]
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4848 [D loss: 0.692826, acc.: 50.98%] [G loss: 0.694264]
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4849 [D loss: 0.692912, acc.: 50.20%] [G loss: 0.693006]
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4850 [D loss: 0.692826, acc.: 51.76%] [G loss: 0.691937]
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4851 [D loss: 0.693081, acc.: 49.80%] [G loss: 0.692020]
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4852 [D loss: 0.693078, acc.: 50.00%] [G loss: 0.694224]
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4853 [D loss: 0.692096, acc.: 53.91%] [G loss: 0.693469]
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4854 [D loss: 0.693120, acc.: 51.17%] [G loss: 0.694023]
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4855 [D loss: 0.693142, acc.: 49.61%] [G loss: 0.692952]
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4856 [D loss: 0.693844, acc.: 48.83%] [G loss: 0.692995]
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4857 [D loss: 0.692434, acc.: 51.76%] [G loss: 0.695082]
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4858 [D loss: 0.693173, acc.: 50.39%] [G loss: 0.695861]
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4859 [D loss: 0.692534, acc.: 50.20%] [G loss: 0.695997]
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4860 [D loss: 0.692264, acc.: 52.54%] [G loss: 0.696280]
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4861 [D loss: 0.693488, acc.: 49.61%] [G loss: 0.695599]
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4862 [D loss: 0.694236, acc.: 45.90%] [G loss: 0.694930]
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4863 [D loss: 0.692254, acc.: 52.93%] [G loss: 0.697307]
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4864 [D loss: 0.693427, acc.: 51.37%] [G loss: 0.697919]
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4865 [D loss: 0.691396, acc.: 53.32%] [G loss: 0.698477]
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4866 [D loss: 0.692657, acc.: 52.93%] [G loss: 0.697059]
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4867 [D loss: 0.692938, acc.: 51.56%] [G loss: 0.698254]
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4868 [D loss: 0.691666, acc.: 53.91%] [G loss: 0.695214]
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4869 [D loss: 0.693108, acc.: 50.20%] [G loss: 0.695360]
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4870 [D loss: 0.693711, acc.: 46.48%] [G loss: 0.694372]
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4871 [D loss: 0.691696, acc.: 54.49%] [G loss: 0.694582]
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4872 [D loss: 0.691400, acc.: 56.25%] [G loss: 0.694825]
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4873 [D loss: 0.691642, acc.: 53.71%] [G loss: 0.693371]
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4874 [D loss: 0.692589, acc.: 51.95%] [G loss: 0.697453]
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4875 [D loss: 0.693975, acc.: 49.02%] [G loss: 0.694715]
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4876 [D loss: 0.693059, acc.: 49.61%] [G loss: 0.694816]
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4877 [D loss: 0.692316, acc.: 52.15%] [G loss: 0.693826]
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4878 [D loss: 0.693971, acc.: 47.66%] [G loss: 0.694306]
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4879 [D loss: 0.691834, acc.: 56.25%] [G loss: 0.696112]
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4880 [D loss: 0.691710, acc.: 55.66%] [G loss: 0.693985]
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4881 [D loss: 0.692461, acc.: 50.78%] [G loss: 0.694863]
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4882 [D loss: 0.692284, acc.: 54.30%] [G loss: 0.692273]
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4883 [D loss: 0.693441, acc.: 48.63%] [G loss: 0.694499]
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4884 [D loss: 0.693242, acc.: 50.59%] [G loss: 0.693759]
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4885 [D loss: 0.693211, acc.: 50.98%] [G loss: 0.692833]
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4886 [D loss: 0.692233, acc.: 52.93%] [G loss: 0.690763]
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4887 [D loss: 0.692783, acc.: 53.12%] [G loss: 0.691666]
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4888 [D loss: 0.692590, acc.: 54.69%] [G loss: 0.691362]
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4889 [D loss: 0.694437, acc.: 45.90%] [G loss: 0.692600]
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4890 [D loss: 0.693434, acc.: 49.22%] [G loss: 0.692630]
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4891 [D loss: 0.692990, acc.: 49.80%] [G loss: 0.691374]
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4892 [D loss: 0.693355, acc.: 47.85%] [G loss: 0.692499]
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4893 [D loss: 0.692853, acc.: 49.22%] [G loss: 0.691695]
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4894 [D loss: 0.694048, acc.: 48.63%] [G loss: 0.692886]
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4895 [D loss: 0.693297, acc.: 49.80%] [G loss: 0.691679]
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4896 [D loss: 0.692985, acc.: 52.54%] [G loss: 0.693042]
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4897 [D loss: 0.692683, acc.: 52.73%] [G loss: 0.694735]
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4898 [D loss: 0.692213, acc.: 55.27%] [G loss: 0.694727]
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4899 [D loss: 0.693500, acc.: 51.76%] [G loss: 0.692472]
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4900 [D loss: 0.692907, acc.: 50.78%] [G loss: 0.695968]
1/1 [==============================] - 0s 14ms/step
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4901 [D loss: 0.692283, acc.: 50.98%] [G loss: 0.694050]
8/8 [==============================] - 0s 2ms/step
4902 [D loss: 0.692216, acc.: 50.98%] [G loss: 0.695105]
8/8 [==============================] - 0s 2ms/step
4903 [D loss: 0.692036, acc.: 54.30%] [G loss: 0.692827]
8/8 [==============================] - 0s 2ms/step
4904 [D loss: 0.692890, acc.: 49.80%] [G loss: 0.693636]
8/8 [==============================] - 0s 2ms/step
4905 [D loss: 0.694171, acc.: 49.22%] [G loss: 0.693772]
8/8 [==============================] - 0s 2ms/step
4906 [D loss: 0.692673, acc.: 48.83%] [G loss: 0.691390]
8/8 [==============================] - 0s 2ms/step
4907 [D loss: 0.693800, acc.: 46.68%] [G loss: 0.692554]
8/8 [==============================] - 0s 2ms/step
4908 [D loss: 0.693044, acc.: 51.56%] [G loss: 0.691424]
8/8 [==============================] - 0s 2ms/step
4909 [D loss: 0.693932, acc.: 49.22%] [G loss: 0.691597]
8/8 [==============================] - 0s 2ms/step
4910 [D loss: 0.693020, acc.: 49.41%] [G loss: 0.692368]
8/8 [==============================] - 0s 2ms/step
4911 [D loss: 0.692764, acc.: 51.37%] [G loss: 0.694014]
8/8 [==============================] - 0s 2ms/step
4912 [D loss: 0.693741, acc.: 49.80%] [G loss: 0.692201]
8/8 [==============================] - 0s 2ms/step
4913 [D loss: 0.693698, acc.: 48.44%] [G loss: 0.693913]
8/8 [==============================] - 0s 2ms/step
4914 [D loss: 0.692658, acc.: 51.95%] [G loss: 0.695104]
8/8 [==============================] - 0s 2ms/step
4915 [D loss: 0.692544, acc.: 51.37%] [G loss: 0.695596]
8/8 [==============================] - 0s 2ms/step
4916 [D loss: 0.692668, acc.: 52.54%] [G loss: 0.695905]
8/8 [==============================] - 0s 2ms/step
4917 [D loss: 0.692034, acc.: 52.34%] [G loss: 0.694126]
8/8 [==============================] - 0s 2ms/step
4918 [D loss: 0.691878, acc.: 55.08%] [G loss: 0.694948]
8/8 [==============================] - 0s 2ms/step
4919 [D loss: 0.692650, acc.: 51.95%] [G loss: 0.696086]
8/8 [==============================] - 0s 2ms/step
4920 [D loss: 0.691535, acc.: 54.88%] [G loss: 0.695985]
8/8 [==============================] - 0s 2ms/step
4921 [D loss: 0.691888, acc.: 52.93%] [G loss: 0.697340]
8/8 [==============================] - 0s 2ms/step
4922 [D loss: 0.692063, acc.: 51.76%] [G loss: 0.696424]
8/8 [==============================] - 0s 2ms/step
4923 [D loss: 0.690865, acc.: 55.47%] [G loss: 0.696602]
8/8 [==============================] - 0s 2ms/step
4924 [D loss: 0.692461, acc.: 52.93%] [G loss: 0.697658]
8/8 [==============================] - 0s 2ms/step
4925 [D loss: 0.692474, acc.: 52.93%] [G loss: 0.696634]
8/8 [==============================] - 0s 2ms/step
4926 [D loss: 0.693021, acc.: 52.54%] [G loss: 0.694579]
8/8 [==============================] - 0s 2ms/step
4927 [D loss: 0.691550, acc.: 54.10%] [G loss: 0.695772]
8/8 [==============================] - 0s 2ms/step
4928 [D loss: 0.693305, acc.: 49.80%] [G loss: 0.694301]
8/8 [==============================] - 0s 2ms/step
4929 [D loss: 0.692848, acc.: 52.54%] [G loss: 0.696102]
8/8 [==============================] - 0s 2ms/step
4930 [D loss: 0.691553, acc.: 54.88%] [G loss: 0.699340]
8/8 [==============================] - 0s 2ms/step
4931 [D loss: 0.693542, acc.: 51.17%] [G loss: 0.697979]
8/8 [==============================] - 0s 2ms/step
4932 [D loss: 0.691916, acc.: 51.95%] [G loss: 0.696182]
8/8 [==============================] - 0s 2ms/step
4933 [D loss: 0.693118, acc.: 47.46%] [G loss: 0.695501]
8/8 [==============================] - 0s 2ms/step
4934 [D loss: 0.692395, acc.: 53.91%] [G loss: 0.695445]
8/8 [==============================] - 0s 2ms/step
4935 [D loss: 0.693418, acc.: 50.00%] [G loss: 0.692742]
8/8 [==============================] - 0s 2ms/step
4936 [D loss: 0.692923, acc.: 48.63%] [G loss: 0.692859]
8/8 [==============================] - 0s 2ms/step
4937 [D loss: 0.693419, acc.: 48.24%] [G loss: 0.691341]
8/8 [==============================] - 0s 2ms/step
4938 [D loss: 0.693224, acc.: 48.24%] [G loss: 0.693266]
8/8 [==============================] - 0s 2ms/step
4939 [D loss: 0.693010, acc.: 50.59%] [G loss: 0.691298]
8/8 [==============================] - 0s 2ms/step
4940 [D loss: 0.692459, acc.: 52.15%] [G loss: 0.692838]
8/8 [==============================] - 0s 2ms/step
4941 [D loss: 0.691961, acc.: 54.30%] [G loss: 0.693920]
8/8 [==============================] - 0s 2ms/step
4942 [D loss: 0.693372, acc.: 48.44%] [G loss: 0.692198]
8/8 [==============================] - 0s 2ms/step
4943 [D loss: 0.693737, acc.: 46.29%] [G loss: 0.692785]
8/8 [==============================] - 0s 2ms/step
4944 [D loss: 0.693251, acc.: 52.15%] [G loss: 0.692287]
8/8 [==============================] - 0s 2ms/step
4945 [D loss: 0.693678, acc.: 49.80%] [G loss: 0.694771]
8/8 [==============================] - 0s 2ms/step
4946 [D loss: 0.692816, acc.: 49.41%] [G loss: 0.693213]
8/8 [==============================] - 0s 2ms/step
4947 [D loss: 0.693289, acc.: 48.24%] [G loss: 0.692527]
8/8 [==============================] - 0s 2ms/step
4948 [D loss: 0.694185, acc.: 45.90%] [G loss: 0.691819]
8/8 [==============================] - 0s 2ms/step
4949 [D loss: 0.692564, acc.: 52.34%] [G loss: 0.692147]
8/8 [==============================] - 0s 2ms/step
4950 [D loss: 0.692438, acc.: 55.27%] [G loss: 0.691327]
8/8 [==============================] - 0s 2ms/step
4951 [D loss: 0.693438, acc.: 46.48%] [G loss: 0.693478]
8/8 [==============================] - 0s 2ms/step
4952 [D loss: 0.691683, acc.: 51.76%] [G loss: 0.693227]
8/8 [==============================] - 0s 2ms/step
4953 [D loss: 0.692393, acc.: 55.47%] [G loss: 0.692231]
8/8 [==============================] - 0s 2ms/step
4954 [D loss: 0.692840, acc.: 52.93%] [G loss: 0.692314]
8/8 [==============================] - 0s 2ms/step
4955 [D loss: 0.693851, acc.: 50.39%] [G loss: 0.692060]
8/8 [==============================] - 0s 2ms/step
4956 [D loss: 0.693475, acc.: 49.61%] [G loss: 0.693722]
8/8 [==============================] - 0s 2ms/step
4957 [D loss: 0.692656, acc.: 50.59%] [G loss: 0.693318]
8/8 [==============================] - 0s 2ms/step
4958 [D loss: 0.692961, acc.: 52.54%] [G loss: 0.691988]
8/8 [==============================] - 0s 2ms/step
4959 [D loss: 0.693235, acc.: 51.17%] [G loss: 0.695383]
8/8 [==============================] - 0s 2ms/step
4960 [D loss: 0.692972, acc.: 49.61%] [G loss: 0.691921]
8/8 [==============================] - 0s 2ms/step
4961 [D loss: 0.693044, acc.: 49.02%] [G loss: 0.693061]
8/8 [==============================] - 0s 2ms/step
4962 [D loss: 0.691789, acc.: 53.52%] [G loss: 0.692886]
8/8 [==============================] - 0s 2ms/step
4963 [D loss: 0.692129, acc.: 51.56%] [G loss: 0.694009]
8/8 [==============================] - 0s 2ms/step
4964 [D loss: 0.692213, acc.: 53.91%] [G loss: 0.691960]
8/8 [==============================] - 0s 2ms/step
4965 [D loss: 0.692651, acc.: 52.73%] [G loss: 0.693319]
8/8 [==============================] - 0s 2ms/step
4966 [D loss: 0.691843, acc.: 54.10%] [G loss: 0.694645]
8/8 [==============================] - 0s 2ms/step
4967 [D loss: 0.693638, acc.: 49.22%] [G loss: 0.694638]
8/8 [==============================] - 0s 2ms/step
4968 [D loss: 0.692603, acc.: 50.20%] [G loss: 0.691724]
8/8 [==============================] - 0s 2ms/step
4969 [D loss: 0.692915, acc.: 49.61%] [G loss: 0.691965]
8/8 [==============================] - 0s 2ms/step
4970 [D loss: 0.691977, acc.: 52.93%] [G loss: 0.693748]
8/8 [==============================] - 0s 2ms/step
4971 [D loss: 0.691472, acc.: 54.69%] [G loss: 0.691165]
8/8 [==============================] - 0s 2ms/step
4972 [D loss: 0.692441, acc.: 51.76%] [G loss: 0.693114]
8/8 [==============================] - 0s 2ms/step
4973 [D loss: 0.693071, acc.: 50.98%] [G loss: 0.693620]
8/8 [==============================] - 0s 2ms/step
4974 [D loss: 0.692581, acc.: 53.12%] [G loss: 0.694652]
8/8 [==============================] - 0s 2ms/step
4975 [D loss: 0.692252, acc.: 51.17%] [G loss: 0.694281]
8/8 [==============================] - 0s 2ms/step
4976 [D loss: 0.692304, acc.: 52.73%] [G loss: 0.694747]
8/8 [==============================] - 0s 2ms/step
4977 [D loss: 0.693242, acc.: 49.61%] [G loss: 0.694036]
8/8 [==============================] - 0s 2ms/step
4978 [D loss: 0.691857, acc.: 54.69%] [G loss: 0.695657]
8/8 [==============================] - 0s 2ms/step
4979 [D loss: 0.692912, acc.: 53.52%] [G loss: 0.694804]
8/8 [==============================] - 0s 2ms/step
4980 [D loss: 0.692230, acc.: 54.10%] [G loss: 0.695294]
8/8 [==============================] - 0s 2ms/step
4981 [D loss: 0.692775, acc.: 53.12%] [G loss: 0.695089]
8/8 [==============================] - 0s 2ms/step
4982 [D loss: 0.692607, acc.: 51.17%] [G loss: 0.694869]
8/8 [==============================] - 0s 2ms/step
4983 [D loss: 0.692598, acc.: 49.02%] [G loss: 0.696720]
8/8 [==============================] - 0s 2ms/step
4984 [D loss: 0.692154, acc.: 52.54%] [G loss: 0.694111]
8/8 [==============================] - 0s 2ms/step
4985 [D loss: 0.693036, acc.: 51.17%] [G loss: 0.693536]
8/8 [==============================] - 0s 2ms/step
4986 [D loss: 0.692567, acc.: 52.54%] [G loss: 0.694946]
8/8 [==============================] - 0s 2ms/step
4987 [D loss: 0.693085, acc.: 50.00%] [G loss: 0.694634]
8/8 [==============================] - 0s 2ms/step
4988 [D loss: 0.694003, acc.: 49.80%] [G loss: 0.695161]
8/8 [==============================] - 0s 2ms/step
4989 [D loss: 0.692716, acc.: 51.56%] [G loss: 0.694884]
8/8 [==============================] - 0s 2ms/step
4990 [D loss: 0.692757, acc.: 52.15%] [G loss: 0.696004]
8/8 [==============================] - 0s 2ms/step
4991 [D loss: 0.692693, acc.: 52.54%] [G loss: 0.693269]
8/8 [==============================] - 0s 2ms/step
4992 [D loss: 0.691593, acc.: 53.91%] [G loss: 0.696556]
8/8 [==============================] - 0s 2ms/step
4993 [D loss: 0.692608, acc.: 52.15%] [G loss: 0.694388]
8/8 [==============================] - 0s 2ms/step
4994 [D loss: 0.692399, acc.: 50.78%] [G loss: 0.693589]
8/8 [==============================] - 0s 2ms/step
4995 [D loss: 0.691880, acc.: 55.66%] [G loss: 0.694131]
8/8 [==============================] - 0s 2ms/step
4996 [D loss: 0.691438, acc.: 54.49%] [G loss: 0.695788]
8/8 [==============================] - 0s 2ms/step
4997 [D loss: 0.693490, acc.: 51.17%] [G loss: 0.694323]
8/8 [==============================] - 0s 2ms/step
4998 [D loss: 0.692937, acc.: 49.02%] [G loss: 0.693610]
8/8 [==============================] - 0s 2ms/step
4999 [D loss: 0.693254, acc.: 48.05%] [G loss: 0.692063]

Loss Curve

plot_losses(dcgan.d_losses, dcgan.g_losses)

Accuracy Curve

plot_accuracy(dcgan.d_accuracy)

Generated Images at Different Epochs (Base Model)

At 100 Epochs

At 1000 Epochs

At 2950 Epochs

Results

Initially, the generator loss is quite high, around 0.9, while the discriminator loss is relatively low, around 0.5. As training progresses, the generator loss decreases, and the discriminator loss increases, eventually converging with both losses around 0.7. This trend suggests that the generator is improving in generating more realistic samples over time, while the discriminator is finding it increasingly challenging to distinguish between real and generated data. When both losses stabilize around a similar value, it often indicates that the GAN has reached a balance, with the generator producing sufficiently realistic data that the discriminator cannot easily differentiate from real data.

The discriminator's accuracy starts very high, around 99%, and gradually decreases, fluctuating between 55% and 60%. This pattern suggests that initially, the discriminator can easily distinguish between real and generated data, as the generator's outputs are not yet realistic. However, as the generator improves, it becomes harder for the discriminator to differentiate, leading to a decrease in accuracy. The fluctuation around 55% to 60% indicates that the discriminator is no longer confidently distinguishing between real and fake samples, suggesting that the generator is producing more convincing outputs.

From the generated images, we can see that certain classes like T, U, X, D, and N are more recognizable. However, most classes are still not very clear, indicating that the generator hasn't yet fully captured the distinctions needed to accurately reproduce all the different classes|

Improving the Discriminator

What is the impact of the discriminator in GANs

The discriminator evaluates whether an image is real (from the training dataset) or fake (generated by the generator). This assessment helps ensure that the generator produces more realistic outputs over time.

The discriminator's performance directly influences the training dynamics of the GAN. A strong discriminator can effectively guide the generator to improve, while a weak discriminator may lead to mode collapse, where the generator produces limited variations of images.

A well-balanced discriminator can help stabilize the training process. If the discriminator is too strong compared to the generator, it may lead to vanishing gradients, making it difficult for the generator to learn. Conversely, if the generator outperforms the discriminator, the latter may not provide useful feedback.

What changed from the previous model

• 1 additional conv2D layer for the discriminator
• 1 additional dense layer after the flatten layer for the discriminator

Why did we choose to improve the discriminator

From the baseline model, it is evident that the GAN is not generating images effectively. While some letters are partially represented, many others are not recognizable at all. To address this issue, we decided to enhance the discriminator. By strengthening the discriminator's ability to differentiate between real and generated images, we aim to provide more precise feedback to the generator. This improved feedback will help the generator refine its outputs and create more realistic and diverse representations of handwritten letters. Ultimately, our goal is to achieve higher-quality image generation, ensuring that each letter is accurately represented in the final dataset.

References

https://www.larksuite.com/en_us/topics/ai-glossary/discriminator-in-gan#pros-&-cons-of-discriminator-(in-gan)

class DCGAN():
    
    # this is the function to build the generator neural network
    def build_generator(self):
        model = Sequential()

        model.add(Dense(128 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 128)))
        
        model.add(UpSampling2D())
        model.add(Conv2D(128, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(UpSampling2D())
        model.add(Conv2D(64, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(self.channels, kernel_size=3, padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)
    
    
    def build_discriminator(self):
        model = Sequential(name='Discriminator')
        model.add(Conv2D(128, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Flatten())
        
        # Add one more dense layer
        model.add(Dense(256))  # Adjust the units as per your architecture needs
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        img = Input(shape=self.img_shape)
        validity = model(img)
        return Model(img, validity)
        
    def __init__(self, rows, cols, channels, z = 100):
        # Input shape
        self.img_rows = rows  # generated image height
        self.img_cols = cols  # generated image width
        self.channels = channels  # generated image channel
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = z  # the input is 1-D vector of noise
        # Reduce learning rate from 0.001 to 0.0002, and beta1 from 0.9 to 0.5, which can stablize training and reduce oscillation
        optimizer = Adam(learning_rate=0.0002, beta_1=0.5)
        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss='binary_crossentropy',
            optimizer=optimizer,
            metrics=['accuracy'])
        # Build the generator
        self.generator = self.build_generator()
        # The generator takes noise as input and generates images
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)
        # For the combined model we will only train the generator
        self.discriminator.trainable = False
        # The discriminator takes generated images as input and determines validity
        valid = self.discriminator(img)
        # The combined model (stacked generator and discriminator)
        # Trains the generator to fool the discriminator
        self.combined = Model(z, valid)
        self.combined.compile(loss='binary_crossentropy',
            optimizer=optimizer)
        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []
        
    def train(self, epochs, batch_size=128, save_interval=50):
        # Assuming your data is in a pandas DataFrame `df`
        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values  # assuming first column is labels, rest are pixels
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)  # reshape to image shape
        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))
        
        for epoch in range(epochs):
            # ---------------------
            # Train Discriminator
            # ---------------------
            # Select a random half of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs = X_train[idx]
            
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            gen_imgs = self.generator.predict(noise)
            
            # Train the discriminator (classify real images as 1 and generated images as 0)
            d_loss_real = self.discriminator.train_on_batch(imgs, valid)
            d_loss_fake = self.discriminator.train_on_batch(gen_imgs, fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)
            
            # ---------------------
            # Train Generator
            # ---------------------
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            
            # Train the generator (generator wants discriminator to predict generated images as 1)
            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            # Print progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100 * d_loss[1], g_loss))
            
            # If at save interval => save generated image samples
            if epoch % save_interval == 0:
                self.save_imgs(epoch)


    def save_imgs(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        # gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/dcgan', exist_ok=True)
        os.makedirs('generated_images/dcgan/improveD', exist_ok=True)
        fig.savefig("generated_images/dcgan/improveD/dcgan_{:d}.png".format(epoch))
        plt.close()

dcgan = DCGAN(28,28,1)
dcgan.train(epochs=3000, batch_size=256, save_interval=50)

Model: "Discriminator"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_5 (Conv2D)           (None, 14, 14, 128)       1280      
                                                                 
 leaky_re_lu_4 (LeakyReLU)   (None, 14, 14, 128)       0         
                                                                 
 dropout_2 (Dropout)         (None, 14, 14, 128)       0         
                                                                 
 conv2d_6 (Conv2D)           (None, 7, 7, 128)         147584    
                                                                 
 leaky_re_lu_5 (LeakyReLU)   (None, 7, 7, 128)         0         
                                                                 
 dropout_3 (Dropout)         (None, 7, 7, 128)         0         
                                                                 
 conv2d_7 (Conv2D)           (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_6 (LeakyReLU)   (None, 4, 4, 256)         0         
                                                                 
 dropout_4 (Dropout)         (None, 4, 4, 256)         0         
                                                                 
 flatten_1 (Flatten)         (None, 4096)              0         
                                                                 
 dense_2 (Dense)             (None, 256)               1048832   
                                                                 
 leaky_re_lu_7 (LeakyReLU)   (None, 256)               0         
                                                                 
 dense_3 (Dense)             (None, 1)                 257       
                                                                 
=================================================================
Total params: 1,493,121
Trainable params: 1,493,121
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_1"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_4 (Dense)             (None, 6272)              633472    
                                                                 
 reshape_1 (Reshape)         (None, 7, 7, 128)         0         
                                                                 
 up_sampling2d_2 (UpSampling  (None, 14, 14, 128)      0         
 2D)                                                             
                                                                 
 conv2d_8 (Conv2D)           (None, 14, 14, 128)       147584    
                                                                 
 batch_normalization_2 (Batc  (None, 14, 14, 128)      512       
 hNormalization)                                                 
                                                                 
 leaky_re_lu_8 (LeakyReLU)   (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_3 (UpSampling  (None, 28, 28, 128)      0         
 2D)                                                             
                                                                 
 conv2d_9 (Conv2D)           (None, 28, 28, 64)        73792     
                                                                 
 batch_normalization_3 (Batc  (None, 28, 28, 64)       256       
 hNormalization)                                                 
                                                                 
 leaky_re_lu_9 (LeakyReLU)   (None, 28, 28, 64)        0         
                                                                 
 conv2d_10 (Conv2D)          (None, 28, 28, 1)         577       
                                                                 
 activation_1 (Activation)   (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 856,193
Trainable params: 855,809
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 0s 2ms/step
0 [D loss: 0.731599, acc.: 13.67%] [G loss: 0.674530]
1/1 [==============================] - 0s 66ms/step
8/8 [==============================] - 0s 3ms/step
1 [D loss: 0.688167, acc.: 55.66%] [G loss: 0.719601]
8/8 [==============================] - 0s 3ms/step
2 [D loss: 0.666227, acc.: 96.48%] [G loss: 0.767053]
8/8 [==============================] - 0s 2ms/step
3 [D loss: 0.640061, acc.: 95.70%] [G loss: 0.828732]
8/8 [==============================] - 0s 2ms/step
4 [D loss: 0.603428, acc.: 94.14%] [G loss: 0.914429]
8/8 [==============================] - 0s 2ms/step
5 [D loss: 0.553608, acc.: 88.28%] [G loss: 1.016197]
8/8 [==============================] - 0s 2ms/step
6 [D loss: 0.489662, acc.: 91.60%] [G loss: 1.088499]
8/8 [==============================] - 0s 2ms/step
7 [D loss: 0.424622, acc.: 93.75%] [G loss: 0.993620]
8/8 [==============================] - 0s 2ms/step
8 [D loss: 0.336502, acc.: 97.27%] [G loss: 0.804489]
8/8 [==============================] - 0s 2ms/step
9 [D loss: 0.267405, acc.: 97.85%] [G loss: 0.603137]
8/8 [==============================] - 0s 2ms/step
10 [D loss: 0.187114, acc.: 99.41%] [G loss: 0.467717]
8/8 [==============================] - 0s 2ms/step
11 [D loss: 0.145992, acc.: 99.41%] [G loss: 0.530257]
8/8 [==============================] - 0s 2ms/step
12 [D loss: 0.164585, acc.: 99.41%] [G loss: 1.560835]
8/8 [==============================] - 0s 2ms/step
13 [D loss: 0.269005, acc.: 96.29%] [G loss: 2.711166]
8/8 [==============================] - 0s 2ms/step
14 [D loss: 0.297754, acc.: 91.60%] [G loss: 2.015169]
8/8 [==============================] - 0s 2ms/step
15 [D loss: 0.174598, acc.: 95.70%] [G loss: 1.143695]
8/8 [==============================] - 0s 2ms/step
16 [D loss: 0.123576, acc.: 98.24%] [G loss: 1.699286]
8/8 [==============================] - 0s 2ms/step
17 [D loss: 0.129987, acc.: 98.05%] [G loss: 2.267991]
8/8 [==============================] - 0s 2ms/step
18 [D loss: 0.293510, acc.: 88.87%] [G loss: 3.078462]
8/8 [==============================] - 0s 2ms/step
19 [D loss: 0.338116, acc.: 88.28%] [G loss: 2.362592]
8/8 [==============================] - 0s 2ms/step
20 [D loss: 0.315013, acc.: 88.09%] [G loss: 1.431502]
8/8 [==============================] - 0s 2ms/step
21 [D loss: 0.145964, acc.: 95.90%] [G loss: 0.941892]
8/8 [==============================] - 0s 2ms/step
22 [D loss: 0.176507, acc.: 96.09%] [G loss: 1.603384]
8/8 [==============================] - 0s 2ms/step
23 [D loss: 0.466317, acc.: 75.59%] [G loss: 3.385806]
8/8 [==============================] - 0s 2ms/step
24 [D loss: 1.214494, acc.: 40.04%] [G loss: 2.178443]
8/8 [==============================] - 0s 2ms/step
25 [D loss: 0.530393, acc.: 73.44%] [G loss: 1.751721]
8/8 [==============================] - 0s 2ms/step
26 [D loss: 0.631545, acc.: 63.67%] [G loss: 1.367377]
8/8 [==============================] - 0s 2ms/step
27 [D loss: 0.856958, acc.: 47.46%] [G loss: 1.287438]
8/8 [==============================] - 0s 2ms/step
28 [D loss: 1.071491, acc.: 35.35%] [G loss: 0.820653]
8/8 [==============================] - 0s 2ms/step
29 [D loss: 1.020890, acc.: 37.30%] [G loss: 0.479978]
8/8 [==============================] - 0s 2ms/step
30 [D loss: 0.884056, acc.: 44.14%] [G loss: 0.443121]
8/8 [==============================] - 0s 2ms/step
31 [D loss: 0.814590, acc.: 46.68%] [G loss: 0.522257]
8/8 [==============================] - 0s 2ms/step
32 [D loss: 0.767765, acc.: 44.14%] [G loss: 0.672310]
8/8 [==============================] - 0s 2ms/step
33 [D loss: 0.683661, acc.: 45.70%] [G loss: 0.859281]
8/8 [==============================] - 0s 2ms/step
34 [D loss: 0.594118, acc.: 69.14%] [G loss: 1.037538]
8/8 [==============================] - 0s 2ms/step
35 [D loss: 0.576063, acc.: 74.80%] [G loss: 1.114644]
8/8 [==============================] - 0s 2ms/step
36 [D loss: 0.521373, acc.: 80.27%] [G loss: 1.190004]
8/8 [==============================] - 0s 2ms/step
37 [D loss: 0.492703, acc.: 82.81%] [G loss: 1.216453]
8/8 [==============================] - 0s 2ms/step
38 [D loss: 0.520534, acc.: 76.56%] [G loss: 1.163862]
8/8 [==============================] - 0s 2ms/step
39 [D loss: 0.487478, acc.: 81.84%] [G loss: 1.061890]
8/8 [==============================] - 0s 2ms/step
40 [D loss: 0.423557, acc.: 87.50%] [G loss: 1.019753]
8/8 [==============================] - 0s 2ms/step
41 [D loss: 0.399260, acc.: 87.70%] [G loss: 0.855824]
8/8 [==============================] - 0s 2ms/step
42 [D loss: 0.360020, acc.: 88.67%] [G loss: 0.699757]
8/8 [==============================] - 0s 2ms/step
43 [D loss: 0.349271, acc.: 89.84%] [G loss: 0.486450]
8/8 [==============================] - 0s 2ms/step
44 [D loss: 0.340917, acc.: 92.97%] [G loss: 0.371254]
8/8 [==============================] - 0s 2ms/step
45 [D loss: 0.299794, acc.: 93.55%] [G loss: 0.368457]
8/8 [==============================] - 0s 2ms/step
46 [D loss: 0.322124, acc.: 92.97%] [G loss: 0.359490]
8/8 [==============================] - 0s 2ms/step
47 [D loss: 0.306047, acc.: 93.55%] [G loss: 0.387532]
8/8 [==============================] - 0s 2ms/step
48 [D loss: 0.451030, acc.: 84.77%] [G loss: 0.370557]
8/8 [==============================] - 0s 2ms/step
49 [D loss: 0.382263, acc.: 88.28%] [G loss: 0.464966]
8/8 [==============================] - 0s 2ms/step
50 [D loss: 0.444717, acc.: 84.77%] [G loss: 0.498820]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
51 [D loss: 0.446488, acc.: 84.38%] [G loss: 0.538101]
8/8 [==============================] - 0s 2ms/step
52 [D loss: 0.516616, acc.: 81.84%] [G loss: 0.565926]
8/8 [==============================] - 0s 2ms/step
53 [D loss: 0.521641, acc.: 79.49%] [G loss: 0.615454]
8/8 [==============================] - 0s 2ms/step
54 [D loss: 0.506084, acc.: 81.64%] [G loss: 0.723173]
8/8 [==============================] - 0s 2ms/step
55 [D loss: 0.543536, acc.: 75.98%] [G loss: 0.906829]
8/8 [==============================] - 0s 2ms/step
56 [D loss: 0.598278, acc.: 72.07%] [G loss: 1.025122]
8/8 [==============================] - 0s 2ms/step
57 [D loss: 0.667752, acc.: 58.79%] [G loss: 1.074676]
8/8 [==============================] - 0s 2ms/step
58 [D loss: 0.610185, acc.: 66.99%] [G loss: 1.094714]
8/8 [==============================] - 0s 2ms/step
59 [D loss: 0.593489, acc.: 69.34%] [G loss: 1.049462]
8/8 [==============================] - 0s 2ms/step
60 [D loss: 0.576292, acc.: 69.73%] [G loss: 1.044429]
8/8 [==============================] - 0s 2ms/step
61 [D loss: 0.555381, acc.: 74.22%] [G loss: 1.044538]
8/8 [==============================] - 0s 2ms/step
62 [D loss: 0.538708, acc.: 76.76%] [G loss: 1.035636]
8/8 [==============================] - 0s 2ms/step
63 [D loss: 0.580378, acc.: 69.73%] [G loss: 1.024680]
8/8 [==============================] - 0s 2ms/step
64 [D loss: 0.659221, acc.: 57.03%] [G loss: 0.996172]
8/8 [==============================] - 0s 2ms/step
65 [D loss: 0.679727, acc.: 56.05%] [G loss: 0.935755]
8/8 [==============================] - 0s 2ms/step
66 [D loss: 0.721579, acc.: 51.37%] [G loss: 0.899123]
8/8 [==============================] - 0s 2ms/step
67 [D loss: 0.755190, acc.: 45.31%] [G loss: 0.901566]
8/8 [==============================] - 0s 2ms/step
68 [D loss: 0.777733, acc.: 45.31%] [G loss: 0.869828]
8/8 [==============================] - 0s 2ms/step
69 [D loss: 0.799220, acc.: 40.23%] [G loss: 0.867344]
8/8 [==============================] - 0s 2ms/step
70 [D loss: 0.791442, acc.: 42.77%] [G loss: 0.844779]
8/8 [==============================] - 0s 2ms/step
71 [D loss: 0.751592, acc.: 45.31%] [G loss: 0.829201]
8/8 [==============================] - 0s 2ms/step
72 [D loss: 0.737960, acc.: 44.53%] [G loss: 0.812879]
8/8 [==============================] - 0s 2ms/step
73 [D loss: 0.751342, acc.: 42.38%] [G loss: 0.819764]
8/8 [==============================] - 0s 2ms/step
74 [D loss: 0.677664, acc.: 50.98%] [G loss: 0.817897]
8/8 [==============================] - 0s 2ms/step
75 [D loss: 0.685930, acc.: 51.37%] [G loss: 0.858997]
8/8 [==============================] - 0s 2ms/step
76 [D loss: 0.689818, acc.: 50.78%] [G loss: 0.872872]
8/8 [==============================] - 0s 2ms/step
77 [D loss: 0.661680, acc.: 53.12%] [G loss: 0.847558]
8/8 [==============================] - 0s 2ms/step
78 [D loss: 0.670170, acc.: 50.78%] [G loss: 0.883474]
8/8 [==============================] - 0s 2ms/step
79 [D loss: 0.654876, acc.: 57.62%] [G loss: 0.882231]
8/8 [==============================] - 0s 2ms/step
80 [D loss: 0.671495, acc.: 57.42%] [G loss: 0.872925]
8/8 [==============================] - 0s 2ms/step
81 [D loss: 0.693567, acc.: 50.59%] [G loss: 0.859107]
8/8 [==============================] - 0s 2ms/step
82 [D loss: 0.664249, acc.: 57.62%] [G loss: 0.850952]
8/8 [==============================] - 0s 2ms/step
83 [D loss: 0.656201, acc.: 58.40%] [G loss: 0.825961]
8/8 [==============================] - 0s 2ms/step
84 [D loss: 0.699870, acc.: 50.00%] [G loss: 0.831962]
8/8 [==============================] - 0s 2ms/step
85 [D loss: 0.679632, acc.: 54.69%] [G loss: 0.826875]
8/8 [==============================] - 0s 2ms/step
86 [D loss: 0.701347, acc.: 51.56%] [G loss: 0.797580]
8/8 [==============================] - 0s 2ms/step
87 [D loss: 0.702314, acc.: 51.95%] [G loss: 0.817647]
8/8 [==============================] - 0s 2ms/step
88 [D loss: 0.716583, acc.: 51.17%] [G loss: 0.815498]
8/8 [==============================] - 0s 2ms/step
89 [D loss: 0.717318, acc.: 51.37%] [G loss: 0.804459]
8/8 [==============================] - 0s 2ms/step
90 [D loss: 0.704582, acc.: 52.54%] [G loss: 0.815714]
8/8 [==============================] - 0s 2ms/step
91 [D loss: 0.696874, acc.: 54.30%] [G loss: 0.833216]
8/8 [==============================] - 0s 2ms/step
92 [D loss: 0.689178, acc.: 56.84%] [G loss: 0.840864]
8/8 [==============================] - 0s 2ms/step
93 [D loss: 0.698009, acc.: 57.03%] [G loss: 0.842884]
8/8 [==============================] - 0s 2ms/step
94 [D loss: 0.688290, acc.: 57.62%] [G loss: 0.849350]
8/8 [==============================] - 0s 2ms/step
95 [D loss: 0.691488, acc.: 56.64%] [G loss: 0.849632]
8/8 [==============================] - 0s 2ms/step
96 [D loss: 0.670445, acc.: 61.52%] [G loss: 0.854067]
8/8 [==============================] - 0s 2ms/step
97 [D loss: 0.677723, acc.: 59.77%] [G loss: 0.836411]
8/8 [==============================] - 0s 2ms/step
98 [D loss: 0.677367, acc.: 59.77%] [G loss: 0.826048]
8/8 [==============================] - 0s 2ms/step
99 [D loss: 0.668485, acc.: 62.70%] [G loss: 0.826581]
8/8 [==============================] - 0s 2ms/step
100 [D loss: 0.680857, acc.: 57.03%] [G loss: 0.844359]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
101 [D loss: 0.667910, acc.: 60.74%] [G loss: 0.831498]
8/8 [==============================] - 0s 2ms/step
102 [D loss: 0.674285, acc.: 59.18%] [G loss: 0.827286]
8/8 [==============================] - 0s 2ms/step
103 [D loss: 0.666347, acc.: 62.30%] [G loss: 0.803821]
8/8 [==============================] - 0s 2ms/step
104 [D loss: 0.678697, acc.: 57.03%] [G loss: 0.799116]
8/8 [==============================] - 0s 2ms/step
105 [D loss: 0.659919, acc.: 60.74%] [G loss: 0.785816]
8/8 [==============================] - 0s 2ms/step
106 [D loss: 0.663990, acc.: 61.52%] [G loss: 0.788006]
8/8 [==============================] - 0s 2ms/step
107 [D loss: 0.668891, acc.: 58.98%] [G loss: 0.775495]
8/8 [==============================] - 0s 2ms/step
108 [D loss: 0.666633, acc.: 59.96%] [G loss: 0.767899]
8/8 [==============================] - 0s 2ms/step
109 [D loss: 0.677958, acc.: 57.03%] [G loss: 0.781011]
8/8 [==============================] - 0s 2ms/step
110 [D loss: 0.655004, acc.: 63.28%] [G loss: 0.791721]
8/8 [==============================] - 0s 2ms/step
111 [D loss: 0.657265, acc.: 64.26%] [G loss: 0.775716]
8/8 [==============================] - 0s 2ms/step
112 [D loss: 0.659495, acc.: 60.35%] [G loss: 0.770859]
8/8 [==============================] - 0s 2ms/step
113 [D loss: 0.635100, acc.: 70.12%] [G loss: 0.787368]
8/8 [==============================] - 0s 2ms/step
114 [D loss: 0.638660, acc.: 66.21%] [G loss: 0.785820]
8/8 [==============================] - 0s 2ms/step
115 [D loss: 0.635389, acc.: 68.75%] [G loss: 0.792266]
8/8 [==============================] - 0s 2ms/step
116 [D loss: 0.632977, acc.: 67.97%] [G loss: 0.823124]
8/8 [==============================] - 0s 2ms/step
117 [D loss: 0.630971, acc.: 69.92%] [G loss: 0.812780]
8/8 [==============================] - 0s 2ms/step
118 [D loss: 0.618432, acc.: 73.05%] [G loss: 0.831121]
8/8 [==============================] - 0s 2ms/step
119 [D loss: 0.626940, acc.: 67.97%] [G loss: 0.838864]
8/8 [==============================] - 0s 2ms/step
120 [D loss: 0.608561, acc.: 72.07%] [G loss: 0.856126]
8/8 [==============================] - 0s 2ms/step
121 [D loss: 0.640498, acc.: 64.45%] [G loss: 0.828193]
8/8 [==============================] - 0s 2ms/step
122 [D loss: 0.640398, acc.: 64.26%] [G loss: 0.818815]
8/8 [==============================] - 0s 2ms/step
123 [D loss: 0.631553, acc.: 65.04%] [G loss: 0.833823]
8/8 [==============================] - 0s 2ms/step
124 [D loss: 0.664820, acc.: 58.79%] [G loss: 0.841973]
8/8 [==============================] - 0s 2ms/step
125 [D loss: 0.678485, acc.: 60.74%] [G loss: 0.804392]
8/8 [==============================] - 0s 2ms/step
126 [D loss: 0.691405, acc.: 56.05%] [G loss: 0.794286]
8/8 [==============================] - 0s 2ms/step
127 [D loss: 0.709273, acc.: 52.93%] [G loss: 0.743801]
8/8 [==============================] - 0s 2ms/step
128 [D loss: 0.721417, acc.: 50.39%] [G loss: 0.752365]
8/8 [==============================] - 0s 2ms/step
129 [D loss: 0.725991, acc.: 52.93%] [G loss: 0.738155]
8/8 [==============================] - 0s 2ms/step
130 [D loss: 0.748711, acc.: 46.68%] [G loss: 0.753593]
8/8 [==============================] - 0s 2ms/step
131 [D loss: 0.739985, acc.: 45.12%] [G loss: 0.752281]
8/8 [==============================] - 0s 2ms/step
132 [D loss: 0.767975, acc.: 40.23%] [G loss: 0.741247]
8/8 [==============================] - 0s 2ms/step
133 [D loss: 0.740197, acc.: 42.97%] [G loss: 0.758490]
8/8 [==============================] - 0s 2ms/step
134 [D loss: 0.742087, acc.: 39.06%] [G loss: 0.753675]
8/8 [==============================] - 0s 2ms/step
135 [D loss: 0.739794, acc.: 41.02%] [G loss: 0.759752]
8/8 [==============================] - 0s 2ms/step
136 [D loss: 0.743025, acc.: 37.30%] [G loss: 0.775503]
8/8 [==============================] - 0s 2ms/step
137 [D loss: 0.730348, acc.: 42.19%] [G loss: 0.772824]
8/8 [==============================] - 0s 2ms/step
138 [D loss: 0.725614, acc.: 42.19%] [G loss: 0.782074]
8/8 [==============================] - 0s 2ms/step
139 [D loss: 0.717099, acc.: 46.29%] [G loss: 0.772827]
8/8 [==============================] - 0s 2ms/step
140 [D loss: 0.721369, acc.: 44.73%] [G loss: 0.790220]
8/8 [==============================] - 0s 2ms/step
141 [D loss: 0.697010, acc.: 51.76%] [G loss: 0.796235]
8/8 [==============================] - 0s 2ms/step
142 [D loss: 0.698467, acc.: 49.80%] [G loss: 0.799625]
8/8 [==============================] - 0s 2ms/step
143 [D loss: 0.697263, acc.: 50.39%] [G loss: 0.801352]
8/8 [==============================] - 0s 2ms/step
144 [D loss: 0.675050, acc.: 57.03%] [G loss: 0.795453]
8/8 [==============================] - 0s 2ms/step
145 [D loss: 0.687627, acc.: 53.71%] [G loss: 0.803217]
8/8 [==============================] - 0s 2ms/step
146 [D loss: 0.686873, acc.: 56.25%] [G loss: 0.828072]
8/8 [==============================] - 0s 2ms/step
147 [D loss: 0.690462, acc.: 53.12%] [G loss: 0.833079]
8/8 [==============================] - 0s 2ms/step
148 [D loss: 0.691103, acc.: 52.73%] [G loss: 0.846718]
8/8 [==============================] - 0s 2ms/step
149 [D loss: 0.696390, acc.: 49.02%] [G loss: 0.829256]
8/8 [==============================] - 0s 2ms/step
150 [D loss: 0.704156, acc.: 50.39%] [G loss: 0.839005]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
151 [D loss: 0.714430, acc.: 48.05%] [G loss: 0.844790]
8/8 [==============================] - 0s 2ms/step
152 [D loss: 0.710022, acc.: 48.63%] [G loss: 0.837899]
8/8 [==============================] - 0s 2ms/step
153 [D loss: 0.710984, acc.: 48.44%] [G loss: 0.827543]
8/8 [==============================] - 0s 2ms/step
154 [D loss: 0.716593, acc.: 47.46%] [G loss: 0.807759]
8/8 [==============================] - 0s 2ms/step
155 [D loss: 0.700194, acc.: 49.61%] [G loss: 0.803003]
8/8 [==============================] - 0s 2ms/step
156 [D loss: 0.707068, acc.: 48.24%] [G loss: 0.795758]
8/8 [==============================] - 0s 2ms/step
157 [D loss: 0.703955, acc.: 50.39%] [G loss: 0.784244]
8/8 [==============================] - 0s 2ms/step
158 [D loss: 0.697617, acc.: 49.80%] [G loss: 0.781611]
8/8 [==============================] - 0s 2ms/step
159 [D loss: 0.699226, acc.: 49.41%] [G loss: 0.771456]
8/8 [==============================] - 0s 2ms/step
160 [D loss: 0.703888, acc.: 50.20%] [G loss: 0.775089]
8/8 [==============================] - 0s 2ms/step
161 [D loss: 0.692666, acc.: 53.91%] [G loss: 0.761636]
8/8 [==============================] - 0s 2ms/step
162 [D loss: 0.689680, acc.: 54.88%] [G loss: 0.750741]
8/8 [==============================] - 0s 2ms/step
163 [D loss: 0.693677, acc.: 53.52%] [G loss: 0.765074]
8/8 [==============================] - 0s 2ms/step
164 [D loss: 0.695181, acc.: 49.41%] [G loss: 0.753308]
8/8 [==============================] - 0s 2ms/step
165 [D loss: 0.695835, acc.: 50.59%] [G loss: 0.771426]
8/8 [==============================] - 0s 2ms/step
166 [D loss: 0.683738, acc.: 56.05%] [G loss: 0.772094]
8/8 [==============================] - 0s 2ms/step
167 [D loss: 0.693122, acc.: 51.95%] [G loss: 0.778392]
8/8 [==============================] - 0s 2ms/step
168 [D loss: 0.685275, acc.: 56.05%] [G loss: 0.784934]
8/8 [==============================] - 0s 2ms/step
169 [D loss: 0.673575, acc.: 60.16%] [G loss: 0.779357]
8/8 [==============================] - 0s 2ms/step
170 [D loss: 0.685386, acc.: 56.45%] [G loss: 0.775822]
8/8 [==============================] - 0s 2ms/step
171 [D loss: 0.681840, acc.: 57.23%] [G loss: 0.776861]
8/8 [==============================] - 0s 2ms/step
172 [D loss: 0.679119, acc.: 59.57%] [G loss: 0.782254]
8/8 [==============================] - 0s 2ms/step
173 [D loss: 0.672895, acc.: 60.94%] [G loss: 0.782354]
8/8 [==============================] - 0s 2ms/step
174 [D loss: 0.673231, acc.: 60.16%] [G loss: 0.789773]
8/8 [==============================] - 0s 2ms/step
175 [D loss: 0.679513, acc.: 57.81%] [G loss: 0.787774]
8/8 [==============================] - 0s 2ms/step
176 [D loss: 0.673388, acc.: 61.52%] [G loss: 0.795823]
8/8 [==============================] - 0s 2ms/step
177 [D loss: 0.669063, acc.: 62.11%] [G loss: 0.788891]
8/8 [==============================] - 0s 2ms/step
178 [D loss: 0.674414, acc.: 58.79%] [G loss: 0.784269]
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179 [D loss: 0.670303, acc.: 59.96%] [G loss: 0.798433]
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180 [D loss: 0.664627, acc.: 63.87%] [G loss: 0.788116]
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181 [D loss: 0.667815, acc.: 61.91%] [G loss: 0.784305]
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182 [D loss: 0.673595, acc.: 59.96%] [G loss: 0.765775]
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184 [D loss: 0.671572, acc.: 60.35%] [G loss: 0.763642]
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185 [D loss: 0.679397, acc.: 54.30%] [G loss: 0.759193]
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186 [D loss: 0.676911, acc.: 58.01%] [G loss: 0.762584]
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189 [D loss: 0.696452, acc.: 50.20%] [G loss: 0.775203]
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190 [D loss: 0.684222, acc.: 54.49%] [G loss: 0.759191]
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191 [D loss: 0.685683, acc.: 55.86%] [G loss: 0.771005]
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192 [D loss: 0.683735, acc.: 56.05%] [G loss: 0.757281]
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193 [D loss: 0.692145, acc.: 50.39%] [G loss: 0.753526]
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194 [D loss: 0.690170, acc.: 53.91%] [G loss: 0.754432]
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195 [D loss: 0.697383, acc.: 49.22%] [G loss: 0.762122]
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196 [D loss: 0.685642, acc.: 52.54%] [G loss: 0.745888]
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197 [D loss: 0.685076, acc.: 56.05%] [G loss: 0.744194]
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204 [D loss: 0.690202, acc.: 51.76%] [G loss: 0.755592]
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205 [D loss: 0.689238, acc.: 51.95%] [G loss: 0.747565]
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206 [D loss: 0.689901, acc.: 53.12%] [G loss: 0.739984]
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207 [D loss: 0.683555, acc.: 58.20%] [G loss: 0.737349]
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208 [D loss: 0.676985, acc.: 57.23%] [G loss: 0.738932]
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211 [D loss: 0.682463, acc.: 55.86%] [G loss: 0.755465]
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214 [D loss: 0.681545, acc.: 55.66%] [G loss: 0.775390]
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215 [D loss: 0.680148, acc.: 57.62%] [G loss: 0.766751]
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216 [D loss: 0.700590, acc.: 49.41%] [G loss: 0.763418]
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217 [D loss: 0.693549, acc.: 53.12%] [G loss: 0.767109]
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218 [D loss: 0.696531, acc.: 53.71%] [G loss: 0.774579]
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219 [D loss: 0.689700, acc.: 53.12%] [G loss: 0.767253]
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220 [D loss: 0.697266, acc.: 50.39%] [G loss: 0.758192]
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221 [D loss: 0.695046, acc.: 50.78%] [G loss: 0.743764]
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222 [D loss: 0.687408, acc.: 52.93%] [G loss: 0.763043]
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223 [D loss: 0.691749, acc.: 52.54%] [G loss: 0.757388]
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224 [D loss: 0.695773, acc.: 51.17%] [G loss: 0.758826]
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225 [D loss: 0.699786, acc.: 53.32%] [G loss: 0.742514]
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226 [D loss: 0.702509, acc.: 49.61%] [G loss: 0.748808]
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227 [D loss: 0.696190, acc.: 55.66%] [G loss: 0.740346]
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228 [D loss: 0.694789, acc.: 50.39%] [G loss: 0.734989]
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229 [D loss: 0.696492, acc.: 51.95%] [G loss: 0.739258]
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230 [D loss: 0.703720, acc.: 47.46%] [G loss: 0.727999]
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231 [D loss: 0.712223, acc.: 44.73%] [G loss: 0.735779]
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232 [D loss: 0.711691, acc.: 45.90%] [G loss: 0.730241]
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233 [D loss: 0.715833, acc.: 41.41%] [G loss: 0.733620]
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234 [D loss: 0.714205, acc.: 47.46%] [G loss: 0.738585]
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235 [D loss: 0.719836, acc.: 42.58%] [G loss: 0.747940]
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236 [D loss: 0.716828, acc.: 43.75%] [G loss: 0.733424]
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237 [D loss: 0.719195, acc.: 43.75%] [G loss: 0.747890]
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238 [D loss: 0.709128, acc.: 45.51%] [G loss: 0.736854]
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239 [D loss: 0.718638, acc.: 40.23%] [G loss: 0.745567]
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240 [D loss: 0.711488, acc.: 40.23%] [G loss: 0.739984]
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241 [D loss: 0.712963, acc.: 43.95%] [G loss: 0.737639]
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242 [D loss: 0.712731, acc.: 43.55%] [G loss: 0.735558]
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243 [D loss: 0.706608, acc.: 46.48%] [G loss: 0.725185]
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244 [D loss: 0.716159, acc.: 41.99%] [G loss: 0.737223]
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245 [D loss: 0.717206, acc.: 40.23%] [G loss: 0.740835]
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246 [D loss: 0.715482, acc.: 38.87%] [G loss: 0.746261]
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247 [D loss: 0.706616, acc.: 44.34%] [G loss: 0.747041]
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248 [D loss: 0.707985, acc.: 43.55%] [G loss: 0.747434]
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251 [D loss: 0.704712, acc.: 46.88%] [G loss: 0.738457]
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252 [D loss: 0.704378, acc.: 43.55%] [G loss: 0.742185]
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253 [D loss: 0.702044, acc.: 47.27%] [G loss: 0.742980]
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254 [D loss: 0.698895, acc.: 47.46%] [G loss: 0.737195]
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256 [D loss: 0.700162, acc.: 44.14%] [G loss: 0.742745]
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257 [D loss: 0.692348, acc.: 51.56%] [G loss: 0.745021]
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258 [D loss: 0.694433, acc.: 49.61%] [G loss: 0.750315]
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259 [D loss: 0.692594, acc.: 48.24%] [G loss: 0.746616]
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260 [D loss: 0.693840, acc.: 49.41%] [G loss: 0.740410]
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261 [D loss: 0.690576, acc.: 50.78%] [G loss: 0.743425]
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262 [D loss: 0.691339, acc.: 50.20%] [G loss: 0.736203]
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263 [D loss: 0.685930, acc.: 56.84%] [G loss: 0.728940]
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264 [D loss: 0.684316, acc.: 52.93%] [G loss: 0.735987]
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265 [D loss: 0.682871, acc.: 57.42%] [G loss: 0.731415]
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266 [D loss: 0.682604, acc.: 56.05%] [G loss: 0.727206]
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267 [D loss: 0.679037, acc.: 60.55%] [G loss: 0.729530]
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268 [D loss: 0.685389, acc.: 53.71%] [G loss: 0.728393]
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269 [D loss: 0.687852, acc.: 53.32%] [G loss: 0.733712]
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270 [D loss: 0.686638, acc.: 50.78%] [G loss: 0.743058]
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271 [D loss: 0.686127, acc.: 55.66%] [G loss: 0.744845]
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272 [D loss: 0.680037, acc.: 58.40%] [G loss: 0.742579]
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273 [D loss: 0.683622, acc.: 56.84%] [G loss: 0.739395]
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274 [D loss: 0.678936, acc.: 59.77%] [G loss: 0.746691]
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275 [D loss: 0.676308, acc.: 61.72%] [G loss: 0.739353]
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276 [D loss: 0.680982, acc.: 58.40%] [G loss: 0.747586]
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277 [D loss: 0.680869, acc.: 57.42%] [G loss: 0.743425]
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278 [D loss: 0.674185, acc.: 62.70%] [G loss: 0.746796]
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279 [D loss: 0.677874, acc.: 59.77%] [G loss: 0.748084]
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280 [D loss: 0.678389, acc.: 61.33%] [G loss: 0.750595]
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281 [D loss: 0.680091, acc.: 57.03%] [G loss: 0.750865]
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282 [D loss: 0.679108, acc.: 57.62%] [G loss: 0.746706]
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283 [D loss: 0.683258, acc.: 55.27%] [G loss: 0.753605]
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284 [D loss: 0.674934, acc.: 59.57%] [G loss: 0.745959]
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285 [D loss: 0.682902, acc.: 53.32%] [G loss: 0.753417]
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286 [D loss: 0.687794, acc.: 53.12%] [G loss: 0.749811]
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287 [D loss: 0.689271, acc.: 54.30%] [G loss: 0.745087]
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288 [D loss: 0.692263, acc.: 51.56%] [G loss: 0.741058]
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289 [D loss: 0.696071, acc.: 50.00%] [G loss: 0.748082]
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290 [D loss: 0.691936, acc.: 49.61%] [G loss: 0.745099]
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291 [D loss: 0.694295, acc.: 50.20%] [G loss: 0.735930]
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292 [D loss: 0.697153, acc.: 50.20%] [G loss: 0.742927]
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293 [D loss: 0.699134, acc.: 50.20%] [G loss: 0.752930]
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294 [D loss: 0.703345, acc.: 46.29%] [G loss: 0.741384]
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295 [D loss: 0.713542, acc.: 41.60%] [G loss: 0.733249]
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296 [D loss: 0.714309, acc.: 41.80%] [G loss: 0.737688]
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297 [D loss: 0.713971, acc.: 43.55%] [G loss: 0.733184]
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298 [D loss: 0.713225, acc.: 44.92%] [G loss: 0.731374]
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301 [D loss: 0.712165, acc.: 41.21%] [G loss: 0.731975]
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302 [D loss: 0.714352, acc.: 40.43%] [G loss: 0.729745]
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303 [D loss: 0.717078, acc.: 40.82%] [G loss: 0.730821]
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304 [D loss: 0.709468, acc.: 45.31%] [G loss: 0.736269]
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305 [D loss: 0.711413, acc.: 40.23%] [G loss: 0.726413]
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306 [D loss: 0.702840, acc.: 46.29%] [G loss: 0.727241]
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307 [D loss: 0.708158, acc.: 42.19%] [G loss: 0.730576]
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308 [D loss: 0.710741, acc.: 41.21%] [G loss: 0.723817]
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309 [D loss: 0.708672, acc.: 42.38%] [G loss: 0.723842]
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310 [D loss: 0.707838, acc.: 42.38%] [G loss: 0.724300]
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311 [D loss: 0.706501, acc.: 43.75%] [G loss: 0.727608]
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312 [D loss: 0.708020, acc.: 42.19%] [G loss: 0.734810]
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313 [D loss: 0.701996, acc.: 45.90%] [G loss: 0.725526]
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314 [D loss: 0.703304, acc.: 41.80%] [G loss: 0.728816]
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315 [D loss: 0.701201, acc.: 43.36%] [G loss: 0.729759]
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316 [D loss: 0.697503, acc.: 47.85%] [G loss: 0.727935]
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317 [D loss: 0.699043, acc.: 45.90%] [G loss: 0.724728]
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318 [D loss: 0.701260, acc.: 43.75%] [G loss: 0.723297]
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319 [D loss: 0.699183, acc.: 47.46%] [G loss: 0.732030]
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320 [D loss: 0.699875, acc.: 47.27%] [G loss: 0.726136]
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321 [D loss: 0.703574, acc.: 44.53%] [G loss: 0.728155]
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322 [D loss: 0.696532, acc.: 47.46%] [G loss: 0.725945]
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323 [D loss: 0.699513, acc.: 47.07%] [G loss: 0.732893]
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324 [D loss: 0.696213, acc.: 47.07%] [G loss: 0.730459]
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325 [D loss: 0.693804, acc.: 50.00%] [G loss: 0.730118]
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326 [D loss: 0.692692, acc.: 48.83%] [G loss: 0.733570]
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327 [D loss: 0.695614, acc.: 49.02%] [G loss: 0.732968]
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328 [D loss: 0.695886, acc.: 50.00%] [G loss: 0.738205]
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329 [D loss: 0.696531, acc.: 48.24%] [G loss: 0.729321]
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330 [D loss: 0.694291, acc.: 49.80%] [G loss: 0.731698]
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331 [D loss: 0.696152, acc.: 48.05%] [G loss: 0.740323]
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332 [D loss: 0.691819, acc.: 50.00%] [G loss: 0.738743]
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333 [D loss: 0.691112, acc.: 52.54%] [G loss: 0.732998]
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334 [D loss: 0.692953, acc.: 49.41%] [G loss: 0.738346]
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335 [D loss: 0.689878, acc.: 53.52%] [G loss: 0.738685]
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336 [D loss: 0.690281, acc.: 55.27%] [G loss: 0.736862]
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337 [D loss: 0.693287, acc.: 51.56%] [G loss: 0.739166]
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338 [D loss: 0.690960, acc.: 53.91%] [G loss: 0.736601]
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339 [D loss: 0.687442, acc.: 54.10%] [G loss: 0.740018]
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340 [D loss: 0.691420, acc.: 51.76%] [G loss: 0.739613]
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341 [D loss: 0.690825, acc.: 53.71%] [G loss: 0.734590]
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342 [D loss: 0.688277, acc.: 55.47%] [G loss: 0.732955]
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343 [D loss: 0.690194, acc.: 52.93%] [G loss: 0.734912]
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344 [D loss: 0.691000, acc.: 52.15%] [G loss: 0.732815]
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345 [D loss: 0.689518, acc.: 52.73%] [G loss: 0.741771]
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346 [D loss: 0.688970, acc.: 56.05%] [G loss: 0.740734]
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347 [D loss: 0.691996, acc.: 51.17%] [G loss: 0.736659]
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348 [D loss: 0.687095, acc.: 53.71%] [G loss: 0.741390]
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349 [D loss: 0.689594, acc.: 56.84%] [G loss: 0.735768]
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351 [D loss: 0.687783, acc.: 55.08%] [G loss: 0.736023]
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352 [D loss: 0.688500, acc.: 55.66%] [G loss: 0.735963]
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353 [D loss: 0.690001, acc.: 54.69%] [G loss: 0.735906]
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354 [D loss: 0.688817, acc.: 56.25%] [G loss: 0.735887]
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355 [D loss: 0.693967, acc.: 53.32%] [G loss: 0.733195]
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356 [D loss: 0.689047, acc.: 54.49%] [G loss: 0.731331]
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357 [D loss: 0.693315, acc.: 50.59%] [G loss: 0.730041]
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358 [D loss: 0.694221, acc.: 52.15%] [G loss: 0.730613]
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359 [D loss: 0.691794, acc.: 53.71%] [G loss: 0.730666]
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360 [D loss: 0.694095, acc.: 50.98%] [G loss: 0.735704]
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361 [D loss: 0.692561, acc.: 51.56%] [G loss: 0.729212]
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362 [D loss: 0.694429, acc.: 48.05%] [G loss: 0.736592]
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363 [D loss: 0.691535, acc.: 51.95%] [G loss: 0.731062]
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364 [D loss: 0.695631, acc.: 52.15%] [G loss: 0.735464]
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365 [D loss: 0.692907, acc.: 49.61%] [G loss: 0.731210]
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366 [D loss: 0.692494, acc.: 52.34%] [G loss: 0.742803]
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367 [D loss: 0.693696, acc.: 52.34%] [G loss: 0.741789]
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368 [D loss: 0.690964, acc.: 52.15%] [G loss: 0.740896]
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369 [D loss: 0.691612, acc.: 50.59%] [G loss: 0.747270]
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370 [D loss: 0.693247, acc.: 52.93%] [G loss: 0.739640]
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371 [D loss: 0.692136, acc.: 51.37%] [G loss: 0.749391]
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372 [D loss: 0.693458, acc.: 51.17%] [G loss: 0.750248]
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373 [D loss: 0.690661, acc.: 50.98%] [G loss: 0.752452]
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374 [D loss: 0.695594, acc.: 49.61%] [G loss: 0.749724]
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375 [D loss: 0.687258, acc.: 53.71%] [G loss: 0.748716]
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376 [D loss: 0.692353, acc.: 50.78%] [G loss: 0.748560]
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377 [D loss: 0.690838, acc.: 53.12%] [G loss: 0.755738]
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378 [D loss: 0.689235, acc.: 53.12%] [G loss: 0.755754]
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379 [D loss: 0.689612, acc.: 51.37%] [G loss: 0.755786]
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380 [D loss: 0.692257, acc.: 52.93%] [G loss: 0.751440]
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381 [D loss: 0.690018, acc.: 53.32%] [G loss: 0.751796]
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382 [D loss: 0.686860, acc.: 53.12%] [G loss: 0.750074]
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383 [D loss: 0.688335, acc.: 52.34%] [G loss: 0.758216]
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384 [D loss: 0.686502, acc.: 56.05%] [G loss: 0.758200]
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385 [D loss: 0.685116, acc.: 55.27%] [G loss: 0.751639]
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386 [D loss: 0.686860, acc.: 53.91%] [G loss: 0.749825]
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387 [D loss: 0.690826, acc.: 54.10%] [G loss: 0.754101]
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388 [D loss: 0.690964, acc.: 52.15%] [G loss: 0.746806]
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389 [D loss: 0.689087, acc.: 53.12%] [G loss: 0.749802]
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390 [D loss: 0.689243, acc.: 52.54%] [G loss: 0.743277]
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391 [D loss: 0.695818, acc.: 49.22%] [G loss: 0.738687]
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392 [D loss: 0.692764, acc.: 52.15%] [G loss: 0.744122]
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393 [D loss: 0.696725, acc.: 50.00%] [G loss: 0.735484]
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394 [D loss: 0.698392, acc.: 48.24%] [G loss: 0.740077]
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395 [D loss: 0.694113, acc.: 50.39%] [G loss: 0.733585]
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396 [D loss: 0.698283, acc.: 48.44%] [G loss: 0.737816]
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397 [D loss: 0.701429, acc.: 46.48%] [G loss: 0.736624]
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398 [D loss: 0.697301, acc.: 46.29%] [G loss: 0.736866]
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399 [D loss: 0.703063, acc.: 44.14%] [G loss: 0.734329]
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400 [D loss: 0.699540, acc.: 46.48%] [G loss: 0.746019]
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401 [D loss: 0.700825, acc.: 46.68%] [G loss: 0.734296]
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402 [D loss: 0.700796, acc.: 44.92%] [G loss: 0.730168]
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403 [D loss: 0.699840, acc.: 45.31%] [G loss: 0.736238]
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404 [D loss: 0.701623, acc.: 44.14%] [G loss: 0.734985]
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405 [D loss: 0.703481, acc.: 43.95%] [G loss: 0.738701]
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406 [D loss: 0.698848, acc.: 48.63%] [G loss: 0.741937]
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407 [D loss: 0.699402, acc.: 44.73%] [G loss: 0.733362]
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408 [D loss: 0.700287, acc.: 44.53%] [G loss: 0.732174]
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409 [D loss: 0.699665, acc.: 46.68%] [G loss: 0.736361]
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410 [D loss: 0.697593, acc.: 47.85%] [G loss: 0.734949]
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411 [D loss: 0.700082, acc.: 48.63%] [G loss: 0.735003]
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412 [D loss: 0.697470, acc.: 48.44%] [G loss: 0.733548]
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413 [D loss: 0.693914, acc.: 50.78%] [G loss: 0.736609]
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414 [D loss: 0.698162, acc.: 49.22%] [G loss: 0.735710]
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415 [D loss: 0.696325, acc.: 50.78%] [G loss: 0.731388]
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416 [D loss: 0.692402, acc.: 50.00%] [G loss: 0.738354]
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417 [D loss: 0.695415, acc.: 50.00%] [G loss: 0.733267]
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418 [D loss: 0.693822, acc.: 50.78%] [G loss: 0.731883]
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419 [D loss: 0.696515, acc.: 45.31%] [G loss: 0.731638]
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420 [D loss: 0.692336, acc.: 52.15%] [G loss: 0.732335]
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421 [D loss: 0.693144, acc.: 52.54%] [G loss: 0.729548]
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422 [D loss: 0.692262, acc.: 52.93%] [G loss: 0.734904]
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423 [D loss: 0.692546, acc.: 53.12%] [G loss: 0.731734]
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424 [D loss: 0.694560, acc.: 50.00%] [G loss: 0.729760]
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425 [D loss: 0.693219, acc.: 51.76%] [G loss: 0.723971]
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426 [D loss: 0.695052, acc.: 49.80%] [G loss: 0.731120]
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427 [D loss: 0.688702, acc.: 53.32%] [G loss: 0.727289]
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428 [D loss: 0.691723, acc.: 50.00%] [G loss: 0.727459]
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429 [D loss: 0.695095, acc.: 46.68%] [G loss: 0.719671]
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430 [D loss: 0.692444, acc.: 52.73%] [G loss: 0.721560]
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431 [D loss: 0.692725, acc.: 50.39%] [G loss: 0.726431]
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432 [D loss: 0.696229, acc.: 48.83%] [G loss: 0.722120]
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433 [D loss: 0.694374, acc.: 51.56%] [G loss: 0.721046]
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434 [D loss: 0.697716, acc.: 49.80%] [G loss: 0.721507]
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435 [D loss: 0.702058, acc.: 47.07%] [G loss: 0.719836]
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436 [D loss: 0.692348, acc.: 52.34%] [G loss: 0.719758]
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437 [D loss: 0.697774, acc.: 47.66%] [G loss: 0.717572]
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438 [D loss: 0.694411, acc.: 49.80%] [G loss: 0.718767]
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439 [D loss: 0.698241, acc.: 48.05%] [G loss: 0.720333]
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440 [D loss: 0.690439, acc.: 54.49%] [G loss: 0.721175]
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441 [D loss: 0.698917, acc.: 46.68%] [G loss: 0.718908]
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442 [D loss: 0.695099, acc.: 50.20%] [G loss: 0.716607]
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443 [D loss: 0.698943, acc.: 48.24%] [G loss: 0.722432]
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444 [D loss: 0.696715, acc.: 48.44%] [G loss: 0.715935]
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445 [D loss: 0.695977, acc.: 50.78%] [G loss: 0.717397]
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446 [D loss: 0.698169, acc.: 45.12%] [G loss: 0.724372]
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447 [D loss: 0.692748, acc.: 50.20%] [G loss: 0.713667]
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448 [D loss: 0.692035, acc.: 51.37%] [G loss: 0.717831]
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449 [D loss: 0.696422, acc.: 46.09%] [G loss: 0.724493]
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450 [D loss: 0.693902, acc.: 47.85%] [G loss: 0.719232]
1/1 [==============================] - 0s 15ms/step
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451 [D loss: 0.695542, acc.: 47.27%] [G loss: 0.725384]
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452 [D loss: 0.690988, acc.: 52.15%] [G loss: 0.722209]
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453 [D loss: 0.692850, acc.: 52.15%] [G loss: 0.719333]
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454 [D loss: 0.689680, acc.: 52.93%] [G loss: 0.721388]
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455 [D loss: 0.695447, acc.: 48.05%] [G loss: 0.723328]
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456 [D loss: 0.687486, acc.: 56.45%] [G loss: 0.719223]
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457 [D loss: 0.689645, acc.: 55.66%] [G loss: 0.720138]
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458 [D loss: 0.689575, acc.: 50.39%] [G loss: 0.722012]
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459 [D loss: 0.690926, acc.: 50.39%] [G loss: 0.720058]
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460 [D loss: 0.689297, acc.: 52.15%] [G loss: 0.723416]
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461 [D loss: 0.691474, acc.: 50.98%] [G loss: 0.712636]
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462 [D loss: 0.691273, acc.: 50.78%] [G loss: 0.723854]
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463 [D loss: 0.689283, acc.: 50.78%] [G loss: 0.724011]
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464 [D loss: 0.689807, acc.: 52.54%] [G loss: 0.722213]
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465 [D loss: 0.692202, acc.: 51.56%] [G loss: 0.729839]
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466 [D loss: 0.688838, acc.: 53.91%] [G loss: 0.727783]
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467 [D loss: 0.688130, acc.: 52.54%] [G loss: 0.722786]
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468 [D loss: 0.690822, acc.: 52.34%] [G loss: 0.730108]
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469 [D loss: 0.688136, acc.: 53.32%] [G loss: 0.725527]
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470 [D loss: 0.689275, acc.: 50.98%] [G loss: 0.725104]
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471 [D loss: 0.687981, acc.: 55.08%] [G loss: 0.723523]
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472 [D loss: 0.690102, acc.: 51.76%] [G loss: 0.724226]
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473 [D loss: 0.691359, acc.: 49.61%] [G loss: 0.721301]
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474 [D loss: 0.689605, acc.: 52.54%] [G loss: 0.723513]
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475 [D loss: 0.692897, acc.: 50.39%] [G loss: 0.724586]
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476 [D loss: 0.692416, acc.: 51.17%] [G loss: 0.724625]
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477 [D loss: 0.691698, acc.: 53.32%] [G loss: 0.726821]
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478 [D loss: 0.691320, acc.: 52.34%] [G loss: 0.730545]
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479 [D loss: 0.689878, acc.: 52.54%] [G loss: 0.732255]
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480 [D loss: 0.693204, acc.: 50.59%] [G loss: 0.726731]
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481 [D loss: 0.691489, acc.: 50.20%] [G loss: 0.728070]
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482 [D loss: 0.692157, acc.: 51.37%] [G loss: 0.724444]
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483 [D loss: 0.694647, acc.: 52.34%] [G loss: 0.724660]
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484 [D loss: 0.693033, acc.: 49.41%] [G loss: 0.718026]
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485 [D loss: 0.696930, acc.: 45.70%] [G loss: 0.719268]
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486 [D loss: 0.690868, acc.: 53.12%] [G loss: 0.721217]
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487 [D loss: 0.696368, acc.: 48.05%] [G loss: 0.724450]
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488 [D loss: 0.697170, acc.: 48.44%] [G loss: 0.722146]
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489 [D loss: 0.698119, acc.: 49.22%] [G loss: 0.724669]
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490 [D loss: 0.698523, acc.: 45.70%] [G loss: 0.724553]
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491 [D loss: 0.700352, acc.: 43.36%] [G loss: 0.726489]
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492 [D loss: 0.698124, acc.: 47.27%] [G loss: 0.719179]
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493 [D loss: 0.703065, acc.: 42.97%] [G loss: 0.722793]
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494 [D loss: 0.695894, acc.: 47.66%] [G loss: 0.720458]
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495 [D loss: 0.695217, acc.: 46.68%] [G loss: 0.717476]
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496 [D loss: 0.695480, acc.: 49.61%] [G loss: 0.718270]
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497 [D loss: 0.698578, acc.: 46.68%] [G loss: 0.724664]
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498 [D loss: 0.696402, acc.: 48.05%] [G loss: 0.728751]
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499 [D loss: 0.696896, acc.: 45.51%] [G loss: 0.722550]
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500 [D loss: 0.696602, acc.: 45.31%] [G loss: 0.725510]
1/1 [==============================] - 0s 14ms/step
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501 [D loss: 0.698218, acc.: 46.88%] [G loss: 0.725981]
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502 [D loss: 0.695670, acc.: 48.05%] [G loss: 0.724472]
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503 [D loss: 0.697058, acc.: 48.63%] [G loss: 0.722799]
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504 [D loss: 0.692779, acc.: 48.63%] [G loss: 0.723114]
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505 [D loss: 0.696027, acc.: 46.48%] [G loss: 0.721921]
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506 [D loss: 0.693681, acc.: 49.61%] [G loss: 0.724857]
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507 [D loss: 0.692535, acc.: 52.15%] [G loss: 0.727188]
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508 [D loss: 0.696835, acc.: 47.66%] [G loss: 0.728104]
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509 [D loss: 0.690894, acc.: 54.30%] [G loss: 0.732002]
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510 [D loss: 0.692712, acc.: 52.34%] [G loss: 0.733242]
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511 [D loss: 0.688532, acc.: 54.30%] [G loss: 0.732655]
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512 [D loss: 0.690258, acc.: 53.12%] [G loss: 0.731578]
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513 [D loss: 0.692217, acc.: 48.44%] [G loss: 0.734158]
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514 [D loss: 0.689771, acc.: 53.91%] [G loss: 0.732322]
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515 [D loss: 0.692837, acc.: 49.22%] [G loss: 0.728479]
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516 [D loss: 0.687973, acc.: 54.30%] [G loss: 0.724732]
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517 [D loss: 0.692667, acc.: 50.20%] [G loss: 0.728458]
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518 [D loss: 0.688470, acc.: 54.69%] [G loss: 0.727491]
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519 [D loss: 0.690442, acc.: 52.34%] [G loss: 0.722728]
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520 [D loss: 0.695550, acc.: 49.41%] [G loss: 0.725950]
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521 [D loss: 0.688572, acc.: 54.49%] [G loss: 0.728531]
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522 [D loss: 0.695040, acc.: 51.95%] [G loss: 0.729932]
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523 [D loss: 0.693691, acc.: 50.20%] [G loss: 0.728186]
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524 [D loss: 0.692355, acc.: 51.37%] [G loss: 0.731548]
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525 [D loss: 0.691054, acc.: 48.44%] [G loss: 0.732104]
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526 [D loss: 0.691516, acc.: 50.59%] [G loss: 0.730713]
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527 [D loss: 0.694895, acc.: 48.44%] [G loss: 0.731565]
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528 [D loss: 0.692985, acc.: 50.00%] [G loss: 0.728402]
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529 [D loss: 0.691076, acc.: 53.32%] [G loss: 0.732284]
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530 [D loss: 0.692720, acc.: 51.17%] [G loss: 0.727588]
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531 [D loss: 0.692410, acc.: 52.73%] [G loss: 0.729096]
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532 [D loss: 0.692089, acc.: 48.24%] [G loss: 0.731012]
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533 [D loss: 0.692517, acc.: 49.02%] [G loss: 0.728188]
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534 [D loss: 0.690666, acc.: 51.37%] [G loss: 0.720717]
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535 [D loss: 0.698678, acc.: 47.27%] [G loss: 0.722067]
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536 [D loss: 0.691386, acc.: 49.80%] [G loss: 0.732465]
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537 [D loss: 0.693690, acc.: 48.63%] [G loss: 0.735084]
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538 [D loss: 0.697160, acc.: 46.48%] [G loss: 0.732325]
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539 [D loss: 0.691535, acc.: 53.52%] [G loss: 0.727427]
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540 [D loss: 0.695001, acc.: 51.56%] [G loss: 0.727730]
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541 [D loss: 0.695663, acc.: 48.44%] [G loss: 0.726303]
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542 [D loss: 0.698313, acc.: 48.44%] [G loss: 0.729560]
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543 [D loss: 0.696650, acc.: 49.41%] [G loss: 0.730907]
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544 [D loss: 0.696245, acc.: 50.20%] [G loss: 0.731999]
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545 [D loss: 0.698327, acc.: 47.46%] [G loss: 0.732909]
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546 [D loss: 0.699059, acc.: 46.29%] [G loss: 0.734119]
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547 [D loss: 0.695811, acc.: 48.05%] [G loss: 0.735926]
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548 [D loss: 0.697194, acc.: 45.70%] [G loss: 0.733864]
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549 [D loss: 0.697571, acc.: 48.24%] [G loss: 0.739552]
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550 [D loss: 0.694892, acc.: 50.00%] [G loss: 0.740232]
1/1 [==============================] - 0s 17ms/step
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551 [D loss: 0.698481, acc.: 46.29%] [G loss: 0.738566]
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552 [D loss: 0.696977, acc.: 47.66%] [G loss: 0.737065]
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553 [D loss: 0.697086, acc.: 46.88%] [G loss: 0.737778]
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554 [D loss: 0.697403, acc.: 46.29%] [G loss: 0.732714]
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555 [D loss: 0.691825, acc.: 51.76%] [G loss: 0.737707]
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556 [D loss: 0.697697, acc.: 45.90%] [G loss: 0.730503]
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557 [D loss: 0.696172, acc.: 45.90%] [G loss: 0.732522]
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558 [D loss: 0.695089, acc.: 50.78%] [G loss: 0.740474]
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559 [D loss: 0.692219, acc.: 49.22%] [G loss: 0.729429]
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560 [D loss: 0.695771, acc.: 48.24%] [G loss: 0.731487]
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561 [D loss: 0.694885, acc.: 49.80%] [G loss: 0.739857]
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562 [D loss: 0.695177, acc.: 49.22%] [G loss: 0.735345]
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563 [D loss: 0.695468, acc.: 48.63%] [G loss: 0.737702]
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564 [D loss: 0.693763, acc.: 49.41%] [G loss: 0.743318]
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565 [D loss: 0.697595, acc.: 47.27%] [G loss: 0.740165]
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566 [D loss: 0.692732, acc.: 49.61%] [G loss: 0.741392]
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567 [D loss: 0.693723, acc.: 48.24%] [G loss: 0.741276]
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568 [D loss: 0.692301, acc.: 49.61%] [G loss: 0.738915]
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569 [D loss: 0.693287, acc.: 50.59%] [G loss: 0.738051]
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570 [D loss: 0.691064, acc.: 50.20%] [G loss: 0.739524]
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571 [D loss: 0.692283, acc.: 51.76%] [G loss: 0.738554]
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572 [D loss: 0.691419, acc.: 52.15%] [G loss: 0.740818]
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573 [D loss: 0.689266, acc.: 53.32%] [G loss: 0.736763]
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574 [D loss: 0.689480, acc.: 51.76%] [G loss: 0.734755]
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575 [D loss: 0.689206, acc.: 51.17%] [G loss: 0.741728]
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576 [D loss: 0.692168, acc.: 49.22%] [G loss: 0.733497]
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577 [D loss: 0.689942, acc.: 50.59%] [G loss: 0.739467]
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578 [D loss: 0.689039, acc.: 51.76%] [G loss: 0.733840]
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579 [D loss: 0.686738, acc.: 54.69%] [G loss: 0.732280]
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580 [D loss: 0.694729, acc.: 49.80%] [G loss: 0.734366]
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581 [D loss: 0.685571, acc.: 53.91%] [G loss: 0.732324]
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582 [D loss: 0.689203, acc.: 52.73%] [G loss: 0.727560]
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583 [D loss: 0.690028, acc.: 52.15%] [G loss: 0.731867]
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584 [D loss: 0.692890, acc.: 50.20%] [G loss: 0.727146]
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585 [D loss: 0.690465, acc.: 50.98%] [G loss: 0.723475]
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586 [D loss: 0.694030, acc.: 50.59%] [G loss: 0.718683]
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587 [D loss: 0.697381, acc.: 50.20%] [G loss: 0.721758]
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588 [D loss: 0.696446, acc.: 45.31%] [G loss: 0.721381]
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589 [D loss: 0.693175, acc.: 49.61%] [G loss: 0.723757]
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590 [D loss: 0.689933, acc.: 51.17%] [G loss: 0.716034]
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591 [D loss: 0.694645, acc.: 49.41%] [G loss: 0.724988]
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592 [D loss: 0.695360, acc.: 45.90%] [G loss: 0.718715]
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593 [D loss: 0.695270, acc.: 46.48%] [G loss: 0.722976]
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594 [D loss: 0.695935, acc.: 47.27%] [G loss: 0.713944]
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595 [D loss: 0.695671, acc.: 49.22%] [G loss: 0.716750]
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596 [D loss: 0.694788, acc.: 46.09%] [G loss: 0.716096]
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597 [D loss: 0.695585, acc.: 46.09%] [G loss: 0.715543]
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598 [D loss: 0.696112, acc.: 46.29%] [G loss: 0.715716]
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599 [D loss: 0.694548, acc.: 47.27%] [G loss: 0.716186]
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600 [D loss: 0.695052, acc.: 45.70%] [G loss: 0.719061]
1/1 [==============================] - 0s 15ms/step
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601 [D loss: 0.697614, acc.: 44.53%] [G loss: 0.716692]
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602 [D loss: 0.697976, acc.: 43.36%] [G loss: 0.719161]
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603 [D loss: 0.699320, acc.: 45.12%] [G loss: 0.715173]
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604 [D loss: 0.692220, acc.: 47.46%] [G loss: 0.717951]
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605 [D loss: 0.697031, acc.: 47.07%] [G loss: 0.715955]
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606 [D loss: 0.694727, acc.: 48.44%] [G loss: 0.718298]
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607 [D loss: 0.691785, acc.: 50.59%] [G loss: 0.714833]
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608 [D loss: 0.692224, acc.: 49.41%] [G loss: 0.718109]
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609 [D loss: 0.692244, acc.: 54.30%] [G loss: 0.716487]
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610 [D loss: 0.692858, acc.: 50.98%] [G loss: 0.714663]
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611 [D loss: 0.690341, acc.: 50.78%] [G loss: 0.711855]
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612 [D loss: 0.692986, acc.: 48.44%] [G loss: 0.718474]
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613 [D loss: 0.695783, acc.: 44.53%] [G loss: 0.715892]
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614 [D loss: 0.688969, acc.: 52.15%] [G loss: 0.721648]
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615 [D loss: 0.690448, acc.: 51.56%] [G loss: 0.723123]
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616 [D loss: 0.690888, acc.: 52.54%] [G loss: 0.722320]
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617 [D loss: 0.687134, acc.: 53.71%] [G loss: 0.715313]
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618 [D loss: 0.696068, acc.: 47.66%] [G loss: 0.720699]
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619 [D loss: 0.693303, acc.: 50.20%] [G loss: 0.722424]
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620 [D loss: 0.689745, acc.: 54.49%] [G loss: 0.723219]
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621 [D loss: 0.696035, acc.: 49.02%] [G loss: 0.723219]
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622 [D loss: 0.689468, acc.: 52.15%] [G loss: 0.726922]
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623 [D loss: 0.689518, acc.: 54.10%] [G loss: 0.730455]
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624 [D loss: 0.689107, acc.: 53.12%] [G loss: 0.729295]
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625 [D loss: 0.691220, acc.: 52.93%] [G loss: 0.732523]
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626 [D loss: 0.688685, acc.: 53.91%] [G loss: 0.733437]
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627 [D loss: 0.691809, acc.: 50.78%] [G loss: 0.737825]
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628 [D loss: 0.692129, acc.: 50.98%] [G loss: 0.739857]
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629 [D loss: 0.693178, acc.: 50.78%] [G loss: 0.737874]
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630 [D loss: 0.690281, acc.: 54.88%] [G loss: 0.738601]
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631 [D loss: 0.692866, acc.: 49.22%] [G loss: 0.740180]
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632 [D loss: 0.690050, acc.: 51.76%] [G loss: 0.741339]
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633 [D loss: 0.690517, acc.: 51.17%] [G loss: 0.748479]
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634 [D loss: 0.690207, acc.: 53.91%] [G loss: 0.744825]
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635 [D loss: 0.691024, acc.: 51.95%] [G loss: 0.743851]
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636 [D loss: 0.690256, acc.: 54.69%] [G loss: 0.744082]
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637 [D loss: 0.693092, acc.: 50.00%] [G loss: 0.747055]
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638 [D loss: 0.687976, acc.: 52.54%] [G loss: 0.742979]
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639 [D loss: 0.690170, acc.: 50.98%] [G loss: 0.750108]
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640 [D loss: 0.689377, acc.: 53.71%] [G loss: 0.744187]
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641 [D loss: 0.690240, acc.: 50.59%] [G loss: 0.746051]
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642 [D loss: 0.685504, acc.: 55.08%] [G loss: 0.747539]
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643 [D loss: 0.690934, acc.: 50.39%] [G loss: 0.740935]
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644 [D loss: 0.688038, acc.: 53.91%] [G loss: 0.734409]
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645 [D loss: 0.687335, acc.: 53.91%] [G loss: 0.734435]
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646 [D loss: 0.693961, acc.: 49.61%] [G loss: 0.732141]
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647 [D loss: 0.691843, acc.: 48.83%] [G loss: 0.740322]
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648 [D loss: 0.690975, acc.: 50.78%] [G loss: 0.734405]
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649 [D loss: 0.689296, acc.: 53.52%] [G loss: 0.723026]
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650 [D loss: 0.691930, acc.: 53.32%] [G loss: 0.737079]
1/1 [==============================] - 0s 16ms/step
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651 [D loss: 0.691827, acc.: 50.59%] [G loss: 0.725839]
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652 [D loss: 0.696480, acc.: 50.59%] [G loss: 0.728084]
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653 [D loss: 0.694260, acc.: 50.00%] [G loss: 0.725960]
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654 [D loss: 0.692337, acc.: 51.56%] [G loss: 0.724187]
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655 [D loss: 0.694150, acc.: 52.34%] [G loss: 0.725124]
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656 [D loss: 0.696571, acc.: 49.80%] [G loss: 0.724087]
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657 [D loss: 0.692669, acc.: 50.59%] [G loss: 0.725261]
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658 [D loss: 0.697122, acc.: 48.24%] [G loss: 0.727015]
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659 [D loss: 0.696830, acc.: 47.27%] [G loss: 0.729847]
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660 [D loss: 0.691999, acc.: 50.59%] [G loss: 0.729330]
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661 [D loss: 0.696875, acc.: 46.68%] [G loss: 0.727549]
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662 [D loss: 0.692813, acc.: 49.80%] [G loss: 0.725078]
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663 [D loss: 0.695082, acc.: 50.00%] [G loss: 0.723187]
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664 [D loss: 0.691913, acc.: 50.00%] [G loss: 0.722454]
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665 [D loss: 0.695408, acc.: 46.68%] [G loss: 0.728192]
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666 [D loss: 0.691671, acc.: 52.34%] [G loss: 0.723167]
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667 [D loss: 0.692523, acc.: 51.17%] [G loss: 0.728374]
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668 [D loss: 0.690231, acc.: 50.20%] [G loss: 0.727473]
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669 [D loss: 0.692548, acc.: 50.59%] [G loss: 0.732879]
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670 [D loss: 0.688090, acc.: 53.52%] [G loss: 0.733543]
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671 [D loss: 0.688517, acc.: 48.83%] [G loss: 0.732639]
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672 [D loss: 0.690270, acc.: 52.34%] [G loss: 0.731306]
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673 [D loss: 0.689340, acc.: 55.27%] [G loss: 0.732489]
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674 [D loss: 0.695290, acc.: 49.61%] [G loss: 0.728725]
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675 [D loss: 0.692155, acc.: 49.02%] [G loss: 0.734096]
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676 [D loss: 0.692328, acc.: 50.78%] [G loss: 0.728476]
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677 [D loss: 0.690876, acc.: 54.88%] [G loss: 0.737325]
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678 [D loss: 0.693596, acc.: 49.61%] [G loss: 0.729637]
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679 [D loss: 0.693569, acc.: 48.83%] [G loss: 0.727343]
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680 [D loss: 0.697173, acc.: 45.90%] [G loss: 0.736632]
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681 [D loss: 0.692722, acc.: 51.95%] [G loss: 0.732814]
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682 [D loss: 0.692748, acc.: 47.85%] [G loss: 0.730063]
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683 [D loss: 0.695138, acc.: 49.02%] [G loss: 0.729182]
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684 [D loss: 0.692373, acc.: 48.63%] [G loss: 0.734962]
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685 [D loss: 0.698204, acc.: 45.90%] [G loss: 0.727707]
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686 [D loss: 0.693722, acc.: 46.88%] [G loss: 0.724345]
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687 [D loss: 0.693701, acc.: 48.24%] [G loss: 0.731327]
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688 [D loss: 0.693295, acc.: 50.78%] [G loss: 0.732752]
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689 [D loss: 0.695316, acc.: 47.07%] [G loss: 0.733090]
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690 [D loss: 0.692760, acc.: 50.78%] [G loss: 0.731115]
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691 [D loss: 0.693123, acc.: 52.15%] [G loss: 0.730410]
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692 [D loss: 0.692978, acc.: 53.71%] [G loss: 0.738418]
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693 [D loss: 0.691994, acc.: 51.56%] [G loss: 0.733184]
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694 [D loss: 0.690915, acc.: 50.78%] [G loss: 0.736595]
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695 [D loss: 0.689126, acc.: 52.54%] [G loss: 0.737850]
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696 [D loss: 0.689559, acc.: 52.93%] [G loss: 0.734846]
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697 [D loss: 0.693047, acc.: 49.61%] [G loss: 0.739203]
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698 [D loss: 0.686575, acc.: 55.66%] [G loss: 0.737137]
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699 [D loss: 0.689811, acc.: 52.93%] [G loss: 0.735863]
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700 [D loss: 0.690967, acc.: 51.37%] [G loss: 0.740205]
1/1 [==============================] - 0s 16ms/step
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701 [D loss: 0.688223, acc.: 52.34%] [G loss: 0.739972]
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702 [D loss: 0.687499, acc.: 55.27%] [G loss: 0.740096]
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703 [D loss: 0.690816, acc.: 49.02%] [G loss: 0.741183]
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704 [D loss: 0.689270, acc.: 51.37%] [G loss: 0.737946]
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705 [D loss: 0.688828, acc.: 52.73%] [G loss: 0.740632]
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706 [D loss: 0.685061, acc.: 55.27%] [G loss: 0.743998]
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707 [D loss: 0.690125, acc.: 53.91%] [G loss: 0.737145]
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708 [D loss: 0.686040, acc.: 56.45%] [G loss: 0.735546]
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709 [D loss: 0.689213, acc.: 52.73%] [G loss: 0.733605]
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710 [D loss: 0.686350, acc.: 53.52%] [G loss: 0.735477]
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711 [D loss: 0.685429, acc.: 52.93%] [G loss: 0.734919]
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712 [D loss: 0.684417, acc.: 53.12%] [G loss: 0.735094]
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713 [D loss: 0.689979, acc.: 50.00%] [G loss: 0.732997]
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714 [D loss: 0.684970, acc.: 54.88%] [G loss: 0.727577]
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715 [D loss: 0.687003, acc.: 53.12%] [G loss: 0.732359]
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716 [D loss: 0.688370, acc.: 53.71%] [G loss: 0.729477]
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717 [D loss: 0.686719, acc.: 53.52%] [G loss: 0.729136]
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718 [D loss: 0.692676, acc.: 49.22%] [G loss: 0.738298]
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719 [D loss: 0.688289, acc.: 50.00%] [G loss: 0.726749]
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720 [D loss: 0.693493, acc.: 46.88%] [G loss: 0.732286]
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721 [D loss: 0.690081, acc.: 51.37%] [G loss: 0.729853]
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722 [D loss: 0.693832, acc.: 49.61%] [G loss: 0.733911]
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723 [D loss: 0.690060, acc.: 49.61%] [G loss: 0.735959]
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724 [D loss: 0.688508, acc.: 51.56%] [G loss: 0.741587]
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725 [D loss: 0.689102, acc.: 53.12%] [G loss: 0.736374]
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726 [D loss: 0.689528, acc.: 52.34%] [G loss: 0.741706]
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727 [D loss: 0.688784, acc.: 54.49%] [G loss: 0.743576]
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728 [D loss: 0.691051, acc.: 51.17%] [G loss: 0.740689]
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729 [D loss: 0.690396, acc.: 51.56%] [G loss: 0.743117]
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730 [D loss: 0.688288, acc.: 52.54%] [G loss: 0.742164]
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731 [D loss: 0.687780, acc.: 53.71%] [G loss: 0.744692]
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732 [D loss: 0.689548, acc.: 50.39%] [G loss: 0.742850]
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733 [D loss: 0.686459, acc.: 55.86%] [G loss: 0.740026]
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734 [D loss: 0.689236, acc.: 54.49%] [G loss: 0.736851]
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735 [D loss: 0.688450, acc.: 55.08%] [G loss: 0.740063]
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736 [D loss: 0.689446, acc.: 52.73%] [G loss: 0.738086]
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737 [D loss: 0.690881, acc.: 50.98%] [G loss: 0.737928]
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738 [D loss: 0.687815, acc.: 54.69%] [G loss: 0.738894]
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739 [D loss: 0.689074, acc.: 53.32%] [G loss: 0.733068]
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740 [D loss: 0.690579, acc.: 51.56%] [G loss: 0.738943]
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741 [D loss: 0.691337, acc.: 52.73%] [G loss: 0.742468]
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742 [D loss: 0.689191, acc.: 51.76%] [G loss: 0.744067]
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743 [D loss: 0.688482, acc.: 54.30%] [G loss: 0.741981]
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744 [D loss: 0.692619, acc.: 49.61%] [G loss: 0.739101]
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745 [D loss: 0.688009, acc.: 53.91%] [G loss: 0.741638]
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746 [D loss: 0.691510, acc.: 50.20%] [G loss: 0.745077]
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747 [D loss: 0.691680, acc.: 51.17%] [G loss: 0.743134]
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748 [D loss: 0.692924, acc.: 49.61%] [G loss: 0.748010]
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749 [D loss: 0.695278, acc.: 50.98%] [G loss: 0.749228]
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750 [D loss: 0.692224, acc.: 52.54%] [G loss: 0.745720]
1/1 [==============================] - 0s 15ms/step
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751 [D loss: 0.689884, acc.: 51.17%] [G loss: 0.747784]
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752 [D loss: 0.690425, acc.: 52.15%] [G loss: 0.742266]
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753 [D loss: 0.691097, acc.: 49.80%] [G loss: 0.752860]
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754 [D loss: 0.691115, acc.: 52.15%] [G loss: 0.755161]
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755 [D loss: 0.688684, acc.: 52.34%] [G loss: 0.761148]
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756 [D loss: 0.691386, acc.: 53.91%] [G loss: 0.753907]
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757 [D loss: 0.690689, acc.: 53.71%] [G loss: 0.750407]
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758 [D loss: 0.692510, acc.: 51.56%] [G loss: 0.754071]
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759 [D loss: 0.686082, acc.: 54.88%] [G loss: 0.749213]
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760 [D loss: 0.686527, acc.: 55.08%] [G loss: 0.754937]
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761 [D loss: 0.687280, acc.: 57.23%] [G loss: 0.746086]
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762 [D loss: 0.690043, acc.: 50.78%] [G loss: 0.748115]
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763 [D loss: 0.690774, acc.: 52.15%] [G loss: 0.744109]
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764 [D loss: 0.687003, acc.: 54.30%] [G loss: 0.744594]
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765 [D loss: 0.688087, acc.: 55.27%] [G loss: 0.742692]
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766 [D loss: 0.692053, acc.: 50.98%] [G loss: 0.741751]
8/8 [==============================] - 0s 2ms/step
767 [D loss: 0.684490, acc.: 57.03%] [G loss: 0.743403]
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768 [D loss: 0.684136, acc.: 58.59%] [G loss: 0.739873]
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769 [D loss: 0.690799, acc.: 49.61%] [G loss: 0.734717]
8/8 [==============================] - 0s 2ms/step
770 [D loss: 0.688259, acc.: 53.52%] [G loss: 0.735911]
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771 [D loss: 0.691715, acc.: 51.37%] [G loss: 0.738438]
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772 [D loss: 0.692675, acc.: 49.61%] [G loss: 0.739400]
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773 [D loss: 0.692843, acc.: 51.95%] [G loss: 0.739134]
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774 [D loss: 0.693040, acc.: 49.80%] [G loss: 0.732549]
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775 [D loss: 0.691316, acc.: 51.95%] [G loss: 0.740802]
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776 [D loss: 0.687992, acc.: 53.71%] [G loss: 0.738493]
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777 [D loss: 0.689253, acc.: 52.54%] [G loss: 0.738930]
8/8 [==============================] - 0s 2ms/step
778 [D loss: 0.684690, acc.: 55.47%] [G loss: 0.737390]
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779 [D loss: 0.688375, acc.: 53.71%] [G loss: 0.733474]
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780 [D loss: 0.687471, acc.: 53.71%] [G loss: 0.743159]
8/8 [==============================] - 0s 2ms/step
781 [D loss: 0.688670, acc.: 51.95%] [G loss: 0.739852]
8/8 [==============================] - 0s 2ms/step
782 [D loss: 0.689570, acc.: 52.54%] [G loss: 0.736168]
8/8 [==============================] - 0s 2ms/step
783 [D loss: 0.684368, acc.: 57.62%] [G loss: 0.737661]
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784 [D loss: 0.687431, acc.: 52.93%] [G loss: 0.735836]
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785 [D loss: 0.682468, acc.: 55.08%] [G loss: 0.737423]
8/8 [==============================] - 0s 2ms/step
786 [D loss: 0.682932, acc.: 54.69%] [G loss: 0.740049]
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787 [D loss: 0.685655, acc.: 54.30%] [G loss: 0.743754]
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788 [D loss: 0.687346, acc.: 54.10%] [G loss: 0.746774]
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789 [D loss: 0.686167, acc.: 53.52%] [G loss: 0.737212]
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790 [D loss: 0.694662, acc.: 48.24%] [G loss: 0.748325]
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791 [D loss: 0.686879, acc.: 52.15%] [G loss: 0.741186]
8/8 [==============================] - 0s 2ms/step
792 [D loss: 0.688488, acc.: 51.17%] [G loss: 0.742150]
8/8 [==============================] - 0s 2ms/step
793 [D loss: 0.689875, acc.: 50.20%] [G loss: 0.740817]
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794 [D loss: 0.693578, acc.: 52.34%] [G loss: 0.742242]
8/8 [==============================] - 0s 2ms/step
795 [D loss: 0.688031, acc.: 54.69%] [G loss: 0.742153]
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796 [D loss: 0.687188, acc.: 56.64%] [G loss: 0.746571]
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797 [D loss: 0.688054, acc.: 54.88%] [G loss: 0.743206]
8/8 [==============================] - 0s 2ms/step
798 [D loss: 0.688457, acc.: 52.73%] [G loss: 0.745953]
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799 [D loss: 0.688701, acc.: 53.12%] [G loss: 0.747759]
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800 [D loss: 0.688267, acc.: 56.45%] [G loss: 0.746162]
1/1 [==============================] - 0s 16ms/step
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801 [D loss: 0.687195, acc.: 55.08%] [G loss: 0.737988]
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802 [D loss: 0.688833, acc.: 51.56%] [G loss: 0.750088]
8/8 [==============================] - 0s 2ms/step
803 [D loss: 0.683926, acc.: 55.08%] [G loss: 0.746015]
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804 [D loss: 0.682932, acc.: 58.20%] [G loss: 0.745667]
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805 [D loss: 0.682155, acc.: 57.23%] [G loss: 0.748325]
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806 [D loss: 0.686439, acc.: 52.93%] [G loss: 0.748556]
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807 [D loss: 0.686668, acc.: 52.54%] [G loss: 0.752604]
8/8 [==============================] - 0s 2ms/step
808 [D loss: 0.686413, acc.: 53.12%] [G loss: 0.746713]
8/8 [==============================] - 0s 2ms/step
809 [D loss: 0.684909, acc.: 54.88%] [G loss: 0.745819]
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810 [D loss: 0.686572, acc.: 55.08%] [G loss: 0.742862]
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811 [D loss: 0.683539, acc.: 54.49%] [G loss: 0.740327]
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812 [D loss: 0.683362, acc.: 58.01%] [G loss: 0.736784]
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813 [D loss: 0.683596, acc.: 56.25%] [G loss: 0.736270]
8/8 [==============================] - 0s 2ms/step
814 [D loss: 0.690480, acc.: 53.32%] [G loss: 0.730891]
8/8 [==============================] - 0s 2ms/step
815 [D loss: 0.684731, acc.: 58.01%] [G loss: 0.729165]
8/8 [==============================] - 0s 2ms/step
816 [D loss: 0.686815, acc.: 52.93%] [G loss: 0.733785]
8/8 [==============================] - 0s 2ms/step
817 [D loss: 0.685440, acc.: 57.23%] [G loss: 0.737753]
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818 [D loss: 0.687925, acc.: 53.91%] [G loss: 0.733331]
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819 [D loss: 0.687700, acc.: 53.91%] [G loss: 0.736576]
8/8 [==============================] - 0s 2ms/step
820 [D loss: 0.686082, acc.: 57.62%] [G loss: 0.733429]
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821 [D loss: 0.683466, acc.: 56.64%] [G loss: 0.730285]
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822 [D loss: 0.686253, acc.: 57.03%] [G loss: 0.726818]
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823 [D loss: 0.685561, acc.: 56.25%] [G loss: 0.729092]
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824 [D loss: 0.687464, acc.: 53.32%] [G loss: 0.730855]
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825 [D loss: 0.683949, acc.: 55.47%] [G loss: 0.730848]
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826 [D loss: 0.685481, acc.: 54.69%] [G loss: 0.738903]
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827 [D loss: 0.691440, acc.: 53.52%] [G loss: 0.739704]
8/8 [==============================] - 0s 2ms/step
828 [D loss: 0.686272, acc.: 56.84%] [G loss: 0.730222]
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829 [D loss: 0.686221, acc.: 54.30%] [G loss: 0.730623]
8/8 [==============================] - 0s 2ms/step
830 [D loss: 0.688262, acc.: 54.49%] [G loss: 0.737276]
8/8 [==============================] - 0s 2ms/step
831 [D loss: 0.687149, acc.: 56.05%] [G loss: 0.738361]
8/8 [==============================] - 0s 2ms/step
832 [D loss: 0.691113, acc.: 52.93%] [G loss: 0.733950]
8/8 [==============================] - 0s 2ms/step
833 [D loss: 0.686207, acc.: 57.23%] [G loss: 0.733963]
8/8 [==============================] - 0s 3ms/step
834 [D loss: 0.690890, acc.: 52.15%] [G loss: 0.741986]
8/8 [==============================] - 0s 2ms/step
835 [D loss: 0.689886, acc.: 53.12%] [G loss: 0.733644]
8/8 [==============================] - 0s 2ms/step
836 [D loss: 0.690131, acc.: 54.30%] [G loss: 0.736465]
8/8 [==============================] - 0s 2ms/step
837 [D loss: 0.689418, acc.: 52.34%] [G loss: 0.739198]
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838 [D loss: 0.683187, acc.: 58.40%] [G loss: 0.745534]
8/8 [==============================] - 0s 2ms/step
839 [D loss: 0.689109, acc.: 53.52%] [G loss: 0.735066]
8/8 [==============================] - 0s 2ms/step
840 [D loss: 0.688342, acc.: 52.73%] [G loss: 0.747701]
8/8 [==============================] - 0s 2ms/step
841 [D loss: 0.686346, acc.: 56.25%] [G loss: 0.739078]
8/8 [==============================] - 0s 2ms/step
842 [D loss: 0.686210, acc.: 53.52%] [G loss: 0.745651]
8/8 [==============================] - 0s 2ms/step
843 [D loss: 0.684328, acc.: 56.05%] [G loss: 0.745545]
8/8 [==============================] - 0s 2ms/step
844 [D loss: 0.685029, acc.: 54.88%] [G loss: 0.747199]
8/8 [==============================] - 0s 2ms/step
845 [D loss: 0.683231, acc.: 58.59%] [G loss: 0.748490]
8/8 [==============================] - 0s 2ms/step
846 [D loss: 0.690126, acc.: 53.12%] [G loss: 0.751745]
8/8 [==============================] - 0s 2ms/step
847 [D loss: 0.680415, acc.: 61.33%] [G loss: 0.747696]
8/8 [==============================] - 0s 2ms/step
848 [D loss: 0.683042, acc.: 59.77%] [G loss: 0.750801]
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849 [D loss: 0.679244, acc.: 58.40%] [G loss: 0.754511]
8/8 [==============================] - 0s 2ms/step
850 [D loss: 0.683903, acc.: 57.62%] [G loss: 0.759008]
1/1 [==============================] - 0s 15ms/step
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851 [D loss: 0.683482, acc.: 57.62%] [G loss: 0.747085]
8/8 [==============================] - 0s 2ms/step
852 [D loss: 0.684835, acc.: 58.01%] [G loss: 0.751734]
8/8 [==============================] - 0s 2ms/step
853 [D loss: 0.683149, acc.: 58.40%] [G loss: 0.746718]
8/8 [==============================] - 0s 2ms/step
854 [D loss: 0.686353, acc.: 52.34%] [G loss: 0.748335]
8/8 [==============================] - 0s 2ms/step
855 [D loss: 0.695942, acc.: 49.80%] [G loss: 0.740141]
8/8 [==============================] - 0s 2ms/step
856 [D loss: 0.683729, acc.: 56.45%] [G loss: 0.746771]
8/8 [==============================] - 0s 2ms/step
857 [D loss: 0.688957, acc.: 52.54%] [G loss: 0.749540]
8/8 [==============================] - 0s 2ms/step
858 [D loss: 0.689507, acc.: 52.15%] [G loss: 0.754976]
8/8 [==============================] - 0s 2ms/step
859 [D loss: 0.690385, acc.: 53.32%] [G loss: 0.750514]
8/8 [==============================] - 0s 2ms/step
860 [D loss: 0.686881, acc.: 55.27%] [G loss: 0.749133]
8/8 [==============================] - 0s 2ms/step
861 [D loss: 0.685385, acc.: 55.27%] [G loss: 0.750169]
8/8 [==============================] - 0s 3ms/step
862 [D loss: 0.691821, acc.: 51.76%] [G loss: 0.747896]
8/8 [==============================] - 0s 2ms/step
863 [D loss: 0.687515, acc.: 54.49%] [G loss: 0.749193]
8/8 [==============================] - 0s 2ms/step
864 [D loss: 0.689056, acc.: 54.49%] [G loss: 0.742154]
8/8 [==============================] - 0s 2ms/step
865 [D loss: 0.688531, acc.: 55.08%] [G loss: 0.740370]
8/8 [==============================] - 0s 2ms/step
866 [D loss: 0.688645, acc.: 53.52%] [G loss: 0.741218]
8/8 [==============================] - 0s 2ms/step
867 [D loss: 0.682873, acc.: 61.13%] [G loss: 0.741813]
8/8 [==============================] - 0s 2ms/step
868 [D loss: 0.685333, acc.: 59.18%] [G loss: 0.733406]
8/8 [==============================] - 0s 2ms/step
869 [D loss: 0.690543, acc.: 54.69%] [G loss: 0.736314]
8/8 [==============================] - 0s 2ms/step
870 [D loss: 0.685683, acc.: 53.71%] [G loss: 0.740611]
8/8 [==============================] - 0s 2ms/step
871 [D loss: 0.685758, acc.: 56.45%] [G loss: 0.736684]
8/8 [==============================] - 0s 2ms/step
872 [D loss: 0.685047, acc.: 57.42%] [G loss: 0.736515]
8/8 [==============================] - 0s 2ms/step
873 [D loss: 0.691363, acc.: 51.56%] [G loss: 0.738812]
8/8 [==============================] - 0s 2ms/step
874 [D loss: 0.689009, acc.: 51.95%] [G loss: 0.744400]
8/8 [==============================] - 0s 2ms/step
875 [D loss: 0.688060, acc.: 54.69%] [G loss: 0.741189]
8/8 [==============================] - 0s 2ms/step
876 [D loss: 0.685779, acc.: 55.47%] [G loss: 0.733733]
8/8 [==============================] - 0s 2ms/step
877 [D loss: 0.686684, acc.: 54.69%] [G loss: 0.738511]
8/8 [==============================] - 0s 2ms/step
878 [D loss: 0.687034, acc.: 54.49%] [G loss: 0.745543]
8/8 [==============================] - 0s 2ms/step
879 [D loss: 0.683101, acc.: 56.05%] [G loss: 0.754967]
8/8 [==============================] - 0s 2ms/step
880 [D loss: 0.683467, acc.: 57.81%] [G loss: 0.740031]
8/8 [==============================] - 0s 2ms/step
881 [D loss: 0.690219, acc.: 52.73%] [G loss: 0.739746]
8/8 [==============================] - 0s 2ms/step
882 [D loss: 0.683954, acc.: 56.45%] [G loss: 0.748757]
8/8 [==============================] - 0s 2ms/step
883 [D loss: 0.681400, acc.: 56.64%] [G loss: 0.747508]
8/8 [==============================] - 0s 2ms/step
884 [D loss: 0.685644, acc.: 58.01%] [G loss: 0.747441]
8/8 [==============================] - 0s 2ms/step
885 [D loss: 0.681402, acc.: 56.45%] [G loss: 0.745997]
8/8 [==============================] - 0s 2ms/step
886 [D loss: 0.680716, acc.: 60.35%] [G loss: 0.740964]
8/8 [==============================] - 0s 2ms/step
887 [D loss: 0.686744, acc.: 54.69%] [G loss: 0.747754]
8/8 [==============================] - 0s 2ms/step
888 [D loss: 0.678508, acc.: 58.40%] [G loss: 0.747708]
8/8 [==============================] - 0s 2ms/step
889 [D loss: 0.683282, acc.: 55.27%] [G loss: 0.753096]
8/8 [==============================] - 0s 2ms/step
890 [D loss: 0.685173, acc.: 56.64%] [G loss: 0.748590]
8/8 [==============================] - 0s 2ms/step
891 [D loss: 0.685437, acc.: 55.08%] [G loss: 0.748584]
8/8 [==============================] - 0s 2ms/step
892 [D loss: 0.685707, acc.: 55.08%] [G loss: 0.744472]
8/8 [==============================] - 0s 2ms/step
893 [D loss: 0.684245, acc.: 57.42%] [G loss: 0.754566]
8/8 [==============================] - 0s 2ms/step
894 [D loss: 0.684552, acc.: 55.86%] [G loss: 0.742870]
8/8 [==============================] - 0s 2ms/step
895 [D loss: 0.685063, acc.: 53.32%] [G loss: 0.747096]
8/8 [==============================] - 0s 2ms/step
896 [D loss: 0.679664, acc.: 57.42%] [G loss: 0.749159]
8/8 [==============================] - 0s 2ms/step
897 [D loss: 0.686126, acc.: 56.25%] [G loss: 0.752753]
8/8 [==============================] - 0s 2ms/step
898 [D loss: 0.690711, acc.: 53.32%] [G loss: 0.734136]
8/8 [==============================] - 0s 2ms/step
899 [D loss: 0.689166, acc.: 53.12%] [G loss: 0.743212]
8/8 [==============================] - 0s 2ms/step
900 [D loss: 0.686800, acc.: 54.88%] [G loss: 0.742051]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
901 [D loss: 0.691802, acc.: 51.37%] [G loss: 0.739858]
8/8 [==============================] - 0s 2ms/step
902 [D loss: 0.692552, acc.: 50.59%] [G loss: 0.739850]
8/8 [==============================] - 0s 2ms/step
903 [D loss: 0.691086, acc.: 50.78%] [G loss: 0.731653]
8/8 [==============================] - 0s 2ms/step
904 [D loss: 0.690963, acc.: 54.88%] [G loss: 0.735206]
8/8 [==============================] - 0s 2ms/step
905 [D loss: 0.685061, acc.: 57.03%] [G loss: 0.735070]
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906 [D loss: 0.687371, acc.: 53.12%] [G loss: 0.739005]
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907 [D loss: 0.683698, acc.: 56.25%] [G loss: 0.727889]
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908 [D loss: 0.682452, acc.: 58.20%] [G loss: 0.728833]
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909 [D loss: 0.693199, acc.: 49.02%] [G loss: 0.725726]
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910 [D loss: 0.690484, acc.: 50.20%] [G loss: 0.724850]
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911 [D loss: 0.692271, acc.: 50.00%] [G loss: 0.728221]
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912 [D loss: 0.693048, acc.: 50.59%] [G loss: 0.733670]
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913 [D loss: 0.685263, acc.: 55.47%] [G loss: 0.735789]
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914 [D loss: 0.685528, acc.: 54.69%] [G loss: 0.733900]
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915 [D loss: 0.683208, acc.: 52.93%] [G loss: 0.739228]
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916 [D loss: 0.684472, acc.: 54.49%] [G loss: 0.737335]
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917 [D loss: 0.691335, acc.: 49.22%] [G loss: 0.739896]
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918 [D loss: 0.692117, acc.: 51.95%] [G loss: 0.731427]
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919 [D loss: 0.686524, acc.: 55.86%] [G loss: 0.732493]
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920 [D loss: 0.686358, acc.: 51.17%] [G loss: 0.734037]
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921 [D loss: 0.683905, acc.: 55.86%] [G loss: 0.740163]
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922 [D loss: 0.685917, acc.: 51.76%] [G loss: 0.740266]
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923 [D loss: 0.677956, acc.: 59.96%] [G loss: 0.732065]
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924 [D loss: 0.684469, acc.: 56.64%] [G loss: 0.739394]
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925 [D loss: 0.686307, acc.: 55.86%] [G loss: 0.748415]
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926 [D loss: 0.681335, acc.: 59.77%] [G loss: 0.745946]
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927 [D loss: 0.687447, acc.: 53.32%] [G loss: 0.738097]
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928 [D loss: 0.681783, acc.: 57.81%] [G loss: 0.749277]
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929 [D loss: 0.679068, acc.: 59.96%] [G loss: 0.739407]
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930 [D loss: 0.673176, acc.: 62.30%] [G loss: 0.744740]
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931 [D loss: 0.683463, acc.: 54.88%] [G loss: 0.740197]
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932 [D loss: 0.684491, acc.: 55.86%] [G loss: 0.727789]
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933 [D loss: 0.691385, acc.: 51.95%] [G loss: 0.722226]
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934 [D loss: 0.689091, acc.: 52.93%] [G loss: 0.730757]
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935 [D loss: 0.691254, acc.: 50.20%] [G loss: 0.729716]
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936 [D loss: 0.684955, acc.: 53.71%] [G loss: 0.727015]
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937 [D loss: 0.688975, acc.: 53.52%] [G loss: 0.730894]
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938 [D loss: 0.685685, acc.: 52.54%] [G loss: 0.736282]
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939 [D loss: 0.688944, acc.: 55.08%] [G loss: 0.739163]
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940 [D loss: 0.692928, acc.: 49.02%] [G loss: 0.739448]
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941 [D loss: 0.695271, acc.: 51.17%] [G loss: 0.738260]
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942 [D loss: 0.688650, acc.: 53.71%] [G loss: 0.740614]
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943 [D loss: 0.685655, acc.: 55.86%] [G loss: 0.751401]
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944 [D loss: 0.682342, acc.: 56.64%] [G loss: 0.751386]
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945 [D loss: 0.686768, acc.: 54.30%] [G loss: 0.744666]
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946 [D loss: 0.683015, acc.: 57.23%] [G loss: 0.745570]
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947 [D loss: 0.684406, acc.: 57.81%] [G loss: 0.744806]
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948 [D loss: 0.682474, acc.: 57.42%] [G loss: 0.744553]
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949 [D loss: 0.688594, acc.: 53.91%] [G loss: 0.735706]
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950 [D loss: 0.682214, acc.: 56.45%] [G loss: 0.738147]
1/1 [==============================] - 0s 15ms/step
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951 [D loss: 0.683789, acc.: 55.66%] [G loss: 0.742146]
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952 [D loss: 0.688684, acc.: 55.08%] [G loss: 0.742835]
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953 [D loss: 0.688810, acc.: 55.08%] [G loss: 0.740716]
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954 [D loss: 0.683391, acc.: 54.49%] [G loss: 0.746644]
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955 [D loss: 0.690958, acc.: 52.54%] [G loss: 0.744618]
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956 [D loss: 0.687274, acc.: 54.88%] [G loss: 0.733268]
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957 [D loss: 0.688637, acc.: 53.32%] [G loss: 0.736409]
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958 [D loss: 0.689186, acc.: 50.98%] [G loss: 0.743620]
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959 [D loss: 0.688788, acc.: 55.86%] [G loss: 0.744796]
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960 [D loss: 0.691027, acc.: 52.34%] [G loss: 0.725932]
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961 [D loss: 0.688596, acc.: 56.84%] [G loss: 0.723592]
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962 [D loss: 0.682787, acc.: 58.01%] [G loss: 0.724865]
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963 [D loss: 0.688206, acc.: 54.88%] [G loss: 0.720878]
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964 [D loss: 0.694376, acc.: 51.76%] [G loss: 0.724239]
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965 [D loss: 0.687055, acc.: 56.25%] [G loss: 0.722768]
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966 [D loss: 0.688378, acc.: 53.32%] [G loss: 0.725888]
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967 [D loss: 0.687786, acc.: 53.71%] [G loss: 0.732362]
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968 [D loss: 0.684139, acc.: 56.64%] [G loss: 0.723502]
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969 [D loss: 0.687378, acc.: 56.05%] [G loss: 0.723674]
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970 [D loss: 0.681451, acc.: 58.20%] [G loss: 0.720489]
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971 [D loss: 0.683862, acc.: 55.47%] [G loss: 0.720321]
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972 [D loss: 0.686587, acc.: 54.30%] [G loss: 0.713675]
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973 [D loss: 0.691229, acc.: 53.71%] [G loss: 0.728700]
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974 [D loss: 0.689138, acc.: 55.27%] [G loss: 0.718926]
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975 [D loss: 0.679840, acc.: 56.84%] [G loss: 0.724448]
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976 [D loss: 0.680605, acc.: 58.01%] [G loss: 0.714149]
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977 [D loss: 0.683697, acc.: 56.45%] [G loss: 0.718087]
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978 [D loss: 0.684970, acc.: 55.08%] [G loss: 0.715957]
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979 [D loss: 0.683397, acc.: 61.13%] [G loss: 0.727421]
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980 [D loss: 0.682985, acc.: 56.84%] [G loss: 0.718368]
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981 [D loss: 0.685121, acc.: 54.88%] [G loss: 0.716090]
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982 [D loss: 0.682712, acc.: 55.08%] [G loss: 0.722334]
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983 [D loss: 0.682448, acc.: 52.54%] [G loss: 0.721138]
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984 [D loss: 0.687547, acc.: 54.88%] [G loss: 0.717278]
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985 [D loss: 0.690296, acc.: 53.52%] [G loss: 0.721983]
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986 [D loss: 0.683600, acc.: 58.20%] [G loss: 0.736675]
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987 [D loss: 0.683095, acc.: 56.64%] [G loss: 0.736191]
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988 [D loss: 0.683528, acc.: 55.47%] [G loss: 0.733376]
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989 [D loss: 0.686097, acc.: 57.03%] [G loss: 0.740246]
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990 [D loss: 0.680189, acc.: 57.23%] [G loss: 0.730517]
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991 [D loss: 0.679994, acc.: 57.81%] [G loss: 0.730655]
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992 [D loss: 0.685155, acc.: 56.84%] [G loss: 0.727509]
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993 [D loss: 0.691127, acc.: 53.52%] [G loss: 0.737427]
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994 [D loss: 0.687696, acc.: 54.69%] [G loss: 0.721961]
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995 [D loss: 0.683194, acc.: 57.03%] [G loss: 0.723266]
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996 [D loss: 0.690270, acc.: 51.56%] [G loss: 0.727078]
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997 [D loss: 0.684491, acc.: 53.12%] [G loss: 0.728981]
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998 [D loss: 0.689568, acc.: 54.30%] [G loss: 0.724435]
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999 [D loss: 0.690954, acc.: 54.30%] [G loss: 0.720902]
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1000 [D loss: 0.691058, acc.: 52.34%] [G loss: 0.727782]
1/1 [==============================] - 0s 16ms/step
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1001 [D loss: 0.688640, acc.: 53.71%] [G loss: 0.726561]
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1002 [D loss: 0.692936, acc.: 54.10%] [G loss: 0.727342]
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1003 [D loss: 0.686458, acc.: 54.88%] [G loss: 0.736855]
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1004 [D loss: 0.691940, acc.: 52.93%] [G loss: 0.735009]
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1005 [D loss: 0.692232, acc.: 51.76%] [G loss: 0.729929]
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1006 [D loss: 0.685167, acc.: 55.08%] [G loss: 0.730730]
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1007 [D loss: 0.681759, acc.: 57.03%] [G loss: 0.743501]
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1008 [D loss: 0.687047, acc.: 55.27%] [G loss: 0.732298]
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1009 [D loss: 0.688456, acc.: 52.73%] [G loss: 0.737105]
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1010 [D loss: 0.686307, acc.: 54.10%] [G loss: 0.737758]
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1011 [D loss: 0.688339, acc.: 53.32%] [G loss: 0.741871]
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1012 [D loss: 0.686243, acc.: 53.52%] [G loss: 0.737583]
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1013 [D loss: 0.687316, acc.: 53.52%] [G loss: 0.745613]
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1014 [D loss: 0.681902, acc.: 55.86%] [G loss: 0.742483]
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1015 [D loss: 0.687514, acc.: 58.40%] [G loss: 0.731261]
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1016 [D loss: 0.680245, acc.: 59.77%] [G loss: 0.740972]
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1017 [D loss: 0.683218, acc.: 57.62%] [G loss: 0.746038]
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1018 [D loss: 0.674427, acc.: 59.18%] [G loss: 0.742211]
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1019 [D loss: 0.682730, acc.: 58.40%] [G loss: 0.735560]
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1020 [D loss: 0.685166, acc.: 55.47%] [G loss: 0.743329]
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1021 [D loss: 0.684787, acc.: 56.64%] [G loss: 0.744335]
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1022 [D loss: 0.686739, acc.: 54.30%] [G loss: 0.737200]
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1023 [D loss: 0.685837, acc.: 56.84%] [G loss: 0.738508]
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1024 [D loss: 0.683910, acc.: 55.66%] [G loss: 0.746674]
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1025 [D loss: 0.682686, acc.: 55.27%] [G loss: 0.741314]
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1026 [D loss: 0.686224, acc.: 54.30%] [G loss: 0.738061]
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1027 [D loss: 0.683407, acc.: 56.84%] [G loss: 0.737911]
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1028 [D loss: 0.686249, acc.: 56.25%] [G loss: 0.718399]
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1029 [D loss: 0.687756, acc.: 55.86%] [G loss: 0.734846]
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1030 [D loss: 0.687646, acc.: 52.93%] [G loss: 0.726574]
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1031 [D loss: 0.680494, acc.: 55.86%] [G loss: 0.734861]
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1032 [D loss: 0.682551, acc.: 58.79%] [G loss: 0.737620]
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1033 [D loss: 0.685065, acc.: 55.86%] [G loss: 0.736508]
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1034 [D loss: 0.679615, acc.: 60.35%] [G loss: 0.744953]
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1035 [D loss: 0.684557, acc.: 57.62%] [G loss: 0.738389]
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1036 [D loss: 0.680546, acc.: 57.42%] [G loss: 0.738227]
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1037 [D loss: 0.684169, acc.: 58.59%] [G loss: 0.733539]
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1038 [D loss: 0.678662, acc.: 59.18%] [G loss: 0.719493]
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1039 [D loss: 0.688595, acc.: 51.76%] [G loss: 0.713077]
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1040 [D loss: 0.686236, acc.: 54.88%] [G loss: 0.709058]
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1041 [D loss: 0.686202, acc.: 53.52%] [G loss: 0.699777]
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1042 [D loss: 0.685302, acc.: 55.86%] [G loss: 0.719758]
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1043 [D loss: 0.687471, acc.: 52.73%] [G loss: 0.706230]
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1044 [D loss: 0.691895, acc.: 51.17%] [G loss: 0.719497]
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1045 [D loss: 0.679460, acc.: 57.42%] [G loss: 0.722977]
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1046 [D loss: 0.681249, acc.: 57.62%] [G loss: 0.709880]
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1047 [D loss: 0.679437, acc.: 57.81%] [G loss: 0.719955]
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1048 [D loss: 0.689802, acc.: 53.12%] [G loss: 0.721533]
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1049 [D loss: 0.685147, acc.: 53.71%] [G loss: 0.713399]
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1050 [D loss: 0.688008, acc.: 52.34%] [G loss: 0.711663]
1/1 [==============================] - 0s 15ms/step
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1051 [D loss: 0.688208, acc.: 54.49%] [G loss: 0.714976]
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1052 [D loss: 0.688803, acc.: 53.12%] [G loss: 0.707726]
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1053 [D loss: 0.688535, acc.: 51.56%] [G loss: 0.708535]
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1054 [D loss: 0.685773, acc.: 57.42%] [G loss: 0.720695]
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1055 [D loss: 0.689265, acc.: 52.93%] [G loss: 0.717419]
8/8 [==============================] - 0s 2ms/step
1056 [D loss: 0.693652, acc.: 51.95%] [G loss: 0.717970]
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1057 [D loss: 0.690863, acc.: 51.76%] [G loss: 0.720084]
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1058 [D loss: 0.686177, acc.: 55.27%] [G loss: 0.722007]
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1059 [D loss: 0.680205, acc.: 53.91%] [G loss: 0.718181]
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1060 [D loss: 0.692665, acc.: 50.59%] [G loss: 0.719300]
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1061 [D loss: 0.693578, acc.: 50.98%] [G loss: 0.718119]
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1062 [D loss: 0.690497, acc.: 51.56%] [G loss: 0.724508]
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1063 [D loss: 0.696517, acc.: 51.56%] [G loss: 0.733735]
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1064 [D loss: 0.693962, acc.: 49.80%] [G loss: 0.725269]
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1065 [D loss: 0.688396, acc.: 54.49%] [G loss: 0.726591]
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1066 [D loss: 0.692645, acc.: 52.93%] [G loss: 0.722790]
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1067 [D loss: 0.693200, acc.: 53.12%] [G loss: 0.723330]
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1068 [D loss: 0.689560, acc.: 53.71%] [G loss: 0.725498]
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1069 [D loss: 0.687511, acc.: 55.27%] [G loss: 0.737651]
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1070 [D loss: 0.692956, acc.: 53.52%] [G loss: 0.744150]
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1071 [D loss: 0.688909, acc.: 55.47%] [G loss: 0.745751]
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1072 [D loss: 0.686174, acc.: 54.30%] [G loss: 0.747671]
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1073 [D loss: 0.683472, acc.: 56.05%] [G loss: 0.758249]
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1074 [D loss: 0.680832, acc.: 58.79%] [G loss: 0.753763]
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1075 [D loss: 0.679361, acc.: 59.77%] [G loss: 0.757021]
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1076 [D loss: 0.689858, acc.: 54.30%] [G loss: 0.762321]
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1077 [D loss: 0.689387, acc.: 54.49%] [G loss: 0.753106]
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1078 [D loss: 0.681890, acc.: 56.25%] [G loss: 0.748683]
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1079 [D loss: 0.680582, acc.: 58.79%] [G loss: 0.753944]
8/8 [==============================] - 0s 2ms/step
1080 [D loss: 0.683949, acc.: 57.23%] [G loss: 0.751467]
8/8 [==============================] - 0s 2ms/step
1081 [D loss: 0.681042, acc.: 56.64%] [G loss: 0.745878]
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1082 [D loss: 0.684560, acc.: 58.79%] [G loss: 0.744571]
8/8 [==============================] - 0s 2ms/step
1083 [D loss: 0.688535, acc.: 53.71%] [G loss: 0.738363]
8/8 [==============================] - 0s 2ms/step
1084 [D loss: 0.694057, acc.: 51.37%] [G loss: 0.734644]
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1085 [D loss: 0.689742, acc.: 55.86%] [G loss: 0.749348]
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1086 [D loss: 0.685000, acc.: 54.49%] [G loss: 0.740990]
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1087 [D loss: 0.690789, acc.: 54.10%] [G loss: 0.738068]
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1088 [D loss: 0.696194, acc.: 55.86%] [G loss: 0.740545]
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1089 [D loss: 0.700828, acc.: 50.78%] [G loss: 0.746411]
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1090 [D loss: 0.683612, acc.: 57.81%] [G loss: 0.743598]
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1091 [D loss: 0.689987, acc.: 53.32%] [G loss: 0.736210]
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1092 [D loss: 0.685721, acc.: 55.86%] [G loss: 0.730824]
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1093 [D loss: 0.691937, acc.: 52.34%] [G loss: 0.733308]
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1094 [D loss: 0.689257, acc.: 52.54%] [G loss: 0.733070]
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1095 [D loss: 0.691854, acc.: 54.69%] [G loss: 0.733029]
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1096 [D loss: 0.688969, acc.: 51.37%] [G loss: 0.739215]
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1097 [D loss: 0.691273, acc.: 50.20%] [G loss: 0.739704]
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1098 [D loss: 0.687679, acc.: 55.47%] [G loss: 0.740803]
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1099 [D loss: 0.688958, acc.: 53.32%] [G loss: 0.735496]
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1100 [D loss: 0.690769, acc.: 53.12%] [G loss: 0.731560]
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1101 [D loss: 0.691001, acc.: 52.93%] [G loss: 0.733159]
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1102 [D loss: 0.693100, acc.: 51.76%] [G loss: 0.738503]
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1103 [D loss: 0.685241, acc.: 56.45%] [G loss: 0.733380]
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1104 [D loss: 0.685575, acc.: 51.95%] [G loss: 0.722765]
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1105 [D loss: 0.680769, acc.: 59.38%] [G loss: 0.718083]
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1106 [D loss: 0.678284, acc.: 58.20%] [G loss: 0.714642]
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1107 [D loss: 0.683805, acc.: 55.08%] [G loss: 0.716925]
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1108 [D loss: 0.679497, acc.: 60.35%] [G loss: 0.709408]
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1109 [D loss: 0.685635, acc.: 54.10%] [G loss: 0.716604]
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1110 [D loss: 0.689718, acc.: 56.45%] [G loss: 0.718944]
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1111 [D loss: 0.685138, acc.: 53.91%] [G loss: 0.723433]
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1112 [D loss: 0.682974, acc.: 55.08%] [G loss: 0.714694]
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1113 [D loss: 0.689550, acc.: 56.25%] [G loss: 0.724418]
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1114 [D loss: 0.682160, acc.: 56.45%] [G loss: 0.724977]
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1115 [D loss: 0.688022, acc.: 56.05%] [G loss: 0.721125]
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1116 [D loss: 0.682448, acc.: 56.25%] [G loss: 0.714021]
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1117 [D loss: 0.686174, acc.: 54.30%] [G loss: 0.719234]
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1118 [D loss: 0.681457, acc.: 57.03%] [G loss: 0.720085]
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1119 [D loss: 0.691406, acc.: 52.34%] [G loss: 0.719310]
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1120 [D loss: 0.692428, acc.: 54.30%] [G loss: 0.729161]
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1121 [D loss: 0.686257, acc.: 56.05%] [G loss: 0.725329]
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1122 [D loss: 0.688418, acc.: 55.47%] [G loss: 0.728410]
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1123 [D loss: 0.689751, acc.: 51.37%] [G loss: 0.740708]
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1124 [D loss: 0.690913, acc.: 51.95%] [G loss: 0.728832]
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1125 [D loss: 0.689641, acc.: 54.88%] [G loss: 0.729709]
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1126 [D loss: 0.685210, acc.: 56.84%] [G loss: 0.733425]
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1127 [D loss: 0.692497, acc.: 52.34%] [G loss: 0.732688]
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1128 [D loss: 0.685821, acc.: 54.10%] [G loss: 0.729475]
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1129 [D loss: 0.690477, acc.: 53.71%] [G loss: 0.738766]
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1130 [D loss: 0.685881, acc.: 57.42%] [G loss: 0.735012]
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1131 [D loss: 0.689407, acc.: 53.12%] [G loss: 0.731968]
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1132 [D loss: 0.693052, acc.: 51.76%] [G loss: 0.732942]
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1133 [D loss: 0.694818, acc.: 51.37%] [G loss: 0.737550]
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1134 [D loss: 0.686231, acc.: 54.88%] [G loss: 0.736870]
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1135 [D loss: 0.683431, acc.: 55.08%] [G loss: 0.734810]
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1136 [D loss: 0.688668, acc.: 51.37%] [G loss: 0.733025]
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1137 [D loss: 0.689478, acc.: 53.12%] [G loss: 0.731373]
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1138 [D loss: 0.688031, acc.: 49.80%] [G loss: 0.728749]
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1139 [D loss: 0.686850, acc.: 51.76%] [G loss: 0.736342]
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1140 [D loss: 0.690584, acc.: 53.91%] [G loss: 0.739191]
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1141 [D loss: 0.685772, acc.: 55.86%] [G loss: 0.736245]
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1142 [D loss: 0.682945, acc.: 56.64%] [G loss: 0.739418]
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1143 [D loss: 0.692545, acc.: 52.34%] [G loss: 0.735969]
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1144 [D loss: 0.682766, acc.: 55.86%] [G loss: 0.732801]
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1145 [D loss: 0.680328, acc.: 59.77%] [G loss: 0.732843]
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1146 [D loss: 0.690354, acc.: 52.54%] [G loss: 0.729301]
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1147 [D loss: 0.694832, acc.: 51.17%] [G loss: 0.730902]
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1148 [D loss: 0.684919, acc.: 55.08%] [G loss: 0.732359]
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1149 [D loss: 0.690268, acc.: 53.71%] [G loss: 0.727028]
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1150 [D loss: 0.681869, acc.: 57.42%] [G loss: 0.729015]
1/1 [==============================] - 0s 15ms/step
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1151 [D loss: 0.683758, acc.: 54.49%] [G loss: 0.717084]
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1152 [D loss: 0.694222, acc.: 50.00%] [G loss: 0.715114]
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1153 [D loss: 0.691612, acc.: 53.12%] [G loss: 0.724547]
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1154 [D loss: 0.690916, acc.: 53.52%] [G loss: 0.727234]
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1155 [D loss: 0.683889, acc.: 57.23%] [G loss: 0.728949]
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1156 [D loss: 0.691111, acc.: 51.95%] [G loss: 0.722982]
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1157 [D loss: 0.685384, acc.: 54.88%] [G loss: 0.718017]
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1158 [D loss: 0.688373, acc.: 53.91%] [G loss: 0.721052]
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1159 [D loss: 0.691007, acc.: 50.20%] [G loss: 0.734949]
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1160 [D loss: 0.687454, acc.: 54.88%] [G loss: 0.732805]
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1161 [D loss: 0.682024, acc.: 57.62%] [G loss: 0.725923]
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1162 [D loss: 0.690295, acc.: 51.17%] [G loss: 0.720081]
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1163 [D loss: 0.684934, acc.: 55.47%] [G loss: 0.731871]
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1164 [D loss: 0.684566, acc.: 56.64%] [G loss: 0.730671]
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1165 [D loss: 0.690986, acc.: 53.71%] [G loss: 0.734867]
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1166 [D loss: 0.681768, acc.: 59.18%] [G loss: 0.739883]
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1167 [D loss: 0.687533, acc.: 54.88%] [G loss: 0.733715]
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1168 [D loss: 0.688417, acc.: 52.73%] [G loss: 0.744001]
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1169 [D loss: 0.687414, acc.: 53.71%] [G loss: 0.736016]
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1170 [D loss: 0.683617, acc.: 57.42%] [G loss: 0.737238]
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1171 [D loss: 0.691775, acc.: 52.34%] [G loss: 0.743098]
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1172 [D loss: 0.687199, acc.: 51.95%] [G loss: 0.727086]
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1173 [D loss: 0.688873, acc.: 54.69%] [G loss: 0.729372]
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1174 [D loss: 0.693320, acc.: 52.54%] [G loss: 0.725266]
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1175 [D loss: 0.687644, acc.: 55.08%] [G loss: 0.725301]
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1176 [D loss: 0.695209, acc.: 52.15%] [G loss: 0.726583]
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1177 [D loss: 0.685991, acc.: 54.49%] [G loss: 0.729193]
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1178 [D loss: 0.686446, acc.: 53.91%] [G loss: 0.729043]
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1179 [D loss: 0.681039, acc.: 57.03%] [G loss: 0.739772]
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1180 [D loss: 0.693585, acc.: 52.15%] [G loss: 0.732641]
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1181 [D loss: 0.691528, acc.: 52.93%] [G loss: 0.736612]
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1182 [D loss: 0.696791, acc.: 50.98%] [G loss: 0.726766]
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1183 [D loss: 0.689088, acc.: 53.32%] [G loss: 0.730852]
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1184 [D loss: 0.696621, acc.: 49.61%] [G loss: 0.724974]
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1185 [D loss: 0.687257, acc.: 55.08%] [G loss: 0.728086]
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1186 [D loss: 0.693423, acc.: 52.54%] [G loss: 0.733232]
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1187 [D loss: 0.689519, acc.: 51.56%] [G loss: 0.726832]
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1188 [D loss: 0.686608, acc.: 54.10%] [G loss: 0.723764]
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1189 [D loss: 0.683146, acc.: 55.66%] [G loss: 0.729923]
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1190 [D loss: 0.687277, acc.: 52.54%] [G loss: 0.726101]
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1191 [D loss: 0.680027, acc.: 56.84%] [G loss: 0.721773]
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1192 [D loss: 0.687118, acc.: 54.10%] [G loss: 0.720709]
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1193 [D loss: 0.693852, acc.: 53.52%] [G loss: 0.741215]
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1194 [D loss: 0.682802, acc.: 56.25%] [G loss: 0.744068]
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1195 [D loss: 0.689818, acc.: 54.10%] [G loss: 0.730867]
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1196 [D loss: 0.685838, acc.: 53.52%] [G loss: 0.728042]
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1197 [D loss: 0.691701, acc.: 49.80%] [G loss: 0.737948]
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1198 [D loss: 0.693830, acc.: 50.39%] [G loss: 0.727932]
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1199 [D loss: 0.694184, acc.: 50.00%] [G loss: 0.739918]
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1200 [D loss: 0.682285, acc.: 54.10%] [G loss: 0.729114]
1/1 [==============================] - 0s 15ms/step
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1201 [D loss: 0.685643, acc.: 56.64%] [G loss: 0.744999]
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1202 [D loss: 0.686332, acc.: 55.47%] [G loss: 0.735643]
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1203 [D loss: 0.686483, acc.: 53.32%] [G loss: 0.729884]
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1204 [D loss: 0.693929, acc.: 51.76%] [G loss: 0.730665]
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1205 [D loss: 0.692622, acc.: 51.56%] [G loss: 0.740340]
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1206 [D loss: 0.676763, acc.: 58.40%] [G loss: 0.736530]
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1207 [D loss: 0.681099, acc.: 55.66%] [G loss: 0.735204]
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1208 [D loss: 0.683856, acc.: 56.45%] [G loss: 0.735789]
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1209 [D loss: 0.687959, acc.: 55.27%] [G loss: 0.729471]
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1210 [D loss: 0.685318, acc.: 58.59%] [G loss: 0.728923]
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1211 [D loss: 0.690587, acc.: 53.32%] [G loss: 0.731237]
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1212 [D loss: 0.680672, acc.: 56.25%] [G loss: 0.734689]
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1213 [D loss: 0.688551, acc.: 54.10%] [G loss: 0.739336]
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1214 [D loss: 0.685242, acc.: 57.42%] [G loss: 0.737200]
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1215 [D loss: 0.686852, acc.: 52.73%] [G loss: 0.730774]
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1216 [D loss: 0.698852, acc.: 51.17%] [G loss: 0.727348]
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1217 [D loss: 0.693297, acc.: 51.95%] [G loss: 0.727569]
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1218 [D loss: 0.685731, acc.: 56.05%] [G loss: 0.718672]
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1219 [D loss: 0.687042, acc.: 53.12%] [G loss: 0.723432]
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1220 [D loss: 0.687848, acc.: 53.12%] [G loss: 0.716853]
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1221 [D loss: 0.693947, acc.: 53.52%] [G loss: 0.726200]
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1222 [D loss: 0.693696, acc.: 49.61%] [G loss: 0.720767]
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1223 [D loss: 0.684043, acc.: 55.08%] [G loss: 0.734557]
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1224 [D loss: 0.684403, acc.: 55.66%] [G loss: 0.740973]
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1225 [D loss: 0.683733, acc.: 57.23%] [G loss: 0.725234]
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1226 [D loss: 0.681541, acc.: 57.03%] [G loss: 0.736726]
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1227 [D loss: 0.680617, acc.: 58.40%] [G loss: 0.734558]
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1228 [D loss: 0.692408, acc.: 54.69%] [G loss: 0.732318]
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1229 [D loss: 0.684653, acc.: 57.62%] [G loss: 0.733833]
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1230 [D loss: 0.679559, acc.: 58.79%] [G loss: 0.738159]
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1231 [D loss: 0.684175, acc.: 58.79%] [G loss: 0.734502]
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1232 [D loss: 0.682442, acc.: 54.69%] [G loss: 0.744122]
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1233 [D loss: 0.686150, acc.: 56.45%] [G loss: 0.734834]
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1234 [D loss: 0.687805, acc.: 55.27%] [G loss: 0.727373]
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1235 [D loss: 0.688406, acc.: 55.08%] [G loss: 0.738789]
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1236 [D loss: 0.688418, acc.: 54.69%] [G loss: 0.733804]
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1237 [D loss: 0.688576, acc.: 55.86%] [G loss: 0.740534]
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1238 [D loss: 0.690864, acc.: 51.76%] [G loss: 0.738706]
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1239 [D loss: 0.690699, acc.: 51.17%] [G loss: 0.729526]
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1240 [D loss: 0.689174, acc.: 52.54%] [G loss: 0.733822]
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1241 [D loss: 0.693608, acc.: 49.41%] [G loss: 0.732496]
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1242 [D loss: 0.688078, acc.: 52.73%] [G loss: 0.723916]
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1243 [D loss: 0.687970, acc.: 53.52%] [G loss: 0.740451]
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1244 [D loss: 0.683069, acc.: 57.03%] [G loss: 0.730816]
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1245 [D loss: 0.691780, acc.: 51.37%] [G loss: 0.729954]
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1246 [D loss: 0.682479, acc.: 56.84%] [G loss: 0.736894]
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1247 [D loss: 0.690556, acc.: 55.47%] [G loss: 0.737177]
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1248 [D loss: 0.685452, acc.: 56.45%] [G loss: 0.738155]
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1249 [D loss: 0.681382, acc.: 58.20%] [G loss: 0.721852]
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1250 [D loss: 0.685722, acc.: 55.27%] [G loss: 0.723670]
1/1 [==============================] - 0s 15ms/step
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1251 [D loss: 0.689683, acc.: 53.12%] [G loss: 0.727689]
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1252 [D loss: 0.692037, acc.: 52.93%] [G loss: 0.722545]
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1253 [D loss: 0.688496, acc.: 51.76%] [G loss: 0.718995]
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1254 [D loss: 0.691143, acc.: 51.56%] [G loss: 0.727347]
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1255 [D loss: 0.689662, acc.: 53.91%] [G loss: 0.714937]
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1256 [D loss: 0.688068, acc.: 52.34%] [G loss: 0.724877]
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1257 [D loss: 0.682340, acc.: 54.88%] [G loss: 0.714836]
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1258 [D loss: 0.687225, acc.: 50.98%] [G loss: 0.718941]
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1259 [D loss: 0.686665, acc.: 52.15%] [G loss: 0.724443]
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1260 [D loss: 0.685655, acc.: 56.05%] [G loss: 0.736918]
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1261 [D loss: 0.688803, acc.: 52.73%] [G loss: 0.734608]
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1262 [D loss: 0.686295, acc.: 55.66%] [G loss: 0.736892]
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1263 [D loss: 0.684810, acc.: 57.23%] [G loss: 0.730726]
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1264 [D loss: 0.692297, acc.: 50.78%] [G loss: 0.728570]
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1265 [D loss: 0.681762, acc.: 55.66%] [G loss: 0.721203]
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1266 [D loss: 0.690311, acc.: 54.88%] [G loss: 0.714291]
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1267 [D loss: 0.695478, acc.: 50.59%] [G loss: 0.727464]
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1268 [D loss: 0.684262, acc.: 57.23%] [G loss: 0.731586]
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1269 [D loss: 0.688390, acc.: 52.15%] [G loss: 0.737550]
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1270 [D loss: 0.692406, acc.: 53.91%] [G loss: 0.738923]
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1271 [D loss: 0.677999, acc.: 61.72%] [G loss: 0.731436]
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1272 [D loss: 0.686092, acc.: 54.49%] [G loss: 0.740176]
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1273 [D loss: 0.683140, acc.: 57.81%] [G loss: 0.734213]
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1274 [D loss: 0.683512, acc.: 54.10%] [G loss: 0.735898]
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1275 [D loss: 0.685191, acc.: 57.62%] [G loss: 0.728677]
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1276 [D loss: 0.683028, acc.: 55.27%] [G loss: 0.733408]
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1277 [D loss: 0.687546, acc.: 52.54%] [G loss: 0.732483]
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1278 [D loss: 0.684733, acc.: 57.42%] [G loss: 0.745310]
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1279 [D loss: 0.683803, acc.: 54.30%] [G loss: 0.733872]
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1280 [D loss: 0.689597, acc.: 54.10%] [G loss: 0.733828]
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1281 [D loss: 0.689356, acc.: 52.73%] [G loss: 0.738867]
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1282 [D loss: 0.682960, acc.: 57.23%] [G loss: 0.740048]
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1283 [D loss: 0.691841, acc.: 52.54%] [G loss: 0.744298]
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1284 [D loss: 0.689317, acc.: 54.10%] [G loss: 0.743030]
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1285 [D loss: 0.692710, acc.: 51.76%] [G loss: 0.724755]
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1286 [D loss: 0.688132, acc.: 54.49%] [G loss: 0.727315]
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1287 [D loss: 0.692731, acc.: 50.20%] [G loss: 0.724614]
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1288 [D loss: 0.684043, acc.: 57.03%] [G loss: 0.726928]
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1289 [D loss: 0.688971, acc.: 52.34%] [G loss: 0.722621]
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1290 [D loss: 0.689560, acc.: 54.10%] [G loss: 0.726867]
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1291 [D loss: 0.691043, acc.: 53.52%] [G loss: 0.739475]
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1292 [D loss: 0.692446, acc.: 51.37%] [G loss: 0.734318]
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1293 [D loss: 0.685846, acc.: 54.10%] [G loss: 0.741928]
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1294 [D loss: 0.687970, acc.: 54.30%] [G loss: 0.745349]
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1295 [D loss: 0.683785, acc.: 54.88%] [G loss: 0.739038]
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1296 [D loss: 0.685165, acc.: 57.42%] [G loss: 0.748425]
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1297 [D loss: 0.688929, acc.: 52.73%] [G loss: 0.743581]
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1298 [D loss: 0.686505, acc.: 55.86%] [G loss: 0.736150]
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1299 [D loss: 0.678608, acc.: 57.42%] [G loss: 0.746069]
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1300 [D loss: 0.685752, acc.: 54.88%] [G loss: 0.734989]
1/1 [==============================] - 0s 15ms/step
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1301 [D loss: 0.685693, acc.: 57.03%] [G loss: 0.732683]
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1302 [D loss: 0.688567, acc.: 53.32%] [G loss: 0.728268]
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1303 [D loss: 0.684152, acc.: 55.47%] [G loss: 0.723725]
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1304 [D loss: 0.686363, acc.: 56.45%] [G loss: 0.739506]
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1305 [D loss: 0.689974, acc.: 53.71%] [G loss: 0.733673]
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1306 [D loss: 0.690231, acc.: 52.93%] [G loss: 0.734452]
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1307 [D loss: 0.689971, acc.: 53.52%] [G loss: 0.743766]
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1308 [D loss: 0.690998, acc.: 53.12%] [G loss: 0.733655]
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1309 [D loss: 0.692311, acc.: 50.78%] [G loss: 0.739695]
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1310 [D loss: 0.686114, acc.: 54.49%] [G loss: 0.723458]
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1311 [D loss: 0.695353, acc.: 48.63%] [G loss: 0.726032]
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1312 [D loss: 0.689777, acc.: 53.71%] [G loss: 0.733612]
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1313 [D loss: 0.698664, acc.: 46.68%] [G loss: 0.738158]
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1314 [D loss: 0.694179, acc.: 50.98%] [G loss: 0.728609]
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1315 [D loss: 0.690693, acc.: 52.73%] [G loss: 0.729084]
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1316 [D loss: 0.686676, acc.: 56.05%] [G loss: 0.729396]
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1317 [D loss: 0.689950, acc.: 51.56%] [G loss: 0.728423]
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1318 [D loss: 0.686511, acc.: 54.49%] [G loss: 0.727109]
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1319 [D loss: 0.689757, acc.: 57.42%] [G loss: 0.716158]
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1320 [D loss: 0.688821, acc.: 54.49%] [G loss: 0.711632]
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1321 [D loss: 0.689611, acc.: 52.54%] [G loss: 0.717171]
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1322 [D loss: 0.683300, acc.: 55.86%] [G loss: 0.724551]
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1323 [D loss: 0.689402, acc.: 54.88%] [G loss: 0.713100]
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1324 [D loss: 0.685321, acc.: 56.25%] [G loss: 0.728421]
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1325 [D loss: 0.685782, acc.: 54.69%] [G loss: 0.731784]
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1326 [D loss: 0.691811, acc.: 51.56%] [G loss: 0.732631]
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1327 [D loss: 0.687673, acc.: 53.71%] [G loss: 0.725861]
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1328 [D loss: 0.691086, acc.: 54.49%] [G loss: 0.728878]
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1329 [D loss: 0.684859, acc.: 54.10%] [G loss: 0.737225]
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1330 [D loss: 0.682835, acc.: 57.42%] [G loss: 0.734062]
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1331 [D loss: 0.685661, acc.: 55.86%] [G loss: 0.732985]
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1332 [D loss: 0.692572, acc.: 54.88%] [G loss: 0.730004]
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1333 [D loss: 0.685990, acc.: 56.05%] [G loss: 0.744667]
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1334 [D loss: 0.686498, acc.: 54.88%] [G loss: 0.736092]
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1335 [D loss: 0.687351, acc.: 51.56%] [G loss: 0.735120]
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1336 [D loss: 0.684180, acc.: 57.42%] [G loss: 0.728267]
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1337 [D loss: 0.686219, acc.: 56.84%] [G loss: 0.727261]
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1338 [D loss: 0.693353, acc.: 50.98%] [G loss: 0.729769]
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1339 [D loss: 0.689709, acc.: 51.56%] [G loss: 0.740648]
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1340 [D loss: 0.692037, acc.: 51.17%] [G loss: 0.735608]
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1341 [D loss: 0.687470, acc.: 55.47%] [G loss: 0.738801]
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1342 [D loss: 0.685249, acc.: 56.05%] [G loss: 0.739775]
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1343 [D loss: 0.690573, acc.: 51.95%] [G loss: 0.745229]
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1344 [D loss: 0.684489, acc.: 56.25%] [G loss: 0.739342]
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1345 [D loss: 0.689357, acc.: 55.66%] [G loss: 0.743341]
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1346 [D loss: 0.683320, acc.: 55.66%] [G loss: 0.742369]
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1347 [D loss: 0.687084, acc.: 53.91%] [G loss: 0.724018]
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1348 [D loss: 0.689511, acc.: 55.47%] [G loss: 0.727756]
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1349 [D loss: 0.687718, acc.: 54.69%] [G loss: 0.732666]
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1350 [D loss: 0.694612, acc.: 48.63%] [G loss: 0.726632]
1/1 [==============================] - 0s 16ms/step
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1351 [D loss: 0.681967, acc.: 57.03%] [G loss: 0.745082]
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1352 [D loss: 0.692609, acc.: 50.59%] [G loss: 0.747091]
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1353 [D loss: 0.684881, acc.: 58.01%] [G loss: 0.743734]
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1354 [D loss: 0.686791, acc.: 53.32%] [G loss: 0.733975]
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1355 [D loss: 0.691895, acc.: 51.95%] [G loss: 0.745838]
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1356 [D loss: 0.688760, acc.: 53.52%] [G loss: 0.724436]
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1357 [D loss: 0.686971, acc.: 56.25%] [G loss: 0.737780]
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1358 [D loss: 0.685186, acc.: 54.69%] [G loss: 0.731075]
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1359 [D loss: 0.687005, acc.: 51.95%] [G loss: 0.723167]
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1360 [D loss: 0.692948, acc.: 48.63%] [G loss: 0.720756]
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1361 [D loss: 0.685317, acc.: 55.66%] [G loss: 0.726904]
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1362 [D loss: 0.689737, acc.: 53.71%] [G loss: 0.719594]
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1363 [D loss: 0.691269, acc.: 51.76%] [G loss: 0.732361]
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1364 [D loss: 0.678578, acc.: 58.79%] [G loss: 0.727664]
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1365 [D loss: 0.685698, acc.: 53.52%] [G loss: 0.731760]
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1366 [D loss: 0.681221, acc.: 56.25%] [G loss: 0.718498]
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1367 [D loss: 0.693880, acc.: 50.59%] [G loss: 0.732239]
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1368 [D loss: 0.686535, acc.: 56.25%] [G loss: 0.731723]
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1369 [D loss: 0.684007, acc.: 58.79%] [G loss: 0.739611]
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1370 [D loss: 0.688708, acc.: 52.93%] [G loss: 0.740975]
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1371 [D loss: 0.682243, acc.: 54.88%] [G loss: 0.736083]
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1372 [D loss: 0.686393, acc.: 54.69%] [G loss: 0.736911]
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1373 [D loss: 0.674512, acc.: 64.45%] [G loss: 0.736671]
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1374 [D loss: 0.685546, acc.: 53.12%] [G loss: 0.729042]
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1375 [D loss: 0.687339, acc.: 54.49%] [G loss: 0.727166]
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1376 [D loss: 0.692098, acc.: 52.15%] [G loss: 0.736522]
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1377 [D loss: 0.683755, acc.: 54.88%] [G loss: 0.740310]
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1378 [D loss: 0.687003, acc.: 56.64%] [G loss: 0.741518]
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1379 [D loss: 0.691164, acc.: 53.52%] [G loss: 0.739770]
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1380 [D loss: 0.686466, acc.: 54.49%] [G loss: 0.728969]
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1381 [D loss: 0.687554, acc.: 53.32%] [G loss: 0.732622]
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1382 [D loss: 0.690699, acc.: 50.39%] [G loss: 0.734243]
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1383 [D loss: 0.693693, acc.: 51.95%] [G loss: 0.728468]
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1384 [D loss: 0.687388, acc.: 54.69%] [G loss: 0.728593]
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1385 [D loss: 0.686000, acc.: 56.25%] [G loss: 0.732571]
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1386 [D loss: 0.682133, acc.: 57.42%] [G loss: 0.730673]
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1387 [D loss: 0.687691, acc.: 53.52%] [G loss: 0.728238]
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1388 [D loss: 0.690003, acc.: 51.95%] [G loss: 0.729680]
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1389 [D loss: 0.688218, acc.: 53.91%] [G loss: 0.740589]
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1390 [D loss: 0.691160, acc.: 53.12%] [G loss: 0.735651]
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1391 [D loss: 0.688926, acc.: 53.71%] [G loss: 0.731047]
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1392 [D loss: 0.686568, acc.: 56.05%] [G loss: 0.730562]
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1393 [D loss: 0.689123, acc.: 51.95%] [G loss: 0.723621]
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1394 [D loss: 0.690252, acc.: 55.47%] [G loss: 0.718835]
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1395 [D loss: 0.695369, acc.: 50.39%] [G loss: 0.724480]
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1396 [D loss: 0.690978, acc.: 51.56%] [G loss: 0.722152]
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1397 [D loss: 0.686724, acc.: 53.52%] [G loss: 0.729468]
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1398 [D loss: 0.689819, acc.: 54.69%] [G loss: 0.734513]
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1399 [D loss: 0.691282, acc.: 52.15%] [G loss: 0.738411]
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1400 [D loss: 0.686207, acc.: 55.47%] [G loss: 0.740230]
1/1 [==============================] - 0s 15ms/step
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1401 [D loss: 0.684832, acc.: 55.27%] [G loss: 0.721848]
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1402 [D loss: 0.685547, acc.: 56.25%] [G loss: 0.718827]
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1403 [D loss: 0.688692, acc.: 51.37%] [G loss: 0.730770]
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1404 [D loss: 0.680900, acc.: 57.03%] [G loss: 0.718647]
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1405 [D loss: 0.681390, acc.: 57.62%] [G loss: 0.731485]
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1406 [D loss: 0.681944, acc.: 57.23%] [G loss: 0.722944]
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1407 [D loss: 0.684908, acc.: 54.49%] [G loss: 0.730809]
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1408 [D loss: 0.678919, acc.: 57.42%] [G loss: 0.725789]
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1409 [D loss: 0.685297, acc.: 56.25%] [G loss: 0.720201]
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1410 [D loss: 0.688325, acc.: 53.71%] [G loss: 0.731602]
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1411 [D loss: 0.694210, acc.: 52.73%] [G loss: 0.720869]
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1412 [D loss: 0.686503, acc.: 54.30%] [G loss: 0.738896]
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1413 [D loss: 0.686097, acc.: 53.52%] [G loss: 0.741119]
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1414 [D loss: 0.685268, acc.: 56.25%] [G loss: 0.737467]
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1415 [D loss: 0.691576, acc.: 53.52%] [G loss: 0.732813]
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1416 [D loss: 0.693145, acc.: 50.59%] [G loss: 0.726973]
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1417 [D loss: 0.687128, acc.: 54.49%] [G loss: 0.727174]
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1418 [D loss: 0.686662, acc.: 52.93%] [G loss: 0.736657]
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1419 [D loss: 0.694237, acc.: 50.00%] [G loss: 0.722763]
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1420 [D loss: 0.685450, acc.: 56.84%] [G loss: 0.729725]
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1421 [D loss: 0.690578, acc.: 52.73%] [G loss: 0.737054]
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1422 [D loss: 0.681602, acc.: 56.84%] [G loss: 0.734864]
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1423 [D loss: 0.684417, acc.: 55.86%] [G loss: 0.734703]
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1424 [D loss: 0.684265, acc.: 54.10%] [G loss: 0.734978]
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1425 [D loss: 0.691967, acc.: 55.47%] [G loss: 0.737526]
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1426 [D loss: 0.691220, acc.: 51.56%] [G loss: 0.740492]
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1427 [D loss: 0.689329, acc.: 49.80%] [G loss: 0.746736]
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1428 [D loss: 0.693060, acc.: 51.17%] [G loss: 0.745846]
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1429 [D loss: 0.689956, acc.: 52.93%] [G loss: 0.736637]
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1430 [D loss: 0.689561, acc.: 54.30%] [G loss: 0.731771]
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1431 [D loss: 0.693512, acc.: 50.00%] [G loss: 0.730995]
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1432 [D loss: 0.689024, acc.: 53.91%] [G loss: 0.735618]
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1433 [D loss: 0.696212, acc.: 49.61%] [G loss: 0.732438]
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1434 [D loss: 0.693781, acc.: 50.78%] [G loss: 0.733593]
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1435 [D loss: 0.692956, acc.: 51.37%] [G loss: 0.731844]
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1436 [D loss: 0.693382, acc.: 51.56%] [G loss: 0.729697]
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1437 [D loss: 0.690969, acc.: 52.73%] [G loss: 0.735657]
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1438 [D loss: 0.695304, acc.: 50.98%] [G loss: 0.730379]
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1439 [D loss: 0.684734, acc.: 55.27%] [G loss: 0.725939]
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1440 [D loss: 0.689331, acc.: 56.64%] [G loss: 0.729279]
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1441 [D loss: 0.686991, acc.: 50.78%] [G loss: 0.720718]
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1442 [D loss: 0.683452, acc.: 56.25%] [G loss: 0.728942]
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1443 [D loss: 0.684783, acc.: 56.84%] [G loss: 0.728434]
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1444 [D loss: 0.685376, acc.: 57.81%] [G loss: 0.729841]
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1445 [D loss: 0.687019, acc.: 55.47%] [G loss: 0.721115]
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1446 [D loss: 0.682352, acc.: 55.86%] [G loss: 0.730092]
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1447 [D loss: 0.688536, acc.: 52.54%] [G loss: 0.729927]
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1448 [D loss: 0.683389, acc.: 53.12%] [G loss: 0.717436]
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1449 [D loss: 0.687707, acc.: 54.69%] [G loss: 0.721240]
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1450 [D loss: 0.689018, acc.: 53.52%] [G loss: 0.719773]
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1451 [D loss: 0.692089, acc.: 49.22%] [G loss: 0.716352]
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1452 [D loss: 0.686575, acc.: 53.71%] [G loss: 0.710151]
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1453 [D loss: 0.694011, acc.: 51.76%] [G loss: 0.721672]
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1454 [D loss: 0.688013, acc.: 53.12%] [G loss: 0.714196]
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1455 [D loss: 0.695174, acc.: 52.73%] [G loss: 0.730640]
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1456 [D loss: 0.684913, acc.: 56.05%] [G loss: 0.728415]
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1457 [D loss: 0.684057, acc.: 55.47%] [G loss: 0.724201]
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1458 [D loss: 0.686088, acc.: 53.32%] [G loss: 0.730718]
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1459 [D loss: 0.692591, acc.: 54.10%] [G loss: 0.721893]
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1460 [D loss: 0.683409, acc.: 53.71%] [G loss: 0.734550]
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1461 [D loss: 0.687542, acc.: 53.52%] [G loss: 0.733587]
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1462 [D loss: 0.690036, acc.: 53.12%] [G loss: 0.737763]
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1463 [D loss: 0.685365, acc.: 55.66%] [G loss: 0.735250]
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1464 [D loss: 0.687000, acc.: 54.10%] [G loss: 0.732902]
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1465 [D loss: 0.691427, acc.: 48.63%] [G loss: 0.740921]
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1466 [D loss: 0.690757, acc.: 52.54%] [G loss: 0.735307]
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1467 [D loss: 0.688906, acc.: 54.30%] [G loss: 0.738159]
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1468 [D loss: 0.684148, acc.: 55.86%] [G loss: 0.733818]
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1469 [D loss: 0.685930, acc.: 55.47%] [G loss: 0.734306]
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1470 [D loss: 0.686053, acc.: 56.84%] [G loss: 0.734978]
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1471 [D loss: 0.684138, acc.: 54.88%] [G loss: 0.734661]
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1472 [D loss: 0.685672, acc.: 51.95%] [G loss: 0.731233]
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1473 [D loss: 0.692079, acc.: 50.98%] [G loss: 0.731118]
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1474 [D loss: 0.693138, acc.: 51.95%] [G loss: 0.742005]
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1475 [D loss: 0.693163, acc.: 52.54%] [G loss: 0.738022]
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1476 [D loss: 0.691322, acc.: 50.59%] [G loss: 0.728287]
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1477 [D loss: 0.685045, acc.: 55.27%] [G loss: 0.728384]
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1478 [D loss: 0.685213, acc.: 56.05%] [G loss: 0.723522]
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1479 [D loss: 0.691380, acc.: 51.17%] [G loss: 0.732544]
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1480 [D loss: 0.683670, acc.: 56.84%] [G loss: 0.735696]
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1481 [D loss: 0.681731, acc.: 57.03%] [G loss: 0.722937]
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1482 [D loss: 0.691461, acc.: 51.95%] [G loss: 0.716569]
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1483 [D loss: 0.681726, acc.: 57.42%] [G loss: 0.726210]
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1484 [D loss: 0.685191, acc.: 54.69%] [G loss: 0.718662]
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1485 [D loss: 0.688099, acc.: 51.76%] [G loss: 0.733195]
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1486 [D loss: 0.681210, acc.: 60.16%] [G loss: 0.727282]
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1487 [D loss: 0.688153, acc.: 51.76%] [G loss: 0.724795]
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1488 [D loss: 0.691613, acc.: 53.12%] [G loss: 0.723939]
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1489 [D loss: 0.691661, acc.: 51.37%] [G loss: 0.713840]
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1490 [D loss: 0.692795, acc.: 52.54%] [G loss: 0.719329]
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1491 [D loss: 0.694579, acc.: 50.98%] [G loss: 0.721286]
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1492 [D loss: 0.693633, acc.: 48.63%] [G loss: 0.719152]
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1493 [D loss: 0.688985, acc.: 53.52%] [G loss: 0.725627]
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1494 [D loss: 0.688141, acc.: 52.34%] [G loss: 0.719053]
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1495 [D loss: 0.692083, acc.: 52.15%] [G loss: 0.731357]
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1496 [D loss: 0.689500, acc.: 51.76%] [G loss: 0.726770]
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1497 [D loss: 0.690149, acc.: 48.24%] [G loss: 0.734109]
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1498 [D loss: 0.678427, acc.: 58.98%] [G loss: 0.736386]
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1499 [D loss: 0.683122, acc.: 57.62%] [G loss: 0.732174]
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1500 [D loss: 0.690118, acc.: 50.98%] [G loss: 0.736673]
1/1 [==============================] - 0s 15ms/step
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1501 [D loss: 0.683370, acc.: 56.25%] [G loss: 0.744394]
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1502 [D loss: 0.687477, acc.: 54.49%] [G loss: 0.727718]
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1503 [D loss: 0.688472, acc.: 55.86%] [G loss: 0.735941]
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1504 [D loss: 0.686791, acc.: 54.10%] [G loss: 0.730165]
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1505 [D loss: 0.687676, acc.: 52.73%] [G loss: 0.733851]
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1506 [D loss: 0.688337, acc.: 53.52%] [G loss: 0.723813]
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1507 [D loss: 0.684942, acc.: 55.08%] [G loss: 0.730859]
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1508 [D loss: 0.686799, acc.: 54.88%] [G loss: 0.720667]
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1509 [D loss: 0.689213, acc.: 49.80%] [G loss: 0.735155]
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1510 [D loss: 0.692197, acc.: 52.15%] [G loss: 0.730008]
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1511 [D loss: 0.684974, acc.: 55.47%] [G loss: 0.734944]
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1512 [D loss: 0.691275, acc.: 52.34%] [G loss: 0.734843]
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1513 [D loss: 0.683017, acc.: 56.05%] [G loss: 0.741532]
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1514 [D loss: 0.688295, acc.: 55.86%] [G loss: 0.733736]
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1515 [D loss: 0.690182, acc.: 52.34%] [G loss: 0.732805]
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1516 [D loss: 0.683229, acc.: 54.69%] [G loss: 0.725762]
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1517 [D loss: 0.688622, acc.: 53.71%] [G loss: 0.744136]
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1518 [D loss: 0.686293, acc.: 55.27%] [G loss: 0.737852]
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1519 [D loss: 0.687715, acc.: 55.66%] [G loss: 0.735864]
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1520 [D loss: 0.692710, acc.: 54.49%] [G loss: 0.729385]
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1521 [D loss: 0.693008, acc.: 52.73%] [G loss: 0.732431]
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1522 [D loss: 0.682891, acc.: 57.42%] [G loss: 0.729577]
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1523 [D loss: 0.686555, acc.: 55.27%] [G loss: 0.725660]
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1524 [D loss: 0.691636, acc.: 50.78%] [G loss: 0.727000]
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1525 [D loss: 0.683132, acc.: 57.23%] [G loss: 0.725225]
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1526 [D loss: 0.683628, acc.: 58.01%] [G loss: 0.725428]
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1527 [D loss: 0.683077, acc.: 56.45%] [G loss: 0.714864]
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1528 [D loss: 0.683656, acc.: 55.86%] [G loss: 0.724090]
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1529 [D loss: 0.681338, acc.: 57.23%] [G loss: 0.725051]
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1530 [D loss: 0.689147, acc.: 51.95%] [G loss: 0.723659]
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1531 [D loss: 0.692274, acc.: 54.88%] [G loss: 0.733405]
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1532 [D loss: 0.684644, acc.: 53.71%] [G loss: 0.718948]
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1533 [D loss: 0.686617, acc.: 54.88%] [G loss: 0.727233]
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1534 [D loss: 0.687470, acc.: 51.56%] [G loss: 0.724717]
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1535 [D loss: 0.682690, acc.: 56.05%] [G loss: 0.730505]
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1536 [D loss: 0.687967, acc.: 52.54%] [G loss: 0.728771]
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1537 [D loss: 0.685577, acc.: 54.69%] [G loss: 0.734965]
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1538 [D loss: 0.679869, acc.: 56.05%] [G loss: 0.728994]
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1539 [D loss: 0.689533, acc.: 52.73%] [G loss: 0.733098]
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1540 [D loss: 0.685276, acc.: 58.20%] [G loss: 0.725210]
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1541 [D loss: 0.688166, acc.: 52.93%] [G loss: 0.735947]
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1542 [D loss: 0.693181, acc.: 49.80%] [G loss: 0.732908]
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1543 [D loss: 0.693986, acc.: 50.98%] [G loss: 0.718437]
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1544 [D loss: 0.685712, acc.: 52.15%] [G loss: 0.731317]
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1545 [D loss: 0.693866, acc.: 51.17%] [G loss: 0.713468]
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1546 [D loss: 0.697573, acc.: 49.22%] [G loss: 0.726133]
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1547 [D loss: 0.686360, acc.: 56.25%] [G loss: 0.732399]
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1548 [D loss: 0.682339, acc.: 58.01%] [G loss: 0.734097]
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1549 [D loss: 0.690833, acc.: 52.73%] [G loss: 0.733823]
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1550 [D loss: 0.683396, acc.: 54.88%] [G loss: 0.736206]
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1551 [D loss: 0.687768, acc.: 55.08%] [G loss: 0.740767]
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1552 [D loss: 0.684793, acc.: 54.69%] [G loss: 0.733489]
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1553 [D loss: 0.691060, acc.: 50.39%] [G loss: 0.719357]
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1554 [D loss: 0.694559, acc.: 50.39%] [G loss: 0.721196]
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1555 [D loss: 0.686704, acc.: 55.86%] [G loss: 0.723565]
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1556 [D loss: 0.689014, acc.: 55.47%] [G loss: 0.720084]
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1557 [D loss: 0.688215, acc.: 55.86%] [G loss: 0.722652]
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1558 [D loss: 0.685874, acc.: 53.32%] [G loss: 0.735485]
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1559 [D loss: 0.688540, acc.: 51.37%] [G loss: 0.732578]
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1560 [D loss: 0.681082, acc.: 59.18%] [G loss: 0.729639]
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1561 [D loss: 0.682007, acc.: 57.81%] [G loss: 0.733910]
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1562 [D loss: 0.689406, acc.: 54.30%] [G loss: 0.725239]
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1563 [D loss: 0.686408, acc.: 54.10%] [G loss: 0.728360]
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1564 [D loss: 0.690345, acc.: 52.54%] [G loss: 0.726806]
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1565 [D loss: 0.690279, acc.: 49.22%] [G loss: 0.730443]
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1566 [D loss: 0.688295, acc.: 54.69%] [G loss: 0.730521]
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1567 [D loss: 0.680326, acc.: 57.81%] [G loss: 0.741219]
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1568 [D loss: 0.688340, acc.: 52.93%] [G loss: 0.742787]
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1569 [D loss: 0.686402, acc.: 55.47%] [G loss: 0.729983]
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1570 [D loss: 0.686583, acc.: 53.32%] [G loss: 0.734803]
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1571 [D loss: 0.682003, acc.: 54.88%] [G loss: 0.739877]
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1572 [D loss: 0.688021, acc.: 53.71%] [G loss: 0.741043]
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1573 [D loss: 0.683972, acc.: 54.49%] [G loss: 0.734012]
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1574 [D loss: 0.685720, acc.: 54.88%] [G loss: 0.728797]
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1575 [D loss: 0.691135, acc.: 52.15%] [G loss: 0.740035]
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1576 [D loss: 0.689449, acc.: 56.64%] [G loss: 0.734424]
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1577 [D loss: 0.691640, acc.: 51.17%] [G loss: 0.730295]
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1578 [D loss: 0.689860, acc.: 51.37%] [G loss: 0.724479]
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1579 [D loss: 0.694563, acc.: 46.68%] [G loss: 0.729216]
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1580 [D loss: 0.684532, acc.: 54.88%] [G loss: 0.725095]
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1581 [D loss: 0.691667, acc.: 50.78%] [G loss: 0.729564]
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1582 [D loss: 0.694667, acc.: 49.41%] [G loss: 0.729209]
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1583 [D loss: 0.695327, acc.: 51.56%] [G loss: 0.730221]
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1584 [D loss: 0.690913, acc.: 51.76%] [G loss: 0.743001]
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1585 [D loss: 0.693410, acc.: 51.17%] [G loss: 0.740555]
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1586 [D loss: 0.684873, acc.: 53.71%] [G loss: 0.747826]
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1587 [D loss: 0.683438, acc.: 56.64%] [G loss: 0.729246]
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1588 [D loss: 0.680979, acc.: 55.86%] [G loss: 0.735946]
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1589 [D loss: 0.685578, acc.: 56.84%] [G loss: 0.729646]
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1590 [D loss: 0.678042, acc.: 57.62%] [G loss: 0.724525]
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1591 [D loss: 0.687049, acc.: 56.05%] [G loss: 0.724284]
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1592 [D loss: 0.688105, acc.: 55.86%] [G loss: 0.730445]
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1593 [D loss: 0.686375, acc.: 52.93%] [G loss: 0.727682]
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1594 [D loss: 0.686573, acc.: 54.10%] [G loss: 0.740393]
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1595 [D loss: 0.688724, acc.: 52.54%] [G loss: 0.732582]
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1596 [D loss: 0.686266, acc.: 56.64%] [G loss: 0.722408]
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1597 [D loss: 0.693776, acc.: 50.39%] [G loss: 0.715583]
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1598 [D loss: 0.686582, acc.: 55.47%] [G loss: 0.716888]
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1599 [D loss: 0.688716, acc.: 56.25%] [G loss: 0.726803]
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1600 [D loss: 0.685317, acc.: 54.10%] [G loss: 0.725832]
1/1 [==============================] - 0s 16ms/step
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1601 [D loss: 0.680470, acc.: 57.03%] [G loss: 0.724263]
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1602 [D loss: 0.685766, acc.: 53.71%] [G loss: 0.726826]
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1603 [D loss: 0.681975, acc.: 58.98%] [G loss: 0.732102]
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1604 [D loss: 0.687976, acc.: 54.88%] [G loss: 0.722523]
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1605 [D loss: 0.686801, acc.: 51.56%] [G loss: 0.721215]
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1606 [D loss: 0.682469, acc.: 55.47%] [G loss: 0.735113]
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1607 [D loss: 0.689529, acc.: 51.76%] [G loss: 0.735748]
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1608 [D loss: 0.681581, acc.: 56.45%] [G loss: 0.738261]
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1609 [D loss: 0.684421, acc.: 51.95%] [G loss: 0.721012]
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1610 [D loss: 0.686743, acc.: 54.49%] [G loss: 0.732078]
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1611 [D loss: 0.684198, acc.: 54.30%] [G loss: 0.738412]
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1612 [D loss: 0.689366, acc.: 51.17%] [G loss: 0.737929]
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1613 [D loss: 0.688237, acc.: 52.15%] [G loss: 0.733838]
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1614 [D loss: 0.689737, acc.: 53.71%] [G loss: 0.749976]
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1615 [D loss: 0.691263, acc.: 51.95%] [G loss: 0.747138]
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1616 [D loss: 0.688117, acc.: 54.30%] [G loss: 0.733407]
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1617 [D loss: 0.688806, acc.: 50.78%] [G loss: 0.716958]
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1618 [D loss: 0.691063, acc.: 51.37%] [G loss: 0.721747]
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1619 [D loss: 0.693380, acc.: 50.78%] [G loss: 0.723341]
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1620 [D loss: 0.691053, acc.: 53.32%] [G loss: 0.718934]
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1621 [D loss: 0.692512, acc.: 52.15%] [G loss: 0.723084]
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1622 [D loss: 0.682933, acc.: 57.81%] [G loss: 0.731524]
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1623 [D loss: 0.685830, acc.: 56.84%] [G loss: 0.730057]
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1624 [D loss: 0.683989, acc.: 54.88%] [G loss: 0.732617]
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1625 [D loss: 0.686702, acc.: 54.30%] [G loss: 0.724528]
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1626 [D loss: 0.682633, acc.: 56.05%] [G loss: 0.722813]
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1627 [D loss: 0.685434, acc.: 53.32%] [G loss: 0.726372]
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1628 [D loss: 0.695499, acc.: 52.73%] [G loss: 0.731318]
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1629 [D loss: 0.688811, acc.: 53.52%] [G loss: 0.719798]
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1630 [D loss: 0.686343, acc.: 55.08%] [G loss: 0.719444]
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1631 [D loss: 0.682992, acc.: 56.25%] [G loss: 0.721277]
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1632 [D loss: 0.682887, acc.: 57.81%] [G loss: 0.725853]
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1633 [D loss: 0.687578, acc.: 52.73%] [G loss: 0.740022]
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1634 [D loss: 0.688892, acc.: 54.10%] [G loss: 0.735091]
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1635 [D loss: 0.689078, acc.: 54.88%] [G loss: 0.726358]
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1636 [D loss: 0.683106, acc.: 56.84%] [G loss: 0.729432]
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1637 [D loss: 0.688049, acc.: 52.54%] [G loss: 0.733807]
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1638 [D loss: 0.686676, acc.: 54.30%] [G loss: 0.721647]
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1639 [D loss: 0.687722, acc.: 53.32%] [G loss: 0.723546]
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1640 [D loss: 0.691670, acc.: 51.95%] [G loss: 0.731321]
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1641 [D loss: 0.683178, acc.: 56.84%] [G loss: 0.720322]
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1642 [D loss: 0.691162, acc.: 51.95%] [G loss: 0.733031]
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1643 [D loss: 0.686912, acc.: 53.91%] [G loss: 0.721935]
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1644 [D loss: 0.691667, acc.: 52.54%] [G loss: 0.735511]
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1645 [D loss: 0.687577, acc.: 52.34%] [G loss: 0.734383]
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1646 [D loss: 0.687951, acc.: 53.12%] [G loss: 0.742009]
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1647 [D loss: 0.696447, acc.: 51.56%] [G loss: 0.734774]
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1648 [D loss: 0.684366, acc.: 55.66%] [G loss: 0.732485]
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1649 [D loss: 0.681794, acc.: 57.03%] [G loss: 0.729257]
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1650 [D loss: 0.688020, acc.: 54.30%] [G loss: 0.724651]
1/1 [==============================] - 0s 15ms/step
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1651 [D loss: 0.681477, acc.: 53.32%] [G loss: 0.725865]
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1652 [D loss: 0.688537, acc.: 53.71%] [G loss: 0.731134]
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1653 [D loss: 0.686777, acc.: 56.05%] [G loss: 0.724065]
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1654 [D loss: 0.688788, acc.: 55.27%] [G loss: 0.731494]
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1655 [D loss: 0.682968, acc.: 56.25%] [G loss: 0.718809]
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1656 [D loss: 0.687699, acc.: 52.93%] [G loss: 0.732177]
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1657 [D loss: 0.683447, acc.: 57.23%] [G loss: 0.724703]
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1658 [D loss: 0.696954, acc.: 50.20%] [G loss: 0.732088]
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1659 [D loss: 0.690845, acc.: 51.95%] [G loss: 0.724281]
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1660 [D loss: 0.681265, acc.: 58.20%] [G loss: 0.728686]
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1661 [D loss: 0.687750, acc.: 55.27%] [G loss: 0.735020]
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1662 [D loss: 0.690157, acc.: 53.52%] [G loss: 0.730874]
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1663 [D loss: 0.691760, acc.: 50.98%] [G loss: 0.738073]
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1664 [D loss: 0.687667, acc.: 54.10%] [G loss: 0.734740]
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1665 [D loss: 0.690026, acc.: 54.88%] [G loss: 0.731874]
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1666 [D loss: 0.682040, acc.: 56.84%] [G loss: 0.737590]
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1667 [D loss: 0.685237, acc.: 55.08%] [G loss: 0.732115]
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1668 [D loss: 0.685888, acc.: 55.47%] [G loss: 0.732367]
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1669 [D loss: 0.690829, acc.: 52.54%] [G loss: 0.727947]
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1670 [D loss: 0.689511, acc.: 53.71%] [G loss: 0.735741]
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1671 [D loss: 0.685299, acc.: 54.69%] [G loss: 0.733169]
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1672 [D loss: 0.689244, acc.: 53.32%] [G loss: 0.730339]
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1673 [D loss: 0.689092, acc.: 53.71%] [G loss: 0.722586]
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1674 [D loss: 0.685590, acc.: 56.45%] [G loss: 0.731265]
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1675 [D loss: 0.690599, acc.: 52.54%] [G loss: 0.739238]
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1676 [D loss: 0.688319, acc.: 50.78%] [G loss: 0.735561]
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1677 [D loss: 0.688553, acc.: 53.32%] [G loss: 0.735133]
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1678 [D loss: 0.692764, acc.: 52.15%] [G loss: 0.733996]
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1679 [D loss: 0.690428, acc.: 53.71%] [G loss: 0.738240]
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1680 [D loss: 0.690890, acc.: 54.49%] [G loss: 0.732138]
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1681 [D loss: 0.684872, acc.: 55.47%] [G loss: 0.733056]
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1682 [D loss: 0.690954, acc.: 51.17%] [G loss: 0.725586]
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1683 [D loss: 0.681189, acc.: 57.23%] [G loss: 0.727778]
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1684 [D loss: 0.687396, acc.: 51.17%] [G loss: 0.727221]
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1685 [D loss: 0.688198, acc.: 54.49%] [G loss: 0.725281]
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1686 [D loss: 0.684534, acc.: 54.49%] [G loss: 0.730634]
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1687 [D loss: 0.681335, acc.: 58.20%] [G loss: 0.727978]
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1688 [D loss: 0.685466, acc.: 55.86%] [G loss: 0.727772]
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1689 [D loss: 0.692038, acc.: 53.52%] [G loss: 0.723467]
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1690 [D loss: 0.690449, acc.: 54.88%] [G loss: 0.727944]
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1691 [D loss: 0.678317, acc.: 59.38%] [G loss: 0.716236]
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1692 [D loss: 0.683772, acc.: 56.25%] [G loss: 0.724466]
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1693 [D loss: 0.686280, acc.: 53.32%] [G loss: 0.721581]
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1694 [D loss: 0.682273, acc.: 58.20%] [G loss: 0.726408]
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1695 [D loss: 0.686942, acc.: 54.88%] [G loss: 0.741667]
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1696 [D loss: 0.686513, acc.: 55.47%] [G loss: 0.730199]
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1697 [D loss: 0.686318, acc.: 55.27%] [G loss: 0.720170]
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1698 [D loss: 0.682796, acc.: 57.81%] [G loss: 0.728925]
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1699 [D loss: 0.690414, acc.: 52.54%] [G loss: 0.730658]
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1700 [D loss: 0.687937, acc.: 54.69%] [G loss: 0.730613]
1/1 [==============================] - 0s 17ms/step
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1701 [D loss: 0.687694, acc.: 52.15%] [G loss: 0.737236]
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1702 [D loss: 0.688709, acc.: 54.30%] [G loss: 0.735183]
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1703 [D loss: 0.689653, acc.: 54.30%] [G loss: 0.724518]
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1704 [D loss: 0.685270, acc.: 54.88%] [G loss: 0.737344]
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1705 [D loss: 0.689576, acc.: 53.71%] [G loss: 0.733415]
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1706 [D loss: 0.689549, acc.: 53.12%] [G loss: 0.747465]
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1707 [D loss: 0.682364, acc.: 56.45%] [G loss: 0.732555]
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1708 [D loss: 0.690476, acc.: 52.15%] [G loss: 0.731489]
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1709 [D loss: 0.688418, acc.: 52.73%] [G loss: 0.726140]
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1710 [D loss: 0.694104, acc.: 47.46%] [G loss: 0.732156]
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1711 [D loss: 0.690174, acc.: 51.76%] [G loss: 0.723742]
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1712 [D loss: 0.681513, acc.: 58.01%] [G loss: 0.721583]
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1713 [D loss: 0.684770, acc.: 52.73%] [G loss: 0.718135]
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1714 [D loss: 0.686221, acc.: 54.10%] [G loss: 0.723251]
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1715 [D loss: 0.690101, acc.: 50.98%] [G loss: 0.730526]
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1716 [D loss: 0.682326, acc.: 58.59%] [G loss: 0.720035]
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1717 [D loss: 0.684527, acc.: 56.05%] [G loss: 0.732465]
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1718 [D loss: 0.687648, acc.: 56.64%] [G loss: 0.731264]
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1719 [D loss: 0.682155, acc.: 57.23%] [G loss: 0.722906]
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1720 [D loss: 0.697764, acc.: 48.24%] [G loss: 0.722613]
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1721 [D loss: 0.686643, acc.: 52.15%] [G loss: 0.732714]
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1722 [D loss: 0.687726, acc.: 54.10%] [G loss: 0.731455]
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1723 [D loss: 0.686800, acc.: 54.49%] [G loss: 0.724243]
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1724 [D loss: 0.695794, acc.: 50.20%] [G loss: 0.720863]
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1725 [D loss: 0.689858, acc.: 52.15%] [G loss: 0.721541]
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1726 [D loss: 0.689625, acc.: 54.30%] [G loss: 0.725573]
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1727 [D loss: 0.685222, acc.: 53.12%] [G loss: 0.736760]
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1728 [D loss: 0.684628, acc.: 56.84%] [G loss: 0.743469]
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1729 [D loss: 0.694135, acc.: 53.12%] [G loss: 0.737573]
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1730 [D loss: 0.686290, acc.: 55.86%] [G loss: 0.734433]
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1731 [D loss: 0.687561, acc.: 55.27%] [G loss: 0.730783]
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1732 [D loss: 0.683993, acc.: 55.86%] [G loss: 0.724607]
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1733 [D loss: 0.686798, acc.: 54.49%] [G loss: 0.722660]
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1734 [D loss: 0.685614, acc.: 52.93%] [G loss: 0.730614]
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1735 [D loss: 0.691699, acc.: 50.00%] [G loss: 0.723008]
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1736 [D loss: 0.688352, acc.: 56.05%] [G loss: 0.715728]
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1737 [D loss: 0.687083, acc.: 56.45%] [G loss: 0.732523]
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1738 [D loss: 0.685421, acc.: 55.47%] [G loss: 0.746705]
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1739 [D loss: 0.681572, acc.: 56.64%] [G loss: 0.733479]
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1740 [D loss: 0.693514, acc.: 50.78%] [G loss: 0.736999]
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1741 [D loss: 0.685300, acc.: 54.88%] [G loss: 0.739526]
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1742 [D loss: 0.687389, acc.: 54.30%] [G loss: 0.728144]
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1743 [D loss: 0.688854, acc.: 51.56%] [G loss: 0.725874]
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1744 [D loss: 0.694986, acc.: 47.85%] [G loss: 0.721039]
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1745 [D loss: 0.689875, acc.: 49.80%] [G loss: 0.719019]
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1746 [D loss: 0.689102, acc.: 53.71%] [G loss: 0.719223]
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1747 [D loss: 0.682726, acc.: 56.25%] [G loss: 0.731068]
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1748 [D loss: 0.690397, acc.: 50.98%] [G loss: 0.742019]
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1749 [D loss: 0.685898, acc.: 52.34%] [G loss: 0.718116]
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1750 [D loss: 0.692176, acc.: 53.71%] [G loss: 0.724970]
1/1 [==============================] - 0s 15ms/step
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1751 [D loss: 0.688996, acc.: 54.10%] [G loss: 0.728321]
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1752 [D loss: 0.686440, acc.: 54.69%] [G loss: 0.737555]
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1753 [D loss: 0.681063, acc.: 58.01%] [G loss: 0.725800]
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1754 [D loss: 0.683965, acc.: 54.88%] [G loss: 0.729930]
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1755 [D loss: 0.679081, acc.: 56.64%] [G loss: 0.732888]
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1756 [D loss: 0.686747, acc.: 52.93%] [G loss: 0.729060]
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1757 [D loss: 0.688575, acc.: 53.12%] [G loss: 0.736231]
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1758 [D loss: 0.691117, acc.: 51.95%] [G loss: 0.740776]
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1759 [D loss: 0.682361, acc.: 56.64%] [G loss: 0.737017]
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1760 [D loss: 0.687758, acc.: 52.73%] [G loss: 0.736053]
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1761 [D loss: 0.685723, acc.: 52.73%] [G loss: 0.735382]
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1762 [D loss: 0.688272, acc.: 54.10%] [G loss: 0.734622]
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1763 [D loss: 0.689695, acc.: 54.88%] [G loss: 0.727729]
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1764 [D loss: 0.693905, acc.: 49.41%] [G loss: 0.735558]
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1765 [D loss: 0.689446, acc.: 50.20%] [G loss: 0.730897]
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1766 [D loss: 0.695851, acc.: 49.41%] [G loss: 0.732536]
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1767 [D loss: 0.680281, acc.: 56.84%] [G loss: 0.723308]
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1768 [D loss: 0.681478, acc.: 56.05%] [G loss: 0.736066]
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1769 [D loss: 0.687125, acc.: 57.42%] [G loss: 0.735747]
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1770 [D loss: 0.684990, acc.: 55.08%] [G loss: 0.720177]
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1771 [D loss: 0.689300, acc.: 52.73%] [G loss: 0.713568]
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1772 [D loss: 0.691138, acc.: 55.08%] [G loss: 0.721313]
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1773 [D loss: 0.686762, acc.: 53.91%] [G loss: 0.728216]
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1774 [D loss: 0.678252, acc.: 59.18%] [G loss: 0.723503]
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1775 [D loss: 0.694968, acc.: 49.02%] [G loss: 0.725210]
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1776 [D loss: 0.680590, acc.: 57.81%] [G loss: 0.720578]
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1777 [D loss: 0.685836, acc.: 55.27%] [G loss: 0.730344]
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1778 [D loss: 0.686363, acc.: 54.10%] [G loss: 0.736594]
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1779 [D loss: 0.686150, acc.: 55.27%] [G loss: 0.736191]
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1780 [D loss: 0.694381, acc.: 52.34%] [G loss: 0.720678]
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1781 [D loss: 0.688087, acc.: 53.52%] [G loss: 0.732299]
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1782 [D loss: 0.694760, acc.: 51.95%] [G loss: 0.740069]
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1783 [D loss: 0.689013, acc.: 53.32%] [G loss: 0.730639]
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1784 [D loss: 0.683880, acc.: 58.01%] [G loss: 0.723209]
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1785 [D loss: 0.691501, acc.: 51.37%] [G loss: 0.726945]
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1786 [D loss: 0.684156, acc.: 56.45%] [G loss: 0.726980]
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1787 [D loss: 0.690831, acc.: 54.49%] [G loss: 0.734082]
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1788 [D loss: 0.680697, acc.: 57.42%] [G loss: 0.729481]
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1789 [D loss: 0.692801, acc.: 52.73%] [G loss: 0.725732]
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1790 [D loss: 0.688887, acc.: 53.12%] [G loss: 0.732610]
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1791 [D loss: 0.684938, acc.: 54.30%] [G loss: 0.735793]
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1792 [D loss: 0.683893, acc.: 55.47%] [G loss: 0.730513]
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1793 [D loss: 0.689440, acc.: 51.76%] [G loss: 0.733844]
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1794 [D loss: 0.688461, acc.: 52.73%] [G loss: 0.720154]
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1795 [D loss: 0.692694, acc.: 50.59%] [G loss: 0.724747]
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1796 [D loss: 0.691324, acc.: 53.71%] [G loss: 0.721270]
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1797 [D loss: 0.685536, acc.: 54.49%] [G loss: 0.734929]
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1798 [D loss: 0.680521, acc.: 56.45%] [G loss: 0.736368]
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1799 [D loss: 0.682275, acc.: 55.66%] [G loss: 0.735671]
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1800 [D loss: 0.684019, acc.: 55.86%] [G loss: 0.736839]
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1801 [D loss: 0.683351, acc.: 55.66%] [G loss: 0.734985]
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1802 [D loss: 0.677421, acc.: 58.98%] [G loss: 0.732285]
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1803 [D loss: 0.687869, acc.: 55.27%] [G loss: 0.731417]
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1804 [D loss: 0.681772, acc.: 57.23%] [G loss: 0.724938]
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1805 [D loss: 0.683977, acc.: 54.69%] [G loss: 0.728791]
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1806 [D loss: 0.691142, acc.: 52.34%] [G loss: 0.727740]
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1807 [D loss: 0.690751, acc.: 55.47%] [G loss: 0.722263]
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1808 [D loss: 0.687281, acc.: 54.30%] [G loss: 0.726247]
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1809 [D loss: 0.681672, acc.: 58.59%] [G loss: 0.720570]
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1810 [D loss: 0.686640, acc.: 54.10%] [G loss: 0.732534]
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1811 [D loss: 0.686621, acc.: 54.88%] [G loss: 0.708874]
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1812 [D loss: 0.693200, acc.: 50.59%] [G loss: 0.722789]
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1813 [D loss: 0.691192, acc.: 52.93%] [G loss: 0.731320]
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1814 [D loss: 0.686692, acc.: 52.34%] [G loss: 0.735766]
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1815 [D loss: 0.683924, acc.: 57.62%] [G loss: 0.726993]
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1816 [D loss: 0.688533, acc.: 50.78%] [G loss: 0.726637]
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1817 [D loss: 0.692231, acc.: 52.73%] [G loss: 0.729586]
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1818 [D loss: 0.682495, acc.: 59.57%] [G loss: 0.741213]
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1819 [D loss: 0.686643, acc.: 56.64%] [G loss: 0.735703]
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1820 [D loss: 0.682831, acc.: 55.86%] [G loss: 0.739666]
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1821 [D loss: 0.684676, acc.: 56.45%] [G loss: 0.734842]
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1822 [D loss: 0.695195, acc.: 51.56%] [G loss: 0.740114]
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1823 [D loss: 0.685057, acc.: 54.49%] [G loss: 0.733521]
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1824 [D loss: 0.695044, acc.: 52.54%] [G loss: 0.729333]
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1825 [D loss: 0.683938, acc.: 55.27%] [G loss: 0.731732]
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1826 [D loss: 0.685669, acc.: 55.27%] [G loss: 0.728345]
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1827 [D loss: 0.683116, acc.: 56.84%] [G loss: 0.734904]
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1828 [D loss: 0.690127, acc.: 50.20%] [G loss: 0.740246]
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1829 [D loss: 0.687361, acc.: 54.88%] [G loss: 0.741835]
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1830 [D loss: 0.678568, acc.: 58.79%] [G loss: 0.733044]
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1831 [D loss: 0.683795, acc.: 54.69%] [G loss: 0.731410]
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1832 [D loss: 0.695698, acc.: 51.95%] [G loss: 0.716479]
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1833 [D loss: 0.685359, acc.: 56.64%] [G loss: 0.730739]
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1834 [D loss: 0.681668, acc.: 56.45%] [G loss: 0.727519]
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1835 [D loss: 0.687021, acc.: 51.95%] [G loss: 0.718768]
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1836 [D loss: 0.687710, acc.: 53.91%] [G loss: 0.717287]
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1837 [D loss: 0.691947, acc.: 52.93%] [G loss: 0.717840]
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1838 [D loss: 0.685702, acc.: 55.08%] [G loss: 0.719198]
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1839 [D loss: 0.688988, acc.: 53.32%] [G loss: 0.725763]
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1840 [D loss: 0.680849, acc.: 58.20%] [G loss: 0.720846]
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1841 [D loss: 0.688673, acc.: 54.10%] [G loss: 0.717499]
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1842 [D loss: 0.690513, acc.: 51.56%] [G loss: 0.718452]
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1843 [D loss: 0.691767, acc.: 50.00%] [G loss: 0.720398]
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1844 [D loss: 0.680854, acc.: 56.64%] [G loss: 0.741565]
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1845 [D loss: 0.684257, acc.: 54.88%] [G loss: 0.736919]
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1846 [D loss: 0.685670, acc.: 55.08%] [G loss: 0.725135]
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1847 [D loss: 0.691546, acc.: 51.56%] [G loss: 0.728249]
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1848 [D loss: 0.682983, acc.: 55.86%] [G loss: 0.728958]
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1849 [D loss: 0.684404, acc.: 56.25%] [G loss: 0.735928]
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1850 [D loss: 0.682821, acc.: 56.25%] [G loss: 0.736238]
1/1 [==============================] - 0s 16ms/step
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1851 [D loss: 0.677402, acc.: 58.98%] [G loss: 0.728033]
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1852 [D loss: 0.688893, acc.: 52.93%] [G loss: 0.728810]
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1853 [D loss: 0.678584, acc.: 56.45%] [G loss: 0.731002]
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1854 [D loss: 0.691420, acc.: 53.91%] [G loss: 0.730861]
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1855 [D loss: 0.683587, acc.: 56.05%] [G loss: 0.733839]
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1856 [D loss: 0.682854, acc.: 55.66%] [G loss: 0.723842]
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1857 [D loss: 0.689104, acc.: 52.93%] [G loss: 0.729186]
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1858 [D loss: 0.687491, acc.: 52.54%] [G loss: 0.731102]
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1859 [D loss: 0.688768, acc.: 54.69%] [G loss: 0.729476]
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1860 [D loss: 0.682941, acc.: 56.84%] [G loss: 0.728422]
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1861 [D loss: 0.692812, acc.: 50.59%] [G loss: 0.726871]
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1862 [D loss: 0.682066, acc.: 57.62%] [G loss: 0.740915]
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1863 [D loss: 0.690446, acc.: 53.71%] [G loss: 0.728003]
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1864 [D loss: 0.683279, acc.: 52.73%] [G loss: 0.725009]
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1865 [D loss: 0.685369, acc.: 56.25%] [G loss: 0.729474]
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1866 [D loss: 0.690614, acc.: 53.71%] [G loss: 0.721535]
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1867 [D loss: 0.691022, acc.: 53.12%] [G loss: 0.724547]
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1868 [D loss: 0.690457, acc.: 51.76%] [G loss: 0.724974]
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1869 [D loss: 0.691489, acc.: 53.91%] [G loss: 0.736226]
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1870 [D loss: 0.690539, acc.: 52.93%] [G loss: 0.726042]
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1871 [D loss: 0.699769, acc.: 48.24%] [G loss: 0.736975]
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1872 [D loss: 0.687270, acc.: 53.32%] [G loss: 0.736881]
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1873 [D loss: 0.687155, acc.: 53.71%] [G loss: 0.727756]
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1874 [D loss: 0.683937, acc.: 58.79%] [G loss: 0.723102]
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1875 [D loss: 0.687165, acc.: 54.30%] [G loss: 0.720640]
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1876 [D loss: 0.688079, acc.: 54.49%] [G loss: 0.714354]
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1877 [D loss: 0.682637, acc.: 55.27%] [G loss: 0.727361]
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1878 [D loss: 0.688827, acc.: 54.30%] [G loss: 0.722016]
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1879 [D loss: 0.687039, acc.: 55.27%] [G loss: 0.715272]
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1880 [D loss: 0.681430, acc.: 58.20%] [G loss: 0.727306]
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1881 [D loss: 0.682380, acc.: 52.93%] [G loss: 0.731129]
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1882 [D loss: 0.688386, acc.: 54.49%] [G loss: 0.725841]
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1883 [D loss: 0.694201, acc.: 52.54%] [G loss: 0.735388]
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1884 [D loss: 0.685068, acc.: 54.49%] [G loss: 0.730542]
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1885 [D loss: 0.686196, acc.: 56.05%] [G loss: 0.733497]
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1886 [D loss: 0.683241, acc.: 56.45%] [G loss: 0.740266]
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1887 [D loss: 0.694348, acc.: 51.37%] [G loss: 0.731205]
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1888 [D loss: 0.687805, acc.: 54.30%] [G loss: 0.732502]
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1889 [D loss: 0.688161, acc.: 55.47%] [G loss: 0.729052]
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1890 [D loss: 0.684366, acc.: 58.20%] [G loss: 0.718342]
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1891 [D loss: 0.690584, acc.: 53.12%] [G loss: 0.729104]
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1892 [D loss: 0.698804, acc.: 47.66%] [G loss: 0.734671]
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1893 [D loss: 0.686413, acc.: 54.10%] [G loss: 0.728836]
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1894 [D loss: 0.682319, acc.: 54.10%] [G loss: 0.722433]
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1895 [D loss: 0.684870, acc.: 57.42%] [G loss: 0.727996]
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1896 [D loss: 0.682696, acc.: 56.25%] [G loss: 0.734859]
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1897 [D loss: 0.683106, acc.: 56.84%] [G loss: 0.726046]
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1898 [D loss: 0.689519, acc.: 53.71%] [G loss: 0.730508]
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1899 [D loss: 0.693860, acc.: 53.52%] [G loss: 0.730751]
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1900 [D loss: 0.686477, acc.: 54.49%] [G loss: 0.722635]
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1901 [D loss: 0.696180, acc.: 52.54%] [G loss: 0.737838]
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1902 [D loss: 0.690604, acc.: 56.45%] [G loss: 0.721931]
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1903 [D loss: 0.687002, acc.: 54.10%] [G loss: 0.740383]
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1904 [D loss: 0.682635, acc.: 55.08%] [G loss: 0.739381]
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1905 [D loss: 0.677539, acc.: 59.38%] [G loss: 0.737668]
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1906 [D loss: 0.689547, acc.: 54.88%] [G loss: 0.736868]
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1907 [D loss: 0.694344, acc.: 52.54%] [G loss: 0.722843]
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1908 [D loss: 0.689875, acc.: 53.52%] [G loss: 0.731417]
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1909 [D loss: 0.682318, acc.: 55.66%] [G loss: 0.731134]
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1910 [D loss: 0.684515, acc.: 56.05%] [G loss: 0.724723]
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1911 [D loss: 0.689712, acc.: 52.15%] [G loss: 0.716025]
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1912 [D loss: 0.692060, acc.: 50.98%] [G loss: 0.716619]
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1913 [D loss: 0.688297, acc.: 52.54%] [G loss: 0.717177]
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1914 [D loss: 0.688391, acc.: 54.88%] [G loss: 0.726344]
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1915 [D loss: 0.681515, acc.: 58.40%] [G loss: 0.731787]
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1916 [D loss: 0.684423, acc.: 56.05%] [G loss: 0.742853]
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1917 [D loss: 0.686988, acc.: 53.12%] [G loss: 0.726002]
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1918 [D loss: 0.690801, acc.: 52.93%] [G loss: 0.731080]
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1919 [D loss: 0.679605, acc.: 56.25%] [G loss: 0.723155]
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1920 [D loss: 0.682698, acc.: 58.20%] [G loss: 0.731936]
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1921 [D loss: 0.693876, acc.: 48.44%] [G loss: 0.723159]
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1922 [D loss: 0.682868, acc.: 55.66%] [G loss: 0.727031]
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1923 [D loss: 0.683667, acc.: 54.49%] [G loss: 0.725072]
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1924 [D loss: 0.683516, acc.: 56.25%] [G loss: 0.728004]
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1925 [D loss: 0.688015, acc.: 55.47%] [G loss: 0.728667]
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1926 [D loss: 0.691668, acc.: 52.34%] [G loss: 0.726941]
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1927 [D loss: 0.686534, acc.: 54.49%] [G loss: 0.722256]
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1928 [D loss: 0.691543, acc.: 50.00%] [G loss: 0.725657]
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1929 [D loss: 0.687893, acc.: 56.25%] [G loss: 0.724079]
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1930 [D loss: 0.690484, acc.: 54.10%] [G loss: 0.729973]
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1931 [D loss: 0.689826, acc.: 52.54%] [G loss: 0.731916]
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1932 [D loss: 0.685228, acc.: 54.10%] [G loss: 0.735575]
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1933 [D loss: 0.691505, acc.: 51.56%] [G loss: 0.727569]
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1934 [D loss: 0.684429, acc.: 54.88%] [G loss: 0.727089]
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1935 [D loss: 0.686076, acc.: 52.93%] [G loss: 0.719851]
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1936 [D loss: 0.691876, acc.: 51.76%] [G loss: 0.732841]
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1937 [D loss: 0.682721, acc.: 54.49%] [G loss: 0.731095]
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1938 [D loss: 0.689198, acc.: 53.91%] [G loss: 0.726412]
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1939 [D loss: 0.691614, acc.: 51.76%] [G loss: 0.719532]
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1940 [D loss: 0.688926, acc.: 53.71%] [G loss: 0.714923]
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1941 [D loss: 0.682464, acc.: 56.25%] [G loss: 0.730353]
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1942 [D loss: 0.689627, acc.: 55.27%] [G loss: 0.725602]
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1943 [D loss: 0.686328, acc.: 51.56%] [G loss: 0.713497]
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1944 [D loss: 0.689803, acc.: 54.69%] [G loss: 0.721183]
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1945 [D loss: 0.685558, acc.: 57.03%] [G loss: 0.731841]
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1946 [D loss: 0.695258, acc.: 50.98%] [G loss: 0.739342]
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1947 [D loss: 0.687261, acc.: 57.81%] [G loss: 0.739501]
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1948 [D loss: 0.690457, acc.: 51.17%] [G loss: 0.732635]
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1949 [D loss: 0.686683, acc.: 57.03%] [G loss: 0.727211]
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1950 [D loss: 0.682853, acc.: 57.42%] [G loss: 0.739771]
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1951 [D loss: 0.680648, acc.: 56.64%] [G loss: 0.725740]
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1952 [D loss: 0.685542, acc.: 55.66%] [G loss: 0.734375]
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1953 [D loss: 0.685002, acc.: 54.88%] [G loss: 0.732299]
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1954 [D loss: 0.691511, acc.: 50.59%] [G loss: 0.737229]
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1955 [D loss: 0.681116, acc.: 57.42%] [G loss: 0.736555]
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1956 [D loss: 0.685941, acc.: 51.95%] [G loss: 0.733236]
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1957 [D loss: 0.680931, acc.: 56.64%] [G loss: 0.723491]
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1958 [D loss: 0.683336, acc.: 56.45%] [G loss: 0.729670]
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1959 [D loss: 0.684645, acc.: 54.30%] [G loss: 0.729167]
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1960 [D loss: 0.689856, acc.: 52.54%] [G loss: 0.727123]
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1961 [D loss: 0.683689, acc.: 54.30%] [G loss: 0.727995]
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1962 [D loss: 0.695624, acc.: 52.15%] [G loss: 0.723386]
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1963 [D loss: 0.691663, acc.: 52.93%] [G loss: 0.721620]
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1964 [D loss: 0.689986, acc.: 54.10%] [G loss: 0.728524]
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1965 [D loss: 0.693725, acc.: 49.41%] [G loss: 0.732328]
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1966 [D loss: 0.688021, acc.: 55.86%] [G loss: 0.723947]
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1967 [D loss: 0.687727, acc.: 53.71%] [G loss: 0.727107]
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1968 [D loss: 0.688863, acc.: 54.88%] [G loss: 0.722583]
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1969 [D loss: 0.688998, acc.: 52.54%] [G loss: 0.733298]
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1970 [D loss: 0.690941, acc.: 54.30%] [G loss: 0.729751]
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1971 [D loss: 0.686826, acc.: 53.52%] [G loss: 0.722917]
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1972 [D loss: 0.690402, acc.: 53.12%] [G loss: 0.727015]
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1973 [D loss: 0.686634, acc.: 53.71%] [G loss: 0.732725]
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1974 [D loss: 0.684357, acc.: 57.81%] [G loss: 0.737952]
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1975 [D loss: 0.685373, acc.: 55.66%] [G loss: 0.732174]
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1976 [D loss: 0.683254, acc.: 55.86%] [G loss: 0.738317]
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1977 [D loss: 0.685790, acc.: 54.69%] [G loss: 0.737543]
8/8 [==============================] - 0s 2ms/step
1978 [D loss: 0.689434, acc.: 54.69%] [G loss: 0.736784]
8/8 [==============================] - 0s 3ms/step
1979 [D loss: 0.680797, acc.: 58.01%] [G loss: 0.735856]
8/8 [==============================] - 0s 2ms/step
1980 [D loss: 0.688143, acc.: 55.66%] [G loss: 0.727336]
8/8 [==============================] - 0s 2ms/step
1981 [D loss: 0.688694, acc.: 54.30%] [G loss: 0.737913]
8/8 [==============================] - 0s 2ms/step
1982 [D loss: 0.693027, acc.: 53.52%] [G loss: 0.719363]
8/8 [==============================] - 0s 2ms/step
1983 [D loss: 0.690205, acc.: 51.95%] [G loss: 0.722595]
8/8 [==============================] - 0s 2ms/step
1984 [D loss: 0.686692, acc.: 55.47%] [G loss: 0.716993]
8/8 [==============================] - 0s 2ms/step
1985 [D loss: 0.687238, acc.: 57.03%] [G loss: 0.713933]
8/8 [==============================] - 0s 2ms/step
1986 [D loss: 0.688377, acc.: 54.10%] [G loss: 0.715673]
8/8 [==============================] - 0s 2ms/step
1987 [D loss: 0.691106, acc.: 53.52%] [G loss: 0.725400]
8/8 [==============================] - 0s 2ms/step
1988 [D loss: 0.687612, acc.: 51.56%] [G loss: 0.720436]
8/8 [==============================] - 0s 2ms/step
1989 [D loss: 0.687073, acc.: 56.25%] [G loss: 0.719942]
8/8 [==============================] - 0s 2ms/step
1990 [D loss: 0.687124, acc.: 53.32%] [G loss: 0.727000]
8/8 [==============================] - 0s 2ms/step
1991 [D loss: 0.681684, acc.: 58.59%] [G loss: 0.720114]
8/8 [==============================] - 0s 2ms/step
1992 [D loss: 0.693811, acc.: 50.00%] [G loss: 0.728784]
8/8 [==============================] - 0s 2ms/step
1993 [D loss: 0.692465, acc.: 54.69%] [G loss: 0.718335]
8/8 [==============================] - 0s 2ms/step
1994 [D loss: 0.701263, acc.: 48.24%] [G loss: 0.728567]
8/8 [==============================] - 0s 2ms/step
1995 [D loss: 0.688045, acc.: 56.64%] [G loss: 0.719805]
8/8 [==============================] - 0s 2ms/step
1996 [D loss: 0.684056, acc.: 55.47%] [G loss: 0.732958]
8/8 [==============================] - 0s 2ms/step
1997 [D loss: 0.686027, acc.: 55.86%] [G loss: 0.724622]
8/8 [==============================] - 0s 2ms/step
1998 [D loss: 0.690274, acc.: 51.95%] [G loss: 0.723094]
8/8 [==============================] - 0s 2ms/step
1999 [D loss: 0.686080, acc.: 54.69%] [G loss: 0.733988]
8/8 [==============================] - 0s 2ms/step
2000 [D loss: 0.685957, acc.: 53.32%] [G loss: 0.732644]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
2001 [D loss: 0.690231, acc.: 54.88%] [G loss: 0.732402]
8/8 [==============================] - 0s 2ms/step
2002 [D loss: 0.690080, acc.: 51.76%] [G loss: 0.734782]
8/8 [==============================] - 0s 2ms/step
2003 [D loss: 0.682996, acc.: 56.45%] [G loss: 0.729888]
8/8 [==============================] - 0s 2ms/step
2004 [D loss: 0.680488, acc.: 58.20%] [G loss: 0.740559]
8/8 [==============================] - 0s 2ms/step
2005 [D loss: 0.690025, acc.: 54.30%] [G loss: 0.733378]
8/8 [==============================] - 0s 2ms/step
2006 [D loss: 0.685036, acc.: 55.27%] [G loss: 0.735379]
8/8 [==============================] - 0s 2ms/step
2007 [D loss: 0.684872, acc.: 54.49%] [G loss: 0.740367]
8/8 [==============================] - 0s 2ms/step
2008 [D loss: 0.678824, acc.: 59.18%] [G loss: 0.737342]
8/8 [==============================] - 0s 2ms/step
2009 [D loss: 0.694119, acc.: 51.56%] [G loss: 0.737575]
8/8 [==============================] - 0s 2ms/step
2010 [D loss: 0.682881, acc.: 55.08%] [G loss: 0.739533]
8/8 [==============================] - 0s 2ms/step
2011 [D loss: 0.683378, acc.: 55.27%] [G loss: 0.730158]
8/8 [==============================] - 0s 2ms/step
2012 [D loss: 0.692626, acc.: 50.59%] [G loss: 0.729204]
8/8 [==============================] - 0s 2ms/step
2013 [D loss: 0.681075, acc.: 59.77%] [G loss: 0.727975]
8/8 [==============================] - 0s 2ms/step
2014 [D loss: 0.688184, acc.: 51.95%] [G loss: 0.732091]
8/8 [==============================] - 0s 2ms/step
2015 [D loss: 0.688413, acc.: 54.10%] [G loss: 0.722621]
8/8 [==============================] - 0s 2ms/step
2016 [D loss: 0.686302, acc.: 55.47%] [G loss: 0.717460]
8/8 [==============================] - 0s 2ms/step
2017 [D loss: 0.686493, acc.: 54.10%] [G loss: 0.732476]
8/8 [==============================] - 0s 2ms/step
2018 [D loss: 0.691945, acc.: 51.17%] [G loss: 0.730550]
8/8 [==============================] - 0s 2ms/step
2019 [D loss: 0.692451, acc.: 52.54%] [G loss: 0.726875]
8/8 [==============================] - 0s 3ms/step
2020 [D loss: 0.689392, acc.: 51.37%] [G loss: 0.721937]
8/8 [==============================] - 0s 2ms/step
2021 [D loss: 0.684615, acc.: 56.05%] [G loss: 0.722575]
8/8 [==============================] - 0s 2ms/step
2022 [D loss: 0.688596, acc.: 54.30%] [G loss: 0.717549]
8/8 [==============================] - 0s 2ms/step
2023 [D loss: 0.686195, acc.: 55.27%] [G loss: 0.721489]
8/8 [==============================] - 0s 2ms/step
2024 [D loss: 0.687083, acc.: 52.93%] [G loss: 0.725357]
8/8 [==============================] - 0s 2ms/step
2025 [D loss: 0.687433, acc.: 56.64%] [G loss: 0.726274]
8/8 [==============================] - 0s 2ms/step
2026 [D loss: 0.685645, acc.: 54.88%] [G loss: 0.730430]
8/8 [==============================] - 0s 2ms/step
2027 [D loss: 0.689133, acc.: 53.32%] [G loss: 0.732298]
8/8 [==============================] - 0s 2ms/step
2028 [D loss: 0.682173, acc.: 55.86%] [G loss: 0.734576]
8/8 [==============================] - 0s 2ms/step
2029 [D loss: 0.683696, acc.: 55.86%] [G loss: 0.733121]
8/8 [==============================] - 0s 2ms/step
2030 [D loss: 0.680653, acc.: 56.64%] [G loss: 0.733770]
8/8 [==============================] - 0s 2ms/step
2031 [D loss: 0.683348, acc.: 55.86%] [G loss: 0.734890]
8/8 [==============================] - 0s 2ms/step
2032 [D loss: 0.687990, acc.: 54.69%] [G loss: 0.734808]
8/8 [==============================] - 0s 2ms/step
2033 [D loss: 0.688197, acc.: 52.93%] [G loss: 0.725597]
8/8 [==============================] - 0s 2ms/step
2034 [D loss: 0.688027, acc.: 50.78%] [G loss: 0.734163]
8/8 [==============================] - 0s 2ms/step
2035 [D loss: 0.681567, acc.: 56.05%] [G loss: 0.737248]
8/8 [==============================] - 0s 2ms/step
2036 [D loss: 0.687069, acc.: 54.88%] [G loss: 0.725505]
8/8 [==============================] - 0s 2ms/step
2037 [D loss: 0.684193, acc.: 55.47%] [G loss: 0.721639]
8/8 [==============================] - 0s 2ms/step
2038 [D loss: 0.683097, acc.: 56.64%] [G loss: 0.731797]
8/8 [==============================] - 0s 2ms/step
2039 [D loss: 0.691103, acc.: 50.78%] [G loss: 0.723722]
8/8 [==============================] - 0s 2ms/step
2040 [D loss: 0.692224, acc.: 52.34%] [G loss: 0.739808]
8/8 [==============================] - 0s 2ms/step
2041 [D loss: 0.687400, acc.: 53.52%] [G loss: 0.733694]
8/8 [==============================] - 0s 2ms/step
2042 [D loss: 0.687045, acc.: 53.91%] [G loss: 0.733923]
8/8 [==============================] - 0s 2ms/step
2043 [D loss: 0.689017, acc.: 54.30%] [G loss: 0.732912]
8/8 [==============================] - 0s 2ms/step
2044 [D loss: 0.675653, acc.: 61.91%] [G loss: 0.731648]
8/8 [==============================] - 0s 3ms/step
2045 [D loss: 0.687320, acc.: 52.73%] [G loss: 0.714256]
8/8 [==============================] - 0s 2ms/step
2046 [D loss: 0.687258, acc.: 52.54%] [G loss: 0.724077]
8/8 [==============================] - 0s 2ms/step
2047 [D loss: 0.682872, acc.: 54.49%] [G loss: 0.709289]
8/8 [==============================] - 0s 2ms/step
2048 [D loss: 0.696339, acc.: 50.98%] [G loss: 0.717893]
8/8 [==============================] - 0s 2ms/step
2049 [D loss: 0.691662, acc.: 53.12%] [G loss: 0.731096]
8/8 [==============================] - 0s 2ms/step
2050 [D loss: 0.680139, acc.: 55.86%] [G loss: 0.731350]
1/1 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 2ms/step
2051 [D loss: 0.688628, acc.: 55.86%] [G loss: 0.731066]
8/8 [==============================] - 0s 2ms/step
2052 [D loss: 0.691111, acc.: 52.15%] [G loss: 0.738177]
8/8 [==============================] - 0s 2ms/step
2053 [D loss: 0.686077, acc.: 54.30%] [G loss: 0.730895]
8/8 [==============================] - 0s 2ms/step
2054 [D loss: 0.685974, acc.: 55.66%] [G loss: 0.719654]
8/8 [==============================] - 0s 2ms/step
2055 [D loss: 0.685665, acc.: 53.52%] [G loss: 0.721553]
8/8 [==============================] - 0s 2ms/step
2056 [D loss: 0.680930, acc.: 58.40%] [G loss: 0.717385]
8/8 [==============================] - 0s 2ms/step
2057 [D loss: 0.685198, acc.: 54.69%] [G loss: 0.722467]
8/8 [==============================] - 0s 2ms/step
2058 [D loss: 0.688322, acc.: 54.10%] [G loss: 0.718578]
8/8 [==============================] - 0s 2ms/step
2059 [D loss: 0.685053, acc.: 53.12%] [G loss: 0.716838]
8/8 [==============================] - 0s 2ms/step
2060 [D loss: 0.686533, acc.: 54.88%] [G loss: 0.727338]
8/8 [==============================] - 0s 2ms/step
2061 [D loss: 0.684300, acc.: 56.64%] [G loss: 0.716406]
8/8 [==============================] - 0s 2ms/step
2062 [D loss: 0.688381, acc.: 52.54%] [G loss: 0.730384]
8/8 [==============================] - 0s 2ms/step
2063 [D loss: 0.689312, acc.: 55.47%] [G loss: 0.731921]
8/8 [==============================] - 0s 2ms/step
2064 [D loss: 0.683417, acc.: 56.05%] [G loss: 0.732375]
8/8 [==============================] - 0s 2ms/step
2065 [D loss: 0.688533, acc.: 55.08%] [G loss: 0.727394]
8/8 [==============================] - 0s 2ms/step
2066 [D loss: 0.687570, acc.: 54.10%] [G loss: 0.733825]
8/8 [==============================] - 0s 2ms/step
2067 [D loss: 0.686710, acc.: 54.88%] [G loss: 0.732857]
8/8 [==============================] - 0s 2ms/step
2068 [D loss: 0.691319, acc.: 55.08%] [G loss: 0.734246]
8/8 [==============================] - 0s 3ms/step
2069 [D loss: 0.694098, acc.: 52.73%] [G loss: 0.730912]
8/8 [==============================] - 0s 2ms/step
2070 [D loss: 0.682574, acc.: 57.23%] [G loss: 0.730150]
8/8 [==============================] - 0s 2ms/step
2071 [D loss: 0.688063, acc.: 53.12%] [G loss: 0.733704]
8/8 [==============================] - 0s 2ms/step
2072 [D loss: 0.683866, acc.: 55.86%] [G loss: 0.727398]
8/8 [==============================] - 0s 2ms/step
2073 [D loss: 0.684992, acc.: 54.69%] [G loss: 0.738602]
8/8 [==============================] - 0s 2ms/step
2074 [D loss: 0.686059, acc.: 56.05%] [G loss: 0.730636]
8/8 [==============================] - 0s 2ms/step
2075 [D loss: 0.683628, acc.: 55.08%] [G loss: 0.733916]
8/8 [==============================] - 0s 2ms/step
2076 [D loss: 0.687804, acc.: 51.17%] [G loss: 0.735175]
8/8 [==============================] - 0s 2ms/step
2077 [D loss: 0.693916, acc.: 50.39%] [G loss: 0.742312]
8/8 [==============================] - 0s 2ms/step
2078 [D loss: 0.685676, acc.: 53.71%] [G loss: 0.728737]
8/8 [==============================] - 0s 2ms/step
2079 [D loss: 0.685312, acc.: 58.01%] [G loss: 0.730266]
8/8 [==============================] - 0s 2ms/step
2080 [D loss: 0.682399, acc.: 55.86%] [G loss: 0.730328]
8/8 [==============================] - 0s 2ms/step
2081 [D loss: 0.686928, acc.: 54.30%] [G loss: 0.730010]
8/8 [==============================] - 0s 2ms/step
2082 [D loss: 0.687613, acc.: 53.52%] [G loss: 0.725122]
8/8 [==============================] - 0s 2ms/step
2083 [D loss: 0.691285, acc.: 52.54%] [G loss: 0.722534]
8/8 [==============================] - 0s 2ms/step
2084 [D loss: 0.686054, acc.: 54.88%] [G loss: 0.732747]
8/8 [==============================] - 0s 2ms/step
2085 [D loss: 0.684246, acc.: 55.86%] [G loss: 0.729448]
8/8 [==============================] - 0s 2ms/step
2086 [D loss: 0.687471, acc.: 53.71%] [G loss: 0.727706]
8/8 [==============================] - 0s 2ms/step
2087 [D loss: 0.696568, acc.: 48.63%] [G loss: 0.727604]
8/8 [==============================] - 0s 2ms/step
2088 [D loss: 0.682537, acc.: 58.59%] [G loss: 0.718690]
8/8 [==============================] - 0s 2ms/step
2089 [D loss: 0.687974, acc.: 55.27%] [G loss: 0.719106]
8/8 [==============================] - 0s 2ms/step
2090 [D loss: 0.691421, acc.: 53.71%] [G loss: 0.724335]
8/8 [==============================] - 0s 2ms/step
2091 [D loss: 0.686151, acc.: 55.86%] [G loss: 0.738716]
8/8 [==============================] - 0s 2ms/step
2092 [D loss: 0.691220, acc.: 51.95%] [G loss: 0.732641]
8/8 [==============================] - 0s 2ms/step
2093 [D loss: 0.683043, acc.: 55.47%] [G loss: 0.730305]
8/8 [==============================] - 0s 2ms/step
2094 [D loss: 0.689534, acc.: 51.76%] [G loss: 0.726553]
8/8 [==============================] - 0s 2ms/step
2095 [D loss: 0.687716, acc.: 52.73%] [G loss: 0.726207]
8/8 [==============================] - 0s 2ms/step
2096 [D loss: 0.692108, acc.: 53.12%] [G loss: 0.722401]
8/8 [==============================] - 0s 2ms/step
2097 [D loss: 0.689943, acc.: 51.76%] [G loss: 0.731700]
8/8 [==============================] - 0s 2ms/step
2098 [D loss: 0.687756, acc.: 52.73%] [G loss: 0.726770]
8/8 [==============================] - 0s 2ms/step
2099 [D loss: 0.689281, acc.: 56.05%] [G loss: 0.717784]
8/8 [==============================] - 0s 2ms/step
2100 [D loss: 0.680658, acc.: 56.25%] [G loss: 0.727801]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
2101 [D loss: 0.688094, acc.: 53.91%] [G loss: 0.726544]
8/8 [==============================] - 0s 2ms/step
2102 [D loss: 0.684348, acc.: 57.23%] [G loss: 0.721051]
8/8 [==============================] - 0s 3ms/step
2103 [D loss: 0.691267, acc.: 51.17%] [G loss: 0.731599]
8/8 [==============================] - 0s 2ms/step
2104 [D loss: 0.683076, acc.: 55.47%] [G loss: 0.726636]
8/8 [==============================] - 0s 2ms/step
2105 [D loss: 0.686580, acc.: 55.47%] [G loss: 0.727064]
8/8 [==============================] - 0s 2ms/step
2106 [D loss: 0.689217, acc.: 53.12%] [G loss: 0.717555]
8/8 [==============================] - 0s 2ms/step
2107 [D loss: 0.688972, acc.: 51.95%] [G loss: 0.731475]
8/8 [==============================] - 0s 2ms/step
2108 [D loss: 0.687228, acc.: 56.45%] [G loss: 0.725593]
8/8 [==============================] - 0s 2ms/step
2109 [D loss: 0.687253, acc.: 57.03%] [G loss: 0.724260]
8/8 [==============================] - 0s 2ms/step
2110 [D loss: 0.691430, acc.: 55.47%] [G loss: 0.720770]
8/8 [==============================] - 0s 2ms/step
2111 [D loss: 0.686666, acc.: 55.47%] [G loss: 0.723244]
8/8 [==============================] - 0s 2ms/step
2112 [D loss: 0.682757, acc.: 57.23%] [G loss: 0.730349]
8/8 [==============================] - 0s 2ms/step
2113 [D loss: 0.686752, acc.: 54.88%] [G loss: 0.722332]
8/8 [==============================] - 0s 2ms/step
2114 [D loss: 0.682993, acc.: 58.40%] [G loss: 0.734238]
8/8 [==============================] - 0s 2ms/step
2115 [D loss: 0.689492, acc.: 55.47%] [G loss: 0.722040]
8/8 [==============================] - 0s 3ms/step
2116 [D loss: 0.684718, acc.: 52.73%] [G loss: 0.732309]
8/8 [==============================] - 0s 2ms/step
2117 [D loss: 0.682713, acc.: 58.01%] [G loss: 0.731811]
8/8 [==============================] - 0s 2ms/step
2118 [D loss: 0.687552, acc.: 56.25%] [G loss: 0.737578]
8/8 [==============================] - 0s 2ms/step
2119 [D loss: 0.685953, acc.: 55.86%] [G loss: 0.735090]
8/8 [==============================] - 0s 2ms/step
2120 [D loss: 0.688071, acc.: 53.32%] [G loss: 0.731417]
8/8 [==============================] - 0s 2ms/step
2121 [D loss: 0.690427, acc.: 54.49%] [G loss: 0.734659]
8/8 [==============================] - 0s 2ms/step
2122 [D loss: 0.692770, acc.: 53.52%] [G loss: 0.729648]
8/8 [==============================] - 0s 2ms/step
2123 [D loss: 0.688842, acc.: 54.88%] [G loss: 0.725305]
8/8 [==============================] - 0s 2ms/step
2124 [D loss: 0.686220, acc.: 53.91%] [G loss: 0.725437]
8/8 [==============================] - 0s 2ms/step
2125 [D loss: 0.685315, acc.: 55.66%] [G loss: 0.711384]
8/8 [==============================] - 0s 2ms/step
2126 [D loss: 0.697540, acc.: 50.20%] [G loss: 0.707531]
8/8 [==============================] - 0s 3ms/step
2127 [D loss: 0.689875, acc.: 54.30%] [G loss: 0.721590]
8/8 [==============================] - 0s 2ms/step
2128 [D loss: 0.698547, acc.: 48.83%] [G loss: 0.723332]
8/8 [==============================] - 0s 2ms/step
2129 [D loss: 0.684309, acc.: 56.25%] [G loss: 0.719576]
8/8 [==============================] - 0s 2ms/step
2130 [D loss: 0.686337, acc.: 56.05%] [G loss: 0.741470]
8/8 [==============================] - 0s 2ms/step
2131 [D loss: 0.681898, acc.: 56.45%] [G loss: 0.731507]
8/8 [==============================] - 0s 2ms/step
2132 [D loss: 0.683960, acc.: 53.12%] [G loss: 0.737138]
8/8 [==============================] - 0s 2ms/step
2133 [D loss: 0.690099, acc.: 54.88%] [G loss: 0.738675]
8/8 [==============================] - 0s 2ms/step
2134 [D loss: 0.684728, acc.: 55.27%] [G loss: 0.741930]
8/8 [==============================] - 0s 2ms/step
2135 [D loss: 0.683389, acc.: 54.10%] [G loss: 0.738203]
8/8 [==============================] - 0s 2ms/step
2136 [D loss: 0.685104, acc.: 54.30%] [G loss: 0.737924]
8/8 [==============================] - 0s 2ms/step
2137 [D loss: 0.684730, acc.: 56.45%] [G loss: 0.720514]
8/8 [==============================] - 0s 2ms/step
2138 [D loss: 0.690322, acc.: 52.93%] [G loss: 0.733584]
8/8 [==============================] - 0s 2ms/step
2139 [D loss: 0.675785, acc.: 58.98%] [G loss: 0.724732]
8/8 [==============================] - 0s 2ms/step
2140 [D loss: 0.687022, acc.: 53.91%] [G loss: 0.718444]
8/8 [==============================] - 0s 2ms/step
2141 [D loss: 0.684050, acc.: 54.10%] [G loss: 0.702524]
8/8 [==============================] - 0s 2ms/step
2142 [D loss: 0.683100, acc.: 57.62%] [G loss: 0.707722]
8/8 [==============================] - 0s 2ms/step
2143 [D loss: 0.688473, acc.: 52.34%] [G loss: 0.705260]
8/8 [==============================] - 0s 2ms/step
2144 [D loss: 0.678945, acc.: 57.81%] [G loss: 0.708702]
8/8 [==============================] - 0s 2ms/step
2145 [D loss: 0.685884, acc.: 56.05%] [G loss: 0.711389]
8/8 [==============================] - 0s 2ms/step
2146 [D loss: 0.687945, acc.: 56.45%] [G loss: 0.718158]
8/8 [==============================] - 0s 2ms/step
2147 [D loss: 0.683897, acc.: 57.42%] [G loss: 0.709896]
8/8 [==============================] - 0s 2ms/step
2148 [D loss: 0.685477, acc.: 54.69%] [G loss: 0.725137]
8/8 [==============================] - 0s 2ms/step
2149 [D loss: 0.691117, acc.: 51.37%] [G loss: 0.734133]
8/8 [==============================] - 0s 2ms/step
2150 [D loss: 0.688167, acc.: 53.12%] [G loss: 0.731424]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 2ms/step
2151 [D loss: 0.685401, acc.: 55.47%] [G loss: 0.728147]
8/8 [==============================] - 0s 2ms/step
2152 [D loss: 0.685821, acc.: 57.03%] [G loss: 0.741564]
8/8 [==============================] - 0s 2ms/step
2153 [D loss: 0.690779, acc.: 52.93%] [G loss: 0.724653]
8/8 [==============================] - 0s 2ms/step
2154 [D loss: 0.684432, acc.: 55.86%] [G loss: 0.731226]
8/8 [==============================] - 0s 2ms/step
2155 [D loss: 0.693184, acc.: 51.56%] [G loss: 0.731958]
8/8 [==============================] - 0s 2ms/step
2156 [D loss: 0.687359, acc.: 52.73%] [G loss: 0.728730]
8/8 [==============================] - 0s 2ms/step
2157 [D loss: 0.682642, acc.: 56.25%] [G loss: 0.712920]
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2158 [D loss: 0.690029, acc.: 51.95%] [G loss: 0.720905]
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2159 [D loss: 0.683196, acc.: 58.79%] [G loss: 0.727168]
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2160 [D loss: 0.682846, acc.: 57.42%] [G loss: 0.734346]
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2161 [D loss: 0.691008, acc.: 51.95%] [G loss: 0.736499]
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2162 [D loss: 0.685506, acc.: 54.49%] [G loss: 0.739684]
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2163 [D loss: 0.691660, acc.: 50.98%] [G loss: 0.731176]
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2164 [D loss: 0.680102, acc.: 58.01%] [G loss: 0.734469]
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2165 [D loss: 0.686038, acc.: 54.49%] [G loss: 0.732806]
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2166 [D loss: 0.677787, acc.: 59.18%] [G loss: 0.729800]
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2167 [D loss: 0.683554, acc.: 58.40%] [G loss: 0.718453]
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2168 [D loss: 0.686261, acc.: 54.10%] [G loss: 0.718811]
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2169 [D loss: 0.684753, acc.: 55.27%] [G loss: 0.719077]
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2170 [D loss: 0.691000, acc.: 53.32%] [G loss: 0.720431]
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2171 [D loss: 0.681904, acc.: 54.88%] [G loss: 0.737500]
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2172 [D loss: 0.686664, acc.: 53.12%] [G loss: 0.726346]
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2173 [D loss: 0.687332, acc.: 53.52%] [G loss: 0.731116]
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2174 [D loss: 0.690876, acc.: 55.47%] [G loss: 0.727899]
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2175 [D loss: 0.696664, acc.: 50.59%] [G loss: 0.724048]
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2176 [D loss: 0.692548, acc.: 50.98%] [G loss: 0.723638]
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2177 [D loss: 0.694081, acc.: 51.76%] [G loss: 0.730139]
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2178 [D loss: 0.681454, acc.: 56.45%] [G loss: 0.721282]
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2179 [D loss: 0.692516, acc.: 50.00%] [G loss: 0.720520]
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2180 [D loss: 0.687724, acc.: 53.32%] [G loss: 0.729289]
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2181 [D loss: 0.685052, acc.: 57.42%] [G loss: 0.738421]
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2182 [D loss: 0.686280, acc.: 54.88%] [G loss: 0.740321]
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2183 [D loss: 0.684509, acc.: 56.05%] [G loss: 0.737016]
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2184 [D loss: 0.686517, acc.: 55.47%] [G loss: 0.731918]
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2185 [D loss: 0.683499, acc.: 57.23%] [G loss: 0.728171]
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2186 [D loss: 0.684463, acc.: 55.47%] [G loss: 0.720837]
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2187 [D loss: 0.687440, acc.: 54.49%] [G loss: 0.728062]
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2188 [D loss: 0.682249, acc.: 57.62%] [G loss: 0.716298]
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2189 [D loss: 0.683813, acc.: 55.27%] [G loss: 0.727921]
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2190 [D loss: 0.692406, acc.: 52.93%] [G loss: 0.721285]
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2191 [D loss: 0.690019, acc.: 53.91%] [G loss: 0.732945]
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2192 [D loss: 0.690079, acc.: 54.10%] [G loss: 0.743296]
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2193 [D loss: 0.691294, acc.: 53.71%] [G loss: 0.734403]
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2194 [D loss: 0.681476, acc.: 56.64%] [G loss: 0.734157]
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2195 [D loss: 0.685452, acc.: 56.25%] [G loss: 0.736225]
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2196 [D loss: 0.688196, acc.: 53.71%] [G loss: 0.727275]
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2197 [D loss: 0.695831, acc.: 49.22%] [G loss: 0.722113]
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2198 [D loss: 0.686426, acc.: 54.88%] [G loss: 0.736235]
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2199 [D loss: 0.690158, acc.: 52.34%] [G loss: 0.724097]
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2200 [D loss: 0.688350, acc.: 55.66%] [G loss: 0.728221]
1/1 [==============================] - 0s 16ms/step
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2201 [D loss: 0.684126, acc.: 53.52%] [G loss: 0.726183]
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2202 [D loss: 0.683018, acc.: 55.47%] [G loss: 0.725829]
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2203 [D loss: 0.690120, acc.: 52.54%] [G loss: 0.718274]
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2204 [D loss: 0.685907, acc.: 54.69%] [G loss: 0.720564]
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2205 [D loss: 0.688399, acc.: 51.76%] [G loss: 0.735287]
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2206 [D loss: 0.680700, acc.: 56.84%] [G loss: 0.723445]
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2207 [D loss: 0.688047, acc.: 56.45%] [G loss: 0.736378]
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2208 [D loss: 0.682614, acc.: 56.05%] [G loss: 0.725992]
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2209 [D loss: 0.689532, acc.: 52.93%] [G loss: 0.723167]
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2210 [D loss: 0.685626, acc.: 54.30%] [G loss: 0.724214]
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2211 [D loss: 0.683771, acc.: 54.88%] [G loss: 0.724652]
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2212 [D loss: 0.687048, acc.: 54.88%] [G loss: 0.722800]
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2213 [D loss: 0.679066, acc.: 58.98%] [G loss: 0.724778]
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2214 [D loss: 0.688410, acc.: 55.27%] [G loss: 0.728068]
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2215 [D loss: 0.679888, acc.: 57.42%] [G loss: 0.737643]
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2216 [D loss: 0.680313, acc.: 53.91%] [G loss: 0.733377]
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2217 [D loss: 0.695037, acc.: 51.95%] [G loss: 0.743127]
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2218 [D loss: 0.691897, acc.: 51.95%] [G loss: 0.729507]
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2219 [D loss: 0.690460, acc.: 53.32%] [G loss: 0.724226]
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2220 [D loss: 0.691482, acc.: 53.32%] [G loss: 0.724541]
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2221 [D loss: 0.693759, acc.: 54.30%] [G loss: 0.714583]
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2222 [D loss: 0.684101, acc.: 55.08%] [G loss: 0.715053]
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2223 [D loss: 0.686286, acc.: 55.27%] [G loss: 0.710437]
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2224 [D loss: 0.686239, acc.: 52.93%] [G loss: 0.714401]
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2225 [D loss: 0.694519, acc.: 53.32%] [G loss: 0.723182]
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2226 [D loss: 0.685409, acc.: 54.69%] [G loss: 0.721478]
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2227 [D loss: 0.684744, acc.: 56.05%] [G loss: 0.728714]
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2228 [D loss: 0.689629, acc.: 54.69%] [G loss: 0.714215]
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2229 [D loss: 0.689409, acc.: 53.32%] [G loss: 0.720461]
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2230 [D loss: 0.693465, acc.: 51.17%] [G loss: 0.721472]
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2231 [D loss: 0.687848, acc.: 54.69%] [G loss: 0.717184]
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2232 [D loss: 0.691400, acc.: 53.71%] [G loss: 0.720066]
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2233 [D loss: 0.686279, acc.: 56.05%] [G loss: 0.730000]
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2234 [D loss: 0.689357, acc.: 53.52%] [G loss: 0.731384]
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2235 [D loss: 0.682672, acc.: 55.66%] [G loss: 0.733437]
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2236 [D loss: 0.682104, acc.: 58.59%] [G loss: 0.730356]
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2237 [D loss: 0.686989, acc.: 55.47%] [G loss: 0.736553]
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2238 [D loss: 0.683611, acc.: 56.84%] [G loss: 0.735613]
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2239 [D loss: 0.683592, acc.: 52.34%] [G loss: 0.739719]
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2240 [D loss: 0.690027, acc.: 51.95%] [G loss: 0.723701]
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2241 [D loss: 0.690479, acc.: 54.69%] [G loss: 0.739355]
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2242 [D loss: 0.687360, acc.: 52.73%] [G loss: 0.717033]
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2243 [D loss: 0.694466, acc.: 53.71%] [G loss: 0.726569]
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2244 [D loss: 0.685170, acc.: 57.03%] [G loss: 0.719746]
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2245 [D loss: 0.692551, acc.: 52.93%] [G loss: 0.724926]
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2246 [D loss: 0.688337, acc.: 55.66%] [G loss: 0.736320]
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2247 [D loss: 0.683251, acc.: 56.45%] [G loss: 0.712983]
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2248 [D loss: 0.684563, acc.: 53.91%] [G loss: 0.725524]
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2249 [D loss: 0.687719, acc.: 52.93%] [G loss: 0.736621]
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2250 [D loss: 0.692936, acc.: 53.12%] [G loss: 0.728602]
1/1 [==============================] - 0s 15ms/step
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2251 [D loss: 0.680582, acc.: 58.40%] [G loss: 0.725858]
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2252 [D loss: 0.687962, acc.: 52.93%] [G loss: 0.724234]
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2253 [D loss: 0.687906, acc.: 54.10%] [G loss: 0.726793]
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2254 [D loss: 0.681041, acc.: 58.20%] [G loss: 0.723969]
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2255 [D loss: 0.686974, acc.: 53.91%] [G loss: 0.729622]
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2256 [D loss: 0.682149, acc.: 57.62%] [G loss: 0.718715]
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2257 [D loss: 0.690764, acc.: 50.59%] [G loss: 0.717752]
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2258 [D loss: 0.688988, acc.: 52.34%] [G loss: 0.729323]
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2259 [D loss: 0.683167, acc.: 54.88%] [G loss: 0.722170]
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2260 [D loss: 0.696828, acc.: 50.98%] [G loss: 0.714459]
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2261 [D loss: 0.690779, acc.: 52.15%] [G loss: 0.720310]
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2262 [D loss: 0.691718, acc.: 51.76%] [G loss: 0.722585]
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2263 [D loss: 0.693304, acc.: 51.76%] [G loss: 0.724607]
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2264 [D loss: 0.682215, acc.: 57.03%] [G loss: 0.721226]
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2265 [D loss: 0.676747, acc.: 59.18%] [G loss: 0.719271]
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2266 [D loss: 0.685791, acc.: 53.71%] [G loss: 0.723572]
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2267 [D loss: 0.681603, acc.: 57.42%] [G loss: 0.718078]
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2268 [D loss: 0.689447, acc.: 51.76%] [G loss: 0.718405]
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2269 [D loss: 0.685583, acc.: 54.49%] [G loss: 0.722748]
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2270 [D loss: 0.681738, acc.: 57.62%] [G loss: 0.709899]
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2271 [D loss: 0.691415, acc.: 50.78%] [G loss: 0.717601]
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2272 [D loss: 0.690521, acc.: 50.00%] [G loss: 0.723273]
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2273 [D loss: 0.687590, acc.: 53.52%] [G loss: 0.737327]
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2274 [D loss: 0.690296, acc.: 53.52%] [G loss: 0.731035]
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2275 [D loss: 0.683029, acc.: 54.88%] [G loss: 0.724074]
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2276 [D loss: 0.681152, acc.: 57.81%] [G loss: 0.728050]
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2277 [D loss: 0.694220, acc.: 50.39%] [G loss: 0.717893]
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2278 [D loss: 0.694521, acc.: 52.93%] [G loss: 0.731632]
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2279 [D loss: 0.682852, acc.: 57.23%] [G loss: 0.739789]
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2280 [D loss: 0.691847, acc.: 49.22%] [G loss: 0.733427]
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2281 [D loss: 0.688375, acc.: 52.93%] [G loss: 0.725126]
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2282 [D loss: 0.687103, acc.: 55.47%] [G loss: 0.725336]
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2283 [D loss: 0.680145, acc.: 56.45%] [G loss: 0.728260]
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2284 [D loss: 0.684505, acc.: 54.69%] [G loss: 0.732526]
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2285 [D loss: 0.684702, acc.: 57.23%] [G loss: 0.723117]
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2286 [D loss: 0.685728, acc.: 52.34%] [G loss: 0.736914]
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2287 [D loss: 0.692594, acc.: 50.98%] [G loss: 0.726967]
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2288 [D loss: 0.688685, acc.: 51.76%] [G loss: 0.720310]
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2289 [D loss: 0.694100, acc.: 51.37%] [G loss: 0.725566]
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2290 [D loss: 0.690632, acc.: 56.05%] [G loss: 0.738599]
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2291 [D loss: 0.682565, acc.: 57.23%] [G loss: 0.738320]
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2292 [D loss: 0.684569, acc.: 56.84%] [G loss: 0.735448]
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2293 [D loss: 0.684114, acc.: 55.27%] [G loss: 0.729347]
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2294 [D loss: 0.697511, acc.: 49.61%] [G loss: 0.718203]
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2295 [D loss: 0.691043, acc.: 53.71%] [G loss: 0.722565]
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2296 [D loss: 0.685554, acc.: 57.03%] [G loss: 0.721820]
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2297 [D loss: 0.687114, acc.: 54.10%] [G loss: 0.717986]
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2298 [D loss: 0.692274, acc.: 50.98%] [G loss: 0.718264]
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2299 [D loss: 0.695912, acc.: 52.73%] [G loss: 0.726679]
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2300 [D loss: 0.690218, acc.: 53.91%] [G loss: 0.725979]
1/1 [==============================] - 0s 16ms/step
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2301 [D loss: 0.679748, acc.: 59.96%] [G loss: 0.720391]
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2302 [D loss: 0.689564, acc.: 52.93%] [G loss: 0.722274]
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2303 [D loss: 0.684085, acc.: 57.42%] [G loss: 0.720787]
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2304 [D loss: 0.688791, acc.: 53.12%] [G loss: 0.734348]
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2305 [D loss: 0.680902, acc.: 56.25%] [G loss: 0.724604]
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2306 [D loss: 0.686335, acc.: 55.08%] [G loss: 0.729514]
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2307 [D loss: 0.687749, acc.: 54.30%] [G loss: 0.719755]
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2308 [D loss: 0.683437, acc.: 57.42%] [G loss: 0.730220]
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2309 [D loss: 0.683412, acc.: 56.25%] [G loss: 0.724026]
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2310 [D loss: 0.687898, acc.: 52.73%] [G loss: 0.725091]
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2311 [D loss: 0.688196, acc.: 52.15%] [G loss: 0.724948]
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2312 [D loss: 0.679824, acc.: 55.86%] [G loss: 0.738648]
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2313 [D loss: 0.676714, acc.: 58.20%] [G loss: 0.720867]
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2314 [D loss: 0.688569, acc.: 52.15%] [G loss: 0.739897]
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2315 [D loss: 0.682835, acc.: 56.25%] [G loss: 0.718330]
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2316 [D loss: 0.687022, acc.: 55.08%] [G loss: 0.720365]
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2317 [D loss: 0.680708, acc.: 57.23%] [G loss: 0.725310]
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2318 [D loss: 0.684887, acc.: 54.69%] [G loss: 0.711144]
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2319 [D loss: 0.687189, acc.: 54.88%] [G loss: 0.723476]
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2320 [D loss: 0.693116, acc.: 51.76%] [G loss: 0.720390]
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2321 [D loss: 0.688193, acc.: 52.54%] [G loss: 0.724402]
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2322 [D loss: 0.693121, acc.: 51.95%] [G loss: 0.727572]
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2323 [D loss: 0.680960, acc.: 58.98%] [G loss: 0.736685]
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2324 [D loss: 0.683681, acc.: 56.84%] [G loss: 0.740350]
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2325 [D loss: 0.679065, acc.: 59.38%] [G loss: 0.742937]
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2326 [D loss: 0.684425, acc.: 53.91%] [G loss: 0.744130]
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2327 [D loss: 0.682398, acc.: 57.62%] [G loss: 0.735353]
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2328 [D loss: 0.680540, acc.: 55.86%] [G loss: 0.721770]
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2329 [D loss: 0.689601, acc.: 53.71%] [G loss: 0.726480]
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2330 [D loss: 0.684258, acc.: 56.84%] [G loss: 0.726071]
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2331 [D loss: 0.679772, acc.: 57.62%] [G loss: 0.718812]
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2332 [D loss: 0.687929, acc.: 54.69%] [G loss: 0.728781]
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2333 [D loss: 0.682627, acc.: 55.47%] [G loss: 0.716900]
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2334 [D loss: 0.694432, acc.: 51.37%] [G loss: 0.718514]
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2335 [D loss: 0.688141, acc.: 57.42%] [G loss: 0.721789]
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2336 [D loss: 0.679191, acc.: 57.23%] [G loss: 0.725186]
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2337 [D loss: 0.679526, acc.: 55.86%] [G loss: 0.729216]
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2338 [D loss: 0.687577, acc.: 55.08%] [G loss: 0.715558]
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2339 [D loss: 0.690096, acc.: 53.71%] [G loss: 0.724380]
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2340 [D loss: 0.692651, acc.: 51.37%] [G loss: 0.720421]
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2341 [D loss: 0.677959, acc.: 58.40%] [G loss: 0.727822]
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2342 [D loss: 0.690994, acc.: 51.95%] [G loss: 0.714106]
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2343 [D loss: 0.687783, acc.: 54.49%] [G loss: 0.729228]
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2344 [D loss: 0.680220, acc.: 55.86%] [G loss: 0.726788]
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2345 [D loss: 0.682463, acc.: 57.23%] [G loss: 0.729343]
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2346 [D loss: 0.680815, acc.: 55.86%] [G loss: 0.728743]
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2347 [D loss: 0.685077, acc.: 53.32%] [G loss: 0.718878]
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2348 [D loss: 0.684784, acc.: 53.12%] [G loss: 0.727357]
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2349 [D loss: 0.687547, acc.: 56.05%] [G loss: 0.732352]
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2350 [D loss: 0.685142, acc.: 54.49%] [G loss: 0.727069]
1/1 [==============================] - 0s 16ms/step
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2351 [D loss: 0.686895, acc.: 56.25%] [G loss: 0.724694]
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2352 [D loss: 0.688463, acc.: 55.47%] [G loss: 0.736038]
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2353 [D loss: 0.688750, acc.: 52.73%] [G loss: 0.723878]
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2354 [D loss: 0.693300, acc.: 51.17%] [G loss: 0.724314]
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2355 [D loss: 0.683845, acc.: 54.88%] [G loss: 0.728233]
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2356 [D loss: 0.682567, acc.: 55.86%] [G loss: 0.732940]
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2357 [D loss: 0.680808, acc.: 56.05%] [G loss: 0.728668]
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2358 [D loss: 0.684700, acc.: 55.86%] [G loss: 0.725537]
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2359 [D loss: 0.688204, acc.: 55.47%] [G loss: 0.731724]
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2360 [D loss: 0.685581, acc.: 53.12%] [G loss: 0.735236]
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2361 [D loss: 0.691058, acc.: 53.32%] [G loss: 0.721851]
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2362 [D loss: 0.694160, acc.: 50.98%] [G loss: 0.722139]
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2363 [D loss: 0.686827, acc.: 52.15%] [G loss: 0.718735]
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2364 [D loss: 0.685672, acc.: 52.73%] [G loss: 0.731983]
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2365 [D loss: 0.685548, acc.: 55.08%] [G loss: 0.717150]
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2366 [D loss: 0.691351, acc.: 50.78%] [G loss: 0.733477]
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2367 [D loss: 0.675737, acc.: 58.98%] [G loss: 0.729380]
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2368 [D loss: 0.684959, acc.: 56.84%] [G loss: 0.727415]
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2369 [D loss: 0.682627, acc.: 56.84%] [G loss: 0.739387]
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2370 [D loss: 0.679135, acc.: 57.81%] [G loss: 0.719365]
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2371 [D loss: 0.684227, acc.: 56.45%] [G loss: 0.721977]
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2372 [D loss: 0.692871, acc.: 54.30%] [G loss: 0.721956]
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2373 [D loss: 0.683980, acc.: 56.25%] [G loss: 0.714840]
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2374 [D loss: 0.681462, acc.: 56.45%] [G loss: 0.717992]
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2375 [D loss: 0.683433, acc.: 56.05%] [G loss: 0.717709]
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2376 [D loss: 0.687293, acc.: 53.71%] [G loss: 0.713982]
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2377 [D loss: 0.687864, acc.: 53.71%] [G loss: 0.721746]
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2378 [D loss: 0.685636, acc.: 54.49%] [G loss: 0.733610]
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2379 [D loss: 0.688971, acc.: 53.32%] [G loss: 0.731425]
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2380 [D loss: 0.682284, acc.: 56.64%] [G loss: 0.723032]
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2381 [D loss: 0.679886, acc.: 57.42%] [G loss: 0.726444]
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2382 [D loss: 0.685052, acc.: 57.62%] [G loss: 0.738916]
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2383 [D loss: 0.691767, acc.: 52.34%] [G loss: 0.734144]
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2384 [D loss: 0.680854, acc.: 54.69%] [G loss: 0.738256]
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2385 [D loss: 0.688135, acc.: 55.27%] [G loss: 0.750733]
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2386 [D loss: 0.686762, acc.: 54.30%] [G loss: 0.744690]
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2387 [D loss: 0.680361, acc.: 58.40%] [G loss: 0.735667]
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2388 [D loss: 0.684713, acc.: 56.45%] [G loss: 0.737450]
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2389 [D loss: 0.683611, acc.: 58.98%] [G loss: 0.742027]
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2390 [D loss: 0.691474, acc.: 53.12%] [G loss: 0.722913]
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2391 [D loss: 0.685590, acc.: 55.08%] [G loss: 0.730874]
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2392 [D loss: 0.682230, acc.: 54.30%] [G loss: 0.732336]
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2393 [D loss: 0.685770, acc.: 53.91%] [G loss: 0.723986]
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2394 [D loss: 0.681299, acc.: 57.23%] [G loss: 0.727594]
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2395 [D loss: 0.683607, acc.: 55.47%] [G loss: 0.713635]
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2396 [D loss: 0.694750, acc.: 49.80%] [G loss: 0.728616]
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2397 [D loss: 0.684613, acc.: 55.08%] [G loss: 0.731490]
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2398 [D loss: 0.683960, acc.: 57.81%] [G loss: 0.724340]
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2399 [D loss: 0.686814, acc.: 54.10%] [G loss: 0.723007]
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2400 [D loss: 0.691850, acc.: 51.76%] [G loss: 0.733691]
1/1 [==============================] - 0s 15ms/step
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2401 [D loss: 0.674100, acc.: 61.72%] [G loss: 0.736244]
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2402 [D loss: 0.673617, acc.: 58.59%] [G loss: 0.725580]
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2403 [D loss: 0.684832, acc.: 54.30%] [G loss: 0.730944]
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2404 [D loss: 0.680104, acc.: 56.64%] [G loss: 0.731661]
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2405 [D loss: 0.687092, acc.: 53.32%] [G loss: 0.721350]
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2406 [D loss: 0.689660, acc.: 51.95%] [G loss: 0.731867]
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2407 [D loss: 0.682439, acc.: 57.23%] [G loss: 0.742128]
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2408 [D loss: 0.686698, acc.: 53.52%] [G loss: 0.735023]
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2409 [D loss: 0.685002, acc.: 54.49%] [G loss: 0.725511]
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2410 [D loss: 0.693766, acc.: 52.73%] [G loss: 0.724933]
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2411 [D loss: 0.690479, acc.: 52.15%] [G loss: 0.741799]
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2412 [D loss: 0.682602, acc.: 55.27%] [G loss: 0.735835]
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2413 [D loss: 0.687471, acc.: 56.25%] [G loss: 0.732404]
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2414 [D loss: 0.681584, acc.: 57.23%] [G loss: 0.719166]
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2415 [D loss: 0.680670, acc.: 59.38%] [G loss: 0.727287]
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2416 [D loss: 0.685374, acc.: 55.47%] [G loss: 0.722664]
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2417 [D loss: 0.687532, acc.: 56.25%] [G loss: 0.728413]
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2418 [D loss: 0.686746, acc.: 53.71%] [G loss: 0.715554]
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2419 [D loss: 0.690931, acc.: 52.34%] [G loss: 0.726939]
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2420 [D loss: 0.683367, acc.: 53.91%] [G loss: 0.721970]
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2421 [D loss: 0.686976, acc.: 52.73%] [G loss: 0.720089]
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2422 [D loss: 0.689965, acc.: 54.49%] [G loss: 0.732096]
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2423 [D loss: 0.676880, acc.: 58.01%] [G loss: 0.725070]
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2424 [D loss: 0.688116, acc.: 53.52%] [G loss: 0.727346]
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2425 [D loss: 0.682362, acc.: 55.27%] [G loss: 0.725176]
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2426 [D loss: 0.686404, acc.: 54.30%] [G loss: 0.729872]
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2427 [D loss: 0.684388, acc.: 57.81%] [G loss: 0.735623]
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2428 [D loss: 0.690943, acc.: 52.34%] [G loss: 0.732941]
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2429 [D loss: 0.686334, acc.: 54.69%] [G loss: 0.731973]
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2430 [D loss: 0.690252, acc.: 52.93%] [G loss: 0.731571]
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2431 [D loss: 0.686272, acc.: 55.27%] [G loss: 0.731845]
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2432 [D loss: 0.681949, acc.: 57.42%] [G loss: 0.718733]
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2433 [D loss: 0.688585, acc.: 54.30%] [G loss: 0.729572]
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2434 [D loss: 0.676985, acc.: 59.57%] [G loss: 0.735735]
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2435 [D loss: 0.686698, acc.: 54.10%] [G loss: 0.731433]
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2436 [D loss: 0.689224, acc.: 54.49%] [G loss: 0.726563]
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2437 [D loss: 0.685182, acc.: 54.30%] [G loss: 0.716779]
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2438 [D loss: 0.684047, acc.: 56.05%] [G loss: 0.722888]
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2439 [D loss: 0.688323, acc.: 52.54%] [G loss: 0.728783]
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2440 [D loss: 0.680732, acc.: 56.45%] [G loss: 0.713325]
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2441 [D loss: 0.694074, acc.: 50.98%] [G loss: 0.730595]
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2442 [D loss: 0.681387, acc.: 58.01%] [G loss: 0.725205]
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2443 [D loss: 0.676461, acc.: 58.40%] [G loss: 0.731563]
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2444 [D loss: 0.685635, acc.: 55.86%] [G loss: 0.720799]
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2445 [D loss: 0.678783, acc.: 58.20%] [G loss: 0.734652]
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2446 [D loss: 0.683396, acc.: 58.98%] [G loss: 0.749182]
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2447 [D loss: 0.688349, acc.: 53.71%] [G loss: 0.734860]
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2448 [D loss: 0.684623, acc.: 56.25%] [G loss: 0.738614]
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2449 [D loss: 0.685928, acc.: 57.23%] [G loss: 0.729144]
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2450 [D loss: 0.687421, acc.: 56.64%] [G loss: 0.736707]
1/1 [==============================] - 0s 16ms/step
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2451 [D loss: 0.683660, acc.: 56.25%] [G loss: 0.734521]
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2452 [D loss: 0.684981, acc.: 55.66%] [G loss: 0.715916]
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2453 [D loss: 0.685193, acc.: 54.30%] [G loss: 0.726361]
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2454 [D loss: 0.683234, acc.: 55.27%] [G loss: 0.716038]
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2455 [D loss: 0.681423, acc.: 55.27%] [G loss: 0.728056]
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2456 [D loss: 0.695824, acc.: 51.76%] [G loss: 0.726411]
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2457 [D loss: 0.688243, acc.: 54.10%] [G loss: 0.731814]
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2458 [D loss: 0.679063, acc.: 56.84%] [G loss: 0.728606]
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2459 [D loss: 0.683603, acc.: 57.03%] [G loss: 0.740330]
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2460 [D loss: 0.685538, acc.: 52.34%] [G loss: 0.737399]
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2461 [D loss: 0.684655, acc.: 53.71%] [G loss: 0.734292]
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2462 [D loss: 0.678172, acc.: 59.57%] [G loss: 0.739789]
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2463 [D loss: 0.684815, acc.: 53.52%] [G loss: 0.738827]
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2464 [D loss: 0.680540, acc.: 57.03%] [G loss: 0.739277]
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2465 [D loss: 0.682119, acc.: 59.38%] [G loss: 0.737671]
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2466 [D loss: 0.689564, acc.: 55.08%] [G loss: 0.736737]
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2467 [D loss: 0.684511, acc.: 57.23%] [G loss: 0.737596]
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2468 [D loss: 0.681104, acc.: 57.23%] [G loss: 0.736766]
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2469 [D loss: 0.686721, acc.: 53.71%] [G loss: 0.729556]
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2470 [D loss: 0.679504, acc.: 55.66%] [G loss: 0.729065]
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2471 [D loss: 0.684272, acc.: 56.84%] [G loss: 0.734692]
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2472 [D loss: 0.687056, acc.: 54.10%] [G loss: 0.740091]
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2473 [D loss: 0.685044, acc.: 57.23%] [G loss: 0.721499]
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2474 [D loss: 0.682655, acc.: 57.23%] [G loss: 0.721680]
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2475 [D loss: 0.690932, acc.: 52.34%] [G loss: 0.721852]
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2476 [D loss: 0.683593, acc.: 56.25%] [G loss: 0.713377]
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2477 [D loss: 0.683913, acc.: 56.05%] [G loss: 0.731737]
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2478 [D loss: 0.688646, acc.: 54.30%] [G loss: 0.713223]
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2479 [D loss: 0.687661, acc.: 53.12%] [G loss: 0.723896]
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2480 [D loss: 0.690576, acc.: 51.56%] [G loss: 0.718902]
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2481 [D loss: 0.681566, acc.: 57.42%] [G loss: 0.735548]
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2482 [D loss: 0.678455, acc.: 60.94%] [G loss: 0.724453]
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2483 [D loss: 0.680200, acc.: 59.18%] [G loss: 0.725478]
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2484 [D loss: 0.680685, acc.: 55.08%] [G loss: 0.735366]
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2485 [D loss: 0.683033, acc.: 54.69%] [G loss: 0.731960]
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2486 [D loss: 0.686722, acc.: 53.91%] [G loss: 0.744913]
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2487 [D loss: 0.680349, acc.: 58.20%] [G loss: 0.726903]
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2488 [D loss: 0.683818, acc.: 53.91%] [G loss: 0.730576]
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2489 [D loss: 0.684442, acc.: 56.25%] [G loss: 0.731221]
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2490 [D loss: 0.681033, acc.: 56.45%] [G loss: 0.735254]
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2491 [D loss: 0.688111, acc.: 53.71%] [G loss: 0.720186]
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2492 [D loss: 0.688566, acc.: 55.47%] [G loss: 0.733826]
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2493 [D loss: 0.692399, acc.: 54.69%] [G loss: 0.718656]
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2494 [D loss: 0.686606, acc.: 53.32%] [G loss: 0.715766]
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2495 [D loss: 0.686663, acc.: 54.10%] [G loss: 0.722640]
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2496 [D loss: 0.683778, acc.: 57.42%] [G loss: 0.717437]
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2497 [D loss: 0.683149, acc.: 57.03%] [G loss: 0.716416]
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2498 [D loss: 0.679624, acc.: 57.62%] [G loss: 0.729603]
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2499 [D loss: 0.685276, acc.: 56.64%] [G loss: 0.725127]
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2500 [D loss: 0.683193, acc.: 57.62%] [G loss: 0.714722]
1/1 [==============================] - 0s 15ms/step
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2501 [D loss: 0.686213, acc.: 54.69%] [G loss: 0.716925]
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2502 [D loss: 0.684947, acc.: 52.54%] [G loss: 0.725595]
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2503 [D loss: 0.678283, acc.: 58.79%] [G loss: 0.730274]
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2504 [D loss: 0.682815, acc.: 53.91%] [G loss: 0.722138]
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2505 [D loss: 0.682360, acc.: 56.05%] [G loss: 0.732702]
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2506 [D loss: 0.687720, acc.: 53.91%] [G loss: 0.734020]
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2507 [D loss: 0.683981, acc.: 55.27%] [G loss: 0.728950]
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2508 [D loss: 0.681839, acc.: 53.91%] [G loss: 0.724371]
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2509 [D loss: 0.677678, acc.: 58.59%] [G loss: 0.735382]
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2510 [D loss: 0.686163, acc.: 55.08%] [G loss: 0.741713]
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2511 [D loss: 0.685935, acc.: 56.45%] [G loss: 0.724988]
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2512 [D loss: 0.686743, acc.: 55.27%] [G loss: 0.724660]
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2513 [D loss: 0.681298, acc.: 55.86%] [G loss: 0.725702]
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2514 [D loss: 0.686027, acc.: 55.08%] [G loss: 0.722925]
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2515 [D loss: 0.688715, acc.: 52.34%] [G loss: 0.725677]
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2516 [D loss: 0.684530, acc.: 53.71%] [G loss: 0.725881]
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2517 [D loss: 0.687898, acc.: 54.49%] [G loss: 0.733134]
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2518 [D loss: 0.682301, acc.: 56.05%] [G loss: 0.740408]
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2519 [D loss: 0.677492, acc.: 60.74%] [G loss: 0.734440]
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2520 [D loss: 0.683916, acc.: 58.01%] [G loss: 0.739280]
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2521 [D loss: 0.683002, acc.: 54.88%] [G loss: 0.735644]
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2522 [D loss: 0.682277, acc.: 58.20%] [G loss: 0.727545]
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2523 [D loss: 0.682604, acc.: 56.64%] [G loss: 0.726157]
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2524 [D loss: 0.687098, acc.: 56.25%] [G loss: 0.728114]
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2525 [D loss: 0.683756, acc.: 57.81%] [G loss: 0.709983]
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2526 [D loss: 0.677887, acc.: 55.86%] [G loss: 0.717853]
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2527 [D loss: 0.682332, acc.: 55.47%] [G loss: 0.726446]
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2528 [D loss: 0.678851, acc.: 58.40%] [G loss: 0.726216]
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2529 [D loss: 0.683711, acc.: 56.45%] [G loss: 0.733322]
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2530 [D loss: 0.687698, acc.: 53.52%] [G loss: 0.730803]
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2531 [D loss: 0.683523, acc.: 55.47%] [G loss: 0.739874]
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2532 [D loss: 0.677348, acc.: 58.59%] [G loss: 0.730597]
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2533 [D loss: 0.693226, acc.: 51.76%] [G loss: 0.738264]
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2534 [D loss: 0.687261, acc.: 53.12%] [G loss: 0.741677]
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2535 [D loss: 0.682817, acc.: 57.62%] [G loss: 0.728750]
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2536 [D loss: 0.678695, acc.: 58.59%] [G loss: 0.736573]
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2537 [D loss: 0.692540, acc.: 52.93%] [G loss: 0.738513]
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2538 [D loss: 0.680321, acc.: 58.20%] [G loss: 0.736547]
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2539 [D loss: 0.680068, acc.: 58.20%] [G loss: 0.731172]
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2540 [D loss: 0.679501, acc.: 58.20%] [G loss: 0.753774]
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2541 [D loss: 0.685790, acc.: 54.88%] [G loss: 0.738419]
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2542 [D loss: 0.688086, acc.: 52.34%] [G loss: 0.750743]
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2543 [D loss: 0.687907, acc.: 53.91%] [G loss: 0.741823]
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2544 [D loss: 0.679699, acc.: 55.66%] [G loss: 0.731151]
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2545 [D loss: 0.678004, acc.: 56.05%] [G loss: 0.743145]
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2546 [D loss: 0.681748, acc.: 56.45%] [G loss: 0.746046]
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2547 [D loss: 0.675091, acc.: 57.81%] [G loss: 0.732497]
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2548 [D loss: 0.689033, acc.: 51.95%] [G loss: 0.737892]
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2549 [D loss: 0.686528, acc.: 56.25%] [G loss: 0.731953]
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2550 [D loss: 0.683631, acc.: 58.79%] [G loss: 0.718173]
1/1 [==============================] - 0s 16ms/step
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2551 [D loss: 0.691309, acc.: 52.15%] [G loss: 0.720779]
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2552 [D loss: 0.688753, acc.: 52.73%] [G loss: 0.724061]
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2553 [D loss: 0.687977, acc.: 54.49%] [G loss: 0.718710]
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2554 [D loss: 0.686552, acc.: 52.73%] [G loss: 0.719732]
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2555 [D loss: 0.684876, acc.: 58.01%] [G loss: 0.735249]
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2556 [D loss: 0.679819, acc.: 56.05%] [G loss: 0.732563]
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2557 [D loss: 0.677288, acc.: 57.81%] [G loss: 0.743033]
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2558 [D loss: 0.682218, acc.: 54.88%] [G loss: 0.725787]
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2559 [D loss: 0.690699, acc.: 52.34%] [G loss: 0.732632]
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2560 [D loss: 0.694772, acc.: 50.78%] [G loss: 0.733090]
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2561 [D loss: 0.678847, acc.: 58.01%] [G loss: 0.726073]
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2562 [D loss: 0.688687, acc.: 52.34%] [G loss: 0.724837]
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2563 [D loss: 0.684494, acc.: 55.47%] [G loss: 0.716966]
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2564 [D loss: 0.686181, acc.: 55.08%] [G loss: 0.718467]
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2565 [D loss: 0.673245, acc.: 60.35%] [G loss: 0.723981]
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2566 [D loss: 0.679449, acc.: 56.05%] [G loss: 0.738837]
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2567 [D loss: 0.692138, acc.: 49.80%] [G loss: 0.741693]
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2568 [D loss: 0.688252, acc.: 55.86%] [G loss: 0.731185]
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2569 [D loss: 0.688531, acc.: 54.10%] [G loss: 0.740112]
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2570 [D loss: 0.684766, acc.: 56.25%] [G loss: 0.739559]
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2571 [D loss: 0.686539, acc.: 54.10%] [G loss: 0.728588]
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2572 [D loss: 0.691654, acc.: 51.17%] [G loss: 0.728327]
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2573 [D loss: 0.690401, acc.: 52.34%] [G loss: 0.734425]
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2574 [D loss: 0.681303, acc.: 57.81%] [G loss: 0.740656]
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2575 [D loss: 0.676206, acc.: 59.77%] [G loss: 0.736476]
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2576 [D loss: 0.683996, acc.: 55.27%] [G loss: 0.741227]
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2577 [D loss: 0.684340, acc.: 56.84%] [G loss: 0.742289]
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2578 [D loss: 0.686253, acc.: 51.76%] [G loss: 0.733419]
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2579 [D loss: 0.687306, acc.: 54.10%] [G loss: 0.730879]
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2580 [D loss: 0.678867, acc.: 57.62%] [G loss: 0.725881]
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2581 [D loss: 0.683746, acc.: 53.71%] [G loss: 0.735277]
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2582 [D loss: 0.683322, acc.: 57.23%] [G loss: 0.735697]
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2583 [D loss: 0.678498, acc.: 59.57%] [G loss: 0.726651]
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2584 [D loss: 0.682787, acc.: 55.86%] [G loss: 0.732528]
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2585 [D loss: 0.689289, acc.: 53.52%] [G loss: 0.729403]
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2586 [D loss: 0.684453, acc.: 54.10%] [G loss: 0.748209]
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2587 [D loss: 0.684609, acc.: 55.47%] [G loss: 0.724210]
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2588 [D loss: 0.684200, acc.: 57.42%] [G loss: 0.728578]
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2589 [D loss: 0.684863, acc.: 55.47%] [G loss: 0.736139]
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2590 [D loss: 0.689029, acc.: 54.49%] [G loss: 0.720263]
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2591 [D loss: 0.685525, acc.: 53.91%] [G loss: 0.729776]
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2592 [D loss: 0.685839, acc.: 56.05%] [G loss: 0.729803]
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2593 [D loss: 0.689457, acc.: 54.88%] [G loss: 0.727516]
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2594 [D loss: 0.680975, acc.: 57.42%] [G loss: 0.723480]
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2595 [D loss: 0.689681, acc.: 54.30%] [G loss: 0.730191]
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2596 [D loss: 0.681995, acc.: 55.86%] [G loss: 0.734935]
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2597 [D loss: 0.676253, acc.: 57.81%] [G loss: 0.733323]
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2598 [D loss: 0.681696, acc.: 53.32%] [G loss: 0.729107]
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2599 [D loss: 0.683301, acc.: 57.62%] [G loss: 0.739240]
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2600 [D loss: 0.693224, acc.: 53.91%] [G loss: 0.742432]
1/1 [==============================] - 0s 16ms/step
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2601 [D loss: 0.687119, acc.: 55.47%] [G loss: 0.736693]
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2602 [D loss: 0.682465, acc.: 56.05%] [G loss: 0.727618]
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2603 [D loss: 0.700143, acc.: 47.85%] [G loss: 0.730736]
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2604 [D loss: 0.682454, acc.: 57.23%] [G loss: 0.739784]
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2605 [D loss: 0.681171, acc.: 59.18%] [G loss: 0.730759]
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2606 [D loss: 0.685636, acc.: 54.69%] [G loss: 0.735837]
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2607 [D loss: 0.685863, acc.: 52.34%] [G loss: 0.723861]
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2608 [D loss: 0.686311, acc.: 51.37%] [G loss: 0.744705]
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2609 [D loss: 0.677984, acc.: 57.03%] [G loss: 0.735538]
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2610 [D loss: 0.676809, acc.: 59.77%] [G loss: 0.736831]
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2611 [D loss: 0.686120, acc.: 54.10%] [G loss: 0.729074]
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2612 [D loss: 0.684186, acc.: 55.47%] [G loss: 0.726940]
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2613 [D loss: 0.689717, acc.: 51.95%] [G loss: 0.736583]
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2614 [D loss: 0.681574, acc.: 54.49%] [G loss: 0.738276]
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2615 [D loss: 0.678967, acc.: 54.30%] [G loss: 0.733580]
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2616 [D loss: 0.682078, acc.: 55.27%] [G loss: 0.734718]
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2617 [D loss: 0.678557, acc.: 57.81%] [G loss: 0.753932]
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2618 [D loss: 0.683141, acc.: 59.18%] [G loss: 0.738809]
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2619 [D loss: 0.686085, acc.: 55.47%] [G loss: 0.737144]
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2620 [D loss: 0.680977, acc.: 58.01%] [G loss: 0.741152]
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2621 [D loss: 0.682834, acc.: 56.64%] [G loss: 0.728130]
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2622 [D loss: 0.679593, acc.: 58.40%] [G loss: 0.725448]
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2623 [D loss: 0.683754, acc.: 56.25%] [G loss: 0.731854]
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2624 [D loss: 0.686588, acc.: 55.27%] [G loss: 0.735825]
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2625 [D loss: 0.679781, acc.: 59.38%] [G loss: 0.723123]
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2626 [D loss: 0.677655, acc.: 59.38%] [G loss: 0.746624]
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2627 [D loss: 0.684697, acc.: 54.88%] [G loss: 0.731989]
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2628 [D loss: 0.684034, acc.: 55.08%] [G loss: 0.731642]
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2629 [D loss: 0.688243, acc.: 55.66%] [G loss: 0.727645]
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2630 [D loss: 0.681653, acc.: 53.91%] [G loss: 0.728658]
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2631 [D loss: 0.686049, acc.: 56.05%] [G loss: 0.719598]
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2632 [D loss: 0.684383, acc.: 56.84%] [G loss: 0.727489]
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2633 [D loss: 0.687515, acc.: 52.93%] [G loss: 0.726258]
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2634 [D loss: 0.684617, acc.: 55.86%] [G loss: 0.737115]
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2635 [D loss: 0.687682, acc.: 54.49%] [G loss: 0.735022]
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2636 [D loss: 0.683848, acc.: 53.12%] [G loss: 0.733027]
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2637 [D loss: 0.681336, acc.: 56.25%] [G loss: 0.739022]
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2638 [D loss: 0.684311, acc.: 57.62%] [G loss: 0.731868]
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2639 [D loss: 0.683255, acc.: 53.91%] [G loss: 0.720025]
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2640 [D loss: 0.684078, acc.: 57.42%] [G loss: 0.713770]
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2641 [D loss: 0.675744, acc.: 58.79%] [G loss: 0.723760]
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2642 [D loss: 0.684925, acc.: 55.47%] [G loss: 0.722832]
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2643 [D loss: 0.682987, acc.: 56.25%] [G loss: 0.720267]
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2644 [D loss: 0.679488, acc.: 57.23%] [G loss: 0.718536]
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2645 [D loss: 0.689224, acc.: 54.69%] [G loss: 0.715887]
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2646 [D loss: 0.680000, acc.: 57.42%] [G loss: 0.722010]
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2647 [D loss: 0.686704, acc.: 53.91%] [G loss: 0.718134]
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2648 [D loss: 0.685001, acc.: 55.86%] [G loss: 0.712328]
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2649 [D loss: 0.677755, acc.: 56.64%] [G loss: 0.730369]
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2650 [D loss: 0.679977, acc.: 57.42%] [G loss: 0.726091]
1/1 [==============================] - 0s 15ms/step
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2651 [D loss: 0.687816, acc.: 56.25%] [G loss: 0.729958]
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2652 [D loss: 0.688207, acc.: 55.66%] [G loss: 0.729863]
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2653 [D loss: 0.682325, acc.: 55.27%] [G loss: 0.728869]
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2654 [D loss: 0.681505, acc.: 56.45%] [G loss: 0.736925]
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2655 [D loss: 0.677231, acc.: 60.35%] [G loss: 0.733538]
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2656 [D loss: 0.684044, acc.: 54.69%] [G loss: 0.748736]
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2657 [D loss: 0.687020, acc.: 53.12%] [G loss: 0.740132]
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2658 [D loss: 0.679764, acc.: 61.13%] [G loss: 0.750969]
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2659 [D loss: 0.686966, acc.: 54.30%] [G loss: 0.748593]
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2660 [D loss: 0.685632, acc.: 53.12%] [G loss: 0.741727]
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2661 [D loss: 0.675381, acc.: 60.74%] [G loss: 0.757779]
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2662 [D loss: 0.686627, acc.: 56.64%] [G loss: 0.728897]
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2663 [D loss: 0.680888, acc.: 55.27%] [G loss: 0.728464]
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2664 [D loss: 0.692981, acc.: 52.34%] [G loss: 0.738739]
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2665 [D loss: 0.690381, acc.: 54.10%] [G loss: 0.724189]
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2666 [D loss: 0.679535, acc.: 56.64%] [G loss: 0.728109]
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2667 [D loss: 0.687838, acc.: 53.32%] [G loss: 0.728078]
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2668 [D loss: 0.682438, acc.: 54.49%] [G loss: 0.741701]
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2669 [D loss: 0.690919, acc.: 54.30%] [G loss: 0.732078]
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2670 [D loss: 0.684749, acc.: 54.49%] [G loss: 0.737498]
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2671 [D loss: 0.685828, acc.: 53.91%] [G loss: 0.734058]
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2672 [D loss: 0.677478, acc.: 58.01%] [G loss: 0.726688]
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2673 [D loss: 0.685943, acc.: 52.54%] [G loss: 0.733383]
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2674 [D loss: 0.686119, acc.: 54.88%] [G loss: 0.729097]
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2675 [D loss: 0.679427, acc.: 58.01%] [G loss: 0.727764]
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2676 [D loss: 0.681710, acc.: 58.59%] [G loss: 0.734009]
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2677 [D loss: 0.680310, acc.: 59.18%] [G loss: 0.738035]
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2678 [D loss: 0.676020, acc.: 58.59%] [G loss: 0.742451]
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2679 [D loss: 0.686931, acc.: 54.30%] [G loss: 0.758682]
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2680 [D loss: 0.685091, acc.: 55.47%] [G loss: 0.740321]
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2681 [D loss: 0.678736, acc.: 59.77%] [G loss: 0.739522]
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2682 [D loss: 0.680845, acc.: 58.79%] [G loss: 0.733631]
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2683 [D loss: 0.680396, acc.: 57.81%] [G loss: 0.733838]
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2684 [D loss: 0.679699, acc.: 58.20%] [G loss: 0.721071]
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2685 [D loss: 0.677351, acc.: 58.40%] [G loss: 0.729621]
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2686 [D loss: 0.683027, acc.: 56.05%] [G loss: 0.733383]
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2687 [D loss: 0.683253, acc.: 56.45%] [G loss: 0.720729]
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2688 [D loss: 0.684935, acc.: 56.64%] [G loss: 0.722454]
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2689 [D loss: 0.682365, acc.: 52.54%] [G loss: 0.723519]
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2690 [D loss: 0.688018, acc.: 52.54%] [G loss: 0.720953]
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2691 [D loss: 0.692450, acc.: 53.71%] [G loss: 0.727543]
8/8 [==============================] - 0s 2ms/step
2692 [D loss: 0.685165, acc.: 53.12%] [G loss: 0.732443]
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2693 [D loss: 0.686958, acc.: 55.66%] [G loss: 0.730663]
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2694 [D loss: 0.684990, acc.: 57.81%] [G loss: 0.723977]
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2695 [D loss: 0.684879, acc.: 57.03%] [G loss: 0.740617]
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2696 [D loss: 0.689513, acc.: 52.73%] [G loss: 0.732594]
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2697 [D loss: 0.682560, acc.: 58.59%] [G loss: 0.732963]
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2698 [D loss: 0.687009, acc.: 53.71%] [G loss: 0.727264]
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2699 [D loss: 0.677670, acc.: 59.38%] [G loss: 0.721463]
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2700 [D loss: 0.681831, acc.: 56.45%] [G loss: 0.729057]
1/1 [==============================] - 0s 15ms/step
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2701 [D loss: 0.678446, acc.: 58.40%] [G loss: 0.733222]
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2702 [D loss: 0.681194, acc.: 55.86%] [G loss: 0.734852]
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2703 [D loss: 0.681063, acc.: 57.03%] [G loss: 0.723454]
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2704 [D loss: 0.680524, acc.: 57.03%] [G loss: 0.720953]
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2705 [D loss: 0.678453, acc.: 59.18%] [G loss: 0.732565]
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2706 [D loss: 0.692285, acc.: 51.37%] [G loss: 0.729351]
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2707 [D loss: 0.679826, acc.: 57.23%] [G loss: 0.742725]
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2708 [D loss: 0.690073, acc.: 54.69%] [G loss: 0.741062]
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2709 [D loss: 0.680251, acc.: 56.64%] [G loss: 0.746449]
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2710 [D loss: 0.678950, acc.: 60.16%] [G loss: 0.739504]
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2711 [D loss: 0.676628, acc.: 59.57%] [G loss: 0.741790]
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2712 [D loss: 0.681134, acc.: 56.45%] [G loss: 0.737810]
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2713 [D loss: 0.687544, acc.: 54.88%] [G loss: 0.738933]
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2714 [D loss: 0.676738, acc.: 56.64%] [G loss: 0.730591]
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2715 [D loss: 0.688720, acc.: 53.52%] [G loss: 0.732372]
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2716 [D loss: 0.682733, acc.: 54.69%] [G loss: 0.740702]
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2717 [D loss: 0.682187, acc.: 56.64%] [G loss: 0.736460]
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2718 [D loss: 0.679041, acc.: 58.59%] [G loss: 0.747823]
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2719 [D loss: 0.682481, acc.: 54.10%] [G loss: 0.731001]
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2720 [D loss: 0.685572, acc.: 52.73%] [G loss: 0.738564]
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2721 [D loss: 0.677884, acc.: 59.38%] [G loss: 0.739967]
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2722 [D loss: 0.684109, acc.: 53.12%] [G loss: 0.732689]
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2723 [D loss: 0.679785, acc.: 59.38%] [G loss: 0.740084]
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2724 [D loss: 0.683314, acc.: 55.66%] [G loss: 0.736437]
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2725 [D loss: 0.687991, acc.: 55.66%] [G loss: 0.744221]
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2726 [D loss: 0.675039, acc.: 57.62%] [G loss: 0.739003]
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2727 [D loss: 0.687103, acc.: 54.69%] [G loss: 0.733732]
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2728 [D loss: 0.684396, acc.: 56.25%] [G loss: 0.751319]
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2729 [D loss: 0.689776, acc.: 54.10%] [G loss: 0.739211]
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2730 [D loss: 0.679502, acc.: 58.98%] [G loss: 0.739269]
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2731 [D loss: 0.681161, acc.: 55.27%] [G loss: 0.733205]
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2732 [D loss: 0.680201, acc.: 57.81%] [G loss: 0.731886]
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2733 [D loss: 0.680142, acc.: 58.40%] [G loss: 0.723096]
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2734 [D loss: 0.677327, acc.: 60.35%] [G loss: 0.718250]
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2735 [D loss: 0.678592, acc.: 57.23%] [G loss: 0.717013]
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2736 [D loss: 0.681048, acc.: 54.49%] [G loss: 0.716499]
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2737 [D loss: 0.688975, acc.: 54.88%] [G loss: 0.717756]
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2738 [D loss: 0.679100, acc.: 55.08%] [G loss: 0.717685]
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2739 [D loss: 0.687985, acc.: 53.52%] [G loss: 0.721196]
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2740 [D loss: 0.689380, acc.: 56.25%] [G loss: 0.723081]
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2741 [D loss: 0.689926, acc.: 54.30%] [G loss: 0.725136]
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2742 [D loss: 0.685383, acc.: 54.49%] [G loss: 0.730384]
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2743 [D loss: 0.686172, acc.: 56.05%] [G loss: 0.736638]
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2744 [D loss: 0.682699, acc.: 58.59%] [G loss: 0.755683]
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2745 [D loss: 0.671570, acc.: 61.13%] [G loss: 0.748154]
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2746 [D loss: 0.680246, acc.: 58.20%] [G loss: 0.739330]
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2747 [D loss: 0.673179, acc.: 59.38%] [G loss: 0.739867]
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2748 [D loss: 0.682690, acc.: 54.69%] [G loss: 0.739476]
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2749 [D loss: 0.685320, acc.: 57.23%] [G loss: 0.730184]
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2750 [D loss: 0.678865, acc.: 55.08%] [G loss: 0.728069]
1/1 [==============================] - 0s 16ms/step
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2751 [D loss: 0.685466, acc.: 54.69%] [G loss: 0.737828]
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2752 [D loss: 0.689870, acc.: 50.98%] [G loss: 0.741304]
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2753 [D loss: 0.682246, acc.: 55.27%] [G loss: 0.740919]
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2754 [D loss: 0.679094, acc.: 58.20%] [G loss: 0.738788]
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2755 [D loss: 0.694991, acc.: 48.63%] [G loss: 0.742860]
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2756 [D loss: 0.688036, acc.: 52.73%] [G loss: 0.746888]
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2757 [D loss: 0.686077, acc.: 54.49%] [G loss: 0.731532]
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2758 [D loss: 0.693684, acc.: 54.88%] [G loss: 0.732178]
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2759 [D loss: 0.682731, acc.: 55.86%] [G loss: 0.727159]
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2760 [D loss: 0.690134, acc.: 53.52%] [G loss: 0.735764]
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2761 [D loss: 0.680593, acc.: 57.23%] [G loss: 0.736167]
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2762 [D loss: 0.682140, acc.: 55.86%] [G loss: 0.744051]
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2763 [D loss: 0.684195, acc.: 54.88%] [G loss: 0.728718]
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2764 [D loss: 0.688978, acc.: 53.71%] [G loss: 0.728689]
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2765 [D loss: 0.678455, acc.: 57.62%] [G loss: 0.728662]
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2766 [D loss: 0.679632, acc.: 58.40%] [G loss: 0.727208]
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2767 [D loss: 0.678972, acc.: 57.03%] [G loss: 0.725941]
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2768 [D loss: 0.677050, acc.: 58.98%] [G loss: 0.731513]
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2769 [D loss: 0.674809, acc.: 59.96%] [G loss: 0.735887]
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2770 [D loss: 0.677180, acc.: 59.18%] [G loss: 0.733319]
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2771 [D loss: 0.678195, acc.: 59.18%] [G loss: 0.734286]
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2772 [D loss: 0.678500, acc.: 56.25%] [G loss: 0.728197]
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2773 [D loss: 0.691334, acc.: 53.32%] [G loss: 0.720630]
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2774 [D loss: 0.685479, acc.: 54.88%] [G loss: 0.733090]
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2775 [D loss: 0.689276, acc.: 51.56%] [G loss: 0.738205]
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2776 [D loss: 0.684632, acc.: 55.86%] [G loss: 0.729251]
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2777 [D loss: 0.684231, acc.: 57.42%] [G loss: 0.726653]
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2778 [D loss: 0.674658, acc.: 60.74%] [G loss: 0.735487]
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2779 [D loss: 0.685867, acc.: 57.03%] [G loss: 0.738564]
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2780 [D loss: 0.677839, acc.: 59.38%] [G loss: 0.741502]
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2781 [D loss: 0.682417, acc.: 57.62%] [G loss: 0.737794]
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2782 [D loss: 0.679917, acc.: 56.64%] [G loss: 0.736848]
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2783 [D loss: 0.687735, acc.: 53.91%] [G loss: 0.733701]
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2784 [D loss: 0.686793, acc.: 54.69%] [G loss: 0.751684]
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2785 [D loss: 0.680610, acc.: 58.01%] [G loss: 0.725924]
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2786 [D loss: 0.691533, acc.: 54.49%] [G loss: 0.728196]
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2787 [D loss: 0.685673, acc.: 55.66%] [G loss: 0.731255]
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2788 [D loss: 0.682325, acc.: 58.79%] [G loss: 0.724631]
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2789 [D loss: 0.687383, acc.: 53.71%] [G loss: 0.735879]
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2790 [D loss: 0.688560, acc.: 54.30%] [G loss: 0.732340]
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2791 [D loss: 0.678841, acc.: 58.98%] [G loss: 0.740234]
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2792 [D loss: 0.675051, acc.: 56.64%] [G loss: 0.723015]
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2793 [D loss: 0.678093, acc.: 57.42%] [G loss: 0.736780]
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2794 [D loss: 0.674643, acc.: 58.20%] [G loss: 0.734197]
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2795 [D loss: 0.678838, acc.: 57.03%] [G loss: 0.746916]
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2796 [D loss: 0.681263, acc.: 59.18%] [G loss: 0.734853]
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2797 [D loss: 0.691788, acc.: 50.98%] [G loss: 0.728792]
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2798 [D loss: 0.678967, acc.: 56.05%] [G loss: 0.736638]
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2799 [D loss: 0.678390, acc.: 57.81%] [G loss: 0.755546]
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2800 [D loss: 0.686058, acc.: 55.86%] [G loss: 0.728234]
1/1 [==============================] - 0s 17ms/step
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2801 [D loss: 0.692203, acc.: 53.71%] [G loss: 0.735212]
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2802 [D loss: 0.694644, acc.: 52.54%] [G loss: 0.739778]
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2803 [D loss: 0.683301, acc.: 58.20%] [G loss: 0.742336]
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2804 [D loss: 0.684152, acc.: 56.25%] [G loss: 0.755822]
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2805 [D loss: 0.679371, acc.: 55.66%] [G loss: 0.735472]
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2806 [D loss: 0.683559, acc.: 57.81%] [G loss: 0.739823]
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2807 [D loss: 0.688086, acc.: 54.69%] [G loss: 0.740691]
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2808 [D loss: 0.679696, acc.: 55.86%] [G loss: 0.742033]
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2809 [D loss: 0.688562, acc.: 55.86%] [G loss: 0.753604]
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2810 [D loss: 0.680248, acc.: 58.01%] [G loss: 0.742279]
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2811 [D loss: 0.678357, acc.: 58.40%] [G loss: 0.730760]
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2812 [D loss: 0.684698, acc.: 55.47%] [G loss: 0.735360]
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2813 [D loss: 0.685884, acc.: 55.66%] [G loss: 0.733816]
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2814 [D loss: 0.684848, acc.: 55.66%] [G loss: 0.728232]
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2815 [D loss: 0.677914, acc.: 57.62%] [G loss: 0.735115]
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2816 [D loss: 0.680869, acc.: 58.01%] [G loss: 0.736155]
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2817 [D loss: 0.682390, acc.: 54.30%] [G loss: 0.743407]
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2818 [D loss: 0.684366, acc.: 56.45%] [G loss: 0.741616]
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2819 [D loss: 0.671551, acc.: 57.23%] [G loss: 0.726446]
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2820 [D loss: 0.669747, acc.: 63.28%] [G loss: 0.732288]
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2821 [D loss: 0.678344, acc.: 58.01%] [G loss: 0.735292]
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2822 [D loss: 0.685186, acc.: 54.69%] [G loss: 0.737109]
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2823 [D loss: 0.675853, acc.: 60.55%] [G loss: 0.726117]
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2824 [D loss: 0.684361, acc.: 55.66%] [G loss: 0.727061]
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2825 [D loss: 0.680771, acc.: 57.42%] [G loss: 0.717803]
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2826 [D loss: 0.680487, acc.: 54.30%] [G loss: 0.729037]
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2827 [D loss: 0.676533, acc.: 57.42%] [G loss: 0.734378]
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2828 [D loss: 0.679954, acc.: 57.03%] [G loss: 0.724881]
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2829 [D loss: 0.686613, acc.: 56.84%] [G loss: 0.738274]
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2830 [D loss: 0.684397, acc.: 53.52%] [G loss: 0.749101]
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2831 [D loss: 0.683113, acc.: 56.45%] [G loss: 0.742187]
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2832 [D loss: 0.687212, acc.: 55.08%] [G loss: 0.743257]
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2833 [D loss: 0.689532, acc.: 54.69%] [G loss: 0.744068]
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2834 [D loss: 0.685790, acc.: 56.45%] [G loss: 0.748471]
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2835 [D loss: 0.682802, acc.: 57.23%] [G loss: 0.754295]
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2836 [D loss: 0.678540, acc.: 57.42%] [G loss: 0.733474]
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2837 [D loss: 0.690242, acc.: 52.93%] [G loss: 0.738975]
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2838 [D loss: 0.677508, acc.: 58.98%] [G loss: 0.743083]
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2839 [D loss: 0.677352, acc.: 59.38%] [G loss: 0.742290]
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2840 [D loss: 0.684266, acc.: 55.47%] [G loss: 0.733307]
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2841 [D loss: 0.684126, acc.: 58.59%] [G loss: 0.729060]
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2842 [D loss: 0.680454, acc.: 56.84%] [G loss: 0.731052]
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2843 [D loss: 0.680352, acc.: 56.84%] [G loss: 0.734488]
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2844 [D loss: 0.690640, acc.: 51.37%] [G loss: 0.728840]
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2845 [D loss: 0.675974, acc.: 58.79%] [G loss: 0.744795]
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2846 [D loss: 0.676250, acc.: 55.86%] [G loss: 0.736968]
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2847 [D loss: 0.680600, acc.: 58.98%] [G loss: 0.746680]
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2848 [D loss: 0.686584, acc.: 56.64%] [G loss: 0.725861]
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2849 [D loss: 0.674319, acc.: 60.55%] [G loss: 0.740638]
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2850 [D loss: 0.677398, acc.: 57.42%] [G loss: 0.730122]
1/1 [==============================] - 0s 15ms/step
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2851 [D loss: 0.683375, acc.: 56.25%] [G loss: 0.730148]
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2852 [D loss: 0.687762, acc.: 54.69%] [G loss: 0.738823]
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2853 [D loss: 0.681949, acc.: 58.59%] [G loss: 0.719478]
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2854 [D loss: 0.671806, acc.: 58.40%] [G loss: 0.732716]
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2855 [D loss: 0.678351, acc.: 58.20%] [G loss: 0.748384]
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2856 [D loss: 0.686938, acc.: 53.12%] [G loss: 0.725927]
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2857 [D loss: 0.687497, acc.: 56.45%] [G loss: 0.740980]
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2858 [D loss: 0.685185, acc.: 56.84%] [G loss: 0.747624]
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2859 [D loss: 0.674176, acc.: 59.96%] [G loss: 0.740423]
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2860 [D loss: 0.686342, acc.: 55.86%] [G loss: 0.729076]
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2861 [D loss: 0.680145, acc.: 57.23%] [G loss: 0.745389]
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2862 [D loss: 0.684120, acc.: 54.10%] [G loss: 0.739969]
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2863 [D loss: 0.677857, acc.: 58.40%] [G loss: 0.737501]
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2864 [D loss: 0.668899, acc.: 61.52%] [G loss: 0.740256]
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2865 [D loss: 0.679214, acc.: 57.81%] [G loss: 0.727246]
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2866 [D loss: 0.680696, acc.: 56.64%] [G loss: 0.735417]
8/8 [==============================] - 0s 2ms/step
2867 [D loss: 0.685755, acc.: 54.49%] [G loss: 0.734525]
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2868 [D loss: 0.682372, acc.: 56.84%] [G loss: 0.732093]
8/8 [==============================] - 0s 2ms/step
2869 [D loss: 0.688861, acc.: 55.47%] [G loss: 0.739912]
8/8 [==============================] - 0s 2ms/step
2870 [D loss: 0.672445, acc.: 60.35%] [G loss: 0.746662]
8/8 [==============================] - 0s 2ms/step
2871 [D loss: 0.679204, acc.: 60.16%] [G loss: 0.745377]
8/8 [==============================] - 0s 2ms/step
2872 [D loss: 0.673823, acc.: 58.40%] [G loss: 0.759226]
8/8 [==============================] - 0s 2ms/step
2873 [D loss: 0.673512, acc.: 59.96%] [G loss: 0.729394]
8/8 [==============================] - 0s 2ms/step
2874 [D loss: 0.679374, acc.: 58.01%] [G loss: 0.747319]
8/8 [==============================] - 0s 2ms/step
2875 [D loss: 0.688402, acc.: 56.64%] [G loss: 0.742370]
8/8 [==============================] - 0s 2ms/step
2876 [D loss: 0.677225, acc.: 55.86%] [G loss: 0.733043]
8/8 [==============================] - 0s 2ms/step
2877 [D loss: 0.676444, acc.: 58.98%] [G loss: 0.729278]
8/8 [==============================] - 0s 2ms/step
2878 [D loss: 0.688626, acc.: 55.08%] [G loss: 0.715138]
8/8 [==============================] - 0s 2ms/step
2879 [D loss: 0.682202, acc.: 58.01%] [G loss: 0.727773]
8/8 [==============================] - 0s 2ms/step
2880 [D loss: 0.687897, acc.: 54.49%] [G loss: 0.727725]
8/8 [==============================] - 0s 2ms/step
2881 [D loss: 0.686530, acc.: 56.45%] [G loss: 0.734872]
8/8 [==============================] - 0s 2ms/step
2882 [D loss: 0.674407, acc.: 59.77%] [G loss: 0.726511]
8/8 [==============================] - 0s 2ms/step
2883 [D loss: 0.689047, acc.: 54.49%] [G loss: 0.725642]
8/8 [==============================] - 0s 2ms/step
2884 [D loss: 0.672172, acc.: 61.33%] [G loss: 0.743318]
8/8 [==============================] - 0s 2ms/step
2885 [D loss: 0.681336, acc.: 55.27%] [G loss: 0.744142]
8/8 [==============================] - 0s 2ms/step
2886 [D loss: 0.681406, acc.: 58.79%] [G loss: 0.743551]
8/8 [==============================] - 0s 2ms/step
2887 [D loss: 0.673381, acc.: 57.81%] [G loss: 0.744473]
8/8 [==============================] - 0s 2ms/step
2888 [D loss: 0.680015, acc.: 56.84%] [G loss: 0.746348]
8/8 [==============================] - 0s 2ms/step
2889 [D loss: 0.682338, acc.: 55.08%] [G loss: 0.730891]
8/8 [==============================] - 0s 2ms/step
2890 [D loss: 0.681976, acc.: 56.25%] [G loss: 0.745117]
8/8 [==============================] - 0s 2ms/step
2891 [D loss: 0.678166, acc.: 57.81%] [G loss: 0.724840]
8/8 [==============================] - 0s 2ms/step
2892 [D loss: 0.678505, acc.: 57.81%] [G loss: 0.728063]
8/8 [==============================] - 0s 2ms/step
2893 [D loss: 0.674724, acc.: 59.38%] [G loss: 0.739863]
8/8 [==============================] - 0s 2ms/step
2894 [D loss: 0.684061, acc.: 54.69%] [G loss: 0.733551]
8/8 [==============================] - 0s 2ms/step
2895 [D loss: 0.677682, acc.: 58.59%] [G loss: 0.732173]
8/8 [==============================] - 0s 2ms/step
2896 [D loss: 0.681093, acc.: 57.81%] [G loss: 0.739293]
8/8 [==============================] - 0s 2ms/step
2897 [D loss: 0.688039, acc.: 55.08%] [G loss: 0.731457]
8/8 [==============================] - 0s 2ms/step
2898 [D loss: 0.684551, acc.: 55.47%] [G loss: 0.734987]
8/8 [==============================] - 0s 2ms/step
2899 [D loss: 0.680221, acc.: 56.64%] [G loss: 0.731955]
8/8 [==============================] - 0s 2ms/step
2900 [D loss: 0.681060, acc.: 59.18%] [G loss: 0.747460]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
2901 [D loss: 0.685423, acc.: 53.71%] [G loss: 0.735130]
8/8 [==============================] - 0s 2ms/step
2902 [D loss: 0.672534, acc.: 61.52%] [G loss: 0.744322]
8/8 [==============================] - 0s 2ms/step
2903 [D loss: 0.683931, acc.: 54.69%] [G loss: 0.724674]
8/8 [==============================] - 0s 2ms/step
2904 [D loss: 0.689002, acc.: 53.52%] [G loss: 0.737772]
8/8 [==============================] - 0s 2ms/step
2905 [D loss: 0.679711, acc.: 57.23%] [G loss: 0.742052]
8/8 [==============================] - 0s 2ms/step
2906 [D loss: 0.678703, acc.: 56.05%] [G loss: 0.719286]
8/8 [==============================] - 0s 2ms/step
2907 [D loss: 0.686412, acc.: 54.30%] [G loss: 0.727869]
8/8 [==============================] - 0s 2ms/step
2908 [D loss: 0.680921, acc.: 55.86%] [G loss: 0.738773]
8/8 [==============================] - 0s 2ms/step
2909 [D loss: 0.685955, acc.: 54.69%] [G loss: 0.739909]
8/8 [==============================] - 0s 2ms/step
2910 [D loss: 0.682426, acc.: 60.16%] [G loss: 0.728868]
8/8 [==============================] - 0s 2ms/step
2911 [D loss: 0.690277, acc.: 52.34%] [G loss: 0.748304]
8/8 [==============================] - 0s 2ms/step
2912 [D loss: 0.680453, acc.: 55.66%] [G loss: 0.740934]
8/8 [==============================] - 0s 2ms/step
2913 [D loss: 0.680617, acc.: 55.08%] [G loss: 0.738050]
8/8 [==============================] - 0s 2ms/step
2914 [D loss: 0.679277, acc.: 57.23%] [G loss: 0.733882]
8/8 [==============================] - 0s 2ms/step
2915 [D loss: 0.688868, acc.: 52.73%] [G loss: 0.734904]
8/8 [==============================] - 0s 2ms/step
2916 [D loss: 0.685242, acc.: 53.12%] [G loss: 0.748743]
8/8 [==============================] - 0s 3ms/step
2917 [D loss: 0.676537, acc.: 58.01%] [G loss: 0.748494]
8/8 [==============================] - 0s 2ms/step
2918 [D loss: 0.675565, acc.: 60.16%] [G loss: 0.741842]
8/8 [==============================] - 0s 2ms/step
2919 [D loss: 0.679255, acc.: 59.57%] [G loss: 0.735126]
8/8 [==============================] - 0s 2ms/step
2920 [D loss: 0.685654, acc.: 55.47%] [G loss: 0.736356]
8/8 [==============================] - 0s 2ms/step
2921 [D loss: 0.674247, acc.: 58.59%] [G loss: 0.742781]
8/8 [==============================] - 0s 2ms/step
2922 [D loss: 0.688199, acc.: 54.88%] [G loss: 0.743575]
8/8 [==============================] - 0s 2ms/step
2923 [D loss: 0.676926, acc.: 56.25%] [G loss: 0.744724]
8/8 [==============================] - 0s 2ms/step
2924 [D loss: 0.675989, acc.: 58.01%] [G loss: 0.742232]
8/8 [==============================] - 0s 2ms/step
2925 [D loss: 0.673619, acc.: 59.57%] [G loss: 0.738319]
8/8 [==============================] - 0s 2ms/step
2926 [D loss: 0.681844, acc.: 55.66%] [G loss: 0.746372]
8/8 [==============================] - 0s 2ms/step
2927 [D loss: 0.671748, acc.: 57.03%] [G loss: 0.735471]
8/8 [==============================] - 0s 2ms/step
2928 [D loss: 0.679278, acc.: 57.42%] [G loss: 0.751260]
8/8 [==============================] - 0s 2ms/step
2929 [D loss: 0.687076, acc.: 54.30%] [G loss: 0.745366]
8/8 [==============================] - 0s 2ms/step
2930 [D loss: 0.675796, acc.: 59.38%] [G loss: 0.738213]
8/8 [==============================] - 0s 2ms/step
2931 [D loss: 0.684562, acc.: 56.45%] [G loss: 0.742511]
8/8 [==============================] - 0s 2ms/step
2932 [D loss: 0.685593, acc.: 54.69%] [G loss: 0.726400]
8/8 [==============================] - 0s 2ms/step
2933 [D loss: 0.681288, acc.: 58.40%] [G loss: 0.713198]
8/8 [==============================] - 0s 2ms/step
2934 [D loss: 0.689833, acc.: 55.66%] [G loss: 0.719804]
8/8 [==============================] - 0s 2ms/step
2935 [D loss: 0.684072, acc.: 54.69%] [G loss: 0.734819]
8/8 [==============================] - 0s 2ms/step
2936 [D loss: 0.675951, acc.: 59.38%] [G loss: 0.745464]
8/8 [==============================] - 0s 2ms/step
2937 [D loss: 0.687316, acc.: 54.10%] [G loss: 0.730200]
8/8 [==============================] - 0s 2ms/step
2938 [D loss: 0.673363, acc.: 59.77%] [G loss: 0.725453]
8/8 [==============================] - 0s 2ms/step
2939 [D loss: 0.690181, acc.: 53.12%] [G loss: 0.740520]
8/8 [==============================] - 0s 2ms/step
2940 [D loss: 0.675633, acc.: 58.59%] [G loss: 0.738481]
8/8 [==============================] - 0s 2ms/step
2941 [D loss: 0.682247, acc.: 56.64%] [G loss: 0.743137]
8/8 [==============================] - 0s 2ms/step
2942 [D loss: 0.685949, acc.: 53.71%] [G loss: 0.740497]
8/8 [==============================] - 0s 2ms/step
2943 [D loss: 0.684893, acc.: 53.71%] [G loss: 0.735637]
8/8 [==============================] - 0s 2ms/step
2944 [D loss: 0.679616, acc.: 54.30%] [G loss: 0.732955]
8/8 [==============================] - 0s 2ms/step
2945 [D loss: 0.689085, acc.: 52.93%] [G loss: 0.748472]
8/8 [==============================] - 0s 2ms/step
2946 [D loss: 0.680164, acc.: 56.05%] [G loss: 0.747391]
8/8 [==============================] - 0s 2ms/step
2947 [D loss: 0.685463, acc.: 56.45%] [G loss: 0.758880]
8/8 [==============================] - 0s 2ms/step
2948 [D loss: 0.681737, acc.: 58.59%] [G loss: 0.747604]
8/8 [==============================] - 0s 2ms/step
2949 [D loss: 0.671912, acc.: 60.35%] [G loss: 0.751444]
8/8 [==============================] - 0s 2ms/step
2950 [D loss: 0.674922, acc.: 58.79%] [G loss: 0.748468]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
2951 [D loss: 0.687175, acc.: 56.64%] [G loss: 0.751808]
8/8 [==============================] - 0s 2ms/step
2952 [D loss: 0.674155, acc.: 60.35%] [G loss: 0.745208]
8/8 [==============================] - 0s 2ms/step
2953 [D loss: 0.677244, acc.: 58.98%] [G loss: 0.741705]
8/8 [==============================] - 0s 2ms/step
2954 [D loss: 0.680912, acc.: 57.23%] [G loss: 0.734824]
8/8 [==============================] - 0s 2ms/step
2955 [D loss: 0.680410, acc.: 57.23%] [G loss: 0.723690]
8/8 [==============================] - 0s 2ms/step
2956 [D loss: 0.677397, acc.: 57.62%] [G loss: 0.735504]
8/8 [==============================] - 0s 2ms/step
2957 [D loss: 0.680666, acc.: 56.25%] [G loss: 0.737872]
8/8 [==============================] - 0s 2ms/step
2958 [D loss: 0.680132, acc.: 57.23%] [G loss: 0.734732]
8/8 [==============================] - 0s 2ms/step
2959 [D loss: 0.683755, acc.: 55.86%] [G loss: 0.755211]
8/8 [==============================] - 0s 2ms/step
2960 [D loss: 0.675558, acc.: 57.42%] [G loss: 0.747544]
8/8 [==============================] - 0s 2ms/step
2961 [D loss: 0.683180, acc.: 57.23%] [G loss: 0.752628]
8/8 [==============================] - 0s 2ms/step
2962 [D loss: 0.687292, acc.: 54.88%] [G loss: 0.747492]
8/8 [==============================] - 0s 2ms/step
2963 [D loss: 0.682711, acc.: 54.69%] [G loss: 0.752056]
8/8 [==============================] - 0s 2ms/step
2964 [D loss: 0.673798, acc.: 58.59%] [G loss: 0.746606]
8/8 [==============================] - 0s 2ms/step
2965 [D loss: 0.684038, acc.: 55.08%] [G loss: 0.746562]
8/8 [==============================] - 0s 2ms/step
2966 [D loss: 0.687517, acc.: 54.30%] [G loss: 0.748361]
8/8 [==============================] - 0s 2ms/step
2967 [D loss: 0.681798, acc.: 56.25%] [G loss: 0.744431]
8/8 [==============================] - 0s 2ms/step
2968 [D loss: 0.682826, acc.: 56.25%] [G loss: 0.752941]
8/8 [==============================] - 0s 2ms/step
2969 [D loss: 0.686324, acc.: 55.08%] [G loss: 0.738948]
8/8 [==============================] - 0s 2ms/step
2970 [D loss: 0.675856, acc.: 58.59%] [G loss: 0.726748]
8/8 [==============================] - 0s 2ms/step
2971 [D loss: 0.681513, acc.: 56.05%] [G loss: 0.741465]
8/8 [==============================] - 0s 2ms/step
2972 [D loss: 0.682867, acc.: 56.45%] [G loss: 0.732497]
8/8 [==============================] - 0s 2ms/step
2973 [D loss: 0.687775, acc.: 54.10%] [G loss: 0.730503]
8/8 [==============================] - 0s 2ms/step
2974 [D loss: 0.680756, acc.: 57.81%] [G loss: 0.733981]
8/8 [==============================] - 0s 2ms/step
2975 [D loss: 0.680344, acc.: 58.20%] [G loss: 0.732587]
8/8 [==============================] - 0s 2ms/step
2976 [D loss: 0.673689, acc.: 59.18%] [G loss: 0.717959]
8/8 [==============================] - 0s 2ms/step
2977 [D loss: 0.682891, acc.: 57.03%] [G loss: 0.751140]
8/8 [==============================] - 0s 2ms/step
2978 [D loss: 0.680409, acc.: 57.81%] [G loss: 0.754480]
8/8 [==============================] - 0s 2ms/step
2979 [D loss: 0.677068, acc.: 59.96%] [G loss: 0.751031]
8/8 [==============================] - 0s 2ms/step
2980 [D loss: 0.676788, acc.: 57.23%] [G loss: 0.760894]
8/8 [==============================] - 0s 2ms/step
2981 [D loss: 0.672972, acc.: 59.38%] [G loss: 0.739621]
8/8 [==============================] - 0s 2ms/step
2982 [D loss: 0.678547, acc.: 59.57%] [G loss: 0.756675]
8/8 [==============================] - 0s 2ms/step
2983 [D loss: 0.681699, acc.: 58.01%] [G loss: 0.742999]
8/8 [==============================] - 0s 2ms/step
2984 [D loss: 0.685200, acc.: 57.42%] [G loss: 0.753664]
8/8 [==============================] - 0s 2ms/step
2985 [D loss: 0.675318, acc.: 57.81%] [G loss: 0.747782]
8/8 [==============================] - 0s 2ms/step
2986 [D loss: 0.683814, acc.: 53.91%] [G loss: 0.728509]
8/8 [==============================] - 0s 2ms/step
2987 [D loss: 0.684129, acc.: 57.03%] [G loss: 0.732041]
8/8 [==============================] - 0s 2ms/step
2988 [D loss: 0.684113, acc.: 54.30%] [G loss: 0.749416]
8/8 [==============================] - 0s 2ms/step
2989 [D loss: 0.685515, acc.: 55.86%] [G loss: 0.753388]
8/8 [==============================] - 0s 2ms/step
2990 [D loss: 0.679027, acc.: 55.08%] [G loss: 0.735903]
8/8 [==============================] - 0s 2ms/step
2991 [D loss: 0.682882, acc.: 56.84%] [G loss: 0.743936]
8/8 [==============================] - 0s 2ms/step
2992 [D loss: 0.682252, acc.: 53.71%] [G loss: 0.748911]
8/8 [==============================] - 0s 2ms/step
2993 [D loss: 0.679727, acc.: 57.03%] [G loss: 0.740013]
8/8 [==============================] - 0s 2ms/step
2994 [D loss: 0.696064, acc.: 53.32%] [G loss: 0.751093]
8/8 [==============================] - 0s 2ms/step
2995 [D loss: 0.682674, acc.: 56.05%] [G loss: 0.747238]
8/8 [==============================] - 0s 2ms/step
2996 [D loss: 0.679983, acc.: 58.98%] [G loss: 0.742158]
8/8 [==============================] - 0s 2ms/step
2997 [D loss: 0.672649, acc.: 61.13%] [G loss: 0.732214]
8/8 [==============================] - 0s 2ms/step
2998 [D loss: 0.673912, acc.: 56.25%] [G loss: 0.740171]
8/8 [==============================] - 0s 2ms/step
2999 [D loss: 0.677711, acc.: 59.77%] [G loss: 0.739667]

Loss Curve

plot_losses(dcgan.d_losses, dcgan.g_losses)

Accuracy Curve

plot_accuracy(dcgan.d_accuracy)

Generated Images at Different Epochs (Improving the Discriminator)

At 100 Epochs

At 1000 Epochs

At 2950 Epochs

Results

Initially, the generator loss is quite high, around 4, while the discriminator loss is relatively low, around 0.2. As training progresses, the generator loss decreases, and the discriminator loss increases, eventually converging with both losses around 0.7. This trend suggests that the generator is improving in generating more realistic samples over time, while the discriminator is finding it increasingly challenging to distinguish between real and generated data. When both losses stabilize around a similar value, it often indicates that the GAN has reached a balance, with the generator producing sufficiently realistic data that the discriminator cannot easily differentiate from real data.

The discriminator's accuracy starts very high, around 99%, and gradually decreases, fluctuating between 50% and 60%. This pattern suggests that initially, the discriminator can easily distinguish between real and generated data, as the generator's outputs are not yet realistic. However, as the generator improves, it becomes harder for the discriminator to differentiate, leading to a decrease in accuracy. The fluctuation around 50% to 60% indicates that the discriminator is no longer confidently distinguishing between real and fake samples, suggesting that the generator is producing more convincing outputs.

The generated images have shown visual improvement, with more classes becoming recognizable. Classes such as R, I, Y, M, O, G, and X are now clearer and easier to distinguish.

Using ReLU for The Generator's Activation Function

What is ReLU activation function

The ReLU (Rectified Linear Unit) activation function is a popular non-linear activation function used in neural networks, particularly in deep learning models. The output of ReLU is zero for any negative input and equal to the input for positive values. This results in outputs ranging from 0 to infinity.

ReLU introduces non-linearity into the model, allowing the generator to learn complex mappings from the latent space to the image space. This is essential for generating high-quality, realistic images.

ReLU's output is zero for negative inputs, leading to sparse activations. This sparsity can improve model performance and reduce the risk of overfitting by encouraging the generator to focus on the most relevant features.

What changed from the previous model

• Generator's activation function is changed from Leaky ReLU to ReLU

Difference between ReLU can Leaky ReLU

ReLU and Leaky ReLU differ in several key aspects for the generator in a GAN. ReLU outputs zero for negative values, while Leaky ReLU provides a small, non-zero output for negative inputs. In terms of gradient flow, ReLU has a gradient of 1 for positive inputs, whereas Leaky ReLU maintains a small gradient for negative inputs.

Why did we use ReLU for the Generator's Activation Function

Despite the improved quality of the images generated in the previous model, the generator is still struggling to learn the image patterns effectively, resulting in some blurry images with patches of white. Therefore, we have decided to use ReLU to enhance the learning process. By incorporating ReLU, we aim to leverage its properties to better capture the intricate details of the images and improve the overall clarity and realism of the generated outputs.

References

https://machinelearningmastery.com/rectified-linear-activation-function-for-deep-learning-neural-networks/

https://machinelearningmastery.com/how-to-train-stable-generative-adversarial-networks/

class DCGAN():
    
    # this is the function to build the generator neural network
    def build_generator(self):
        model = Sequential()

        model.add(Dense(128 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 128)))
        
        model.add(UpSampling2D())
        model.add(Conv2D(128, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(UpSampling2D())
        model.add(Conv2D(64, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(Conv2D(self.channels, kernel_size=3, padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)
    
    
    def build_discriminator(self):
        model = Sequential(name='Discriminator')
        model.add(Conv2D(128, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Flatten())
        
        # Add one more dense layer
        model.add(Dense(256))  # Adjust the units as per your architecture needs
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        img = Input(shape=self.img_shape)
        validity = model(img)
        return Model(img, validity)
        
    def __init__(self, rows, cols, channels, z = 100):
        # Input shape
        self.img_rows = rows  # generated image height
        self.img_cols = cols  # generated image width
        self.channels = channels  # generated image channel
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = z  # the input is 1-D vector of noise
        # Reduce learning rate from 0.001 to 0.0002, and beta1 from 0.9 to 0.5, which can stablize training and reduce oscillation
        optimizer = Adam(learning_rate=0.0002, beta_1=0.5)
        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss='binary_crossentropy',
            optimizer=optimizer,
            metrics=['accuracy'])
        # Build the generator
        self.generator = self.build_generator()
        # The generator takes noise as input and generates images
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)
        # For the combined model we will only train the generator
        self.discriminator.trainable = False
        # The discriminator takes generated images as input and determines validity
        valid = self.discriminator(img)
        # The combined model (stacked generator and discriminator)
        # Trains the generator to fool the discriminator
        self.combined = Model(z, valid)
        self.combined.compile(loss='binary_crossentropy',
            optimizer=optimizer)
        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []
        
    def train(self, epochs, batch_size=128, save_interval=50):
        # Assuming your data is in a pandas DataFrame `df`
        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values  # assuming first column is labels, rest are pixels
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)  # reshape to image shape
        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))
        
        for epoch in range(epochs):
            # ---------------------
            # Train Discriminator
            # ---------------------
            # Select a random half of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs = X_train[idx]
            
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            gen_imgs = self.generator.predict(noise)
            
            # Train the discriminator (classify real images as 1 and generated images as 0)
            d_loss_real = self.discriminator.train_on_batch(imgs, valid)
            d_loss_fake = self.discriminator.train_on_batch(gen_imgs, fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)
            
            # ---------------------
            # Train Generator
            # ---------------------
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            
            # Train the generator (generator wants discriminator to predict generated images as 1)
            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            # Print progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100 * d_loss[1], g_loss))
            
            # If at save interval => save generated image samples
            if epoch % save_interval == 0:
                self.save_imgs(epoch)


    def save_imgs(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        # gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/dcgan', exist_ok=True)
        os.makedirs('generated_images/dcgan/generatorReLU', exist_ok=True)
        fig.savefig("generated_images/dcgan/generatorReLU/dcgan_{:d}.png".format(epoch))
        plt.close()

dcgan = DCGAN(28,28,1)
dcgan.train(epochs=3000, batch_size=256, save_interval=50)

Model: "Discriminator"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_11 (Conv2D)          (None, 14, 14, 128)       1280      
                                                                 
 leaky_re_lu_10 (LeakyReLU)  (None, 14, 14, 128)       0         
                                                                 
 dropout_5 (Dropout)         (None, 14, 14, 128)       0         
                                                                 
 conv2d_12 (Conv2D)          (None, 7, 7, 128)         147584    
                                                                 
 leaky_re_lu_11 (LeakyReLU)  (None, 7, 7, 128)         0         
                                                                 
 dropout_6 (Dropout)         (None, 7, 7, 128)         0         
                                                                 
 conv2d_13 (Conv2D)          (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_12 (LeakyReLU)  (None, 4, 4, 256)         0         
                                                                 
 dropout_7 (Dropout)         (None, 4, 4, 256)         0         
                                                                 
 flatten_2 (Flatten)         (None, 4096)              0         
                                                                 
 dense_5 (Dense)             (None, 256)               1048832   
                                                                 
 leaky_re_lu_13 (LeakyReLU)  (None, 256)               0         
                                                                 
 dense_6 (Dense)             (None, 1)                 257       
                                                                 
=================================================================
Total params: 1,493,121
Trainable params: 1,493,121
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_2"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_7 (Dense)             (None, 6272)              633472    
                                                                 
 reshape_2 (Reshape)         (None, 7, 7, 128)         0         
                                                                 
 up_sampling2d_4 (UpSampling  (None, 14, 14, 128)      0         
 2D)                                                             
                                                                 
 conv2d_14 (Conv2D)          (None, 14, 14, 128)       147584    
                                                                 
 batch_normalization_4 (Batc  (None, 14, 14, 128)      512       
 hNormalization)                                                 
                                                                 
 activation_2 (Activation)   (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_5 (UpSampling  (None, 28, 28, 128)      0         
 2D)                                                             
                                                                 
 conv2d_15 (Conv2D)          (None, 28, 28, 64)        73792     
                                                                 
 batch_normalization_5 (Batc  (None, 28, 28, 64)       256       
 hNormalization)                                                 
                                                                 
 activation_3 (Activation)   (None, 28, 28, 64)        0         
                                                                 
 conv2d_16 (Conv2D)          (None, 28, 28, 1)         577       
                                                                 
 activation_4 (Activation)   (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 856,193
Trainable params: 855,809
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 0s 2ms/step
0 [D loss: 0.747605, acc.: 35.55%] [G loss: 0.659055]
1/1 [==============================] - 0s 65ms/step
8/8 [==============================] - 0s 3ms/step
1 [D loss: 0.690158, acc.: 51.56%] [G loss: 0.709701]
8/8 [==============================] - 0s 4ms/step
2 [D loss: 0.665135, acc.: 94.34%] [G loss: 0.759639]
8/8 [==============================] - 0s 3ms/step
3 [D loss: 0.638869, acc.: 96.29%] [G loss: 0.819388]
8/8 [==============================] - 0s 2ms/step
4 [D loss: 0.609963, acc.: 90.82%] [G loss: 0.884547]
8/8 [==============================] - 0s 2ms/step
5 [D loss: 0.572678, acc.: 88.87%] [G loss: 0.948456]
8/8 [==============================] - 0s 2ms/step
6 [D loss: 0.522274, acc.: 91.02%] [G loss: 0.982704]
8/8 [==============================] - 0s 2ms/step
7 [D loss: 0.468084, acc.: 92.58%] [G loss: 0.928087]
8/8 [==============================] - 0s 2ms/step
8 [D loss: 0.400430, acc.: 94.73%] [G loss: 0.809170]
8/8 [==============================] - 0s 2ms/step
9 [D loss: 0.318151, acc.: 96.48%] [G loss: 0.656174]
8/8 [==============================] - 0s 2ms/step
10 [D loss: 0.290455, acc.: 95.90%] [G loss: 0.588733]
8/8 [==============================] - 0s 2ms/step
11 [D loss: 0.322192, acc.: 95.12%] [G loss: 0.970770]
8/8 [==============================] - 0s 2ms/step
12 [D loss: 0.416918, acc.: 88.09%] [G loss: 1.711396]
8/8 [==============================] - 0s 2ms/step
13 [D loss: 0.534367, acc.: 83.40%] [G loss: 1.683226]
8/8 [==============================] - 0s 2ms/step
14 [D loss: 0.391265, acc.: 91.02%] [G loss: 1.251752]
8/8 [==============================] - 0s 2ms/step
15 [D loss: 0.231163, acc.: 97.27%] [G loss: 0.875173]
8/8 [==============================] - 0s 2ms/step
16 [D loss: 0.232471, acc.: 98.63%] [G loss: 1.165284]
8/8 [==============================] - 0s 2ms/step
17 [D loss: 0.335558, acc.: 90.43%] [G loss: 2.163861]
8/8 [==============================] - 0s 2ms/step
18 [D loss: 0.639096, acc.: 59.18%] [G loss: 1.968271]
8/8 [==============================] - 0s 2ms/step
19 [D loss: 0.406363, acc.: 88.87%] [G loss: 1.297511]
8/8 [==============================] - 0s 2ms/step
20 [D loss: 0.245678, acc.: 97.85%] [G loss: 0.791470]
8/8 [==============================] - 0s 2ms/step
21 [D loss: 0.222428, acc.: 98.63%] [G loss: 0.726639]
8/8 [==============================] - 0s 2ms/step
22 [D loss: 0.293175, acc.: 93.95%] [G loss: 1.120762]
8/8 [==============================] - 0s 2ms/step
23 [D loss: 0.649253, acc.: 52.15%] [G loss: 1.303225]
8/8 [==============================] - 0s 2ms/step
24 [D loss: 0.914318, acc.: 36.33%] [G loss: 0.814520]
8/8 [==============================] - 0s 2ms/step
25 [D loss: 0.649009, acc.: 46.88%] [G loss: 0.639908]
8/8 [==============================] - 0s 2ms/step
26 [D loss: 0.642054, acc.: 46.09%] [G loss: 0.415729]
8/8 [==============================] - 0s 2ms/step
27 [D loss: 0.648106, acc.: 48.24%] [G loss: 0.431568]
8/8 [==============================] - 0s 2ms/step
28 [D loss: 0.691206, acc.: 46.48%] [G loss: 0.470920]
8/8 [==============================] - 0s 2ms/step
29 [D loss: 0.747195, acc.: 45.70%] [G loss: 0.606263]
8/8 [==============================] - 0s 2ms/step
30 [D loss: 0.779885, acc.: 41.21%] [G loss: 0.687530]
8/8 [==============================] - 0s 2ms/step
31 [D loss: 0.806183, acc.: 40.43%] [G loss: 0.829860]
8/8 [==============================] - 0s 2ms/step
32 [D loss: 0.762089, acc.: 44.92%] [G loss: 1.009914]
8/8 [==============================] - 0s 2ms/step
33 [D loss: 0.746842, acc.: 46.88%] [G loss: 1.123964]
8/8 [==============================] - 0s 2ms/step
34 [D loss: 0.767297, acc.: 46.29%] [G loss: 1.121636]
8/8 [==============================] - 0s 2ms/step
35 [D loss: 0.747997, acc.: 50.39%] [G loss: 1.134413]
8/8 [==============================] - 0s 2ms/step
36 [D loss: 0.692822, acc.: 58.20%] [G loss: 1.097804]
8/8 [==============================] - 0s 2ms/step
37 [D loss: 0.710982, acc.: 54.10%] [G loss: 1.065309]
8/8 [==============================] - 0s 2ms/step
38 [D loss: 0.689754, acc.: 57.23%] [G loss: 0.994186]
8/8 [==============================] - 0s 2ms/step
39 [D loss: 0.691343, acc.: 59.38%] [G loss: 0.959112]
8/8 [==============================] - 0s 2ms/step
40 [D loss: 0.665536, acc.: 63.87%] [G loss: 0.898441]
8/8 [==============================] - 0s 2ms/step
41 [D loss: 0.681091, acc.: 58.40%] [G loss: 0.888544]
8/8 [==============================] - 0s 2ms/step
42 [D loss: 0.649314, acc.: 62.30%] [G loss: 0.861145]
8/8 [==============================] - 0s 2ms/step
43 [D loss: 0.667331, acc.: 60.35%] [G loss: 0.825352]
8/8 [==============================] - 0s 2ms/step
44 [D loss: 0.636259, acc.: 64.65%] [G loss: 0.832851]
8/8 [==============================] - 0s 2ms/step
45 [D loss: 0.646390, acc.: 63.87%] [G loss: 0.845165]
8/8 [==============================] - 0s 2ms/step
46 [D loss: 0.663379, acc.: 59.38%] [G loss: 0.841431]
8/8 [==============================] - 0s 2ms/step
47 [D loss: 0.639847, acc.: 66.99%] [G loss: 0.827628]
8/8 [==============================] - 0s 2ms/step
48 [D loss: 0.644602, acc.: 65.23%] [G loss: 0.810255]
8/8 [==============================] - 0s 2ms/step
49 [D loss: 0.637822, acc.: 66.02%] [G loss: 0.799757]
8/8 [==============================] - 0s 2ms/step
50 [D loss: 0.634150, acc.: 64.65%] [G loss: 0.746885]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
51 [D loss: 0.609610, acc.: 70.51%] [G loss: 0.727811]
8/8 [==============================] - 0s 2ms/step
52 [D loss: 0.625419, acc.: 63.87%] [G loss: 0.719651]
8/8 [==============================] - 0s 2ms/step
53 [D loss: 0.620072, acc.: 68.75%] [G loss: 0.712744]
8/8 [==============================] - 0s 2ms/step
54 [D loss: 0.606518, acc.: 69.53%] [G loss: 0.730840]
8/8 [==============================] - 0s 2ms/step
55 [D loss: 0.603937, acc.: 69.34%] [G loss: 0.742944]
8/8 [==============================] - 0s 2ms/step
56 [D loss: 0.633804, acc.: 62.30%] [G loss: 0.739570]
8/8 [==============================] - 0s 2ms/step
57 [D loss: 0.618878, acc.: 66.99%] [G loss: 0.765281]
8/8 [==============================] - 0s 2ms/step
58 [D loss: 0.620283, acc.: 66.99%] [G loss: 0.768613]
8/8 [==============================] - 0s 2ms/step
59 [D loss: 0.629342, acc.: 66.21%] [G loss: 0.777874]
8/8 [==============================] - 0s 2ms/step
60 [D loss: 0.628802, acc.: 64.65%] [G loss: 0.780772]
8/8 [==============================] - 0s 2ms/step
61 [D loss: 0.640329, acc.: 63.48%] [G loss: 0.775845]
8/8 [==============================] - 0s 2ms/step
62 [D loss: 0.645269, acc.: 61.33%] [G loss: 0.791851]
8/8 [==============================] - 0s 2ms/step
63 [D loss: 0.665886, acc.: 57.03%] [G loss: 0.776936]
8/8 [==============================] - 0s 2ms/step
64 [D loss: 0.670024, acc.: 58.40%] [G loss: 0.772435]
8/8 [==============================] - 0s 2ms/step
65 [D loss: 0.672301, acc.: 54.69%] [G loss: 0.764311]
8/8 [==============================] - 0s 2ms/step
66 [D loss: 0.673007, acc.: 56.05%] [G loss: 0.767043]
8/8 [==============================] - 0s 2ms/step
67 [D loss: 0.678121, acc.: 56.05%] [G loss: 0.756292]
8/8 [==============================] - 0s 2ms/step
68 [D loss: 0.698209, acc.: 49.61%] [G loss: 0.757064]
8/8 [==============================] - 0s 2ms/step
69 [D loss: 0.703378, acc.: 47.27%] [G loss: 0.756465]
8/8 [==============================] - 0s 2ms/step
70 [D loss: 0.718362, acc.: 44.92%] [G loss: 0.770511]
8/8 [==============================] - 0s 2ms/step
71 [D loss: 0.716373, acc.: 46.48%] [G loss: 0.756430]
8/8 [==============================] - 0s 2ms/step
72 [D loss: 0.715183, acc.: 49.41%] [G loss: 0.762810]
8/8 [==============================] - 0s 2ms/step
73 [D loss: 0.713680, acc.: 47.46%] [G loss: 0.761725]
8/8 [==============================] - 0s 2ms/step
74 [D loss: 0.726271, acc.: 43.75%] [G loss: 0.759180]
8/8 [==============================] - 0s 2ms/step
75 [D loss: 0.711375, acc.: 48.83%] [G loss: 0.766039]
8/8 [==============================] - 0s 2ms/step
76 [D loss: 0.704619, acc.: 51.17%] [G loss: 0.758123]
8/8 [==============================] - 0s 2ms/step
77 [D loss: 0.687830, acc.: 55.08%] [G loss: 0.769765]
8/8 [==============================] - 0s 2ms/step
78 [D loss: 0.692960, acc.: 55.08%] [G loss: 0.776250]
8/8 [==============================] - 0s 2ms/step
79 [D loss: 0.669465, acc.: 60.74%] [G loss: 0.788747]
8/8 [==============================] - 0s 2ms/step
80 [D loss: 0.665493, acc.: 63.09%] [G loss: 0.770249]
8/8 [==============================] - 0s 2ms/step
81 [D loss: 0.648886, acc.: 61.33%] [G loss: 0.793240]
8/8 [==============================] - 0s 2ms/step
82 [D loss: 0.657585, acc.: 60.74%] [G loss: 0.783272]
8/8 [==============================] - 0s 2ms/step
83 [D loss: 0.634254, acc.: 65.23%] [G loss: 0.782965]
8/8 [==============================] - 0s 2ms/step
84 [D loss: 0.649270, acc.: 61.91%] [G loss: 0.798704]
8/8 [==============================] - 0s 2ms/step
85 [D loss: 0.641908, acc.: 61.52%] [G loss: 0.795052]
8/8 [==============================] - 0s 2ms/step
86 [D loss: 0.663938, acc.: 58.98%] [G loss: 0.791827]
8/8 [==============================] - 0s 2ms/step
87 [D loss: 0.644102, acc.: 60.94%] [G loss: 0.786715]
8/8 [==============================] - 0s 2ms/step
88 [D loss: 0.648367, acc.: 62.11%] [G loss: 0.774852]
8/8 [==============================] - 0s 2ms/step
89 [D loss: 0.651336, acc.: 63.28%] [G loss: 0.764187]
8/8 [==============================] - 0s 2ms/step
90 [D loss: 0.679462, acc.: 55.86%] [G loss: 0.745775]
8/8 [==============================] - 0s 2ms/step
91 [D loss: 0.665817, acc.: 61.33%] [G loss: 0.730142]
8/8 [==============================] - 0s 2ms/step
92 [D loss: 0.671057, acc.: 54.10%] [G loss: 0.707878]
8/8 [==============================] - 0s 2ms/step
93 [D loss: 0.665357, acc.: 56.84%] [G loss: 0.709990]
8/8 [==============================] - 0s 2ms/step
94 [D loss: 0.674944, acc.: 56.45%] [G loss: 0.706814]
8/8 [==============================] - 0s 2ms/step
95 [D loss: 0.676469, acc.: 55.86%] [G loss: 0.716918]
8/8 [==============================] - 0s 2ms/step
96 [D loss: 0.675960, acc.: 56.05%] [G loss: 0.729966]
8/8 [==============================] - 0s 2ms/step
97 [D loss: 0.674832, acc.: 58.98%] [G loss: 0.735070]
8/8 [==============================] - 0s 2ms/step
98 [D loss: 0.680289, acc.: 54.88%] [G loss: 0.736506]
8/8 [==============================] - 0s 2ms/step
99 [D loss: 0.674267, acc.: 56.25%] [G loss: 0.743221]
8/8 [==============================] - 0s 2ms/step
100 [D loss: 0.673444, acc.: 55.86%] [G loss: 0.768513]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
101 [D loss: 0.671050, acc.: 59.77%] [G loss: 0.780357]
8/8 [==============================] - 0s 2ms/step
102 [D loss: 0.665914, acc.: 63.28%] [G loss: 0.790500]
8/8 [==============================] - 0s 2ms/step
103 [D loss: 0.664263, acc.: 59.57%] [G loss: 0.783826]
8/8 [==============================] - 0s 2ms/step
104 [D loss: 0.661451, acc.: 61.91%] [G loss: 0.798986]
8/8 [==============================] - 0s 2ms/step
105 [D loss: 0.645281, acc.: 63.48%] [G loss: 0.799232]
8/8 [==============================] - 0s 2ms/step
106 [D loss: 0.645980, acc.: 63.67%] [G loss: 0.790005]
8/8 [==============================] - 0s 2ms/step
107 [D loss: 0.642647, acc.: 63.48%] [G loss: 0.796308]
8/8 [==============================] - 0s 2ms/step
108 [D loss: 0.654187, acc.: 61.33%] [G loss: 0.805153]
8/8 [==============================] - 0s 2ms/step
109 [D loss: 0.656980, acc.: 58.79%] [G loss: 0.782672]
8/8 [==============================] - 0s 2ms/step
110 [D loss: 0.674100, acc.: 53.91%] [G loss: 0.776655]
8/8 [==============================] - 0s 2ms/step
111 [D loss: 0.678759, acc.: 49.41%] [G loss: 0.803339]
8/8 [==============================] - 0s 2ms/step
112 [D loss: 0.673456, acc.: 56.84%] [G loss: 0.808815]
8/8 [==============================] - 0s 2ms/step
113 [D loss: 0.682151, acc.: 54.49%] [G loss: 0.799579]
8/8 [==============================] - 0s 2ms/step
114 [D loss: 0.701662, acc.: 49.02%] [G loss: 0.803673]
8/8 [==============================] - 0s 2ms/step
115 [D loss: 0.712798, acc.: 49.22%] [G loss: 0.821166]
8/8 [==============================] - 0s 2ms/step
116 [D loss: 0.713254, acc.: 47.27%] [G loss: 0.812380]
8/8 [==============================] - 0s 2ms/step
117 [D loss: 0.705732, acc.: 50.39%] [G loss: 0.811526]
8/8 [==============================] - 0s 2ms/step
118 [D loss: 0.709438, acc.: 51.95%] [G loss: 0.785610]
8/8 [==============================] - 0s 2ms/step
119 [D loss: 0.719737, acc.: 45.90%] [G loss: 0.793462]
8/8 [==============================] - 0s 2ms/step
120 [D loss: 0.724662, acc.: 45.51%] [G loss: 0.785231]
8/8 [==============================] - 0s 2ms/step
121 [D loss: 0.695884, acc.: 49.61%] [G loss: 0.801851]
8/8 [==============================] - 0s 2ms/step
122 [D loss: 0.699884, acc.: 50.39%] [G loss: 0.802992]
8/8 [==============================] - 0s 2ms/step
123 [D loss: 0.685545, acc.: 54.10%] [G loss: 0.793938]
8/8 [==============================] - 0s 2ms/step
124 [D loss: 0.708808, acc.: 48.63%] [G loss: 0.788155]
8/8 [==============================] - 0s 2ms/step
125 [D loss: 0.710087, acc.: 50.00%] [G loss: 0.796822]
8/8 [==============================] - 0s 2ms/step
126 [D loss: 0.679188, acc.: 56.64%] [G loss: 0.806771]
8/8 [==============================] - 0s 2ms/step
127 [D loss: 0.685375, acc.: 56.05%] [G loss: 0.806637]
8/8 [==============================] - 0s 2ms/step
128 [D loss: 0.700444, acc.: 47.46%] [G loss: 0.778519]
8/8 [==============================] - 0s 2ms/step
129 [D loss: 0.688828, acc.: 55.86%] [G loss: 0.804074]
8/8 [==============================] - 0s 2ms/step
130 [D loss: 0.690282, acc.: 53.32%] [G loss: 0.780554]
8/8 [==============================] - 0s 2ms/step
131 [D loss: 0.677249, acc.: 58.98%] [G loss: 0.772507]
8/8 [==============================] - 0s 2ms/step
132 [D loss: 0.679591, acc.: 57.42%] [G loss: 0.788784]
8/8 [==============================] - 0s 2ms/step
133 [D loss: 0.685195, acc.: 56.25%] [G loss: 0.780722]
8/8 [==============================] - 0s 2ms/step
134 [D loss: 0.691020, acc.: 55.47%] [G loss: 0.762556]
8/8 [==============================] - 0s 2ms/step
135 [D loss: 0.691818, acc.: 52.34%] [G loss: 0.740728]
8/8 [==============================] - 0s 2ms/step
136 [D loss: 0.687823, acc.: 55.47%] [G loss: 0.750586]
8/8 [==============================] - 0s 2ms/step
137 [D loss: 0.696587, acc.: 52.93%] [G loss: 0.760523]
8/8 [==============================] - 0s 2ms/step
138 [D loss: 0.695718, acc.: 52.54%] [G loss: 0.738678]
8/8 [==============================] - 0s 2ms/step
139 [D loss: 0.700172, acc.: 52.34%] [G loss: 0.750062]
8/8 [==============================] - 0s 2ms/step
140 [D loss: 0.713475, acc.: 45.90%] [G loss: 0.737543]
8/8 [==============================] - 0s 2ms/step
141 [D loss: 0.704309, acc.: 48.83%] [G loss: 0.744547]
8/8 [==============================] - 0s 2ms/step
142 [D loss: 0.708979, acc.: 48.05%] [G loss: 0.741278]
8/8 [==============================] - 0s 2ms/step
143 [D loss: 0.707457, acc.: 45.70%] [G loss: 0.744979]
8/8 [==============================] - 0s 2ms/step
144 [D loss: 0.721823, acc.: 41.60%] [G loss: 0.733502]
8/8 [==============================] - 0s 2ms/step
145 [D loss: 0.709541, acc.: 45.70%] [G loss: 0.724943]
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146 [D loss: 0.696550, acc.: 49.80%] [G loss: 0.731479]
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147 [D loss: 0.707675, acc.: 46.29%] [G loss: 0.731335]
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148 [D loss: 0.704612, acc.: 46.68%] [G loss: 0.728618]
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149 [D loss: 0.707339, acc.: 47.27%] [G loss: 0.730551]
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151 [D loss: 0.702225, acc.: 48.05%] [G loss: 0.738964]
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153 [D loss: 0.702006, acc.: 47.27%] [G loss: 0.736106]
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154 [D loss: 0.695640, acc.: 51.37%] [G loss: 0.746504]
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155 [D loss: 0.691723, acc.: 54.30%] [G loss: 0.755850]
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156 [D loss: 0.694671, acc.: 51.95%] [G loss: 0.754050]
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157 [D loss: 0.699063, acc.: 46.68%] [G loss: 0.759522]
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158 [D loss: 0.688838, acc.: 54.49%] [G loss: 0.758808]
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159 [D loss: 0.692156, acc.: 52.93%] [G loss: 0.761251]
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160 [D loss: 0.676968, acc.: 60.16%] [G loss: 0.761241]
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161 [D loss: 0.681677, acc.: 56.25%] [G loss: 0.754194]
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162 [D loss: 0.681440, acc.: 58.59%] [G loss: 0.749151]
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163 [D loss: 0.678212, acc.: 60.94%] [G loss: 0.751524]
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164 [D loss: 0.673400, acc.: 62.50%] [G loss: 0.752784]
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165 [D loss: 0.679850, acc.: 59.77%] [G loss: 0.757338]
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166 [D loss: 0.672063, acc.: 60.35%] [G loss: 0.753734]
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167 [D loss: 0.675188, acc.: 58.40%] [G loss: 0.751865]
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168 [D loss: 0.673577, acc.: 58.40%] [G loss: 0.744353]
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169 [D loss: 0.680297, acc.: 56.45%] [G loss: 0.748181]
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170 [D loss: 0.677678, acc.: 60.94%] [G loss: 0.748062]
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171 [D loss: 0.683953, acc.: 55.08%] [G loss: 0.747927]
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172 [D loss: 0.678789, acc.: 59.38%] [G loss: 0.748105]
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173 [D loss: 0.684947, acc.: 57.03%] [G loss: 0.752090]
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174 [D loss: 0.684674, acc.: 54.30%] [G loss: 0.756527]
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175 [D loss: 0.697726, acc.: 50.20%] [G loss: 0.743582]
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176 [D loss: 0.687597, acc.: 53.12%] [G loss: 0.739254]
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177 [D loss: 0.698392, acc.: 51.17%] [G loss: 0.737134]
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178 [D loss: 0.687858, acc.: 53.32%] [G loss: 0.742473]
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179 [D loss: 0.698747, acc.: 52.34%] [G loss: 0.736227]
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180 [D loss: 0.704508, acc.: 47.46%] [G loss: 0.740179]
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181 [D loss: 0.711315, acc.: 44.34%] [G loss: 0.733266]
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182 [D loss: 0.710497, acc.: 43.75%] [G loss: 0.743053]
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183 [D loss: 0.714499, acc.: 43.16%] [G loss: 0.748073]
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184 [D loss: 0.708924, acc.: 43.36%] [G loss: 0.736093]
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185 [D loss: 0.711485, acc.: 44.53%] [G loss: 0.730471]
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186 [D loss: 0.710689, acc.: 47.46%] [G loss: 0.733609]
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187 [D loss: 0.708473, acc.: 44.14%] [G loss: 0.729229]
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188 [D loss: 0.712871, acc.: 43.55%] [G loss: 0.729820]
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189 [D loss: 0.715163, acc.: 40.62%] [G loss: 0.731234]
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190 [D loss: 0.717589, acc.: 42.77%] [G loss: 0.748812]
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191 [D loss: 0.706299, acc.: 44.53%] [G loss: 0.744923]
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192 [D loss: 0.714317, acc.: 39.45%] [G loss: 0.738987]
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193 [D loss: 0.708927, acc.: 42.97%] [G loss: 0.744326]
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194 [D loss: 0.709334, acc.: 45.90%] [G loss: 0.742817]
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195 [D loss: 0.710996, acc.: 40.43%] [G loss: 0.742895]
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196 [D loss: 0.710886, acc.: 40.04%] [G loss: 0.737412]
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197 [D loss: 0.704657, acc.: 44.73%] [G loss: 0.748563]
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198 [D loss: 0.701768, acc.: 46.68%] [G loss: 0.746348]
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199 [D loss: 0.704124, acc.: 47.85%] [G loss: 0.745955]
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201 [D loss: 0.702715, acc.: 47.07%] [G loss: 0.747905]
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202 [D loss: 0.705114, acc.: 44.92%] [G loss: 0.744781]
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203 [D loss: 0.703511, acc.: 44.34%] [G loss: 0.744710]
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204 [D loss: 0.696930, acc.: 47.85%] [G loss: 0.742976]
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205 [D loss: 0.709477, acc.: 42.77%] [G loss: 0.746313]
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206 [D loss: 0.700499, acc.: 44.92%] [G loss: 0.741303]
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207 [D loss: 0.700417, acc.: 46.48%] [G loss: 0.743909]
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208 [D loss: 0.702485, acc.: 44.14%] [G loss: 0.744471]
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209 [D loss: 0.697411, acc.: 48.44%] [G loss: 0.745418]
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210 [D loss: 0.701229, acc.: 46.68%] [G loss: 0.753461]
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211 [D loss: 0.697659, acc.: 49.61%] [G loss: 0.744223]
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212 [D loss: 0.694178, acc.: 51.76%] [G loss: 0.750998]
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213 [D loss: 0.688687, acc.: 51.76%] [G loss: 0.748438]
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214 [D loss: 0.694651, acc.: 50.78%] [G loss: 0.748353]
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215 [D loss: 0.692161, acc.: 52.93%] [G loss: 0.748031]
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216 [D loss: 0.693378, acc.: 50.59%] [G loss: 0.748205]
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217 [D loss: 0.687997, acc.: 53.12%] [G loss: 0.738159]
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218 [D loss: 0.690744, acc.: 51.95%] [G loss: 0.741480]
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219 [D loss: 0.695368, acc.: 50.59%] [G loss: 0.741553]
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220 [D loss: 0.691008, acc.: 51.76%] [G loss: 0.732368]
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221 [D loss: 0.691702, acc.: 50.98%] [G loss: 0.736768]
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222 [D loss: 0.694122, acc.: 51.17%] [G loss: 0.740508]
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223 [D loss: 0.691585, acc.: 51.17%] [G loss: 0.738911]
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224 [D loss: 0.685319, acc.: 52.54%] [G loss: 0.743922]
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225 [D loss: 0.691749, acc.: 53.91%] [G loss: 0.746676]
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226 [D loss: 0.687167, acc.: 52.73%] [G loss: 0.740235]
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227 [D loss: 0.695085, acc.: 49.02%] [G loss: 0.743897]
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228 [D loss: 0.693406, acc.: 47.85%] [G loss: 0.740104]
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229 [D loss: 0.695662, acc.: 51.76%] [G loss: 0.754634]
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230 [D loss: 0.691239, acc.: 51.56%] [G loss: 0.747055]
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231 [D loss: 0.696697, acc.: 50.39%] [G loss: 0.740475]
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232 [D loss: 0.698240, acc.: 45.31%] [G loss: 0.748819]
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233 [D loss: 0.690475, acc.: 53.71%] [G loss: 0.741377]
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234 [D loss: 0.696913, acc.: 49.80%] [G loss: 0.736179]
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235 [D loss: 0.697641, acc.: 48.05%] [G loss: 0.748071]
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236 [D loss: 0.695472, acc.: 50.20%] [G loss: 0.744690]
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237 [D loss: 0.700023, acc.: 45.12%] [G loss: 0.741396]
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238 [D loss: 0.702140, acc.: 47.07%] [G loss: 0.730856]
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239 [D loss: 0.698375, acc.: 46.09%] [G loss: 0.729082]
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240 [D loss: 0.697246, acc.: 47.46%] [G loss: 0.731133]
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241 [D loss: 0.691421, acc.: 53.12%] [G loss: 0.726450]
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242 [D loss: 0.705248, acc.: 43.75%] [G loss: 0.725443]
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243 [D loss: 0.708166, acc.: 43.75%] [G loss: 0.730833]
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244 [D loss: 0.704738, acc.: 44.73%] [G loss: 0.733422]
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245 [D loss: 0.701332, acc.: 46.09%] [G loss: 0.728657]
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246 [D loss: 0.700622, acc.: 46.48%] [G loss: 0.725378]
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247 [D loss: 0.703283, acc.: 44.92%] [G loss: 0.719631]
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248 [D loss: 0.701106, acc.: 47.46%] [G loss: 0.718541]
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249 [D loss: 0.709969, acc.: 39.06%] [G loss: 0.725205]
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250 [D loss: 0.707333, acc.: 41.80%] [G loss: 0.722355]
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251 [D loss: 0.703065, acc.: 41.02%] [G loss: 0.718512]
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252 [D loss: 0.708412, acc.: 40.04%] [G loss: 0.717535]
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253 [D loss: 0.708919, acc.: 38.48%] [G loss: 0.711434]
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254 [D loss: 0.706941, acc.: 42.58%] [G loss: 0.712758]
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255 [D loss: 0.705458, acc.: 42.19%] [G loss: 0.713579]
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256 [D loss: 0.699636, acc.: 48.05%] [G loss: 0.713233]
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257 [D loss: 0.705653, acc.: 41.02%] [G loss: 0.719177]
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258 [D loss: 0.704283, acc.: 41.02%] [G loss: 0.714985]
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259 [D loss: 0.702510, acc.: 42.19%] [G loss: 0.714428]
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260 [D loss: 0.703731, acc.: 44.34%] [G loss: 0.717549]
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261 [D loss: 0.704270, acc.: 41.41%] [G loss: 0.719657]
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262 [D loss: 0.705628, acc.: 38.87%] [G loss: 0.718191]
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263 [D loss: 0.702659, acc.: 41.02%] [G loss: 0.717117]
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264 [D loss: 0.703775, acc.: 43.75%] [G loss: 0.720400]
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265 [D loss: 0.701835, acc.: 40.62%] [G loss: 0.713987]
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266 [D loss: 0.707926, acc.: 39.45%] [G loss: 0.717326]
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267 [D loss: 0.702760, acc.: 42.97%] [G loss: 0.720416]
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268 [D loss: 0.702067, acc.: 43.75%] [G loss: 0.718559]
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269 [D loss: 0.701133, acc.: 43.95%] [G loss: 0.724258]
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270 [D loss: 0.701028, acc.: 41.99%] [G loss: 0.720896]
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271 [D loss: 0.697237, acc.: 48.44%] [G loss: 0.719512]
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272 [D loss: 0.697240, acc.: 47.66%] [G loss: 0.727166]
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273 [D loss: 0.698315, acc.: 44.34%] [G loss: 0.725774]
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274 [D loss: 0.693589, acc.: 49.02%] [G loss: 0.725852]
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275 [D loss: 0.695281, acc.: 50.98%] [G loss: 0.721597]
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276 [D loss: 0.693741, acc.: 50.78%] [G loss: 0.727615]
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277 [D loss: 0.695386, acc.: 48.63%] [G loss: 0.728277]
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278 [D loss: 0.695514, acc.: 49.80%] [G loss: 0.731722]
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279 [D loss: 0.693051, acc.: 50.98%] [G loss: 0.725827]
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280 [D loss: 0.690074, acc.: 50.39%] [G loss: 0.730685]
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281 [D loss: 0.689073, acc.: 54.88%] [G loss: 0.726129]
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282 [D loss: 0.693026, acc.: 51.56%] [G loss: 0.728347]
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283 [D loss: 0.691607, acc.: 51.76%] [G loss: 0.727547]
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284 [D loss: 0.690961, acc.: 52.73%] [G loss: 0.731836]
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285 [D loss: 0.689392, acc.: 53.32%] [G loss: 0.726489]
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286 [D loss: 0.692683, acc.: 50.20%] [G loss: 0.723716]
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287 [D loss: 0.688642, acc.: 52.73%] [G loss: 0.729669]
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288 [D loss: 0.692643, acc.: 50.59%] [G loss: 0.726367]
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289 [D loss: 0.690776, acc.: 53.52%] [G loss: 0.728892]
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290 [D loss: 0.689529, acc.: 51.56%] [G loss: 0.722769]
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291 [D loss: 0.691382, acc.: 52.34%] [G loss: 0.728861]
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292 [D loss: 0.690184, acc.: 51.95%] [G loss: 0.730475]
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293 [D loss: 0.693394, acc.: 49.22%] [G loss: 0.729694]
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294 [D loss: 0.692416, acc.: 51.37%] [G loss: 0.725938]
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295 [D loss: 0.690933, acc.: 51.56%] [G loss: 0.720813]
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296 [D loss: 0.693844, acc.: 48.24%] [G loss: 0.724940]
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297 [D loss: 0.692979, acc.: 51.37%] [G loss: 0.727142]
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298 [D loss: 0.695381, acc.: 50.00%] [G loss: 0.728082]
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301 [D loss: 0.693544, acc.: 50.59%] [G loss: 0.731725]
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303 [D loss: 0.691640, acc.: 51.37%] [G loss: 0.726411]
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304 [D loss: 0.699671, acc.: 44.73%] [G loss: 0.728884]
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305 [D loss: 0.690271, acc.: 52.54%] [G loss: 0.728160]
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306 [D loss: 0.698095, acc.: 47.27%] [G loss: 0.729996]
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307 [D loss: 0.697180, acc.: 48.05%] [G loss: 0.727140]
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309 [D loss: 0.700003, acc.: 45.12%] [G loss: 0.728253]
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310 [D loss: 0.698130, acc.: 47.27%] [G loss: 0.731657]
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311 [D loss: 0.699014, acc.: 45.70%] [G loss: 0.731562]
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312 [D loss: 0.696960, acc.: 46.29%] [G loss: 0.728089]
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313 [D loss: 0.695569, acc.: 50.20%] [G loss: 0.730590]
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314 [D loss: 0.701646, acc.: 44.34%] [G loss: 0.730824]
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315 [D loss: 0.699027, acc.: 45.12%] [G loss: 0.729855]
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316 [D loss: 0.699592, acc.: 43.95%] [G loss: 0.726349]
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317 [D loss: 0.697761, acc.: 45.12%] [G loss: 0.728646]
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318 [D loss: 0.699942, acc.: 46.68%] [G loss: 0.730041]
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319 [D loss: 0.697659, acc.: 45.90%] [G loss: 0.732629]
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320 [D loss: 0.702273, acc.: 42.38%] [G loss: 0.731960]
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321 [D loss: 0.697735, acc.: 47.85%] [G loss: 0.729358]
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322 [D loss: 0.700484, acc.: 45.31%] [G loss: 0.733830]
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323 [D loss: 0.702617, acc.: 42.97%] [G loss: 0.734702]
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324 [D loss: 0.703997, acc.: 42.97%] [G loss: 0.732319]
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325 [D loss: 0.701198, acc.: 46.48%] [G loss: 0.733663]
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326 [D loss: 0.699493, acc.: 42.97%] [G loss: 0.732868]
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327 [D loss: 0.702468, acc.: 43.16%] [G loss: 0.736007]
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328 [D loss: 0.698081, acc.: 45.90%] [G loss: 0.736806]
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329 [D loss: 0.698992, acc.: 48.24%] [G loss: 0.734812]
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330 [D loss: 0.699873, acc.: 44.92%] [G loss: 0.730652]
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331 [D loss: 0.696755, acc.: 48.44%] [G loss: 0.734812]
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332 [D loss: 0.697832, acc.: 45.90%] [G loss: 0.734825]
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333 [D loss: 0.698994, acc.: 45.31%] [G loss: 0.735005]
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334 [D loss: 0.699846, acc.: 44.53%] [G loss: 0.729505]
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335 [D loss: 0.698903, acc.: 46.09%] [G loss: 0.733645]
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336 [D loss: 0.698528, acc.: 44.92%] [G loss: 0.732914]
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337 [D loss: 0.698992, acc.: 46.88%] [G loss: 0.731395]
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338 [D loss: 0.698043, acc.: 45.31%] [G loss: 0.729827]
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339 [D loss: 0.698383, acc.: 46.29%] [G loss: 0.731368]
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340 [D loss: 0.697552, acc.: 48.83%] [G loss: 0.731167]
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341 [D loss: 0.696578, acc.: 49.02%] [G loss: 0.734362]
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342 [D loss: 0.696908, acc.: 46.48%] [G loss: 0.729888]
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343 [D loss: 0.697718, acc.: 48.24%] [G loss: 0.730222]
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344 [D loss: 0.699032, acc.: 46.09%] [G loss: 0.729085]
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345 [D loss: 0.696842, acc.: 48.05%] [G loss: 0.727573]
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346 [D loss: 0.697594, acc.: 47.46%] [G loss: 0.729165]
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347 [D loss: 0.695136, acc.: 51.95%] [G loss: 0.729774]
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348 [D loss: 0.698956, acc.: 45.31%] [G loss: 0.726747]
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349 [D loss: 0.697083, acc.: 47.66%] [G loss: 0.728953]
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350 [D loss: 0.697109, acc.: 48.24%] [G loss: 0.726955]
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351 [D loss: 0.699146, acc.: 45.70%] [G loss: 0.726413]
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352 [D loss: 0.694059, acc.: 50.78%] [G loss: 0.725935]
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353 [D loss: 0.696917, acc.: 47.66%] [G loss: 0.728646]
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354 [D loss: 0.697937, acc.: 47.07%] [G loss: 0.723278]
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355 [D loss: 0.695574, acc.: 51.37%] [G loss: 0.725810]
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356 [D loss: 0.694166, acc.: 50.00%] [G loss: 0.725038]
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357 [D loss: 0.691731, acc.: 52.15%] [G loss: 0.723418]
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358 [D loss: 0.697167, acc.: 45.51%] [G loss: 0.725111]
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359 [D loss: 0.694781, acc.: 51.37%] [G loss: 0.721816]
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360 [D loss: 0.695538, acc.: 45.12%] [G loss: 0.721285]
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361 [D loss: 0.696545, acc.: 46.09%] [G loss: 0.722962]
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362 [D loss: 0.694213, acc.: 49.22%] [G loss: 0.724363]
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363 [D loss: 0.696861, acc.: 49.22%] [G loss: 0.720828]
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364 [D loss: 0.695924, acc.: 47.46%] [G loss: 0.721452]
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365 [D loss: 0.696066, acc.: 46.48%] [G loss: 0.722541]
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366 [D loss: 0.694531, acc.: 50.59%] [G loss: 0.723493]
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367 [D loss: 0.694824, acc.: 49.41%] [G loss: 0.722970]
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368 [D loss: 0.691475, acc.: 53.52%] [G loss: 0.721605]
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369 [D loss: 0.694743, acc.: 50.00%] [G loss: 0.725000]
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370 [D loss: 0.694689, acc.: 49.41%] [G loss: 0.721584]
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371 [D loss: 0.695416, acc.: 47.07%] [G loss: 0.719221]
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372 [D loss: 0.694641, acc.: 50.20%] [G loss: 0.722763]
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373 [D loss: 0.695610, acc.: 48.63%] [G loss: 0.720938]
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374 [D loss: 0.693414, acc.: 49.80%] [G loss: 0.718381]
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375 [D loss: 0.694221, acc.: 48.83%] [G loss: 0.720921]
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376 [D loss: 0.696298, acc.: 46.68%] [G loss: 0.720869]
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377 [D loss: 0.697164, acc.: 47.07%] [G loss: 0.722962]
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378 [D loss: 0.691079, acc.: 52.34%] [G loss: 0.717845]
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379 [D loss: 0.693553, acc.: 50.78%] [G loss: 0.718071]
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380 [D loss: 0.692792, acc.: 48.63%] [G loss: 0.718117]
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381 [D loss: 0.695736, acc.: 47.46%] [G loss: 0.720413]
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382 [D loss: 0.693331, acc.: 50.20%] [G loss: 0.719833]
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383 [D loss: 0.693045, acc.: 52.15%] [G loss: 0.720804]
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384 [D loss: 0.694218, acc.: 49.02%] [G loss: 0.718408]
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385 [D loss: 0.694377, acc.: 48.05%] [G loss: 0.718428]
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386 [D loss: 0.694183, acc.: 46.29%] [G loss: 0.717081]
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387 [D loss: 0.695523, acc.: 48.24%] [G loss: 0.716979]
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388 [D loss: 0.694368, acc.: 50.20%] [G loss: 0.721055]
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389 [D loss: 0.695084, acc.: 49.02%] [G loss: 0.720116]
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390 [D loss: 0.694895, acc.: 49.22%] [G loss: 0.722276]
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391 [D loss: 0.695356, acc.: 47.46%] [G loss: 0.719544]
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392 [D loss: 0.697459, acc.: 45.12%] [G loss: 0.718134]
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393 [D loss: 0.697591, acc.: 44.14%] [G loss: 0.718795]
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394 [D loss: 0.694900, acc.: 48.44%] [G loss: 0.719062]
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395 [D loss: 0.694024, acc.: 48.44%] [G loss: 0.720816]
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396 [D loss: 0.696606, acc.: 47.46%] [G loss: 0.717773]
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397 [D loss: 0.693145, acc.: 51.17%] [G loss: 0.721776]
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398 [D loss: 0.696422, acc.: 47.66%] [G loss: 0.722404]
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399 [D loss: 0.694353, acc.: 50.20%] [G loss: 0.718041]
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400 [D loss: 0.694262, acc.: 46.88%] [G loss: 0.719581]
1/1 [==============================] - 0s 15ms/step
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401 [D loss: 0.696855, acc.: 45.12%] [G loss: 0.721286]
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402 [D loss: 0.693491, acc.: 49.61%] [G loss: 0.721074]
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403 [D loss: 0.696783, acc.: 46.48%] [G loss: 0.721663]
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404 [D loss: 0.694960, acc.: 48.44%] [G loss: 0.725601]
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405 [D loss: 0.698091, acc.: 45.51%] [G loss: 0.720244]
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406 [D loss: 0.692641, acc.: 51.37%] [G loss: 0.721176]
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407 [D loss: 0.695768, acc.: 47.66%] [G loss: 0.720484]
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408 [D loss: 0.693946, acc.: 50.00%] [G loss: 0.721327]
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409 [D loss: 0.693699, acc.: 50.00%] [G loss: 0.722737]
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410 [D loss: 0.694221, acc.: 49.22%] [G loss: 0.719173]
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411 [D loss: 0.693053, acc.: 48.63%] [G loss: 0.723016]
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412 [D loss: 0.694052, acc.: 47.07%] [G loss: 0.719782]
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413 [D loss: 0.695987, acc.: 48.63%] [G loss: 0.721550]
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414 [D loss: 0.693571, acc.: 50.98%] [G loss: 0.724013]
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415 [D loss: 0.695285, acc.: 47.66%] [G loss: 0.720983]
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416 [D loss: 0.693211, acc.: 49.41%] [G loss: 0.722250]
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417 [D loss: 0.692941, acc.: 50.59%] [G loss: 0.723268]
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418 [D loss: 0.691965, acc.: 51.76%] [G loss: 0.724089]
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419 [D loss: 0.693520, acc.: 49.80%] [G loss: 0.718989]
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420 [D loss: 0.694778, acc.: 47.27%] [G loss: 0.717770]
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421 [D loss: 0.690617, acc.: 53.12%] [G loss: 0.717059]
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422 [D loss: 0.694020, acc.: 49.02%] [G loss: 0.721378]
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423 [D loss: 0.690284, acc.: 52.93%] [G loss: 0.722341]
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424 [D loss: 0.693009, acc.: 53.12%] [G loss: 0.722265]
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425 [D loss: 0.692499, acc.: 50.00%] [G loss: 0.723850]
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426 [D loss: 0.692763, acc.: 49.61%] [G loss: 0.723594]
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427 [D loss: 0.690102, acc.: 51.37%] [G loss: 0.720669]
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428 [D loss: 0.688952, acc.: 54.10%] [G loss: 0.720380]
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429 [D loss: 0.692207, acc.: 49.22%] [G loss: 0.717530]
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430 [D loss: 0.692536, acc.: 49.61%] [G loss: 0.720076]
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431 [D loss: 0.695302, acc.: 46.68%] [G loss: 0.718116]
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432 [D loss: 0.692766, acc.: 51.76%] [G loss: 0.719296]
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433 [D loss: 0.693436, acc.: 49.22%] [G loss: 0.719286]
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434 [D loss: 0.692972, acc.: 50.98%] [G loss: 0.718238]
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435 [D loss: 0.693281, acc.: 49.22%] [G loss: 0.716693]
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436 [D loss: 0.691347, acc.: 50.78%] [G loss: 0.719480]
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437 [D loss: 0.694028, acc.: 49.22%] [G loss: 0.719551]
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438 [D loss: 0.695007, acc.: 43.55%] [G loss: 0.718693]
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439 [D loss: 0.691922, acc.: 50.20%] [G loss: 0.720447]
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440 [D loss: 0.694106, acc.: 47.46%] [G loss: 0.719626]
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441 [D loss: 0.695505, acc.: 47.07%] [G loss: 0.715983]
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442 [D loss: 0.692521, acc.: 52.34%] [G loss: 0.717876]
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443 [D loss: 0.695021, acc.: 49.22%] [G loss: 0.717145]
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444 [D loss: 0.691699, acc.: 51.17%] [G loss: 0.721191]
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445 [D loss: 0.692423, acc.: 49.41%] [G loss: 0.720335]
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446 [D loss: 0.692493, acc.: 49.61%] [G loss: 0.717878]
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447 [D loss: 0.695707, acc.: 46.88%] [G loss: 0.716050]
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448 [D loss: 0.695581, acc.: 47.85%] [G loss: 0.718793]
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449 [D loss: 0.693127, acc.: 48.24%] [G loss: 0.719870]
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450 [D loss: 0.696751, acc.: 45.70%] [G loss: 0.721474]
1/1 [==============================] - 0s 15ms/step
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451 [D loss: 0.694438, acc.: 49.41%] [G loss: 0.720090]
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452 [D loss: 0.694764, acc.: 47.85%] [G loss: 0.721262]
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453 [D loss: 0.692938, acc.: 51.76%] [G loss: 0.721873]
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454 [D loss: 0.694665, acc.: 47.46%] [G loss: 0.716289]
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455 [D loss: 0.692471, acc.: 50.20%] [G loss: 0.722430]
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456 [D loss: 0.695915, acc.: 47.46%] [G loss: 0.715834]
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457 [D loss: 0.693134, acc.: 48.05%] [G loss: 0.727599]
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458 [D loss: 0.694545, acc.: 47.27%] [G loss: 0.722562]
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459 [D loss: 0.694823, acc.: 48.44%] [G loss: 0.723081]
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460 [D loss: 0.697937, acc.: 43.55%] [G loss: 0.722336]
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461 [D loss: 0.695279, acc.: 45.51%] [G loss: 0.724089]
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462 [D loss: 0.694414, acc.: 49.02%] [G loss: 0.728573]
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463 [D loss: 0.693583, acc.: 46.68%] [G loss: 0.725648]
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464 [D loss: 0.691280, acc.: 52.34%] [G loss: 0.725652]
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465 [D loss: 0.694889, acc.: 46.68%] [G loss: 0.725443]
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466 [D loss: 0.689676, acc.: 52.15%] [G loss: 0.726946]
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467 [D loss: 0.695272, acc.: 47.85%] [G loss: 0.730224]
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468 [D loss: 0.692780, acc.: 48.63%] [G loss: 0.725772]
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469 [D loss: 0.694680, acc.: 49.02%] [G loss: 0.728628]
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470 [D loss: 0.689736, acc.: 52.15%] [G loss: 0.728545]
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471 [D loss: 0.692486, acc.: 50.78%] [G loss: 0.726903]
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472 [D loss: 0.692834, acc.: 50.78%] [G loss: 0.723676]
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473 [D loss: 0.693707, acc.: 45.51%] [G loss: 0.725182]
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474 [D loss: 0.691684, acc.: 51.17%] [G loss: 0.725167]
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475 [D loss: 0.695402, acc.: 47.66%] [G loss: 0.729611]
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476 [D loss: 0.691899, acc.: 49.02%] [G loss: 0.726811]
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477 [D loss: 0.693398, acc.: 51.76%] [G loss: 0.729302]
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478 [D loss: 0.693933, acc.: 48.83%] [G loss: 0.724106]
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479 [D loss: 0.694413, acc.: 49.41%] [G loss: 0.727677]
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480 [D loss: 0.692602, acc.: 47.85%] [G loss: 0.730659]
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481 [D loss: 0.696361, acc.: 45.70%] [G loss: 0.727156]
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482 [D loss: 0.692146, acc.: 50.98%] [G loss: 0.726476]
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483 [D loss: 0.693601, acc.: 47.07%] [G loss: 0.730384]
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484 [D loss: 0.693612, acc.: 47.27%] [G loss: 0.727231]
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485 [D loss: 0.695274, acc.: 48.63%] [G loss: 0.730092]
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486 [D loss: 0.695964, acc.: 49.61%] [G loss: 0.723356]
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487 [D loss: 0.695872, acc.: 45.90%] [G loss: 0.725467]
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488 [D loss: 0.696087, acc.: 49.22%] [G loss: 0.723065]
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489 [D loss: 0.694436, acc.: 50.20%] [G loss: 0.723262]
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490 [D loss: 0.692007, acc.: 52.54%] [G loss: 0.723854]
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491 [D loss: 0.695459, acc.: 47.85%] [G loss: 0.723830]
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492 [D loss: 0.695551, acc.: 48.83%] [G loss: 0.723697]
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493 [D loss: 0.697713, acc.: 47.46%] [G loss: 0.723301]
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494 [D loss: 0.696862, acc.: 47.27%] [G loss: 0.726665]
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495 [D loss: 0.695429, acc.: 47.27%] [G loss: 0.726134]
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496 [D loss: 0.693466, acc.: 51.95%] [G loss: 0.721891]
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497 [D loss: 0.694947, acc.: 48.83%] [G loss: 0.721396]
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498 [D loss: 0.697345, acc.: 44.34%] [G loss: 0.720800]
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499 [D loss: 0.694828, acc.: 47.66%] [G loss: 0.718950]
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500 [D loss: 0.694801, acc.: 49.02%] [G loss: 0.721650]
1/1 [==============================] - 0s 14ms/step
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501 [D loss: 0.696542, acc.: 46.68%] [G loss: 0.721956]
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502 [D loss: 0.694708, acc.: 50.39%] [G loss: 0.719500]
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503 [D loss: 0.696378, acc.: 48.24%] [G loss: 0.720010]
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504 [D loss: 0.698232, acc.: 44.73%] [G loss: 0.721270]
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505 [D loss: 0.694951, acc.: 47.85%] [G loss: 0.723872]
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506 [D loss: 0.694131, acc.: 50.78%] [G loss: 0.724235]
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507 [D loss: 0.693067, acc.: 50.00%] [G loss: 0.723123]
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508 [D loss: 0.692734, acc.: 50.59%] [G loss: 0.720459]
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509 [D loss: 0.690418, acc.: 49.61%] [G loss: 0.723504]
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510 [D loss: 0.691828, acc.: 55.27%] [G loss: 0.722492]
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511 [D loss: 0.694866, acc.: 47.07%] [G loss: 0.725316]
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512 [D loss: 0.691002, acc.: 51.76%] [G loss: 0.725876]
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513 [D loss: 0.690581, acc.: 54.30%] [G loss: 0.728697]
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514 [D loss: 0.691537, acc.: 52.93%] [G loss: 0.726947]
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515 [D loss: 0.693183, acc.: 49.61%] [G loss: 0.724450]
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516 [D loss: 0.692006, acc.: 52.15%] [G loss: 0.725797]
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517 [D loss: 0.689179, acc.: 53.52%] [G loss: 0.727038]
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518 [D loss: 0.688990, acc.: 54.49%] [G loss: 0.725070]
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519 [D loss: 0.689281, acc.: 53.71%] [G loss: 0.725622]
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520 [D loss: 0.690467, acc.: 51.95%] [G loss: 0.726394]
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521 [D loss: 0.689176, acc.: 52.54%] [G loss: 0.724893]
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522 [D loss: 0.689358, acc.: 51.17%] [G loss: 0.719733]
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523 [D loss: 0.689867, acc.: 52.93%] [G loss: 0.722735]
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524 [D loss: 0.688395, acc.: 54.30%] [G loss: 0.719465]
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525 [D loss: 0.687023, acc.: 54.88%] [G loss: 0.719772]
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526 [D loss: 0.686690, acc.: 54.69%] [G loss: 0.725069]
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527 [D loss: 0.686086, acc.: 54.30%] [G loss: 0.720172]
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528 [D loss: 0.687362, acc.: 56.25%] [G loss: 0.724438]
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529 [D loss: 0.693539, acc.: 52.15%] [G loss: 0.722926]
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530 [D loss: 0.691395, acc.: 49.22%] [G loss: 0.717007]
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531 [D loss: 0.690280, acc.: 53.71%] [G loss: 0.725003]
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532 [D loss: 0.689968, acc.: 52.34%] [G loss: 0.722852]
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533 [D loss: 0.687998, acc.: 53.71%] [G loss: 0.724840]
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534 [D loss: 0.692170, acc.: 52.73%] [G loss: 0.723545]
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535 [D loss: 0.694304, acc.: 48.83%] [G loss: 0.722791]
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536 [D loss: 0.692686, acc.: 50.39%] [G loss: 0.727277]
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537 [D loss: 0.692471, acc.: 51.37%] [G loss: 0.725772]
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538 [D loss: 0.693207, acc.: 49.02%] [G loss: 0.722784]
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539 [D loss: 0.693952, acc.: 49.61%] [G loss: 0.731277]
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540 [D loss: 0.695106, acc.: 50.20%] [G loss: 0.726017]
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541 [D loss: 0.693808, acc.: 47.66%] [G loss: 0.732381]
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542 [D loss: 0.694433, acc.: 49.61%] [G loss: 0.723654]
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543 [D loss: 0.694057, acc.: 49.41%] [G loss: 0.723519]
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544 [D loss: 0.693277, acc.: 50.59%] [G loss: 0.724248]
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545 [D loss: 0.693647, acc.: 47.66%] [G loss: 0.719690]
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546 [D loss: 0.694616, acc.: 49.02%] [G loss: 0.721815]
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547 [D loss: 0.694805, acc.: 48.63%] [G loss: 0.722663]
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548 [D loss: 0.693198, acc.: 52.34%] [G loss: 0.727476]
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549 [D loss: 0.692586, acc.: 50.20%] [G loss: 0.724632]
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550 [D loss: 0.693903, acc.: 51.17%] [G loss: 0.725196]
1/1 [==============================] - 0s 15ms/step
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551 [D loss: 0.693576, acc.: 50.59%] [G loss: 0.723938]
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552 [D loss: 0.694632, acc.: 48.05%] [G loss: 0.729774]
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553 [D loss: 0.692726, acc.: 52.73%] [G loss: 0.723483]
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554 [D loss: 0.697118, acc.: 45.51%] [G loss: 0.719227]
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555 [D loss: 0.693792, acc.: 51.76%] [G loss: 0.722669]
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556 [D loss: 0.694059, acc.: 50.39%] [G loss: 0.724513]
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557 [D loss: 0.695709, acc.: 47.85%] [G loss: 0.720902]
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558 [D loss: 0.696429, acc.: 45.51%] [G loss: 0.720264]
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559 [D loss: 0.694715, acc.: 50.39%] [G loss: 0.722825]
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560 [D loss: 0.695815, acc.: 48.24%] [G loss: 0.719351]
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561 [D loss: 0.697722, acc.: 44.34%] [G loss: 0.720071]
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562 [D loss: 0.696811, acc.: 49.22%] [G loss: 0.720134]
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563 [D loss: 0.696420, acc.: 48.83%] [G loss: 0.721475]
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564 [D loss: 0.699498, acc.: 43.16%] [G loss: 0.719879]
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565 [D loss: 0.697141, acc.: 43.95%] [G loss: 0.720792]
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566 [D loss: 0.695532, acc.: 47.07%] [G loss: 0.717876]
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567 [D loss: 0.694043, acc.: 50.78%] [G loss: 0.724217]
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568 [D loss: 0.694346, acc.: 49.61%] [G loss: 0.720677]
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569 [D loss: 0.695324, acc.: 46.48%] [G loss: 0.721236]
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570 [D loss: 0.693314, acc.: 50.78%] [G loss: 0.720915]
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571 [D loss: 0.694680, acc.: 45.12%] [G loss: 0.718641]
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572 [D loss: 0.695231, acc.: 47.66%] [G loss: 0.721862]
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573 [D loss: 0.693009, acc.: 48.44%] [G loss: 0.721693]
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574 [D loss: 0.697542, acc.: 45.12%] [G loss: 0.720490]
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575 [D loss: 0.693166, acc.: 49.41%] [G loss: 0.718823]
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576 [D loss: 0.693237, acc.: 47.85%] [G loss: 0.721128]
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577 [D loss: 0.694849, acc.: 49.22%] [G loss: 0.720454]
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578 [D loss: 0.693799, acc.: 48.05%] [G loss: 0.717770]
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579 [D loss: 0.693312, acc.: 47.46%] [G loss: 0.719494]
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580 [D loss: 0.694033, acc.: 48.05%] [G loss: 0.723350]
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581 [D loss: 0.694008, acc.: 46.48%] [G loss: 0.717562]
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582 [D loss: 0.693723, acc.: 47.85%] [G loss: 0.720526]
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583 [D loss: 0.692995, acc.: 49.61%] [G loss: 0.720639]
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584 [D loss: 0.694317, acc.: 47.07%] [G loss: 0.722021]
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585 [D loss: 0.692336, acc.: 51.56%] [G loss: 0.724049]
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586 [D loss: 0.691828, acc.: 51.95%] [G loss: 0.720025]
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587 [D loss: 0.692488, acc.: 50.39%] [G loss: 0.722152]
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588 [D loss: 0.690568, acc.: 51.37%] [G loss: 0.722594]
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589 [D loss: 0.688675, acc.: 54.49%] [G loss: 0.718249]
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590 [D loss: 0.691076, acc.: 52.54%] [G loss: 0.719143]
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591 [D loss: 0.690961, acc.: 54.10%] [G loss: 0.722203]
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592 [D loss: 0.693544, acc.: 48.05%] [G loss: 0.722220]
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593 [D loss: 0.689936, acc.: 54.49%] [G loss: 0.723275]
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594 [D loss: 0.689813, acc.: 52.34%] [G loss: 0.720685]
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595 [D loss: 0.689566, acc.: 55.08%] [G loss: 0.721090]
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596 [D loss: 0.689193, acc.: 55.66%] [G loss: 0.718828]
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597 [D loss: 0.691140, acc.: 50.20%] [G loss: 0.724066]
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598 [D loss: 0.688986, acc.: 56.05%] [G loss: 0.719626]
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599 [D loss: 0.691064, acc.: 52.15%] [G loss: 0.721447]
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600 [D loss: 0.689082, acc.: 53.71%] [G loss: 0.724041]
1/1 [==============================] - 0s 17ms/step
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601 [D loss: 0.690069, acc.: 51.37%] [G loss: 0.719334]
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602 [D loss: 0.689637, acc.: 52.93%] [G loss: 0.722778]
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603 [D loss: 0.691438, acc.: 50.20%] [G loss: 0.721749]
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604 [D loss: 0.689402, acc.: 55.27%] [G loss: 0.718625]
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605 [D loss: 0.690457, acc.: 53.12%] [G loss: 0.717095]
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606 [D loss: 0.691278, acc.: 52.34%] [G loss: 0.719672]
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607 [D loss: 0.690582, acc.: 53.12%] [G loss: 0.721172]
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608 [D loss: 0.689497, acc.: 54.69%] [G loss: 0.722430]
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609 [D loss: 0.692529, acc.: 51.56%] [G loss: 0.719757]
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610 [D loss: 0.692542, acc.: 48.44%] [G loss: 0.722748]
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611 [D loss: 0.691574, acc.: 50.98%] [G loss: 0.719712]
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612 [D loss: 0.691025, acc.: 52.34%] [G loss: 0.719897]
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613 [D loss: 0.693169, acc.: 50.39%] [G loss: 0.722792]
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614 [D loss: 0.690180, acc.: 54.49%] [G loss: 0.719857]
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615 [D loss: 0.694729, acc.: 49.41%] [G loss: 0.719858]
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616 [D loss: 0.693595, acc.: 47.07%] [G loss: 0.726167]
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617 [D loss: 0.692454, acc.: 51.95%] [G loss: 0.723672]
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618 [D loss: 0.692151, acc.: 50.00%] [G loss: 0.725816]
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619 [D loss: 0.691220, acc.: 51.37%] [G loss: 0.720919]
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620 [D loss: 0.693010, acc.: 49.61%] [G loss: 0.726776]
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621 [D loss: 0.693309, acc.: 50.00%] [G loss: 0.722066]
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622 [D loss: 0.693098, acc.: 48.83%] [G loss: 0.724715]
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623 [D loss: 0.693400, acc.: 49.61%] [G loss: 0.723171]
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624 [D loss: 0.692515, acc.: 49.61%] [G loss: 0.717914]
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625 [D loss: 0.693572, acc.: 49.02%] [G loss: 0.722326]
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626 [D loss: 0.693842, acc.: 49.41%] [G loss: 0.720166]
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627 [D loss: 0.694060, acc.: 48.63%] [G loss: 0.722470]
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628 [D loss: 0.693540, acc.: 50.78%] [G loss: 0.720075]
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629 [D loss: 0.694027, acc.: 48.24%] [G loss: 0.720713]
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630 [D loss: 0.693356, acc.: 49.02%] [G loss: 0.717501]
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631 [D loss: 0.693025, acc.: 49.41%] [G loss: 0.721159]
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632 [D loss: 0.695956, acc.: 47.66%] [G loss: 0.716322]
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633 [D loss: 0.691348, acc.: 51.76%] [G loss: 0.717044]
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634 [D loss: 0.690639, acc.: 50.78%] [G loss: 0.721877]
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635 [D loss: 0.690375, acc.: 52.54%] [G loss: 0.720945]
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636 [D loss: 0.695219, acc.: 46.68%] [G loss: 0.726525]
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637 [D loss: 0.690130, acc.: 53.71%] [G loss: 0.724012]
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638 [D loss: 0.690891, acc.: 51.37%] [G loss: 0.724409]
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639 [D loss: 0.691178, acc.: 52.34%] [G loss: 0.723499]
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640 [D loss: 0.690693, acc.: 52.93%] [G loss: 0.722185]
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641 [D loss: 0.689388, acc.: 57.42%] [G loss: 0.725730]
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642 [D loss: 0.692941, acc.: 50.20%] [G loss: 0.727382]
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643 [D loss: 0.691598, acc.: 52.73%] [G loss: 0.726186]
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644 [D loss: 0.690522, acc.: 51.56%] [G loss: 0.726350]
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645 [D loss: 0.690311, acc.: 50.39%] [G loss: 0.722151]
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646 [D loss: 0.690842, acc.: 52.34%] [G loss: 0.726954]
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647 [D loss: 0.692735, acc.: 51.37%] [G loss: 0.726290]
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648 [D loss: 0.690156, acc.: 53.12%] [G loss: 0.722756]
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649 [D loss: 0.692569, acc.: 48.63%] [G loss: 0.720911]
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650 [D loss: 0.690110, acc.: 54.69%] [G loss: 0.725280]
1/1 [==============================] - 0s 16ms/step
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651 [D loss: 0.690731, acc.: 50.98%] [G loss: 0.725952]
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652 [D loss: 0.689552, acc.: 51.37%] [G loss: 0.725780]
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653 [D loss: 0.691554, acc.: 50.20%] [G loss: 0.723315]
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654 [D loss: 0.690649, acc.: 52.73%] [G loss: 0.727696]
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655 [D loss: 0.688434, acc.: 52.15%] [G loss: 0.722659]
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656 [D loss: 0.690536, acc.: 52.34%] [G loss: 0.721887]
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657 [D loss: 0.688565, acc.: 53.12%] [G loss: 0.721044]
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658 [D loss: 0.690872, acc.: 51.76%] [G loss: 0.724637]
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659 [D loss: 0.686540, acc.: 58.79%] [G loss: 0.719102]
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660 [D loss: 0.688979, acc.: 55.47%] [G loss: 0.719913]
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661 [D loss: 0.693404, acc.: 51.17%] [G loss: 0.724045]
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662 [D loss: 0.691246, acc.: 51.17%] [G loss: 0.720658]
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663 [D loss: 0.690858, acc.: 51.17%] [G loss: 0.722169]
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664 [D loss: 0.690710, acc.: 50.00%] [G loss: 0.715672]
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665 [D loss: 0.689675, acc.: 54.88%] [G loss: 0.718809]
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666 [D loss: 0.691045, acc.: 50.98%] [G loss: 0.718275]
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667 [D loss: 0.692078, acc.: 51.76%] [G loss: 0.721485]
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668 [D loss: 0.691652, acc.: 49.80%] [G loss: 0.719361]
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669 [D loss: 0.689995, acc.: 51.76%] [G loss: 0.720123]
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670 [D loss: 0.691545, acc.: 50.39%] [G loss: 0.725697]
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671 [D loss: 0.688693, acc.: 55.66%] [G loss: 0.716565]
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672 [D loss: 0.689807, acc.: 52.15%] [G loss: 0.725084]
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673 [D loss: 0.688894, acc.: 54.30%] [G loss: 0.722444]
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674 [D loss: 0.691712, acc.: 50.78%] [G loss: 0.725016]
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675 [D loss: 0.690859, acc.: 53.12%] [G loss: 0.725778]
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676 [D loss: 0.693004, acc.: 49.02%] [G loss: 0.719259]
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677 [D loss: 0.687912, acc.: 55.86%] [G loss: 0.722351]
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678 [D loss: 0.689980, acc.: 53.32%] [G loss: 0.730080]
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679 [D loss: 0.690312, acc.: 53.12%] [G loss: 0.720179]
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680 [D loss: 0.691352, acc.: 49.41%] [G loss: 0.720935]
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681 [D loss: 0.689995, acc.: 53.32%] [G loss: 0.720738]
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682 [D loss: 0.686295, acc.: 55.08%] [G loss: 0.726259]
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683 [D loss: 0.690817, acc.: 50.98%] [G loss: 0.728374]
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684 [D loss: 0.689612, acc.: 53.91%] [G loss: 0.724592]
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685 [D loss: 0.689719, acc.: 54.10%] [G loss: 0.724679]
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686 [D loss: 0.688125, acc.: 54.88%] [G loss: 0.724960]
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687 [D loss: 0.690922, acc.: 52.34%] [G loss: 0.725407]
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688 [D loss: 0.686430, acc.: 57.81%] [G loss: 0.724190]
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689 [D loss: 0.691844, acc.: 52.54%] [G loss: 0.724842]
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690 [D loss: 0.691373, acc.: 51.37%] [G loss: 0.722886]
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691 [D loss: 0.693524, acc.: 51.37%] [G loss: 0.729047]
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692 [D loss: 0.688759, acc.: 52.93%] [G loss: 0.723459]
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693 [D loss: 0.691205, acc.: 52.73%] [G loss: 0.722348]
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694 [D loss: 0.693837, acc.: 51.56%] [G loss: 0.728591]
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695 [D loss: 0.688305, acc.: 54.88%] [G loss: 0.726855]
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696 [D loss: 0.692472, acc.: 50.20%] [G loss: 0.724853]
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697 [D loss: 0.690334, acc.: 51.95%] [G loss: 0.728395]
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698 [D loss: 0.694204, acc.: 47.46%] [G loss: 0.725144]
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699 [D loss: 0.690968, acc.: 52.15%] [G loss: 0.726470]
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700 [D loss: 0.692028, acc.: 51.37%] [G loss: 0.727943]
1/1 [==============================] - 0s 15ms/step
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701 [D loss: 0.694936, acc.: 48.44%] [G loss: 0.730383]
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702 [D loss: 0.696818, acc.: 47.85%] [G loss: 0.728057]
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703 [D loss: 0.693912, acc.: 51.17%] [G loss: 0.728103]
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704 [D loss: 0.695013, acc.: 48.83%] [G loss: 0.723661]
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705 [D loss: 0.695635, acc.: 47.27%] [G loss: 0.728340]
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706 [D loss: 0.691934, acc.: 51.56%] [G loss: 0.729646]
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707 [D loss: 0.693727, acc.: 48.83%] [G loss: 0.720548]
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708 [D loss: 0.695387, acc.: 48.05%] [G loss: 0.722793]
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709 [D loss: 0.697025, acc.: 46.48%] [G loss: 0.729251]
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710 [D loss: 0.692888, acc.: 53.52%] [G loss: 0.727343]
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711 [D loss: 0.693228, acc.: 50.59%] [G loss: 0.726068]
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712 [D loss: 0.691309, acc.: 53.52%] [G loss: 0.728626]
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713 [D loss: 0.694309, acc.: 49.02%] [G loss: 0.726225]
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714 [D loss: 0.695819, acc.: 48.44%] [G loss: 0.730174]
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715 [D loss: 0.693984, acc.: 48.24%] [G loss: 0.729058]
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716 [D loss: 0.692148, acc.: 52.15%] [G loss: 0.729688]
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717 [D loss: 0.695010, acc.: 50.20%] [G loss: 0.728627]
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718 [D loss: 0.694207, acc.: 49.41%] [G loss: 0.731683]
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719 [D loss: 0.690915, acc.: 51.17%] [G loss: 0.729811]
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720 [D loss: 0.694458, acc.: 48.05%] [G loss: 0.730461]
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721 [D loss: 0.692689, acc.: 48.05%] [G loss: 0.728166]
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722 [D loss: 0.692450, acc.: 51.17%] [G loss: 0.733609]
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723 [D loss: 0.691854, acc.: 50.39%] [G loss: 0.735115]
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724 [D loss: 0.692465, acc.: 50.39%] [G loss: 0.737281]
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725 [D loss: 0.689263, acc.: 55.27%] [G loss: 0.733272]
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726 [D loss: 0.691848, acc.: 53.52%] [G loss: 0.735115]
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727 [D loss: 0.690816, acc.: 53.12%] [G loss: 0.733571]
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728 [D loss: 0.691164, acc.: 51.76%] [G loss: 0.740294]
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729 [D loss: 0.691412, acc.: 52.54%] [G loss: 0.739016]
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730 [D loss: 0.686674, acc.: 56.05%] [G loss: 0.742187]
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731 [D loss: 0.689919, acc.: 55.66%] [G loss: 0.739224]
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732 [D loss: 0.689500, acc.: 55.86%] [G loss: 0.738739]
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733 [D loss: 0.688029, acc.: 56.25%] [G loss: 0.736614]
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734 [D loss: 0.686026, acc.: 55.86%] [G loss: 0.741966]
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735 [D loss: 0.689823, acc.: 52.93%] [G loss: 0.739814]
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736 [D loss: 0.687103, acc.: 54.88%] [G loss: 0.744736]
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737 [D loss: 0.684885, acc.: 57.03%] [G loss: 0.742265]
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738 [D loss: 0.686122, acc.: 54.49%] [G loss: 0.737750]
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739 [D loss: 0.685457, acc.: 56.84%] [G loss: 0.736272]
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740 [D loss: 0.685275, acc.: 54.88%] [G loss: 0.737505]
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741 [D loss: 0.687802, acc.: 52.93%] [G loss: 0.734852]
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742 [D loss: 0.688772, acc.: 55.27%] [G loss: 0.740170]
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743 [D loss: 0.685355, acc.: 55.86%] [G loss: 0.735787]
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744 [D loss: 0.682752, acc.: 58.01%] [G loss: 0.739131]
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745 [D loss: 0.689093, acc.: 54.69%] [G loss: 0.739095]
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746 [D loss: 0.688684, acc.: 52.93%] [G loss: 0.738336]
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747 [D loss: 0.686736, acc.: 56.25%] [G loss: 0.735384]
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748 [D loss: 0.689941, acc.: 54.10%] [G loss: 0.739935]
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749 [D loss: 0.689418, acc.: 53.52%] [G loss: 0.740381]
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750 [D loss: 0.689880, acc.: 53.32%] [G loss: 0.734480]
1/1 [==============================] - 0s 16ms/step
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751 [D loss: 0.689236, acc.: 54.49%] [G loss: 0.733766]
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752 [D loss: 0.690272, acc.: 53.32%] [G loss: 0.732841]
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753 [D loss: 0.685868, acc.: 53.71%] [G loss: 0.728148]
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754 [D loss: 0.690684, acc.: 53.12%] [G loss: 0.730513]
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755 [D loss: 0.687623, acc.: 54.49%] [G loss: 0.724530]
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756 [D loss: 0.687306, acc.: 56.64%] [G loss: 0.727169]
8/8 [==============================] - 0s 2ms/step
757 [D loss: 0.689189, acc.: 52.34%] [G loss: 0.728588]
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758 [D loss: 0.685540, acc.: 55.86%] [G loss: 0.732509]
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759 [D loss: 0.689407, acc.: 55.27%] [G loss: 0.726098]
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760 [D loss: 0.687004, acc.: 56.84%] [G loss: 0.725866]
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761 [D loss: 0.689771, acc.: 54.69%] [G loss: 0.722502]
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762 [D loss: 0.689784, acc.: 53.71%] [G loss: 0.726244]
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763 [D loss: 0.692771, acc.: 51.76%] [G loss: 0.724878]
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764 [D loss: 0.691020, acc.: 50.00%] [G loss: 0.725858]
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765 [D loss: 0.692621, acc.: 51.56%] [G loss: 0.729212]
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766 [D loss: 0.689747, acc.: 52.54%] [G loss: 0.725949]
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767 [D loss: 0.685918, acc.: 57.81%] [G loss: 0.726454]
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768 [D loss: 0.690567, acc.: 52.34%] [G loss: 0.720574]
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769 [D loss: 0.692876, acc.: 51.95%] [G loss: 0.718777]
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770 [D loss: 0.695145, acc.: 50.00%] [G loss: 0.718880]
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771 [D loss: 0.693224, acc.: 50.59%] [G loss: 0.730376]
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772 [D loss: 0.693453, acc.: 49.22%] [G loss: 0.723685]
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773 [D loss: 0.696219, acc.: 48.83%] [G loss: 0.721204]
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774 [D loss: 0.691972, acc.: 53.12%] [G loss: 0.729699]
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775 [D loss: 0.686970, acc.: 56.05%] [G loss: 0.725296]
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776 [D loss: 0.692787, acc.: 50.39%] [G loss: 0.727177]
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777 [D loss: 0.689444, acc.: 53.91%] [G loss: 0.728780]
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778 [D loss: 0.689256, acc.: 50.78%] [G loss: 0.729779]
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779 [D loss: 0.688463, acc.: 55.27%] [G loss: 0.726185]
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780 [D loss: 0.690863, acc.: 51.37%] [G loss: 0.732867]
8/8 [==============================] - 0s 2ms/step
781 [D loss: 0.691991, acc.: 49.80%] [G loss: 0.726792]
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782 [D loss: 0.688068, acc.: 55.08%] [G loss: 0.731067]
8/8 [==============================] - 0s 2ms/step
783 [D loss: 0.687177, acc.: 51.76%] [G loss: 0.734335]
8/8 [==============================] - 0s 2ms/step
784 [D loss: 0.685644, acc.: 57.42%] [G loss: 0.728548]
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785 [D loss: 0.686140, acc.: 55.47%] [G loss: 0.733078]
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786 [D loss: 0.688553, acc.: 52.93%] [G loss: 0.733220]
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787 [D loss: 0.687670, acc.: 55.47%] [G loss: 0.728955]
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788 [D loss: 0.688531, acc.: 53.91%] [G loss: 0.725141]
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789 [D loss: 0.690984, acc.: 51.76%] [G loss: 0.724841]
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790 [D loss: 0.687949, acc.: 56.25%] [G loss: 0.726204]
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791 [D loss: 0.686769, acc.: 57.03%] [G loss: 0.717006]
8/8 [==============================] - 0s 2ms/step
792 [D loss: 0.687363, acc.: 55.27%] [G loss: 0.719784]
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793 [D loss: 0.687573, acc.: 53.91%] [G loss: 0.725471]
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794 [D loss: 0.686150, acc.: 55.66%] [G loss: 0.724246]
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795 [D loss: 0.684982, acc.: 56.45%] [G loss: 0.720495]
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796 [D loss: 0.689301, acc.: 51.56%] [G loss: 0.720357]
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797 [D loss: 0.687959, acc.: 53.32%] [G loss: 0.715103]
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798 [D loss: 0.682360, acc.: 58.98%] [G loss: 0.720964]
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799 [D loss: 0.685945, acc.: 55.08%] [G loss: 0.722659]
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800 [D loss: 0.694806, acc.: 48.05%] [G loss: 0.723053]
1/1 [==============================] - 0s 16ms/step
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801 [D loss: 0.683663, acc.: 57.42%] [G loss: 0.719269]
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802 [D loss: 0.687643, acc.: 58.59%] [G loss: 0.721094]
8/8 [==============================] - 0s 2ms/step
803 [D loss: 0.690089, acc.: 54.10%] [G loss: 0.717909]
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804 [D loss: 0.689784, acc.: 53.91%] [G loss: 0.721967]
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805 [D loss: 0.684549, acc.: 58.20%] [G loss: 0.722001]
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806 [D loss: 0.691899, acc.: 52.93%] [G loss: 0.724061]
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807 [D loss: 0.689326, acc.: 52.93%] [G loss: 0.726607]
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808 [D loss: 0.684845, acc.: 58.20%] [G loss: 0.729012]
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809 [D loss: 0.686790, acc.: 55.08%] [G loss: 0.722538]
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810 [D loss: 0.688934, acc.: 53.91%] [G loss: 0.723813]
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811 [D loss: 0.688692, acc.: 51.37%] [G loss: 0.727923]
8/8 [==============================] - 0s 2ms/step
812 [D loss: 0.686263, acc.: 55.47%] [G loss: 0.730427]
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813 [D loss: 0.685284, acc.: 57.62%] [G loss: 0.736807]
8/8 [==============================] - 0s 2ms/step
814 [D loss: 0.685492, acc.: 55.66%] [G loss: 0.730489]
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815 [D loss: 0.687219, acc.: 55.86%] [G loss: 0.733124]
8/8 [==============================] - 0s 2ms/step
816 [D loss: 0.682327, acc.: 56.45%] [G loss: 0.732644]
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817 [D loss: 0.685855, acc.: 56.05%] [G loss: 0.734210]
8/8 [==============================] - 0s 2ms/step
818 [D loss: 0.679029, acc.: 62.30%] [G loss: 0.731464]
8/8 [==============================] - 0s 2ms/step
819 [D loss: 0.681866, acc.: 59.18%] [G loss: 0.730350]
8/8 [==============================] - 0s 2ms/step
820 [D loss: 0.690368, acc.: 53.71%] [G loss: 0.730528]
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821 [D loss: 0.687720, acc.: 54.88%] [G loss: 0.730601]
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822 [D loss: 0.688594, acc.: 53.91%] [G loss: 0.730372]
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823 [D loss: 0.687409, acc.: 54.30%] [G loss: 0.729558]
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824 [D loss: 0.685841, acc.: 57.81%] [G loss: 0.723296]
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825 [D loss: 0.678064, acc.: 60.55%] [G loss: 0.730244]
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826 [D loss: 0.690523, acc.: 52.54%] [G loss: 0.727337]
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827 [D loss: 0.685620, acc.: 53.71%] [G loss: 0.718856]
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828 [D loss: 0.685989, acc.: 55.47%] [G loss: 0.722032]
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829 [D loss: 0.688558, acc.: 54.30%] [G loss: 0.715135]
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830 [D loss: 0.694668, acc.: 49.02%] [G loss: 0.712562]
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831 [D loss: 0.691986, acc.: 52.54%] [G loss: 0.722150]
8/8 [==============================] - 0s 2ms/step
832 [D loss: 0.688931, acc.: 53.71%] [G loss: 0.719078]
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833 [D loss: 0.691528, acc.: 52.34%] [G loss: 0.715700]
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834 [D loss: 0.690312, acc.: 53.52%] [G loss: 0.714757]
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835 [D loss: 0.689951, acc.: 52.54%] [G loss: 0.719143]
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836 [D loss: 0.691802, acc.: 51.17%] [G loss: 0.723238]
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837 [D loss: 0.689690, acc.: 52.34%] [G loss: 0.716625]
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838 [D loss: 0.692710, acc.: 50.00%] [G loss: 0.716863]
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839 [D loss: 0.688675, acc.: 55.27%] [G loss: 0.723194]
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840 [D loss: 0.690409, acc.: 55.47%] [G loss: 0.725107]
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841 [D loss: 0.686026, acc.: 55.66%] [G loss: 0.723959]
8/8 [==============================] - 0s 2ms/step
842 [D loss: 0.689289, acc.: 53.52%] [G loss: 0.724467]
8/8 [==============================] - 0s 2ms/step
843 [D loss: 0.688103, acc.: 54.10%] [G loss: 0.716659]
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844 [D loss: 0.686947, acc.: 53.32%] [G loss: 0.722895]
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845 [D loss: 0.686772, acc.: 53.52%] [G loss: 0.720004]
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846 [D loss: 0.684684, acc.: 55.66%] [G loss: 0.718807]
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847 [D loss: 0.682497, acc.: 58.40%] [G loss: 0.718142]
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848 [D loss: 0.690370, acc.: 55.66%] [G loss: 0.714566]
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849 [D loss: 0.687659, acc.: 57.23%] [G loss: 0.714480]
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850 [D loss: 0.688454, acc.: 53.12%] [G loss: 0.716347]
1/1 [==============================] - 0s 15ms/step
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851 [D loss: 0.689509, acc.: 52.93%] [G loss: 0.718991]
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852 [D loss: 0.692681, acc.: 52.93%] [G loss: 0.715198]
8/8 [==============================] - 0s 2ms/step
853 [D loss: 0.687470, acc.: 55.66%] [G loss: 0.715703]
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854 [D loss: 0.683666, acc.: 58.20%] [G loss: 0.709288]
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855 [D loss: 0.683675, acc.: 55.86%] [G loss: 0.714152]
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856 [D loss: 0.689042, acc.: 56.84%] [G loss: 0.719226]
8/8 [==============================] - 0s 2ms/step
857 [D loss: 0.685794, acc.: 55.47%] [G loss: 0.717754]
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858 [D loss: 0.689438, acc.: 52.73%] [G loss: 0.711147]
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859 [D loss: 0.684121, acc.: 58.98%] [G loss: 0.711714]
8/8 [==============================] - 0s 2ms/step
860 [D loss: 0.685587, acc.: 56.64%] [G loss: 0.716957]
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861 [D loss: 0.692669, acc.: 51.95%] [G loss: 0.715354]
8/8 [==============================] - 0s 2ms/step
862 [D loss: 0.692047, acc.: 49.41%] [G loss: 0.717143]
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863 [D loss: 0.686996, acc.: 55.86%] [G loss: 0.712300]
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864 [D loss: 0.687913, acc.: 56.05%] [G loss: 0.719396]
8/8 [==============================] - 0s 2ms/step
865 [D loss: 0.692712, acc.: 53.71%] [G loss: 0.715872]
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866 [D loss: 0.687733, acc.: 55.86%] [G loss: 0.718267]
8/8 [==============================] - 0s 2ms/step
867 [D loss: 0.690698, acc.: 52.15%] [G loss: 0.716767]
8/8 [==============================] - 0s 2ms/step
868 [D loss: 0.687018, acc.: 56.45%] [G loss: 0.715933]
8/8 [==============================] - 0s 2ms/step
869 [D loss: 0.684902, acc.: 55.86%] [G loss: 0.717172]
8/8 [==============================] - 0s 2ms/step
870 [D loss: 0.686694, acc.: 56.64%] [G loss: 0.722513]
8/8 [==============================] - 0s 2ms/step
871 [D loss: 0.686752, acc.: 57.42%] [G loss: 0.718065]
8/8 [==============================] - 0s 2ms/step
872 [D loss: 0.684802, acc.: 57.62%] [G loss: 0.712959]
8/8 [==============================] - 0s 2ms/step
873 [D loss: 0.687782, acc.: 54.30%] [G loss: 0.725262]
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874 [D loss: 0.683023, acc.: 60.35%] [G loss: 0.717843]
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875 [D loss: 0.686299, acc.: 57.42%] [G loss: 0.726913]
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876 [D loss: 0.685421, acc.: 58.20%] [G loss: 0.722785]
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877 [D loss: 0.687733, acc.: 56.45%] [G loss: 0.723057]
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878 [D loss: 0.685350, acc.: 57.81%] [G loss: 0.724593]
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879 [D loss: 0.686556, acc.: 55.08%] [G loss: 0.725179]
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880 [D loss: 0.685218, acc.: 56.05%] [G loss: 0.730525]
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881 [D loss: 0.683431, acc.: 58.79%] [G loss: 0.731732]
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882 [D loss: 0.679980, acc.: 60.74%] [G loss: 0.724481]
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883 [D loss: 0.683439, acc.: 59.77%] [G loss: 0.727121]
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884 [D loss: 0.683608, acc.: 57.42%] [G loss: 0.725692]
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885 [D loss: 0.678709, acc.: 60.55%] [G loss: 0.722235]
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886 [D loss: 0.684610, acc.: 53.71%] [G loss: 0.728086]
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887 [D loss: 0.679138, acc.: 58.40%] [G loss: 0.721896]
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888 [D loss: 0.681881, acc.: 56.84%] [G loss: 0.729425]
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889 [D loss: 0.681663, acc.: 57.23%] [G loss: 0.724023]
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890 [D loss: 0.677446, acc.: 58.20%] [G loss: 0.727995]
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891 [D loss: 0.681263, acc.: 59.38%] [G loss: 0.722660]
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892 [D loss: 0.680668, acc.: 59.38%] [G loss: 0.719947]
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893 [D loss: 0.684566, acc.: 56.45%] [G loss: 0.716491]
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894 [D loss: 0.684457, acc.: 54.69%] [G loss: 0.717683]
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895 [D loss: 0.684357, acc.: 57.81%] [G loss: 0.712710]
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896 [D loss: 0.682881, acc.: 58.79%] [G loss: 0.723954]
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897 [D loss: 0.686527, acc.: 56.25%] [G loss: 0.722429]
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898 [D loss: 0.686906, acc.: 58.98%] [G loss: 0.727845]
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899 [D loss: 0.686208, acc.: 55.08%] [G loss: 0.722539]
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900 [D loss: 0.683239, acc.: 58.98%] [G loss: 0.719855]
1/1 [==============================] - 0s 16ms/step
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901 [D loss: 0.687544, acc.: 56.64%] [G loss: 0.714850]
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902 [D loss: 0.678435, acc.: 59.57%] [G loss: 0.719981]
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903 [D loss: 0.679896, acc.: 59.57%] [G loss: 0.717937]
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904 [D loss: 0.680514, acc.: 58.40%] [G loss: 0.715765]
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905 [D loss: 0.691511, acc.: 52.73%] [G loss: 0.724863]
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906 [D loss: 0.688063, acc.: 53.52%] [G loss: 0.713027]
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907 [D loss: 0.693913, acc.: 48.05%] [G loss: 0.718440]
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908 [D loss: 0.687739, acc.: 53.52%] [G loss: 0.712431]
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909 [D loss: 0.689906, acc.: 52.73%] [G loss: 0.713904]
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910 [D loss: 0.687136, acc.: 54.10%] [G loss: 0.713928]
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911 [D loss: 0.692005, acc.: 54.88%] [G loss: 0.710600]
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912 [D loss: 0.686451, acc.: 55.86%] [G loss: 0.712777]
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913 [D loss: 0.685212, acc.: 53.91%] [G loss: 0.714019]
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914 [D loss: 0.689236, acc.: 51.17%] [G loss: 0.704658]
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915 [D loss: 0.688733, acc.: 52.34%] [G loss: 0.704671]
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916 [D loss: 0.686601, acc.: 56.25%] [G loss: 0.704814]
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917 [D loss: 0.693791, acc.: 50.59%] [G loss: 0.706035]
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918 [D loss: 0.694341, acc.: 49.22%] [G loss: 0.706008]
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919 [D loss: 0.693605, acc.: 50.39%] [G loss: 0.706038]
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920 [D loss: 0.687744, acc.: 54.30%] [G loss: 0.706035]
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921 [D loss: 0.688236, acc.: 50.78%] [G loss: 0.696802]
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922 [D loss: 0.689574, acc.: 55.27%] [G loss: 0.698331]
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923 [D loss: 0.691666, acc.: 52.73%] [G loss: 0.705317]
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924 [D loss: 0.693731, acc.: 49.02%] [G loss: 0.705006]
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925 [D loss: 0.689928, acc.: 51.17%] [G loss: 0.702239]
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926 [D loss: 0.687686, acc.: 51.56%] [G loss: 0.710996]
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927 [D loss: 0.690187, acc.: 52.15%] [G loss: 0.711359]
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928 [D loss: 0.685138, acc.: 54.49%] [G loss: 0.705813]
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929 [D loss: 0.683101, acc.: 54.30%] [G loss: 0.710864]
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930 [D loss: 0.684297, acc.: 55.86%] [G loss: 0.710234]
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931 [D loss: 0.679521, acc.: 60.74%] [G loss: 0.715960]
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932 [D loss: 0.683265, acc.: 55.27%] [G loss: 0.716458]
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933 [D loss: 0.683828, acc.: 57.62%] [G loss: 0.713646]
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934 [D loss: 0.681651, acc.: 57.62%] [G loss: 0.714514]
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935 [D loss: 0.680110, acc.: 62.70%] [G loss: 0.712064]
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936 [D loss: 0.683727, acc.: 58.59%] [G loss: 0.712807]
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937 [D loss: 0.684925, acc.: 55.08%] [G loss: 0.725965]
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938 [D loss: 0.676153, acc.: 61.72%] [G loss: 0.711248]
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939 [D loss: 0.678560, acc.: 60.35%] [G loss: 0.731598]
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940 [D loss: 0.681025, acc.: 58.40%] [G loss: 0.729865]
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941 [D loss: 0.679779, acc.: 58.98%] [G loss: 0.732516]
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942 [D loss: 0.678409, acc.: 59.38%] [G loss: 0.728368]
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943 [D loss: 0.680759, acc.: 56.45%] [G loss: 0.726163]
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944 [D loss: 0.671384, acc.: 63.48%] [G loss: 0.724219]
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945 [D loss: 0.680534, acc.: 58.20%] [G loss: 0.716938]
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946 [D loss: 0.685571, acc.: 54.49%] [G loss: 0.719209]
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947 [D loss: 0.682864, acc.: 57.23%] [G loss: 0.712602]
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948 [D loss: 0.686677, acc.: 57.81%] [G loss: 0.714629]
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949 [D loss: 0.683064, acc.: 58.20%] [G loss: 0.708707]
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950 [D loss: 0.686050, acc.: 53.12%] [G loss: 0.705288]
1/1 [==============================] - 0s 16ms/step
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951 [D loss: 0.685582, acc.: 56.25%] [G loss: 0.706036]
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952 [D loss: 0.681823, acc.: 59.96%] [G loss: 0.709298]
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953 [D loss: 0.693094, acc.: 48.05%] [G loss: 0.709878]
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954 [D loss: 0.688413, acc.: 52.93%] [G loss: 0.699824]
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955 [D loss: 0.699720, acc.: 48.05%] [G loss: 0.692313]
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956 [D loss: 0.690701, acc.: 52.34%] [G loss: 0.700150]
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957 [D loss: 0.696137, acc.: 45.12%] [G loss: 0.702971]
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958 [D loss: 0.690656, acc.: 51.17%] [G loss: 0.701424]
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959 [D loss: 0.695153, acc.: 50.20%] [G loss: 0.705528]
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960 [D loss: 0.685741, acc.: 54.69%] [G loss: 0.703648]
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961 [D loss: 0.691079, acc.: 50.59%] [G loss: 0.709792]
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962 [D loss: 0.684672, acc.: 56.25%] [G loss: 0.718151]
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963 [D loss: 0.684181, acc.: 56.25%] [G loss: 0.714103]
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964 [D loss: 0.693080, acc.: 50.00%] [G loss: 0.710327]
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965 [D loss: 0.689789, acc.: 52.15%] [G loss: 0.713434]
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966 [D loss: 0.689245, acc.: 52.15%] [G loss: 0.704749]
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967 [D loss: 0.688406, acc.: 53.32%] [G loss: 0.717323]
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968 [D loss: 0.688774, acc.: 53.91%] [G loss: 0.710224]
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969 [D loss: 0.691223, acc.: 50.00%] [G loss: 0.705870]
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970 [D loss: 0.685826, acc.: 54.69%] [G loss: 0.716028]
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971 [D loss: 0.686224, acc.: 57.42%] [G loss: 0.705374]
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972 [D loss: 0.685165, acc.: 55.86%] [G loss: 0.705341]
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973 [D loss: 0.684645, acc.: 57.23%] [G loss: 0.711361]
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974 [D loss: 0.689154, acc.: 52.15%] [G loss: 0.708619]
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975 [D loss: 0.688503, acc.: 53.91%] [G loss: 0.718795]
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976 [D loss: 0.681844, acc.: 56.64%] [G loss: 0.713538]
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977 [D loss: 0.685735, acc.: 55.66%] [G loss: 0.714525]
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978 [D loss: 0.680419, acc.: 58.40%] [G loss: 0.719498]
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979 [D loss: 0.683458, acc.: 55.08%] [G loss: 0.733004]
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980 [D loss: 0.678461, acc.: 58.59%] [G loss: 0.725622]
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981 [D loss: 0.684151, acc.: 56.05%] [G loss: 0.716146]
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982 [D loss: 0.689352, acc.: 54.30%] [G loss: 0.729352]
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983 [D loss: 0.691533, acc.: 51.56%] [G loss: 0.735120]
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984 [D loss: 0.683755, acc.: 57.81%] [G loss: 0.715409]
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985 [D loss: 0.688347, acc.: 53.71%] [G loss: 0.720771]
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986 [D loss: 0.684791, acc.: 57.23%] [G loss: 0.713803]
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987 [D loss: 0.683359, acc.: 57.62%] [G loss: 0.716900]
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988 [D loss: 0.688072, acc.: 55.47%] [G loss: 0.723432]
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989 [D loss: 0.686732, acc.: 56.25%] [G loss: 0.716008]
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990 [D loss: 0.695487, acc.: 50.59%] [G loss: 0.722621]
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991 [D loss: 0.688743, acc.: 51.76%] [G loss: 0.715286]
8/8 [==============================] - 0s 2ms/step
992 [D loss: 0.689135, acc.: 55.47%] [G loss: 0.711821]
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993 [D loss: 0.691511, acc.: 52.93%] [G loss: 0.717151]
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994 [D loss: 0.687492, acc.: 52.93%] [G loss: 0.709456]
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995 [D loss: 0.688034, acc.: 52.93%] [G loss: 0.715130]
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996 [D loss: 0.693815, acc.: 49.22%] [G loss: 0.720794]
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997 [D loss: 0.686133, acc.: 53.71%] [G loss: 0.719789]
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998 [D loss: 0.688524, acc.: 52.54%] [G loss: 0.712722]
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999 [D loss: 0.694544, acc.: 50.00%] [G loss: 0.704453]
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1000 [D loss: 0.698737, acc.: 50.20%] [G loss: 0.712128]
1/1 [==============================] - 0s 16ms/step
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1001 [D loss: 0.692460, acc.: 52.15%] [G loss: 0.719506]
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1002 [D loss: 0.687159, acc.: 52.54%] [G loss: 0.708871]
8/8 [==============================] - 0s 2ms/step
1003 [D loss: 0.685842, acc.: 54.88%] [G loss: 0.716678]
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1004 [D loss: 0.695077, acc.: 52.15%] [G loss: 0.715837]
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1005 [D loss: 0.694013, acc.: 52.73%] [G loss: 0.719694]
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1006 [D loss: 0.691083, acc.: 53.32%] [G loss: 0.718202]
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1007 [D loss: 0.685513, acc.: 55.08%] [G loss: 0.720614]
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1008 [D loss: 0.689738, acc.: 52.54%] [G loss: 0.716671]
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1009 [D loss: 0.690144, acc.: 53.12%] [G loss: 0.725364]
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1010 [D loss: 0.687444, acc.: 54.88%] [G loss: 0.719076]
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1011 [D loss: 0.684135, acc.: 58.01%] [G loss: 0.726416]
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1012 [D loss: 0.688721, acc.: 55.27%] [G loss: 0.728826]
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1013 [D loss: 0.689578, acc.: 52.34%] [G loss: 0.724429]
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1014 [D loss: 0.683158, acc.: 58.40%] [G loss: 0.726033]
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1015 [D loss: 0.685785, acc.: 57.42%] [G loss: 0.721989]
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1016 [D loss: 0.690045, acc.: 55.86%] [G loss: 0.724332]
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1017 [D loss: 0.682310, acc.: 55.47%] [G loss: 0.720754]
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1018 [D loss: 0.691320, acc.: 54.10%] [G loss: 0.726228]
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1019 [D loss: 0.683686, acc.: 59.38%] [G loss: 0.722914]
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1020 [D loss: 0.682210, acc.: 60.35%] [G loss: 0.736573]
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1021 [D loss: 0.683466, acc.: 59.77%] [G loss: 0.730572]
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1022 [D loss: 0.684951, acc.: 56.64%] [G loss: 0.722952]
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1023 [D loss: 0.680859, acc.: 57.42%] [G loss: 0.725565]
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1024 [D loss: 0.691378, acc.: 51.76%] [G loss: 0.720441]
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1025 [D loss: 0.688906, acc.: 55.86%] [G loss: 0.729154]
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1026 [D loss: 0.693007, acc.: 52.15%] [G loss: 0.726840]
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1027 [D loss: 0.684251, acc.: 55.86%] [G loss: 0.738468]
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1028 [D loss: 0.690314, acc.: 50.78%] [G loss: 0.726917]
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1029 [D loss: 0.686006, acc.: 55.47%] [G loss: 0.734534]
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1030 [D loss: 0.691349, acc.: 54.10%] [G loss: 0.728253]
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1031 [D loss: 0.690625, acc.: 53.91%] [G loss: 0.734662]
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1032 [D loss: 0.689486, acc.: 51.76%] [G loss: 0.723041]
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1033 [D loss: 0.691507, acc.: 50.59%] [G loss: 0.726783]
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1034 [D loss: 0.684510, acc.: 58.79%] [G loss: 0.726899]
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1035 [D loss: 0.685858, acc.: 54.69%] [G loss: 0.729067]
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1036 [D loss: 0.686116, acc.: 54.49%] [G loss: 0.727809]
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1037 [D loss: 0.684631, acc.: 56.45%] [G loss: 0.727469]
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1038 [D loss: 0.691033, acc.: 53.71%] [G loss: 0.718911]
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1039 [D loss: 0.694224, acc.: 48.63%] [G loss: 0.717968]
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1040 [D loss: 0.689854, acc.: 54.69%] [G loss: 0.721085]
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1041 [D loss: 0.692246, acc.: 53.91%] [G loss: 0.709989]
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1042 [D loss: 0.681260, acc.: 58.01%] [G loss: 0.711375]
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1043 [D loss: 0.689309, acc.: 55.47%] [G loss: 0.712312]
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1044 [D loss: 0.698369, acc.: 48.83%] [G loss: 0.712874]
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1045 [D loss: 0.694591, acc.: 51.56%] [G loss: 0.707932]
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1046 [D loss: 0.693018, acc.: 53.52%] [G loss: 0.709175]
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1047 [D loss: 0.690837, acc.: 53.52%] [G loss: 0.706958]
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1048 [D loss: 0.689488, acc.: 51.56%] [G loss: 0.710707]
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1049 [D loss: 0.692521, acc.: 50.98%] [G loss: 0.700440]
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1050 [D loss: 0.694632, acc.: 51.56%] [G loss: 0.716361]
1/1 [==============================] - 0s 15ms/step
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1051 [D loss: 0.689162, acc.: 56.05%] [G loss: 0.720235]
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1052 [D loss: 0.688256, acc.: 54.69%] [G loss: 0.712616]
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1053 [D loss: 0.683045, acc.: 57.03%] [G loss: 0.715965]
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1054 [D loss: 0.686176, acc.: 54.10%] [G loss: 0.715275]
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1055 [D loss: 0.684704, acc.: 56.64%] [G loss: 0.722979]
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1056 [D loss: 0.690815, acc.: 50.98%] [G loss: 0.716060]
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1057 [D loss: 0.681160, acc.: 59.38%] [G loss: 0.721687]
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1058 [D loss: 0.679085, acc.: 58.01%] [G loss: 0.723006]
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1059 [D loss: 0.688696, acc.: 55.27%] [G loss: 0.708871]
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1060 [D loss: 0.697624, acc.: 50.39%] [G loss: 0.719725]
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1061 [D loss: 0.690873, acc.: 52.34%] [G loss: 0.708208]
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1062 [D loss: 0.695136, acc.: 50.78%] [G loss: 0.711881]
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1063 [D loss: 0.696128, acc.: 49.22%] [G loss: 0.713945]
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1064 [D loss: 0.695872, acc.: 48.05%] [G loss: 0.717920]
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1065 [D loss: 0.691807, acc.: 52.15%] [G loss: 0.726947]
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1066 [D loss: 0.687887, acc.: 51.76%] [G loss: 0.731925]
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1067 [D loss: 0.690603, acc.: 53.12%] [G loss: 0.733015]
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1068 [D loss: 0.677556, acc.: 60.55%] [G loss: 0.734406]
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1069 [D loss: 0.683148, acc.: 58.98%] [G loss: 0.734061]
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1070 [D loss: 0.680409, acc.: 57.62%] [G loss: 0.740247]
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1071 [D loss: 0.683995, acc.: 58.40%] [G loss: 0.731630]
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1072 [D loss: 0.686961, acc.: 57.23%] [G loss: 0.728877]
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1073 [D loss: 0.684598, acc.: 56.25%] [G loss: 0.715352]
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1074 [D loss: 0.691273, acc.: 52.34%] [G loss: 0.717745]
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1075 [D loss: 0.692030, acc.: 52.73%] [G loss: 0.717831]
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1076 [D loss: 0.693990, acc.: 51.76%] [G loss: 0.716009]
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1077 [D loss: 0.690393, acc.: 51.95%] [G loss: 0.707989]
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1078 [D loss: 0.694380, acc.: 51.17%] [G loss: 0.712947]
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1079 [D loss: 0.695541, acc.: 51.95%] [G loss: 0.710876]
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1080 [D loss: 0.692970, acc.: 51.76%] [G loss: 0.703783]
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1081 [D loss: 0.693549, acc.: 51.56%] [G loss: 0.701587]
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1082 [D loss: 0.697169, acc.: 50.39%] [G loss: 0.709287]
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1083 [D loss: 0.694375, acc.: 49.61%] [G loss: 0.710275]
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1084 [D loss: 0.696098, acc.: 51.17%] [G loss: 0.712544]
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1085 [D loss: 0.696776, acc.: 48.63%] [G loss: 0.714475]
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1086 [D loss: 0.686222, acc.: 55.66%] [G loss: 0.708474]
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1087 [D loss: 0.690510, acc.: 52.34%] [G loss: 0.720910]
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1088 [D loss: 0.690502, acc.: 51.95%] [G loss: 0.721276]
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1089 [D loss: 0.689707, acc.: 53.32%] [G loss: 0.718588]
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1090 [D loss: 0.681220, acc.: 56.64%] [G loss: 0.729558]
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1091 [D loss: 0.684680, acc.: 58.40%] [G loss: 0.720143]
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1092 [D loss: 0.684192, acc.: 56.05%] [G loss: 0.715513]
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1093 [D loss: 0.690811, acc.: 55.47%] [G loss: 0.713159]
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1094 [D loss: 0.692345, acc.: 52.15%] [G loss: 0.717762]
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1095 [D loss: 0.688257, acc.: 55.66%] [G loss: 0.718157]
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1096 [D loss: 0.688111, acc.: 53.91%] [G loss: 0.718819]
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1097 [D loss: 0.690860, acc.: 51.95%] [G loss: 0.716150]
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1098 [D loss: 0.693911, acc.: 51.95%] [G loss: 0.710771]
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1099 [D loss: 0.695246, acc.: 48.44%] [G loss: 0.717662]
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1100 [D loss: 0.699811, acc.: 49.61%] [G loss: 0.704459]
1/1 [==============================] - 0s 17ms/step
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1101 [D loss: 0.693175, acc.: 51.95%] [G loss: 0.711814]
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1102 [D loss: 0.695588, acc.: 50.59%] [G loss: 0.715956]
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1103 [D loss: 0.693875, acc.: 49.80%] [G loss: 0.710874]
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1104 [D loss: 0.692088, acc.: 50.39%] [G loss: 0.715751]
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1105 [D loss: 0.691469, acc.: 53.91%] [G loss: 0.707235]
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1106 [D loss: 0.691255, acc.: 51.56%] [G loss: 0.719408]
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1107 [D loss: 0.696038, acc.: 51.56%] [G loss: 0.720263]
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1108 [D loss: 0.690294, acc.: 53.71%] [G loss: 0.717202]
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1109 [D loss: 0.685109, acc.: 55.47%] [G loss: 0.717057]
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1110 [D loss: 0.691641, acc.: 50.78%] [G loss: 0.716130]
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1111 [D loss: 0.687696, acc.: 56.84%] [G loss: 0.717769]
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1112 [D loss: 0.690554, acc.: 53.32%] [G loss: 0.717179]
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1113 [D loss: 0.687776, acc.: 54.88%] [G loss: 0.717846]
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1114 [D loss: 0.692067, acc.: 51.56%] [G loss: 0.723428]
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1115 [D loss: 0.688012, acc.: 52.34%] [G loss: 0.716682]
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1116 [D loss: 0.687272, acc.: 51.76%] [G loss: 0.725872]
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1117 [D loss: 0.687546, acc.: 58.20%] [G loss: 0.719051]
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1118 [D loss: 0.685573, acc.: 55.47%] [G loss: 0.709361]
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1119 [D loss: 0.687885, acc.: 55.66%] [G loss: 0.721217]
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1120 [D loss: 0.688521, acc.: 53.32%] [G loss: 0.712643]
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1121 [D loss: 0.689150, acc.: 51.76%] [G loss: 0.724916]
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1122 [D loss: 0.687399, acc.: 54.49%] [G loss: 0.719420]
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1123 [D loss: 0.683786, acc.: 55.66%] [G loss: 0.732297]
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1124 [D loss: 0.695163, acc.: 50.00%] [G loss: 0.727016]
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1125 [D loss: 0.688706, acc.: 55.27%] [G loss: 0.716397]
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1126 [D loss: 0.687996, acc.: 53.12%] [G loss: 0.721669]
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1127 [D loss: 0.686676, acc.: 55.08%] [G loss: 0.726049]
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1128 [D loss: 0.692331, acc.: 50.00%] [G loss: 0.717418]
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1129 [D loss: 0.692272, acc.: 54.30%] [G loss: 0.718198]
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1130 [D loss: 0.693767, acc.: 51.76%] [G loss: 0.716298]
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1131 [D loss: 0.689043, acc.: 52.93%] [G loss: 0.714810]
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1132 [D loss: 0.696486, acc.: 50.20%] [G loss: 0.714859]
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1133 [D loss: 0.687227, acc.: 52.15%] [G loss: 0.715977]
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1134 [D loss: 0.696483, acc.: 49.22%] [G loss: 0.712379]
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1135 [D loss: 0.693944, acc.: 51.56%] [G loss: 0.713781]
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1136 [D loss: 0.693334, acc.: 51.76%] [G loss: 0.715939]
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1137 [D loss: 0.695165, acc.: 48.63%] [G loss: 0.716234]
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1138 [D loss: 0.686670, acc.: 56.45%] [G loss: 0.716038]
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1139 [D loss: 0.689688, acc.: 54.10%] [G loss: 0.720106]
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1140 [D loss: 0.685519, acc.: 57.81%] [G loss: 0.723675]
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1141 [D loss: 0.683793, acc.: 57.03%] [G loss: 0.716322]
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1142 [D loss: 0.688354, acc.: 53.52%] [G loss: 0.720541]
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1143 [D loss: 0.689619, acc.: 55.86%] [G loss: 0.711603]
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1144 [D loss: 0.682048, acc.: 59.96%] [G loss: 0.714896]
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1145 [D loss: 0.687952, acc.: 53.32%] [G loss: 0.715034]
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1146 [D loss: 0.689136, acc.: 56.45%] [G loss: 0.709236]
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1147 [D loss: 0.687591, acc.: 53.71%] [G loss: 0.707499]
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1148 [D loss: 0.690444, acc.: 53.91%] [G loss: 0.710021]
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1149 [D loss: 0.689588, acc.: 52.15%] [G loss: 0.712479]
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1150 [D loss: 0.684440, acc.: 56.64%] [G loss: 0.707072]
1/1 [==============================] - 0s 15ms/step
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1151 [D loss: 0.692981, acc.: 49.41%] [G loss: 0.711996]
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1152 [D loss: 0.690887, acc.: 52.73%] [G loss: 0.708476]
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1153 [D loss: 0.697948, acc.: 48.24%] [G loss: 0.715868]
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1154 [D loss: 0.695892, acc.: 48.63%] [G loss: 0.714076]
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1155 [D loss: 0.694925, acc.: 50.20%] [G loss: 0.712878]
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1156 [D loss: 0.695634, acc.: 49.22%] [G loss: 0.719549]
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1157 [D loss: 0.701474, acc.: 44.34%] [G loss: 0.720091]
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1158 [D loss: 0.690202, acc.: 51.76%] [G loss: 0.716250]
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1159 [D loss: 0.687356, acc.: 54.69%] [G loss: 0.718662]
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1160 [D loss: 0.690560, acc.: 53.32%] [G loss: 0.711886]
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1161 [D loss: 0.694578, acc.: 50.98%] [G loss: 0.709964]
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1162 [D loss: 0.689327, acc.: 53.71%] [G loss: 0.716616]
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1163 [D loss: 0.689188, acc.: 53.71%] [G loss: 0.715458]
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1164 [D loss: 0.694724, acc.: 50.78%] [G loss: 0.719611]
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1165 [D loss: 0.691799, acc.: 52.54%] [G loss: 0.711614]
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1166 [D loss: 0.689098, acc.: 54.69%] [G loss: 0.711939]
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1167 [D loss: 0.687429, acc.: 53.71%] [G loss: 0.722929]
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1168 [D loss: 0.693206, acc.: 52.34%] [G loss: 0.717015]
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1169 [D loss: 0.688361, acc.: 52.34%] [G loss: 0.710947]
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1170 [D loss: 0.690569, acc.: 56.84%] [G loss: 0.711847]
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1171 [D loss: 0.685214, acc.: 56.25%] [G loss: 0.708346]
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1172 [D loss: 0.693494, acc.: 53.52%] [G loss: 0.717337]
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1173 [D loss: 0.692165, acc.: 51.95%] [G loss: 0.732297]
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1174 [D loss: 0.689964, acc.: 52.34%] [G loss: 0.724259]
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1175 [D loss: 0.690400, acc.: 53.12%] [G loss: 0.727246]
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1176 [D loss: 0.693542, acc.: 50.59%] [G loss: 0.728207]
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1177 [D loss: 0.686300, acc.: 54.69%] [G loss: 0.731084]
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1178 [D loss: 0.685925, acc.: 57.23%] [G loss: 0.732794]
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1179 [D loss: 0.688613, acc.: 50.98%] [G loss: 0.727814]
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1180 [D loss: 0.685302, acc.: 57.81%] [G loss: 0.732349]
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1181 [D loss: 0.687088, acc.: 54.69%] [G loss: 0.725417]
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1182 [D loss: 0.685820, acc.: 55.27%] [G loss: 0.724301]
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1183 [D loss: 0.695240, acc.: 49.41%] [G loss: 0.717730]
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1184 [D loss: 0.691572, acc.: 50.78%] [G loss: 0.719947]
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1185 [D loss: 0.692386, acc.: 50.20%] [G loss: 0.720806]
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1186 [D loss: 0.694401, acc.: 51.37%] [G loss: 0.717951]
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1187 [D loss: 0.693255, acc.: 52.73%] [G loss: 0.706521]
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1188 [D loss: 0.693185, acc.: 47.07%] [G loss: 0.711909]
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1189 [D loss: 0.694617, acc.: 49.80%] [G loss: 0.714368]
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1190 [D loss: 0.699077, acc.: 45.31%] [G loss: 0.716592]
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1191 [D loss: 0.693781, acc.: 52.34%] [G loss: 0.709212]
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1192 [D loss: 0.689641, acc.: 53.52%] [G loss: 0.714329]
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1193 [D loss: 0.692850, acc.: 50.39%] [G loss: 0.719197]
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1194 [D loss: 0.689011, acc.: 51.95%] [G loss: 0.714272]
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1195 [D loss: 0.688070, acc.: 53.32%] [G loss: 0.714341]
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1196 [D loss: 0.690604, acc.: 50.78%] [G loss: 0.717613]
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1197 [D loss: 0.688516, acc.: 56.25%] [G loss: 0.711625]
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1198 [D loss: 0.688670, acc.: 54.10%] [G loss: 0.713972]
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1199 [D loss: 0.696431, acc.: 45.51%] [G loss: 0.715311]
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1200 [D loss: 0.691838, acc.: 50.20%] [G loss: 0.718097]
1/1 [==============================] - 0s 16ms/step
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1201 [D loss: 0.686206, acc.: 53.71%] [G loss: 0.709928]
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1202 [D loss: 0.690236, acc.: 54.10%] [G loss: 0.714359]
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1203 [D loss: 0.689568, acc.: 53.52%] [G loss: 0.723759]
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1204 [D loss: 0.689305, acc.: 54.49%] [G loss: 0.729492]
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1205 [D loss: 0.688787, acc.: 53.91%] [G loss: 0.728771]
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1206 [D loss: 0.684389, acc.: 56.45%] [G loss: 0.724154]
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1207 [D loss: 0.683070, acc.: 57.81%] [G loss: 0.728174]
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1208 [D loss: 0.681058, acc.: 57.42%] [G loss: 0.729940]
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1209 [D loss: 0.691968, acc.: 52.34%] [G loss: 0.725830]
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1210 [D loss: 0.688851, acc.: 53.12%] [G loss: 0.725794]
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1211 [D loss: 0.686620, acc.: 54.49%] [G loss: 0.720714]
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1212 [D loss: 0.686345, acc.: 56.05%] [G loss: 0.725991]
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1213 [D loss: 0.682960, acc.: 55.86%] [G loss: 0.727552]
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1214 [D loss: 0.686573, acc.: 57.62%] [G loss: 0.723625]
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1215 [D loss: 0.687714, acc.: 57.81%] [G loss: 0.720319]
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1216 [D loss: 0.687553, acc.: 53.71%] [G loss: 0.714703]
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1217 [D loss: 0.688112, acc.: 52.34%] [G loss: 0.718248]
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1218 [D loss: 0.688282, acc.: 54.10%] [G loss: 0.712187]
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1219 [D loss: 0.692824, acc.: 51.17%] [G loss: 0.710639]
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1220 [D loss: 0.696041, acc.: 50.59%] [G loss: 0.705738]
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1221 [D loss: 0.694208, acc.: 49.02%] [G loss: 0.711397]
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1222 [D loss: 0.690420, acc.: 53.52%] [G loss: 0.714716]
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1223 [D loss: 0.697179, acc.: 49.41%] [G loss: 0.704559]
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1224 [D loss: 0.694752, acc.: 50.59%] [G loss: 0.707928]
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1225 [D loss: 0.696211, acc.: 48.63%] [G loss: 0.712351]
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1226 [D loss: 0.692596, acc.: 50.39%] [G loss: 0.712262]
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1227 [D loss: 0.696333, acc.: 50.00%] [G loss: 0.711098]
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1228 [D loss: 0.694492, acc.: 49.41%] [G loss: 0.715058]
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1229 [D loss: 0.694113, acc.: 48.05%] [G loss: 0.715236]
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1230 [D loss: 0.691246, acc.: 50.78%] [G loss: 0.716812]
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1231 [D loss: 0.684658, acc.: 57.42%] [G loss: 0.717292]
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1232 [D loss: 0.689821, acc.: 52.93%] [G loss: 0.714009]
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1233 [D loss: 0.685646, acc.: 54.10%] [G loss: 0.711504]
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1234 [D loss: 0.687629, acc.: 54.69%] [G loss: 0.724091]
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1235 [D loss: 0.685292, acc.: 56.45%] [G loss: 0.724380]
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1236 [D loss: 0.682589, acc.: 59.38%] [G loss: 0.716551]
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1237 [D loss: 0.682559, acc.: 58.98%] [G loss: 0.717708]
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1238 [D loss: 0.682488, acc.: 55.27%] [G loss: 0.722257]
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1239 [D loss: 0.684158, acc.: 53.71%] [G loss: 0.722876]
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1240 [D loss: 0.687343, acc.: 54.88%] [G loss: 0.722286]
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1241 [D loss: 0.683017, acc.: 57.03%] [G loss: 0.714581]
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1242 [D loss: 0.686740, acc.: 57.23%] [G loss: 0.719456]
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1243 [D loss: 0.691004, acc.: 50.78%] [G loss: 0.711466]
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1244 [D loss: 0.688234, acc.: 52.54%] [G loss: 0.716895]
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1245 [D loss: 0.693694, acc.: 50.20%] [G loss: 0.709312]
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1246 [D loss: 0.690345, acc.: 54.69%] [G loss: 0.711054]
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1247 [D loss: 0.694066, acc.: 49.22%] [G loss: 0.714452]
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1248 [D loss: 0.691958, acc.: 50.98%] [G loss: 0.712989]
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1249 [D loss: 0.692129, acc.: 52.15%] [G loss: 0.708123]
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1250 [D loss: 0.690111, acc.: 52.34%] [G loss: 0.715843]
1/1 [==============================] - 0s 16ms/step
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1251 [D loss: 0.694903, acc.: 49.41%] [G loss: 0.711866]
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1252 [D loss: 0.691103, acc.: 53.91%] [G loss: 0.720608]
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1253 [D loss: 0.690856, acc.: 52.73%] [G loss: 0.722769]
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1254 [D loss: 0.686848, acc.: 55.86%] [G loss: 0.718462]
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1255 [D loss: 0.691570, acc.: 51.17%] [G loss: 0.718148]
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1256 [D loss: 0.690776, acc.: 51.95%] [G loss: 0.717247]
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1257 [D loss: 0.686650, acc.: 54.10%] [G loss: 0.723812]
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1258 [D loss: 0.690778, acc.: 52.54%] [G loss: 0.719856]
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1259 [D loss: 0.691476, acc.: 52.93%] [G loss: 0.725030]
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1260 [D loss: 0.687176, acc.: 51.95%] [G loss: 0.719844]
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1261 [D loss: 0.690715, acc.: 53.71%] [G loss: 0.717003]
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1262 [D loss: 0.685704, acc.: 54.88%] [G loss: 0.725823]
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1263 [D loss: 0.689489, acc.: 52.73%] [G loss: 0.719644]
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1264 [D loss: 0.693236, acc.: 50.98%] [G loss: 0.716621]
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1265 [D loss: 0.685537, acc.: 53.32%] [G loss: 0.719176]
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1266 [D loss: 0.686085, acc.: 53.52%] [G loss: 0.705210]
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1267 [D loss: 0.692559, acc.: 50.59%] [G loss: 0.710128]
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1268 [D loss: 0.690849, acc.: 54.10%] [G loss: 0.716832]
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1269 [D loss: 0.688747, acc.: 53.91%] [G loss: 0.714981]
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1270 [D loss: 0.693046, acc.: 50.98%] [G loss: 0.718325]
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1271 [D loss: 0.694759, acc.: 49.80%] [G loss: 0.716437]
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1272 [D loss: 0.687782, acc.: 55.08%] [G loss: 0.713156]
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1273 [D loss: 0.684129, acc.: 57.42%] [G loss: 0.717159]
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1274 [D loss: 0.686144, acc.: 53.12%] [G loss: 0.720304]
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1275 [D loss: 0.693799, acc.: 48.63%] [G loss: 0.714028]
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1276 [D loss: 0.691996, acc.: 50.78%] [G loss: 0.714923]
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1277 [D loss: 0.692385, acc.: 51.76%] [G loss: 0.713234]
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1278 [D loss: 0.690466, acc.: 55.47%] [G loss: 0.702066]
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1279 [D loss: 0.694419, acc.: 50.00%] [G loss: 0.705833]
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1280 [D loss: 0.698218, acc.: 49.61%] [G loss: 0.709732]
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1281 [D loss: 0.690954, acc.: 52.15%] [G loss: 0.708803]
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1282 [D loss: 0.697259, acc.: 47.66%] [G loss: 0.714453]
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1283 [D loss: 0.689006, acc.: 54.49%] [G loss: 0.720285]
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1284 [D loss: 0.689357, acc.: 51.95%] [G loss: 0.716888]
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1285 [D loss: 0.691660, acc.: 52.93%] [G loss: 0.719357]
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1286 [D loss: 0.690992, acc.: 54.69%] [G loss: 0.722469]
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1287 [D loss: 0.687920, acc.: 55.47%] [G loss: 0.727370]
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1288 [D loss: 0.685781, acc.: 53.71%] [G loss: 0.723987]
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1289 [D loss: 0.686486, acc.: 56.45%] [G loss: 0.727074]
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1290 [D loss: 0.682183, acc.: 59.57%] [G loss: 0.719599]
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1291 [D loss: 0.688418, acc.: 53.52%] [G loss: 0.728193]
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1292 [D loss: 0.688838, acc.: 53.71%] [G loss: 0.725820]
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1293 [D loss: 0.682840, acc.: 57.62%] [G loss: 0.718003]
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1294 [D loss: 0.690857, acc.: 49.02%] [G loss: 0.704068]
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1295 [D loss: 0.693795, acc.: 51.17%] [G loss: 0.711714]
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1296 [D loss: 0.696988, acc.: 47.46%] [G loss: 0.707223]
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1297 [D loss: 0.698149, acc.: 48.05%] [G loss: 0.701904]
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1298 [D loss: 0.693591, acc.: 50.98%] [G loss: 0.708409]
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1299 [D loss: 0.693489, acc.: 51.56%] [G loss: 0.703874]
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1300 [D loss: 0.690830, acc.: 53.71%] [G loss: 0.715689]
1/1 [==============================] - 0s 16ms/step
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1301 [D loss: 0.692320, acc.: 49.80%] [G loss: 0.708790]
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1302 [D loss: 0.689758, acc.: 51.95%] [G loss: 0.709065]
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1303 [D loss: 0.688028, acc.: 54.49%] [G loss: 0.716312]
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1304 [D loss: 0.692236, acc.: 49.80%] [G loss: 0.715948]
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1305 [D loss: 0.694879, acc.: 50.20%] [G loss: 0.712565]
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1306 [D loss: 0.684683, acc.: 56.05%] [G loss: 0.711359]
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1307 [D loss: 0.696082, acc.: 47.07%] [G loss: 0.718525]
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1308 [D loss: 0.694748, acc.: 50.98%] [G loss: 0.716818]
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1309 [D loss: 0.690823, acc.: 52.54%] [G loss: 0.716195]
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1310 [D loss: 0.692979, acc.: 51.37%] [G loss: 0.720911]
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1311 [D loss: 0.692799, acc.: 48.24%] [G loss: 0.711092]
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1312 [D loss: 0.693029, acc.: 52.73%] [G loss: 0.717836]
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1313 [D loss: 0.687910, acc.: 55.08%] [G loss: 0.714199]
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1314 [D loss: 0.688737, acc.: 53.52%] [G loss: 0.714136]
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1315 [D loss: 0.691251, acc.: 54.49%] [G loss: 0.709787]
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1316 [D loss: 0.691431, acc.: 51.95%] [G loss: 0.725415]
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1317 [D loss: 0.691364, acc.: 51.17%] [G loss: 0.723219]
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1318 [D loss: 0.688789, acc.: 53.52%] [G loss: 0.720997]
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1319 [D loss: 0.685651, acc.: 54.88%] [G loss: 0.718599]
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1320 [D loss: 0.690588, acc.: 53.71%] [G loss: 0.727085]
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1321 [D loss: 0.684308, acc.: 58.40%] [G loss: 0.722988]
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1322 [D loss: 0.688244, acc.: 53.71%] [G loss: 0.719145]
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1323 [D loss: 0.684250, acc.: 55.86%] [G loss: 0.718951]
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1324 [D loss: 0.682013, acc.: 55.47%] [G loss: 0.716420]
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1325 [D loss: 0.693165, acc.: 53.12%] [G loss: 0.722934]
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1326 [D loss: 0.689621, acc.: 54.10%] [G loss: 0.709427]
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1327 [D loss: 0.696681, acc.: 52.15%] [G loss: 0.722602]
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1328 [D loss: 0.691491, acc.: 50.98%] [G loss: 0.710992]
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1329 [D loss: 0.688855, acc.: 52.73%] [G loss: 0.716588]
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1330 [D loss: 0.692500, acc.: 49.80%] [G loss: 0.710649]
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1331 [D loss: 0.690148, acc.: 51.37%] [G loss: 0.714497]
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1332 [D loss: 0.691640, acc.: 52.93%] [G loss: 0.718249]
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1333 [D loss: 0.691229, acc.: 50.59%] [G loss: 0.713735]
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1334 [D loss: 0.694773, acc.: 50.59%] [G loss: 0.706611]
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1335 [D loss: 0.689064, acc.: 52.15%] [G loss: 0.713557]
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1336 [D loss: 0.689433, acc.: 54.49%] [G loss: 0.705429]
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1337 [D loss: 0.690076, acc.: 51.95%] [G loss: 0.707135]
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1338 [D loss: 0.688668, acc.: 52.73%] [G loss: 0.708359]
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1339 [D loss: 0.690571, acc.: 53.52%] [G loss: 0.718274]
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1340 [D loss: 0.689306, acc.: 52.54%] [G loss: 0.708387]
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1341 [D loss: 0.691852, acc.: 50.59%] [G loss: 0.711154]
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1342 [D loss: 0.692620, acc.: 50.39%] [G loss: 0.711671]
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1343 [D loss: 0.694949, acc.: 52.15%] [G loss: 0.709505]
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1344 [D loss: 0.691355, acc.: 51.37%] [G loss: 0.704724]
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1345 [D loss: 0.687888, acc.: 55.27%] [G loss: 0.707196]
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1346 [D loss: 0.693844, acc.: 50.59%] [G loss: 0.703318]
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1347 [D loss: 0.691824, acc.: 52.34%] [G loss: 0.708849]
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1348 [D loss: 0.694749, acc.: 49.02%] [G loss: 0.710468]
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1349 [D loss: 0.694654, acc.: 47.27%] [G loss: 0.704855]
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1350 [D loss: 0.689412, acc.: 54.69%] [G loss: 0.701849]
1/1 [==============================] - 0s 15ms/step
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1351 [D loss: 0.691632, acc.: 51.95%] [G loss: 0.712807]
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1352 [D loss: 0.689767, acc.: 51.95%] [G loss: 0.713395]
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1353 [D loss: 0.688306, acc.: 54.69%] [G loss: 0.702545]
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1354 [D loss: 0.691622, acc.: 51.56%] [G loss: 0.716085]
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1355 [D loss: 0.686324, acc.: 56.05%] [G loss: 0.711173]
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1356 [D loss: 0.692401, acc.: 51.95%] [G loss: 0.717426]
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1357 [D loss: 0.689281, acc.: 55.08%] [G loss: 0.711826]
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1358 [D loss: 0.685443, acc.: 57.81%] [G loss: 0.715873]
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1359 [D loss: 0.688597, acc.: 57.81%] [G loss: 0.722923]
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1360 [D loss: 0.686294, acc.: 55.86%] [G loss: 0.707757]
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1361 [D loss: 0.692474, acc.: 52.34%] [G loss: 0.716209]
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1362 [D loss: 0.686305, acc.: 54.49%] [G loss: 0.718352]
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1363 [D loss: 0.686456, acc.: 56.45%] [G loss: 0.718428]
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1364 [D loss: 0.688061, acc.: 52.15%] [G loss: 0.719030]
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1365 [D loss: 0.685249, acc.: 55.66%] [G loss: 0.726203]
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1366 [D loss: 0.680616, acc.: 59.38%] [G loss: 0.712620]
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1367 [D loss: 0.685175, acc.: 55.27%] [G loss: 0.710770]
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1368 [D loss: 0.685494, acc.: 52.34%] [G loss: 0.710527]
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1369 [D loss: 0.689750, acc.: 52.54%] [G loss: 0.720134]
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1370 [D loss: 0.686895, acc.: 54.30%] [G loss: 0.709625]
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1371 [D loss: 0.691629, acc.: 52.73%] [G loss: 0.705171]
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1372 [D loss: 0.687302, acc.: 55.27%] [G loss: 0.709626]
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1373 [D loss: 0.694024, acc.: 50.20%] [G loss: 0.716807]
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1374 [D loss: 0.691458, acc.: 51.17%] [G loss: 0.720338]
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1375 [D loss: 0.691616, acc.: 53.32%] [G loss: 0.714952]
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1376 [D loss: 0.693683, acc.: 48.05%] [G loss: 0.716333]
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1377 [D loss: 0.688713, acc.: 54.30%] [G loss: 0.708552]
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1378 [D loss: 0.690795, acc.: 51.37%] [G loss: 0.716440]
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1379 [D loss: 0.693046, acc.: 52.93%] [G loss: 0.712379]
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1380 [D loss: 0.693509, acc.: 49.02%] [G loss: 0.714001]
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1381 [D loss: 0.691293, acc.: 54.69%] [G loss: 0.711596]
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1382 [D loss: 0.691912, acc.: 52.73%] [G loss: 0.712311]
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1383 [D loss: 0.688394, acc.: 54.69%] [G loss: 0.715845]
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1384 [D loss: 0.691174, acc.: 52.93%] [G loss: 0.714556]
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1385 [D loss: 0.692184, acc.: 52.15%] [G loss: 0.712862]
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1386 [D loss: 0.691907, acc.: 54.10%] [G loss: 0.709775]
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1387 [D loss: 0.686976, acc.: 53.12%] [G loss: 0.717067]
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1388 [D loss: 0.693086, acc.: 51.56%] [G loss: 0.717331]
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1389 [D loss: 0.693579, acc.: 50.78%] [G loss: 0.720786]
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1390 [D loss: 0.688368, acc.: 54.10%] [G loss: 0.722390]
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1391 [D loss: 0.686668, acc.: 58.01%] [G loss: 0.721500]
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1392 [D loss: 0.687462, acc.: 52.54%] [G loss: 0.713320]
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1393 [D loss: 0.687629, acc.: 52.34%] [G loss: 0.710186]
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1394 [D loss: 0.693155, acc.: 48.63%] [G loss: 0.710557]
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1395 [D loss: 0.686052, acc.: 54.30%] [G loss: 0.713570]
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1396 [D loss: 0.692523, acc.: 53.91%] [G loss: 0.722638]
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1397 [D loss: 0.690503, acc.: 54.30%] [G loss: 0.721937]
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1398 [D loss: 0.685596, acc.: 55.08%] [G loss: 0.713873]
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1399 [D loss: 0.688684, acc.: 51.76%] [G loss: 0.720771]
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1400 [D loss: 0.688641, acc.: 52.15%] [G loss: 0.718571]
1/1 [==============================] - 0s 16ms/step
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1401 [D loss: 0.687505, acc.: 53.91%] [G loss: 0.717726]
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1402 [D loss: 0.693400, acc.: 51.56%] [G loss: 0.718647]
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1403 [D loss: 0.691754, acc.: 51.95%] [G loss: 0.720892]
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1404 [D loss: 0.683960, acc.: 57.62%] [G loss: 0.709139]
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1405 [D loss: 0.690964, acc.: 52.73%] [G loss: 0.715842]
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1406 [D loss: 0.692084, acc.: 50.59%] [G loss: 0.723459]
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1407 [D loss: 0.684723, acc.: 55.86%] [G loss: 0.723681]
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1408 [D loss: 0.691742, acc.: 51.95%] [G loss: 0.713878]
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1409 [D loss: 0.692340, acc.: 53.71%] [G loss: 0.717025]
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1410 [D loss: 0.691537, acc.: 52.54%] [G loss: 0.709735]
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1411 [D loss: 0.692845, acc.: 51.37%] [G loss: 0.708476]
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1412 [D loss: 0.687985, acc.: 51.76%] [G loss: 0.714175]
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1413 [D loss: 0.693190, acc.: 49.61%] [G loss: 0.708658]
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1414 [D loss: 0.688048, acc.: 54.49%] [G loss: 0.717603]
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1415 [D loss: 0.692809, acc.: 51.37%] [G loss: 0.710962]
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1416 [D loss: 0.694250, acc.: 49.02%] [G loss: 0.703686]
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1417 [D loss: 0.689518, acc.: 54.88%] [G loss: 0.709255]
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1418 [D loss: 0.688696, acc.: 55.27%] [G loss: 0.710883]
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1419 [D loss: 0.691098, acc.: 52.54%] [G loss: 0.706970]
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1420 [D loss: 0.688962, acc.: 54.10%] [G loss: 0.711807]
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1421 [D loss: 0.683479, acc.: 56.25%] [G loss: 0.713217]
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1422 [D loss: 0.684088, acc.: 55.08%] [G loss: 0.718545]
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1423 [D loss: 0.691005, acc.: 50.59%] [G loss: 0.720952]
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1424 [D loss: 0.694407, acc.: 50.59%] [G loss: 0.714645]
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1425 [D loss: 0.688997, acc.: 56.05%] [G loss: 0.719835]
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1426 [D loss: 0.686645, acc.: 55.27%] [G loss: 0.721940]
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1427 [D loss: 0.684911, acc.: 58.20%] [G loss: 0.710729]
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1428 [D loss: 0.687225, acc.: 55.66%] [G loss: 0.710466]
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1429 [D loss: 0.696274, acc.: 48.63%] [G loss: 0.710601]
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1430 [D loss: 0.688201, acc.: 54.69%] [G loss: 0.708971]
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1431 [D loss: 0.690792, acc.: 51.76%] [G loss: 0.714095]
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1432 [D loss: 0.691959, acc.: 51.17%] [G loss: 0.712182]
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1433 [D loss: 0.688429, acc.: 54.10%] [G loss: 0.708855]
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1434 [D loss: 0.688935, acc.: 53.12%] [G loss: 0.715286]
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1435 [D loss: 0.687950, acc.: 56.05%] [G loss: 0.713431]
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1436 [D loss: 0.689760, acc.: 55.08%] [G loss: 0.715109]
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1437 [D loss: 0.698152, acc.: 48.24%] [G loss: 0.707588]
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1438 [D loss: 0.695388, acc.: 48.83%] [G loss: 0.710070]
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1439 [D loss: 0.694847, acc.: 52.34%] [G loss: 0.715151]
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1440 [D loss: 0.691411, acc.: 52.73%] [G loss: 0.716002]
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1441 [D loss: 0.688504, acc.: 55.47%] [G loss: 0.717213]
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1442 [D loss: 0.691184, acc.: 53.52%] [G loss: 0.715872]
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1443 [D loss: 0.689546, acc.: 53.91%] [G loss: 0.717365]
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1444 [D loss: 0.691991, acc.: 50.39%] [G loss: 0.716217]
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1445 [D loss: 0.688716, acc.: 55.27%] [G loss: 0.716092]
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1446 [D loss: 0.691338, acc.: 53.32%] [G loss: 0.711424]
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1447 [D loss: 0.691384, acc.: 51.56%] [G loss: 0.717125]
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1448 [D loss: 0.688152, acc.: 52.93%] [G loss: 0.716578]
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1449 [D loss: 0.686280, acc.: 56.25%] [G loss: 0.716599]
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1450 [D loss: 0.687075, acc.: 55.08%] [G loss: 0.717121]
1/1 [==============================] - 0s 16ms/step
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1451 [D loss: 0.692226, acc.: 51.37%] [G loss: 0.712538]
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1452 [D loss: 0.686014, acc.: 56.25%] [G loss: 0.715049]
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1453 [D loss: 0.691044, acc.: 52.15%] [G loss: 0.723669]
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1454 [D loss: 0.690564, acc.: 54.69%] [G loss: 0.714748]
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1455 [D loss: 0.691340, acc.: 53.32%] [G loss: 0.714842]
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1456 [D loss: 0.686501, acc.: 56.45%] [G loss: 0.715097]
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1457 [D loss: 0.694374, acc.: 51.17%] [G loss: 0.714779]
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1458 [D loss: 0.689996, acc.: 53.12%] [G loss: 0.710462]
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1459 [D loss: 0.692541, acc.: 52.15%] [G loss: 0.714323]
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1460 [D loss: 0.693683, acc.: 49.22%] [G loss: 0.711325]
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1461 [D loss: 0.695866, acc.: 50.20%] [G loss: 0.720786]
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1462 [D loss: 0.689237, acc.: 53.32%] [G loss: 0.711807]
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1463 [D loss: 0.689818, acc.: 52.73%] [G loss: 0.713543]
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1464 [D loss: 0.687265, acc.: 56.05%] [G loss: 0.719134]
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1465 [D loss: 0.686547, acc.: 56.05%] [G loss: 0.717706]
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1466 [D loss: 0.692511, acc.: 51.56%] [G loss: 0.718854]
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1467 [D loss: 0.692043, acc.: 52.15%] [G loss: 0.714001]
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1468 [D loss: 0.686431, acc.: 54.88%] [G loss: 0.712299]
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1469 [D loss: 0.686277, acc.: 57.42%] [G loss: 0.714609]
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1470 [D loss: 0.691147, acc.: 52.15%] [G loss: 0.714912]
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1471 [D loss: 0.686949, acc.: 57.03%] [G loss: 0.711698]
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1472 [D loss: 0.684829, acc.: 57.42%] [G loss: 0.713512]
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1473 [D loss: 0.690098, acc.: 52.54%] [G loss: 0.704132]
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1474 [D loss: 0.687593, acc.: 53.52%] [G loss: 0.713240]
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1475 [D loss: 0.690349, acc.: 51.76%] [G loss: 0.710657]
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1476 [D loss: 0.692872, acc.: 50.20%] [G loss: 0.711924]
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1477 [D loss: 0.692135, acc.: 50.98%] [G loss: 0.712181]
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1478 [D loss: 0.695420, acc.: 50.98%] [G loss: 0.707425]
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1479 [D loss: 0.690025, acc.: 52.15%] [G loss: 0.711196]
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1480 [D loss: 0.689426, acc.: 50.00%] [G loss: 0.706786]
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1481 [D loss: 0.690340, acc.: 51.37%] [G loss: 0.712761]
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1482 [D loss: 0.690947, acc.: 53.12%] [G loss: 0.706567]
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1483 [D loss: 0.692246, acc.: 53.32%] [G loss: 0.707371]
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1484 [D loss: 0.695121, acc.: 50.39%] [G loss: 0.708425]
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1485 [D loss: 0.693499, acc.: 51.56%] [G loss: 0.708690]
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1486 [D loss: 0.692680, acc.: 50.78%] [G loss: 0.707093]
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1487 [D loss: 0.689621, acc.: 54.30%] [G loss: 0.712391]
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1488 [D loss: 0.685474, acc.: 57.23%] [G loss: 0.720252]
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1489 [D loss: 0.693180, acc.: 48.63%] [G loss: 0.707788]
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1490 [D loss: 0.693407, acc.: 51.17%] [G loss: 0.708005]
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1491 [D loss: 0.691141, acc.: 50.59%] [G loss: 0.709611]
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1492 [D loss: 0.692335, acc.: 50.00%] [G loss: 0.715476]
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1493 [D loss: 0.694279, acc.: 52.54%] [G loss: 0.710498]
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1494 [D loss: 0.693337, acc.: 50.78%] [G loss: 0.716038]
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1495 [D loss: 0.688791, acc.: 53.32%] [G loss: 0.716891]
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1496 [D loss: 0.692676, acc.: 54.30%] [G loss: 0.712685]
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1497 [D loss: 0.688898, acc.: 56.25%] [G loss: 0.720809]
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1498 [D loss: 0.693272, acc.: 48.05%] [G loss: 0.716869]
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1499 [D loss: 0.685692, acc.: 55.86%] [G loss: 0.717600]
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1500 [D loss: 0.688366, acc.: 54.88%] [G loss: 0.718337]
1/1 [==============================] - 0s 16ms/step
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1501 [D loss: 0.687899, acc.: 53.91%] [G loss: 0.723210]
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1502 [D loss: 0.689801, acc.: 54.10%] [G loss: 0.712666]
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1503 [D loss: 0.689308, acc.: 53.71%] [G loss: 0.710873]
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1504 [D loss: 0.688371, acc.: 55.66%] [G loss: 0.713380]
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1505 [D loss: 0.684587, acc.: 57.23%] [G loss: 0.714182]
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1506 [D loss: 0.686519, acc.: 56.05%] [G loss: 0.723547]
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1507 [D loss: 0.689407, acc.: 52.93%] [G loss: 0.716022]
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1508 [D loss: 0.687126, acc.: 54.10%] [G loss: 0.712120]
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1509 [D loss: 0.687425, acc.: 54.88%] [G loss: 0.716094]
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1510 [D loss: 0.690654, acc.: 53.32%] [G loss: 0.713312]
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1511 [D loss: 0.689506, acc.: 54.49%] [G loss: 0.716889]
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1512 [D loss: 0.688403, acc.: 53.91%] [G loss: 0.709832]
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1513 [D loss: 0.689380, acc.: 52.54%] [G loss: 0.717932]
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1514 [D loss: 0.689409, acc.: 53.32%] [G loss: 0.710499]
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1515 [D loss: 0.693817, acc.: 50.98%] [G loss: 0.712818]
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1516 [D loss: 0.693389, acc.: 50.98%] [G loss: 0.714120]
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1517 [D loss: 0.690614, acc.: 52.54%] [G loss: 0.705497]
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1518 [D loss: 0.689759, acc.: 53.52%] [G loss: 0.712835]
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1519 [D loss: 0.695424, acc.: 49.61%] [G loss: 0.705335]
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1520 [D loss: 0.691411, acc.: 51.76%] [G loss: 0.710634]
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1521 [D loss: 0.691781, acc.: 52.73%] [G loss: 0.709508]
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1522 [D loss: 0.693139, acc.: 48.44%] [G loss: 0.709041]
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1523 [D loss: 0.693673, acc.: 49.22%] [G loss: 0.710691]
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1524 [D loss: 0.694584, acc.: 49.80%] [G loss: 0.711782]
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1525 [D loss: 0.692618, acc.: 51.17%] [G loss: 0.712011]
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1526 [D loss: 0.691011, acc.: 53.91%] [G loss: 0.716630]
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1527 [D loss: 0.688042, acc.: 54.49%] [G loss: 0.714890]
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1528 [D loss: 0.691793, acc.: 51.17%] [G loss: 0.716725]
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1529 [D loss: 0.691345, acc.: 52.15%] [G loss: 0.717723]
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1530 [D loss: 0.691078, acc.: 51.95%] [G loss: 0.720038]
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1531 [D loss: 0.693990, acc.: 49.80%] [G loss: 0.718377]
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1532 [D loss: 0.687315, acc.: 53.32%] [G loss: 0.720407]
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1533 [D loss: 0.693171, acc.: 49.80%] [G loss: 0.725351]
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1534 [D loss: 0.690723, acc.: 53.12%] [G loss: 0.719593]
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1535 [D loss: 0.688806, acc.: 54.30%] [G loss: 0.718990]
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1536 [D loss: 0.687200, acc.: 53.12%] [G loss: 0.726646]
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1537 [D loss: 0.693180, acc.: 49.22%] [G loss: 0.722356]
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1538 [D loss: 0.685116, acc.: 58.79%] [G loss: 0.724726]
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1539 [D loss: 0.683590, acc.: 57.62%] [G loss: 0.722240]
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1540 [D loss: 0.685027, acc.: 56.45%] [G loss: 0.721324]
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1541 [D loss: 0.686404, acc.: 54.49%] [G loss: 0.718803]
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1542 [D loss: 0.686175, acc.: 55.08%] [G loss: 0.716634]
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1543 [D loss: 0.691655, acc.: 51.37%] [G loss: 0.716765]
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1544 [D loss: 0.687026, acc.: 54.88%] [G loss: 0.711844]
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1545 [D loss: 0.689694, acc.: 55.86%] [G loss: 0.710856]
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1546 [D loss: 0.686334, acc.: 52.34%] [G loss: 0.713211]
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1547 [D loss: 0.690628, acc.: 50.59%] [G loss: 0.713086]
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1548 [D loss: 0.687876, acc.: 53.91%] [G loss: 0.713636]
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1549 [D loss: 0.692407, acc.: 51.76%] [G loss: 0.706811]
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1550 [D loss: 0.693826, acc.: 49.80%] [G loss: 0.705320]
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1551 [D loss: 0.691682, acc.: 50.39%] [G loss: 0.703052]
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1552 [D loss: 0.692301, acc.: 50.20%] [G loss: 0.702544]
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1553 [D loss: 0.688920, acc.: 53.91%] [G loss: 0.711285]
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1554 [D loss: 0.683434, acc.: 56.45%] [G loss: 0.710782]
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1555 [D loss: 0.688012, acc.: 55.47%] [G loss: 0.720413]
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1556 [D loss: 0.690282, acc.: 50.98%] [G loss: 0.714587]
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1557 [D loss: 0.686554, acc.: 56.64%] [G loss: 0.717540]
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1558 [D loss: 0.690463, acc.: 53.32%] [G loss: 0.710878]
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1559 [D loss: 0.692708, acc.: 50.39%] [G loss: 0.712148]
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1560 [D loss: 0.693675, acc.: 54.30%] [G loss: 0.710046]
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1561 [D loss: 0.698353, acc.: 48.24%] [G loss: 0.705248]
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1562 [D loss: 0.690416, acc.: 50.98%] [G loss: 0.709665]
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1563 [D loss: 0.688762, acc.: 52.93%] [G loss: 0.708640]
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1564 [D loss: 0.691903, acc.: 53.52%] [G loss: 0.704448]
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1565 [D loss: 0.691213, acc.: 54.10%] [G loss: 0.718497]
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1566 [D loss: 0.685798, acc.: 55.47%] [G loss: 0.713199]
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1567 [D loss: 0.693736, acc.: 50.59%] [G loss: 0.701168]
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1568 [D loss: 0.687599, acc.: 54.49%] [G loss: 0.710458]
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1569 [D loss: 0.693766, acc.: 51.37%] [G loss: 0.710649]
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1570 [D loss: 0.691761, acc.: 53.52%] [G loss: 0.703736]
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1571 [D loss: 0.691281, acc.: 54.30%] [G loss: 0.709295]
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1572 [D loss: 0.690120, acc.: 55.27%] [G loss: 0.712333]
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1573 [D loss: 0.686308, acc.: 53.71%] [G loss: 0.710605]
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1574 [D loss: 0.685353, acc.: 58.79%] [G loss: 0.709626]
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1575 [D loss: 0.688285, acc.: 52.93%] [G loss: 0.707637]
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1576 [D loss: 0.687334, acc.: 55.66%] [G loss: 0.707543]
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1577 [D loss: 0.684931, acc.: 54.10%] [G loss: 0.717030]
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1578 [D loss: 0.691848, acc.: 51.95%] [G loss: 0.713675]
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1579 [D loss: 0.693352, acc.: 52.34%] [G loss: 0.717546]
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1580 [D loss: 0.693523, acc.: 52.34%] [G loss: 0.711082]
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1581 [D loss: 0.689904, acc.: 53.52%] [G loss: 0.717272]
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1582 [D loss: 0.688311, acc.: 53.52%] [G loss: 0.722602]
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1583 [D loss: 0.692400, acc.: 50.39%] [G loss: 0.716273]
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1584 [D loss: 0.689482, acc.: 53.71%] [G loss: 0.717249]
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1585 [D loss: 0.686542, acc.: 57.42%] [G loss: 0.715660]
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1586 [D loss: 0.692251, acc.: 50.98%] [G loss: 0.718464]
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1587 [D loss: 0.689728, acc.: 52.93%] [G loss: 0.719619]
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1588 [D loss: 0.686881, acc.: 56.84%] [G loss: 0.715228]
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1589 [D loss: 0.686657, acc.: 55.47%] [G loss: 0.720806]
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1590 [D loss: 0.686146, acc.: 55.47%] [G loss: 0.721523]
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1591 [D loss: 0.687972, acc.: 54.30%] [G loss: 0.709814]
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1592 [D loss: 0.693850, acc.: 50.59%] [G loss: 0.712006]
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1593 [D loss: 0.697952, acc.: 48.05%] [G loss: 0.712220]
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1594 [D loss: 0.692672, acc.: 49.22%] [G loss: 0.710391]
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1595 [D loss: 0.689318, acc.: 54.10%] [G loss: 0.715372]
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1596 [D loss: 0.693514, acc.: 54.10%] [G loss: 0.715641]
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1597 [D loss: 0.688227, acc.: 54.10%] [G loss: 0.719668]
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1598 [D loss: 0.686474, acc.: 54.30%] [G loss: 0.717926]
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1599 [D loss: 0.688599, acc.: 54.30%] [G loss: 0.714819]
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1600 [D loss: 0.690883, acc.: 55.27%] [G loss: 0.714204]
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1601 [D loss: 0.691221, acc.: 53.71%] [G loss: 0.711108]
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1602 [D loss: 0.692216, acc.: 52.93%] [G loss: 0.717014]
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1603 [D loss: 0.690587, acc.: 52.15%] [G loss: 0.717970]
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1604 [D loss: 0.686750, acc.: 54.10%] [G loss: 0.710839]
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1605 [D loss: 0.690945, acc.: 54.88%] [G loss: 0.714097]
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1606 [D loss: 0.689211, acc.: 54.88%] [G loss: 0.717234]
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1607 [D loss: 0.688426, acc.: 53.91%] [G loss: 0.708940]
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1608 [D loss: 0.684085, acc.: 57.62%] [G loss: 0.713253]
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1609 [D loss: 0.688251, acc.: 55.66%] [G loss: 0.707378]
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1610 [D loss: 0.683998, acc.: 57.23%] [G loss: 0.704031]
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1611 [D loss: 0.687197, acc.: 57.23%] [G loss: 0.707729]
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1612 [D loss: 0.688623, acc.: 52.73%] [G loss: 0.700548]
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1613 [D loss: 0.691011, acc.: 52.93%] [G loss: 0.707711]
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1614 [D loss: 0.689893, acc.: 53.12%] [G loss: 0.701594]
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1615 [D loss: 0.700156, acc.: 46.29%] [G loss: 0.703580]
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1616 [D loss: 0.691524, acc.: 55.27%] [G loss: 0.703115]
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1617 [D loss: 0.693500, acc.: 50.39%] [G loss: 0.711204]
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1618 [D loss: 0.691521, acc.: 53.71%] [G loss: 0.712378]
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1619 [D loss: 0.690664, acc.: 53.12%] [G loss: 0.709777]
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1620 [D loss: 0.689510, acc.: 52.93%] [G loss: 0.707736]
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1621 [D loss: 0.692430, acc.: 51.95%] [G loss: 0.713046]
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1622 [D loss: 0.691690, acc.: 50.39%] [G loss: 0.711948]
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1623 [D loss: 0.693362, acc.: 51.95%] [G loss: 0.715983]
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1624 [D loss: 0.690150, acc.: 52.54%] [G loss: 0.717447]
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1625 [D loss: 0.693368, acc.: 48.05%] [G loss: 0.721846]
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1626 [D loss: 0.694907, acc.: 49.61%] [G loss: 0.719855]
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1627 [D loss: 0.692118, acc.: 50.98%] [G loss: 0.725495]
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1628 [D loss: 0.685129, acc.: 54.69%] [G loss: 0.723132]
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1629 [D loss: 0.690262, acc.: 52.54%] [G loss: 0.724809]
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1630 [D loss: 0.691033, acc.: 54.88%] [G loss: 0.720134]
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1631 [D loss: 0.689298, acc.: 55.08%] [G loss: 0.720392]
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1632 [D loss: 0.686417, acc.: 54.88%] [G loss: 0.716601]
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1633 [D loss: 0.684460, acc.: 57.03%] [G loss: 0.720483]
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1634 [D loss: 0.684141, acc.: 54.69%] [G loss: 0.714988]
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1635 [D loss: 0.685650, acc.: 56.25%] [G loss: 0.704630]
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1636 [D loss: 0.698462, acc.: 50.98%] [G loss: 0.716079]
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1637 [D loss: 0.691260, acc.: 50.78%] [G loss: 0.711139]
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1638 [D loss: 0.686781, acc.: 52.15%] [G loss: 0.713298]
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1639 [D loss: 0.686453, acc.: 54.10%] [G loss: 0.714346]
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1640 [D loss: 0.690376, acc.: 52.54%] [G loss: 0.714421]
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1641 [D loss: 0.692418, acc.: 48.83%] [G loss: 0.709550]
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1642 [D loss: 0.689874, acc.: 51.37%] [G loss: 0.710720]
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1643 [D loss: 0.685956, acc.: 54.69%] [G loss: 0.712743]
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1644 [D loss: 0.690453, acc.: 51.17%] [G loss: 0.718030]
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1645 [D loss: 0.690166, acc.: 50.78%] [G loss: 0.707336]
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1646 [D loss: 0.690881, acc.: 52.73%] [G loss: 0.710092]
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1647 [D loss: 0.695501, acc.: 51.76%] [G loss: 0.705959]
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1648 [D loss: 0.687120, acc.: 53.71%] [G loss: 0.717180]
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1649 [D loss: 0.688846, acc.: 55.86%] [G loss: 0.714110]
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1650 [D loss: 0.688421, acc.: 52.15%] [G loss: 0.713565]
1/1 [==============================] - 0s 16ms/step
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1651 [D loss: 0.690669, acc.: 52.15%] [G loss: 0.712623]
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1652 [D loss: 0.692286, acc.: 53.91%] [G loss: 0.719420]
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1653 [D loss: 0.693160, acc.: 50.98%] [G loss: 0.714730]
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1654 [D loss: 0.687424, acc.: 55.66%] [G loss: 0.719400]
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1655 [D loss: 0.685971, acc.: 56.84%] [G loss: 0.715972]
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1656 [D loss: 0.691971, acc.: 53.71%] [G loss: 0.717258]
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1657 [D loss: 0.685939, acc.: 58.01%] [G loss: 0.713188]
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1658 [D loss: 0.688690, acc.: 52.15%] [G loss: 0.716140]
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1659 [D loss: 0.685982, acc.: 57.62%] [G loss: 0.722485]
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1660 [D loss: 0.685891, acc.: 56.25%] [G loss: 0.722881]
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1661 [D loss: 0.687054, acc.: 54.30%] [G loss: 0.716869]
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1662 [D loss: 0.689937, acc.: 51.95%] [G loss: 0.711292]
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1663 [D loss: 0.689619, acc.: 53.32%] [G loss: 0.715253]
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1664 [D loss: 0.687413, acc.: 54.69%] [G loss: 0.715484]
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1665 [D loss: 0.688038, acc.: 56.84%] [G loss: 0.718175]
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1666 [D loss: 0.691859, acc.: 52.34%] [G loss: 0.718758]
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1667 [D loss: 0.689059, acc.: 55.47%] [G loss: 0.711963]
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1668 [D loss: 0.689777, acc.: 53.32%] [G loss: 0.712783]
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1669 [D loss: 0.692557, acc.: 49.22%] [G loss: 0.708382]
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1670 [D loss: 0.692871, acc.: 53.32%] [G loss: 0.715616]
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1671 [D loss: 0.689391, acc.: 51.95%] [G loss: 0.719223]
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1672 [D loss: 0.691831, acc.: 52.54%] [G loss: 0.714951]
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1673 [D loss: 0.692684, acc.: 50.20%] [G loss: 0.718244]
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1674 [D loss: 0.692171, acc.: 51.37%] [G loss: 0.720385]
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1675 [D loss: 0.688376, acc.: 53.91%] [G loss: 0.713192]
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1676 [D loss: 0.689761, acc.: 53.91%] [G loss: 0.717691]
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1677 [D loss: 0.689741, acc.: 53.52%] [G loss: 0.717361]
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1678 [D loss: 0.692042, acc.: 53.32%] [G loss: 0.711711]
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1679 [D loss: 0.684932, acc.: 56.05%] [G loss: 0.715735]
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1680 [D loss: 0.686410, acc.: 55.86%] [G loss: 0.724408]
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1681 [D loss: 0.687107, acc.: 57.23%] [G loss: 0.720494]
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1682 [D loss: 0.685709, acc.: 54.88%] [G loss: 0.715769]
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1683 [D loss: 0.689394, acc.: 54.10%] [G loss: 0.719296]
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1684 [D loss: 0.685551, acc.: 57.62%] [G loss: 0.716594]
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1685 [D loss: 0.686785, acc.: 55.08%] [G loss: 0.705600]
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1686 [D loss: 0.684203, acc.: 58.40%] [G loss: 0.710947]
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1687 [D loss: 0.688814, acc.: 54.49%] [G loss: 0.714401]
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1688 [D loss: 0.684928, acc.: 55.66%] [G loss: 0.710007]
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1689 [D loss: 0.690543, acc.: 51.95%] [G loss: 0.708173]
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1690 [D loss: 0.685548, acc.: 54.49%] [G loss: 0.709288]
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1691 [D loss: 0.682012, acc.: 58.98%] [G loss: 0.709012]
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1692 [D loss: 0.692697, acc.: 50.59%] [G loss: 0.712754]
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1693 [D loss: 0.685648, acc.: 55.86%] [G loss: 0.703422]
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1694 [D loss: 0.684322, acc.: 56.64%] [G loss: 0.700965]
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1695 [D loss: 0.693742, acc.: 52.54%] [G loss: 0.705480]
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1696 [D loss: 0.686682, acc.: 55.86%] [G loss: 0.698959]
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1697 [D loss: 0.691723, acc.: 54.30%] [G loss: 0.701783]
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1698 [D loss: 0.691121, acc.: 53.91%] [G loss: 0.697650]
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1699 [D loss: 0.690314, acc.: 51.95%] [G loss: 0.701959]
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1700 [D loss: 0.693010, acc.: 53.71%] [G loss: 0.705387]
1/1 [==============================] - 0s 16ms/step
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1701 [D loss: 0.689277, acc.: 54.10%] [G loss: 0.703310]
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1702 [D loss: 0.686427, acc.: 55.27%] [G loss: 0.702047]
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1703 [D loss: 0.692182, acc.: 50.20%] [G loss: 0.708092]
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1704 [D loss: 0.690874, acc.: 51.76%] [G loss: 0.710312]
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1705 [D loss: 0.689659, acc.: 55.47%] [G loss: 0.713706]
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1706 [D loss: 0.690545, acc.: 51.76%] [G loss: 0.719711]
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1707 [D loss: 0.693018, acc.: 54.49%] [G loss: 0.708874]
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1708 [D loss: 0.686846, acc.: 56.05%] [G loss: 0.721871]
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1709 [D loss: 0.691243, acc.: 52.93%] [G loss: 0.717600]
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1710 [D loss: 0.687427, acc.: 53.12%] [G loss: 0.716175]
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1711 [D loss: 0.692905, acc.: 51.37%] [G loss: 0.716224]
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1712 [D loss: 0.688693, acc.: 53.71%] [G loss: 0.716128]
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1713 [D loss: 0.689774, acc.: 55.47%] [G loss: 0.720483]
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1714 [D loss: 0.683858, acc.: 57.23%] [G loss: 0.715587]
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1715 [D loss: 0.689953, acc.: 52.93%] [G loss: 0.723348]
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1716 [D loss: 0.685886, acc.: 58.59%] [G loss: 0.719358]
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1717 [D loss: 0.693967, acc.: 50.59%] [G loss: 0.719554]
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1718 [D loss: 0.685938, acc.: 57.23%] [G loss: 0.713897]
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1719 [D loss: 0.691568, acc.: 52.34%] [G loss: 0.720333]
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1720 [D loss: 0.689017, acc.: 53.71%] [G loss: 0.715556]
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1721 [D loss: 0.689506, acc.: 52.93%] [G loss: 0.714627]
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1722 [D loss: 0.688921, acc.: 56.05%] [G loss: 0.720643]
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1723 [D loss: 0.687034, acc.: 54.30%] [G loss: 0.716674]
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1724 [D loss: 0.690340, acc.: 49.80%] [G loss: 0.715807]
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1725 [D loss: 0.687054, acc.: 54.10%] [G loss: 0.719898]
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1726 [D loss: 0.688877, acc.: 53.91%] [G loss: 0.714000]
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1727 [D loss: 0.682985, acc.: 56.84%] [G loss: 0.717259]
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1728 [D loss: 0.689940, acc.: 54.30%] [G loss: 0.711462]
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1729 [D loss: 0.687879, acc.: 53.71%] [G loss: 0.715504]
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1730 [D loss: 0.692394, acc.: 53.52%] [G loss: 0.713271]
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1731 [D loss: 0.691313, acc.: 54.49%] [G loss: 0.710205]
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1732 [D loss: 0.697050, acc.: 48.05%] [G loss: 0.718651]
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1733 [D loss: 0.692010, acc.: 52.15%] [G loss: 0.719545]
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1734 [D loss: 0.688668, acc.: 55.08%] [G loss: 0.711668]
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1735 [D loss: 0.689202, acc.: 52.93%] [G loss: 0.716735]
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1736 [D loss: 0.687283, acc.: 54.10%] [G loss: 0.712530]
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1737 [D loss: 0.690805, acc.: 52.73%] [G loss: 0.712131]
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1738 [D loss: 0.690938, acc.: 53.71%] [G loss: 0.714615]
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1739 [D loss: 0.690714, acc.: 51.17%] [G loss: 0.714163]
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1740 [D loss: 0.689596, acc.: 54.30%] [G loss: 0.717400]
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1741 [D loss: 0.691616, acc.: 51.56%] [G loss: 0.711631]
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1742 [D loss: 0.683627, acc.: 56.84%] [G loss: 0.713260]
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1743 [D loss: 0.687253, acc.: 54.88%] [G loss: 0.711242]
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1744 [D loss: 0.690997, acc.: 52.73%] [G loss: 0.711735]
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1745 [D loss: 0.690679, acc.: 51.95%] [G loss: 0.713552]
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1746 [D loss: 0.681137, acc.: 57.62%] [G loss: 0.714613]
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1747 [D loss: 0.678067, acc.: 58.98%] [G loss: 0.714295]
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1748 [D loss: 0.686146, acc.: 56.05%] [G loss: 0.714927]
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1749 [D loss: 0.686968, acc.: 55.66%] [G loss: 0.712915]
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1750 [D loss: 0.687550, acc.: 54.49%] [G loss: 0.715466]
1/1 [==============================] - 0s 16ms/step
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1751 [D loss: 0.687104, acc.: 54.10%] [G loss: 0.705239]
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1752 [D loss: 0.694133, acc.: 49.80%] [G loss: 0.722012]
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1753 [D loss: 0.692599, acc.: 53.32%] [G loss: 0.717170]
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1754 [D loss: 0.692305, acc.: 52.73%] [G loss: 0.713029]
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1755 [D loss: 0.684117, acc.: 55.86%] [G loss: 0.714356]
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1756 [D loss: 0.695761, acc.: 50.00%] [G loss: 0.716496]
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1757 [D loss: 0.688331, acc.: 54.30%] [G loss: 0.718507]
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1758 [D loss: 0.687414, acc.: 52.73%] [G loss: 0.717204]
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1759 [D loss: 0.688804, acc.: 53.91%] [G loss: 0.719510]
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1760 [D loss: 0.693328, acc.: 47.46%] [G loss: 0.722812]
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1761 [D loss: 0.692859, acc.: 53.12%] [G loss: 0.724460]
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1762 [D loss: 0.687764, acc.: 54.30%] [G loss: 0.731104]
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1763 [D loss: 0.688858, acc.: 54.10%] [G loss: 0.720701]
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1764 [D loss: 0.684234, acc.: 55.66%] [G loss: 0.716336]
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1765 [D loss: 0.690737, acc.: 50.59%] [G loss: 0.719238]
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1766 [D loss: 0.686154, acc.: 54.10%] [G loss: 0.717925]
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1767 [D loss: 0.691266, acc.: 50.98%] [G loss: 0.710126]
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1768 [D loss: 0.685686, acc.: 53.91%] [G loss: 0.708049]
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1769 [D loss: 0.689922, acc.: 52.34%] [G loss: 0.713764]
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1770 [D loss: 0.685799, acc.: 57.23%] [G loss: 0.706845]
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1771 [D loss: 0.688712, acc.: 54.49%] [G loss: 0.717425]
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1772 [D loss: 0.687394, acc.: 53.32%] [G loss: 0.712156]
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1773 [D loss: 0.688553, acc.: 54.88%] [G loss: 0.707271]
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1774 [D loss: 0.688458, acc.: 54.49%] [G loss: 0.717523]
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1775 [D loss: 0.686866, acc.: 58.20%] [G loss: 0.717518]
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1776 [D loss: 0.688588, acc.: 55.08%] [G loss: 0.712619]
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1777 [D loss: 0.685606, acc.: 58.40%] [G loss: 0.710305]
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1778 [D loss: 0.681758, acc.: 59.57%] [G loss: 0.709314]
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1779 [D loss: 0.687286, acc.: 53.71%] [G loss: 0.704261]
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1780 [D loss: 0.695188, acc.: 50.59%] [G loss: 0.710858]
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1781 [D loss: 0.690434, acc.: 52.73%] [G loss: 0.708438]
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1782 [D loss: 0.686393, acc.: 55.08%] [G loss: 0.713033]
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1783 [D loss: 0.684117, acc.: 57.62%] [G loss: 0.706996]
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1784 [D loss: 0.687608, acc.: 54.69%] [G loss: 0.724964]
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1785 [D loss: 0.688896, acc.: 53.52%] [G loss: 0.706091]
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1786 [D loss: 0.689766, acc.: 50.98%] [G loss: 0.713688]
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1787 [D loss: 0.697942, acc.: 46.48%] [G loss: 0.712547]
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1788 [D loss: 0.687773, acc.: 52.93%] [G loss: 0.712886]
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1789 [D loss: 0.693378, acc.: 50.98%] [G loss: 0.715524]
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1790 [D loss: 0.688602, acc.: 53.32%] [G loss: 0.720090]
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1791 [D loss: 0.683253, acc.: 57.03%] [G loss: 0.720249]
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1792 [D loss: 0.685441, acc.: 54.10%] [G loss: 0.725967]
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1793 [D loss: 0.688147, acc.: 55.27%] [G loss: 0.725407]
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1794 [D loss: 0.690733, acc.: 55.47%] [G loss: 0.720345]
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1795 [D loss: 0.687118, acc.: 55.08%] [G loss: 0.717219]
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1796 [D loss: 0.682665, acc.: 56.45%] [G loss: 0.713757]
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1797 [D loss: 0.683503, acc.: 58.01%] [G loss: 0.718446]
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1798 [D loss: 0.688861, acc.: 52.93%] [G loss: 0.714789]
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1799 [D loss: 0.692600, acc.: 53.12%] [G loss: 0.715541]
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1800 [D loss: 0.690624, acc.: 53.32%] [G loss: 0.715063]
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1801 [D loss: 0.692777, acc.: 53.71%] [G loss: 0.723937]
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1802 [D loss: 0.690946, acc.: 51.76%] [G loss: 0.721288]
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1803 [D loss: 0.691973, acc.: 50.00%] [G loss: 0.721586]
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1804 [D loss: 0.681209, acc.: 57.23%] [G loss: 0.719130]
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1805 [D loss: 0.684595, acc.: 56.25%] [G loss: 0.728442]
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1806 [D loss: 0.685115, acc.: 55.08%] [G loss: 0.721685]
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1807 [D loss: 0.684687, acc.: 54.30%] [G loss: 0.722713]
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1808 [D loss: 0.690184, acc.: 52.54%] [G loss: 0.717647]
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1809 [D loss: 0.697098, acc.: 48.83%] [G loss: 0.716002]
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1810 [D loss: 0.691846, acc.: 51.17%] [G loss: 0.711716]
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1811 [D loss: 0.683109, acc.: 57.03%] [G loss: 0.706696]
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1812 [D loss: 0.689878, acc.: 51.56%] [G loss: 0.721420]
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1813 [D loss: 0.694330, acc.: 49.80%] [G loss: 0.716642]
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1814 [D loss: 0.696024, acc.: 49.22%] [G loss: 0.706159]
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1815 [D loss: 0.693617, acc.: 52.15%] [G loss: 0.713653]
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1816 [D loss: 0.687590, acc.: 54.30%] [G loss: 0.712974]
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1817 [D loss: 0.687761, acc.: 54.69%] [G loss: 0.706653]
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1818 [D loss: 0.686794, acc.: 53.52%] [G loss: 0.717606]
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1819 [D loss: 0.679473, acc.: 58.01%] [G loss: 0.719024]
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1820 [D loss: 0.689471, acc.: 53.12%] [G loss: 0.712461]
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1821 [D loss: 0.694004, acc.: 51.37%] [G loss: 0.722584]
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1822 [D loss: 0.687230, acc.: 54.88%] [G loss: 0.718136]
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1823 [D loss: 0.686505, acc.: 54.88%] [G loss: 0.719310]
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1824 [D loss: 0.688553, acc.: 53.32%] [G loss: 0.719611]
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1825 [D loss: 0.689702, acc.: 52.54%] [G loss: 0.713183]
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1826 [D loss: 0.685972, acc.: 55.27%] [G loss: 0.715105]
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1827 [D loss: 0.685230, acc.: 56.25%] [G loss: 0.716317]
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1828 [D loss: 0.689242, acc.: 53.32%] [G loss: 0.717704]
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1829 [D loss: 0.682946, acc.: 58.59%] [G loss: 0.721364]
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1830 [D loss: 0.687338, acc.: 55.08%] [G loss: 0.721234]
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1831 [D loss: 0.684157, acc.: 55.66%] [G loss: 0.715187]
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1832 [D loss: 0.688254, acc.: 52.93%] [G loss: 0.710276]
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1833 [D loss: 0.686347, acc.: 57.03%] [G loss: 0.725231]
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1834 [D loss: 0.687009, acc.: 55.08%] [G loss: 0.718371]
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1835 [D loss: 0.685101, acc.: 54.49%] [G loss: 0.719167]
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1836 [D loss: 0.691799, acc.: 52.34%] [G loss: 0.723077]
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1837 [D loss: 0.684723, acc.: 53.52%] [G loss: 0.715931]
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1838 [D loss: 0.688921, acc.: 52.73%] [G loss: 0.715937]
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1839 [D loss: 0.690113, acc.: 52.15%] [G loss: 0.718923]
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1840 [D loss: 0.689108, acc.: 54.69%] [G loss: 0.713271]
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1841 [D loss: 0.690512, acc.: 51.95%] [G loss: 0.707873]
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1842 [D loss: 0.690424, acc.: 52.15%] [G loss: 0.710517]
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1843 [D loss: 0.695416, acc.: 49.80%] [G loss: 0.702067]
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1844 [D loss: 0.695450, acc.: 47.07%] [G loss: 0.710108]
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1845 [D loss: 0.690139, acc.: 51.76%] [G loss: 0.713264]
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1846 [D loss: 0.686449, acc.: 55.86%] [G loss: 0.710761]
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1847 [D loss: 0.694446, acc.: 50.20%] [G loss: 0.704810]
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1848 [D loss: 0.688206, acc.: 52.93%] [G loss: 0.711128]
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1849 [D loss: 0.691879, acc.: 51.76%] [G loss: 0.711108]
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1850 [D loss: 0.694111, acc.: 51.37%] [G loss: 0.712276]
1/1 [==============================] - 0s 16ms/step
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1851 [D loss: 0.688626, acc.: 56.05%] [G loss: 0.713821]
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1852 [D loss: 0.693037, acc.: 50.59%] [G loss: 0.718171]
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1853 [D loss: 0.687339, acc.: 54.49%] [G loss: 0.710915]
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1854 [D loss: 0.686728, acc.: 53.12%] [G loss: 0.717909]
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1855 [D loss: 0.688631, acc.: 57.23%] [G loss: 0.711289]
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1856 [D loss: 0.681881, acc.: 59.57%] [G loss: 0.711092]
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1857 [D loss: 0.681291, acc.: 56.64%] [G loss: 0.715680]
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1858 [D loss: 0.686281, acc.: 58.20%] [G loss: 0.703730]
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1859 [D loss: 0.685566, acc.: 55.08%] [G loss: 0.716736]
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1860 [D loss: 0.687138, acc.: 56.45%] [G loss: 0.714116]
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1861 [D loss: 0.683953, acc.: 56.25%] [G loss: 0.710303]
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1862 [D loss: 0.683842, acc.: 57.62%] [G loss: 0.709937]
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1863 [D loss: 0.684415, acc.: 56.25%] [G loss: 0.706324]
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1864 [D loss: 0.688134, acc.: 54.49%] [G loss: 0.717368]
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1865 [D loss: 0.684440, acc.: 55.66%] [G loss: 0.711834]
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1866 [D loss: 0.695250, acc.: 53.12%] [G loss: 0.705217]
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1867 [D loss: 0.692913, acc.: 51.56%] [G loss: 0.703950]
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1868 [D loss: 0.696573, acc.: 51.17%] [G loss: 0.709109]
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1869 [D loss: 0.693361, acc.: 49.02%] [G loss: 0.708235]
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1870 [D loss: 0.692031, acc.: 51.37%] [G loss: 0.714253]
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1871 [D loss: 0.692989, acc.: 50.39%] [G loss: 0.711672]
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1872 [D loss: 0.685479, acc.: 56.25%] [G loss: 0.718263]
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1873 [D loss: 0.689419, acc.: 53.91%] [G loss: 0.721244]
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1874 [D loss: 0.685043, acc.: 52.73%] [G loss: 0.713467]
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1875 [D loss: 0.695715, acc.: 50.20%] [G loss: 0.719449]
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1876 [D loss: 0.688965, acc.: 56.45%] [G loss: 0.715387]
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1877 [D loss: 0.690110, acc.: 50.59%] [G loss: 0.718664]
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1878 [D loss: 0.692023, acc.: 52.54%] [G loss: 0.721614]
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1879 [D loss: 0.694537, acc.: 50.00%] [G loss: 0.712614]
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1880 [D loss: 0.686361, acc.: 54.88%] [G loss: 0.719375]
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1881 [D loss: 0.685228, acc.: 54.10%] [G loss: 0.715765]
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1882 [D loss: 0.683399, acc.: 57.81%] [G loss: 0.721619]
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1883 [D loss: 0.691910, acc.: 49.22%] [G loss: 0.719024]
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1884 [D loss: 0.690667, acc.: 53.91%] [G loss: 0.717097]
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1885 [D loss: 0.686129, acc.: 55.27%] [G loss: 0.721984]
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1886 [D loss: 0.682055, acc.: 58.01%] [G loss: 0.714260]
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1887 [D loss: 0.686298, acc.: 52.93%] [G loss: 0.713994]
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1888 [D loss: 0.690062, acc.: 52.34%] [G loss: 0.708881]
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1889 [D loss: 0.690200, acc.: 54.30%] [G loss: 0.707310]
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1890 [D loss: 0.694270, acc.: 48.05%] [G loss: 0.711275]
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1891 [D loss: 0.685120, acc.: 57.03%] [G loss: 0.718472]
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1892 [D loss: 0.687533, acc.: 54.30%] [G loss: 0.731360]
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1893 [D loss: 0.688795, acc.: 54.49%] [G loss: 0.723187]
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1894 [D loss: 0.683740, acc.: 55.66%] [G loss: 0.725416]
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1895 [D loss: 0.680575, acc.: 58.59%] [G loss: 0.719553]
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1896 [D loss: 0.684157, acc.: 56.45%] [G loss: 0.713858]
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1897 [D loss: 0.695071, acc.: 49.02%] [G loss: 0.712904]
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1898 [D loss: 0.687680, acc.: 54.88%] [G loss: 0.707320]
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1899 [D loss: 0.687160, acc.: 56.84%] [G loss: 0.709237]
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1900 [D loss: 0.691996, acc.: 52.15%] [G loss: 0.708333]
1/1 [==============================] - 0s 16ms/step
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1901 [D loss: 0.696656, acc.: 46.88%] [G loss: 0.709291]
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1902 [D loss: 0.686678, acc.: 55.27%] [G loss: 0.698954]
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1903 [D loss: 0.686410, acc.: 54.69%] [G loss: 0.709614]
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1904 [D loss: 0.685342, acc.: 56.25%] [G loss: 0.702653]
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1905 [D loss: 0.686421, acc.: 55.47%] [G loss: 0.699709]
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1906 [D loss: 0.692771, acc.: 54.30%] [G loss: 0.708934]
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1907 [D loss: 0.690432, acc.: 51.95%] [G loss: 0.707839]
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1908 [D loss: 0.694692, acc.: 52.15%] [G loss: 0.713354]
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1909 [D loss: 0.689665, acc.: 55.08%] [G loss: 0.713327]
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1910 [D loss: 0.687164, acc.: 53.52%] [G loss: 0.715611]
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1911 [D loss: 0.688816, acc.: 54.30%] [G loss: 0.716629]
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1912 [D loss: 0.686570, acc.: 55.66%] [G loss: 0.721594]
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1913 [D loss: 0.689531, acc.: 54.10%] [G loss: 0.721680]
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1914 [D loss: 0.690888, acc.: 52.15%] [G loss: 0.720978]
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1915 [D loss: 0.689643, acc.: 53.32%] [G loss: 0.721138]
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1916 [D loss: 0.686880, acc.: 57.03%] [G loss: 0.708551]
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1917 [D loss: 0.684188, acc.: 56.25%] [G loss: 0.717488]
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1918 [D loss: 0.686272, acc.: 56.84%] [G loss: 0.712090]
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1919 [D loss: 0.687640, acc.: 55.27%] [G loss: 0.720787]
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1920 [D loss: 0.683275, acc.: 58.20%] [G loss: 0.715683]
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1921 [D loss: 0.687888, acc.: 53.71%] [G loss: 0.724365]
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1922 [D loss: 0.683981, acc.: 55.08%] [G loss: 0.717558]
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1923 [D loss: 0.679807, acc.: 58.01%] [G loss: 0.716419]
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1924 [D loss: 0.688090, acc.: 51.17%] [G loss: 0.715221]
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1925 [D loss: 0.694103, acc.: 50.59%] [G loss: 0.726045]
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1926 [D loss: 0.689719, acc.: 53.71%] [G loss: 0.715307]
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1927 [D loss: 0.689121, acc.: 52.93%] [G loss: 0.704004]
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1928 [D loss: 0.688801, acc.: 55.47%] [G loss: 0.712120]
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1929 [D loss: 0.696335, acc.: 49.22%] [G loss: 0.715236]
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1930 [D loss: 0.691572, acc.: 53.71%] [G loss: 0.717319]
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1931 [D loss: 0.684362, acc.: 56.84%] [G loss: 0.716476]
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1932 [D loss: 0.684901, acc.: 55.86%] [G loss: 0.725667]
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1933 [D loss: 0.687286, acc.: 56.05%] [G loss: 0.716972]
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1934 [D loss: 0.684150, acc.: 55.47%] [G loss: 0.719952]
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1935 [D loss: 0.688620, acc.: 50.20%] [G loss: 0.718380]
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1936 [D loss: 0.685547, acc.: 55.08%] [G loss: 0.707658]
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1937 [D loss: 0.686828, acc.: 56.64%] [G loss: 0.715554]
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1938 [D loss: 0.688956, acc.: 54.88%] [G loss: 0.719460]
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1939 [D loss: 0.687286, acc.: 54.88%] [G loss: 0.712365]
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1940 [D loss: 0.686621, acc.: 56.45%] [G loss: 0.711888]
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1941 [D loss: 0.685091, acc.: 55.47%] [G loss: 0.709657]
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1942 [D loss: 0.687269, acc.: 52.34%] [G loss: 0.711564]
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1943 [D loss: 0.687249, acc.: 54.49%] [G loss: 0.706436]
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1944 [D loss: 0.692302, acc.: 51.95%] [G loss: 0.707404]
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1945 [D loss: 0.695376, acc.: 48.63%] [G loss: 0.708109]
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1946 [D loss: 0.684829, acc.: 53.71%] [G loss: 0.710176]
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1947 [D loss: 0.692844, acc.: 51.37%] [G loss: 0.711708]
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1948 [D loss: 0.693441, acc.: 53.12%] [G loss: 0.707619]
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1949 [D loss: 0.691258, acc.: 51.56%] [G loss: 0.704931]
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1950 [D loss: 0.691899, acc.: 51.76%] [G loss: 0.702076]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
1951 [D loss: 0.682609, acc.: 57.03%] [G loss: 0.702751]
8/8 [==============================] - 0s 2ms/step
1952 [D loss: 0.688971, acc.: 53.12%] [G loss: 0.715750]
8/8 [==============================] - 0s 2ms/step
1953 [D loss: 0.687433, acc.: 52.93%] [G loss: 0.705999]
8/8 [==============================] - 0s 2ms/step
1954 [D loss: 0.689631, acc.: 54.69%] [G loss: 0.708594]
8/8 [==============================] - 0s 2ms/step
1955 [D loss: 0.684997, acc.: 58.01%] [G loss: 0.710676]
8/8 [==============================] - 0s 2ms/step
1956 [D loss: 0.689766, acc.: 53.52%] [G loss: 0.709685]
8/8 [==============================] - 0s 2ms/step
1957 [D loss: 0.688834, acc.: 53.71%] [G loss: 0.716848]
8/8 [==============================] - 0s 2ms/step
1958 [D loss: 0.684046, acc.: 57.81%] [G loss: 0.717907]
8/8 [==============================] - 0s 2ms/step
1959 [D loss: 0.689672, acc.: 53.52%] [G loss: 0.723608]
8/8 [==============================] - 0s 2ms/step
1960 [D loss: 0.688171, acc.: 55.27%] [G loss: 0.719851]
8/8 [==============================] - 0s 2ms/step
1961 [D loss: 0.692732, acc.: 52.73%] [G loss: 0.712583]
8/8 [==============================] - 0s 2ms/step
1962 [D loss: 0.687019, acc.: 56.84%] [G loss: 0.719629]
8/8 [==============================] - 0s 2ms/step
1963 [D loss: 0.690156, acc.: 53.52%] [G loss: 0.718200]
8/8 [==============================] - 0s 2ms/step
1964 [D loss: 0.692585, acc.: 54.30%] [G loss: 0.726548]
8/8 [==============================] - 0s 2ms/step
1965 [D loss: 0.679944, acc.: 57.42%] [G loss: 0.714322]
8/8 [==============================] - 0s 2ms/step
1966 [D loss: 0.688291, acc.: 53.71%] [G loss: 0.707988]
8/8 [==============================] - 0s 2ms/step
1967 [D loss: 0.685381, acc.: 53.71%] [G loss: 0.707211]
8/8 [==============================] - 0s 2ms/step
1968 [D loss: 0.688611, acc.: 53.12%] [G loss: 0.708707]
8/8 [==============================] - 0s 2ms/step
1969 [D loss: 0.690773, acc.: 53.32%] [G loss: 0.717760]
8/8 [==============================] - 0s 2ms/step
1970 [D loss: 0.683085, acc.: 58.01%] [G loss: 0.711633]
8/8 [==============================] - 0s 2ms/step
1971 [D loss: 0.692479, acc.: 53.12%] [G loss: 0.713491]
8/8 [==============================] - 0s 2ms/step
1972 [D loss: 0.688857, acc.: 51.95%] [G loss: 0.720986]
8/8 [==============================] - 0s 2ms/step
1973 [D loss: 0.688994, acc.: 53.12%] [G loss: 0.713440]
8/8 [==============================] - 0s 2ms/step
1974 [D loss: 0.693702, acc.: 47.66%] [G loss: 0.720411]
8/8 [==============================] - 0s 2ms/step
1975 [D loss: 0.691503, acc.: 53.12%] [G loss: 0.715508]
8/8 [==============================] - 0s 3ms/step
1976 [D loss: 0.690889, acc.: 53.32%] [G loss: 0.707737]
8/8 [==============================] - 0s 2ms/step
1977 [D loss: 0.691395, acc.: 51.76%] [G loss: 0.720198]
8/8 [==============================] - 0s 2ms/step
1978 [D loss: 0.691217, acc.: 51.37%] [G loss: 0.712779]
8/8 [==============================] - 0s 2ms/step
1979 [D loss: 0.687647, acc.: 54.69%] [G loss: 0.708491]
8/8 [==============================] - 0s 2ms/step
1980 [D loss: 0.685375, acc.: 56.84%] [G loss: 0.710266]
8/8 [==============================] - 0s 2ms/step
1981 [D loss: 0.689889, acc.: 53.12%] [G loss: 0.715358]
8/8 [==============================] - 0s 2ms/step
1982 [D loss: 0.686633, acc.: 56.05%] [G loss: 0.708425]
8/8 [==============================] - 0s 2ms/step
1983 [D loss: 0.687609, acc.: 55.27%] [G loss: 0.711764]
8/8 [==============================] - 0s 2ms/step
1984 [D loss: 0.683847, acc.: 56.64%] [G loss: 0.716362]
8/8 [==============================] - 0s 2ms/step
1985 [D loss: 0.680462, acc.: 58.20%] [G loss: 0.714004]
8/8 [==============================] - 0s 2ms/step
1986 [D loss: 0.687067, acc.: 57.23%] [G loss: 0.704883]
8/8 [==============================] - 0s 2ms/step
1987 [D loss: 0.687302, acc.: 57.23%] [G loss: 0.709025]
8/8 [==============================] - 0s 2ms/step
1988 [D loss: 0.688367, acc.: 55.27%] [G loss: 0.713920]
8/8 [==============================] - 0s 2ms/step
1989 [D loss: 0.688116, acc.: 54.49%] [G loss: 0.709398]
8/8 [==============================] - 0s 2ms/step
1990 [D loss: 0.689287, acc.: 52.93%] [G loss: 0.718211]
8/8 [==============================] - 0s 2ms/step
1991 [D loss: 0.688186, acc.: 55.47%] [G loss: 0.718398]
8/8 [==============================] - 0s 2ms/step
1992 [D loss: 0.685252, acc.: 57.42%] [G loss: 0.720246]
8/8 [==============================] - 0s 2ms/step
1993 [D loss: 0.686849, acc.: 53.52%] [G loss: 0.720935]
8/8 [==============================] - 0s 2ms/step
1994 [D loss: 0.684452, acc.: 59.57%] [G loss: 0.709592]
8/8 [==============================] - 0s 2ms/step
1995 [D loss: 0.690893, acc.: 53.12%] [G loss: 0.713861]
8/8 [==============================] - 0s 2ms/step
1996 [D loss: 0.681270, acc.: 60.74%] [G loss: 0.726590]
8/8 [==============================] - 0s 2ms/step
1997 [D loss: 0.691295, acc.: 52.93%] [G loss: 0.720064]
8/8 [==============================] - 0s 2ms/step
1998 [D loss: 0.686704, acc.: 57.03%] [G loss: 0.732080]
8/8 [==============================] - 0s 2ms/step
1999 [D loss: 0.684261, acc.: 54.69%] [G loss: 0.726725]
8/8 [==============================] - 0s 2ms/step
2000 [D loss: 0.685875, acc.: 56.84%] [G loss: 0.719571]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
2001 [D loss: 0.689571, acc.: 53.71%] [G loss: 0.727132]
8/8 [==============================] - 0s 2ms/step
2002 [D loss: 0.690195, acc.: 52.15%] [G loss: 0.708925]
8/8 [==============================] - 0s 2ms/step
2003 [D loss: 0.694189, acc.: 51.17%] [G loss: 0.707482]
8/8 [==============================] - 0s 2ms/step
2004 [D loss: 0.688296, acc.: 57.42%] [G loss: 0.716134]
8/8 [==============================] - 0s 2ms/step
2005 [D loss: 0.685503, acc.: 55.66%] [G loss: 0.707754]
8/8 [==============================] - 0s 2ms/step
2006 [D loss: 0.688135, acc.: 54.69%] [G loss: 0.707266]
8/8 [==============================] - 0s 2ms/step
2007 [D loss: 0.692377, acc.: 53.32%] [G loss: 0.715056]
8/8 [==============================] - 0s 2ms/step
2008 [D loss: 0.691645, acc.: 52.34%] [G loss: 0.712745]
8/8 [==============================] - 0s 2ms/step
2009 [D loss: 0.691263, acc.: 51.37%] [G loss: 0.717552]
8/8 [==============================] - 0s 2ms/step
2010 [D loss: 0.685679, acc.: 55.66%] [G loss: 0.718157]
8/8 [==============================] - 0s 3ms/step
2011 [D loss: 0.684215, acc.: 56.84%] [G loss: 0.722356]
8/8 [==============================] - 0s 2ms/step
2012 [D loss: 0.682451, acc.: 57.03%] [G loss: 0.718202]
8/8 [==============================] - 0s 2ms/step
2013 [D loss: 0.689338, acc.: 56.45%] [G loss: 0.715282]
8/8 [==============================] - 0s 2ms/step
2014 [D loss: 0.689810, acc.: 53.52%] [G loss: 0.714815]
8/8 [==============================] - 0s 2ms/step
2015 [D loss: 0.692491, acc.: 53.12%] [G loss: 0.702811]
8/8 [==============================] - 0s 2ms/step
2016 [D loss: 0.689727, acc.: 54.88%] [G loss: 0.714772]
8/8 [==============================] - 0s 2ms/step
2017 [D loss: 0.690006, acc.: 53.71%] [G loss: 0.717518]
8/8 [==============================] - 0s 2ms/step
2018 [D loss: 0.688684, acc.: 53.32%] [G loss: 0.716023]
8/8 [==============================] - 0s 2ms/step
2019 [D loss: 0.688943, acc.: 51.17%] [G loss: 0.707179]
8/8 [==============================] - 0s 2ms/step
2020 [D loss: 0.685452, acc.: 54.30%] [G loss: 0.711231]
8/8 [==============================] - 0s 2ms/step
2021 [D loss: 0.689200, acc.: 54.69%] [G loss: 0.703810]
8/8 [==============================] - 0s 2ms/step
2022 [D loss: 0.690577, acc.: 52.73%] [G loss: 0.716836]
8/8 [==============================] - 0s 2ms/step
2023 [D loss: 0.682286, acc.: 58.01%] [G loss: 0.718611]
8/8 [==============================] - 0s 2ms/step
2024 [D loss: 0.686491, acc.: 59.38%] [G loss: 0.715263]
8/8 [==============================] - 0s 2ms/step
2025 [D loss: 0.686876, acc.: 55.66%] [G loss: 0.717307]
8/8 [==============================] - 0s 2ms/step
2026 [D loss: 0.686210, acc.: 54.30%] [G loss: 0.717989]
8/8 [==============================] - 0s 2ms/step
2027 [D loss: 0.695147, acc.: 50.78%] [G loss: 0.713003]
8/8 [==============================] - 0s 2ms/step
2028 [D loss: 0.691441, acc.: 52.34%] [G loss: 0.723525]
8/8 [==============================] - 0s 2ms/step
2029 [D loss: 0.684774, acc.: 57.03%] [G loss: 0.725961]
8/8 [==============================] - 0s 2ms/step
2030 [D loss: 0.683135, acc.: 56.64%] [G loss: 0.728446]
8/8 [==============================] - 0s 2ms/step
2031 [D loss: 0.685926, acc.: 53.32%] [G loss: 0.724863]
8/8 [==============================] - 0s 2ms/step
2032 [D loss: 0.694412, acc.: 52.54%] [G loss: 0.715936]
8/8 [==============================] - 0s 2ms/step
2033 [D loss: 0.690145, acc.: 53.12%] [G loss: 0.718548]
8/8 [==============================] - 0s 2ms/step
2034 [D loss: 0.697618, acc.: 49.80%] [G loss: 0.716058]
8/8 [==============================] - 0s 2ms/step
2035 [D loss: 0.685144, acc.: 56.25%] [G loss: 0.719858]
8/8 [==============================] - 0s 2ms/step
2036 [D loss: 0.683412, acc.: 57.23%] [G loss: 0.722546]
8/8 [==============================] - 0s 2ms/step
2037 [D loss: 0.683786, acc.: 53.91%] [G loss: 0.727962]
8/8 [==============================] - 0s 2ms/step
2038 [D loss: 0.689618, acc.: 54.49%] [G loss: 0.714572]
8/8 [==============================] - 0s 2ms/step
2039 [D loss: 0.695079, acc.: 49.80%] [G loss: 0.719563]
8/8 [==============================] - 0s 2ms/step
2040 [D loss: 0.682831, acc.: 58.79%] [G loss: 0.711579]
8/8 [==============================] - 0s 2ms/step
2041 [D loss: 0.701384, acc.: 49.61%] [G loss: 0.717853]
8/8 [==============================] - 0s 2ms/step
2042 [D loss: 0.686279, acc.: 54.69%] [G loss: 0.705871]
8/8 [==============================] - 0s 2ms/step
2043 [D loss: 0.687968, acc.: 56.25%] [G loss: 0.707947]
8/8 [==============================] - 0s 2ms/step
2044 [D loss: 0.686346, acc.: 56.25%] [G loss: 0.716576]
8/8 [==============================] - 0s 2ms/step
2045 [D loss: 0.685933, acc.: 54.49%] [G loss: 0.709453]
8/8 [==============================] - 0s 2ms/step
2046 [D loss: 0.689173, acc.: 52.73%] [G loss: 0.706281]
8/8 [==============================] - 0s 2ms/step
2047 [D loss: 0.688999, acc.: 51.56%] [G loss: 0.716733]
8/8 [==============================] - 0s 2ms/step
2048 [D loss: 0.687473, acc.: 53.71%] [G loss: 0.720950]
8/8 [==============================] - 0s 2ms/step
2049 [D loss: 0.683563, acc.: 56.25%] [G loss: 0.717670]
8/8 [==============================] - 0s 2ms/step
2050 [D loss: 0.681875, acc.: 58.40%] [G loss: 0.719542]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
2051 [D loss: 0.686980, acc.: 53.12%] [G loss: 0.711250]
8/8 [==============================] - 0s 2ms/step
2052 [D loss: 0.689718, acc.: 56.64%] [G loss: 0.721282]
8/8 [==============================] - 0s 2ms/step
2053 [D loss: 0.684320, acc.: 56.05%] [G loss: 0.716246]
8/8 [==============================] - 0s 2ms/step
2054 [D loss: 0.688019, acc.: 54.49%] [G loss: 0.716995]
8/8 [==============================] - 0s 2ms/step
2055 [D loss: 0.681486, acc.: 57.42%] [G loss: 0.716079]
8/8 [==============================] - 0s 2ms/step
2056 [D loss: 0.684941, acc.: 55.27%] [G loss: 0.718922]
8/8 [==============================] - 0s 2ms/step
2057 [D loss: 0.687941, acc.: 53.71%] [G loss: 0.713972]
8/8 [==============================] - 0s 2ms/step
2058 [D loss: 0.690743, acc.: 52.54%] [G loss: 0.718360]
8/8 [==============================] - 0s 2ms/step
2059 [D loss: 0.693748, acc.: 52.73%] [G loss: 0.710084]
8/8 [==============================] - 0s 2ms/step
2060 [D loss: 0.688901, acc.: 52.93%] [G loss: 0.701759]
8/8 [==============================] - 0s 2ms/step
2061 [D loss: 0.689500, acc.: 54.30%] [G loss: 0.707229]
8/8 [==============================] - 0s 2ms/step
2062 [D loss: 0.692058, acc.: 50.78%] [G loss: 0.706972]
8/8 [==============================] - 0s 2ms/step
2063 [D loss: 0.695850, acc.: 47.66%] [G loss: 0.712851]
8/8 [==============================] - 0s 2ms/step
2064 [D loss: 0.688826, acc.: 54.88%] [G loss: 0.708188]
8/8 [==============================] - 0s 2ms/step
2065 [D loss: 0.695776, acc.: 49.41%] [G loss: 0.714377]
8/8 [==============================] - 0s 2ms/step
2066 [D loss: 0.691257, acc.: 53.32%] [G loss: 0.707151]
8/8 [==============================] - 0s 2ms/step
2067 [D loss: 0.686849, acc.: 55.27%] [G loss: 0.713349]
8/8 [==============================] - 0s 2ms/step
2068 [D loss: 0.683436, acc.: 58.20%] [G loss: 0.712209]
8/8 [==============================] - 0s 2ms/step
2069 [D loss: 0.689917, acc.: 52.73%] [G loss: 0.708610]
8/8 [==============================] - 0s 2ms/step
2070 [D loss: 0.684048, acc.: 56.25%] [G loss: 0.719251]
8/8 [==============================] - 0s 2ms/step
2071 [D loss: 0.688099, acc.: 52.73%] [G loss: 0.709156]
8/8 [==============================] - 0s 2ms/step
2072 [D loss: 0.690134, acc.: 51.56%] [G loss: 0.708999]
8/8 [==============================] - 0s 2ms/step
2073 [D loss: 0.691351, acc.: 50.59%] [G loss: 0.710677]
8/8 [==============================] - 0s 2ms/step
2074 [D loss: 0.684182, acc.: 57.62%] [G loss: 0.715337]
8/8 [==============================] - 0s 2ms/step
2075 [D loss: 0.684094, acc.: 55.66%] [G loss: 0.707594]
8/8 [==============================] - 0s 2ms/step
2076 [D loss: 0.688660, acc.: 53.12%] [G loss: 0.710132]
8/8 [==============================] - 0s 2ms/step
2077 [D loss: 0.683142, acc.: 54.49%] [G loss: 0.709041]
8/8 [==============================] - 0s 2ms/step
2078 [D loss: 0.685657, acc.: 53.71%] [G loss: 0.712594]
8/8 [==============================] - 0s 2ms/step
2079 [D loss: 0.688475, acc.: 53.12%] [G loss: 0.722336]
8/8 [==============================] - 0s 2ms/step
2080 [D loss: 0.686100, acc.: 54.49%] [G loss: 0.713666]
8/8 [==============================] - 0s 2ms/step
2081 [D loss: 0.687855, acc.: 54.88%] [G loss: 0.712946]
8/8 [==============================] - 0s 2ms/step
2082 [D loss: 0.687437, acc.: 55.66%] [G loss: 0.715575]
8/8 [==============================] - 0s 2ms/step
2083 [D loss: 0.682731, acc.: 57.03%] [G loss: 0.713481]
8/8 [==============================] - 0s 2ms/step
2084 [D loss: 0.696667, acc.: 47.27%] [G loss: 0.714855]
8/8 [==============================] - 0s 2ms/step
2085 [D loss: 0.687452, acc.: 54.30%] [G loss: 0.717247]
8/8 [==============================] - 0s 2ms/step
2086 [D loss: 0.683293, acc.: 55.86%] [G loss: 0.712090]
8/8 [==============================] - 0s 2ms/step
2087 [D loss: 0.688676, acc.: 51.95%] [G loss: 0.708467]
8/8 [==============================] - 0s 2ms/step
2088 [D loss: 0.686229, acc.: 56.84%] [G loss: 0.709819]
8/8 [==============================] - 0s 2ms/step
2089 [D loss: 0.686845, acc.: 55.66%] [G loss: 0.708433]
8/8 [==============================] - 0s 2ms/step
2090 [D loss: 0.689175, acc.: 55.27%] [G loss: 0.716169]
8/8 [==============================] - 0s 2ms/step
2091 [D loss: 0.683633, acc.: 56.05%] [G loss: 0.714347]
8/8 [==============================] - 0s 2ms/step
2092 [D loss: 0.680313, acc.: 59.38%] [G loss: 0.713918]
8/8 [==============================] - 0s 2ms/step
2093 [D loss: 0.687723, acc.: 50.98%] [G loss: 0.712955]
8/8 [==============================] - 0s 2ms/step
2094 [D loss: 0.677415, acc.: 58.20%] [G loss: 0.715397]
8/8 [==============================] - 0s 2ms/step
2095 [D loss: 0.686398, acc.: 54.88%] [G loss: 0.712599]
8/8 [==============================] - 0s 2ms/step
2096 [D loss: 0.693189, acc.: 51.76%] [G loss: 0.713854]
8/8 [==============================] - 0s 2ms/step
2097 [D loss: 0.689888, acc.: 56.84%] [G loss: 0.713490]
8/8 [==============================] - 0s 2ms/step
2098 [D loss: 0.692024, acc.: 51.37%] [G loss: 0.710128]
8/8 [==============================] - 0s 2ms/step
2099 [D loss: 0.687530, acc.: 54.30%] [G loss: 0.707694]
8/8 [==============================] - 0s 2ms/step
2100 [D loss: 0.690880, acc.: 51.95%] [G loss: 0.721881]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
2101 [D loss: 0.683900, acc.: 58.20%] [G loss: 0.713437]
8/8 [==============================] - 0s 2ms/step
2102 [D loss: 0.694581, acc.: 50.00%] [G loss: 0.706744]
8/8 [==============================] - 0s 2ms/step
2103 [D loss: 0.687615, acc.: 54.69%] [G loss: 0.713661]
8/8 [==============================] - 0s 2ms/step
2104 [D loss: 0.690224, acc.: 53.12%] [G loss: 0.710615]
8/8 [==============================] - 0s 2ms/step
2105 [D loss: 0.686520, acc.: 55.66%] [G loss: 0.719396]
8/8 [==============================] - 0s 2ms/step
2106 [D loss: 0.685473, acc.: 55.08%] [G loss: 0.718631]
8/8 [==============================] - 0s 2ms/step
2107 [D loss: 0.680900, acc.: 58.79%] [G loss: 0.714120]
8/8 [==============================] - 0s 2ms/step
2108 [D loss: 0.689694, acc.: 52.93%] [G loss: 0.709540]
8/8 [==============================] - 0s 2ms/step
2109 [D loss: 0.686590, acc.: 54.10%] [G loss: 0.712956]
8/8 [==============================] - 0s 2ms/step
2110 [D loss: 0.685541, acc.: 55.66%] [G loss: 0.725306]
8/8 [==============================] - 0s 2ms/step
2111 [D loss: 0.685111, acc.: 58.20%] [G loss: 0.709448]
8/8 [==============================] - 0s 2ms/step
2112 [D loss: 0.688132, acc.: 53.12%] [G loss: 0.712278]
8/8 [==============================] - 0s 2ms/step
2113 [D loss: 0.691116, acc.: 51.56%] [G loss: 0.709391]
8/8 [==============================] - 0s 2ms/step
2114 [D loss: 0.686401, acc.: 54.49%] [G loss: 0.713905]
8/8 [==============================] - 0s 2ms/step
2115 [D loss: 0.687837, acc.: 53.52%] [G loss: 0.718243]
8/8 [==============================] - 0s 2ms/step
2116 [D loss: 0.686096, acc.: 55.08%] [G loss: 0.713928]
8/8 [==============================] - 0s 2ms/step
2117 [D loss: 0.689771, acc.: 50.39%] [G loss: 0.709874]
8/8 [==============================] - 0s 2ms/step
2118 [D loss: 0.683681, acc.: 58.01%] [G loss: 0.712120]
8/8 [==============================] - 0s 2ms/step
2119 [D loss: 0.692481, acc.: 50.78%] [G loss: 0.718977]
8/8 [==============================] - 0s 2ms/step
2120 [D loss: 0.683899, acc.: 56.05%] [G loss: 0.717095]
8/8 [==============================] - 0s 2ms/step
2121 [D loss: 0.685861, acc.: 58.59%] [G loss: 0.712140]
8/8 [==============================] - 0s 2ms/step
2122 [D loss: 0.684906, acc.: 57.23%] [G loss: 0.718504]
8/8 [==============================] - 0s 2ms/step
2123 [D loss: 0.690299, acc.: 53.12%] [G loss: 0.714715]
8/8 [==============================] - 0s 2ms/step
2124 [D loss: 0.688705, acc.: 57.42%] [G loss: 0.709246]
8/8 [==============================] - 0s 2ms/step
2125 [D loss: 0.687262, acc.: 54.49%] [G loss: 0.715400]
8/8 [==============================] - 0s 2ms/step
2126 [D loss: 0.688871, acc.: 54.88%] [G loss: 0.715612]
8/8 [==============================] - 0s 2ms/step
2127 [D loss: 0.685819, acc.: 55.66%] [G loss: 0.713092]
8/8 [==============================] - 0s 2ms/step
2128 [D loss: 0.690064, acc.: 50.78%] [G loss: 0.713793]
8/8 [==============================] - 0s 2ms/step
2129 [D loss: 0.695089, acc.: 50.59%] [G loss: 0.721014]
8/8 [==============================] - 0s 2ms/step
2130 [D loss: 0.682875, acc.: 57.42%] [G loss: 0.712911]
8/8 [==============================] - 0s 2ms/step
2131 [D loss: 0.689061, acc.: 53.71%] [G loss: 0.710413]
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2132 [D loss: 0.683792, acc.: 56.45%] [G loss: 0.726530]
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2133 [D loss: 0.689879, acc.: 52.93%] [G loss: 0.717585]
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2134 [D loss: 0.687375, acc.: 55.66%] [G loss: 0.718094]
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2135 [D loss: 0.685847, acc.: 56.64%] [G loss: 0.714525]
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2136 [D loss: 0.688178, acc.: 54.30%] [G loss: 0.714535]
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2137 [D loss: 0.686633, acc.: 55.66%] [G loss: 0.716402]
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2138 [D loss: 0.691073, acc.: 52.15%] [G loss: 0.711980]
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2139 [D loss: 0.686891, acc.: 53.71%] [G loss: 0.721711]
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2140 [D loss: 0.683914, acc.: 54.69%] [G loss: 0.718756]
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2141 [D loss: 0.684740, acc.: 54.49%] [G loss: 0.707649]
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2142 [D loss: 0.688390, acc.: 56.64%] [G loss: 0.716836]
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2143 [D loss: 0.683950, acc.: 55.47%] [G loss: 0.719131]
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2144 [D loss: 0.683373, acc.: 56.84%] [G loss: 0.715307]
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2145 [D loss: 0.685247, acc.: 55.86%] [G loss: 0.715123]
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2146 [D loss: 0.680205, acc.: 59.96%] [G loss: 0.715302]
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2147 [D loss: 0.681661, acc.: 57.23%] [G loss: 0.719623]
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2148 [D loss: 0.688803, acc.: 52.73%] [G loss: 0.717709]
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2149 [D loss: 0.685313, acc.: 54.88%] [G loss: 0.715149]
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2150 [D loss: 0.686665, acc.: 55.47%] [G loss: 0.710527]
1/1 [==============================] - 0s 17ms/step
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2151 [D loss: 0.687331, acc.: 50.98%] [G loss: 0.713861]
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2152 [D loss: 0.691817, acc.: 52.34%] [G loss: 0.719269]
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2153 [D loss: 0.689305, acc.: 53.91%] [G loss: 0.708589]
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2154 [D loss: 0.685178, acc.: 54.30%] [G loss: 0.715713]
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2155 [D loss: 0.695129, acc.: 50.39%] [G loss: 0.724272]
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2156 [D loss: 0.685923, acc.: 55.47%] [G loss: 0.715048]
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2157 [D loss: 0.687128, acc.: 56.25%] [G loss: 0.716663]
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2158 [D loss: 0.681811, acc.: 57.81%] [G loss: 0.702821]
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2159 [D loss: 0.695448, acc.: 50.00%] [G loss: 0.714755]
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2160 [D loss: 0.686833, acc.: 51.56%] [G loss: 0.710707]
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2161 [D loss: 0.681331, acc.: 56.25%] [G loss: 0.706357]
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2162 [D loss: 0.699753, acc.: 48.24%] [G loss: 0.702559]
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2163 [D loss: 0.685922, acc.: 55.86%] [G loss: 0.711873]
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2164 [D loss: 0.686581, acc.: 55.66%] [G loss: 0.713424]
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2165 [D loss: 0.688030, acc.: 53.32%] [G loss: 0.712739]
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2166 [D loss: 0.688183, acc.: 53.71%] [G loss: 0.714310]
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2167 [D loss: 0.685554, acc.: 55.66%] [G loss: 0.715570]
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2168 [D loss: 0.680854, acc.: 56.45%] [G loss: 0.715276]
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2169 [D loss: 0.692377, acc.: 50.39%] [G loss: 0.717921]
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2170 [D loss: 0.684890, acc.: 55.86%] [G loss: 0.721224]
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2171 [D loss: 0.685521, acc.: 56.05%] [G loss: 0.715051]
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2172 [D loss: 0.682327, acc.: 56.64%] [G loss: 0.719413]
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2173 [D loss: 0.685188, acc.: 54.30%] [G loss: 0.718523]
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2174 [D loss: 0.682560, acc.: 55.47%] [G loss: 0.721057]
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2175 [D loss: 0.683059, acc.: 58.20%] [G loss: 0.720164]
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2176 [D loss: 0.686302, acc.: 55.86%] [G loss: 0.713723]
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2177 [D loss: 0.695451, acc.: 52.93%] [G loss: 0.722037]
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2178 [D loss: 0.695939, acc.: 48.44%] [G loss: 0.720079]
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2179 [D loss: 0.694136, acc.: 49.80%] [G loss: 0.725825]
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2180 [D loss: 0.681923, acc.: 58.01%] [G loss: 0.715641]
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2181 [D loss: 0.681519, acc.: 57.23%] [G loss: 0.715714]
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2182 [D loss: 0.687157, acc.: 53.91%] [G loss: 0.715950]
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2183 [D loss: 0.684790, acc.: 57.23%] [G loss: 0.723862]
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2184 [D loss: 0.685728, acc.: 54.69%] [G loss: 0.715690]
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2185 [D loss: 0.680060, acc.: 57.62%] [G loss: 0.720526]
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2186 [D loss: 0.683946, acc.: 56.05%] [G loss: 0.721131]
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2187 [D loss: 0.686236, acc.: 55.86%] [G loss: 0.715539]
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2188 [D loss: 0.692690, acc.: 52.54%] [G loss: 0.715081]
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2189 [D loss: 0.684543, acc.: 54.69%] [G loss: 0.722221]
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2190 [D loss: 0.682424, acc.: 56.05%] [G loss: 0.722345]
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2191 [D loss: 0.684484, acc.: 56.45%] [G loss: 0.722319]
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2192 [D loss: 0.679803, acc.: 57.62%] [G loss: 0.713883]
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2193 [D loss: 0.693589, acc.: 52.93%] [G loss: 0.719007]
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2194 [D loss: 0.696605, acc.: 50.20%] [G loss: 0.720580]
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2195 [D loss: 0.691746, acc.: 51.76%] [G loss: 0.712911]
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2196 [D loss: 0.689824, acc.: 53.12%] [G loss: 0.709300]
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2197 [D loss: 0.685303, acc.: 56.45%] [G loss: 0.713080]
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2198 [D loss: 0.691947, acc.: 53.71%] [G loss: 0.715818]
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2199 [D loss: 0.688904, acc.: 53.12%] [G loss: 0.705361]
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2200 [D loss: 0.690181, acc.: 54.49%] [G loss: 0.704352]
1/1 [==============================] - 0s 16ms/step
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2201 [D loss: 0.686599, acc.: 55.47%] [G loss: 0.702471]
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2202 [D loss: 0.693206, acc.: 51.76%] [G loss: 0.703978]
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2203 [D loss: 0.689980, acc.: 54.30%] [G loss: 0.704435]
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2204 [D loss: 0.689232, acc.: 54.49%] [G loss: 0.706907]
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2205 [D loss: 0.688992, acc.: 53.12%] [G loss: 0.706071]
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2206 [D loss: 0.690077, acc.: 52.54%] [G loss: 0.708830]
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2207 [D loss: 0.686083, acc.: 53.71%] [G loss: 0.712981]
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2208 [D loss: 0.689098, acc.: 55.47%] [G loss: 0.710203]
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2209 [D loss: 0.683859, acc.: 54.88%] [G loss: 0.705119]
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2210 [D loss: 0.686433, acc.: 54.88%] [G loss: 0.715850]
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2211 [D loss: 0.686382, acc.: 56.25%] [G loss: 0.712450]
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2212 [D loss: 0.684637, acc.: 58.20%] [G loss: 0.715089]
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2213 [D loss: 0.684207, acc.: 55.27%] [G loss: 0.717230]
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2214 [D loss: 0.683752, acc.: 57.42%] [G loss: 0.719408]
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2215 [D loss: 0.681619, acc.: 58.01%] [G loss: 0.712950]
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2216 [D loss: 0.688677, acc.: 54.30%] [G loss: 0.719681]
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2217 [D loss: 0.685740, acc.: 54.88%] [G loss: 0.717170]
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2218 [D loss: 0.691046, acc.: 53.32%] [G loss: 0.715390]
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2219 [D loss: 0.693022, acc.: 50.39%] [G loss: 0.716478]
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2220 [D loss: 0.692028, acc.: 54.30%] [G loss: 0.717013]
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2221 [D loss: 0.690018, acc.: 53.12%] [G loss: 0.718218]
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2222 [D loss: 0.688231, acc.: 55.27%] [G loss: 0.716254]
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2223 [D loss: 0.685983, acc.: 55.86%] [G loss: 0.715760]
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2224 [D loss: 0.696064, acc.: 47.85%] [G loss: 0.711414]
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2225 [D loss: 0.691679, acc.: 52.54%] [G loss: 0.714002]
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2226 [D loss: 0.692205, acc.: 49.80%] [G loss: 0.721819]
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2227 [D loss: 0.684891, acc.: 54.69%] [G loss: 0.721701]
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2228 [D loss: 0.687291, acc.: 55.47%] [G loss: 0.723231]
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2229 [D loss: 0.689108, acc.: 55.47%] [G loss: 0.731458]
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2230 [D loss: 0.692219, acc.: 52.93%] [G loss: 0.716737]
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2231 [D loss: 0.683097, acc.: 57.81%] [G loss: 0.715950]
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2232 [D loss: 0.693120, acc.: 54.69%] [G loss: 0.715048]
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2233 [D loss: 0.685267, acc.: 53.71%] [G loss: 0.719791]
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2234 [D loss: 0.689568, acc.: 52.54%] [G loss: 0.712731]
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2235 [D loss: 0.692828, acc.: 51.37%] [G loss: 0.703732]
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2236 [D loss: 0.687990, acc.: 54.30%] [G loss: 0.707704]
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2237 [D loss: 0.689971, acc.: 53.32%] [G loss: 0.707631]
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2238 [D loss: 0.684743, acc.: 55.47%] [G loss: 0.710518]
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2239 [D loss: 0.687202, acc.: 55.27%] [G loss: 0.715436]
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2240 [D loss: 0.687391, acc.: 55.47%] [G loss: 0.711853]
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2241 [D loss: 0.681900, acc.: 59.18%] [G loss: 0.722806]
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2242 [D loss: 0.689209, acc.: 56.45%] [G loss: 0.714048]
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2243 [D loss: 0.687990, acc.: 53.12%] [G loss: 0.706473]
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2244 [D loss: 0.684940, acc.: 54.69%] [G loss: 0.715617]
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2245 [D loss: 0.688800, acc.: 53.71%] [G loss: 0.714509]
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2246 [D loss: 0.688923, acc.: 52.54%] [G loss: 0.713021]
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2247 [D loss: 0.690134, acc.: 53.91%] [G loss: 0.706991]
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2248 [D loss: 0.682183, acc.: 55.27%] [G loss: 0.715677]
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2249 [D loss: 0.693591, acc.: 53.91%] [G loss: 0.701684]
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2250 [D loss: 0.683379, acc.: 56.84%] [G loss: 0.706885]
1/1 [==============================] - 0s 15ms/step
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2251 [D loss: 0.692737, acc.: 52.73%] [G loss: 0.713969]
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2252 [D loss: 0.687069, acc.: 53.32%] [G loss: 0.712405]
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2253 [D loss: 0.689561, acc.: 49.41%] [G loss: 0.705680]
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2254 [D loss: 0.686253, acc.: 55.86%] [G loss: 0.711861]
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2255 [D loss: 0.688461, acc.: 53.12%] [G loss: 0.710686]
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2256 [D loss: 0.681160, acc.: 56.45%] [G loss: 0.711653]
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2257 [D loss: 0.689665, acc.: 54.69%] [G loss: 0.716807]
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2258 [D loss: 0.687435, acc.: 53.91%] [G loss: 0.713466]
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2259 [D loss: 0.690435, acc.: 55.08%] [G loss: 0.718427]
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2260 [D loss: 0.683330, acc.: 60.74%] [G loss: 0.703908]
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2261 [D loss: 0.687186, acc.: 54.69%] [G loss: 0.711177]
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2262 [D loss: 0.687388, acc.: 53.32%] [G loss: 0.702692]
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2263 [D loss: 0.692654, acc.: 51.17%] [G loss: 0.721126]
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2264 [D loss: 0.686445, acc.: 55.47%] [G loss: 0.712176]
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2265 [D loss: 0.691652, acc.: 53.12%] [G loss: 0.712124]
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2266 [D loss: 0.693361, acc.: 55.47%] [G loss: 0.717998]
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2267 [D loss: 0.683569, acc.: 55.86%] [G loss: 0.717069]
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2268 [D loss: 0.693808, acc.: 48.24%] [G loss: 0.714087]
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2269 [D loss: 0.684078, acc.: 54.10%] [G loss: 0.724395]
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2270 [D loss: 0.687308, acc.: 54.30%] [G loss: 0.719091]
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2271 [D loss: 0.686978, acc.: 54.49%] [G loss: 0.717943]
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2272 [D loss: 0.688198, acc.: 52.93%] [G loss: 0.723055]
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2273 [D loss: 0.690948, acc.: 51.56%] [G loss: 0.720788]
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2274 [D loss: 0.685888, acc.: 56.05%] [G loss: 0.714586]
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2275 [D loss: 0.685556, acc.: 59.57%] [G loss: 0.718669]
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2276 [D loss: 0.691443, acc.: 52.73%] [G loss: 0.716199]
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2277 [D loss: 0.683960, acc.: 56.05%] [G loss: 0.708304]
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2278 [D loss: 0.687123, acc.: 54.30%] [G loss: 0.710353]
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2279 [D loss: 0.685701, acc.: 54.49%] [G loss: 0.709589]
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2280 [D loss: 0.683559, acc.: 55.08%] [G loss: 0.714780]
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2281 [D loss: 0.691707, acc.: 52.93%] [G loss: 0.714656]
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2282 [D loss: 0.687277, acc.: 52.93%] [G loss: 0.718514]
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2283 [D loss: 0.685515, acc.: 56.84%] [G loss: 0.729249]
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2284 [D loss: 0.682524, acc.: 57.03%] [G loss: 0.716045]
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2285 [D loss: 0.692137, acc.: 52.54%] [G loss: 0.724180]
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2286 [D loss: 0.683507, acc.: 56.45%] [G loss: 0.717382]
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2287 [D loss: 0.684635, acc.: 56.84%] [G loss: 0.725513]
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2288 [D loss: 0.685073, acc.: 53.91%] [G loss: 0.715444]
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2289 [D loss: 0.684899, acc.: 56.25%] [G loss: 0.713341]
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2290 [D loss: 0.688315, acc.: 56.05%] [G loss: 0.714473]
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2291 [D loss: 0.687860, acc.: 55.27%] [G loss: 0.713127]
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2292 [D loss: 0.682295, acc.: 56.05%] [G loss: 0.714952]
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2293 [D loss: 0.685741, acc.: 57.23%] [G loss: 0.711303]
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2294 [D loss: 0.687976, acc.: 54.10%] [G loss: 0.715382]
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2295 [D loss: 0.686317, acc.: 54.88%] [G loss: 0.715225]
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2296 [D loss: 0.690175, acc.: 53.12%] [G loss: 0.722862]
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2297 [D loss: 0.688034, acc.: 55.08%] [G loss: 0.713981]
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2298 [D loss: 0.685958, acc.: 56.84%] [G loss: 0.710974]
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2299 [D loss: 0.689610, acc.: 52.15%] [G loss: 0.710439]
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2300 [D loss: 0.690815, acc.: 53.91%] [G loss: 0.716924]
1/1 [==============================] - 0s 16ms/step
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2301 [D loss: 0.687925, acc.: 58.01%] [G loss: 0.718519]
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2302 [D loss: 0.687115, acc.: 56.45%] [G loss: 0.709299]
8/8 [==============================] - 0s 2ms/step
2303 [D loss: 0.687020, acc.: 57.81%] [G loss: 0.716759]
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2304 [D loss: 0.680602, acc.: 56.64%] [G loss: 0.715589]
8/8 [==============================] - 0s 2ms/step
2305 [D loss: 0.682368, acc.: 56.45%] [G loss: 0.721634]
8/8 [==============================] - 0s 2ms/step
2306 [D loss: 0.683244, acc.: 55.66%] [G loss: 0.715363]
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2307 [D loss: 0.684818, acc.: 56.05%] [G loss: 0.712541]
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2308 [D loss: 0.684697, acc.: 54.49%] [G loss: 0.713965]
8/8 [==============================] - 0s 2ms/step
2309 [D loss: 0.686397, acc.: 57.81%] [G loss: 0.712253]
8/8 [==============================] - 0s 2ms/step
2310 [D loss: 0.683515, acc.: 56.84%] [G loss: 0.712998]
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2311 [D loss: 0.687624, acc.: 54.49%] [G loss: 0.714229]
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2312 [D loss: 0.689688, acc.: 52.93%] [G loss: 0.719899]
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2313 [D loss: 0.684157, acc.: 57.62%] [G loss: 0.715084]
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2314 [D loss: 0.689099, acc.: 54.10%] [G loss: 0.724255]
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2315 [D loss: 0.691635, acc.: 52.73%] [G loss: 0.715852]
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2316 [D loss: 0.690263, acc.: 54.30%] [G loss: 0.725963]
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2317 [D loss: 0.690340, acc.: 53.12%] [G loss: 0.714985]
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2318 [D loss: 0.690454, acc.: 50.78%] [G loss: 0.724057]
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2319 [D loss: 0.694699, acc.: 52.93%] [G loss: 0.719882]
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2320 [D loss: 0.677667, acc.: 57.81%] [G loss: 0.713002]
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2321 [D loss: 0.689353, acc.: 53.12%] [G loss: 0.718557]
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2322 [D loss: 0.687808, acc.: 54.49%] [G loss: 0.723245]
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2323 [D loss: 0.687893, acc.: 55.08%] [G loss: 0.712831]
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2324 [D loss: 0.681474, acc.: 57.81%] [G loss: 0.709955]
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2325 [D loss: 0.689197, acc.: 50.78%] [G loss: 0.721519]
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2326 [D loss: 0.687122, acc.: 55.47%] [G loss: 0.720014]
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2327 [D loss: 0.682132, acc.: 56.05%] [G loss: 0.720819]
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2328 [D loss: 0.687512, acc.: 54.10%] [G loss: 0.727792]
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2329 [D loss: 0.681792, acc.: 57.62%] [G loss: 0.718294]
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2330 [D loss: 0.693109, acc.: 51.95%] [G loss: 0.712194]
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2331 [D loss: 0.689844, acc.: 51.56%] [G loss: 0.704230]
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2332 [D loss: 0.694876, acc.: 51.56%] [G loss: 0.709409]
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2333 [D loss: 0.689916, acc.: 51.95%] [G loss: 0.716048]
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2334 [D loss: 0.687502, acc.: 54.30%] [G loss: 0.698239]
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2335 [D loss: 0.693352, acc.: 53.32%] [G loss: 0.709992]
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2336 [D loss: 0.689268, acc.: 55.08%] [G loss: 0.707313]
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2337 [D loss: 0.690710, acc.: 53.12%] [G loss: 0.714322]
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2338 [D loss: 0.685193, acc.: 55.27%] [G loss: 0.714375]
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2339 [D loss: 0.686914, acc.: 56.05%] [G loss: 0.715295]
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2340 [D loss: 0.687086, acc.: 54.49%] [G loss: 0.710671]
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2341 [D loss: 0.684703, acc.: 57.03%] [G loss: 0.713525]
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2342 [D loss: 0.683669, acc.: 54.88%] [G loss: 0.713009]
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2343 [D loss: 0.682128, acc.: 58.01%] [G loss: 0.721439]
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2344 [D loss: 0.683672, acc.: 56.45%] [G loss: 0.720025]
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2345 [D loss: 0.683321, acc.: 57.03%] [G loss: 0.720662]
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2346 [D loss: 0.685203, acc.: 54.88%] [G loss: 0.721138]
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2347 [D loss: 0.682399, acc.: 54.49%] [G loss: 0.712509]
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2348 [D loss: 0.685406, acc.: 56.05%] [G loss: 0.725423]
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2349 [D loss: 0.690227, acc.: 52.54%] [G loss: 0.719632]
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2350 [D loss: 0.684724, acc.: 53.71%] [G loss: 0.714718]
1/1 [==============================] - 0s 16ms/step
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2351 [D loss: 0.684554, acc.: 56.64%] [G loss: 0.720364]
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2352 [D loss: 0.686680, acc.: 55.47%] [G loss: 0.719394]
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2353 [D loss: 0.689118, acc.: 52.15%] [G loss: 0.720089]
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2354 [D loss: 0.686131, acc.: 56.05%] [G loss: 0.723444]
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2355 [D loss: 0.680799, acc.: 56.05%] [G loss: 0.721971]
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2356 [D loss: 0.687829, acc.: 53.32%] [G loss: 0.709185]
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2357 [D loss: 0.687397, acc.: 55.27%] [G loss: 0.711339]
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2358 [D loss: 0.689168, acc.: 52.34%] [G loss: 0.711515]
8/8 [==============================] - 0s 2ms/step
2359 [D loss: 0.696819, acc.: 50.98%] [G loss: 0.719269]
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2360 [D loss: 0.689954, acc.: 54.69%] [G loss: 0.724793]
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2361 [D loss: 0.690247, acc.: 53.12%] [G loss: 0.727472]
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2362 [D loss: 0.693289, acc.: 51.56%] [G loss: 0.728060]
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2363 [D loss: 0.685923, acc.: 55.66%] [G loss: 0.727295]
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2364 [D loss: 0.686627, acc.: 55.47%] [G loss: 0.726931]
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2365 [D loss: 0.687118, acc.: 53.52%] [G loss: 0.715676]
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2366 [D loss: 0.681890, acc.: 57.62%] [G loss: 0.719223]
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2367 [D loss: 0.680250, acc.: 58.20%] [G loss: 0.729306]
8/8 [==============================] - 0s 2ms/step
2368 [D loss: 0.690948, acc.: 51.17%] [G loss: 0.724868]
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2369 [D loss: 0.692117, acc.: 53.52%] [G loss: 0.722020]
8/8 [==============================] - 0s 2ms/step
2370 [D loss: 0.693558, acc.: 52.54%] [G loss: 0.718966]
8/8 [==============================] - 0s 2ms/step
2371 [D loss: 0.680651, acc.: 56.45%] [G loss: 0.723541]
8/8 [==============================] - 0s 2ms/step
2372 [D loss: 0.678110, acc.: 59.77%] [G loss: 0.726394]
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2373 [D loss: 0.679414, acc.: 60.94%] [G loss: 0.724399]
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2374 [D loss: 0.680454, acc.: 57.81%] [G loss: 0.723449]
8/8 [==============================] - 0s 2ms/step
2375 [D loss: 0.687807, acc.: 54.88%] [G loss: 0.727998]
8/8 [==============================] - 0s 2ms/step
2376 [D loss: 0.688297, acc.: 53.91%] [G loss: 0.723613]
8/8 [==============================] - 0s 2ms/step
2377 [D loss: 0.679162, acc.: 57.62%] [G loss: 0.728786]
8/8 [==============================] - 0s 2ms/step
2378 [D loss: 0.679582, acc.: 57.42%] [G loss: 0.733808]
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2379 [D loss: 0.681219, acc.: 59.18%] [G loss: 0.723629]
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2380 [D loss: 0.688282, acc.: 55.08%] [G loss: 0.720674]
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2381 [D loss: 0.689004, acc.: 52.54%] [G loss: 0.718865]
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2382 [D loss: 0.692549, acc.: 52.15%] [G loss: 0.713503]
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2383 [D loss: 0.688819, acc.: 55.47%] [G loss: 0.719975]
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2384 [D loss: 0.685050, acc.: 55.08%] [G loss: 0.720207]
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2385 [D loss: 0.685347, acc.: 55.27%] [G loss: 0.728150]
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2386 [D loss: 0.688241, acc.: 53.91%] [G loss: 0.720805]
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2387 [D loss: 0.691164, acc.: 52.93%] [G loss: 0.722911]
8/8 [==============================] - 0s 2ms/step
2388 [D loss: 0.689366, acc.: 50.78%] [G loss: 0.719018]
8/8 [==============================] - 0s 2ms/step
2389 [D loss: 0.680812, acc.: 58.79%] [G loss: 0.724652]
8/8 [==============================] - 0s 2ms/step
2390 [D loss: 0.687024, acc.: 55.66%] [G loss: 0.726483]
8/8 [==============================] - 0s 2ms/step
2391 [D loss: 0.687378, acc.: 55.27%] [G loss: 0.708804]
8/8 [==============================] - 0s 2ms/step
2392 [D loss: 0.695617, acc.: 50.39%] [G loss: 0.707697]
8/8 [==============================] - 0s 2ms/step
2393 [D loss: 0.695584, acc.: 51.17%] [G loss: 0.706044]
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2394 [D loss: 0.692381, acc.: 52.15%] [G loss: 0.721438]
8/8 [==============================] - 0s 2ms/step
2395 [D loss: 0.685611, acc.: 56.45%] [G loss: 0.721530]
8/8 [==============================] - 0s 2ms/step
2396 [D loss: 0.686395, acc.: 56.25%] [G loss: 0.725124]
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2397 [D loss: 0.686513, acc.: 56.05%] [G loss: 0.722246]
8/8 [==============================] - 0s 2ms/step
2398 [D loss: 0.691138, acc.: 53.12%] [G loss: 0.720168]
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2399 [D loss: 0.700318, acc.: 49.02%] [G loss: 0.721793]
8/8 [==============================] - 0s 2ms/step
2400 [D loss: 0.691206, acc.: 52.73%] [G loss: 0.720508]
1/1 [==============================] - 0s 16ms/step
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2401 [D loss: 0.683482, acc.: 56.84%] [G loss: 0.727000]
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2402 [D loss: 0.683216, acc.: 56.25%] [G loss: 0.721947]
8/8 [==============================] - 0s 2ms/step
2403 [D loss: 0.686456, acc.: 54.30%] [G loss: 0.720863]
8/8 [==============================] - 0s 2ms/step
2404 [D loss: 0.681907, acc.: 57.81%] [G loss: 0.721424]
8/8 [==============================] - 0s 2ms/step
2405 [D loss: 0.687301, acc.: 51.56%] [G loss: 0.725938]
8/8 [==============================] - 0s 2ms/step
2406 [D loss: 0.686443, acc.: 56.25%] [G loss: 0.719494]
8/8 [==============================] - 0s 2ms/step
2407 [D loss: 0.684519, acc.: 55.66%] [G loss: 0.718320]
8/8 [==============================] - 0s 2ms/step
2408 [D loss: 0.683927, acc.: 56.84%] [G loss: 0.724174]
8/8 [==============================] - 0s 2ms/step
2409 [D loss: 0.687308, acc.: 56.05%] [G loss: 0.724833]
8/8 [==============================] - 0s 2ms/step
2410 [D loss: 0.690267, acc.: 53.12%] [G loss: 0.723526]
8/8 [==============================] - 0s 2ms/step
2411 [D loss: 0.685660, acc.: 54.69%] [G loss: 0.721117]
8/8 [==============================] - 0s 2ms/step
2412 [D loss: 0.682640, acc.: 55.08%] [G loss: 0.731086]
8/8 [==============================] - 0s 2ms/step
2413 [D loss: 0.676873, acc.: 59.38%] [G loss: 0.730885]
8/8 [==============================] - 0s 2ms/step
2414 [D loss: 0.677423, acc.: 60.16%] [G loss: 0.723397]
8/8 [==============================] - 0s 3ms/step
2415 [D loss: 0.683878, acc.: 55.47%] [G loss: 0.723373]
8/8 [==============================] - 0s 2ms/step
2416 [D loss: 0.687780, acc.: 53.52%] [G loss: 0.709917]
8/8 [==============================] - 0s 2ms/step
2417 [D loss: 0.692970, acc.: 54.10%] [G loss: 0.712767]
8/8 [==============================] - 0s 2ms/step
2418 [D loss: 0.690026, acc.: 51.76%] [G loss: 0.707335]
8/8 [==============================] - 0s 2ms/step
2419 [D loss: 0.685107, acc.: 54.69%] [G loss: 0.722334]
8/8 [==============================] - 0s 2ms/step
2420 [D loss: 0.691663, acc.: 53.71%] [G loss: 0.709677]
8/8 [==============================] - 0s 2ms/step
2421 [D loss: 0.691182, acc.: 51.76%] [G loss: 0.713670]
8/8 [==============================] - 0s 2ms/step
2422 [D loss: 0.693123, acc.: 51.76%] [G loss: 0.711595]
8/8 [==============================] - 0s 2ms/step
2423 [D loss: 0.694008, acc.: 50.39%] [G loss: 0.719270]
8/8 [==============================] - 0s 2ms/step
2424 [D loss: 0.692476, acc.: 52.93%] [G loss: 0.726118]
8/8 [==============================] - 0s 2ms/step
2425 [D loss: 0.690369, acc.: 54.10%] [G loss: 0.724196]
8/8 [==============================] - 0s 2ms/step
2426 [D loss: 0.684558, acc.: 55.86%] [G loss: 0.716193]
8/8 [==============================] - 0s 2ms/step
2427 [D loss: 0.686983, acc.: 55.27%] [G loss: 0.711260]
8/8 [==============================] - 0s 2ms/step
2428 [D loss: 0.697710, acc.: 48.05%] [G loss: 0.715465]
8/8 [==============================] - 0s 2ms/step
2429 [D loss: 0.691842, acc.: 51.56%] [G loss: 0.716311]
8/8 [==============================] - 0s 2ms/step
2430 [D loss: 0.684632, acc.: 53.71%] [G loss: 0.721597]
8/8 [==============================] - 0s 2ms/step
2431 [D loss: 0.683596, acc.: 58.01%] [G loss: 0.733820]
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2432 [D loss: 0.684832, acc.: 56.25%] [G loss: 0.730110]
8/8 [==============================] - 0s 2ms/step
2433 [D loss: 0.680232, acc.: 55.86%] [G loss: 0.723799]
8/8 [==============================] - 0s 2ms/step
2434 [D loss: 0.692565, acc.: 51.37%] [G loss: 0.734142]
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2435 [D loss: 0.694068, acc.: 52.93%] [G loss: 0.730199]
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2436 [D loss: 0.686410, acc.: 54.49%] [G loss: 0.731289]
8/8 [==============================] - 0s 2ms/step
2437 [D loss: 0.678612, acc.: 58.01%] [G loss: 0.726409]
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2438 [D loss: 0.675428, acc.: 59.96%] [G loss: 0.719983]
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2439 [D loss: 0.688122, acc.: 56.25%] [G loss: 0.720449]
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2440 [D loss: 0.694250, acc.: 47.85%] [G loss: 0.715724]
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2441 [D loss: 0.691681, acc.: 52.73%] [G loss: 0.720776]
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2442 [D loss: 0.685372, acc.: 55.08%] [G loss: 0.721540]
8/8 [==============================] - 0s 2ms/step
2443 [D loss: 0.681062, acc.: 56.45%] [G loss: 0.721015]
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2444 [D loss: 0.680467, acc.: 58.59%] [G loss: 0.737162]
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2445 [D loss: 0.685422, acc.: 56.84%] [G loss: 0.738612]
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2446 [D loss: 0.686456, acc.: 52.93%] [G loss: 0.715234]
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2447 [D loss: 0.690661, acc.: 52.15%] [G loss: 0.720286]
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2448 [D loss: 0.697520, acc.: 49.41%] [G loss: 0.708754]
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2449 [D loss: 0.684216, acc.: 56.25%] [G loss: 0.715340]
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2450 [D loss: 0.689867, acc.: 52.34%] [G loss: 0.717982]
1/1 [==============================] - 0s 15ms/step
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2451 [D loss: 0.684567, acc.: 53.71%] [G loss: 0.709596]
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2452 [D loss: 0.687449, acc.: 53.71%] [G loss: 0.709899]
8/8 [==============================] - 0s 2ms/step
2453 [D loss: 0.687557, acc.: 53.52%] [G loss: 0.710148]
8/8 [==============================] - 0s 2ms/step
2454 [D loss: 0.683924, acc.: 58.79%] [G loss: 0.714098]
8/8 [==============================] - 0s 2ms/step
2455 [D loss: 0.684060, acc.: 54.69%] [G loss: 0.723301]
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2456 [D loss: 0.681925, acc.: 56.45%] [G loss: 0.712005]
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2457 [D loss: 0.686489, acc.: 53.91%] [G loss: 0.728304]
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2458 [D loss: 0.688404, acc.: 55.08%] [G loss: 0.721179]
8/8 [==============================] - 0s 2ms/step
2459 [D loss: 0.681645, acc.: 56.84%] [G loss: 0.726393]
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2460 [D loss: 0.687393, acc.: 55.86%] [G loss: 0.720381]
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2461 [D loss: 0.695616, acc.: 49.80%] [G loss: 0.715165]
8/8 [==============================] - 0s 2ms/step
2462 [D loss: 0.683977, acc.: 55.08%] [G loss: 0.727640]
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2463 [D loss: 0.688508, acc.: 54.30%] [G loss: 0.712936]
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2464 [D loss: 0.684983, acc.: 56.05%] [G loss: 0.718095]
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2465 [D loss: 0.688439, acc.: 55.27%] [G loss: 0.718450]
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2466 [D loss: 0.681686, acc.: 55.86%] [G loss: 0.720813]
8/8 [==============================] - 0s 2ms/step
2467 [D loss: 0.687136, acc.: 54.69%] [G loss: 0.730416]
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2468 [D loss: 0.683078, acc.: 56.84%] [G loss: 0.720366]
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2469 [D loss: 0.682735, acc.: 56.45%] [G loss: 0.722672]
8/8 [==============================] - 0s 2ms/step
2470 [D loss: 0.688017, acc.: 55.66%] [G loss: 0.715936]
8/8 [==============================] - 0s 2ms/step
2471 [D loss: 0.686968, acc.: 54.30%] [G loss: 0.713683]
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2472 [D loss: 0.683116, acc.: 55.86%] [G loss: 0.720893]
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2473 [D loss: 0.692432, acc.: 50.78%] [G loss: 0.707871]
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2474 [D loss: 0.677721, acc.: 59.77%] [G loss: 0.719112]
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2475 [D loss: 0.686091, acc.: 52.54%] [G loss: 0.706038]
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2476 [D loss: 0.683381, acc.: 58.40%] [G loss: 0.700666]
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2477 [D loss: 0.682222, acc.: 58.20%] [G loss: 0.709447]
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2478 [D loss: 0.693690, acc.: 52.34%] [G loss: 0.703600]
8/8 [==============================] - 0s 2ms/step
2479 [D loss: 0.687252, acc.: 54.49%] [G loss: 0.712206]
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2480 [D loss: 0.698478, acc.: 47.27%] [G loss: 0.710836]
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2481 [D loss: 0.690707, acc.: 53.52%] [G loss: 0.713785]
8/8 [==============================] - 0s 2ms/step
2482 [D loss: 0.683379, acc.: 58.01%] [G loss: 0.710176]
8/8 [==============================] - 0s 2ms/step
2483 [D loss: 0.683212, acc.: 55.86%] [G loss: 0.705220]
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2484 [D loss: 0.682357, acc.: 55.86%] [G loss: 0.714305]
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2485 [D loss: 0.685818, acc.: 53.91%] [G loss: 0.717519]
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2486 [D loss: 0.683556, acc.: 55.66%] [G loss: 0.728042]
8/8 [==============================] - 0s 2ms/step
2487 [D loss: 0.681150, acc.: 55.27%] [G loss: 0.727048]
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2488 [D loss: 0.680720, acc.: 57.62%] [G loss: 0.730709]
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2489 [D loss: 0.683706, acc.: 55.27%] [G loss: 0.722345]
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2490 [D loss: 0.682379, acc.: 55.66%] [G loss: 0.729358]
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2491 [D loss: 0.686416, acc.: 56.05%] [G loss: 0.720777]
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2492 [D loss: 0.683913, acc.: 56.45%] [G loss: 0.728231]
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2493 [D loss: 0.680685, acc.: 55.47%] [G loss: 0.723831]
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2494 [D loss: 0.675240, acc.: 57.62%] [G loss: 0.716782]
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2495 [D loss: 0.674605, acc.: 59.77%] [G loss: 0.721000]
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2496 [D loss: 0.686803, acc.: 54.49%] [G loss: 0.710660]
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2497 [D loss: 0.683534, acc.: 56.25%] [G loss: 0.711151]
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2498 [D loss: 0.678996, acc.: 58.01%] [G loss: 0.709798]
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2499 [D loss: 0.695300, acc.: 51.95%] [G loss: 0.703132]
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2500 [D loss: 0.690845, acc.: 53.32%] [G loss: 0.708490]
1/1 [==============================] - 0s 16ms/step
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2501 [D loss: 0.690925, acc.: 52.34%] [G loss: 0.716183]
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2502 [D loss: 0.684870, acc.: 54.49%] [G loss: 0.714792]
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2503 [D loss: 0.688972, acc.: 53.52%] [G loss: 0.705226]
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2504 [D loss: 0.684735, acc.: 54.30%] [G loss: 0.704611]
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2505 [D loss: 0.698799, acc.: 47.27%] [G loss: 0.715346]
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2506 [D loss: 0.678410, acc.: 57.81%] [G loss: 0.720990]
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2507 [D loss: 0.687052, acc.: 53.71%] [G loss: 0.723832]
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2508 [D loss: 0.688142, acc.: 51.95%] [G loss: 0.717596]
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2509 [D loss: 0.677728, acc.: 56.84%] [G loss: 0.727431]
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2510 [D loss: 0.678942, acc.: 58.40%] [G loss: 0.723919]
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2511 [D loss: 0.683548, acc.: 54.49%] [G loss: 0.721242]
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2512 [D loss: 0.687240, acc.: 52.93%] [G loss: 0.714443]
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2513 [D loss: 0.686142, acc.: 54.49%] [G loss: 0.713401]
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2514 [D loss: 0.685128, acc.: 57.03%] [G loss: 0.717656]
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2515 [D loss: 0.692071, acc.: 54.30%] [G loss: 0.709356]
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2516 [D loss: 0.682127, acc.: 57.81%] [G loss: 0.716011]
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2517 [D loss: 0.682117, acc.: 57.42%] [G loss: 0.718771]
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2518 [D loss: 0.691821, acc.: 53.52%] [G loss: 0.720690]
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2519 [D loss: 0.685141, acc.: 53.32%] [G loss: 0.712478]
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2520 [D loss: 0.696996, acc.: 49.22%] [G loss: 0.714804]
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2521 [D loss: 0.693628, acc.: 52.93%] [G loss: 0.723157]
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2522 [D loss: 0.688204, acc.: 54.10%] [G loss: 0.733729]
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2523 [D loss: 0.679952, acc.: 57.81%] [G loss: 0.731602]
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2524 [D loss: 0.691017, acc.: 51.76%] [G loss: 0.723477]
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2525 [D loss: 0.689173, acc.: 51.56%] [G loss: 0.713885]
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2526 [D loss: 0.684792, acc.: 58.20%] [G loss: 0.725150]
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2527 [D loss: 0.682791, acc.: 56.45%] [G loss: 0.725766]
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2528 [D loss: 0.683553, acc.: 57.81%] [G loss: 0.726536]
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2529 [D loss: 0.687726, acc.: 57.03%] [G loss: 0.728357]
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2530 [D loss: 0.693686, acc.: 50.59%] [G loss: 0.731365]
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2531 [D loss: 0.678755, acc.: 57.03%] [G loss: 0.717032]
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2532 [D loss: 0.692645, acc.: 51.37%] [G loss: 0.727291]
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2533 [D loss: 0.687481, acc.: 55.86%] [G loss: 0.732413]
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2534 [D loss: 0.685273, acc.: 57.03%] [G loss: 0.731194]
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2535 [D loss: 0.685194, acc.: 54.10%] [G loss: 0.719146]
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2536 [D loss: 0.686572, acc.: 56.05%] [G loss: 0.721820]
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2537 [D loss: 0.688864, acc.: 52.34%] [G loss: 0.730401]
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2538 [D loss: 0.688270, acc.: 55.27%] [G loss: 0.735122]
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2539 [D loss: 0.681551, acc.: 57.62%] [G loss: 0.725343]
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2540 [D loss: 0.682156, acc.: 58.01%] [G loss: 0.742270]
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2541 [D loss: 0.687061, acc.: 54.88%] [G loss: 0.736298]
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2542 [D loss: 0.686758, acc.: 55.86%] [G loss: 0.730106]
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2543 [D loss: 0.690935, acc.: 53.91%] [G loss: 0.715970]
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2544 [D loss: 0.680391, acc.: 58.01%] [G loss: 0.728378]
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2545 [D loss: 0.679800, acc.: 58.79%] [G loss: 0.724100]
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2546 [D loss: 0.681244, acc.: 58.20%] [G loss: 0.711781]
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2547 [D loss: 0.684230, acc.: 55.27%] [G loss: 0.707726]
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2548 [D loss: 0.689209, acc.: 53.71%] [G loss: 0.707307]
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2549 [D loss: 0.696188, acc.: 49.61%] [G loss: 0.710127]
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2550 [D loss: 0.687263, acc.: 53.52%] [G loss: 0.730626]
1/1 [==============================] - 0s 16ms/step
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2551 [D loss: 0.679120, acc.: 59.96%] [G loss: 0.750488]
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2552 [D loss: 0.676353, acc.: 58.98%] [G loss: 0.749869]
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2553 [D loss: 0.687169, acc.: 57.23%] [G loss: 0.751363]
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2554 [D loss: 0.683111, acc.: 55.27%] [G loss: 0.738186]
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2555 [D loss: 0.695218, acc.: 52.34%] [G loss: 0.728317]
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2556 [D loss: 0.683343, acc.: 55.08%] [G loss: 0.716443]
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2557 [D loss: 0.686241, acc.: 54.10%] [G loss: 0.715677]
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2558 [D loss: 0.690342, acc.: 53.91%] [G loss: 0.725098]
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2559 [D loss: 0.689714, acc.: 51.76%] [G loss: 0.709876]
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2560 [D loss: 0.688851, acc.: 52.15%] [G loss: 0.708972]
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2561 [D loss: 0.681867, acc.: 57.03%] [G loss: 0.719388]
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2562 [D loss: 0.674102, acc.: 60.94%] [G loss: 0.716442]
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2563 [D loss: 0.677229, acc.: 55.27%] [G loss: 0.717205]
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2564 [D loss: 0.680990, acc.: 58.79%] [G loss: 0.711966]
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2565 [D loss: 0.692556, acc.: 51.17%] [G loss: 0.709048]
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2566 [D loss: 0.687169, acc.: 56.25%] [G loss: 0.707296]
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2567 [D loss: 0.693347, acc.: 50.59%] [G loss: 0.715179]
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2568 [D loss: 0.682556, acc.: 58.98%] [G loss: 0.720808]
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2569 [D loss: 0.674885, acc.: 60.55%] [G loss: 0.725297]
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2570 [D loss: 0.673312, acc.: 59.77%] [G loss: 0.715779]
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2571 [D loss: 0.691734, acc.: 53.32%] [G loss: 0.709084]
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2572 [D loss: 0.688078, acc.: 52.93%] [G loss: 0.704821]
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2573 [D loss: 0.689773, acc.: 52.93%] [G loss: 0.715933]
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2574 [D loss: 0.689978, acc.: 52.54%] [G loss: 0.726819]
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2575 [D loss: 0.678657, acc.: 58.01%] [G loss: 0.739277]
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2576 [D loss: 0.683482, acc.: 59.38%] [G loss: 0.732285]
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2577 [D loss: 0.685537, acc.: 55.47%] [G loss: 0.722371]
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2578 [D loss: 0.680225, acc.: 54.88%] [G loss: 0.730795]
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2579 [D loss: 0.681313, acc.: 54.49%] [G loss: 0.729913]
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2580 [D loss: 0.683986, acc.: 55.27%] [G loss: 0.723796]
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2581 [D loss: 0.685644, acc.: 56.64%] [G loss: 0.711453]
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2582 [D loss: 0.691165, acc.: 52.34%] [G loss: 0.717192]
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2583 [D loss: 0.685630, acc.: 52.73%] [G loss: 0.723943]
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2584 [D loss: 0.689515, acc.: 57.42%] [G loss: 0.717462]
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2585 [D loss: 0.688518, acc.: 53.12%] [G loss: 0.715960]
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2586 [D loss: 0.686296, acc.: 54.69%] [G loss: 0.727784]
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2587 [D loss: 0.682579, acc.: 58.01%] [G loss: 0.729823]
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2588 [D loss: 0.675124, acc.: 56.64%] [G loss: 0.731740]
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2589 [D loss: 0.681254, acc.: 57.03%] [G loss: 0.732332]
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2590 [D loss: 0.690375, acc.: 56.05%] [G loss: 0.730294]
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2591 [D loss: 0.688582, acc.: 51.37%] [G loss: 0.738039]
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2592 [D loss: 0.691883, acc.: 50.00%] [G loss: 0.729344]
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2593 [D loss: 0.683338, acc.: 57.81%] [G loss: 0.723261]
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2594 [D loss: 0.678304, acc.: 58.79%] [G loss: 0.719807]
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2595 [D loss: 0.688841, acc.: 53.32%] [G loss: 0.721680]
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2596 [D loss: 0.687690, acc.: 52.54%] [G loss: 0.717969]
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2597 [D loss: 0.692559, acc.: 52.73%] [G loss: 0.725717]
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2598 [D loss: 0.686847, acc.: 51.95%] [G loss: 0.722587]
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2599 [D loss: 0.688455, acc.: 53.12%] [G loss: 0.737865]
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2600 [D loss: 0.686380, acc.: 53.71%] [G loss: 0.725786]
1/1 [==============================] - 0s 15ms/step
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2601 [D loss: 0.681280, acc.: 58.79%] [G loss: 0.720656]
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2602 [D loss: 0.687251, acc.: 50.20%] [G loss: 0.720536]
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2603 [D loss: 0.682412, acc.: 54.49%] [G loss: 0.714697]
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2604 [D loss: 0.690045, acc.: 52.34%] [G loss: 0.715871]
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2605 [D loss: 0.687841, acc.: 55.86%] [G loss: 0.722505]
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2606 [D loss: 0.684188, acc.: 53.32%] [G loss: 0.732762]
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2607 [D loss: 0.683209, acc.: 57.23%] [G loss: 0.731279]
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2608 [D loss: 0.687999, acc.: 55.08%] [G loss: 0.727917]
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2609 [D loss: 0.679954, acc.: 56.05%] [G loss: 0.720602]
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2610 [D loss: 0.684591, acc.: 56.45%] [G loss: 0.711572]
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2611 [D loss: 0.684812, acc.: 54.30%] [G loss: 0.725601]
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2612 [D loss: 0.678471, acc.: 59.38%] [G loss: 0.724212]
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2613 [D loss: 0.683717, acc.: 58.40%] [G loss: 0.722097]
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2614 [D loss: 0.683310, acc.: 58.40%] [G loss: 0.724674]
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2615 [D loss: 0.686799, acc.: 54.88%] [G loss: 0.719664]
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2616 [D loss: 0.686621, acc.: 54.49%] [G loss: 0.724820]
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2617 [D loss: 0.685940, acc.: 55.08%] [G loss: 0.721260]
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2618 [D loss: 0.695201, acc.: 50.20%] [G loss: 0.731752]
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2619 [D loss: 0.682602, acc.: 56.05%] [G loss: 0.715714]
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2620 [D loss: 0.686386, acc.: 55.08%] [G loss: 0.721478]
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2621 [D loss: 0.680678, acc.: 55.47%] [G loss: 0.723507]
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2622 [D loss: 0.683058, acc.: 54.49%] [G loss: 0.729048]
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2623 [D loss: 0.686081, acc.: 56.64%] [G loss: 0.712881]
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2624 [D loss: 0.680946, acc.: 56.25%] [G loss: 0.733998]
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2625 [D loss: 0.680284, acc.: 57.62%] [G loss: 0.722283]
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2626 [D loss: 0.680251, acc.: 58.40%] [G loss: 0.724256]
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2627 [D loss: 0.674036, acc.: 60.55%] [G loss: 0.732142]
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2628 [D loss: 0.680690, acc.: 58.59%] [G loss: 0.727444]
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2629 [D loss: 0.694591, acc.: 51.17%] [G loss: 0.721225]
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2630 [D loss: 0.685004, acc.: 56.84%] [G loss: 0.717018]
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2631 [D loss: 0.682865, acc.: 54.69%] [G loss: 0.707824]
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2632 [D loss: 0.687072, acc.: 55.66%] [G loss: 0.709381]
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2633 [D loss: 0.681376, acc.: 58.79%] [G loss: 0.712850]
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2634 [D loss: 0.694343, acc.: 51.17%] [G loss: 0.719744]
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2635 [D loss: 0.684978, acc.: 54.30%] [G loss: 0.715850]
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2636 [D loss: 0.677858, acc.: 59.18%] [G loss: 0.710302]
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2637 [D loss: 0.681648, acc.: 55.86%] [G loss: 0.709549]
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2638 [D loss: 0.685328, acc.: 55.86%] [G loss: 0.717484]
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2639 [D loss: 0.688781, acc.: 52.73%] [G loss: 0.713852]
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2640 [D loss: 0.685788, acc.: 56.84%] [G loss: 0.718883]
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2641 [D loss: 0.685870, acc.: 56.64%] [G loss: 0.730167]
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2642 [D loss: 0.678938, acc.: 59.18%] [G loss: 0.732874]
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2643 [D loss: 0.678403, acc.: 59.57%] [G loss: 0.718957]
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2644 [D loss: 0.680737, acc.: 56.84%] [G loss: 0.716885]
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2645 [D loss: 0.692889, acc.: 52.73%] [G loss: 0.709568]
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2646 [D loss: 0.689622, acc.: 53.71%] [G loss: 0.705469]
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2647 [D loss: 0.695032, acc.: 51.37%] [G loss: 0.716280]
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2648 [D loss: 0.688799, acc.: 51.37%] [G loss: 0.716799]
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2649 [D loss: 0.685264, acc.: 57.03%] [G loss: 0.727342]
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2650 [D loss: 0.685239, acc.: 56.84%] [G loss: 0.742409]
1/1 [==============================] - 0s 16ms/step
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2651 [D loss: 0.688972, acc.: 55.08%] [G loss: 0.730706]
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2652 [D loss: 0.676294, acc.: 59.57%] [G loss: 0.734650]
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2653 [D loss: 0.686531, acc.: 54.10%] [G loss: 0.740677]
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2654 [D loss: 0.685444, acc.: 55.08%] [G loss: 0.727294]
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2655 [D loss: 0.680348, acc.: 58.79%] [G loss: 0.743430]
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2656 [D loss: 0.688580, acc.: 54.69%] [G loss: 0.729759]
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2657 [D loss: 0.685610, acc.: 57.42%] [G loss: 0.744751]
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2658 [D loss: 0.682660, acc.: 55.27%] [G loss: 0.726948]
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2659 [D loss: 0.685732, acc.: 55.86%] [G loss: 0.726984]
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2660 [D loss: 0.683268, acc.: 58.59%] [G loss: 0.727797]
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2661 [D loss: 0.685542, acc.: 56.84%] [G loss: 0.720444]
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2662 [D loss: 0.685404, acc.: 58.40%] [G loss: 0.730297]
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2663 [D loss: 0.688039, acc.: 54.49%] [G loss: 0.733571]
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2664 [D loss: 0.681609, acc.: 53.71%] [G loss: 0.735576]
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2665 [D loss: 0.688870, acc.: 53.32%] [G loss: 0.722804]
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2666 [D loss: 0.684909, acc.: 57.81%] [G loss: 0.720777]
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2667 [D loss: 0.681945, acc.: 56.45%] [G loss: 0.724772]
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2668 [D loss: 0.672754, acc.: 61.91%] [G loss: 0.722983]
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2669 [D loss: 0.682205, acc.: 57.62%] [G loss: 0.720227]
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2670 [D loss: 0.679552, acc.: 58.59%] [G loss: 0.718066]
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2671 [D loss: 0.690773, acc.: 53.91%] [G loss: 0.713387]
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2672 [D loss: 0.691159, acc.: 52.54%] [G loss: 0.721239]
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2673 [D loss: 0.684586, acc.: 57.81%] [G loss: 0.726660]
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2674 [D loss: 0.682138, acc.: 56.64%] [G loss: 0.723785]
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2675 [D loss: 0.680183, acc.: 57.42%] [G loss: 0.720724]
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2676 [D loss: 0.676060, acc.: 61.13%] [G loss: 0.731242]
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2677 [D loss: 0.669479, acc.: 60.35%] [G loss: 0.724133]
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2678 [D loss: 0.679940, acc.: 59.57%] [G loss: 0.723102]
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2679 [D loss: 0.676648, acc.: 59.38%] [G loss: 0.723045]
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2680 [D loss: 0.679185, acc.: 59.77%] [G loss: 0.717885]
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2681 [D loss: 0.689695, acc.: 56.05%] [G loss: 0.713002]
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2682 [D loss: 0.691357, acc.: 53.71%] [G loss: 0.700096]
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2683 [D loss: 0.686037, acc.: 53.71%] [G loss: 0.718472]
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2684 [D loss: 0.688192, acc.: 52.73%] [G loss: 0.712812]
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2685 [D loss: 0.694326, acc.: 49.80%] [G loss: 0.728867]
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2686 [D loss: 0.679276, acc.: 57.03%] [G loss: 0.734763]
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2687 [D loss: 0.685927, acc.: 55.47%] [G loss: 0.729217]
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2688 [D loss: 0.685639, acc.: 56.64%] [G loss: 0.729829]
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2689 [D loss: 0.676524, acc.: 58.98%] [G loss: 0.732290]
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2690 [D loss: 0.683868, acc.: 56.64%] [G loss: 0.743363]
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2691 [D loss: 0.681519, acc.: 54.88%] [G loss: 0.717490]
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2692 [D loss: 0.691638, acc.: 51.95%] [G loss: 0.729194]
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2693 [D loss: 0.688390, acc.: 51.95%] [G loss: 0.727993]
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2694 [D loss: 0.684480, acc.: 55.08%] [G loss: 0.726509]
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2695 [D loss: 0.685492, acc.: 54.30%] [G loss: 0.721692]
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2696 [D loss: 0.688191, acc.: 52.73%] [G loss: 0.727378]
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2697 [D loss: 0.685092, acc.: 54.10%] [G loss: 0.721106]
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2698 [D loss: 0.683300, acc.: 55.86%] [G loss: 0.726599]
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2699 [D loss: 0.675017, acc.: 60.94%] [G loss: 0.727379]
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2700 [D loss: 0.686067, acc.: 55.86%] [G loss: 0.732253]
1/1 [==============================] - 0s 16ms/step
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2701 [D loss: 0.682961, acc.: 57.62%] [G loss: 0.725294]
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2702 [D loss: 0.681184, acc.: 57.81%] [G loss: 0.724692]
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2703 [D loss: 0.688662, acc.: 52.93%] [G loss: 0.734851]
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2704 [D loss: 0.676112, acc.: 58.59%] [G loss: 0.739440]
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2705 [D loss: 0.678743, acc.: 57.23%] [G loss: 0.730800]
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2706 [D loss: 0.685418, acc.: 55.08%] [G loss: 0.726218]
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2707 [D loss: 0.688728, acc.: 53.71%] [G loss: 0.723596]
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2708 [D loss: 0.690402, acc.: 53.32%] [G loss: 0.726372]
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2709 [D loss: 0.682234, acc.: 55.86%] [G loss: 0.719618]
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2710 [D loss: 0.683397, acc.: 55.66%] [G loss: 0.723421]
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2711 [D loss: 0.683442, acc.: 57.23%] [G loss: 0.727799]
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2712 [D loss: 0.683269, acc.: 56.45%] [G loss: 0.735123]
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2713 [D loss: 0.691802, acc.: 51.17%] [G loss: 0.728304]
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2714 [D loss: 0.689381, acc.: 56.64%] [G loss: 0.735860]
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2715 [D loss: 0.685311, acc.: 55.66%] [G loss: 0.730752]
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2716 [D loss: 0.675599, acc.: 62.30%] [G loss: 0.730419]
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2717 [D loss: 0.683372, acc.: 56.84%] [G loss: 0.735697]
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2718 [D loss: 0.678828, acc.: 57.81%] [G loss: 0.722440]
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2719 [D loss: 0.688388, acc.: 54.10%] [G loss: 0.714059]
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2720 [D loss: 0.691954, acc.: 50.98%] [G loss: 0.718789]
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2721 [D loss: 0.694386, acc.: 50.20%] [G loss: 0.723997]
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2722 [D loss: 0.692995, acc.: 52.73%] [G loss: 0.722054]
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2723 [D loss: 0.680384, acc.: 58.59%] [G loss: 0.740386]
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2724 [D loss: 0.675732, acc.: 59.18%] [G loss: 0.752901]
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2725 [D loss: 0.668334, acc.: 59.18%] [G loss: 0.759579]
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2726 [D loss: 0.680497, acc.: 57.81%] [G loss: 0.749788]
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2727 [D loss: 0.690623, acc.: 52.93%] [G loss: 0.736777]
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2728 [D loss: 0.687196, acc.: 57.81%] [G loss: 0.729988]
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2729 [D loss: 0.689005, acc.: 52.54%] [G loss: 0.719128]
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2730 [D loss: 0.689036, acc.: 58.20%] [G loss: 0.715774]
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2731 [D loss: 0.683519, acc.: 55.66%] [G loss: 0.724945]
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2732 [D loss: 0.685778, acc.: 51.56%] [G loss: 0.714739]
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2733 [D loss: 0.687208, acc.: 54.30%] [G loss: 0.723036]
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2734 [D loss: 0.688572, acc.: 52.73%] [G loss: 0.731016]
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2735 [D loss: 0.676145, acc.: 61.52%] [G loss: 0.725013]
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2736 [D loss: 0.669749, acc.: 62.89%] [G loss: 0.728402]
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2737 [D loss: 0.669986, acc.: 62.50%] [G loss: 0.724210]
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2738 [D loss: 0.687324, acc.: 55.86%] [G loss: 0.722782]
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2739 [D loss: 0.691372, acc.: 53.71%] [G loss: 0.712208]
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2740 [D loss: 0.687111, acc.: 53.52%] [G loss: 0.720735]
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2741 [D loss: 0.679705, acc.: 57.81%] [G loss: 0.729114]
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2742 [D loss: 0.675537, acc.: 60.35%] [G loss: 0.718356]
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2743 [D loss: 0.679836, acc.: 58.59%] [G loss: 0.712038]
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2744 [D loss: 0.686146, acc.: 53.12%] [G loss: 0.704831]
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2745 [D loss: 0.687067, acc.: 56.25%] [G loss: 0.705920]
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2746 [D loss: 0.689022, acc.: 52.54%] [G loss: 0.711788]
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2747 [D loss: 0.689792, acc.: 54.49%] [G loss: 0.706278]
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2748 [D loss: 0.687772, acc.: 53.12%] [G loss: 0.717608]
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2749 [D loss: 0.684063, acc.: 58.01%] [G loss: 0.717041]
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2750 [D loss: 0.682968, acc.: 57.03%] [G loss: 0.716376]
1/1 [==============================] - 0s 16ms/step
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2751 [D loss: 0.690933, acc.: 52.93%] [G loss: 0.732237]
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2752 [D loss: 0.689784, acc.: 55.08%] [G loss: 0.727759]
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2753 [D loss: 0.689781, acc.: 52.54%] [G loss: 0.736130]
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2754 [D loss: 0.680328, acc.: 55.86%] [G loss: 0.725492]
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2755 [D loss: 0.678637, acc.: 58.98%] [G loss: 0.731822]
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2756 [D loss: 0.685773, acc.: 57.23%] [G loss: 0.735408]
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2757 [D loss: 0.688849, acc.: 55.27%] [G loss: 0.736114]
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2758 [D loss: 0.686734, acc.: 55.08%] [G loss: 0.728324]
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2759 [D loss: 0.687710, acc.: 54.88%] [G loss: 0.719796]
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2760 [D loss: 0.675996, acc.: 57.62%] [G loss: 0.734272]
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2761 [D loss: 0.683552, acc.: 56.84%] [G loss: 0.735229]
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2762 [D loss: 0.681163, acc.: 57.03%] [G loss: 0.734521]
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2763 [D loss: 0.685573, acc.: 57.42%] [G loss: 0.725898]
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2764 [D loss: 0.684595, acc.: 56.84%] [G loss: 0.725520]
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2765 [D loss: 0.686573, acc.: 55.27%] [G loss: 0.729940]
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2766 [D loss: 0.683163, acc.: 57.03%] [G loss: 0.733767]
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2767 [D loss: 0.682443, acc.: 54.30%] [G loss: 0.728024]
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2768 [D loss: 0.684684, acc.: 56.84%] [G loss: 0.728298]
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2769 [D loss: 0.689846, acc.: 53.91%] [G loss: 0.726957]
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2770 [D loss: 0.670828, acc.: 60.16%] [G loss: 0.735147]
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2771 [D loss: 0.675856, acc.: 59.77%] [G loss: 0.739847]
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2772 [D loss: 0.679453, acc.: 58.01%] [G loss: 0.739881]
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2773 [D loss: 0.679777, acc.: 56.64%] [G loss: 0.747216]
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2774 [D loss: 0.686777, acc.: 56.25%] [G loss: 0.732512]
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2775 [D loss: 0.684277, acc.: 57.03%] [G loss: 0.739067]
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2776 [D loss: 0.681574, acc.: 55.47%] [G loss: 0.727095]
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2777 [D loss: 0.676414, acc.: 59.38%] [G loss: 0.719951]
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2778 [D loss: 0.685237, acc.: 53.52%] [G loss: 0.722484]
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2779 [D loss: 0.684510, acc.: 53.91%] [G loss: 0.718134]
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2780 [D loss: 0.683580, acc.: 56.64%] [G loss: 0.714052]
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2781 [D loss: 0.691953, acc.: 51.95%] [G loss: 0.711947]
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2782 [D loss: 0.688525, acc.: 53.52%] [G loss: 0.730202]
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2783 [D loss: 0.683163, acc.: 55.27%] [G loss: 0.729630]
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2784 [D loss: 0.682423, acc.: 59.18%] [G loss: 0.725257]
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2785 [D loss: 0.686858, acc.: 52.93%] [G loss: 0.713064]
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2786 [D loss: 0.682182, acc.: 55.27%] [G loss: 0.728462]
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2787 [D loss: 0.679044, acc.: 57.03%] [G loss: 0.718810]
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2788 [D loss: 0.677356, acc.: 58.01%] [G loss: 0.728675]
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2789 [D loss: 0.678684, acc.: 58.59%] [G loss: 0.730365]
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2790 [D loss: 0.688260, acc.: 53.12%] [G loss: 0.720303]
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2791 [D loss: 0.677534, acc.: 58.79%] [G loss: 0.719136]
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2792 [D loss: 0.681812, acc.: 54.30%] [G loss: 0.718362]
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2793 [D loss: 0.681373, acc.: 53.71%] [G loss: 0.722816]
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2794 [D loss: 0.687101, acc.: 56.45%] [G loss: 0.723392]
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2795 [D loss: 0.678872, acc.: 59.18%] [G loss: 0.736194]
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2796 [D loss: 0.681053, acc.: 58.98%] [G loss: 0.718476]
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2797 [D loss: 0.682912, acc.: 57.23%] [G loss: 0.735086]
8/8 [==============================] - 0s 2ms/step
2798 [D loss: 0.688366, acc.: 54.10%] [G loss: 0.722127]
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2799 [D loss: 0.689262, acc.: 56.25%] [G loss: 0.714691]
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2800 [D loss: 0.690123, acc.: 55.08%] [G loss: 0.723733]
1/1 [==============================] - 0s 17ms/step
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2801 [D loss: 0.685965, acc.: 55.08%] [G loss: 0.729282]
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2802 [D loss: 0.684444, acc.: 55.08%] [G loss: 0.722073]
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2803 [D loss: 0.682817, acc.: 55.86%] [G loss: 0.719487]
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2804 [D loss: 0.680487, acc.: 57.81%] [G loss: 0.718992]
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2805 [D loss: 0.688455, acc.: 54.10%] [G loss: 0.721369]
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2806 [D loss: 0.696075, acc.: 47.66%] [G loss: 0.720309]
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2807 [D loss: 0.683823, acc.: 57.42%] [G loss: 0.727364]
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2808 [D loss: 0.676755, acc.: 58.79%] [G loss: 0.733529]
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2809 [D loss: 0.683254, acc.: 57.42%] [G loss: 0.743113]
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2810 [D loss: 0.680156, acc.: 59.57%] [G loss: 0.736635]
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2811 [D loss: 0.683677, acc.: 55.66%] [G loss: 0.723948]
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2812 [D loss: 0.689729, acc.: 53.52%] [G loss: 0.726840]
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2813 [D loss: 0.677824, acc.: 58.59%] [G loss: 0.732484]
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2814 [D loss: 0.678602, acc.: 57.42%] [G loss: 0.723471]
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2815 [D loss: 0.677013, acc.: 60.16%] [G loss: 0.732255]
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2816 [D loss: 0.682152, acc.: 55.47%] [G loss: 0.730887]
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2817 [D loss: 0.689228, acc.: 52.54%] [G loss: 0.723688]
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2818 [D loss: 0.687168, acc.: 55.66%] [G loss: 0.738991]
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2819 [D loss: 0.676565, acc.: 59.18%] [G loss: 0.737512]
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2820 [D loss: 0.678259, acc.: 57.42%] [G loss: 0.746039]
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2821 [D loss: 0.677509, acc.: 59.18%] [G loss: 0.740292]
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2822 [D loss: 0.686537, acc.: 53.52%] [G loss: 0.730550]
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2823 [D loss: 0.683415, acc.: 56.64%] [G loss: 0.725494]
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2824 [D loss: 0.682506, acc.: 55.27%] [G loss: 0.725906]
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2825 [D loss: 0.682005, acc.: 56.84%] [G loss: 0.733490]
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2826 [D loss: 0.674379, acc.: 57.42%] [G loss: 0.729392]
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2827 [D loss: 0.688674, acc.: 52.54%] [G loss: 0.718793]
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2828 [D loss: 0.682265, acc.: 56.64%] [G loss: 0.710130]
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2829 [D loss: 0.687695, acc.: 56.05%] [G loss: 0.712623]
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2830 [D loss: 0.689700, acc.: 51.95%] [G loss: 0.720781]
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2831 [D loss: 0.677992, acc.: 58.20%] [G loss: 0.724356]
8/8 [==============================] - 0s 2ms/step
2832 [D loss: 0.678492, acc.: 58.01%] [G loss: 0.729690]
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2833 [D loss: 0.677799, acc.: 56.45%] [G loss: 0.720556]
8/8 [==============================] - 0s 2ms/step
2834 [D loss: 0.690661, acc.: 53.91%] [G loss: 0.727145]
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2835 [D loss: 0.684034, acc.: 57.42%] [G loss: 0.726669]
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2836 [D loss: 0.691795, acc.: 53.12%] [G loss: 0.727421]
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2837 [D loss: 0.681747, acc.: 54.69%] [G loss: 0.734068]
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2838 [D loss: 0.679844, acc.: 56.64%] [G loss: 0.730775]
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2839 [D loss: 0.684965, acc.: 54.88%] [G loss: 0.736659]
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2840 [D loss: 0.679186, acc.: 57.03%] [G loss: 0.739083]
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2841 [D loss: 0.678879, acc.: 54.49%] [G loss: 0.733123]
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2842 [D loss: 0.684939, acc.: 53.52%] [G loss: 0.736829]
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2843 [D loss: 0.682365, acc.: 57.42%] [G loss: 0.736525]
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2844 [D loss: 0.681709, acc.: 57.03%] [G loss: 0.738607]
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2845 [D loss: 0.675580, acc.: 58.59%] [G loss: 0.737291]
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2846 [D loss: 0.683680, acc.: 54.69%] [G loss: 0.723041]
8/8 [==============================] - 0s 2ms/step
2847 [D loss: 0.681492, acc.: 56.84%] [G loss: 0.730142]
8/8 [==============================] - 0s 2ms/step
2848 [D loss: 0.690969, acc.: 54.69%] [G loss: 0.735105]
8/8 [==============================] - 0s 2ms/step
2849 [D loss: 0.675897, acc.: 61.91%] [G loss: 0.724944]
8/8 [==============================] - 0s 2ms/step
2850 [D loss: 0.681339, acc.: 55.66%] [G loss: 0.723020]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
2851 [D loss: 0.688598, acc.: 53.71%] [G loss: 0.739428]
8/8 [==============================] - 0s 2ms/step
2852 [D loss: 0.682114, acc.: 55.47%] [G loss: 0.724143]
8/8 [==============================] - 0s 2ms/step
2853 [D loss: 0.686493, acc.: 52.34%] [G loss: 0.739272]
8/8 [==============================] - 0s 2ms/step
2854 [D loss: 0.679224, acc.: 57.03%] [G loss: 0.742753]
8/8 [==============================] - 0s 2ms/step
2855 [D loss: 0.678225, acc.: 60.16%] [G loss: 0.760486]
8/8 [==============================] - 0s 2ms/step
2856 [D loss: 0.666813, acc.: 60.74%] [G loss: 0.751975]
8/8 [==============================] - 0s 2ms/step
2857 [D loss: 0.676194, acc.: 57.62%] [G loss: 0.744331]
8/8 [==============================] - 0s 2ms/step
2858 [D loss: 0.680420, acc.: 59.18%] [G loss: 0.732360]
8/8 [==============================] - 0s 2ms/step
2859 [D loss: 0.694196, acc.: 50.39%] [G loss: 0.724602]
8/8 [==============================] - 0s 2ms/step
2860 [D loss: 0.689929, acc.: 48.44%] [G loss: 0.715786]
8/8 [==============================] - 0s 2ms/step
2861 [D loss: 0.684066, acc.: 57.81%] [G loss: 0.725914]
8/8 [==============================] - 0s 2ms/step
2862 [D loss: 0.690327, acc.: 51.37%] [G loss: 0.728247]
8/8 [==============================] - 0s 2ms/step
2863 [D loss: 0.686349, acc.: 55.27%] [G loss: 0.714898]
8/8 [==============================] - 0s 2ms/step
2864 [D loss: 0.690217, acc.: 53.52%] [G loss: 0.725815]
8/8 [==============================] - 0s 2ms/step
2865 [D loss: 0.687240, acc.: 52.93%] [G loss: 0.714950]
8/8 [==============================] - 0s 2ms/step
2866 [D loss: 0.689179, acc.: 54.88%] [G loss: 0.725028]
8/8 [==============================] - 0s 2ms/step
2867 [D loss: 0.675825, acc.: 60.16%] [G loss: 0.731939]
8/8 [==============================] - 0s 2ms/step
2868 [D loss: 0.682810, acc.: 59.57%] [G loss: 0.732018]
8/8 [==============================] - 0s 2ms/step
2869 [D loss: 0.679941, acc.: 59.38%] [G loss: 0.731065]
8/8 [==============================] - 0s 2ms/step
2870 [D loss: 0.680535, acc.: 58.40%] [G loss: 0.724894]
8/8 [==============================] - 0s 2ms/step
2871 [D loss: 0.680097, acc.: 56.64%] [G loss: 0.736063]
8/8 [==============================] - 0s 2ms/step
2872 [D loss: 0.673527, acc.: 60.16%] [G loss: 0.740790]
8/8 [==============================] - 0s 2ms/step
2873 [D loss: 0.678133, acc.: 57.23%] [G loss: 0.736201]
8/8 [==============================] - 0s 2ms/step
2874 [D loss: 0.676414, acc.: 58.40%] [G loss: 0.746455]
8/8 [==============================] - 0s 2ms/step
2875 [D loss: 0.679221, acc.: 56.45%] [G loss: 0.736814]
8/8 [==============================] - 0s 2ms/step
2876 [D loss: 0.674197, acc.: 58.79%] [G loss: 0.723612]
8/8 [==============================] - 0s 2ms/step
2877 [D loss: 0.683809, acc.: 54.30%] [G loss: 0.733279]
8/8 [==============================] - 0s 2ms/step
2878 [D loss: 0.685565, acc.: 54.10%] [G loss: 0.731464]
8/8 [==============================] - 0s 2ms/step
2879 [D loss: 0.677650, acc.: 57.62%] [G loss: 0.725755]
8/8 [==============================] - 0s 2ms/step
2880 [D loss: 0.682724, acc.: 56.45%] [G loss: 0.737385]
8/8 [==============================] - 0s 2ms/step
2881 [D loss: 0.679653, acc.: 56.45%] [G loss: 0.730320]
8/8 [==============================] - 0s 2ms/step
2882 [D loss: 0.687427, acc.: 54.10%] [G loss: 0.731065]
8/8 [==============================] - 0s 2ms/step
2883 [D loss: 0.679542, acc.: 59.18%] [G loss: 0.735912]
8/8 [==============================] - 0s 2ms/step
2884 [D loss: 0.683248, acc.: 57.23%] [G loss: 0.737046]
8/8 [==============================] - 0s 2ms/step
2885 [D loss: 0.680706, acc.: 54.30%] [G loss: 0.720225]
8/8 [==============================] - 0s 2ms/step
2886 [D loss: 0.680496, acc.: 57.62%] [G loss: 0.730041]
8/8 [==============================] - 0s 2ms/step
2887 [D loss: 0.687308, acc.: 54.88%] [G loss: 0.724943]
8/8 [==============================] - 0s 2ms/step
2888 [D loss: 0.682879, acc.: 56.45%] [G loss: 0.728818]
8/8 [==============================] - 0s 2ms/step
2889 [D loss: 0.686083, acc.: 53.12%] [G loss: 0.724278]
8/8 [==============================] - 0s 2ms/step
2890 [D loss: 0.691468, acc.: 53.52%] [G loss: 0.717188]
8/8 [==============================] - 0s 2ms/step
2891 [D loss: 0.680155, acc.: 56.45%] [G loss: 0.725492]
8/8 [==============================] - 0s 2ms/step
2892 [D loss: 0.679594, acc.: 57.42%] [G loss: 0.722758]
8/8 [==============================] - 0s 2ms/step
2893 [D loss: 0.682228, acc.: 55.47%] [G loss: 0.736299]
8/8 [==============================] - 0s 2ms/step
2894 [D loss: 0.687216, acc.: 55.08%] [G loss: 0.720571]
8/8 [==============================] - 0s 2ms/step
2895 [D loss: 0.672560, acc.: 61.72%] [G loss: 0.726022]
8/8 [==============================] - 0s 2ms/step
2896 [D loss: 0.680203, acc.: 57.23%] [G loss: 0.729727]
8/8 [==============================] - 0s 2ms/step
2897 [D loss: 0.685107, acc.: 58.59%] [G loss: 0.733799]
8/8 [==============================] - 0s 2ms/step
2898 [D loss: 0.676936, acc.: 55.08%] [G loss: 0.723642]
8/8 [==============================] - 0s 2ms/step
2899 [D loss: 0.671722, acc.: 61.13%] [G loss: 0.714011]
8/8 [==============================] - 0s 2ms/step
2900 [D loss: 0.676497, acc.: 59.57%] [G loss: 0.730832]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 2ms/step
2901 [D loss: 0.684142, acc.: 55.66%] [G loss: 0.730700]
8/8 [==============================] - 0s 2ms/step
2902 [D loss: 0.683035, acc.: 56.84%] [G loss: 0.739298]
8/8 [==============================] - 0s 2ms/step
2903 [D loss: 0.673466, acc.: 57.42%] [G loss: 0.740461]
8/8 [==============================] - 0s 2ms/step
2904 [D loss: 0.682238, acc.: 56.64%] [G loss: 0.727811]
8/8 [==============================] - 0s 2ms/step
2905 [D loss: 0.684170, acc.: 55.27%] [G loss: 0.723609]
8/8 [==============================] - 0s 2ms/step
2906 [D loss: 0.688692, acc.: 54.49%] [G loss: 0.731895]
8/8 [==============================] - 0s 2ms/step
2907 [D loss: 0.675062, acc.: 57.23%] [G loss: 0.739797]
8/8 [==============================] - 0s 2ms/step
2908 [D loss: 0.675402, acc.: 59.77%] [G loss: 0.733990]
8/8 [==============================] - 0s 2ms/step
2909 [D loss: 0.680393, acc.: 56.25%] [G loss: 0.724969]
8/8 [==============================] - 0s 2ms/step
2910 [D loss: 0.679375, acc.: 55.86%] [G loss: 0.735682]
8/8 [==============================] - 0s 2ms/step
2911 [D loss: 0.682571, acc.: 54.88%] [G loss: 0.721858]
8/8 [==============================] - 0s 2ms/step
2912 [D loss: 0.680486, acc.: 56.84%] [G loss: 0.735258]
8/8 [==============================] - 0s 2ms/step
2913 [D loss: 0.685097, acc.: 55.08%] [G loss: 0.732873]
8/8 [==============================] - 0s 2ms/step
2914 [D loss: 0.676484, acc.: 58.79%] [G loss: 0.736707]
8/8 [==============================] - 0s 2ms/step
2915 [D loss: 0.684920, acc.: 55.47%] [G loss: 0.735266]
8/8 [==============================] - 0s 2ms/step
2916 [D loss: 0.689682, acc.: 52.54%] [G loss: 0.727679]
8/8 [==============================] - 0s 2ms/step
2917 [D loss: 0.679880, acc.: 56.84%] [G loss: 0.731432]
8/8 [==============================] - 0s 2ms/step
2918 [D loss: 0.689077, acc.: 53.91%] [G loss: 0.725435]
8/8 [==============================] - 0s 2ms/step
2919 [D loss: 0.679283, acc.: 60.16%] [G loss: 0.729551]
8/8 [==============================] - 0s 2ms/step
2920 [D loss: 0.679642, acc.: 55.86%] [G loss: 0.726650]
8/8 [==============================] - 0s 2ms/step
2921 [D loss: 0.679096, acc.: 59.18%] [G loss: 0.739683]
8/8 [==============================] - 0s 2ms/step
2922 [D loss: 0.677755, acc.: 59.77%] [G loss: 0.718425]
8/8 [==============================] - 0s 2ms/step
2923 [D loss: 0.674627, acc.: 61.13%] [G loss: 0.729532]
8/8 [==============================] - 0s 2ms/step
2924 [D loss: 0.677522, acc.: 59.18%] [G loss: 0.714964]
8/8 [==============================] - 0s 2ms/step
2925 [D loss: 0.679233, acc.: 60.94%] [G loss: 0.718431]
8/8 [==============================] - 0s 2ms/step
2926 [D loss: 0.680195, acc.: 56.45%] [G loss: 0.732686]
8/8 [==============================] - 0s 2ms/step
2927 [D loss: 0.684228, acc.: 58.01%] [G loss: 0.709434]
8/8 [==============================] - 0s 2ms/step
2928 [D loss: 0.678312, acc.: 59.38%] [G loss: 0.735211]
8/8 [==============================] - 0s 2ms/step
2929 [D loss: 0.685923, acc.: 55.66%] [G loss: 0.736490]
8/8 [==============================] - 0s 2ms/step
2930 [D loss: 0.676073, acc.: 56.45%] [G loss: 0.731643]
8/8 [==============================] - 0s 2ms/step
2931 [D loss: 0.682246, acc.: 56.64%] [G loss: 0.733091]
8/8 [==============================] - 0s 2ms/step
2932 [D loss: 0.677673, acc.: 56.05%] [G loss: 0.738088]
8/8 [==============================] - 0s 2ms/step
2933 [D loss: 0.687878, acc.: 54.69%] [G loss: 0.727615]
8/8 [==============================] - 0s 2ms/step
2934 [D loss: 0.683603, acc.: 54.10%] [G loss: 0.741510]
8/8 [==============================] - 0s 2ms/step
2935 [D loss: 0.686201, acc.: 55.47%] [G loss: 0.744228]
8/8 [==============================] - 0s 2ms/step
2936 [D loss: 0.682322, acc.: 56.05%] [G loss: 0.736807]
8/8 [==============================] - 0s 2ms/step
2937 [D loss: 0.675521, acc.: 58.59%] [G loss: 0.747188]
8/8 [==============================] - 0s 2ms/step
2938 [D loss: 0.677088, acc.: 56.45%] [G loss: 0.731888]
8/8 [==============================] - 0s 2ms/step
2939 [D loss: 0.688339, acc.: 51.37%] [G loss: 0.736233]
8/8 [==============================] - 0s 2ms/step
2940 [D loss: 0.685077, acc.: 54.69%] [G loss: 0.752113]
8/8 [==============================] - 0s 2ms/step
2941 [D loss: 0.684899, acc.: 54.69%] [G loss: 0.743934]
8/8 [==============================] - 0s 2ms/step
2942 [D loss: 0.670077, acc.: 60.74%] [G loss: 0.736504]
8/8 [==============================] - 0s 2ms/step
2943 [D loss: 0.680551, acc.: 58.98%] [G loss: 0.729082]
8/8 [==============================] - 0s 2ms/step
2944 [D loss: 0.677843, acc.: 54.88%] [G loss: 0.734680]
8/8 [==============================] - 0s 2ms/step
2945 [D loss: 0.687599, acc.: 52.73%] [G loss: 0.741585]
8/8 [==============================] - 0s 2ms/step
2946 [D loss: 0.679216, acc.: 57.42%] [G loss: 0.742336]
8/8 [==============================] - 0s 2ms/step
2947 [D loss: 0.683029, acc.: 55.66%] [G loss: 0.740320]
8/8 [==============================] - 0s 2ms/step
2948 [D loss: 0.678978, acc.: 59.96%] [G loss: 0.735138]
8/8 [==============================] - 0s 2ms/step
2949 [D loss: 0.687513, acc.: 53.52%] [G loss: 0.732434]
8/8 [==============================] - 0s 2ms/step
2950 [D loss: 0.675236, acc.: 60.16%] [G loss: 0.722700]
1/1 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 2ms/step
2951 [D loss: 0.673607, acc.: 59.96%] [G loss: 0.728479]
8/8 [==============================] - 0s 2ms/step
2952 [D loss: 0.679785, acc.: 55.27%] [G loss: 0.736756]
8/8 [==============================] - 0s 2ms/step
2953 [D loss: 0.679509, acc.: 57.62%] [G loss: 0.747987]
8/8 [==============================] - 0s 2ms/step
2954 [D loss: 0.677200, acc.: 57.81%] [G loss: 0.721637]
8/8 [==============================] - 0s 2ms/step
2955 [D loss: 0.669637, acc.: 60.74%] [G loss: 0.717614]
8/8 [==============================] - 0s 2ms/step
2956 [D loss: 0.686230, acc.: 53.71%] [G loss: 0.716070]
8/8 [==============================] - 0s 2ms/step
2957 [D loss: 0.690592, acc.: 52.54%] [G loss: 0.731591]
8/8 [==============================] - 0s 2ms/step
2958 [D loss: 0.682734, acc.: 57.03%] [G loss: 0.726115]
8/8 [==============================] - 0s 2ms/step
2959 [D loss: 0.684042, acc.: 57.81%] [G loss: 0.717728]
8/8 [==============================] - 0s 2ms/step
2960 [D loss: 0.680251, acc.: 58.59%] [G loss: 0.733495]
8/8 [==============================] - 0s 2ms/step
2961 [D loss: 0.674161, acc.: 59.57%] [G loss: 0.727767]
8/8 [==============================] - 0s 2ms/step
2962 [D loss: 0.680082, acc.: 57.81%] [G loss: 0.739569]
8/8 [==============================] - 0s 2ms/step
2963 [D loss: 0.676361, acc.: 56.25%] [G loss: 0.753264]
8/8 [==============================] - 0s 2ms/step
2964 [D loss: 0.678502, acc.: 58.98%] [G loss: 0.736477]
8/8 [==============================] - 0s 2ms/step
2965 [D loss: 0.674197, acc.: 58.59%] [G loss: 0.739962]
8/8 [==============================] - 0s 2ms/step
2966 [D loss: 0.680494, acc.: 58.98%] [G loss: 0.742693]
8/8 [==============================] - 0s 2ms/step
2967 [D loss: 0.679301, acc.: 56.84%] [G loss: 0.732572]
8/8 [==============================] - 0s 2ms/step
2968 [D loss: 0.677176, acc.: 57.42%] [G loss: 0.748239]
8/8 [==============================] - 0s 2ms/step
2969 [D loss: 0.679678, acc.: 58.01%] [G loss: 0.740076]
8/8 [==============================] - 0s 2ms/step
2970 [D loss: 0.684755, acc.: 54.88%] [G loss: 0.740602]
8/8 [==============================] - 0s 2ms/step
2971 [D loss: 0.684469, acc.: 53.52%] [G loss: 0.737874]
8/8 [==============================] - 0s 2ms/step
2972 [D loss: 0.684941, acc.: 55.66%] [G loss: 0.724456]
8/8 [==============================] - 0s 2ms/step
2973 [D loss: 0.677754, acc.: 56.45%] [G loss: 0.727751]
8/8 [==============================] - 0s 2ms/step
2974 [D loss: 0.680419, acc.: 57.23%] [G loss: 0.740806]
8/8 [==============================] - 0s 2ms/step
2975 [D loss: 0.678878, acc.: 55.47%] [G loss: 0.740893]
8/8 [==============================] - 0s 2ms/step
2976 [D loss: 0.679981, acc.: 58.40%] [G loss: 0.730281]
8/8 [==============================] - 0s 2ms/step
2977 [D loss: 0.684109, acc.: 53.12%] [G loss: 0.744551]
8/8 [==============================] - 0s 2ms/step
2978 [D loss: 0.680846, acc.: 57.42%] [G loss: 0.739716]
8/8 [==============================] - 0s 2ms/step
2979 [D loss: 0.682376, acc.: 58.98%] [G loss: 0.743080]
8/8 [==============================] - 0s 2ms/step
2980 [D loss: 0.683993, acc.: 55.27%] [G loss: 0.751500]
8/8 [==============================] - 0s 2ms/step
2981 [D loss: 0.673129, acc.: 58.20%] [G loss: 0.728489]
8/8 [==============================] - 0s 2ms/step
2982 [D loss: 0.677087, acc.: 59.77%] [G loss: 0.723861]
8/8 [==============================] - 0s 2ms/step
2983 [D loss: 0.679728, acc.: 56.45%] [G loss: 0.750059]
8/8 [==============================] - 0s 2ms/step
2984 [D loss: 0.679586, acc.: 57.03%] [G loss: 0.739923]
8/8 [==============================] - 0s 2ms/step
2985 [D loss: 0.687248, acc.: 54.88%] [G loss: 0.730563]
8/8 [==============================] - 0s 3ms/step
2986 [D loss: 0.679032, acc.: 55.86%] [G loss: 0.735626]
8/8 [==============================] - 0s 2ms/step
2987 [D loss: 0.680637, acc.: 57.23%] [G loss: 0.720515]
8/8 [==============================] - 0s 2ms/step
2988 [D loss: 0.682587, acc.: 57.81%] [G loss: 0.730696]
8/8 [==============================] - 0s 2ms/step
2989 [D loss: 0.678304, acc.: 59.57%] [G loss: 0.722374]
8/8 [==============================] - 0s 2ms/step
2990 [D loss: 0.672372, acc.: 59.18%] [G loss: 0.723715]
8/8 [==============================] - 0s 2ms/step
2991 [D loss: 0.683871, acc.: 59.38%] [G loss: 0.720834]
8/8 [==============================] - 0s 2ms/step
2992 [D loss: 0.674970, acc.: 58.79%] [G loss: 0.725751]
8/8 [==============================] - 0s 2ms/step
2993 [D loss: 0.681092, acc.: 56.05%] [G loss: 0.719340]
8/8 [==============================] - 0s 2ms/step
2994 [D loss: 0.691218, acc.: 50.98%] [G loss: 0.721510]
8/8 [==============================] - 0s 2ms/step
2995 [D loss: 0.674699, acc.: 58.40%] [G loss: 0.733926]
8/8 [==============================] - 0s 2ms/step
2996 [D loss: 0.680377, acc.: 56.45%] [G loss: 0.737268]
8/8 [==============================] - 0s 2ms/step
2997 [D loss: 0.683530, acc.: 56.05%] [G loss: 0.727683]
8/8 [==============================] - 0s 2ms/step
2998 [D loss: 0.684916, acc.: 55.86%] [G loss: 0.734156]
8/8 [==============================] - 0s 2ms/step
2999 [D loss: 0.684582, acc.: 54.88%] [G loss: 0.739142]

Plot Loss

plot_losses(dcgan.d_losses, dcgan.g_losses)

Plot Accuracy

plot_accuracy(dcgan.d_accuracy)

Generated Images at Different Epochs (Using ReLU for The Generator's Activation Function)

At 100 Epochs

At 1000 Epochs

At 2950 Epochs

Results

Initially, the generator loss is high, around 3, while the discriminator loss is low, around 0.3. As training progresses, the generator loss decreases and the discriminator loss increases, converging around 0.7. This indicates that the generator is getting better at producing realistic samples, making it harder for the discriminator to distinguish between real and generated data. The stabilization of losses suggests that the GAN has reached a balance.

The discriminator's accuracy starts at 99% but gradually decreases, fluctuating between 50% and 60%. This trend shows that as the generator improves, the discriminator finds it increasingly difficult to differentiate between real and fake samples, indicating the generator's outputs are becoming more convincing.

The generated images have improved in terms of sharpness. Previously, some of the images produced were quite blurry, but after changing the activation function of the generator, the images are now visually sharper. This change has helped the model produce clearer and more defined images, making the different classes easier to distinguish. This improvement in image quality suggests that the new activation function better captures the complex patterns and details require

Adding More Dense Units to The Generator

What changed from the previous model

• Dense units in the first Dense layer of the generator increased from 128 to 1500
• Number of epochs increased from 3000 to 10000

Why did we increase the number of dense units for the generator

We increased the number of dense units for the generator to enhance its capacity to learn and represent complex patterns in the data. With more dense units, the generator can capture a greater variety of features and nuances, which is essential for producing high-quality, detailed images.

Why did we increase the number of epochs

From the previous models, we observed that 3000 epochs were insufficient for the generator to fully learn the underlying patterns in the data. By increasing the number of epochs to 10000, we aim to provide the model with more training time to refine its outputs and improve image quality. This extended training period allows the generator to better capture the complexities of the dataset, leading to more realistic and detailed images.

class DCGAN():
    
    # this is the function to build the generator neural network
    def build_generator(self):
        model = Sequential()

        model.add(Dense(1500 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 1500)))
        
        model.add(UpSampling2D())
        model.add(Conv2D(128, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(UpSampling2D())
        model.add(Conv2D(64, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(Conv2D(self.channels, kernel_size=3, padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)
    
    def build_discriminator(self):
        model = Sequential(name='Discriminator')
        model.add(Conv2D(128, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Flatten())
        
        # Add one more dense layer
        model.add(Dense(256))  # Adjust the units as per your architecture needs
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        img = Input(shape=self.img_shape)
        validity = model(img)
        return Model(img, validity)
        
    def __init__(self, rows, cols, channels, z = 100):
        # Input shape
        self.img_rows = rows  # generated image height
        self.img_cols = cols  # generated image width
        self.channels = channels  # generated image channel
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = z  # the input is 1-D vector of noise
        # Reduce learning rate from 0.001 to 0.0002, and beta1 from 0.9 to 0.5, which can stablize training and reduce oscillation
        optimizer = Adam(learning_rate=0.0002, beta_1=0.5)
        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss='binary_crossentropy',
            optimizer=optimizer,
            metrics=['accuracy'])
        # Build the generator
        self.generator = self.build_generator()
        # The generator takes noise as input and generates images
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)
        # For the combined model we will only train the generator
        self.discriminator.trainable = False
        # The discriminator takes generated images as input and determines validity
        valid = self.discriminator(img)
        # The combined model (stacked generator and discriminator)
        # Trains the generator to fool the discriminator
        self.combined = Model(z, valid)
        self.combined.compile(loss='binary_crossentropy',
            optimizer=optimizer)
        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []
        
    def train(self, epochs, batch_size=128, save_interval=50):
        # Assuming your data is in a pandas DataFrame `df`
        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values  # assuming first column is labels, rest are pixels
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)  # reshape to image shape
        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))
        
        for epoch in range(epochs):
            # ---------------------
            # Train Discriminator
            # ---------------------
            # Select a random half of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs = X_train[idx]
            
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            gen_imgs = self.generator.predict(noise)
            
            # Train the discriminator (classify real images as 1 and generated images as 0)
            d_loss_real = self.discriminator.train_on_batch(imgs, valid)
            d_loss_fake = self.discriminator.train_on_batch(gen_imgs, fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)
            
            # ---------------------
            # Train Generator
            # ---------------------
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            
            # Train the generator (generator wants discriminator to predict generated images as 1)
            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            # Print progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100 * d_loss[1], g_loss))
            
            # If at save interval => save generated image samples
            if epoch % save_interval == 0:
                self.save_imgs(epoch)

    def save_imgs(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        # gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/dcgan', exist_ok=True)
        os.makedirs('generated_images/dcgan/generatorDenser', exist_ok=True)
        fig.savefig("generated_images/dcgan/generatorDenser/dcgan_{:d}.png".format(epoch))
        plt.close()

dcgan = DCGAN(28,28,1)
dcgan.train(epochs=10000, batch_size=256, save_interval=50)

Model: "Discriminator"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_17 (Conv2D)          (None, 14, 14, 128)       1280      
                                                                 
 leaky_re_lu_14 (LeakyReLU)  (None, 14, 14, 128)       0         
                                                                 
 dropout_8 (Dropout)         (None, 14, 14, 128)       0         
                                                                 
 conv2d_18 (Conv2D)          (None, 7, 7, 128)         147584    
                                                                 
 leaky_re_lu_15 (LeakyReLU)  (None, 7, 7, 128)         0         
                                                                 
 dropout_9 (Dropout)         (None, 7, 7, 128)         0         
                                                                 
 conv2d_19 (Conv2D)          (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_16 (LeakyReLU)  (None, 4, 4, 256)         0         
                                                                 
 dropout_10 (Dropout)        (None, 4, 4, 256)         0         
                                                                 
 flatten_3 (Flatten)         (None, 4096)              0         
                                                                 
 dense_8 (Dense)             (None, 256)               1048832   
                                                                 
 leaky_re_lu_17 (LeakyReLU)  (None, 256)               0         
                                                                 
 dense_9 (Dense)             (None, 1)                 257       
                                                                 
=================================================================
Total params: 1,493,121
Trainable params: 1,493,121
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_3"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_10 (Dense)            (None, 73500)             7423500   
                                                                 
 reshape_3 (Reshape)         (None, 7, 7, 1500)        0         
                                                                 
 up_sampling2d_6 (UpSampling  (None, 14, 14, 1500)     0         
 2D)                                                             
                                                                 
 conv2d_20 (Conv2D)          (None, 14, 14, 128)       1728128   
                                                                 
 batch_normalization_6 (Batc  (None, 14, 14, 128)      512       
 hNormalization)                                                 
                                                                 
 activation_5 (Activation)   (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_7 (UpSampling  (None, 28, 28, 128)      0         
 2D)                                                             
                                                                 
 conv2d_21 (Conv2D)          (None, 28, 28, 64)        73792     
                                                                 
 batch_normalization_7 (Batc  (None, 28, 28, 64)       256       
 hNormalization)                                                 
                                                                 
 activation_6 (Activation)   (None, 28, 28, 64)        0         
                                                                 
 conv2d_22 (Conv2D)          (None, 28, 28, 1)         577       
                                                                 
 activation_7 (Activation)   (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 9,226,765
Trainable params: 9,226,381
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 0s 4ms/step
0 [D loss: 0.738896, acc.: 31.84%] [G loss: 0.661677]
1/1 [==============================] - 0s 84ms/step
8/8 [==============================] - 0s 4ms/step
1 [D loss: 0.686949, acc.: 53.71%] [G loss: 0.712721]
8/8 [==============================] - 0s 4ms/step
2 [D loss: 0.654763, acc.: 97.66%] [G loss: 0.761778]
8/8 [==============================] - 0s 4ms/step
3 [D loss: 0.618117, acc.: 90.04%] [G loss: 0.810963]
8/8 [==============================] - 0s 4ms/step
4 [D loss: 0.575347, acc.: 82.03%] [G loss: 0.851170]
8/8 [==============================] - 0s 4ms/step
5 [D loss: 0.556624, acc.: 73.24%] [G loss: 0.808994]
8/8 [==============================] - 0s 4ms/step
6 [D loss: 0.527236, acc.: 81.25%] [G loss: 0.724829]
8/8 [==============================] - 0s 4ms/step
7 [D loss: 0.515918, acc.: 83.79%] [G loss: 0.626063]
8/8 [==============================] - 0s 4ms/step
8 [D loss: 0.493019, acc.: 87.89%] [G loss: 0.595478]
8/8 [==============================] - 0s 4ms/step
9 [D loss: 0.446843, acc.: 92.58%] [G loss: 0.543316]
8/8 [==============================] - 0s 4ms/step
10 [D loss: 0.387897, acc.: 96.29%] [G loss: 0.473762]
8/8 [==============================] - 0s 4ms/step
11 [D loss: 0.298978, acc.: 98.63%] [G loss: 0.424054]
8/8 [==============================] - 0s 4ms/step
12 [D loss: 0.223133, acc.: 99.41%] [G loss: 0.390012]
8/8 [==============================] - 0s 4ms/step
13 [D loss: 0.183362, acc.: 99.80%] [G loss: 0.398394]
8/8 [==============================] - 0s 4ms/step
14 [D loss: 0.115779, acc.: 99.61%] [G loss: 0.307967]
8/8 [==============================] - 0s 4ms/step
15 [D loss: 0.099795, acc.: 99.80%] [G loss: 0.309522]
8/8 [==============================] - 0s 4ms/step
16 [D loss: 0.098906, acc.: 99.22%] [G loss: 0.443558]
8/8 [==============================] - 0s 4ms/step
17 [D loss: 0.104019, acc.: 99.22%] [G loss: 0.197996]
8/8 [==============================] - 0s 4ms/step
18 [D loss: 0.053760, acc.: 100.00%] [G loss: 0.339361]
8/8 [==============================] - 0s 4ms/step
19 [D loss: 0.241811, acc.: 95.31%] [G loss: 1.584208]
8/8 [==============================] - 0s 4ms/step
20 [D loss: 0.352921, acc.: 88.48%] [G loss: 0.192546]
8/8 [==============================] - 0s 4ms/step
21 [D loss: 0.049233, acc.: 99.80%] [G loss: 0.086972]
8/8 [==============================] - 0s 4ms/step
22 [D loss: 0.065682, acc.: 99.80%] [G loss: 0.115748]
8/8 [==============================] - 0s 4ms/step
23 [D loss: 0.208656, acc.: 94.34%] [G loss: 1.474425]
8/8 [==============================] - 0s 4ms/step
24 [D loss: 1.950912, acc.: 32.42%] [G loss: 1.446525]
8/8 [==============================] - 0s 4ms/step
25 [D loss: 0.949277, acc.: 50.00%] [G loss: 0.807729]
8/8 [==============================] - 0s 4ms/step
26 [D loss: 0.871859, acc.: 38.87%] [G loss: 0.745275]
8/8 [==============================] - 0s 4ms/step
27 [D loss: 0.952570, acc.: 33.20%] [G loss: 0.794637]
8/8 [==============================] - 0s 4ms/step
28 [D loss: 1.093155, acc.: 27.73%] [G loss: 0.803499]
8/8 [==============================] - 0s 4ms/step
29 [D loss: 0.994839, acc.: 25.98%] [G loss: 0.857621]
8/8 [==============================] - 0s 4ms/step
30 [D loss: 0.854553, acc.: 28.52%] [G loss: 0.868261]
8/8 [==============================] - 0s 4ms/step
31 [D loss: 0.813590, acc.: 36.72%] [G loss: 0.822913]
8/8 [==============================] - 0s 4ms/step
32 [D loss: 0.800935, acc.: 38.87%] [G loss: 0.769670]
8/8 [==============================] - 0s 4ms/step
33 [D loss: 0.828644, acc.: 40.23%] [G loss: 0.737847]
8/8 [==============================] - 0s 4ms/step
34 [D loss: 0.835274, acc.: 36.33%] [G loss: 0.678786]
8/8 [==============================] - 0s 4ms/step
35 [D loss: 0.790628, acc.: 39.45%] [G loss: 0.622352]
8/8 [==============================] - 0s 4ms/step
36 [D loss: 0.787050, acc.: 39.65%] [G loss: 0.578679]
8/8 [==============================] - 0s 4ms/step
37 [D loss: 0.774708, acc.: 36.33%] [G loss: 0.543476]
8/8 [==============================] - 0s 4ms/step
38 [D loss: 0.764425, acc.: 39.06%] [G loss: 0.536526]
8/8 [==============================] - 0s 4ms/step
39 [D loss: 0.752409, acc.: 41.99%] [G loss: 0.528272]
8/8 [==============================] - 0s 4ms/step
40 [D loss: 0.732940, acc.: 43.75%] [G loss: 0.535800]
8/8 [==============================] - 0s 4ms/step
41 [D loss: 0.723357, acc.: 43.36%] [G loss: 0.535236]
8/8 [==============================] - 0s 4ms/step
42 [D loss: 0.731527, acc.: 42.97%] [G loss: 0.544879]
8/8 [==============================] - 0s 4ms/step
43 [D loss: 0.739818, acc.: 44.53%] [G loss: 0.549193]
8/8 [==============================] - 0s 4ms/step
44 [D loss: 0.754484, acc.: 44.53%] [G loss: 0.564941]
8/8 [==============================] - 0s 4ms/step
45 [D loss: 0.769315, acc.: 41.21%] [G loss: 0.583952]
8/8 [==============================] - 0s 4ms/step
46 [D loss: 0.755168, acc.: 40.43%] [G loss: 0.616277]
8/8 [==============================] - 0s 4ms/step
47 [D loss: 0.738274, acc.: 38.48%] [G loss: 0.649108]
8/8 [==============================] - 0s 4ms/step
48 [D loss: 0.724181, acc.: 34.38%] [G loss: 0.675715]
8/8 [==============================] - 0s 4ms/step
49 [D loss: 0.709686, acc.: 39.84%] [G loss: 0.708754]
8/8 [==============================] - 0s 4ms/step
50 [D loss: 0.697633, acc.: 47.27%] [G loss: 0.737438]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 4ms/step
51 [D loss: 0.682312, acc.: 62.89%] [G loss: 0.768289]
8/8 [==============================] - 0s 4ms/step
52 [D loss: 0.666608, acc.: 75.00%] [G loss: 0.790053]
8/8 [==============================] - 0s 4ms/step
53 [D loss: 0.655205, acc.: 76.95%] [G loss: 0.812141]
8/8 [==============================] - 0s 4ms/step
54 [D loss: 0.644511, acc.: 81.64%] [G loss: 0.831935]
8/8 [==============================] - 0s 4ms/step
55 [D loss: 0.632447, acc.: 81.05%] [G loss: 0.834877]
8/8 [==============================] - 0s 4ms/step
56 [D loss: 0.625216, acc.: 80.66%] [G loss: 0.838910]
8/8 [==============================] - 0s 4ms/step
57 [D loss: 0.628263, acc.: 79.30%] [G loss: 0.835292]
8/8 [==============================] - 0s 4ms/step
58 [D loss: 0.631641, acc.: 75.20%] [G loss: 0.814878]
8/8 [==============================] - 0s 4ms/step
59 [D loss: 0.626919, acc.: 71.29%] [G loss: 0.790712]
8/8 [==============================] - 0s 4ms/step
60 [D loss: 0.659537, acc.: 56.64%] [G loss: 0.755739]
8/8 [==============================] - 0s 4ms/step
61 [D loss: 0.678187, acc.: 46.29%] [G loss: 0.729284]
8/8 [==============================] - 0s 4ms/step
62 [D loss: 0.695490, acc.: 41.99%] [G loss: 0.709148]
8/8 [==============================] - 0s 4ms/step
63 [D loss: 0.701217, acc.: 39.65%] [G loss: 0.693754]
8/8 [==============================] - 0s 4ms/step
64 [D loss: 0.708586, acc.: 38.67%] [G loss: 0.682935]
8/8 [==============================] - 0s 4ms/step
65 [D loss: 0.712831, acc.: 36.72%] [G loss: 0.675492]
8/8 [==============================] - 0s 4ms/step
66 [D loss: 0.708279, acc.: 38.67%] [G loss: 0.671595]
8/8 [==============================] - 0s 4ms/step
67 [D loss: 0.694703, acc.: 40.82%] [G loss: 0.670833]
8/8 [==============================] - 0s 4ms/step
68 [D loss: 0.688226, acc.: 43.36%] [G loss: 0.663695]
8/8 [==============================] - 0s 4ms/step
69 [D loss: 0.681940, acc.: 45.51%] [G loss: 0.663810]
8/8 [==============================] - 0s 4ms/step
70 [D loss: 0.682418, acc.: 44.34%] [G loss: 0.659723]
8/8 [==============================] - 0s 4ms/step
71 [D loss: 0.685078, acc.: 43.16%] [G loss: 0.664227]
8/8 [==============================] - 0s 4ms/step
72 [D loss: 0.681529, acc.: 44.73%] [G loss: 0.667177]
8/8 [==============================] - 0s 4ms/step
73 [D loss: 0.680071, acc.: 45.70%] [G loss: 0.672783]
8/8 [==============================] - 0s 4ms/step
74 [D loss: 0.684625, acc.: 44.92%] [G loss: 0.676202]
8/8 [==============================] - 0s 4ms/step
75 [D loss: 0.685722, acc.: 45.70%] [G loss: 0.676543]
8/8 [==============================] - 0s 4ms/step
76 [D loss: 0.678256, acc.: 47.07%] [G loss: 0.677320]
8/8 [==============================] - 0s 4ms/step
77 [D loss: 0.675386, acc.: 49.41%] [G loss: 0.671065]
8/8 [==============================] - 0s 4ms/step
78 [D loss: 0.669434, acc.: 48.83%] [G loss: 0.677717]
8/8 [==============================] - 0s 4ms/step
79 [D loss: 0.666775, acc.: 53.12%] [G loss: 0.667079]
8/8 [==============================] - 0s 4ms/step
80 [D loss: 0.665534, acc.: 53.32%] [G loss: 0.667842]
8/8 [==============================] - 0s 4ms/step
81 [D loss: 0.665174, acc.: 52.15%] [G loss: 0.664205]
8/8 [==============================] - 0s 4ms/step
82 [D loss: 0.659384, acc.: 51.56%] [G loss: 0.673499]
8/8 [==============================] - 0s 4ms/step
83 [D loss: 0.671787, acc.: 50.98%] [G loss: 0.672759]
8/8 [==============================] - 0s 4ms/step
84 [D loss: 0.678070, acc.: 52.15%] [G loss: 0.672402]
8/8 [==============================] - 0s 4ms/step
85 [D loss: 0.680348, acc.: 49.61%] [G loss: 0.677655]
8/8 [==============================] - 0s 4ms/step
86 [D loss: 0.683000, acc.: 52.34%] [G loss: 0.697538]
8/8 [==============================] - 0s 4ms/step
87 [D loss: 0.680103, acc.: 53.12%] [G loss: 0.709467]
8/8 [==============================] - 0s 4ms/step
88 [D loss: 0.691940, acc.: 49.41%] [G loss: 0.723361]
8/8 [==============================] - 0s 4ms/step
89 [D loss: 0.686200, acc.: 54.49%] [G loss: 0.736486]
8/8 [==============================] - 0s 4ms/step
90 [D loss: 0.694956, acc.: 47.85%] [G loss: 0.734555]
8/8 [==============================] - 0s 4ms/step
91 [D loss: 0.686319, acc.: 53.91%] [G loss: 0.732046]
8/8 [==============================] - 0s 4ms/step
92 [D loss: 0.691578, acc.: 49.80%] [G loss: 0.720305]
8/8 [==============================] - 0s 4ms/step
93 [D loss: 0.694870, acc.: 48.83%] [G loss: 0.713375]
8/8 [==============================] - 0s 4ms/step
94 [D loss: 0.696031, acc.: 48.44%] [G loss: 0.695875]
8/8 [==============================] - 0s 4ms/step
95 [D loss: 0.714820, acc.: 41.41%] [G loss: 0.691652]
8/8 [==============================] - 0s 4ms/step
96 [D loss: 0.712751, acc.: 40.62%] [G loss: 0.677417]
8/8 [==============================] - 0s 4ms/step
97 [D loss: 0.712606, acc.: 45.12%] [G loss: 0.674056]
8/8 [==============================] - 0s 4ms/step
98 [D loss: 0.707241, acc.: 44.14%] [G loss: 0.675601]
8/8 [==============================] - 0s 4ms/step
99 [D loss: 0.697781, acc.: 49.41%] [G loss: 0.680391]
8/8 [==============================] - 0s 4ms/step
100 [D loss: 0.687715, acc.: 49.02%] [G loss: 0.678414]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 4ms/step
101 [D loss: 0.694699, acc.: 51.37%] [G loss: 0.683110]
8/8 [==============================] - 0s 4ms/step
102 [D loss: 0.701945, acc.: 45.90%] [G loss: 0.685262]
8/8 [==============================] - 0s 4ms/step
103 [D loss: 0.690209, acc.: 50.78%] [G loss: 0.687687]
8/8 [==============================] - 0s 4ms/step
104 [D loss: 0.692884, acc.: 48.44%] [G loss: 0.683047]
8/8 [==============================] - 0s 4ms/step
105 [D loss: 0.690914, acc.: 50.78%] [G loss: 0.683345]
8/8 [==============================] - 0s 4ms/step
106 [D loss: 0.700751, acc.: 46.88%] [G loss: 0.684611]
8/8 [==============================] - 0s 4ms/step
107 [D loss: 0.704031, acc.: 42.38%] [G loss: 0.680031]
8/8 [==============================] - 0s 4ms/step
108 [D loss: 0.710165, acc.: 39.65%] [G loss: 0.683612]
8/8 [==============================] - 0s 4ms/step
109 [D loss: 0.693949, acc.: 49.02%] [G loss: 0.706026]
8/8 [==============================] - 0s 4ms/step
110 [D loss: 0.700570, acc.: 47.66%] [G loss: 0.698775]
8/8 [==============================] - 0s 4ms/step
111 [D loss: 0.693854, acc.: 49.61%] [G loss: 0.709922]
8/8 [==============================] - 0s 4ms/step
112 [D loss: 0.691689, acc.: 50.39%] [G loss: 0.717036]
8/8 [==============================] - 0s 4ms/step
113 [D loss: 0.692050, acc.: 50.78%] [G loss: 0.718751]
8/8 [==============================] - 0s 4ms/step
114 [D loss: 0.684986, acc.: 57.23%] [G loss: 0.720571]
8/8 [==============================] - 0s 4ms/step
115 [D loss: 0.690094, acc.: 54.88%] [G loss: 0.719757]
8/8 [==============================] - 0s 4ms/step
116 [D loss: 0.691682, acc.: 51.95%] [G loss: 0.718981]
8/8 [==============================] - 0s 4ms/step
117 [D loss: 0.698249, acc.: 46.29%] [G loss: 0.701351]
8/8 [==============================] - 0s 4ms/step
118 [D loss: 0.704718, acc.: 46.29%] [G loss: 0.697814]
8/8 [==============================] - 0s 4ms/step
119 [D loss: 0.726334, acc.: 36.52%] [G loss: 0.694159]
8/8 [==============================] - 0s 4ms/step
120 [D loss: 0.723533, acc.: 35.16%] [G loss: 0.684143]
8/8 [==============================] - 0s 4ms/step
121 [D loss: 0.724663, acc.: 33.59%] [G loss: 0.676316]
8/8 [==============================] - 0s 4ms/step
122 [D loss: 0.733955, acc.: 28.32%] [G loss: 0.683347]
8/8 [==============================] - 0s 4ms/step
123 [D loss: 0.730699, acc.: 24.61%] [G loss: 0.684182]
8/8 [==============================] - 0s 4ms/step
124 [D loss: 0.722347, acc.: 30.86%] [G loss: 0.700363]
8/8 [==============================] - 0s 4ms/step
125 [D loss: 0.718344, acc.: 32.42%] [G loss: 0.710243]
8/8 [==============================] - 0s 4ms/step
126 [D loss: 0.710722, acc.: 35.94%] [G loss: 0.716103]
8/8 [==============================] - 0s 4ms/step
127 [D loss: 0.701132, acc.: 43.75%] [G loss: 0.726533]
8/8 [==============================] - 0s 4ms/step
128 [D loss: 0.698733, acc.: 46.88%] [G loss: 0.730879]
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129 [D loss: 0.694163, acc.: 50.78%] [G loss: 0.737134]
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130 [D loss: 0.685058, acc.: 59.38%] [G loss: 0.740986]
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131 [D loss: 0.684763, acc.: 58.01%] [G loss: 0.749415]
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132 [D loss: 0.678021, acc.: 62.70%] [G loss: 0.754265]
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133 [D loss: 0.677294, acc.: 62.70%] [G loss: 0.763713]
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134 [D loss: 0.670254, acc.: 66.80%] [G loss: 0.765171]
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135 [D loss: 0.662576, acc.: 69.92%] [G loss: 0.769054]
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136 [D loss: 0.663953, acc.: 65.04%] [G loss: 0.771338]
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137 [D loss: 0.665369, acc.: 65.04%] [G loss: 0.760894]
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138 [D loss: 0.662620, acc.: 63.28%] [G loss: 0.741645]
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139 [D loss: 0.668252, acc.: 61.52%] [G loss: 0.749078]
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140 [D loss: 0.674521, acc.: 55.86%] [G loss: 0.733139]
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141 [D loss: 0.676479, acc.: 56.64%] [G loss: 0.720865]
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142 [D loss: 0.676608, acc.: 57.03%] [G loss: 0.701969]
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143 [D loss: 0.703029, acc.: 47.07%] [G loss: 0.693411]
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144 [D loss: 0.692080, acc.: 46.68%] [G loss: 0.683717]
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145 [D loss: 0.697286, acc.: 45.12%] [G loss: 0.667839]
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146 [D loss: 0.709720, acc.: 39.65%] [G loss: 0.665154]
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147 [D loss: 0.713294, acc.: 41.80%] [G loss: 0.665599]
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148 [D loss: 0.718677, acc.: 35.35%] [G loss: 0.675474]
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149 [D loss: 0.723818, acc.: 35.74%] [G loss: 0.670618]
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151 [D loss: 0.715434, acc.: 36.72%] [G loss: 0.669546]
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152 [D loss: 0.710276, acc.: 38.48%] [G loss: 0.670632]
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153 [D loss: 0.717451, acc.: 35.74%] [G loss: 0.677359]
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154 [D loss: 0.713768, acc.: 33.59%] [G loss: 0.678390]
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155 [D loss: 0.707179, acc.: 35.74%] [G loss: 0.681739]
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156 [D loss: 0.708862, acc.: 36.33%] [G loss: 0.681604]
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157 [D loss: 0.708226, acc.: 33.59%] [G loss: 0.683168]
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158 [D loss: 0.704961, acc.: 37.89%] [G loss: 0.690826]
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159 [D loss: 0.700304, acc.: 42.19%] [G loss: 0.692526]
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160 [D loss: 0.699222, acc.: 41.41%] [G loss: 0.694600]
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161 [D loss: 0.698918, acc.: 45.51%] [G loss: 0.697059]
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162 [D loss: 0.696847, acc.: 46.88%] [G loss: 0.695059]
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163 [D loss: 0.691766, acc.: 51.95%] [G loss: 0.703982]
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164 [D loss: 0.690003, acc.: 53.32%] [G loss: 0.704053]
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165 [D loss: 0.687643, acc.: 54.69%] [G loss: 0.707789]
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166 [D loss: 0.687412, acc.: 56.64%] [G loss: 0.705644]
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167 [D loss: 0.684272, acc.: 57.62%] [G loss: 0.708287]
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168 [D loss: 0.682919, acc.: 58.79%] [G loss: 0.708803]
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169 [D loss: 0.680804, acc.: 58.59%] [G loss: 0.713908]
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170 [D loss: 0.676853, acc.: 61.33%] [G loss: 0.709217]
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171 [D loss: 0.676730, acc.: 62.11%] [G loss: 0.710125]
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172 [D loss: 0.678554, acc.: 59.57%] [G loss: 0.709512]
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173 [D loss: 0.676159, acc.: 58.40%] [G loss: 0.711750]
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174 [D loss: 0.682104, acc.: 55.66%] [G loss: 0.704149]
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175 [D loss: 0.679470, acc.: 58.40%] [G loss: 0.700678]
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176 [D loss: 0.689150, acc.: 51.76%] [G loss: 0.702623]
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177 [D loss: 0.687960, acc.: 54.10%] [G loss: 0.701003]
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178 [D loss: 0.682999, acc.: 58.79%] [G loss: 0.696163]
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179 [D loss: 0.692424, acc.: 52.93%] [G loss: 0.695323]
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180 [D loss: 0.701301, acc.: 49.02%] [G loss: 0.694787]
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181 [D loss: 0.697292, acc.: 52.15%] [G loss: 0.698060]
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182 [D loss: 0.707327, acc.: 45.31%] [G loss: 0.693310]
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183 [D loss: 0.710858, acc.: 39.26%] [G loss: 0.703654]
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184 [D loss: 0.714970, acc.: 36.72%] [G loss: 0.698618]
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185 [D loss: 0.708909, acc.: 41.99%] [G loss: 0.700092]
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186 [D loss: 0.708850, acc.: 38.48%] [G loss: 0.703081]
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187 [D loss: 0.710677, acc.: 38.67%] [G loss: 0.708692]
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188 [D loss: 0.712586, acc.: 32.81%] [G loss: 0.711833]
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189 [D loss: 0.711507, acc.: 37.30%] [G loss: 0.715136]
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190 [D loss: 0.707261, acc.: 39.26%] [G loss: 0.716320]
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191 [D loss: 0.707516, acc.: 37.11%] [G loss: 0.716622]
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192 [D loss: 0.704284, acc.: 40.23%] [G loss: 0.720405]
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193 [D loss: 0.703038, acc.: 42.77%] [G loss: 0.723916]
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194 [D loss: 0.701599, acc.: 40.23%] [G loss: 0.721742]
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195 [D loss: 0.697916, acc.: 45.90%] [G loss: 0.723125]
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196 [D loss: 0.700073, acc.: 42.19%] [G loss: 0.721395]
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197 [D loss: 0.700209, acc.: 41.21%] [G loss: 0.718298]
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198 [D loss: 0.700161, acc.: 41.80%] [G loss: 0.713656]
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199 [D loss: 0.696424, acc.: 48.44%] [G loss: 0.713572]
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200 [D loss: 0.699428, acc.: 44.92%] [G loss: 0.714130]
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201 [D loss: 0.697440, acc.: 45.90%] [G loss: 0.712838]
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202 [D loss: 0.697593, acc.: 46.09%] [G loss: 0.710837]
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203 [D loss: 0.695937, acc.: 45.51%] [G loss: 0.701966]
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204 [D loss: 0.697981, acc.: 41.80%] [G loss: 0.699057]
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205 [D loss: 0.697921, acc.: 42.97%] [G loss: 0.698322]
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206 [D loss: 0.701183, acc.: 38.48%] [G loss: 0.697468]
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207 [D loss: 0.701436, acc.: 39.45%] [G loss: 0.695961]
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208 [D loss: 0.700681, acc.: 39.26%] [G loss: 0.692249]
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209 [D loss: 0.702202, acc.: 36.72%] [G loss: 0.694665]
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210 [D loss: 0.699320, acc.: 40.62%] [G loss: 0.693745]
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211 [D loss: 0.701115, acc.: 37.50%] [G loss: 0.696915]
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212 [D loss: 0.697212, acc.: 43.16%] [G loss: 0.698657]
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213 [D loss: 0.698557, acc.: 45.51%] [G loss: 0.697597]
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214 [D loss: 0.697257, acc.: 42.19%] [G loss: 0.699950]
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215 [D loss: 0.695789, acc.: 48.44%] [G loss: 0.702165]
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216 [D loss: 0.692792, acc.: 52.15%] [G loss: 0.702516]
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217 [D loss: 0.691735, acc.: 52.34%] [G loss: 0.704574]
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218 [D loss: 0.692239, acc.: 53.32%] [G loss: 0.707618]
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219 [D loss: 0.690925, acc.: 55.47%] [G loss: 0.703446]
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220 [D loss: 0.689482, acc.: 54.30%] [G loss: 0.711198]
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221 [D loss: 0.689680, acc.: 58.40%] [G loss: 0.711078]
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222 [D loss: 0.691032, acc.: 55.47%] [G loss: 0.714833]
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223 [D loss: 0.688453, acc.: 55.27%] [G loss: 0.714852]
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224 [D loss: 0.685727, acc.: 62.50%] [G loss: 0.717018]
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225 [D loss: 0.684554, acc.: 60.94%] [G loss: 0.719759]
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226 [D loss: 0.682882, acc.: 61.13%] [G loss: 0.725226]
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227 [D loss: 0.680628, acc.: 64.65%] [G loss: 0.724400]
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228 [D loss: 0.683077, acc.: 60.74%] [G loss: 0.726082]
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229 [D loss: 0.685097, acc.: 58.59%] [G loss: 0.724014]
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230 [D loss: 0.680558, acc.: 60.74%] [G loss: 0.724499]
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231 [D loss: 0.684655, acc.: 58.01%] [G loss: 0.722103]
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232 [D loss: 0.686306, acc.: 56.84%] [G loss: 0.718891]
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233 [D loss: 0.688682, acc.: 53.71%] [G loss: 0.713168]
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234 [D loss: 0.690652, acc.: 50.20%] [G loss: 0.713337]
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235 [D loss: 0.694542, acc.: 50.39%] [G loss: 0.707183]
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236 [D loss: 0.692364, acc.: 52.54%] [G loss: 0.704133]
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237 [D loss: 0.700793, acc.: 44.14%] [G loss: 0.702106]
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238 [D loss: 0.700526, acc.: 45.70%] [G loss: 0.699725]
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239 [D loss: 0.696190, acc.: 47.07%] [G loss: 0.704655]
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240 [D loss: 0.704980, acc.: 39.84%] [G loss: 0.698185]
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241 [D loss: 0.701324, acc.: 43.55%] [G loss: 0.692730]
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242 [D loss: 0.709119, acc.: 38.09%] [G loss: 0.697545]
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243 [D loss: 0.705358, acc.: 40.43%] [G loss: 0.697085]
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244 [D loss: 0.706171, acc.: 39.84%] [G loss: 0.694506]
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245 [D loss: 0.703581, acc.: 39.65%] [G loss: 0.701544]
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246 [D loss: 0.704072, acc.: 42.58%] [G loss: 0.706213]
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247 [D loss: 0.706619, acc.: 39.26%] [G loss: 0.705410]
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248 [D loss: 0.703858, acc.: 40.43%] [G loss: 0.711873]
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249 [D loss: 0.702544, acc.: 42.58%] [G loss: 0.714108]
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250 [D loss: 0.695639, acc.: 49.80%] [G loss: 0.718778]
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251 [D loss: 0.693211, acc.: 52.93%] [G loss: 0.718434]
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252 [D loss: 0.694866, acc.: 50.78%] [G loss: 0.721764]
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253 [D loss: 0.693603, acc.: 51.17%] [G loss: 0.717292]
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254 [D loss: 0.689562, acc.: 52.93%] [G loss: 0.725498]
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255 [D loss: 0.691849, acc.: 50.39%] [G loss: 0.725303]
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256 [D loss: 0.688762, acc.: 55.08%] [G loss: 0.725141]
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257 [D loss: 0.692172, acc.: 51.56%] [G loss: 0.724790]
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258 [D loss: 0.689658, acc.: 52.15%] [G loss: 0.720428]
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259 [D loss: 0.694118, acc.: 50.78%] [G loss: 0.719875]
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260 [D loss: 0.695460, acc.: 50.98%] [G loss: 0.720194]
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261 [D loss: 0.690813, acc.: 55.08%] [G loss: 0.719904]
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262 [D loss: 0.695205, acc.: 47.85%] [G loss: 0.718385]
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263 [D loss: 0.695520, acc.: 46.48%] [G loss: 0.711215]
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264 [D loss: 0.694040, acc.: 48.83%] [G loss: 0.714793]
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265 [D loss: 0.697864, acc.: 42.38%] [G loss: 0.711647]
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266 [D loss: 0.699322, acc.: 43.36%] [G loss: 0.710821]
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267 [D loss: 0.697490, acc.: 46.68%] [G loss: 0.708534]
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268 [D loss: 0.701184, acc.: 43.75%] [G loss: 0.710340]
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269 [D loss: 0.700843, acc.: 41.60%] [G loss: 0.709872]
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270 [D loss: 0.698261, acc.: 43.36%] [G loss: 0.707956]
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271 [D loss: 0.703292, acc.: 39.65%] [G loss: 0.709347]
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272 [D loss: 0.699170, acc.: 42.38%] [G loss: 0.709149]
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273 [D loss: 0.698023, acc.: 45.90%] [G loss: 0.709548]
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274 [D loss: 0.700865, acc.: 41.60%] [G loss: 0.708272]
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275 [D loss: 0.698400, acc.: 48.44%] [G loss: 0.711282]
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276 [D loss: 0.701202, acc.: 43.16%] [G loss: 0.707772]
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277 [D loss: 0.699623, acc.: 44.53%] [G loss: 0.709013]
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278 [D loss: 0.699614, acc.: 43.75%] [G loss: 0.709265]
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279 [D loss: 0.699782, acc.: 43.75%] [G loss: 0.707259]
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280 [D loss: 0.698559, acc.: 43.36%] [G loss: 0.707779]
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281 [D loss: 0.701583, acc.: 40.62%] [G loss: 0.708997]
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282 [D loss: 0.700100, acc.: 39.84%] [G loss: 0.709024]
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283 [D loss: 0.701191, acc.: 41.02%] [G loss: 0.711076]
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284 [D loss: 0.701202, acc.: 40.62%] [G loss: 0.710470]
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285 [D loss: 0.701397, acc.: 41.99%] [G loss: 0.710571]
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286 [D loss: 0.701436, acc.: 41.41%] [G loss: 0.710599]
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287 [D loss: 0.698094, acc.: 44.34%] [G loss: 0.712843]
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288 [D loss: 0.699484, acc.: 43.36%] [G loss: 0.714436]
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289 [D loss: 0.701256, acc.: 40.62%] [G loss: 0.715842]
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290 [D loss: 0.698045, acc.: 43.75%] [G loss: 0.715997]
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291 [D loss: 0.696172, acc.: 47.07%] [G loss: 0.715995]
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292 [D loss: 0.696825, acc.: 46.29%] [G loss: 0.716646]
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293 [D loss: 0.699538, acc.: 43.95%] [G loss: 0.717471]
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294 [D loss: 0.699235, acc.: 45.70%] [G loss: 0.719320]
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295 [D loss: 0.697818, acc.: 46.48%] [G loss: 0.718519]
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296 [D loss: 0.695107, acc.: 52.15%] [G loss: 0.720799]
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297 [D loss: 0.695846, acc.: 48.24%] [G loss: 0.719096]
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298 [D loss: 0.695825, acc.: 47.66%] [G loss: 0.722703]
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301 [D loss: 0.696443, acc.: 48.44%] [G loss: 0.719910]
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303 [D loss: 0.696089, acc.: 47.66%] [G loss: 0.719755]
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306 [D loss: 0.695127, acc.: 47.66%] [G loss: 0.717127]
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311 [D loss: 0.695565, acc.: 45.31%] [G loss: 0.714233]
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312 [D loss: 0.695801, acc.: 50.20%] [G loss: 0.714297]
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313 [D loss: 0.696499, acc.: 45.31%] [G loss: 0.713794]
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314 [D loss: 0.695685, acc.: 47.07%] [G loss: 0.714620]
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315 [D loss: 0.696151, acc.: 47.66%] [G loss: 0.710929]
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316 [D loss: 0.694194, acc.: 49.02%] [G loss: 0.714459]
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317 [D loss: 0.696476, acc.: 46.48%] [G loss: 0.711303]
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318 [D loss: 0.694523, acc.: 48.44%] [G loss: 0.710104]
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319 [D loss: 0.695430, acc.: 48.24%] [G loss: 0.711622]
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320 [D loss: 0.693546, acc.: 49.61%] [G loss: 0.713255]
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321 [D loss: 0.694063, acc.: 50.59%] [G loss: 0.712471]
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322 [D loss: 0.692037, acc.: 51.95%] [G loss: 0.712629]
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323 [D loss: 0.693274, acc.: 51.17%] [G loss: 0.712065]
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324 [D loss: 0.694685, acc.: 49.02%] [G loss: 0.712099]
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325 [D loss: 0.694137, acc.: 48.63%] [G loss: 0.712501]
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326 [D loss: 0.695372, acc.: 49.22%] [G loss: 0.709617]
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327 [D loss: 0.694727, acc.: 46.88%] [G loss: 0.710996]
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328 [D loss: 0.692070, acc.: 53.12%] [G loss: 0.711230]
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329 [D loss: 0.692716, acc.: 50.00%] [G loss: 0.705611]
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330 [D loss: 0.693009, acc.: 51.95%] [G loss: 0.705723]
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331 [D loss: 0.693865, acc.: 50.59%] [G loss: 0.705637]
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332 [D loss: 0.690886, acc.: 52.93%] [G loss: 0.703792]
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333 [D loss: 0.693511, acc.: 49.41%] [G loss: 0.706304]
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334 [D loss: 0.694408, acc.: 49.22%] [G loss: 0.705299]
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335 [D loss: 0.694562, acc.: 48.63%] [G loss: 0.703564]
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336 [D loss: 0.695372, acc.: 50.20%] [G loss: 0.700555]
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337 [D loss: 0.692934, acc.: 50.20%] [G loss: 0.700344]
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338 [D loss: 0.689638, acc.: 55.86%] [G loss: 0.701645]
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339 [D loss: 0.695253, acc.: 48.24%] [G loss: 0.700864]
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340 [D loss: 0.696720, acc.: 43.75%] [G loss: 0.699596]
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341 [D loss: 0.694103, acc.: 47.46%] [G loss: 0.700013]
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342 [D loss: 0.697298, acc.: 44.73%] [G loss: 0.700440]
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343 [D loss: 0.693963, acc.: 49.22%] [G loss: 0.696693]
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344 [D loss: 0.696957, acc.: 43.95%] [G loss: 0.698034]
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345 [D loss: 0.695667, acc.: 45.12%] [G loss: 0.699866]
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346 [D loss: 0.696874, acc.: 45.51%] [G loss: 0.696762]
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347 [D loss: 0.697337, acc.: 42.38%] [G loss: 0.697839]
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348 [D loss: 0.694619, acc.: 48.63%] [G loss: 0.700482]
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349 [D loss: 0.697240, acc.: 44.92%] [G loss: 0.697528]
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350 [D loss: 0.696203, acc.: 46.88%] [G loss: 0.699779]
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351 [D loss: 0.696888, acc.: 44.92%] [G loss: 0.700403]
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352 [D loss: 0.698580, acc.: 43.95%] [G loss: 0.702196]
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353 [D loss: 0.698097, acc.: 44.92%] [G loss: 0.700272]
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354 [D loss: 0.698125, acc.: 42.97%] [G loss: 0.701897]
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355 [D loss: 0.696888, acc.: 41.60%] [G loss: 0.701274]
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356 [D loss: 0.696590, acc.: 43.95%] [G loss: 0.701969]
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357 [D loss: 0.696669, acc.: 43.75%] [G loss: 0.702293]
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358 [D loss: 0.697483, acc.: 42.77%] [G loss: 0.705106]
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359 [D loss: 0.697166, acc.: 43.55%] [G loss: 0.707333]
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360 [D loss: 0.696906, acc.: 43.75%] [G loss: 0.705717]
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361 [D loss: 0.696795, acc.: 46.09%] [G loss: 0.707783]
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362 [D loss: 0.695177, acc.: 47.07%] [G loss: 0.705617]
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363 [D loss: 0.695999, acc.: 45.12%] [G loss: 0.706255]
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364 [D loss: 0.696155, acc.: 46.68%] [G loss: 0.708778]
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365 [D loss: 0.696196, acc.: 45.31%] [G loss: 0.709649]
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366 [D loss: 0.695689, acc.: 47.07%] [G loss: 0.712487]
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367 [D loss: 0.693756, acc.: 49.22%] [G loss: 0.712615]
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368 [D loss: 0.694919, acc.: 50.78%] [G loss: 0.713806]
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369 [D loss: 0.693096, acc.: 52.34%] [G loss: 0.713660]
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370 [D loss: 0.692264, acc.: 54.10%] [G loss: 0.714909]
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371 [D loss: 0.693765, acc.: 52.54%] [G loss: 0.716100]
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372 [D loss: 0.692218, acc.: 54.10%] [G loss: 0.717669]
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373 [D loss: 0.691939, acc.: 53.91%] [G loss: 0.714171]
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374 [D loss: 0.691555, acc.: 54.69%] [G loss: 0.717952]
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375 [D loss: 0.693273, acc.: 51.17%] [G loss: 0.714827]
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376 [D loss: 0.691832, acc.: 54.10%] [G loss: 0.716317]
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377 [D loss: 0.692579, acc.: 54.10%] [G loss: 0.714181]
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378 [D loss: 0.693715, acc.: 52.73%] [G loss: 0.714558]
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379 [D loss: 0.696543, acc.: 46.68%] [G loss: 0.711572]
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380 [D loss: 0.692557, acc.: 52.34%] [G loss: 0.711130]
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381 [D loss: 0.694294, acc.: 50.20%] [G loss: 0.711905]
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382 [D loss: 0.696781, acc.: 46.88%] [G loss: 0.711311]
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383 [D loss: 0.697182, acc.: 46.48%] [G loss: 0.708936]
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384 [D loss: 0.697321, acc.: 42.97%] [G loss: 0.707998]
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385 [D loss: 0.696357, acc.: 46.29%] [G loss: 0.708799]
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386 [D loss: 0.697849, acc.: 43.75%] [G loss: 0.704747]
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387 [D loss: 0.699212, acc.: 41.21%] [G loss: 0.706433]
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388 [D loss: 0.700473, acc.: 42.38%] [G loss: 0.702658]
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389 [D loss: 0.699517, acc.: 41.41%] [G loss: 0.706865]
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390 [D loss: 0.701528, acc.: 37.89%] [G loss: 0.704033]
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391 [D loss: 0.699258, acc.: 43.16%] [G loss: 0.706293]
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392 [D loss: 0.699954, acc.: 38.28%] [G loss: 0.702640]
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393 [D loss: 0.701604, acc.: 37.30%] [G loss: 0.704594]
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394 [D loss: 0.700061, acc.: 39.26%] [G loss: 0.706949]
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395 [D loss: 0.698107, acc.: 42.97%] [G loss: 0.705708]
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396 [D loss: 0.701056, acc.: 41.02%] [G loss: 0.705908]
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397 [D loss: 0.700721, acc.: 38.87%] [G loss: 0.706207]
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398 [D loss: 0.699687, acc.: 40.62%] [G loss: 0.709304]
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399 [D loss: 0.698897, acc.: 43.95%] [G loss: 0.707739]
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400 [D loss: 0.699728, acc.: 40.23%] [G loss: 0.709096]
1/1 [==============================] - 0s 16ms/step
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401 [D loss: 0.699366, acc.: 41.80%] [G loss: 0.712329]
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402 [D loss: 0.697128, acc.: 44.92%] [G loss: 0.710186]
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403 [D loss: 0.697653, acc.: 45.12%] [G loss: 0.713960]
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404 [D loss: 0.694703, acc.: 47.66%] [G loss: 0.714100]
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405 [D loss: 0.697689, acc.: 41.21%] [G loss: 0.715191]
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406 [D loss: 0.696552, acc.: 47.07%] [G loss: 0.715770]
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407 [D loss: 0.694145, acc.: 47.85%] [G loss: 0.717956]
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408 [D loss: 0.694405, acc.: 48.05%] [G loss: 0.717995]
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409 [D loss: 0.693365, acc.: 51.17%] [G loss: 0.718852]
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410 [D loss: 0.691301, acc.: 50.98%] [G loss: 0.719951]
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411 [D loss: 0.693652, acc.: 50.20%] [G loss: 0.716964]
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412 [D loss: 0.691866, acc.: 53.32%] [G loss: 0.717839]
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413 [D loss: 0.691875, acc.: 51.56%] [G loss: 0.718845]
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414 [D loss: 0.693533, acc.: 48.44%] [G loss: 0.718136]
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415 [D loss: 0.692464, acc.: 48.63%] [G loss: 0.717946]
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416 [D loss: 0.692452, acc.: 51.37%] [G loss: 0.719278]
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417 [D loss: 0.692532, acc.: 47.46%] [G loss: 0.719320]
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418 [D loss: 0.691966, acc.: 50.00%] [G loss: 0.715944]
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419 [D loss: 0.692819, acc.: 49.22%] [G loss: 0.713504]
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420 [D loss: 0.694539, acc.: 48.44%] [G loss: 0.710033]
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421 [D loss: 0.694342, acc.: 45.90%] [G loss: 0.711274]
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422 [D loss: 0.694849, acc.: 48.83%] [G loss: 0.708089]
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423 [D loss: 0.695413, acc.: 47.07%] [G loss: 0.706157]
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424 [D loss: 0.696487, acc.: 43.36%] [G loss: 0.708378]
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425 [D loss: 0.695463, acc.: 46.68%] [G loss: 0.706837]
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426 [D loss: 0.698166, acc.: 41.41%] [G loss: 0.703879]
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427 [D loss: 0.696245, acc.: 45.31%] [G loss: 0.705439]
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428 [D loss: 0.698664, acc.: 41.41%] [G loss: 0.702788]
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429 [D loss: 0.699070, acc.: 38.28%] [G loss: 0.702418]
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430 [D loss: 0.698982, acc.: 41.21%] [G loss: 0.699455]
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431 [D loss: 0.697811, acc.: 44.14%] [G loss: 0.700899]
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432 [D loss: 0.698086, acc.: 42.19%] [G loss: 0.697863]
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433 [D loss: 0.697578, acc.: 42.58%] [G loss: 0.700691]
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434 [D loss: 0.696171, acc.: 42.77%] [G loss: 0.700383]
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435 [D loss: 0.697354, acc.: 41.02%] [G loss: 0.698945]
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436 [D loss: 0.695471, acc.: 45.31%] [G loss: 0.702669]
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437 [D loss: 0.696611, acc.: 45.70%] [G loss: 0.701856]
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438 [D loss: 0.697695, acc.: 41.41%] [G loss: 0.700324]
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439 [D loss: 0.693588, acc.: 49.41%] [G loss: 0.702446]
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440 [D loss: 0.695639, acc.: 46.29%] [G loss: 0.702534]
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441 [D loss: 0.695954, acc.: 46.68%] [G loss: 0.703884]
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442 [D loss: 0.696301, acc.: 44.53%] [G loss: 0.700799]
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443 [D loss: 0.696970, acc.: 43.55%] [G loss: 0.703153]
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444 [D loss: 0.693261, acc.: 50.59%] [G loss: 0.706640]
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445 [D loss: 0.693820, acc.: 49.02%] [G loss: 0.702904]
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446 [D loss: 0.694038, acc.: 48.24%] [G loss: 0.704470]
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447 [D loss: 0.694973, acc.: 48.63%] [G loss: 0.704792]
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448 [D loss: 0.693201, acc.: 50.39%] [G loss: 0.704019]
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449 [D loss: 0.696221, acc.: 46.48%] [G loss: 0.704790]
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450 [D loss: 0.693552, acc.: 51.76%] [G loss: 0.704131]
1/1 [==============================] - 0s 17ms/step
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451 [D loss: 0.695332, acc.: 47.27%] [G loss: 0.706181]
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452 [D loss: 0.694430, acc.: 49.22%] [G loss: 0.704846]
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453 [D loss: 0.694974, acc.: 47.27%] [G loss: 0.703610]
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454 [D loss: 0.697319, acc.: 44.53%] [G loss: 0.702421]
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455 [D loss: 0.696717, acc.: 45.90%] [G loss: 0.703915]
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456 [D loss: 0.697115, acc.: 44.92%] [G loss: 0.703045]
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457 [D loss: 0.696857, acc.: 45.12%] [G loss: 0.702447]
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458 [D loss: 0.696687, acc.: 46.29%] [G loss: 0.703369]
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459 [D loss: 0.696232, acc.: 44.73%] [G loss: 0.702710]
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460 [D loss: 0.698295, acc.: 43.36%] [G loss: 0.700981]
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461 [D loss: 0.697870, acc.: 41.99%] [G loss: 0.701122]
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462 [D loss: 0.698136, acc.: 39.26%] [G loss: 0.703695]
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463 [D loss: 0.696953, acc.: 44.92%] [G loss: 0.702460]
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464 [D loss: 0.696719, acc.: 44.34%] [G loss: 0.706516]
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465 [D loss: 0.698654, acc.: 41.02%] [G loss: 0.705962]
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466 [D loss: 0.697329, acc.: 46.48%] [G loss: 0.709139]
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467 [D loss: 0.697724, acc.: 42.77%] [G loss: 0.708442]
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468 [D loss: 0.696431, acc.: 44.73%] [G loss: 0.708437]
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469 [D loss: 0.695363, acc.: 48.44%] [G loss: 0.709813]
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470 [D loss: 0.695943, acc.: 47.27%] [G loss: 0.708997]
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471 [D loss: 0.694448, acc.: 50.59%] [G loss: 0.710096]
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472 [D loss: 0.695086, acc.: 48.05%] [G loss: 0.712993]
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473 [D loss: 0.693970, acc.: 49.02%] [G loss: 0.712216]
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474 [D loss: 0.694446, acc.: 49.41%] [G loss: 0.711892]
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475 [D loss: 0.694705, acc.: 46.29%] [G loss: 0.711401]
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476 [D loss: 0.695296, acc.: 46.88%] [G loss: 0.714216]
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477 [D loss: 0.691575, acc.: 53.32%] [G loss: 0.716828]
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478 [D loss: 0.693127, acc.: 50.20%] [G loss: 0.715816]
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479 [D loss: 0.693479, acc.: 49.61%] [G loss: 0.714590]
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480 [D loss: 0.694549, acc.: 48.63%] [G loss: 0.715836]
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481 [D loss: 0.694930, acc.: 48.05%] [G loss: 0.715695]
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482 [D loss: 0.694024, acc.: 49.80%] [G loss: 0.714636]
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483 [D loss: 0.694138, acc.: 48.63%] [G loss: 0.714246]
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484 [D loss: 0.695689, acc.: 48.83%] [G loss: 0.714222]
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485 [D loss: 0.695658, acc.: 48.05%] [G loss: 0.712008]
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486 [D loss: 0.695665, acc.: 49.41%] [G loss: 0.710062]
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487 [D loss: 0.696376, acc.: 45.70%] [G loss: 0.709638]
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488 [D loss: 0.695366, acc.: 45.90%] [G loss: 0.709593]
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489 [D loss: 0.694873, acc.: 48.83%] [G loss: 0.708553]
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490 [D loss: 0.697284, acc.: 42.58%] [G loss: 0.708161]
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491 [D loss: 0.696294, acc.: 47.27%] [G loss: 0.706930]
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492 [D loss: 0.696889, acc.: 44.14%] [G loss: 0.707616]
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493 [D loss: 0.697153, acc.: 42.97%] [G loss: 0.705825]
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494 [D loss: 0.696862, acc.: 43.55%] [G loss: 0.703667]
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495 [D loss: 0.696557, acc.: 44.14%] [G loss: 0.705569]
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496 [D loss: 0.698466, acc.: 41.80%] [G loss: 0.703813]
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497 [D loss: 0.696956, acc.: 43.16%] [G loss: 0.702273]
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498 [D loss: 0.697537, acc.: 41.60%] [G loss: 0.701443]
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499 [D loss: 0.697958, acc.: 41.02%] [G loss: 0.704245]
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500 [D loss: 0.697883, acc.: 41.80%] [G loss: 0.702092]
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501 [D loss: 0.698121, acc.: 40.43%] [G loss: 0.701883]
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502 [D loss: 0.697626, acc.: 39.06%] [G loss: 0.702880]
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503 [D loss: 0.698430, acc.: 36.72%] [G loss: 0.702081]
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504 [D loss: 0.696545, acc.: 41.80%] [G loss: 0.703584]
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505 [D loss: 0.699128, acc.: 38.87%] [G loss: 0.704293]
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506 [D loss: 0.696831, acc.: 42.58%] [G loss: 0.704093]
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507 [D loss: 0.696402, acc.: 43.95%] [G loss: 0.705729]
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508 [D loss: 0.695353, acc.: 45.31%] [G loss: 0.706171]
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509 [D loss: 0.695619, acc.: 45.12%] [G loss: 0.707404]
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510 [D loss: 0.694742, acc.: 47.27%] [G loss: 0.707205]
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511 [D loss: 0.694550, acc.: 47.27%] [G loss: 0.708999]
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512 [D loss: 0.693802, acc.: 50.98%] [G loss: 0.708668]
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513 [D loss: 0.693520, acc.: 50.00%] [G loss: 0.711183]
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514 [D loss: 0.692546, acc.: 52.73%] [G loss: 0.711706]
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515 [D loss: 0.692638, acc.: 52.54%] [G loss: 0.711976]
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516 [D loss: 0.694130, acc.: 49.02%] [G loss: 0.709052]
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517 [D loss: 0.692639, acc.: 51.95%] [G loss: 0.710818]
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518 [D loss: 0.693042, acc.: 51.17%] [G loss: 0.709875]
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519 [D loss: 0.692051, acc.: 52.34%] [G loss: 0.709062]
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520 [D loss: 0.692341, acc.: 54.88%] [G loss: 0.707906]
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521 [D loss: 0.691734, acc.: 57.23%] [G loss: 0.707147]
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522 [D loss: 0.691396, acc.: 54.88%] [G loss: 0.706549]
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523 [D loss: 0.691400, acc.: 54.10%] [G loss: 0.703791]
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524 [D loss: 0.691998, acc.: 51.76%] [G loss: 0.705887]
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525 [D loss: 0.690559, acc.: 54.88%] [G loss: 0.703853]
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526 [D loss: 0.693824, acc.: 48.63%] [G loss: 0.701679]
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527 [D loss: 0.692006, acc.: 52.93%] [G loss: 0.698827]
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528 [D loss: 0.694661, acc.: 48.24%] [G loss: 0.698882]
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529 [D loss: 0.694244, acc.: 50.00%] [G loss: 0.697876]
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530 [D loss: 0.694976, acc.: 48.44%] [G loss: 0.695347]
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531 [D loss: 0.693169, acc.: 52.54%] [G loss: 0.695368]
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532 [D loss: 0.694692, acc.: 49.61%] [G loss: 0.692926]
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533 [D loss: 0.695083, acc.: 48.83%] [G loss: 0.693277]
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534 [D loss: 0.695324, acc.: 48.44%] [G loss: 0.692461]
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535 [D loss: 0.696955, acc.: 47.46%] [G loss: 0.695186]
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536 [D loss: 0.695904, acc.: 46.09%] [G loss: 0.700293]
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537 [D loss: 0.696153, acc.: 45.70%] [G loss: 0.694843]
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538 [D loss: 0.695389, acc.: 47.66%] [G loss: 0.696969]
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539 [D loss: 0.695136, acc.: 46.09%] [G loss: 0.697513]
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540 [D loss: 0.695417, acc.: 49.02%] [G loss: 0.696945]
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541 [D loss: 0.694332, acc.: 48.24%] [G loss: 0.700736]
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542 [D loss: 0.695380, acc.: 46.88%] [G loss: 0.698803]
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543 [D loss: 0.693854, acc.: 51.56%] [G loss: 0.699240]
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544 [D loss: 0.693858, acc.: 50.00%] [G loss: 0.700027]
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545 [D loss: 0.694076, acc.: 50.20%] [G loss: 0.702066]
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546 [D loss: 0.694503, acc.: 47.66%] [G loss: 0.702697]
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547 [D loss: 0.692183, acc.: 53.12%] [G loss: 0.705093]
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548 [D loss: 0.693167, acc.: 51.76%] [G loss: 0.707555]
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549 [D loss: 0.691427, acc.: 54.30%] [G loss: 0.708856]
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550 [D loss: 0.691328, acc.: 53.91%] [G loss: 0.710683]
1/1 [==============================] - 0s 16ms/step
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551 [D loss: 0.691984, acc.: 53.71%] [G loss: 0.710541]
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552 [D loss: 0.689863, acc.: 55.86%] [G loss: 0.713491]
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553 [D loss: 0.689747, acc.: 54.69%] [G loss: 0.715816]
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554 [D loss: 0.689785, acc.: 57.03%] [G loss: 0.717209]
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555 [D loss: 0.690141, acc.: 55.08%] [G loss: 0.717033]
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556 [D loss: 0.690377, acc.: 52.93%] [G loss: 0.720125]
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557 [D loss: 0.690903, acc.: 52.93%] [G loss: 0.717342]
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558 [D loss: 0.692254, acc.: 50.98%] [G loss: 0.719812]
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559 [D loss: 0.695413, acc.: 49.41%] [G loss: 0.716929]
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560 [D loss: 0.697001, acc.: 46.09%] [G loss: 0.713671]
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561 [D loss: 0.699358, acc.: 42.38%] [G loss: 0.711505]
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562 [D loss: 0.703975, acc.: 37.50%] [G loss: 0.705798]
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563 [D loss: 0.700632, acc.: 40.43%] [G loss: 0.704534]
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564 [D loss: 0.704980, acc.: 35.55%] [G loss: 0.700467]
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565 [D loss: 0.703526, acc.: 34.96%] [G loss: 0.702870]
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566 [D loss: 0.699342, acc.: 40.82%] [G loss: 0.702296]
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567 [D loss: 0.702125, acc.: 37.50%] [G loss: 0.703406]
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568 [D loss: 0.700995, acc.: 36.91%] [G loss: 0.701361]
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569 [D loss: 0.698749, acc.: 41.60%] [G loss: 0.705241]
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570 [D loss: 0.700354, acc.: 37.50%] [G loss: 0.703983]
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571 [D loss: 0.698612, acc.: 41.99%] [G loss: 0.705239]
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572 [D loss: 0.696635, acc.: 41.80%] [G loss: 0.710213]
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573 [D loss: 0.697205, acc.: 39.84%] [G loss: 0.710030]
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574 [D loss: 0.696065, acc.: 44.73%] [G loss: 0.713992]
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575 [D loss: 0.695184, acc.: 44.14%] [G loss: 0.714861]
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576 [D loss: 0.693158, acc.: 47.07%] [G loss: 0.716427]
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577 [D loss: 0.693858, acc.: 47.66%] [G loss: 0.718039]
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578 [D loss: 0.693178, acc.: 49.02%] [G loss: 0.719491]
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579 [D loss: 0.691935, acc.: 51.56%] [G loss: 0.720226]
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580 [D loss: 0.690955, acc.: 51.17%] [G loss: 0.723527]
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581 [D loss: 0.690524, acc.: 54.30%] [G loss: 0.723290]
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582 [D loss: 0.690809, acc.: 55.66%] [G loss: 0.725911]
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583 [D loss: 0.690533, acc.: 53.32%] [G loss: 0.725486]
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584 [D loss: 0.688997, acc.: 53.91%] [G loss: 0.726710]
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585 [D loss: 0.689838, acc.: 55.47%] [G loss: 0.727407]
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586 [D loss: 0.690489, acc.: 55.47%] [G loss: 0.725686]
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587 [D loss: 0.691185, acc.: 54.88%] [G loss: 0.725565]
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588 [D loss: 0.689479, acc.: 53.71%] [G loss: 0.724080]
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589 [D loss: 0.691289, acc.: 52.54%] [G loss: 0.719276]
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590 [D loss: 0.690025, acc.: 52.93%] [G loss: 0.718688]
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591 [D loss: 0.695598, acc.: 50.20%] [G loss: 0.720619]
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592 [D loss: 0.695437, acc.: 49.22%] [G loss: 0.717546]
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593 [D loss: 0.695364, acc.: 47.27%] [G loss: 0.714400]
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594 [D loss: 0.696838, acc.: 44.73%] [G loss: 0.713171]
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595 [D loss: 0.695612, acc.: 45.70%] [G loss: 0.712247]
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596 [D loss: 0.697857, acc.: 43.95%] [G loss: 0.707810]
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597 [D loss: 0.698920, acc.: 41.99%] [G loss: 0.704683]
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598 [D loss: 0.697842, acc.: 44.34%] [G loss: 0.708110]
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599 [D loss: 0.698857, acc.: 42.97%] [G loss: 0.704936]
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600 [D loss: 0.697414, acc.: 40.82%] [G loss: 0.706452]
1/1 [==============================] - 0s 17ms/step
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601 [D loss: 0.697344, acc.: 45.70%] [G loss: 0.705357]
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602 [D loss: 0.698848, acc.: 43.16%] [G loss: 0.707236]
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603 [D loss: 0.699468, acc.: 39.84%] [G loss: 0.705930]
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604 [D loss: 0.697638, acc.: 45.12%] [G loss: 0.705986]
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605 [D loss: 0.697327, acc.: 43.95%] [G loss: 0.706870]
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606 [D loss: 0.695703, acc.: 47.46%] [G loss: 0.707686]
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607 [D loss: 0.697309, acc.: 43.75%] [G loss: 0.707496]
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608 [D loss: 0.696377, acc.: 45.31%] [G loss: 0.707454]
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609 [D loss: 0.696147, acc.: 44.73%] [G loss: 0.708463]
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610 [D loss: 0.694913, acc.: 46.68%] [G loss: 0.711026]
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611 [D loss: 0.695194, acc.: 48.63%] [G loss: 0.710522]
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612 [D loss: 0.694537, acc.: 47.85%] [G loss: 0.710402]
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613 [D loss: 0.693562, acc.: 50.59%] [G loss: 0.710859]
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614 [D loss: 0.694698, acc.: 48.24%] [G loss: 0.710766]
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615 [D loss: 0.693950, acc.: 48.24%] [G loss: 0.712359]
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616 [D loss: 0.694118, acc.: 48.05%] [G loss: 0.711309]
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617 [D loss: 0.693084, acc.: 50.00%] [G loss: 0.711440]
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618 [D loss: 0.693839, acc.: 47.07%] [G loss: 0.713174]
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619 [D loss: 0.693757, acc.: 49.80%] [G loss: 0.714495]
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620 [D loss: 0.693075, acc.: 47.46%] [G loss: 0.715364]
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621 [D loss: 0.693284, acc.: 49.61%] [G loss: 0.715504]
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622 [D loss: 0.693246, acc.: 50.00%] [G loss: 0.715117]
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623 [D loss: 0.690775, acc.: 52.93%] [G loss: 0.714217]
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624 [D loss: 0.691350, acc.: 50.78%] [G loss: 0.715475]
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625 [D loss: 0.692364, acc.: 50.98%] [G loss: 0.718695]
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626 [D loss: 0.691879, acc.: 53.32%] [G loss: 0.719129]
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627 [D loss: 0.692361, acc.: 54.30%] [G loss: 0.718028]
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628 [D loss: 0.691461, acc.: 53.52%] [G loss: 0.719087]
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629 [D loss: 0.691095, acc.: 54.10%] [G loss: 0.716920]
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630 [D loss: 0.691697, acc.: 51.95%] [G loss: 0.718422]
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631 [D loss: 0.691836, acc.: 51.56%] [G loss: 0.719208]
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632 [D loss: 0.690372, acc.: 56.45%] [G loss: 0.720355]
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633 [D loss: 0.691550, acc.: 53.52%] [G loss: 0.717751]
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634 [D loss: 0.692104, acc.: 52.93%] [G loss: 0.716087]
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635 [D loss: 0.692417, acc.: 53.91%] [G loss: 0.717034]
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636 [D loss: 0.692814, acc.: 57.03%] [G loss: 0.714900]
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637 [D loss: 0.693388, acc.: 50.20%] [G loss: 0.712170]
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638 [D loss: 0.695090, acc.: 48.44%] [G loss: 0.713041]
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639 [D loss: 0.694932, acc.: 48.44%] [G loss: 0.707743]
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640 [D loss: 0.695729, acc.: 44.53%] [G loss: 0.708829]
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641 [D loss: 0.695916, acc.: 45.90%] [G loss: 0.707002]
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642 [D loss: 0.694712, acc.: 48.24%] [G loss: 0.706637]
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643 [D loss: 0.696291, acc.: 46.88%] [G loss: 0.701963]
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644 [D loss: 0.695128, acc.: 45.12%] [G loss: 0.707633]
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645 [D loss: 0.694929, acc.: 47.46%] [G loss: 0.704417]
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646 [D loss: 0.695562, acc.: 44.14%] [G loss: 0.700997]
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647 [D loss: 0.696840, acc.: 40.82%] [G loss: 0.700384]
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648 [D loss: 0.695284, acc.: 46.88%] [G loss: 0.703355]
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649 [D loss: 0.695476, acc.: 50.20%] [G loss: 0.700062]
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650 [D loss: 0.696197, acc.: 43.75%] [G loss: 0.702394]
1/1 [==============================] - 0s 18ms/step
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651 [D loss: 0.695549, acc.: 44.14%] [G loss: 0.700069]
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652 [D loss: 0.696196, acc.: 42.58%] [G loss: 0.701076]
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653 [D loss: 0.695495, acc.: 46.88%] [G loss: 0.700653]
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654 [D loss: 0.695399, acc.: 43.55%] [G loss: 0.701221]
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655 [D loss: 0.694644, acc.: 47.07%] [G loss: 0.699956]
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656 [D loss: 0.693505, acc.: 48.24%] [G loss: 0.700787]
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657 [D loss: 0.695389, acc.: 45.90%] [G loss: 0.700422]
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658 [D loss: 0.694678, acc.: 42.77%] [G loss: 0.700756]
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659 [D loss: 0.694538, acc.: 45.12%] [G loss: 0.698816]
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660 [D loss: 0.695450, acc.: 43.55%] [G loss: 0.700365]
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661 [D loss: 0.693625, acc.: 49.02%] [G loss: 0.700870]
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662 [D loss: 0.693138, acc.: 51.37%] [G loss: 0.700838]
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663 [D loss: 0.693640, acc.: 48.83%] [G loss: 0.700463]
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664 [D loss: 0.692799, acc.: 49.41%] [G loss: 0.700265]
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665 [D loss: 0.693895, acc.: 46.29%] [G loss: 0.701676]
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666 [D loss: 0.693726, acc.: 49.02%] [G loss: 0.701343]
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667 [D loss: 0.693814, acc.: 48.83%] [G loss: 0.699459]
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668 [D loss: 0.693449, acc.: 47.66%] [G loss: 0.700842]
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669 [D loss: 0.692267, acc.: 51.37%] [G loss: 0.699387]
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670 [D loss: 0.694052, acc.: 47.66%] [G loss: 0.697166]
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671 [D loss: 0.693259, acc.: 50.39%] [G loss: 0.696352]
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672 [D loss: 0.694436, acc.: 47.27%] [G loss: 0.697022]
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673 [D loss: 0.694240, acc.: 46.68%] [G loss: 0.698459]
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674 [D loss: 0.695862, acc.: 46.29%] [G loss: 0.696486]
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675 [D loss: 0.695613, acc.: 41.80%] [G loss: 0.697889]
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676 [D loss: 0.696489, acc.: 43.36%] [G loss: 0.698441]
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677 [D loss: 0.696471, acc.: 45.90%] [G loss: 0.698371]
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678 [D loss: 0.696033, acc.: 45.70%] [G loss: 0.698246]
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679 [D loss: 0.695866, acc.: 44.34%] [G loss: 0.700033]
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680 [D loss: 0.696429, acc.: 43.16%] [G loss: 0.699359]
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681 [D loss: 0.697729, acc.: 40.62%] [G loss: 0.699557]
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682 [D loss: 0.695987, acc.: 46.48%] [G loss: 0.699648]
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683 [D loss: 0.696399, acc.: 41.80%] [G loss: 0.702389]
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684 [D loss: 0.696095, acc.: 44.14%] [G loss: 0.700354]
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685 [D loss: 0.694782, acc.: 46.88%] [G loss: 0.699796]
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686 [D loss: 0.695901, acc.: 41.60%] [G loss: 0.702453]
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687 [D loss: 0.696239, acc.: 45.12%] [G loss: 0.702505]
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688 [D loss: 0.695936, acc.: 46.88%] [G loss: 0.703361]
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689 [D loss: 0.695128, acc.: 47.46%] [G loss: 0.704331]
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690 [D loss: 0.695565, acc.: 44.73%] [G loss: 0.704582]
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691 [D loss: 0.694730, acc.: 45.70%] [G loss: 0.704657]
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692 [D loss: 0.694855, acc.: 44.92%] [G loss: 0.707085]
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693 [D loss: 0.695384, acc.: 47.27%] [G loss: 0.708395]
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694 [D loss: 0.694796, acc.: 45.90%] [G loss: 0.707127]
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695 [D loss: 0.693793, acc.: 51.37%] [G loss: 0.710628]
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696 [D loss: 0.694166, acc.: 47.07%] [G loss: 0.709809]
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697 [D loss: 0.694739, acc.: 48.24%] [G loss: 0.709793]
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698 [D loss: 0.693836, acc.: 49.61%] [G loss: 0.709080]
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699 [D loss: 0.694514, acc.: 47.66%] [G loss: 0.710153]
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700 [D loss: 0.695333, acc.: 46.68%] [G loss: 0.711344]
1/1 [==============================] - 0s 17ms/step
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701 [D loss: 0.695044, acc.: 46.29%] [G loss: 0.708667]
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702 [D loss: 0.695055, acc.: 47.07%] [G loss: 0.712416]
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703 [D loss: 0.695937, acc.: 46.48%] [G loss: 0.710590]
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704 [D loss: 0.695189, acc.: 45.90%] [G loss: 0.710432]
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705 [D loss: 0.694493, acc.: 48.83%] [G loss: 0.712460]
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706 [D loss: 0.694107, acc.: 48.24%] [G loss: 0.709945]
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707 [D loss: 0.695073, acc.: 48.05%] [G loss: 0.709592]
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708 [D loss: 0.695189, acc.: 47.46%] [G loss: 0.709718]
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709 [D loss: 0.693847, acc.: 50.20%] [G loss: 0.709010]
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710 [D loss: 0.694957, acc.: 47.85%] [G loss: 0.710912]
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711 [D loss: 0.695316, acc.: 48.24%] [G loss: 0.710684]
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712 [D loss: 0.694319, acc.: 46.68%] [G loss: 0.709652]
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713 [D loss: 0.694315, acc.: 50.20%] [G loss: 0.710679]
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714 [D loss: 0.693424, acc.: 49.41%] [G loss: 0.711680]
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715 [D loss: 0.696150, acc.: 45.51%] [G loss: 0.709139]
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716 [D loss: 0.694077, acc.: 48.63%] [G loss: 0.709516]
8/8 [==============================] - 0s 4ms/step
717 [D loss: 0.695245, acc.: 46.68%] [G loss: 0.709106]
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718 [D loss: 0.694280, acc.: 49.80%] [G loss: 0.708912]
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719 [D loss: 0.693893, acc.: 48.44%] [G loss: 0.710912]
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720 [D loss: 0.695119, acc.: 48.83%] [G loss: 0.708829]
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721 [D loss: 0.692700, acc.: 50.98%] [G loss: 0.709318]
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722 [D loss: 0.694541, acc.: 49.22%] [G loss: 0.708818]
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723 [D loss: 0.695115, acc.: 45.70%] [G loss: 0.710560]
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724 [D loss: 0.695717, acc.: 46.88%] [G loss: 0.710681]
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725 [D loss: 0.693211, acc.: 50.78%] [G loss: 0.709620]
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726 [D loss: 0.693368, acc.: 50.20%] [G loss: 0.711899]
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727 [D loss: 0.692961, acc.: 51.17%] [G loss: 0.711026]
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728 [D loss: 0.694106, acc.: 50.98%] [G loss: 0.712562]
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729 [D loss: 0.693305, acc.: 53.71%] [G loss: 0.711442]
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730 [D loss: 0.693087, acc.: 51.37%] [G loss: 0.714454]
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731 [D loss: 0.692987, acc.: 51.37%] [G loss: 0.711905]
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732 [D loss: 0.692084, acc.: 55.27%] [G loss: 0.713005]
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733 [D loss: 0.692137, acc.: 49.41%] [G loss: 0.712356]
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734 [D loss: 0.691957, acc.: 53.32%] [G loss: 0.712481]
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735 [D loss: 0.693279, acc.: 51.76%] [G loss: 0.712161]
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736 [D loss: 0.692208, acc.: 52.34%] [G loss: 0.712272]
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737 [D loss: 0.692788, acc.: 51.76%] [G loss: 0.710601]
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738 [D loss: 0.692939, acc.: 51.17%] [G loss: 0.711332]
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739 [D loss: 0.691798, acc.: 54.30%] [G loss: 0.712158]
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740 [D loss: 0.691767, acc.: 54.30%] [G loss: 0.712493]
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741 [D loss: 0.692182, acc.: 51.95%] [G loss: 0.710795]
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742 [D loss: 0.692633, acc.: 53.71%] [G loss: 0.710211]
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743 [D loss: 0.693356, acc.: 51.76%] [G loss: 0.709217]
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744 [D loss: 0.691862, acc.: 54.30%] [G loss: 0.710491]
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745 [D loss: 0.694415, acc.: 48.83%] [G loss: 0.707699]
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746 [D loss: 0.692396, acc.: 53.32%] [G loss: 0.709805]
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747 [D loss: 0.696466, acc.: 46.68%] [G loss: 0.709230]
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748 [D loss: 0.696742, acc.: 44.53%] [G loss: 0.706897]
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749 [D loss: 0.695259, acc.: 47.27%] [G loss: 0.708440]
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750 [D loss: 0.694491, acc.: 49.80%] [G loss: 0.707016]
1/1 [==============================] - 0s 16ms/step
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751 [D loss: 0.698470, acc.: 41.60%] [G loss: 0.705730]
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752 [D loss: 0.696475, acc.: 45.31%] [G loss: 0.709638]
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753 [D loss: 0.695797, acc.: 46.09%] [G loss: 0.709846]
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754 [D loss: 0.695295, acc.: 47.07%] [G loss: 0.711509]
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755 [D loss: 0.694843, acc.: 48.63%] [G loss: 0.709666]
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756 [D loss: 0.695074, acc.: 48.44%] [G loss: 0.712208]
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757 [D loss: 0.692845, acc.: 50.59%] [G loss: 0.710979]
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758 [D loss: 0.694426, acc.: 46.68%] [G loss: 0.714172]
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759 [D loss: 0.692986, acc.: 49.61%] [G loss: 0.714038]
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760 [D loss: 0.693178, acc.: 50.39%] [G loss: 0.716129]
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761 [D loss: 0.691619, acc.: 53.52%] [G loss: 0.714106]
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762 [D loss: 0.693894, acc.: 49.80%] [G loss: 0.716653]
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763 [D loss: 0.689946, acc.: 54.88%] [G loss: 0.717122]
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764 [D loss: 0.692726, acc.: 48.83%] [G loss: 0.713004]
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765 [D loss: 0.691054, acc.: 51.95%] [G loss: 0.718243]
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766 [D loss: 0.692984, acc.: 47.85%] [G loss: 0.715011]
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767 [D loss: 0.692081, acc.: 50.98%] [G loss: 0.712633]
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768 [D loss: 0.691928, acc.: 50.39%] [G loss: 0.712377]
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769 [D loss: 0.692973, acc.: 51.17%] [G loss: 0.712503]
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770 [D loss: 0.692675, acc.: 49.22%] [G loss: 0.713063]
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771 [D loss: 0.693190, acc.: 50.59%] [G loss: 0.711426]
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772 [D loss: 0.695499, acc.: 47.66%] [G loss: 0.709731]
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773 [D loss: 0.694987, acc.: 49.80%] [G loss: 0.707425]
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774 [D loss: 0.692095, acc.: 52.73%] [G loss: 0.707681]
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775 [D loss: 0.695147, acc.: 45.51%] [G loss: 0.706193]
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776 [D loss: 0.694935, acc.: 46.09%] [G loss: 0.708929]
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777 [D loss: 0.695709, acc.: 46.48%] [G loss: 0.704387]
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778 [D loss: 0.695107, acc.: 48.24%] [G loss: 0.706237]
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779 [D loss: 0.696128, acc.: 45.31%] [G loss: 0.707132]
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780 [D loss: 0.696201, acc.: 46.09%] [G loss: 0.706985]
8/8 [==============================] - 0s 4ms/step
781 [D loss: 0.696581, acc.: 45.51%] [G loss: 0.706379]
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782 [D loss: 0.697097, acc.: 44.53%] [G loss: 0.704935]
8/8 [==============================] - 0s 4ms/step
783 [D loss: 0.696297, acc.: 46.29%] [G loss: 0.705452]
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784 [D loss: 0.696262, acc.: 44.53%] [G loss: 0.706548]
8/8 [==============================] - 0s 4ms/step
785 [D loss: 0.695856, acc.: 45.51%] [G loss: 0.708179]
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786 [D loss: 0.695184, acc.: 45.31%] [G loss: 0.707634]
8/8 [==============================] - 0s 4ms/step
787 [D loss: 0.695841, acc.: 46.29%] [G loss: 0.708308]
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788 [D loss: 0.695575, acc.: 43.55%] [G loss: 0.711274]
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789 [D loss: 0.693833, acc.: 50.39%] [G loss: 0.711132]
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790 [D loss: 0.694839, acc.: 45.70%] [G loss: 0.715730]
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791 [D loss: 0.696008, acc.: 44.34%] [G loss: 0.713080]
8/8 [==============================] - 0s 4ms/step
792 [D loss: 0.694763, acc.: 48.63%] [G loss: 0.712994]
8/8 [==============================] - 0s 4ms/step
793 [D loss: 0.695149, acc.: 46.68%] [G loss: 0.715302]
8/8 [==============================] - 0s 4ms/step
794 [D loss: 0.693395, acc.: 49.41%] [G loss: 0.715927]
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795 [D loss: 0.694331, acc.: 48.63%] [G loss: 0.717540]
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796 [D loss: 0.694956, acc.: 48.44%] [G loss: 0.717742]
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797 [D loss: 0.693599, acc.: 49.61%] [G loss: 0.719515]
8/8 [==============================] - 0s 4ms/step
798 [D loss: 0.693381, acc.: 49.02%] [G loss: 0.720406]
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799 [D loss: 0.695307, acc.: 48.63%] [G loss: 0.720688]
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800 [D loss: 0.692418, acc.: 50.20%] [G loss: 0.720405]
1/1 [==============================] - 0s 17ms/step
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801 [D loss: 0.693281, acc.: 50.59%] [G loss: 0.724537]
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802 [D loss: 0.692644, acc.: 50.39%] [G loss: 0.724922]
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803 [D loss: 0.691969, acc.: 50.39%] [G loss: 0.725333]
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804 [D loss: 0.692115, acc.: 49.22%] [G loss: 0.727619]
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805 [D loss: 0.692191, acc.: 50.59%] [G loss: 0.726418]
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806 [D loss: 0.692227, acc.: 50.20%] [G loss: 0.724798]
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807 [D loss: 0.693373, acc.: 50.59%] [G loss: 0.727533]
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808 [D loss: 0.691075, acc.: 50.39%] [G loss: 0.727883]
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809 [D loss: 0.691195, acc.: 48.83%] [G loss: 0.728585]
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810 [D loss: 0.692635, acc.: 50.59%] [G loss: 0.729348]
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811 [D loss: 0.695236, acc.: 48.44%] [G loss: 0.727778]
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812 [D loss: 0.692089, acc.: 51.56%] [G loss: 0.725956]
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813 [D loss: 0.690672, acc.: 52.73%] [G loss: 0.729406]
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814 [D loss: 0.693701, acc.: 49.80%] [G loss: 0.723209]
8/8 [==============================] - 0s 4ms/step
815 [D loss: 0.693863, acc.: 49.61%] [G loss: 0.723027]
8/8 [==============================] - 0s 4ms/step
816 [D loss: 0.694156, acc.: 52.34%] [G loss: 0.720150]
8/8 [==============================] - 0s 4ms/step
817 [D loss: 0.692451, acc.: 53.12%] [G loss: 0.716026]
8/8 [==============================] - 0s 4ms/step
818 [D loss: 0.696460, acc.: 49.02%] [G loss: 0.712976]
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819 [D loss: 0.696734, acc.: 48.63%] [G loss: 0.709312]
8/8 [==============================] - 0s 4ms/step
820 [D loss: 0.696768, acc.: 50.98%] [G loss: 0.709693]
8/8 [==============================] - 0s 4ms/step
821 [D loss: 0.696833, acc.: 45.51%] [G loss: 0.706133]
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822 [D loss: 0.696678, acc.: 46.48%] [G loss: 0.705457]
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823 [D loss: 0.696270, acc.: 47.66%] [G loss: 0.705144]
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824 [D loss: 0.694698, acc.: 50.00%] [G loss: 0.704539]
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825 [D loss: 0.694505, acc.: 50.78%] [G loss: 0.705774]
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826 [D loss: 0.694599, acc.: 47.85%] [G loss: 0.704729]
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827 [D loss: 0.693346, acc.: 49.80%] [G loss: 0.703322]
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828 [D loss: 0.691516, acc.: 52.93%] [G loss: 0.704178]
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829 [D loss: 0.692958, acc.: 53.12%] [G loss: 0.705623]
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830 [D loss: 0.691013, acc.: 52.34%] [G loss: 0.705946]
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831 [D loss: 0.690310, acc.: 54.10%] [G loss: 0.704207]
8/8 [==============================] - 0s 4ms/step
832 [D loss: 0.690059, acc.: 57.42%] [G loss: 0.705039]
8/8 [==============================] - 0s 4ms/step
833 [D loss: 0.691249, acc.: 54.69%] [G loss: 0.705790]
8/8 [==============================] - 0s 4ms/step
834 [D loss: 0.691355, acc.: 53.52%] [G loss: 0.706627]
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835 [D loss: 0.692269, acc.: 52.73%] [G loss: 0.704914]
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836 [D loss: 0.691648, acc.: 56.64%] [G loss: 0.701719]
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837 [D loss: 0.691137, acc.: 56.45%] [G loss: 0.702706]
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838 [D loss: 0.692900, acc.: 51.76%] [G loss: 0.699359]
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839 [D loss: 0.693434, acc.: 52.15%] [G loss: 0.701593]
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840 [D loss: 0.691827, acc.: 52.54%] [G loss: 0.698109]
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841 [D loss: 0.694335, acc.: 49.22%] [G loss: 0.698026]
8/8 [==============================] - 0s 4ms/step
842 [D loss: 0.693002, acc.: 50.98%] [G loss: 0.696388]
8/8 [==============================] - 0s 4ms/step
843 [D loss: 0.692922, acc.: 51.17%] [G loss: 0.696233]
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844 [D loss: 0.696035, acc.: 46.09%] [G loss: 0.694976]
8/8 [==============================] - 0s 4ms/step
845 [D loss: 0.695824, acc.: 47.46%] [G loss: 0.695362]
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846 [D loss: 0.696362, acc.: 46.09%] [G loss: 0.692691]
8/8 [==============================] - 0s 4ms/step
847 [D loss: 0.697051, acc.: 45.90%] [G loss: 0.692862]
8/8 [==============================] - 0s 4ms/step
848 [D loss: 0.696813, acc.: 43.55%] [G loss: 0.694749]
8/8 [==============================] - 0s 4ms/step
849 [D loss: 0.696318, acc.: 44.14%] [G loss: 0.693385]
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850 [D loss: 0.696965, acc.: 44.92%] [G loss: 0.694578]
1/1 [==============================] - 0s 17ms/step
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851 [D loss: 0.698633, acc.: 39.45%] [G loss: 0.695211]
8/8 [==============================] - 0s 4ms/step
852 [D loss: 0.698263, acc.: 40.82%] [G loss: 0.696887]
8/8 [==============================] - 0s 4ms/step
853 [D loss: 0.695694, acc.: 44.34%] [G loss: 0.696099]
8/8 [==============================] - 0s 4ms/step
854 [D loss: 0.694910, acc.: 46.09%] [G loss: 0.696951]
8/8 [==============================] - 0s 4ms/step
855 [D loss: 0.696775, acc.: 44.53%] [G loss: 0.698284]
8/8 [==============================] - 0s 4ms/step
856 [D loss: 0.696095, acc.: 41.41%] [G loss: 0.697904]
8/8 [==============================] - 0s 4ms/step
857 [D loss: 0.694502, acc.: 47.46%] [G loss: 0.698822]
8/8 [==============================] - 0s 4ms/step
858 [D loss: 0.693946, acc.: 50.20%] [G loss: 0.699591]
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859 [D loss: 0.695588, acc.: 46.68%] [G loss: 0.699530]
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860 [D loss: 0.695093, acc.: 43.95%] [G loss: 0.699427]
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861 [D loss: 0.694995, acc.: 48.05%] [G loss: 0.699228]
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862 [D loss: 0.693395, acc.: 48.63%] [G loss: 0.700132]
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863 [D loss: 0.694594, acc.: 46.09%] [G loss: 0.701099]
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864 [D loss: 0.693016, acc.: 48.05%] [G loss: 0.702398]
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865 [D loss: 0.693416, acc.: 46.68%] [G loss: 0.701574]
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866 [D loss: 0.693127, acc.: 49.02%] [G loss: 0.702956]
8/8 [==============================] - 0s 4ms/step
867 [D loss: 0.692592, acc.: 50.20%] [G loss: 0.704389]
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868 [D loss: 0.692512, acc.: 52.73%] [G loss: 0.704411]
8/8 [==============================] - 0s 4ms/step
869 [D loss: 0.692230, acc.: 49.61%] [G loss: 0.705160]
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870 [D loss: 0.691176, acc.: 55.08%] [G loss: 0.705297]
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871 [D loss: 0.690989, acc.: 55.47%] [G loss: 0.705634]
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872 [D loss: 0.690764, acc.: 51.56%] [G loss: 0.705894]
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873 [D loss: 0.691629, acc.: 52.15%] [G loss: 0.706903]
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874 [D loss: 0.690055, acc.: 54.69%] [G loss: 0.706849]
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875 [D loss: 0.692038, acc.: 52.73%] [G loss: 0.706959]
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876 [D loss: 0.692146, acc.: 51.56%] [G loss: 0.708566]
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877 [D loss: 0.690818, acc.: 53.12%] [G loss: 0.712306]
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878 [D loss: 0.690863, acc.: 51.76%] [G loss: 0.709652]
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879 [D loss: 0.690988, acc.: 52.15%] [G loss: 0.706375]
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880 [D loss: 0.691977, acc.: 51.56%] [G loss: 0.706022]
8/8 [==============================] - 0s 4ms/step
881 [D loss: 0.692925, acc.: 47.85%] [G loss: 0.710283]
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882 [D loss: 0.690985, acc.: 55.47%] [G loss: 0.709941]
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883 [D loss: 0.690741, acc.: 50.78%] [G loss: 0.715739]
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884 [D loss: 0.693134, acc.: 51.76%] [G loss: 0.703977]
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885 [D loss: 0.693927, acc.: 48.63%] [G loss: 0.709161]
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886 [D loss: 0.695859, acc.: 46.88%] [G loss: 0.712481]
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887 [D loss: 0.692162, acc.: 49.22%] [G loss: 0.712423]
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888 [D loss: 0.691922, acc.: 51.56%] [G loss: 0.711563]
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889 [D loss: 0.693804, acc.: 49.02%] [G loss: 0.707190]
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890 [D loss: 0.693450, acc.: 50.78%] [G loss: 0.713547]
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891 [D loss: 0.694470, acc.: 50.78%] [G loss: 0.711775]
8/8 [==============================] - 0s 4ms/step
892 [D loss: 0.692720, acc.: 52.34%] [G loss: 0.709957]
8/8 [==============================] - 0s 4ms/step
893 [D loss: 0.694428, acc.: 49.61%] [G loss: 0.706527]
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894 [D loss: 0.696740, acc.: 45.51%] [G loss: 0.707903]
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895 [D loss: 0.693798, acc.: 50.98%] [G loss: 0.707011]
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896 [D loss: 0.694517, acc.: 48.24%] [G loss: 0.709482]
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897 [D loss: 0.694786, acc.: 48.63%] [G loss: 0.710186]
8/8 [==============================] - 0s 4ms/step
898 [D loss: 0.695609, acc.: 43.16%] [G loss: 0.705193]
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899 [D loss: 0.697861, acc.: 42.19%] [G loss: 0.705295]
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900 [D loss: 0.694587, acc.: 47.07%] [G loss: 0.705215]
1/1 [==============================] - 0s 16ms/step
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901 [D loss: 0.698367, acc.: 40.62%] [G loss: 0.703198]
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902 [D loss: 0.697708, acc.: 40.43%] [G loss: 0.703640]
8/8 [==============================] - 0s 4ms/step
903 [D loss: 0.696545, acc.: 43.55%] [G loss: 0.703167]
8/8 [==============================] - 0s 4ms/step
904 [D loss: 0.694855, acc.: 45.70%] [G loss: 0.704732]
8/8 [==============================] - 0s 4ms/step
905 [D loss: 0.697710, acc.: 42.19%] [G loss: 0.706600]
8/8 [==============================] - 0s 4ms/step
906 [D loss: 0.696194, acc.: 41.80%] [G loss: 0.703186]
8/8 [==============================] - 0s 4ms/step
907 [D loss: 0.695684, acc.: 46.88%] [G loss: 0.707214]
8/8 [==============================] - 0s 4ms/step
908 [D loss: 0.695779, acc.: 45.70%] [G loss: 0.703883]
8/8 [==============================] - 0s 4ms/step
909 [D loss: 0.696677, acc.: 41.99%] [G loss: 0.706976]
8/8 [==============================] - 0s 4ms/step
910 [D loss: 0.695315, acc.: 45.31%] [G loss: 0.703699]
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911 [D loss: 0.694583, acc.: 47.85%] [G loss: 0.708917]
8/8 [==============================] - 0s 4ms/step
912 [D loss: 0.694293, acc.: 47.46%] [G loss: 0.706871]
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913 [D loss: 0.692132, acc.: 50.98%] [G loss: 0.707568]
8/8 [==============================] - 0s 4ms/step
914 [D loss: 0.692346, acc.: 52.73%] [G loss: 0.707265]
8/8 [==============================] - 0s 4ms/step
915 [D loss: 0.693268, acc.: 51.95%] [G loss: 0.707791]
8/8 [==============================] - 0s 4ms/step
916 [D loss: 0.694152, acc.: 46.48%] [G loss: 0.708564]
8/8 [==============================] - 0s 4ms/step
917 [D loss: 0.692523, acc.: 51.56%] [G loss: 0.709220]
8/8 [==============================] - 0s 4ms/step
918 [D loss: 0.692513, acc.: 49.02%] [G loss: 0.710156]
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919 [D loss: 0.692605, acc.: 51.76%] [G loss: 0.711276]
8/8 [==============================] - 0s 4ms/step
920 [D loss: 0.692396, acc.: 49.80%] [G loss: 0.710665]
8/8 [==============================] - 0s 4ms/step
921 [D loss: 0.692086, acc.: 52.15%] [G loss: 0.709548]
8/8 [==============================] - 0s 4ms/step
922 [D loss: 0.692190, acc.: 51.17%] [G loss: 0.710657]
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923 [D loss: 0.690808, acc.: 53.32%] [G loss: 0.709273]
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924 [D loss: 0.691814, acc.: 51.17%] [G loss: 0.709980]
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925 [D loss: 0.691703, acc.: 52.34%] [G loss: 0.712702]
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926 [D loss: 0.692551, acc.: 49.61%] [G loss: 0.709814]
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927 [D loss: 0.695028, acc.: 48.05%] [G loss: 0.706893]
8/8 [==============================] - 0s 4ms/step
928 [D loss: 0.692551, acc.: 51.37%] [G loss: 0.709371]
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929 [D loss: 0.694166, acc.: 49.41%] [G loss: 0.706462]
8/8 [==============================] - 0s 4ms/step
930 [D loss: 0.693846, acc.: 46.88%] [G loss: 0.704897]
8/8 [==============================] - 0s 4ms/step
931 [D loss: 0.696546, acc.: 44.92%] [G loss: 0.706524]
8/8 [==============================] - 0s 4ms/step
932 [D loss: 0.696604, acc.: 44.34%] [G loss: 0.707030]
8/8 [==============================] - 0s 4ms/step
933 [D loss: 0.695544, acc.: 47.07%] [G loss: 0.707047]
8/8 [==============================] - 0s 4ms/step
934 [D loss: 0.697315, acc.: 42.97%] [G loss: 0.704560]
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935 [D loss: 0.697987, acc.: 41.80%] [G loss: 0.703219]
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936 [D loss: 0.696076, acc.: 45.70%] [G loss: 0.703625]
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937 [D loss: 0.697829, acc.: 42.97%] [G loss: 0.703842]
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938 [D loss: 0.696663, acc.: 47.27%] [G loss: 0.704570]
8/8 [==============================] - 0s 4ms/step
939 [D loss: 0.697116, acc.: 42.58%] [G loss: 0.702602]
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940 [D loss: 0.695724, acc.: 47.07%] [G loss: 0.705211]
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941 [D loss: 0.694842, acc.: 46.88%] [G loss: 0.705048]
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942 [D loss: 0.694588, acc.: 46.09%] [G loss: 0.705022]
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943 [D loss: 0.693748, acc.: 49.41%] [G loss: 0.708882]
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944 [D loss: 0.694078, acc.: 49.80%] [G loss: 0.710723]
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945 [D loss: 0.693634, acc.: 52.15%] [G loss: 0.707842]
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946 [D loss: 0.691767, acc.: 53.12%] [G loss: 0.710692]
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947 [D loss: 0.691868, acc.: 52.93%] [G loss: 0.711577]
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948 [D loss: 0.691837, acc.: 53.91%] [G loss: 0.713590]
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949 [D loss: 0.691484, acc.: 53.52%] [G loss: 0.714953]
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950 [D loss: 0.691101, acc.: 53.12%] [G loss: 0.716635]
1/1 [==============================] - 0s 15ms/step
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951 [D loss: 0.691714, acc.: 52.73%] [G loss: 0.718781]
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952 [D loss: 0.691785, acc.: 53.91%] [G loss: 0.716633]
8/8 [==============================] - 0s 4ms/step
953 [D loss: 0.688809, acc.: 57.23%] [G loss: 0.717098]
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954 [D loss: 0.690104, acc.: 55.66%] [G loss: 0.716262]
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955 [D loss: 0.690320, acc.: 56.64%] [G loss: 0.716494]
8/8 [==============================] - 0s 4ms/step
956 [D loss: 0.689529, acc.: 55.66%] [G loss: 0.717764]
8/8 [==============================] - 0s 4ms/step
957 [D loss: 0.691787, acc.: 54.10%] [G loss: 0.715796]
8/8 [==============================] - 0s 4ms/step
958 [D loss: 0.691361, acc.: 51.76%] [G loss: 0.715446]
8/8 [==============================] - 0s 4ms/step
959 [D loss: 0.690976, acc.: 54.49%] [G loss: 0.713896]
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960 [D loss: 0.693396, acc.: 53.52%] [G loss: 0.711296]
8/8 [==============================] - 0s 4ms/step
961 [D loss: 0.693444, acc.: 49.22%] [G loss: 0.712556]
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962 [D loss: 0.693227, acc.: 50.78%] [G loss: 0.707242]
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963 [D loss: 0.693423, acc.: 50.59%] [G loss: 0.708228]
8/8 [==============================] - 0s 4ms/step
964 [D loss: 0.694642, acc.: 52.15%] [G loss: 0.705296]
8/8 [==============================] - 0s 4ms/step
965 [D loss: 0.695942, acc.: 46.29%] [G loss: 0.704052]
8/8 [==============================] - 0s 4ms/step
966 [D loss: 0.696588, acc.: 45.31%] [G loss: 0.702217]
8/8 [==============================] - 0s 4ms/step
967 [D loss: 0.696073, acc.: 44.34%] [G loss: 0.701528]
8/8 [==============================] - 0s 4ms/step
968 [D loss: 0.696733, acc.: 47.07%] [G loss: 0.700558]
8/8 [==============================] - 0s 4ms/step
969 [D loss: 0.696430, acc.: 48.44%] [G loss: 0.699606]
8/8 [==============================] - 0s 4ms/step
970 [D loss: 0.698315, acc.: 41.21%] [G loss: 0.698027]
8/8 [==============================] - 0s 4ms/step
971 [D loss: 0.695077, acc.: 47.85%] [G loss: 0.698358]
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972 [D loss: 0.696213, acc.: 45.12%] [G loss: 0.696532]
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973 [D loss: 0.696909, acc.: 45.70%] [G loss: 0.698239]
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974 [D loss: 0.696977, acc.: 45.12%] [G loss: 0.701326]
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975 [D loss: 0.695649, acc.: 48.44%] [G loss: 0.696992]
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976 [D loss: 0.695047, acc.: 45.31%] [G loss: 0.698633]
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977 [D loss: 0.694378, acc.: 48.05%] [G loss: 0.696990]
8/8 [==============================] - 0s 4ms/step
978 [D loss: 0.694765, acc.: 47.66%] [G loss: 0.698124]
8/8 [==============================] - 0s 4ms/step
979 [D loss: 0.694947, acc.: 51.56%] [G loss: 0.702133]
8/8 [==============================] - 0s 4ms/step
980 [D loss: 0.695457, acc.: 42.97%] [G loss: 0.700987]
8/8 [==============================] - 0s 4ms/step
981 [D loss: 0.695163, acc.: 46.29%] [G loss: 0.702130]
8/8 [==============================] - 0s 4ms/step
982 [D loss: 0.694455, acc.: 46.48%] [G loss: 0.702027]
8/8 [==============================] - 0s 4ms/step
983 [D loss: 0.693180, acc.: 50.59%] [G loss: 0.702633]
8/8 [==============================] - 0s 4ms/step
984 [D loss: 0.692580, acc.: 50.78%] [G loss: 0.702392]
8/8 [==============================] - 0s 4ms/step
985 [D loss: 0.692960, acc.: 49.02%] [G loss: 0.704133]
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986 [D loss: 0.692201, acc.: 52.34%] [G loss: 0.704409]
8/8 [==============================] - 0s 4ms/step
987 [D loss: 0.694239, acc.: 48.44%] [G loss: 0.706782]
8/8 [==============================] - 0s 4ms/step
988 [D loss: 0.693594, acc.: 50.98%] [G loss: 0.706110]
8/8 [==============================] - 0s 4ms/step
989 [D loss: 0.691240, acc.: 54.30%] [G loss: 0.704983]
8/8 [==============================] - 0s 4ms/step
990 [D loss: 0.691932, acc.: 52.54%] [G loss: 0.706414]
8/8 [==============================] - 0s 4ms/step
991 [D loss: 0.690895, acc.: 53.52%] [G loss: 0.706700]
8/8 [==============================] - 0s 4ms/step
992 [D loss: 0.694038, acc.: 51.76%] [G loss: 0.708462]
8/8 [==============================] - 0s 4ms/step
993 [D loss: 0.692650, acc.: 50.78%] [G loss: 0.707369]
8/8 [==============================] - 0s 4ms/step
994 [D loss: 0.691253, acc.: 53.32%] [G loss: 0.709817]
8/8 [==============================] - 0s 4ms/step
995 [D loss: 0.692653, acc.: 51.37%] [G loss: 0.709181]
8/8 [==============================] - 0s 4ms/step
996 [D loss: 0.692787, acc.: 53.71%] [G loss: 0.712138]
8/8 [==============================] - 0s 4ms/step
997 [D loss: 0.693683, acc.: 49.80%] [G loss: 0.704971]
8/8 [==============================] - 0s 4ms/step
998 [D loss: 0.693886, acc.: 52.15%] [G loss: 0.708842]
8/8 [==============================] - 0s 4ms/step
999 [D loss: 0.692817, acc.: 50.59%] [G loss: 0.708645]
8/8 [==============================] - 0s 4ms/step
1000 [D loss: 0.691698, acc.: 56.25%] [G loss: 0.705499]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 4ms/step
1001 [D loss: 0.692821, acc.: 51.76%] [G loss: 0.705642]
8/8 [==============================] - 0s 4ms/step
1002 [D loss: 0.695250, acc.: 49.22%] [G loss: 0.701523]
8/8 [==============================] - 0s 4ms/step
1003 [D loss: 0.696324, acc.: 45.51%] [G loss: 0.705810]
8/8 [==============================] - 0s 4ms/step
1004 [D loss: 0.695994, acc.: 47.66%] [G loss: 0.703681]
8/8 [==============================] - 0s 4ms/step
1005 [D loss: 0.695598, acc.: 46.29%] [G loss: 0.699966]
8/8 [==============================] - 0s 4ms/step
1006 [D loss: 0.696990, acc.: 44.14%] [G loss: 0.699529]
8/8 [==============================] - 0s 4ms/step
1007 [D loss: 0.696933, acc.: 44.73%] [G loss: 0.699800]
8/8 [==============================] - 0s 4ms/step
1008 [D loss: 0.696207, acc.: 44.34%] [G loss: 0.699335]
8/8 [==============================] - 0s 4ms/step
1009 [D loss: 0.697736, acc.: 42.19%] [G loss: 0.699769]
8/8 [==============================] - 0s 4ms/step
1010 [D loss: 0.697838, acc.: 42.19%] [G loss: 0.700629]
8/8 [==============================] - 0s 4ms/step
1011 [D loss: 0.698198, acc.: 42.38%] [G loss: 0.696797]
8/8 [==============================] - 0s 4ms/step
1012 [D loss: 0.696676, acc.: 43.95%] [G loss: 0.697712]
8/8 [==============================] - 0s 4ms/step
1013 [D loss: 0.696311, acc.: 45.31%] [G loss: 0.696731]
8/8 [==============================] - 0s 4ms/step
1014 [D loss: 0.695652, acc.: 44.34%] [G loss: 0.696299]
8/8 [==============================] - 0s 4ms/step
1015 [D loss: 0.695698, acc.: 43.75%] [G loss: 0.695286]
8/8 [==============================] - 0s 4ms/step
1016 [D loss: 0.695840, acc.: 42.97%] [G loss: 0.694961]
8/8 [==============================] - 0s 4ms/step
1017 [D loss: 0.695392, acc.: 45.51%] [G loss: 0.694973]
8/8 [==============================] - 0s 4ms/step
1018 [D loss: 0.694000, acc.: 47.66%] [G loss: 0.694183]
8/8 [==============================] - 0s 4ms/step
1019 [D loss: 0.694808, acc.: 47.07%] [G loss: 0.695486]
8/8 [==============================] - 0s 4ms/step
1020 [D loss: 0.692700, acc.: 50.20%] [G loss: 0.695066]
8/8 [==============================] - 0s 4ms/step
1021 [D loss: 0.693754, acc.: 46.09%] [G loss: 0.695644]
8/8 [==============================] - 0s 4ms/step
1022 [D loss: 0.695422, acc.: 43.55%] [G loss: 0.695203]
8/8 [==============================] - 0s 4ms/step
1023 [D loss: 0.691772, acc.: 54.49%] [G loss: 0.699066]
8/8 [==============================] - 0s 4ms/step
1024 [D loss: 0.692953, acc.: 50.39%] [G loss: 0.698242]
8/8 [==============================] - 0s 4ms/step
1025 [D loss: 0.692895, acc.: 49.80%] [G loss: 0.700165]
8/8 [==============================] - 0s 4ms/step
1026 [D loss: 0.692066, acc.: 52.34%] [G loss: 0.702080]
8/8 [==============================] - 0s 4ms/step
1027 [D loss: 0.690997, acc.: 55.27%] [G loss: 0.701144]
8/8 [==============================] - 0s 4ms/step
1028 [D loss: 0.690314, acc.: 56.25%] [G loss: 0.701009]
8/8 [==============================] - 0s 4ms/step
1029 [D loss: 0.689780, acc.: 58.40%] [G loss: 0.706325]
8/8 [==============================] - 0s 4ms/step
1030 [D loss: 0.689418, acc.: 56.45%] [G loss: 0.705815]
8/8 [==============================] - 0s 4ms/step
1031 [D loss: 0.690151, acc.: 55.27%] [G loss: 0.706991]
8/8 [==============================] - 0s 4ms/step
1032 [D loss: 0.687931, acc.: 61.33%] [G loss: 0.708580]
8/8 [==============================] - 0s 4ms/step
1033 [D loss: 0.687635, acc.: 57.42%] [G loss: 0.708544]
8/8 [==============================] - 0s 4ms/step
1034 [D loss: 0.690143, acc.: 53.12%] [G loss: 0.711854]
8/8 [==============================] - 0s 4ms/step
1035 [D loss: 0.689274, acc.: 56.45%] [G loss: 0.709731]
8/8 [==============================] - 0s 4ms/step
1036 [D loss: 0.689496, acc.: 57.42%] [G loss: 0.708936]
8/8 [==============================] - 0s 4ms/step
1037 [D loss: 0.690877, acc.: 51.95%] [G loss: 0.710146]
8/8 [==============================] - 0s 4ms/step
1038 [D loss: 0.690905, acc.: 52.54%] [G loss: 0.710845]
8/8 [==============================] - 0s 4ms/step
1039 [D loss: 0.689534, acc.: 55.66%] [G loss: 0.706157]
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1040 [D loss: 0.694771, acc.: 48.44%] [G loss: 0.706484]
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1041 [D loss: 0.692629, acc.: 49.22%] [G loss: 0.707207]
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1042 [D loss: 0.693717, acc.: 51.37%] [G loss: 0.706124]
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1043 [D loss: 0.695854, acc.: 45.70%] [G loss: 0.704286]
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1044 [D loss: 0.695376, acc.: 45.51%] [G loss: 0.703603]
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1045 [D loss: 0.697715, acc.: 44.92%] [G loss: 0.704725]
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1046 [D loss: 0.699664, acc.: 40.43%] [G loss: 0.702755]
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1047 [D loss: 0.698928, acc.: 42.77%] [G loss: 0.702388]
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1048 [D loss: 0.699172, acc.: 41.99%] [G loss: 0.701987]
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1049 [D loss: 0.696431, acc.: 44.73%] [G loss: 0.701116]
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1050 [D loss: 0.697758, acc.: 43.36%] [G loss: 0.703332]
1/1 [==============================] - 0s 17ms/step
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1051 [D loss: 0.696855, acc.: 45.51%] [G loss: 0.700126]
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1052 [D loss: 0.696989, acc.: 46.09%] [G loss: 0.702351]
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1053 [D loss: 0.694660, acc.: 49.41%] [G loss: 0.703410]
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1054 [D loss: 0.695902, acc.: 45.51%] [G loss: 0.702573]
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1055 [D loss: 0.694601, acc.: 47.27%] [G loss: 0.704529]
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1056 [D loss: 0.693620, acc.: 47.27%] [G loss: 0.706622]
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1057 [D loss: 0.692869, acc.: 51.17%] [G loss: 0.705992]
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1058 [D loss: 0.692529, acc.: 53.12%] [G loss: 0.704487]
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1059 [D loss: 0.692784, acc.: 50.98%] [G loss: 0.706724]
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1060 [D loss: 0.693704, acc.: 50.39%] [G loss: 0.706119]
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1061 [D loss: 0.690311, acc.: 57.42%] [G loss: 0.707395]
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1062 [D loss: 0.691697, acc.: 53.91%] [G loss: 0.705665]
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1063 [D loss: 0.691249, acc.: 56.45%] [G loss: 0.706954]
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1064 [D loss: 0.690333, acc.: 58.01%] [G loss: 0.707475]
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1065 [D loss: 0.690529, acc.: 55.47%] [G loss: 0.703088]
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1066 [D loss: 0.692462, acc.: 50.98%] [G loss: 0.703219]
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1067 [D loss: 0.693697, acc.: 51.37%] [G loss: 0.701168]
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1068 [D loss: 0.696219, acc.: 42.38%] [G loss: 0.699250]
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1069 [D loss: 0.694189, acc.: 45.51%] [G loss: 0.697194]
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1070 [D loss: 0.697014, acc.: 45.12%] [G loss: 0.697637]
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1071 [D loss: 0.696358, acc.: 44.53%] [G loss: 0.698016]
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1072 [D loss: 0.695678, acc.: 44.73%] [G loss: 0.698830]
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1073 [D loss: 0.695558, acc.: 45.90%] [G loss: 0.696754]
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1074 [D loss: 0.697038, acc.: 44.14%] [G loss: 0.696759]
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1075 [D loss: 0.694691, acc.: 47.85%] [G loss: 0.696223]
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1076 [D loss: 0.694070, acc.: 49.41%] [G loss: 0.697648]
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1077 [D loss: 0.694918, acc.: 46.48%] [G loss: 0.698582]
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1078 [D loss: 0.695846, acc.: 43.36%] [G loss: 0.700144]
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1079 [D loss: 0.694771, acc.: 49.22%] [G loss: 0.699569]
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1080 [D loss: 0.693588, acc.: 47.85%] [G loss: 0.701611]
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1081 [D loss: 0.693059, acc.: 51.76%] [G loss: 0.700507]
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1082 [D loss: 0.691438, acc.: 53.71%] [G loss: 0.704661]
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1083 [D loss: 0.693352, acc.: 52.15%] [G loss: 0.705363]
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1084 [D loss: 0.691457, acc.: 53.91%] [G loss: 0.705086]
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1085 [D loss: 0.692511, acc.: 50.98%] [G loss: 0.708384]
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1086 [D loss: 0.689253, acc.: 58.40%] [G loss: 0.707153]
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1087 [D loss: 0.690594, acc.: 55.47%] [G loss: 0.709841]
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1088 [D loss: 0.689807, acc.: 58.79%] [G loss: 0.708105]
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1089 [D loss: 0.689327, acc.: 58.20%] [G loss: 0.706273]
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1090 [D loss: 0.689561, acc.: 56.84%] [G loss: 0.709638]
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1091 [D loss: 0.689640, acc.: 52.93%] [G loss: 0.710934]
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1092 [D loss: 0.689586, acc.: 55.47%] [G loss: 0.707796]
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1093 [D loss: 0.692374, acc.: 51.76%] [G loss: 0.708166]
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1094 [D loss: 0.690327, acc.: 53.12%] [G loss: 0.707295]
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1095 [D loss: 0.693698, acc.: 48.83%] [G loss: 0.707882]
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1096 [D loss: 0.693040, acc.: 48.44%] [G loss: 0.704664]
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1097 [D loss: 0.694506, acc.: 50.20%] [G loss: 0.703630]
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1098 [D loss: 0.693576, acc.: 49.22%] [G loss: 0.700911]
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1099 [D loss: 0.695922, acc.: 44.92%] [G loss: 0.699751]
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1100 [D loss: 0.695924, acc.: 45.51%] [G loss: 0.700918]
1/1 [==============================] - 0s 15ms/step
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1101 [D loss: 0.698740, acc.: 40.62%] [G loss: 0.700350]
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1102 [D loss: 0.697922, acc.: 42.58%] [G loss: 0.700668]
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1103 [D loss: 0.695074, acc.: 46.68%] [G loss: 0.699620]
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1104 [D loss: 0.695323, acc.: 45.31%] [G loss: 0.699086]
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1105 [D loss: 0.695651, acc.: 45.12%] [G loss: 0.700924]
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1106 [D loss: 0.696035, acc.: 45.51%] [G loss: 0.702306]
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1107 [D loss: 0.695841, acc.: 44.34%] [G loss: 0.701943]
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1108 [D loss: 0.694630, acc.: 47.66%] [G loss: 0.703652]
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1109 [D loss: 0.694531, acc.: 47.46%] [G loss: 0.702113]
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1110 [D loss: 0.693787, acc.: 49.61%] [G loss: 0.702959]
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1111 [D loss: 0.695979, acc.: 46.09%] [G loss: 0.704833]
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1112 [D loss: 0.695551, acc.: 44.92%] [G loss: 0.703682]
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1113 [D loss: 0.693667, acc.: 48.83%] [G loss: 0.706506]
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1114 [D loss: 0.693639, acc.: 50.00%] [G loss: 0.703670]
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1115 [D loss: 0.691460, acc.: 53.12%] [G loss: 0.706771]
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1116 [D loss: 0.692118, acc.: 52.15%] [G loss: 0.706576]
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1117 [D loss: 0.693646, acc.: 49.22%] [G loss: 0.704559]
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1118 [D loss: 0.693973, acc.: 47.27%] [G loss: 0.704257]
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1119 [D loss: 0.694256, acc.: 48.24%] [G loss: 0.701565]
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1120 [D loss: 0.693639, acc.: 49.61%] [G loss: 0.702907]
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1121 [D loss: 0.693316, acc.: 49.41%] [G loss: 0.704334]
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1122 [D loss: 0.694149, acc.: 47.07%] [G loss: 0.701485]
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1123 [D loss: 0.693743, acc.: 48.24%] [G loss: 0.700316]
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1124 [D loss: 0.693204, acc.: 47.66%] [G loss: 0.699796]
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1125 [D loss: 0.693389, acc.: 49.22%] [G loss: 0.700224]
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1126 [D loss: 0.695180, acc.: 44.14%] [G loss: 0.701856]
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1127 [D loss: 0.694503, acc.: 49.80%] [G loss: 0.699758]
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1128 [D loss: 0.693092, acc.: 52.34%] [G loss: 0.700148]
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1129 [D loss: 0.692125, acc.: 53.71%] [G loss: 0.698419]
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1130 [D loss: 0.693042, acc.: 50.39%] [G loss: 0.701078]
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1131 [D loss: 0.692659, acc.: 50.59%] [G loss: 0.700189]
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1132 [D loss: 0.693396, acc.: 48.44%] [G loss: 0.699423]
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1133 [D loss: 0.693685, acc.: 46.68%] [G loss: 0.697903]
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1134 [D loss: 0.692682, acc.: 49.61%] [G loss: 0.700013]
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1135 [D loss: 0.691324, acc.: 53.12%] [G loss: 0.701599]
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1136 [D loss: 0.690256, acc.: 54.88%] [G loss: 0.700443]
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1137 [D loss: 0.690644, acc.: 54.10%] [G loss: 0.701954]
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1138 [D loss: 0.690108, acc.: 55.08%] [G loss: 0.703140]
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1139 [D loss: 0.691099, acc.: 52.73%] [G loss: 0.701968]
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1140 [D loss: 0.690227, acc.: 54.69%] [G loss: 0.699464]
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1141 [D loss: 0.690988, acc.: 52.54%] [G loss: 0.700526]
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1142 [D loss: 0.688006, acc.: 56.84%] [G loss: 0.697783]
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1143 [D loss: 0.690778, acc.: 53.71%] [G loss: 0.697290]
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1144 [D loss: 0.691392, acc.: 52.54%] [G loss: 0.696609]
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1145 [D loss: 0.693424, acc.: 49.61%] [G loss: 0.695236]
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1146 [D loss: 0.695211, acc.: 51.76%] [G loss: 0.691485]
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1147 [D loss: 0.694604, acc.: 47.85%] [G loss: 0.690039]
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1148 [D loss: 0.695059, acc.: 49.61%] [G loss: 0.690449]
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1149 [D loss: 0.699037, acc.: 45.70%] [G loss: 0.689352]
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1150 [D loss: 0.698243, acc.: 43.36%] [G loss: 0.688732]
1/1 [==============================] - 0s 16ms/step
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1151 [D loss: 0.697678, acc.: 47.46%] [G loss: 0.690258]
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1152 [D loss: 0.697600, acc.: 44.92%] [G loss: 0.692034]
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1153 [D loss: 0.696663, acc.: 46.29%] [G loss: 0.689841]
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1154 [D loss: 0.695190, acc.: 45.51%] [G loss: 0.690281]
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1155 [D loss: 0.695997, acc.: 47.27%] [G loss: 0.690849]
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1156 [D loss: 0.695969, acc.: 46.09%] [G loss: 0.691649]
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1157 [D loss: 0.696145, acc.: 46.88%] [G loss: 0.690615]
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1158 [D loss: 0.694083, acc.: 46.88%] [G loss: 0.690600]
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1159 [D loss: 0.693973, acc.: 47.66%] [G loss: 0.690753]
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1160 [D loss: 0.694933, acc.: 46.09%] [G loss: 0.692800]
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1161 [D loss: 0.693516, acc.: 50.59%] [G loss: 0.694210]
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1162 [D loss: 0.692526, acc.: 50.39%] [G loss: 0.693751]
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1163 [D loss: 0.693815, acc.: 50.00%] [G loss: 0.693240]
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1164 [D loss: 0.693187, acc.: 51.56%] [G loss: 0.696501]
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1165 [D loss: 0.692611, acc.: 51.95%] [G loss: 0.697005]
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1166 [D loss: 0.691640, acc.: 53.12%] [G loss: 0.699193]
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1167 [D loss: 0.694514, acc.: 49.41%] [G loss: 0.696637]
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1168 [D loss: 0.692872, acc.: 50.20%] [G loss: 0.699424]
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1169 [D loss: 0.692481, acc.: 50.59%] [G loss: 0.698624]
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1170 [D loss: 0.694014, acc.: 47.66%] [G loss: 0.699596]
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1171 [D loss: 0.693674, acc.: 48.83%] [G loss: 0.702041]
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1172 [D loss: 0.694537, acc.: 48.83%] [G loss: 0.700009]
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1173 [D loss: 0.694258, acc.: 48.63%] [G loss: 0.698217]
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1174 [D loss: 0.695669, acc.: 44.53%] [G loss: 0.698862]
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1175 [D loss: 0.695368, acc.: 43.75%] [G loss: 0.699591]
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1176 [D loss: 0.695384, acc.: 42.97%] [G loss: 0.699245]
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1177 [D loss: 0.694922, acc.: 42.58%] [G loss: 0.701527]
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1178 [D loss: 0.693685, acc.: 48.44%] [G loss: 0.702586]
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1179 [D loss: 0.693745, acc.: 48.83%] [G loss: 0.701828]
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1180 [D loss: 0.694217, acc.: 45.70%] [G loss: 0.702534]
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1181 [D loss: 0.692620, acc.: 52.93%] [G loss: 0.703580]
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1182 [D loss: 0.693272, acc.: 52.93%] [G loss: 0.703483]
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1183 [D loss: 0.691729, acc.: 52.93%] [G loss: 0.705537]
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1184 [D loss: 0.692886, acc.: 50.78%] [G loss: 0.706946]
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1185 [D loss: 0.692135, acc.: 53.32%] [G loss: 0.706228]
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1186 [D loss: 0.690166, acc.: 55.27%] [G loss: 0.710828]
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1187 [D loss: 0.690519, acc.: 58.40%] [G loss: 0.709940]
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1188 [D loss: 0.692071, acc.: 53.52%] [G loss: 0.711152]
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1189 [D loss: 0.692170, acc.: 53.12%] [G loss: 0.712211]
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1190 [D loss: 0.691213, acc.: 53.12%] [G loss: 0.712984]
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1191 [D loss: 0.689198, acc.: 53.91%] [G loss: 0.713172]
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1192 [D loss: 0.692290, acc.: 50.59%] [G loss: 0.711686]
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1193 [D loss: 0.692101, acc.: 51.76%] [G loss: 0.713043]
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1194 [D loss: 0.692819, acc.: 51.56%] [G loss: 0.710241]
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1195 [D loss: 0.692672, acc.: 50.59%] [G loss: 0.709903]
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1196 [D loss: 0.691364, acc.: 51.76%] [G loss: 0.711737]
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1197 [D loss: 0.696452, acc.: 44.73%] [G loss: 0.710494]
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1198 [D loss: 0.694831, acc.: 47.27%] [G loss: 0.710559]
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1199 [D loss: 0.697258, acc.: 45.70%] [G loss: 0.708176]
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1200 [D loss: 0.697126, acc.: 43.16%] [G loss: 0.707520]
1/1 [==============================] - 0s 18ms/step
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1201 [D loss: 0.696331, acc.: 48.44%] [G loss: 0.708423]
8/8 [==============================] - 0s 4ms/step
1202 [D loss: 0.695567, acc.: 48.05%] [G loss: 0.708472]
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1203 [D loss: 0.696517, acc.: 47.07%] [G loss: 0.707468]
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1204 [D loss: 0.694911, acc.: 47.46%] [G loss: 0.707828]
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1205 [D loss: 0.694744, acc.: 46.88%] [G loss: 0.709168]
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1206 [D loss: 0.692782, acc.: 49.22%] [G loss: 0.707079]
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1207 [D loss: 0.692442, acc.: 51.56%] [G loss: 0.709321]
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1208 [D loss: 0.692113, acc.: 51.56%] [G loss: 0.707721]
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1209 [D loss: 0.688010, acc.: 60.55%] [G loss: 0.709117]
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1210 [D loss: 0.690664, acc.: 53.32%] [G loss: 0.708469]
8/8 [==============================] - 0s 4ms/step
1211 [D loss: 0.689682, acc.: 57.62%] [G loss: 0.705695]
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1212 [D loss: 0.690301, acc.: 54.69%] [G loss: 0.706271]
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1213 [D loss: 0.689459, acc.: 56.25%] [G loss: 0.705936]
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1214 [D loss: 0.691626, acc.: 53.71%] [G loss: 0.704008]
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1215 [D loss: 0.690084, acc.: 56.25%] [G loss: 0.699250]
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1216 [D loss: 0.691830, acc.: 51.95%] [G loss: 0.701466]
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1217 [D loss: 0.692267, acc.: 50.78%] [G loss: 0.695248]
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1218 [D loss: 0.693453, acc.: 47.66%] [G loss: 0.694504]
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1219 [D loss: 0.693316, acc.: 50.39%] [G loss: 0.691804]
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1220 [D loss: 0.694799, acc.: 47.27%] [G loss: 0.689330]
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1221 [D loss: 0.694527, acc.: 49.22%] [G loss: 0.688454]
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1222 [D loss: 0.694871, acc.: 46.48%] [G loss: 0.686113]
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1223 [D loss: 0.694532, acc.: 48.83%] [G loss: 0.683360]
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1224 [D loss: 0.695100, acc.: 46.09%] [G loss: 0.684386]
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1225 [D loss: 0.693271, acc.: 49.22%] [G loss: 0.685773]
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1226 [D loss: 0.695403, acc.: 47.07%] [G loss: 0.684082]
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1227 [D loss: 0.694141, acc.: 48.44%] [G loss: 0.686420]
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1228 [D loss: 0.693238, acc.: 49.61%] [G loss: 0.687288]
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1229 [D loss: 0.692698, acc.: 50.98%] [G loss: 0.686749]
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1230 [D loss: 0.692634, acc.: 49.22%] [G loss: 0.689781]
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1231 [D loss: 0.691779, acc.: 53.52%] [G loss: 0.688850]
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1232 [D loss: 0.693022, acc.: 51.76%] [G loss: 0.691654]
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1233 [D loss: 0.690460, acc.: 53.32%] [G loss: 0.689823]
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1234 [D loss: 0.691644, acc.: 52.34%] [G loss: 0.687547]
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1235 [D loss: 0.693089, acc.: 49.41%] [G loss: 0.691315]
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1236 [D loss: 0.691029, acc.: 51.76%] [G loss: 0.688326]
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1237 [D loss: 0.693036, acc.: 48.83%] [G loss: 0.691113]
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1238 [D loss: 0.693095, acc.: 47.07%] [G loss: 0.689696]
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1239 [D loss: 0.694352, acc.: 48.24%] [G loss: 0.688827]
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1240 [D loss: 0.694287, acc.: 49.02%] [G loss: 0.689322]
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1241 [D loss: 0.696505, acc.: 43.75%] [G loss: 0.685237]
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1242 [D loss: 0.695877, acc.: 45.31%] [G loss: 0.690872]
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1243 [D loss: 0.697142, acc.: 42.97%] [G loss: 0.691176]
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1244 [D loss: 0.696737, acc.: 42.97%] [G loss: 0.688846]
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1245 [D loss: 0.695838, acc.: 47.07%] [G loss: 0.691165]
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1246 [D loss: 0.697164, acc.: 41.60%] [G loss: 0.691809]
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1247 [D loss: 0.697416, acc.: 41.21%] [G loss: 0.692218]
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1248 [D loss: 0.694665, acc.: 44.53%] [G loss: 0.693402]
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1249 [D loss: 0.694771, acc.: 46.09%] [G loss: 0.694244]
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1250 [D loss: 0.694942, acc.: 45.12%] [G loss: 0.694176]
1/1 [==============================] - 0s 17ms/step
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1251 [D loss: 0.695279, acc.: 44.73%] [G loss: 0.696138]
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1252 [D loss: 0.694035, acc.: 47.27%] [G loss: 0.697205]
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1253 [D loss: 0.693645, acc.: 47.07%] [G loss: 0.694697]
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1254 [D loss: 0.695059, acc.: 44.92%] [G loss: 0.695891]
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1255 [D loss: 0.693813, acc.: 50.59%] [G loss: 0.697882]
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1256 [D loss: 0.695766, acc.: 46.09%] [G loss: 0.698756]
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1257 [D loss: 0.694491, acc.: 46.88%] [G loss: 0.702111]
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1258 [D loss: 0.694543, acc.: 44.92%] [G loss: 0.703062]
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1259 [D loss: 0.693586, acc.: 48.24%] [G loss: 0.703201]
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1260 [D loss: 0.692658, acc.: 50.98%] [G loss: 0.704621]
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1261 [D loss: 0.692396, acc.: 50.98%] [G loss: 0.707065]
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1262 [D loss: 0.693808, acc.: 50.00%] [G loss: 0.708749]
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1263 [D loss: 0.691284, acc.: 52.15%] [G loss: 0.711296]
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1264 [D loss: 0.692480, acc.: 50.98%] [G loss: 0.713562]
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1265 [D loss: 0.692038, acc.: 49.41%] [G loss: 0.714647]
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1266 [D loss: 0.691167, acc.: 52.15%] [G loss: 0.713204]
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1267 [D loss: 0.691172, acc.: 55.66%] [G loss: 0.718358]
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1268 [D loss: 0.690650, acc.: 54.30%] [G loss: 0.719808]
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1269 [D loss: 0.689461, acc.: 56.64%] [G loss: 0.720190]
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1270 [D loss: 0.689445, acc.: 52.34%] [G loss: 0.723293]
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1271 [D loss: 0.688965, acc.: 55.27%] [G loss: 0.723319]
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1272 [D loss: 0.688121, acc.: 56.45%] [G loss: 0.723964]
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1273 [D loss: 0.690388, acc.: 54.10%] [G loss: 0.722419]
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1274 [D loss: 0.692414, acc.: 50.00%] [G loss: 0.724617]
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1275 [D loss: 0.692270, acc.: 49.80%] [G loss: 0.722394]
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1276 [D loss: 0.694001, acc.: 48.63%] [G loss: 0.720585]
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1277 [D loss: 0.695701, acc.: 46.09%] [G loss: 0.717757]
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1278 [D loss: 0.696753, acc.: 48.05%] [G loss: 0.713527]
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1279 [D loss: 0.695298, acc.: 50.59%] [G loss: 0.712850]
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1280 [D loss: 0.695326, acc.: 49.22%] [G loss: 0.713172]
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1281 [D loss: 0.697141, acc.: 45.12%] [G loss: 0.706718]
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1282 [D loss: 0.696287, acc.: 46.48%] [G loss: 0.705173]
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1283 [D loss: 0.695963, acc.: 47.66%] [G loss: 0.704935]
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1284 [D loss: 0.696861, acc.: 44.14%] [G loss: 0.701350]
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1285 [D loss: 0.697059, acc.: 43.75%] [G loss: 0.698344]
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1286 [D loss: 0.696794, acc.: 42.19%] [G loss: 0.696870]
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1287 [D loss: 0.695465, acc.: 47.46%] [G loss: 0.695709]
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1288 [D loss: 0.695944, acc.: 45.70%] [G loss: 0.697980]
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1289 [D loss: 0.694186, acc.: 49.22%] [G loss: 0.698681]
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1290 [D loss: 0.694971, acc.: 46.29%] [G loss: 0.695701]
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1291 [D loss: 0.694292, acc.: 47.66%] [G loss: 0.697521]
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1292 [D loss: 0.693279, acc.: 50.20%] [G loss: 0.696681]
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1293 [D loss: 0.692355, acc.: 50.78%] [G loss: 0.696876]
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1294 [D loss: 0.692019, acc.: 53.71%] [G loss: 0.700169]
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1295 [D loss: 0.690478, acc.: 53.71%] [G loss: 0.699097]
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1296 [D loss: 0.690897, acc.: 58.20%] [G loss: 0.698223]
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1297 [D loss: 0.692263, acc.: 52.34%] [G loss: 0.697527]
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1298 [D loss: 0.690427, acc.: 57.42%] [G loss: 0.696805]
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1299 [D loss: 0.691736, acc.: 51.56%] [G loss: 0.695095]
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1300 [D loss: 0.691570, acc.: 50.59%] [G loss: 0.692695]
1/1 [==============================] - 0s 18ms/step
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1301 [D loss: 0.690482, acc.: 56.05%] [G loss: 0.694600]
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1302 [D loss: 0.693710, acc.: 52.15%] [G loss: 0.693777]
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1303 [D loss: 0.693170, acc.: 50.00%] [G loss: 0.693207]
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1304 [D loss: 0.692228, acc.: 53.71%] [G loss: 0.693659]
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1305 [D loss: 0.695533, acc.: 48.24%] [G loss: 0.694421]
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1306 [D loss: 0.693925, acc.: 48.05%] [G loss: 0.693664]
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1307 [D loss: 0.695371, acc.: 45.70%] [G loss: 0.693527]
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1308 [D loss: 0.696873, acc.: 44.53%] [G loss: 0.695327]
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1309 [D loss: 0.696510, acc.: 44.53%] [G loss: 0.696684]
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1310 [D loss: 0.693818, acc.: 46.48%] [G loss: 0.696473]
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1311 [D loss: 0.692518, acc.: 49.22%] [G loss: 0.699605]
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1312 [D loss: 0.693362, acc.: 50.78%] [G loss: 0.700392]
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1313 [D loss: 0.693087, acc.: 45.90%] [G loss: 0.699618]
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1314 [D loss: 0.695162, acc.: 47.85%] [G loss: 0.700144]
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1315 [D loss: 0.692256, acc.: 50.00%] [G loss: 0.697954]
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1316 [D loss: 0.693109, acc.: 52.34%] [G loss: 0.698340]
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1317 [D loss: 0.693737, acc.: 47.66%] [G loss: 0.701139]
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1318 [D loss: 0.694836, acc.: 46.68%] [G loss: 0.696785]
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1319 [D loss: 0.698338, acc.: 39.84%] [G loss: 0.697987]
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1320 [D loss: 0.695703, acc.: 48.05%] [G loss: 0.696811]
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1321 [D loss: 0.694380, acc.: 50.39%] [G loss: 0.700132]
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1322 [D loss: 0.694042, acc.: 45.31%] [G loss: 0.698527]
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1323 [D loss: 0.693925, acc.: 49.02%] [G loss: 0.697015]
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1324 [D loss: 0.697181, acc.: 41.99%] [G loss: 0.697003]
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1325 [D loss: 0.696772, acc.: 43.36%] [G loss: 0.698048]
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1326 [D loss: 0.695686, acc.: 43.95%] [G loss: 0.702392]
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1327 [D loss: 0.695568, acc.: 44.14%] [G loss: 0.699511]
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1328 [D loss: 0.694545, acc.: 46.09%] [G loss: 0.701798]
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1329 [D loss: 0.694008, acc.: 48.63%] [G loss: 0.702352]
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1330 [D loss: 0.694341, acc.: 48.63%] [G loss: 0.705837]
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1331 [D loss: 0.693124, acc.: 49.02%] [G loss: 0.706118]
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1332 [D loss: 0.692298, acc.: 52.15%] [G loss: 0.706880]
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1333 [D loss: 0.692908, acc.: 52.54%] [G loss: 0.707573]
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1334 [D loss: 0.693313, acc.: 51.76%] [G loss: 0.710483]
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1335 [D loss: 0.691926, acc.: 51.76%] [G loss: 0.712631]
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1336 [D loss: 0.692118, acc.: 55.66%] [G loss: 0.712366]
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1337 [D loss: 0.691291, acc.: 55.86%] [G loss: 0.712811]
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1338 [D loss: 0.689630, acc.: 56.84%] [G loss: 0.714838]
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1339 [D loss: 0.689514, acc.: 55.66%] [G loss: 0.714988]
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1340 [D loss: 0.691111, acc.: 55.08%] [G loss: 0.716471]
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1341 [D loss: 0.691006, acc.: 54.88%] [G loss: 0.713303]
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1342 [D loss: 0.689572, acc.: 57.42%] [G loss: 0.715792]
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1343 [D loss: 0.690822, acc.: 54.69%] [G loss: 0.712570]
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1344 [D loss: 0.692316, acc.: 52.54%] [G loss: 0.711455]
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1345 [D loss: 0.691383, acc.: 57.03%] [G loss: 0.710670]
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1346 [D loss: 0.691899, acc.: 52.73%] [G loss: 0.711247]
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1347 [D loss: 0.693788, acc.: 50.00%] [G loss: 0.706795]
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1348 [D loss: 0.696462, acc.: 47.66%] [G loss: 0.706117]
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1349 [D loss: 0.695051, acc.: 46.68%] [G loss: 0.701669]
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1350 [D loss: 0.695740, acc.: 45.90%] [G loss: 0.700546]
1/1 [==============================] - 0s 16ms/step
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1351 [D loss: 0.696286, acc.: 46.88%] [G loss: 0.699291]
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1352 [D loss: 0.696384, acc.: 44.53%] [G loss: 0.698642]
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1353 [D loss: 0.696489, acc.: 43.95%] [G loss: 0.694723]
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1354 [D loss: 0.694499, acc.: 46.09%] [G loss: 0.694461]
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1355 [D loss: 0.693699, acc.: 48.44%] [G loss: 0.695843]
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1356 [D loss: 0.694551, acc.: 46.29%] [G loss: 0.693777]
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1357 [D loss: 0.692742, acc.: 48.24%] [G loss: 0.695646]
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1358 [D loss: 0.695262, acc.: 43.95%] [G loss: 0.695695]
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1359 [D loss: 0.692735, acc.: 47.46%] [G loss: 0.696913]
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1360 [D loss: 0.692969, acc.: 48.83%] [G loss: 0.698144]
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1361 [D loss: 0.691676, acc.: 49.61%] [G loss: 0.697263]
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1362 [D loss: 0.692087, acc.: 50.20%] [G loss: 0.698425]
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1363 [D loss: 0.691606, acc.: 52.73%] [G loss: 0.700836]
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1364 [D loss: 0.689419, acc.: 58.40%] [G loss: 0.698932]
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1365 [D loss: 0.690178, acc.: 54.30%] [G loss: 0.700356]
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1366 [D loss: 0.694085, acc.: 46.88%] [G loss: 0.699174]
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1367 [D loss: 0.693219, acc.: 48.83%] [G loss: 0.696101]
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1368 [D loss: 0.694032, acc.: 46.29%] [G loss: 0.693380]
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1369 [D loss: 0.696149, acc.: 44.34%] [G loss: 0.698928]
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1370 [D loss: 0.696075, acc.: 45.31%] [G loss: 0.698041]
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1371 [D loss: 0.696225, acc.: 50.98%] [G loss: 0.695008]
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1372 [D loss: 0.696370, acc.: 44.14%] [G loss: 0.695272]
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1373 [D loss: 0.697572, acc.: 41.41%] [G loss: 0.694358]
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1374 [D loss: 0.697173, acc.: 45.90%] [G loss: 0.694087]
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1375 [D loss: 0.699251, acc.: 41.80%] [G loss: 0.692712]
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1376 [D loss: 0.694967, acc.: 47.85%] [G loss: 0.696064]
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1377 [D loss: 0.697113, acc.: 45.51%] [G loss: 0.697966]
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1378 [D loss: 0.693861, acc.: 49.02%] [G loss: 0.699671]
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1379 [D loss: 0.694869, acc.: 47.27%] [G loss: 0.698829]
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1380 [D loss: 0.692909, acc.: 51.17%] [G loss: 0.702360]
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1381 [D loss: 0.690869, acc.: 54.30%] [G loss: 0.703933]
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1382 [D loss: 0.690878, acc.: 53.71%] [G loss: 0.704271]
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1383 [D loss: 0.689787, acc.: 55.08%] [G loss: 0.703361]
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1384 [D loss: 0.689481, acc.: 55.27%] [G loss: 0.704632]
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1385 [D loss: 0.691105, acc.: 50.20%] [G loss: 0.703675]
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1386 [D loss: 0.689423, acc.: 59.18%] [G loss: 0.703911]
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1387 [D loss: 0.690135, acc.: 51.95%] [G loss: 0.703704]
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1388 [D loss: 0.691337, acc.: 52.34%] [G loss: 0.701448]
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1389 [D loss: 0.692136, acc.: 50.78%] [G loss: 0.699344]
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1390 [D loss: 0.692708, acc.: 49.61%] [G loss: 0.701336]
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1391 [D loss: 0.693920, acc.: 46.88%] [G loss: 0.695203]
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1392 [D loss: 0.694250, acc.: 48.24%] [G loss: 0.693459]
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1393 [D loss: 0.696463, acc.: 43.75%] [G loss: 0.693068]
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1394 [D loss: 0.696871, acc.: 41.60%] [G loss: 0.691800]
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1395 [D loss: 0.696968, acc.: 40.62%] [G loss: 0.690814]
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1396 [D loss: 0.697763, acc.: 38.67%] [G loss: 0.691090]
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1397 [D loss: 0.697338, acc.: 39.26%] [G loss: 0.694450]
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1398 [D loss: 0.698009, acc.: 39.06%] [G loss: 0.696382]
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1399 [D loss: 0.694707, acc.: 47.46%] [G loss: 0.698212]
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1400 [D loss: 0.692961, acc.: 50.59%] [G loss: 0.700185]
1/1 [==============================] - 0s 18ms/step
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1401 [D loss: 0.692192, acc.: 53.71%] [G loss: 0.699458]
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1402 [D loss: 0.691142, acc.: 55.66%] [G loss: 0.700948]
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1403 [D loss: 0.689414, acc.: 57.23%] [G loss: 0.703033]
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1404 [D loss: 0.690017, acc.: 58.79%] [G loss: 0.701794]
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1405 [D loss: 0.689479, acc.: 54.69%] [G loss: 0.705029]
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1406 [D loss: 0.690868, acc.: 55.66%] [G loss: 0.704407]
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1407 [D loss: 0.691674, acc.: 50.20%] [G loss: 0.700788]
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1408 [D loss: 0.690744, acc.: 54.69%] [G loss: 0.702320]
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1409 [D loss: 0.694491, acc.: 47.66%] [G loss: 0.699392]
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1410 [D loss: 0.693309, acc.: 47.46%] [G loss: 0.697868]
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1411 [D loss: 0.696263, acc.: 45.70%] [G loss: 0.702000]
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1412 [D loss: 0.694847, acc.: 45.31%] [G loss: 0.701754]
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1413 [D loss: 0.694311, acc.: 47.27%] [G loss: 0.700403]
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1414 [D loss: 0.695344, acc.: 46.88%] [G loss: 0.700069]
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1415 [D loss: 0.694180, acc.: 47.66%] [G loss: 0.699499]
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1416 [D loss: 0.695847, acc.: 47.66%] [G loss: 0.699361]
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1417 [D loss: 0.694389, acc.: 48.63%] [G loss: 0.699085]
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1418 [D loss: 0.696332, acc.: 45.51%] [G loss: 0.699167]
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1419 [D loss: 0.695874, acc.: 46.29%] [G loss: 0.699877]
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1420 [D loss: 0.691913, acc.: 53.32%] [G loss: 0.700119]
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1421 [D loss: 0.690960, acc.: 55.08%] [G loss: 0.701696]
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1422 [D loss: 0.689824, acc.: 55.86%] [G loss: 0.702429]
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1423 [D loss: 0.688005, acc.: 58.79%] [G loss: 0.699949]
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1424 [D loss: 0.687367, acc.: 59.18%] [G loss: 0.701709]
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1425 [D loss: 0.688946, acc.: 57.03%] [G loss: 0.700240]
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1426 [D loss: 0.689074, acc.: 56.05%] [G loss: 0.698708]
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1427 [D loss: 0.691109, acc.: 55.47%] [G loss: 0.694803]
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1428 [D loss: 0.692804, acc.: 52.73%] [G loss: 0.695696]
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1429 [D loss: 0.691372, acc.: 54.49%] [G loss: 0.690127]
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1430 [D loss: 0.696748, acc.: 47.27%] [G loss: 0.686920]
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1431 [D loss: 0.698858, acc.: 48.44%] [G loss: 0.687989]
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1432 [D loss: 0.696181, acc.: 50.59%] [G loss: 0.683291]
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1433 [D loss: 0.695795, acc.: 50.20%] [G loss: 0.685605]
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1434 [D loss: 0.698973, acc.: 46.68%] [G loss: 0.682247]
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1435 [D loss: 0.696060, acc.: 46.09%] [G loss: 0.687559]
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1436 [D loss: 0.698413, acc.: 45.90%] [G loss: 0.685846]
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1437 [D loss: 0.696981, acc.: 46.09%] [G loss: 0.687034]
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1438 [D loss: 0.697616, acc.: 45.12%] [G loss: 0.689710]
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1439 [D loss: 0.694842, acc.: 47.46%] [G loss: 0.689029]
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1440 [D loss: 0.695516, acc.: 46.68%] [G loss: 0.694761]
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1441 [D loss: 0.693448, acc.: 46.29%] [G loss: 0.697258]
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1442 [D loss: 0.694342, acc.: 47.46%] [G loss: 0.697304]
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1443 [D loss: 0.691190, acc.: 54.49%] [G loss: 0.701786]
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1444 [D loss: 0.692942, acc.: 50.59%] [G loss: 0.705068]
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1445 [D loss: 0.691047, acc.: 54.69%] [G loss: 0.706392]
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1446 [D loss: 0.690390, acc.: 53.71%] [G loss: 0.709549]
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1447 [D loss: 0.690597, acc.: 54.69%] [G loss: 0.711398]
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1448 [D loss: 0.688409, acc.: 56.25%] [G loss: 0.710894]
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1449 [D loss: 0.689575, acc.: 52.73%] [G loss: 0.713866]
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1450 [D loss: 0.689387, acc.: 53.32%] [G loss: 0.713484]
1/1 [==============================] - 0s 16ms/step
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1451 [D loss: 0.688161, acc.: 56.05%] [G loss: 0.711838]
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1452 [D loss: 0.690808, acc.: 51.95%] [G loss: 0.718507]
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1453 [D loss: 0.694087, acc.: 49.41%] [G loss: 0.707598]
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1454 [D loss: 0.694522, acc.: 47.27%] [G loss: 0.704425]
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1455 [D loss: 0.696588, acc.: 46.29%] [G loss: 0.705785]
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1456 [D loss: 0.696247, acc.: 44.73%] [G loss: 0.704147]
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1457 [D loss: 0.699109, acc.: 41.80%] [G loss: 0.700745]
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1458 [D loss: 0.698171, acc.: 42.77%] [G loss: 0.702822]
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1459 [D loss: 0.697743, acc.: 42.77%] [G loss: 0.701002]
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1460 [D loss: 0.696751, acc.: 45.31%] [G loss: 0.701036]
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1461 [D loss: 0.695845, acc.: 49.02%] [G loss: 0.702090]
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1462 [D loss: 0.694697, acc.: 48.83%] [G loss: 0.703018]
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1463 [D loss: 0.692909, acc.: 53.52%] [G loss: 0.702200]
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1464 [D loss: 0.691853, acc.: 54.69%] [G loss: 0.701483]
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1465 [D loss: 0.692356, acc.: 53.12%] [G loss: 0.702420]
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1466 [D loss: 0.690166, acc.: 57.42%] [G loss: 0.700863]
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1467 [D loss: 0.691399, acc.: 54.88%] [G loss: 0.699167]
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1468 [D loss: 0.691510, acc.: 54.10%] [G loss: 0.696576]
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1469 [D loss: 0.692679, acc.: 50.98%] [G loss: 0.693301]
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1470 [D loss: 0.692398, acc.: 51.17%] [G loss: 0.696116]
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1471 [D loss: 0.694871, acc.: 47.85%] [G loss: 0.692791]
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1472 [D loss: 0.694833, acc.: 46.88%] [G loss: 0.693133]
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1473 [D loss: 0.695197, acc.: 48.44%] [G loss: 0.692628]
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1474 [D loss: 0.696052, acc.: 44.34%] [G loss: 0.691844]
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1475 [D loss: 0.696091, acc.: 44.92%] [G loss: 0.689763]
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1476 [D loss: 0.695961, acc.: 44.73%] [G loss: 0.690050]
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1477 [D loss: 0.695471, acc.: 46.68%] [G loss: 0.692448]
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1478 [D loss: 0.695658, acc.: 43.55%] [G loss: 0.692083]
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1479 [D loss: 0.695560, acc.: 40.62%] [G loss: 0.692564]
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1480 [D loss: 0.696067, acc.: 43.75%] [G loss: 0.694136]
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1481 [D loss: 0.694857, acc.: 45.90%] [G loss: 0.693271]
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1482 [D loss: 0.693535, acc.: 49.61%] [G loss: 0.693301]
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1483 [D loss: 0.693688, acc.: 48.63%] [G loss: 0.696737]
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1484 [D loss: 0.693471, acc.: 49.80%] [G loss: 0.698215]
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1485 [D loss: 0.693172, acc.: 51.56%] [G loss: 0.697745]
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1486 [D loss: 0.692163, acc.: 51.56%] [G loss: 0.698806]
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1487 [D loss: 0.691976, acc.: 50.59%] [G loss: 0.701023]
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1488 [D loss: 0.691425, acc.: 53.71%] [G loss: 0.700913]
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1489 [D loss: 0.691098, acc.: 52.73%] [G loss: 0.703226]
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1490 [D loss: 0.690207, acc.: 56.45%] [G loss: 0.704418]
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1491 [D loss: 0.690530, acc.: 54.49%] [G loss: 0.704927]
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1492 [D loss: 0.689041, acc.: 57.42%] [G loss: 0.704257]
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1493 [D loss: 0.692256, acc.: 52.93%] [G loss: 0.705000]
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1494 [D loss: 0.689499, acc.: 54.49%] [G loss: 0.705683]
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1495 [D loss: 0.691528, acc.: 50.98%] [G loss: 0.708450]
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1496 [D loss: 0.690381, acc.: 54.69%] [G loss: 0.708971]
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1497 [D loss: 0.691842, acc.: 52.15%] [G loss: 0.708930]
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1498 [D loss: 0.690424, acc.: 55.27%] [G loss: 0.708990]
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1499 [D loss: 0.693387, acc.: 50.59%] [G loss: 0.710072]
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1500 [D loss: 0.691680, acc.: 52.34%] [G loss: 0.706039]
1/1 [==============================] - 0s 16ms/step
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1501 [D loss: 0.693102, acc.: 50.20%] [G loss: 0.709198]
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1502 [D loss: 0.692743, acc.: 52.54%] [G loss: 0.707405]
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1503 [D loss: 0.694695, acc.: 48.44%] [G loss: 0.704907]
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1504 [D loss: 0.695209, acc.: 45.51%] [G loss: 0.703847]
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1505 [D loss: 0.696012, acc.: 48.63%] [G loss: 0.703768]
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1506 [D loss: 0.697482, acc.: 45.31%] [G loss: 0.707237]
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1507 [D loss: 0.695990, acc.: 44.73%] [G loss: 0.703562]
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1508 [D loss: 0.697140, acc.: 41.99%] [G loss: 0.701340]
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1509 [D loss: 0.696860, acc.: 44.14%] [G loss: 0.697777]
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1510 [D loss: 0.698825, acc.: 38.48%] [G loss: 0.698409]
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1511 [D loss: 0.695958, acc.: 43.16%] [G loss: 0.697231]
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1512 [D loss: 0.696082, acc.: 49.22%] [G loss: 0.696835]
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1513 [D loss: 0.696616, acc.: 42.58%] [G loss: 0.698369]
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1514 [D loss: 0.695258, acc.: 43.95%] [G loss: 0.698204]
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1515 [D loss: 0.694837, acc.: 42.19%] [G loss: 0.697029]
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1516 [D loss: 0.695575, acc.: 42.97%] [G loss: 0.698336]
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1517 [D loss: 0.694380, acc.: 47.46%] [G loss: 0.696294]
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1518 [D loss: 0.695248, acc.: 44.92%] [G loss: 0.696094]
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1519 [D loss: 0.693250, acc.: 49.80%] [G loss: 0.696569]
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1520 [D loss: 0.692301, acc.: 49.41%] [G loss: 0.697714]
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1521 [D loss: 0.691991, acc.: 52.54%] [G loss: 0.698701]
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1522 [D loss: 0.691753, acc.: 54.10%] [G loss: 0.696521]
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1523 [D loss: 0.690636, acc.: 58.01%] [G loss: 0.698979]
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1524 [D loss: 0.690722, acc.: 58.40%] [G loss: 0.699483]
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1525 [D loss: 0.690376, acc.: 58.20%] [G loss: 0.699987]
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1526 [D loss: 0.689572, acc.: 58.59%] [G loss: 0.698852]
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1527 [D loss: 0.690734, acc.: 55.27%] [G loss: 0.696775]
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1528 [D loss: 0.689990, acc.: 59.96%] [G loss: 0.699480]
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1529 [D loss: 0.688942, acc.: 58.98%] [G loss: 0.698081]
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1530 [D loss: 0.688869, acc.: 58.59%] [G loss: 0.698396]
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1531 [D loss: 0.689214, acc.: 57.03%] [G loss: 0.694189]
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1532 [D loss: 0.689115, acc.: 56.84%] [G loss: 0.690540]
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1533 [D loss: 0.692007, acc.: 51.56%] [G loss: 0.689461]
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1534 [D loss: 0.691952, acc.: 51.17%] [G loss: 0.687421]
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1535 [D loss: 0.693601, acc.: 48.05%] [G loss: 0.685964]
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1536 [D loss: 0.695259, acc.: 45.51%] [G loss: 0.683099]
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1537 [D loss: 0.695680, acc.: 41.99%] [G loss: 0.689686]
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1538 [D loss: 0.694441, acc.: 47.66%] [G loss: 0.687805]
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1539 [D loss: 0.693699, acc.: 47.46%] [G loss: 0.684592]
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1540 [D loss: 0.693060, acc.: 50.59%] [G loss: 0.686655]
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1541 [D loss: 0.694720, acc.: 44.92%] [G loss: 0.686792]
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1542 [D loss: 0.695371, acc.: 46.88%] [G loss: 0.685432]
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1543 [D loss: 0.695938, acc.: 42.97%] [G loss: 0.687750]
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1544 [D loss: 0.694739, acc.: 46.09%] [G loss: 0.688844]
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1545 [D loss: 0.693370, acc.: 50.98%] [G loss: 0.688783]
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1546 [D loss: 0.693616, acc.: 50.98%] [G loss: 0.687374]
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1547 [D loss: 0.695526, acc.: 47.85%] [G loss: 0.690400]
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1548 [D loss: 0.694803, acc.: 45.70%] [G loss: 0.690817]
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1549 [D loss: 0.692679, acc.: 50.59%] [G loss: 0.692267]
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1550 [D loss: 0.695162, acc.: 47.27%] [G loss: 0.692045]
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1551 [D loss: 0.694327, acc.: 48.83%] [G loss: 0.692603]
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1552 [D loss: 0.693225, acc.: 50.20%] [G loss: 0.696404]
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1553 [D loss: 0.693879, acc.: 49.22%] [G loss: 0.696486]
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1554 [D loss: 0.693613, acc.: 47.46%] [G loss: 0.697073]
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1555 [D loss: 0.694427, acc.: 49.22%] [G loss: 0.698753]
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1556 [D loss: 0.693117, acc.: 51.37%] [G loss: 0.697976]
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1557 [D loss: 0.694954, acc.: 43.95%] [G loss: 0.698047]
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1558 [D loss: 0.692209, acc.: 50.78%] [G loss: 0.698059]
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1559 [D loss: 0.694015, acc.: 44.92%] [G loss: 0.700123]
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1560 [D loss: 0.694913, acc.: 45.51%] [G loss: 0.697303]
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1561 [D loss: 0.694844, acc.: 47.46%] [G loss: 0.698683]
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1562 [D loss: 0.693779, acc.: 47.85%] [G loss: 0.699380]
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1563 [D loss: 0.693314, acc.: 49.22%] [G loss: 0.697874]
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1564 [D loss: 0.692490, acc.: 50.39%] [G loss: 0.700576]
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1565 [D loss: 0.695869, acc.: 44.53%] [G loss: 0.700683]
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1566 [D loss: 0.693860, acc.: 47.27%] [G loss: 0.700789]
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1567 [D loss: 0.692394, acc.: 52.34%] [G loss: 0.699889]
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1568 [D loss: 0.693817, acc.: 48.44%] [G loss: 0.699111]
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1569 [D loss: 0.691534, acc.: 53.91%] [G loss: 0.698130]
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1570 [D loss: 0.693235, acc.: 51.95%] [G loss: 0.697738]
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1571 [D loss: 0.693728, acc.: 50.59%] [G loss: 0.699990]
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1572 [D loss: 0.692722, acc.: 51.17%] [G loss: 0.698477]
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1573 [D loss: 0.694762, acc.: 47.27%] [G loss: 0.698842]
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1574 [D loss: 0.692647, acc.: 50.98%] [G loss: 0.699380]
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1575 [D loss: 0.693582, acc.: 51.76%] [G loss: 0.698476]
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1576 [D loss: 0.694353, acc.: 47.85%] [G loss: 0.698301]
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1577 [D loss: 0.694676, acc.: 49.61%] [G loss: 0.697066]
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1578 [D loss: 0.693242, acc.: 47.66%] [G loss: 0.696733]
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1579 [D loss: 0.694622, acc.: 45.90%] [G loss: 0.697697]
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1580 [D loss: 0.694234, acc.: 48.24%] [G loss: 0.700544]
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1581 [D loss: 0.693153, acc.: 54.10%] [G loss: 0.699208]
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1582 [D loss: 0.693232, acc.: 49.41%] [G loss: 0.700135]
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1583 [D loss: 0.692555, acc.: 51.95%] [G loss: 0.699551]
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1584 [D loss: 0.692860, acc.: 53.52%] [G loss: 0.699462]
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1585 [D loss: 0.694060, acc.: 48.83%] [G loss: 0.699888]
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1586 [D loss: 0.690283, acc.: 55.08%] [G loss: 0.697014]
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1587 [D loss: 0.691153, acc.: 53.12%] [G loss: 0.701137]
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1588 [D loss: 0.692027, acc.: 52.34%] [G loss: 0.698670]
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1589 [D loss: 0.693663, acc.: 49.02%] [G loss: 0.698967]
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1590 [D loss: 0.692943, acc.: 50.59%] [G loss: 0.696851]
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1591 [D loss: 0.692841, acc.: 48.63%] [G loss: 0.697751]
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1592 [D loss: 0.694017, acc.: 49.41%] [G loss: 0.698162]
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1593 [D loss: 0.693549, acc.: 47.07%] [G loss: 0.697571]
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1594 [D loss: 0.693026, acc.: 51.17%] [G loss: 0.694602]
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1595 [D loss: 0.693505, acc.: 49.80%] [G loss: 0.697607]
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1596 [D loss: 0.693717, acc.: 49.80%] [G loss: 0.696683]
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1597 [D loss: 0.693847, acc.: 48.63%] [G loss: 0.695790]
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1598 [D loss: 0.694462, acc.: 47.46%] [G loss: 0.697104]
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1599 [D loss: 0.692997, acc.: 49.80%] [G loss: 0.696096]
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1600 [D loss: 0.693664, acc.: 50.98%] [G loss: 0.696083]
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1601 [D loss: 0.695209, acc.: 44.92%] [G loss: 0.696032]
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1602 [D loss: 0.693640, acc.: 45.90%] [G loss: 0.695792]
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1603 [D loss: 0.692338, acc.: 52.54%] [G loss: 0.697732]
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1604 [D loss: 0.692945, acc.: 51.56%] [G loss: 0.698225]
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1605 [D loss: 0.692981, acc.: 51.37%] [G loss: 0.697997]
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1606 [D loss: 0.692055, acc.: 52.34%] [G loss: 0.696457]
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1607 [D loss: 0.692467, acc.: 50.59%] [G loss: 0.699452]
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1608 [D loss: 0.692820, acc.: 50.39%] [G loss: 0.697796]
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1609 [D loss: 0.691770, acc.: 53.52%] [G loss: 0.699045]
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1610 [D loss: 0.692388, acc.: 52.34%] [G loss: 0.696378]
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1611 [D loss: 0.693956, acc.: 45.70%] [G loss: 0.697908]
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1612 [D loss: 0.695435, acc.: 45.51%] [G loss: 0.694501]
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1613 [D loss: 0.695106, acc.: 49.61%] [G loss: 0.696773]
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1614 [D loss: 0.693621, acc.: 49.80%] [G loss: 0.696343]
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1615 [D loss: 0.694070, acc.: 47.85%] [G loss: 0.695617]
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1616 [D loss: 0.694615, acc.: 47.27%] [G loss: 0.696732]
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1617 [D loss: 0.696939, acc.: 42.38%] [G loss: 0.696667]
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1618 [D loss: 0.694499, acc.: 45.90%] [G loss: 0.698466]
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1619 [D loss: 0.694619, acc.: 43.16%] [G loss: 0.697908]
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1620 [D loss: 0.695208, acc.: 45.51%] [G loss: 0.697767]
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1621 [D loss: 0.695506, acc.: 44.14%] [G loss: 0.696561]
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1622 [D loss: 0.694434, acc.: 48.63%] [G loss: 0.697947]
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1623 [D loss: 0.692678, acc.: 47.46%] [G loss: 0.697558]
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1624 [D loss: 0.693801, acc.: 50.78%] [G loss: 0.698372]
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1625 [D loss: 0.692057, acc.: 54.30%] [G loss: 0.698322]
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1626 [D loss: 0.692296, acc.: 53.32%] [G loss: 0.697998]
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1627 [D loss: 0.692598, acc.: 50.00%] [G loss: 0.701716]
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1628 [D loss: 0.692784, acc.: 51.95%] [G loss: 0.697794]
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1629 [D loss: 0.691852, acc.: 53.12%] [G loss: 0.702069]
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1630 [D loss: 0.691463, acc.: 53.71%] [G loss: 0.701896]
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1631 [D loss: 0.691234, acc.: 56.84%] [G loss: 0.700267]
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1632 [D loss: 0.691140, acc.: 54.49%] [G loss: 0.701757]
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1633 [D loss: 0.693348, acc.: 50.20%] [G loss: 0.699783]
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1634 [D loss: 0.691715, acc.: 53.52%] [G loss: 0.701794]
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1635 [D loss: 0.691092, acc.: 54.88%] [G loss: 0.701403]
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1636 [D loss: 0.691909, acc.: 54.30%] [G loss: 0.695561]
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1637 [D loss: 0.691837, acc.: 53.91%] [G loss: 0.698003]
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1638 [D loss: 0.694017, acc.: 49.41%] [G loss: 0.695548]
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1639 [D loss: 0.693038, acc.: 50.00%] [G loss: 0.697077]
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1640 [D loss: 0.695693, acc.: 43.55%] [G loss: 0.696037]
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1641 [D loss: 0.694465, acc.: 49.22%] [G loss: 0.695482]
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1642 [D loss: 0.694456, acc.: 47.07%] [G loss: 0.695645]
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1643 [D loss: 0.694509, acc.: 46.88%] [G loss: 0.690674]
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1644 [D loss: 0.696812, acc.: 44.73%] [G loss: 0.691104]
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1645 [D loss: 0.695347, acc.: 45.90%] [G loss: 0.691736]
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1646 [D loss: 0.696697, acc.: 44.92%] [G loss: 0.691817]
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1647 [D loss: 0.698012, acc.: 41.21%] [G loss: 0.692833]
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1648 [D loss: 0.695635, acc.: 43.95%] [G loss: 0.691217]
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1649 [D loss: 0.694816, acc.: 49.80%] [G loss: 0.693425]
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1650 [D loss: 0.695886, acc.: 42.77%] [G loss: 0.694202]
1/1 [==============================] - 0s 16ms/step
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1651 [D loss: 0.693985, acc.: 48.83%] [G loss: 0.694479]
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1652 [D loss: 0.694503, acc.: 47.85%] [G loss: 0.696627]
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1653 [D loss: 0.694292, acc.: 48.05%] [G loss: 0.700695]
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1654 [D loss: 0.693750, acc.: 48.83%] [G loss: 0.699225]
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1655 [D loss: 0.691507, acc.: 52.15%] [G loss: 0.701247]
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1656 [D loss: 0.691380, acc.: 56.64%] [G loss: 0.699072]
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1657 [D loss: 0.692350, acc.: 52.34%] [G loss: 0.699560]
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1658 [D loss: 0.690810, acc.: 54.88%] [G loss: 0.703089]
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1659 [D loss: 0.691032, acc.: 53.91%] [G loss: 0.703460]
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1660 [D loss: 0.690661, acc.: 55.27%] [G loss: 0.703716]
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1661 [D loss: 0.690836, acc.: 55.27%] [G loss: 0.701146]
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1662 [D loss: 0.690894, acc.: 55.47%] [G loss: 0.702416]
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1663 [D loss: 0.691570, acc.: 56.05%] [G loss: 0.700009]
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1664 [D loss: 0.692757, acc.: 52.54%] [G loss: 0.700618]
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1665 [D loss: 0.690482, acc.: 55.47%] [G loss: 0.701426]
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1666 [D loss: 0.691296, acc.: 56.84%] [G loss: 0.701632]
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1667 [D loss: 0.692265, acc.: 52.34%] [G loss: 0.697516]
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1668 [D loss: 0.693955, acc.: 50.00%] [G loss: 0.696839]
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1669 [D loss: 0.693999, acc.: 49.80%] [G loss: 0.696989]
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1670 [D loss: 0.695156, acc.: 46.29%] [G loss: 0.695648]
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1671 [D loss: 0.695390, acc.: 43.95%] [G loss: 0.693836]
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1672 [D loss: 0.695663, acc.: 42.97%] [G loss: 0.694532]
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1673 [D loss: 0.696700, acc.: 41.02%] [G loss: 0.693426]
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1674 [D loss: 0.695815, acc.: 43.75%] [G loss: 0.693257]
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1675 [D loss: 0.694021, acc.: 50.59%] [G loss: 0.692320]
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1676 [D loss: 0.694771, acc.: 47.07%] [G loss: 0.692983]
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1677 [D loss: 0.694011, acc.: 46.68%] [G loss: 0.693307]
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1678 [D loss: 0.693714, acc.: 45.51%] [G loss: 0.694743]
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1679 [D loss: 0.693556, acc.: 50.78%] [G loss: 0.694105]
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1680 [D loss: 0.692099, acc.: 53.12%] [G loss: 0.695450]
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1681 [D loss: 0.693608, acc.: 50.00%] [G loss: 0.696366]
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1682 [D loss: 0.693251, acc.: 48.83%] [G loss: 0.694580]
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1683 [D loss: 0.694903, acc.: 44.53%] [G loss: 0.694857]
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1684 [D loss: 0.692711, acc.: 50.00%] [G loss: 0.692398]
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1685 [D loss: 0.692676, acc.: 51.56%] [G loss: 0.691310]
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1686 [D loss: 0.693923, acc.: 49.22%] [G loss: 0.692881]
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1687 [D loss: 0.695577, acc.: 43.36%] [G loss: 0.691863]
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1688 [D loss: 0.696266, acc.: 44.73%] [G loss: 0.691889]
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1689 [D loss: 0.694441, acc.: 43.36%] [G loss: 0.693280]
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1690 [D loss: 0.694933, acc.: 44.92%] [G loss: 0.693127]
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1691 [D loss: 0.694774, acc.: 42.77%] [G loss: 0.691681]
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1692 [D loss: 0.694632, acc.: 45.12%] [G loss: 0.692690]
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1693 [D loss: 0.692943, acc.: 49.02%] [G loss: 0.695881]
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1694 [D loss: 0.692877, acc.: 50.98%] [G loss: 0.697292]
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1695 [D loss: 0.691714, acc.: 52.93%] [G loss: 0.697668]
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1696 [D loss: 0.691265, acc.: 52.54%] [G loss: 0.697974]
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1697 [D loss: 0.690886, acc.: 56.64%] [G loss: 0.699103]
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1698 [D loss: 0.689903, acc.: 59.77%] [G loss: 0.699759]
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1699 [D loss: 0.688947, acc.: 57.42%] [G loss: 0.700893]
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1700 [D loss: 0.688313, acc.: 57.62%] [G loss: 0.706081]
1/1 [==============================] - 0s 17ms/step
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1701 [D loss: 0.686781, acc.: 64.06%] [G loss: 0.704489]
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1702 [D loss: 0.687344, acc.: 58.79%] [G loss: 0.706138]
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1703 [D loss: 0.690087, acc.: 53.91%] [G loss: 0.704490]
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1704 [D loss: 0.685867, acc.: 60.74%] [G loss: 0.702512]
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1705 [D loss: 0.688334, acc.: 56.25%] [G loss: 0.700700]
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1706 [D loss: 0.695413, acc.: 46.09%] [G loss: 0.700146]
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1707 [D loss: 0.693060, acc.: 48.63%] [G loss: 0.698584]
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1708 [D loss: 0.695263, acc.: 46.88%] [G loss: 0.696363]
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1709 [D loss: 0.693761, acc.: 50.20%] [G loss: 0.694012]
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1710 [D loss: 0.698344, acc.: 41.60%] [G loss: 0.694067]
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1711 [D loss: 0.696841, acc.: 46.48%] [G loss: 0.693306]
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1712 [D loss: 0.699343, acc.: 41.60%] [G loss: 0.689992]
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1713 [D loss: 0.697021, acc.: 44.53%] [G loss: 0.689331]
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1714 [D loss: 0.701307, acc.: 35.74%] [G loss: 0.689204]
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1715 [D loss: 0.698687, acc.: 38.67%] [G loss: 0.690716]
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1716 [D loss: 0.698131, acc.: 39.45%] [G loss: 0.690282]
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1717 [D loss: 0.697415, acc.: 42.38%] [G loss: 0.691393]
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1718 [D loss: 0.697250, acc.: 41.41%] [G loss: 0.693460]
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1719 [D loss: 0.696372, acc.: 42.77%] [G loss: 0.693979]
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1720 [D loss: 0.694782, acc.: 44.92%] [G loss: 0.694790]
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1721 [D loss: 0.694227, acc.: 43.55%] [G loss: 0.697995]
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1722 [D loss: 0.693964, acc.: 48.44%] [G loss: 0.698217]
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1723 [D loss: 0.691829, acc.: 54.49%] [G loss: 0.701135]
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1724 [D loss: 0.691003, acc.: 55.86%] [G loss: 0.701137]
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1725 [D loss: 0.690290, acc.: 54.49%] [G loss: 0.704159]
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1726 [D loss: 0.690189, acc.: 53.52%] [G loss: 0.703287]
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1727 [D loss: 0.688775, acc.: 61.91%] [G loss: 0.703014]
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1728 [D loss: 0.688885, acc.: 60.16%] [G loss: 0.703900]
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1729 [D loss: 0.689551, acc.: 57.03%] [G loss: 0.703076]
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1730 [D loss: 0.688986, acc.: 60.94%] [G loss: 0.704711]
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1731 [D loss: 0.688714, acc.: 58.20%] [G loss: 0.703135]
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1732 [D loss: 0.689820, acc.: 55.66%] [G loss: 0.701200]
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1733 [D loss: 0.690574, acc.: 52.93%] [G loss: 0.698411]
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1734 [D loss: 0.691995, acc.: 54.10%] [G loss: 0.698020]
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1735 [D loss: 0.690399, acc.: 52.73%] [G loss: 0.694034]
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1736 [D loss: 0.692218, acc.: 55.27%] [G loss: 0.694388]
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1737 [D loss: 0.692115, acc.: 53.12%] [G loss: 0.693358]
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1738 [D loss: 0.692329, acc.: 49.80%] [G loss: 0.690027]
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1739 [D loss: 0.692484, acc.: 50.78%] [G loss: 0.688800]
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1740 [D loss: 0.693913, acc.: 48.44%] [G loss: 0.687490]
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1741 [D loss: 0.692679, acc.: 52.34%] [G loss: 0.684384]
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1742 [D loss: 0.694637, acc.: 49.22%] [G loss: 0.684349]
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1743 [D loss: 0.695868, acc.: 44.92%] [G loss: 0.685625]
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1744 [D loss: 0.695208, acc.: 46.09%] [G loss: 0.684337]
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1745 [D loss: 0.694704, acc.: 46.88%] [G loss: 0.685613]
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1746 [D loss: 0.695347, acc.: 46.09%] [G loss: 0.686394]
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1747 [D loss: 0.695967, acc.: 43.55%] [G loss: 0.688390]
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1748 [D loss: 0.696419, acc.: 45.12%] [G loss: 0.687350]
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1749 [D loss: 0.697824, acc.: 41.02%] [G loss: 0.687010]
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1750 [D loss: 0.695987, acc.: 44.34%] [G loss: 0.689704]
1/1 [==============================] - 0s 16ms/step
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1751 [D loss: 0.695661, acc.: 47.07%] [G loss: 0.689956]
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1752 [D loss: 0.695875, acc.: 42.19%] [G loss: 0.687978]
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1753 [D loss: 0.696583, acc.: 44.34%] [G loss: 0.689800]
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1754 [D loss: 0.696353, acc.: 42.58%] [G loss: 0.690912]
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1755 [D loss: 0.695342, acc.: 43.55%] [G loss: 0.693012]
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1756 [D loss: 0.693807, acc.: 48.44%] [G loss: 0.694406]
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1757 [D loss: 0.693423, acc.: 48.63%] [G loss: 0.696114]
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1758 [D loss: 0.693095, acc.: 47.85%] [G loss: 0.695131]
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1759 [D loss: 0.693764, acc.: 47.27%] [G loss: 0.696454]
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1760 [D loss: 0.692382, acc.: 50.98%] [G loss: 0.697883]
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1761 [D loss: 0.691840, acc.: 53.52%] [G loss: 0.701834]
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1762 [D loss: 0.691048, acc.: 54.88%] [G loss: 0.702014]
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1763 [D loss: 0.688768, acc.: 59.18%] [G loss: 0.703677]
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1764 [D loss: 0.689783, acc.: 55.47%] [G loss: 0.703982]
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1765 [D loss: 0.690402, acc.: 54.30%] [G loss: 0.704958]
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1766 [D loss: 0.690173, acc.: 54.49%] [G loss: 0.707249]
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1767 [D loss: 0.688940, acc.: 57.62%] [G loss: 0.705936]
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1768 [D loss: 0.688497, acc.: 55.86%] [G loss: 0.705564]
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1769 [D loss: 0.691075, acc.: 53.52%] [G loss: 0.706756]
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1770 [D loss: 0.689796, acc.: 51.95%] [G loss: 0.700798]
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1771 [D loss: 0.692032, acc.: 51.76%] [G loss: 0.700095]
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1772 [D loss: 0.693538, acc.: 50.98%] [G loss: 0.700240]
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1773 [D loss: 0.693089, acc.: 50.78%] [G loss: 0.698542]
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1774 [D loss: 0.695332, acc.: 47.27%] [G loss: 0.697022]
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1775 [D loss: 0.697572, acc.: 44.14%] [G loss: 0.692919]
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1776 [D loss: 0.699500, acc.: 40.82%] [G loss: 0.693229]
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1777 [D loss: 0.698037, acc.: 41.21%] [G loss: 0.691621]
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1778 [D loss: 0.698437, acc.: 41.21%] [G loss: 0.696927]
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1779 [D loss: 0.697726, acc.: 41.80%] [G loss: 0.693464]
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1780 [D loss: 0.697388, acc.: 40.04%] [G loss: 0.695146]
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1781 [D loss: 0.695878, acc.: 43.36%] [G loss: 0.694061]
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1782 [D loss: 0.695690, acc.: 43.95%] [G loss: 0.693799]
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1783 [D loss: 0.695928, acc.: 45.51%] [G loss: 0.694069]
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1784 [D loss: 0.695587, acc.: 44.34%] [G loss: 0.695736]
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1785 [D loss: 0.694780, acc.: 45.31%] [G loss: 0.693261]
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1786 [D loss: 0.695147, acc.: 45.31%] [G loss: 0.694643]
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1787 [D loss: 0.694034, acc.: 49.02%] [G loss: 0.696323]
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1788 [D loss: 0.693294, acc.: 48.24%] [G loss: 0.694743]
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1789 [D loss: 0.693424, acc.: 48.24%] [G loss: 0.697703]
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1790 [D loss: 0.694105, acc.: 47.85%] [G loss: 0.697008]
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1791 [D loss: 0.692287, acc.: 46.68%] [G loss: 0.698176]
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1792 [D loss: 0.692403, acc.: 50.78%] [G loss: 0.697654]
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1793 [D loss: 0.691675, acc.: 51.17%] [G loss: 0.700567]
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1794 [D loss: 0.692297, acc.: 48.83%] [G loss: 0.701504]
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1795 [D loss: 0.691993, acc.: 49.80%] [G loss: 0.698571]
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1796 [D loss: 0.693056, acc.: 49.02%] [G loss: 0.699726]
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1797 [D loss: 0.692544, acc.: 50.98%] [G loss: 0.701993]
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1798 [D loss: 0.691001, acc.: 54.88%] [G loss: 0.700541]
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1799 [D loss: 0.691081, acc.: 54.88%] [G loss: 0.701423]
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1800 [D loss: 0.690702, acc.: 55.86%] [G loss: 0.701956]
1/1 [==============================] - 0s 16ms/step
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1801 [D loss: 0.691550, acc.: 54.10%] [G loss: 0.704749]
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1802 [D loss: 0.692368, acc.: 52.73%] [G loss: 0.704574]
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1803 [D loss: 0.690907, acc.: 55.27%] [G loss: 0.706829]
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1804 [D loss: 0.689267, acc.: 58.59%] [G loss: 0.703999]
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1805 [D loss: 0.690370, acc.: 57.42%] [G loss: 0.709438]
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1806 [D loss: 0.690491, acc.: 55.08%] [G loss: 0.704867]
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1807 [D loss: 0.690215, acc.: 56.25%] [G loss: 0.707549]
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1808 [D loss: 0.689075, acc.: 59.96%] [G loss: 0.707909]
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1809 [D loss: 0.692150, acc.: 54.10%] [G loss: 0.707242]
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1810 [D loss: 0.690574, acc.: 54.10%] [G loss: 0.705474]
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1811 [D loss: 0.690651, acc.: 54.69%] [G loss: 0.705702]
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1812 [D loss: 0.693682, acc.: 51.76%] [G loss: 0.707695]
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1813 [D loss: 0.691093, acc.: 53.52%] [G loss: 0.704913]
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1814 [D loss: 0.692623, acc.: 51.56%] [G loss: 0.700958]
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1815 [D loss: 0.696970, acc.: 45.12%] [G loss: 0.699326]
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1816 [D loss: 0.695710, acc.: 46.68%] [G loss: 0.700614]
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1817 [D loss: 0.695489, acc.: 47.66%] [G loss: 0.695730]
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1818 [D loss: 0.696087, acc.: 44.14%] [G loss: 0.695588]
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1819 [D loss: 0.698594, acc.: 38.87%] [G loss: 0.696864]
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1820 [D loss: 0.696660, acc.: 42.77%] [G loss: 0.695667]
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1821 [D loss: 0.697980, acc.: 41.21%] [G loss: 0.695494]
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1822 [D loss: 0.698573, acc.: 40.62%] [G loss: 0.695668]
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1823 [D loss: 0.694483, acc.: 47.85%] [G loss: 0.698140]
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1824 [D loss: 0.695280, acc.: 47.66%] [G loss: 0.695561]
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1825 [D loss: 0.695057, acc.: 45.90%] [G loss: 0.697891]
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1826 [D loss: 0.694404, acc.: 46.09%] [G loss: 0.700125]
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1827 [D loss: 0.694666, acc.: 45.12%] [G loss: 0.698605]
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1828 [D loss: 0.692181, acc.: 53.12%] [G loss: 0.699835]
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1829 [D loss: 0.693332, acc.: 50.59%] [G loss: 0.700572]
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1830 [D loss: 0.692246, acc.: 52.54%] [G loss: 0.702744]
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1831 [D loss: 0.691693, acc.: 54.10%] [G loss: 0.699527]
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1832 [D loss: 0.691381, acc.: 52.93%] [G loss: 0.701035]
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1833 [D loss: 0.690864, acc.: 58.20%] [G loss: 0.702339]
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1834 [D loss: 0.691347, acc.: 55.27%] [G loss: 0.702027]
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1835 [D loss: 0.691136, acc.: 56.45%] [G loss: 0.701020]
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1836 [D loss: 0.689845, acc.: 57.42%] [G loss: 0.703410]
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1837 [D loss: 0.689896, acc.: 57.62%] [G loss: 0.699947]
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1838 [D loss: 0.689718, acc.: 55.47%] [G loss: 0.702668]
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1839 [D loss: 0.690294, acc.: 55.08%] [G loss: 0.699972]
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1840 [D loss: 0.690284, acc.: 53.32%] [G loss: 0.700806]
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1841 [D loss: 0.690093, acc.: 53.71%] [G loss: 0.700641]
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1842 [D loss: 0.691234, acc.: 52.34%] [G loss: 0.696726]
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1843 [D loss: 0.692669, acc.: 49.22%] [G loss: 0.695101]
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1844 [D loss: 0.692981, acc.: 49.80%] [G loss: 0.696300]
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1845 [D loss: 0.693961, acc.: 50.78%] [G loss: 0.692864]
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1846 [D loss: 0.691547, acc.: 52.73%] [G loss: 0.692153]
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1847 [D loss: 0.696781, acc.: 42.77%] [G loss: 0.691580]
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1848 [D loss: 0.696439, acc.: 41.80%] [G loss: 0.689932]
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1849 [D loss: 0.696728, acc.: 43.36%] [G loss: 0.693652]
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1850 [D loss: 0.694237, acc.: 46.88%] [G loss: 0.687700]
1/1 [==============================] - 0s 17ms/step
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1851 [D loss: 0.694821, acc.: 46.88%] [G loss: 0.690494]
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1852 [D loss: 0.695051, acc.: 43.95%] [G loss: 0.687806]
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1853 [D loss: 0.695361, acc.: 46.68%] [G loss: 0.687236]
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1854 [D loss: 0.697097, acc.: 43.16%] [G loss: 0.688374]
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1855 [D loss: 0.696535, acc.: 42.77%] [G loss: 0.690722]
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1856 [D loss: 0.695414, acc.: 46.68%] [G loss: 0.688666]
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1857 [D loss: 0.696218, acc.: 44.53%] [G loss: 0.688675]
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1858 [D loss: 0.696040, acc.: 45.12%] [G loss: 0.691730]
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1859 [D loss: 0.695304, acc.: 46.68%] [G loss: 0.692479]
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1860 [D loss: 0.694801, acc.: 51.76%] [G loss: 0.695084]
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1861 [D loss: 0.693644, acc.: 49.22%] [G loss: 0.694535]
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1862 [D loss: 0.690712, acc.: 55.86%] [G loss: 0.694818]
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1863 [D loss: 0.692633, acc.: 51.76%] [G loss: 0.696698]
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1864 [D loss: 0.692017, acc.: 51.76%] [G loss: 0.698016]
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1865 [D loss: 0.691384, acc.: 55.47%] [G loss: 0.698893]
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1866 [D loss: 0.689999, acc.: 55.66%] [G loss: 0.701400]
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1867 [D loss: 0.689956, acc.: 55.47%] [G loss: 0.699677]
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1868 [D loss: 0.691523, acc.: 53.32%] [G loss: 0.696765]
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1869 [D loss: 0.691798, acc.: 50.78%] [G loss: 0.699905]
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1870 [D loss: 0.690803, acc.: 53.52%] [G loss: 0.700434]
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1871 [D loss: 0.691965, acc.: 50.59%] [G loss: 0.701228]
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1872 [D loss: 0.692012, acc.: 51.76%] [G loss: 0.700288]
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1873 [D loss: 0.691288, acc.: 53.91%] [G loss: 0.699414]
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1874 [D loss: 0.692083, acc.: 53.91%] [G loss: 0.698265]
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1875 [D loss: 0.693643, acc.: 49.41%] [G loss: 0.701001]
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1876 [D loss: 0.692406, acc.: 50.98%] [G loss: 0.699318]
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1877 [D loss: 0.692759, acc.: 52.54%] [G loss: 0.697205]
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1878 [D loss: 0.694607, acc.: 48.44%] [G loss: 0.694237]
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1879 [D loss: 0.694452, acc.: 47.85%] [G loss: 0.696316]
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1880 [D loss: 0.691731, acc.: 54.10%] [G loss: 0.694445]
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1881 [D loss: 0.695022, acc.: 46.29%] [G loss: 0.695044]
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1882 [D loss: 0.694741, acc.: 49.41%] [G loss: 0.695024]
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1883 [D loss: 0.695724, acc.: 45.70%] [G loss: 0.695215]
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1884 [D loss: 0.695008, acc.: 46.88%] [G loss: 0.693676]
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1885 [D loss: 0.695298, acc.: 47.27%] [G loss: 0.693276]
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1886 [D loss: 0.694931, acc.: 45.90%] [G loss: 0.694163]
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1887 [D loss: 0.694884, acc.: 46.68%] [G loss: 0.695995]
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1888 [D loss: 0.696632, acc.: 42.38%] [G loss: 0.693378]
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1889 [D loss: 0.697080, acc.: 42.19%] [G loss: 0.696370]
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1890 [D loss: 0.695170, acc.: 45.51%] [G loss: 0.698039]
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1891 [D loss: 0.694749, acc.: 46.29%] [G loss: 0.696796]
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1892 [D loss: 0.693739, acc.: 46.48%] [G loss: 0.698597]
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1893 [D loss: 0.694904, acc.: 44.73%] [G loss: 0.698342]
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1894 [D loss: 0.694112, acc.: 46.68%] [G loss: 0.698990]
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1895 [D loss: 0.692764, acc.: 49.61%] [G loss: 0.699995]
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1896 [D loss: 0.692519, acc.: 49.61%] [G loss: 0.699052]
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1897 [D loss: 0.692439, acc.: 53.12%] [G loss: 0.703048]
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1898 [D loss: 0.691523, acc.: 53.71%] [G loss: 0.702522]
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1899 [D loss: 0.690830, acc.: 57.81%] [G loss: 0.702581]
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1900 [D loss: 0.690596, acc.: 58.01%] [G loss: 0.703675]
1/1 [==============================] - 0s 17ms/step
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1901 [D loss: 0.691771, acc.: 51.56%] [G loss: 0.704448]
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1902 [D loss: 0.691435, acc.: 54.10%] [G loss: 0.706678]
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1903 [D loss: 0.688692, acc.: 60.16%] [G loss: 0.706513]
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1904 [D loss: 0.690843, acc.: 55.27%] [G loss: 0.706980]
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1905 [D loss: 0.690468, acc.: 53.91%] [G loss: 0.708766]
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1906 [D loss: 0.689780, acc.: 56.25%] [G loss: 0.707077]
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1907 [D loss: 0.688246, acc.: 56.84%] [G loss: 0.705162]
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1908 [D loss: 0.689247, acc.: 54.49%] [G loss: 0.701207]
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1909 [D loss: 0.689325, acc.: 55.47%] [G loss: 0.704555]
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1910 [D loss: 0.691191, acc.: 54.30%] [G loss: 0.701263]
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1911 [D loss: 0.694224, acc.: 45.70%] [G loss: 0.699147]
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1912 [D loss: 0.695914, acc.: 42.97%] [G loss: 0.698578]
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1913 [D loss: 0.693900, acc.: 47.07%] [G loss: 0.694684]
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1914 [D loss: 0.696499, acc.: 43.55%] [G loss: 0.694158]
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1915 [D loss: 0.695561, acc.: 47.27%] [G loss: 0.695225]
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1916 [D loss: 0.695398, acc.: 43.55%] [G loss: 0.693163]
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1917 [D loss: 0.694501, acc.: 47.07%] [G loss: 0.692279]
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1918 [D loss: 0.696553, acc.: 43.55%] [G loss: 0.691216]
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1919 [D loss: 0.694776, acc.: 44.92%] [G loss: 0.691045]
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1920 [D loss: 0.693275, acc.: 49.41%] [G loss: 0.692568]
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1921 [D loss: 0.692506, acc.: 50.20%] [G loss: 0.691426]
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1922 [D loss: 0.694372, acc.: 45.70%] [G loss: 0.690635]
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1923 [D loss: 0.692751, acc.: 50.59%] [G loss: 0.687572]
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1924 [D loss: 0.694729, acc.: 50.39%] [G loss: 0.687894]
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1925 [D loss: 0.693220, acc.: 50.00%] [G loss: 0.687554]
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1926 [D loss: 0.693530, acc.: 48.63%] [G loss: 0.691997]
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1927 [D loss: 0.695366, acc.: 46.88%] [G loss: 0.686871]
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1928 [D loss: 0.692418, acc.: 50.78%] [G loss: 0.687967]
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1929 [D loss: 0.692739, acc.: 51.95%] [G loss: 0.686453]
8/8 [==============================] - 0s 4ms/step
1930 [D loss: 0.694035, acc.: 49.80%] [G loss: 0.685650]
8/8 [==============================] - 0s 4ms/step
1931 [D loss: 0.693886, acc.: 52.34%] [G loss: 0.685465]
8/8 [==============================] - 0s 4ms/step
1932 [D loss: 0.695471, acc.: 48.05%] [G loss: 0.688178]
8/8 [==============================] - 0s 4ms/step
1933 [D loss: 0.694480, acc.: 48.24%] [G loss: 0.686847]
8/8 [==============================] - 0s 4ms/step
1934 [D loss: 0.693348, acc.: 50.78%] [G loss: 0.689644]
8/8 [==============================] - 0s 4ms/step
1935 [D loss: 0.692678, acc.: 50.59%] [G loss: 0.690038]
8/8 [==============================] - 0s 4ms/step
1936 [D loss: 0.694066, acc.: 51.95%] [G loss: 0.693054]
8/8 [==============================] - 0s 4ms/step
1937 [D loss: 0.693901, acc.: 46.88%] [G loss: 0.694213]
8/8 [==============================] - 0s 4ms/step
1938 [D loss: 0.692520, acc.: 52.93%] [G loss: 0.698233]
8/8 [==============================] - 0s 4ms/step
1939 [D loss: 0.690752, acc.: 55.86%] [G loss: 0.699182]
8/8 [==============================] - 0s 4ms/step
1940 [D loss: 0.691190, acc.: 57.23%] [G loss: 0.698733]
8/8 [==============================] - 0s 4ms/step
1941 [D loss: 0.691204, acc.: 54.69%] [G loss: 0.699938]
8/8 [==============================] - 0s 4ms/step
1942 [D loss: 0.692273, acc.: 50.78%] [G loss: 0.701382]
8/8 [==============================] - 0s 4ms/step
1943 [D loss: 0.689687, acc.: 58.01%] [G loss: 0.703522]
8/8 [==============================] - 0s 4ms/step
1944 [D loss: 0.689637, acc.: 57.42%] [G loss: 0.702281]
8/8 [==============================] - 0s 4ms/step
1945 [D loss: 0.689910, acc.: 55.66%] [G loss: 0.705064]
8/8 [==============================] - 0s 4ms/step
1946 [D loss: 0.690259, acc.: 55.66%] [G loss: 0.701098]
8/8 [==============================] - 0s 4ms/step
1947 [D loss: 0.692991, acc.: 49.22%] [G loss: 0.703686]
8/8 [==============================] - 0s 4ms/step
1948 [D loss: 0.692780, acc.: 52.34%] [G loss: 0.701509]
8/8 [==============================] - 0s 4ms/step
1949 [D loss: 0.692350, acc.: 51.17%] [G loss: 0.703723]
8/8 [==============================] - 0s 4ms/step
1950 [D loss: 0.693767, acc.: 50.98%] [G loss: 0.698784]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 4ms/step
1951 [D loss: 0.690692, acc.: 54.49%] [G loss: 0.701374]
8/8 [==============================] - 0s 4ms/step
1952 [D loss: 0.694337, acc.: 46.48%] [G loss: 0.694973]
8/8 [==============================] - 0s 4ms/step
1953 [D loss: 0.696610, acc.: 46.48%] [G loss: 0.699189]
8/8 [==============================] - 0s 4ms/step
1954 [D loss: 0.695773, acc.: 45.51%] [G loss: 0.695049]
8/8 [==============================] - 0s 4ms/step
1955 [D loss: 0.696244, acc.: 46.29%] [G loss: 0.692723]
8/8 [==============================] - 0s 4ms/step
1956 [D loss: 0.695677, acc.: 44.53%] [G loss: 0.695017]
8/8 [==============================] - 0s 4ms/step
1957 [D loss: 0.697558, acc.: 39.84%] [G loss: 0.695613]
8/8 [==============================] - 0s 4ms/step
1958 [D loss: 0.696308, acc.: 45.51%] [G loss: 0.694724]
8/8 [==============================] - 0s 4ms/step
1959 [D loss: 0.696852, acc.: 44.73%] [G loss: 0.695549]
8/8 [==============================] - 0s 4ms/step
1960 [D loss: 0.695661, acc.: 45.90%] [G loss: 0.695921]
8/8 [==============================] - 0s 4ms/step
1961 [D loss: 0.696232, acc.: 41.99%] [G loss: 0.698190]
8/8 [==============================] - 0s 4ms/step
1962 [D loss: 0.694636, acc.: 45.31%] [G loss: 0.696838]
8/8 [==============================] - 0s 4ms/step
1963 [D loss: 0.694368, acc.: 48.24%] [G loss: 0.698120]
8/8 [==============================] - 0s 4ms/step
1964 [D loss: 0.693863, acc.: 49.61%] [G loss: 0.698355]
8/8 [==============================] - 0s 4ms/step
1965 [D loss: 0.692604, acc.: 50.39%] [G loss: 0.702206]
8/8 [==============================] - 0s 4ms/step
1966 [D loss: 0.692498, acc.: 49.61%] [G loss: 0.702160]
8/8 [==============================] - 0s 4ms/step
1967 [D loss: 0.690740, acc.: 53.71%] [G loss: 0.702081]
8/8 [==============================] - 0s 4ms/step
1968 [D loss: 0.690827, acc.: 53.91%] [G loss: 0.706122]
8/8 [==============================] - 0s 4ms/step
1969 [D loss: 0.690988, acc.: 54.49%] [G loss: 0.705833]
8/8 [==============================] - 0s 4ms/step
1970 [D loss: 0.690089, acc.: 54.10%] [G loss: 0.703577]
8/8 [==============================] - 0s 4ms/step
1971 [D loss: 0.689794, acc.: 59.38%] [G loss: 0.704557]
8/8 [==============================] - 0s 4ms/step
1972 [D loss: 0.691565, acc.: 53.71%] [G loss: 0.708052]
8/8 [==============================] - 0s 4ms/step
1973 [D loss: 0.689823, acc.: 57.42%] [G loss: 0.706692]
8/8 [==============================] - 0s 4ms/step
1974 [D loss: 0.692061, acc.: 55.08%] [G loss: 0.706382]
8/8 [==============================] - 0s 4ms/step
1975 [D loss: 0.689667, acc.: 57.23%] [G loss: 0.705913]
8/8 [==============================] - 0s 4ms/step
1976 [D loss: 0.692568, acc.: 52.93%] [G loss: 0.706418]
8/8 [==============================] - 0s 4ms/step
1977 [D loss: 0.693676, acc.: 51.95%] [G loss: 0.705914]
8/8 [==============================] - 0s 4ms/step
1978 [D loss: 0.691453, acc.: 51.76%] [G loss: 0.699450]
8/8 [==============================] - 0s 4ms/step
1979 [D loss: 0.695790, acc.: 48.24%] [G loss: 0.701969]
8/8 [==============================] - 0s 4ms/step
1980 [D loss: 0.693169, acc.: 51.37%] [G loss: 0.701777]
8/8 [==============================] - 0s 4ms/step
1981 [D loss: 0.694035, acc.: 50.78%] [G loss: 0.697470]
8/8 [==============================] - 0s 4ms/step
1982 [D loss: 0.694493, acc.: 50.59%] [G loss: 0.698902]
8/8 [==============================] - 0s 4ms/step
1983 [D loss: 0.694220, acc.: 48.83%] [G loss: 0.697382]
8/8 [==============================] - 0s 4ms/step
1984 [D loss: 0.696614, acc.: 47.07%] [G loss: 0.696245]
8/8 [==============================] - 0s 4ms/step
1985 [D loss: 0.696323, acc.: 47.66%] [G loss: 0.693359]
8/8 [==============================] - 0s 4ms/step
1986 [D loss: 0.697997, acc.: 45.12%] [G loss: 0.696689]
8/8 [==============================] - 0s 4ms/step
1987 [D loss: 0.696570, acc.: 46.88%] [G loss: 0.695321]
8/8 [==============================] - 0s 4ms/step
1988 [D loss: 0.696964, acc.: 43.55%] [G loss: 0.695032]
8/8 [==============================] - 0s 4ms/step
1989 [D loss: 0.696369, acc.: 45.12%] [G loss: 0.696971]
8/8 [==============================] - 0s 4ms/step
1990 [D loss: 0.694220, acc.: 45.70%] [G loss: 0.698666]
8/8 [==============================] - 0s 4ms/step
1991 [D loss: 0.693908, acc.: 47.66%] [G loss: 0.699856]
8/8 [==============================] - 0s 4ms/step
1992 [D loss: 0.694157, acc.: 47.66%] [G loss: 0.701625]
8/8 [==============================] - 0s 4ms/step
1993 [D loss: 0.694321, acc.: 47.66%] [G loss: 0.702677]
8/8 [==============================] - 0s 4ms/step
1994 [D loss: 0.693179, acc.: 47.85%] [G loss: 0.699562]
8/8 [==============================] - 0s 4ms/step
1995 [D loss: 0.692768, acc.: 51.17%] [G loss: 0.701541]
8/8 [==============================] - 0s 4ms/step
1996 [D loss: 0.692849, acc.: 52.34%] [G loss: 0.699861]
8/8 [==============================] - 0s 4ms/step
1997 [D loss: 0.692598, acc.: 49.80%] [G loss: 0.701640]
8/8 [==============================] - 0s 4ms/step
1998 [D loss: 0.691739, acc.: 53.91%] [G loss: 0.701257]
8/8 [==============================] - 0s 4ms/step
1999 [D loss: 0.692236, acc.: 52.93%] [G loss: 0.700187]
8/8 [==============================] - 0s 4ms/step
2000 [D loss: 0.693103, acc.: 50.20%] [G loss: 0.699195]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 4ms/step
2001 [D loss: 0.690013, acc.: 56.45%] [G loss: 0.699032]
8/8 [==============================] - 0s 4ms/step
2002 [D loss: 0.691440, acc.: 55.27%] [G loss: 0.699348]
8/8 [==============================] - 0s 4ms/step
2003 [D loss: 0.692523, acc.: 51.76%] [G loss: 0.697329]
8/8 [==============================] - 0s 4ms/step
2004 [D loss: 0.691852, acc.: 54.30%] [G loss: 0.698453]
8/8 [==============================] - 0s 4ms/step
2005 [D loss: 0.691925, acc.: 52.54%] [G loss: 0.697180]
8/8 [==============================] - 0s 4ms/step
2006 [D loss: 0.691282, acc.: 55.47%] [G loss: 0.695242]
8/8 [==============================] - 0s 4ms/step
2007 [D loss: 0.691140, acc.: 53.52%] [G loss: 0.695758]
8/8 [==============================] - 0s 4ms/step
2008 [D loss: 0.690534, acc.: 55.47%] [G loss: 0.694069]
8/8 [==============================] - 0s 4ms/step
2009 [D loss: 0.691426, acc.: 52.93%] [G loss: 0.694578]
8/8 [==============================] - 0s 4ms/step
2010 [D loss: 0.690423, acc.: 55.08%] [G loss: 0.692792]
8/8 [==============================] - 0s 4ms/step
2011 [D loss: 0.691451, acc.: 52.15%] [G loss: 0.693331]
8/8 [==============================] - 0s 4ms/step
2012 [D loss: 0.692506, acc.: 49.02%] [G loss: 0.689063]
8/8 [==============================] - 0s 4ms/step
2013 [D loss: 0.692343, acc.: 53.91%] [G loss: 0.690215]
8/8 [==============================] - 0s 4ms/step
2014 [D loss: 0.692836, acc.: 50.20%] [G loss: 0.688458]
8/8 [==============================] - 0s 4ms/step
2015 [D loss: 0.693701, acc.: 48.83%] [G loss: 0.689381]
8/8 [==============================] - 0s 4ms/step
2016 [D loss: 0.694628, acc.: 45.90%] [G loss: 0.688050]
8/8 [==============================] - 0s 4ms/step
2017 [D loss: 0.695289, acc.: 45.31%] [G loss: 0.686319]
8/8 [==============================] - 0s 4ms/step
2018 [D loss: 0.695602, acc.: 44.73%] [G loss: 0.686830]
8/8 [==============================] - 0s 4ms/step
2019 [D loss: 0.695707, acc.: 43.95%] [G loss: 0.685466]
8/8 [==============================] - 0s 4ms/step
2020 [D loss: 0.695336, acc.: 48.63%] [G loss: 0.684446]
8/8 [==============================] - 0s 4ms/step
2021 [D loss: 0.696717, acc.: 40.62%] [G loss: 0.686913]
8/8 [==============================] - 0s 4ms/step
2022 [D loss: 0.696373, acc.: 46.29%] [G loss: 0.688084]
8/8 [==============================] - 0s 4ms/step
2023 [D loss: 0.696022, acc.: 42.38%] [G loss: 0.687429]
8/8 [==============================] - 0s 4ms/step
2024 [D loss: 0.695817, acc.: 44.53%] [G loss: 0.688023]
8/8 [==============================] - 0s 4ms/step
2025 [D loss: 0.694557, acc.: 46.29%] [G loss: 0.690880]
8/8 [==============================] - 0s 4ms/step
2026 [D loss: 0.696073, acc.: 43.95%] [G loss: 0.694221]
8/8 [==============================] - 0s 4ms/step
2027 [D loss: 0.694146, acc.: 47.85%] [G loss: 0.692216]
8/8 [==============================] - 0s 4ms/step
2028 [D loss: 0.694488, acc.: 46.48%] [G loss: 0.691871]
8/8 [==============================] - 0s 4ms/step
2029 [D loss: 0.694157, acc.: 49.22%] [G loss: 0.695719]
8/8 [==============================] - 0s 4ms/step
2030 [D loss: 0.692194, acc.: 52.15%] [G loss: 0.698175]
8/8 [==============================] - 0s 4ms/step
2031 [D loss: 0.692975, acc.: 49.61%] [G loss: 0.698928]
8/8 [==============================] - 0s 4ms/step
2032 [D loss: 0.691337, acc.: 55.47%] [G loss: 0.699506]
8/8 [==============================] - 0s 4ms/step
2033 [D loss: 0.691537, acc.: 52.73%] [G loss: 0.700433]
8/8 [==============================] - 0s 4ms/step
2034 [D loss: 0.690458, acc.: 56.64%] [G loss: 0.703000]
8/8 [==============================] - 0s 4ms/step
2035 [D loss: 0.692280, acc.: 51.17%] [G loss: 0.702849]
8/8 [==============================] - 0s 4ms/step
2036 [D loss: 0.691449, acc.: 54.69%] [G loss: 0.704294]
8/8 [==============================] - 0s 4ms/step
2037 [D loss: 0.691236, acc.: 54.30%] [G loss: 0.703325]
8/8 [==============================] - 0s 4ms/step
2038 [D loss: 0.692887, acc.: 53.91%] [G loss: 0.703370]
8/8 [==============================] - 0s 4ms/step
2039 [D loss: 0.691787, acc.: 53.52%] [G loss: 0.703954]
8/8 [==============================] - 0s 4ms/step
2040 [D loss: 0.693067, acc.: 51.56%] [G loss: 0.704451]
8/8 [==============================] - 0s 4ms/step
2041 [D loss: 0.691321, acc.: 52.73%] [G loss: 0.704494]
8/8 [==============================] - 0s 4ms/step
2042 [D loss: 0.692773, acc.: 53.12%] [G loss: 0.704609]
8/8 [==============================] - 0s 4ms/step
2043 [D loss: 0.691585, acc.: 54.30%] [G loss: 0.703885]
8/8 [==============================] - 0s 4ms/step
2044 [D loss: 0.692739, acc.: 51.95%] [G loss: 0.706407]
8/8 [==============================] - 0s 4ms/step
2045 [D loss: 0.693452, acc.: 49.22%] [G loss: 0.703608]
8/8 [==============================] - 0s 4ms/step
2046 [D loss: 0.691615, acc.: 53.52%] [G loss: 0.701504]
8/8 [==============================] - 0s 4ms/step
2047 [D loss: 0.693441, acc.: 48.44%] [G loss: 0.702281]
8/8 [==============================] - 0s 4ms/step
2048 [D loss: 0.693318, acc.: 49.80%] [G loss: 0.703173]
8/8 [==============================] - 0s 4ms/step
2049 [D loss: 0.696108, acc.: 46.29%] [G loss: 0.701405]
8/8 [==============================] - 0s 4ms/step
2050 [D loss: 0.695365, acc.: 46.88%] [G loss: 0.700835]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 4ms/step
2051 [D loss: 0.693616, acc.: 49.61%] [G loss: 0.702422]
8/8 [==============================] - 0s 4ms/step
2052 [D loss: 0.693469, acc.: 50.20%] [G loss: 0.699665]
8/8 [==============================] - 0s 4ms/step
2053 [D loss: 0.695704, acc.: 44.14%] [G loss: 0.698835]
8/8 [==============================] - 0s 4ms/step
2054 [D loss: 0.694253, acc.: 47.85%] [G loss: 0.701084]
8/8 [==============================] - 0s 4ms/step
2055 [D loss: 0.693886, acc.: 47.46%] [G loss: 0.699570]
8/8 [==============================] - 0s 4ms/step
2056 [D loss: 0.693900, acc.: 50.20%] [G loss: 0.700705]
8/8 [==============================] - 0s 4ms/step
2057 [D loss: 0.693978, acc.: 49.02%] [G loss: 0.700971]
8/8 [==============================] - 0s 4ms/step
2058 [D loss: 0.691941, acc.: 51.56%] [G loss: 0.697799]
8/8 [==============================] - 0s 4ms/step
2059 [D loss: 0.696389, acc.: 42.58%] [G loss: 0.698063]
8/8 [==============================] - 0s 4ms/step
2060 [D loss: 0.695891, acc.: 44.34%] [G loss: 0.698497]
8/8 [==============================] - 0s 4ms/step
2061 [D loss: 0.693471, acc.: 49.41%] [G loss: 0.698596]
8/8 [==============================] - 0s 4ms/step
2062 [D loss: 0.693278, acc.: 48.63%] [G loss: 0.698271]
8/8 [==============================] - 0s 4ms/step
2063 [D loss: 0.692619, acc.: 48.24%] [G loss: 0.700227]
8/8 [==============================] - 0s 4ms/step
2064 [D loss: 0.692736, acc.: 50.20%] [G loss: 0.699264]
8/8 [==============================] - 0s 4ms/step
2065 [D loss: 0.692962, acc.: 48.24%] [G loss: 0.699050]
8/8 [==============================] - 0s 4ms/step
2066 [D loss: 0.692465, acc.: 54.10%] [G loss: 0.698628]
8/8 [==============================] - 0s 4ms/step
2067 [D loss: 0.691993, acc.: 53.12%] [G loss: 0.698345]
8/8 [==============================] - 0s 4ms/step
2068 [D loss: 0.692237, acc.: 50.39%] [G loss: 0.700467]
8/8 [==============================] - 0s 4ms/step
2069 [D loss: 0.691318, acc.: 52.73%] [G loss: 0.700018]
8/8 [==============================] - 0s 4ms/step
2070 [D loss: 0.690683, acc.: 54.10%] [G loss: 0.699562]
8/8 [==============================] - 0s 4ms/step
2071 [D loss: 0.689183, acc.: 61.13%] [G loss: 0.702565]
8/8 [==============================] - 0s 4ms/step
2072 [D loss: 0.691524, acc.: 50.98%] [G loss: 0.699780]
8/8 [==============================] - 0s 4ms/step
2073 [D loss: 0.690600, acc.: 55.86%] [G loss: 0.699632]
8/8 [==============================] - 0s 4ms/step
2074 [D loss: 0.690546, acc.: 53.12%] [G loss: 0.702148]
8/8 [==============================] - 0s 4ms/step
2075 [D loss: 0.690218, acc.: 54.30%] [G loss: 0.698390]
8/8 [==============================] - 0s 4ms/step
2076 [D loss: 0.690857, acc.: 56.45%] [G loss: 0.697330]
8/8 [==============================] - 0s 4ms/step
2077 [D loss: 0.692143, acc.: 52.93%] [G loss: 0.696724]
8/8 [==============================] - 0s 4ms/step
2078 [D loss: 0.692458, acc.: 52.73%] [G loss: 0.694519]
8/8 [==============================] - 0s 4ms/step
2079 [D loss: 0.692734, acc.: 51.56%] [G loss: 0.692472]
8/8 [==============================] - 0s 4ms/step
2080 [D loss: 0.692644, acc.: 52.15%] [G loss: 0.690122]
8/8 [==============================] - 0s 4ms/step
2081 [D loss: 0.695415, acc.: 45.31%] [G loss: 0.689723]
8/8 [==============================] - 0s 4ms/step
2082 [D loss: 0.693092, acc.: 48.63%] [G loss: 0.688268]
8/8 [==============================] - 0s 4ms/step
2083 [D loss: 0.697243, acc.: 43.75%] [G loss: 0.685303]
8/8 [==============================] - 0s 4ms/step
2084 [D loss: 0.695249, acc.: 45.31%] [G loss: 0.687878]
8/8 [==============================] - 0s 4ms/step
2085 [D loss: 0.697083, acc.: 42.58%] [G loss: 0.686185]
8/8 [==============================] - 0s 4ms/step
2086 [D loss: 0.695649, acc.: 42.38%] [G loss: 0.685165]
8/8 [==============================] - 0s 4ms/step
2087 [D loss: 0.695485, acc.: 44.14%] [G loss: 0.687471]
8/8 [==============================] - 0s 4ms/step
2088 [D loss: 0.695353, acc.: 42.97%] [G loss: 0.688118]
8/8 [==============================] - 0s 4ms/step
2089 [D loss: 0.696337, acc.: 41.99%] [G loss: 0.686945]
8/8 [==============================] - 0s 4ms/step
2090 [D loss: 0.695565, acc.: 43.16%] [G loss: 0.688551]
8/8 [==============================] - 0s 4ms/step
2091 [D loss: 0.695900, acc.: 43.75%] [G loss: 0.687899]
8/8 [==============================] - 0s 4ms/step
2092 [D loss: 0.694027, acc.: 47.85%] [G loss: 0.690675]
8/8 [==============================] - 0s 4ms/step
2093 [D loss: 0.693965, acc.: 48.44%] [G loss: 0.692087]
8/8 [==============================] - 0s 4ms/step
2094 [D loss: 0.693107, acc.: 50.20%] [G loss: 0.691596]
8/8 [==============================] - 0s 4ms/step
2095 [D loss: 0.693508, acc.: 48.05%] [G loss: 0.691970]
8/8 [==============================] - 0s 4ms/step
2096 [D loss: 0.693018, acc.: 47.07%] [G loss: 0.692719]
8/8 [==============================] - 0s 4ms/step
2097 [D loss: 0.693698, acc.: 47.85%] [G loss: 0.693349]
8/8 [==============================] - 0s 4ms/step
2098 [D loss: 0.692822, acc.: 51.37%] [G loss: 0.694975]
8/8 [==============================] - 0s 4ms/step
2099 [D loss: 0.694217, acc.: 46.68%] [G loss: 0.695682]
8/8 [==============================] - 0s 4ms/step
2100 [D loss: 0.693865, acc.: 49.41%] [G loss: 0.695567]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 4ms/step
2101 [D loss: 0.692979, acc.: 52.54%] [G loss: 0.697874]
8/8 [==============================] - 0s 4ms/step
2102 [D loss: 0.691310, acc.: 55.47%] [G loss: 0.699615]
8/8 [==============================] - 0s 4ms/step
2103 [D loss: 0.691971, acc.: 51.76%] [G loss: 0.699357]
8/8 [==============================] - 0s 4ms/step
2104 [D loss: 0.692529, acc.: 49.80%] [G loss: 0.699466]
8/8 [==============================] - 0s 4ms/step
2105 [D loss: 0.691068, acc.: 54.49%] [G loss: 0.700926]
8/8 [==============================] - 0s 4ms/step
2106 [D loss: 0.692550, acc.: 52.93%] [G loss: 0.701763]
8/8 [==============================] - 0s 4ms/step
2107 [D loss: 0.693027, acc.: 50.98%] [G loss: 0.702322]
8/8 [==============================] - 0s 4ms/step
2108 [D loss: 0.692967, acc.: 47.27%] [G loss: 0.702874]
8/8 [==============================] - 0s 4ms/step
2109 [D loss: 0.690422, acc.: 56.84%] [G loss: 0.702604]
8/8 [==============================] - 0s 4ms/step
2110 [D loss: 0.692618, acc.: 50.39%] [G loss: 0.704144]
8/8 [==============================] - 0s 4ms/step
2111 [D loss: 0.692925, acc.: 49.22%] [G loss: 0.702256]
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2112 [D loss: 0.690828, acc.: 54.30%] [G loss: 0.703845]
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2113 [D loss: 0.693235, acc.: 50.78%] [G loss: 0.702814]
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2114 [D loss: 0.692436, acc.: 50.59%] [G loss: 0.704219]
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2115 [D loss: 0.693270, acc.: 50.78%] [G loss: 0.702321]
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2116 [D loss: 0.693453, acc.: 49.02%] [G loss: 0.704822]
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2117 [D loss: 0.692482, acc.: 51.95%] [G loss: 0.703082]
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2118 [D loss: 0.693004, acc.: 52.34%] [G loss: 0.704614]
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2119 [D loss: 0.692572, acc.: 49.80%] [G loss: 0.706818]
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2120 [D loss: 0.692493, acc.: 50.59%] [G loss: 0.704457]
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2121 [D loss: 0.694371, acc.: 48.05%] [G loss: 0.703701]
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2122 [D loss: 0.694131, acc.: 47.07%] [G loss: 0.701860]
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2123 [D loss: 0.693945, acc.: 51.17%] [G loss: 0.702367]
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2124 [D loss: 0.694150, acc.: 46.48%] [G loss: 0.702365]
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2125 [D loss: 0.695264, acc.: 47.27%] [G loss: 0.701455]
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2126 [D loss: 0.693865, acc.: 49.41%] [G loss: 0.702745]
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2127 [D loss: 0.693066, acc.: 49.41%] [G loss: 0.704292]
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2128 [D loss: 0.694234, acc.: 47.27%] [G loss: 0.702176]
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2129 [D loss: 0.694330, acc.: 48.24%] [G loss: 0.701203]
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2130 [D loss: 0.691188, acc.: 53.32%] [G loss: 0.699191]
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2131 [D loss: 0.692860, acc.: 50.98%] [G loss: 0.701712]
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2132 [D loss: 0.694151, acc.: 47.85%] [G loss: 0.701035]
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2133 [D loss: 0.693254, acc.: 50.98%] [G loss: 0.702058]
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2134 [D loss: 0.692157, acc.: 53.12%] [G loss: 0.702663]
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2135 [D loss: 0.693055, acc.: 52.15%] [G loss: 0.702253]
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2136 [D loss: 0.692294, acc.: 50.00%] [G loss: 0.700818]
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2137 [D loss: 0.691905, acc.: 55.66%] [G loss: 0.699026]
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2138 [D loss: 0.694123, acc.: 50.20%] [G loss: 0.699266]
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2139 [D loss: 0.694233, acc.: 50.20%] [G loss: 0.697177]
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2140 [D loss: 0.692971, acc.: 51.37%] [G loss: 0.696850]
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2141 [D loss: 0.696240, acc.: 41.80%] [G loss: 0.694895]
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2142 [D loss: 0.693496, acc.: 48.44%] [G loss: 0.697269]
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2143 [D loss: 0.693110, acc.: 49.61%] [G loss: 0.696423]
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2144 [D loss: 0.694571, acc.: 47.85%] [G loss: 0.694071]
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2145 [D loss: 0.693540, acc.: 49.22%] [G loss: 0.695134]
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2146 [D loss: 0.694088, acc.: 47.07%] [G loss: 0.694998]
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2147 [D loss: 0.692749, acc.: 50.98%] [G loss: 0.694289]
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2148 [D loss: 0.693657, acc.: 49.41%] [G loss: 0.692697]
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2149 [D loss: 0.692114, acc.: 51.95%] [G loss: 0.693290]
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2150 [D loss: 0.692679, acc.: 52.34%] [G loss: 0.692342]
1/1 [==============================] - 0s 16ms/step
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2151 [D loss: 0.691468, acc.: 49.80%] [G loss: 0.692168]
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2152 [D loss: 0.692389, acc.: 49.41%] [G loss: 0.693022]
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2153 [D loss: 0.691568, acc.: 55.66%] [G loss: 0.693179]
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2154 [D loss: 0.691235, acc.: 54.10%] [G loss: 0.693247]
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2155 [D loss: 0.691792, acc.: 53.52%] [G loss: 0.692867]
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2156 [D loss: 0.691465, acc.: 55.47%] [G loss: 0.691712]
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2157 [D loss: 0.691327, acc.: 52.93%] [G loss: 0.692855]
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2158 [D loss: 0.690837, acc.: 54.49%] [G loss: 0.695605]
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2159 [D loss: 0.691758, acc.: 53.71%] [G loss: 0.692023]
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2160 [D loss: 0.693050, acc.: 50.39%] [G loss: 0.692255]
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2161 [D loss: 0.692394, acc.: 51.56%] [G loss: 0.692639]
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2162 [D loss: 0.694230, acc.: 48.05%] [G loss: 0.693287]
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2163 [D loss: 0.692160, acc.: 53.12%] [G loss: 0.692889]
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2164 [D loss: 0.692936, acc.: 50.00%] [G loss: 0.695415]
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2165 [D loss: 0.693063, acc.: 48.44%] [G loss: 0.693757]
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2166 [D loss: 0.693255, acc.: 49.41%] [G loss: 0.691410]
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2167 [D loss: 0.693342, acc.: 49.80%] [G loss: 0.692758]
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2168 [D loss: 0.695305, acc.: 45.31%] [G loss: 0.695022]
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2169 [D loss: 0.693568, acc.: 47.27%] [G loss: 0.693716]
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2170 [D loss: 0.693819, acc.: 46.88%] [G loss: 0.692700]
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2171 [D loss: 0.695822, acc.: 46.88%] [G loss: 0.695271]
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2172 [D loss: 0.693393, acc.: 50.59%] [G loss: 0.693313]
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2173 [D loss: 0.694023, acc.: 49.80%] [G loss: 0.692484]
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2174 [D loss: 0.695268, acc.: 44.92%] [G loss: 0.693258]
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2175 [D loss: 0.695739, acc.: 47.46%] [G loss: 0.695865]
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2176 [D loss: 0.695432, acc.: 44.34%] [G loss: 0.695593]
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2177 [D loss: 0.694484, acc.: 47.27%] [G loss: 0.695238]
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2178 [D loss: 0.695113, acc.: 45.31%] [G loss: 0.698646]
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2179 [D loss: 0.694309, acc.: 47.27%] [G loss: 0.699080]
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2180 [D loss: 0.692804, acc.: 49.61%] [G loss: 0.698526]
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2181 [D loss: 0.692604, acc.: 50.39%] [G loss: 0.699464]
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2182 [D loss: 0.692430, acc.: 52.73%] [G loss: 0.700277]
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2183 [D loss: 0.692654, acc.: 51.76%] [G loss: 0.701565]
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2184 [D loss: 0.694087, acc.: 49.61%] [G loss: 0.701778]
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2185 [D loss: 0.693476, acc.: 49.80%] [G loss: 0.701426]
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2186 [D loss: 0.693766, acc.: 48.44%] [G loss: 0.700628]
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2187 [D loss: 0.692784, acc.: 49.80%] [G loss: 0.700309]
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2188 [D loss: 0.693859, acc.: 48.44%] [G loss: 0.697875]
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2189 [D loss: 0.694303, acc.: 45.31%] [G loss: 0.699168]
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2190 [D loss: 0.693256, acc.: 48.05%] [G loss: 0.698708]
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2191 [D loss: 0.692902, acc.: 47.66%] [G loss: 0.699352]
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2192 [D loss: 0.691587, acc.: 53.71%] [G loss: 0.699815]
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2193 [D loss: 0.694143, acc.: 46.48%] [G loss: 0.699022]
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2194 [D loss: 0.691630, acc.: 54.30%] [G loss: 0.699345]
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2195 [D loss: 0.691455, acc.: 56.45%] [G loss: 0.697738]
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2196 [D loss: 0.690771, acc.: 54.69%] [G loss: 0.698213]
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2197 [D loss: 0.692543, acc.: 52.34%] [G loss: 0.697352]
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2198 [D loss: 0.692314, acc.: 52.54%] [G loss: 0.697771]
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2199 [D loss: 0.694338, acc.: 45.90%] [G loss: 0.697382]
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2200 [D loss: 0.692321, acc.: 53.32%] [G loss: 0.696016]
1/1 [==============================] - 0s 16ms/step
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2201 [D loss: 0.691917, acc.: 52.15%] [G loss: 0.692099]
8/8 [==============================] - 0s 4ms/step
2202 [D loss: 0.693655, acc.: 48.63%] [G loss: 0.695306]
8/8 [==============================] - 0s 4ms/step
2203 [D loss: 0.694384, acc.: 45.51%] [G loss: 0.693151]
8/8 [==============================] - 0s 4ms/step
2204 [D loss: 0.693478, acc.: 46.09%] [G loss: 0.697004]
8/8 [==============================] - 0s 4ms/step
2205 [D loss: 0.692838, acc.: 49.80%] [G loss: 0.697720]
8/8 [==============================] - 0s 4ms/step
2206 [D loss: 0.691808, acc.: 52.34%] [G loss: 0.697580]
8/8 [==============================] - 0s 4ms/step
2207 [D loss: 0.692669, acc.: 51.17%] [G loss: 0.696640]
8/8 [==============================] - 0s 4ms/step
2208 [D loss: 0.691932, acc.: 48.83%] [G loss: 0.696655]
8/8 [==============================] - 0s 4ms/step
2209 [D loss: 0.692612, acc.: 50.98%] [G loss: 0.698899]
8/8 [==============================] - 0s 4ms/step
2210 [D loss: 0.693388, acc.: 50.20%] [G loss: 0.697045]
8/8 [==============================] - 0s 4ms/step
2211 [D loss: 0.692221, acc.: 54.49%] [G loss: 0.698156]
8/8 [==============================] - 0s 4ms/step
2212 [D loss: 0.693201, acc.: 48.05%] [G loss: 0.695773]
8/8 [==============================] - 0s 4ms/step
2213 [D loss: 0.693570, acc.: 52.15%] [G loss: 0.697469]
8/8 [==============================] - 0s 4ms/step
2214 [D loss: 0.694171, acc.: 46.09%] [G loss: 0.695212]
8/8 [==============================] - 0s 4ms/step
2215 [D loss: 0.691650, acc.: 53.12%] [G loss: 0.697399]
8/8 [==============================] - 0s 4ms/step
2216 [D loss: 0.693850, acc.: 48.24%] [G loss: 0.695413]
8/8 [==============================] - 0s 4ms/step
2217 [D loss: 0.695545, acc.: 48.63%] [G loss: 0.693019]
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2218 [D loss: 0.694238, acc.: 49.41%] [G loss: 0.692447]
8/8 [==============================] - 0s 4ms/step
2219 [D loss: 0.696414, acc.: 45.12%] [G loss: 0.692718]
8/8 [==============================] - 0s 4ms/step
2220 [D loss: 0.695969, acc.: 45.31%] [G loss: 0.692068]
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2221 [D loss: 0.696187, acc.: 44.34%] [G loss: 0.689556]
8/8 [==============================] - 0s 4ms/step
2222 [D loss: 0.697526, acc.: 42.77%] [G loss: 0.690341]
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2223 [D loss: 0.695395, acc.: 45.70%] [G loss: 0.690862]
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2224 [D loss: 0.695867, acc.: 40.82%] [G loss: 0.691730]
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2225 [D loss: 0.694400, acc.: 48.05%] [G loss: 0.691853]
8/8 [==============================] - 0s 4ms/step
2226 [D loss: 0.694409, acc.: 43.36%] [G loss: 0.693875]
8/8 [==============================] - 0s 4ms/step
2227 [D loss: 0.694217, acc.: 48.24%] [G loss: 0.695949]
8/8 [==============================] - 0s 4ms/step
2228 [D loss: 0.693015, acc.: 49.61%] [G loss: 0.697938]
8/8 [==============================] - 0s 4ms/step
2229 [D loss: 0.692390, acc.: 51.56%] [G loss: 0.698320]
8/8 [==============================] - 0s 4ms/step
2230 [D loss: 0.691369, acc.: 53.52%] [G loss: 0.700725]
8/8 [==============================] - 0s 4ms/step
2231 [D loss: 0.691068, acc.: 57.62%] [G loss: 0.700227]
8/8 [==============================] - 0s 4ms/step
2232 [D loss: 0.690430, acc.: 56.64%] [G loss: 0.703397]
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2233 [D loss: 0.691603, acc.: 54.30%] [G loss: 0.707564]
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2234 [D loss: 0.689033, acc.: 59.38%] [G loss: 0.705131]
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2235 [D loss: 0.691042, acc.: 53.32%] [G loss: 0.707037]
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2236 [D loss: 0.691368, acc.: 54.88%] [G loss: 0.707155]
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2237 [D loss: 0.691012, acc.: 53.32%] [G loss: 0.706595]
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2238 [D loss: 0.691130, acc.: 54.49%] [G loss: 0.705706]
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2239 [D loss: 0.692581, acc.: 51.76%] [G loss: 0.705274]
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2240 [D loss: 0.691898, acc.: 49.80%] [G loss: 0.701097]
8/8 [==============================] - 0s 4ms/step
2241 [D loss: 0.693467, acc.: 49.22%] [G loss: 0.700942]
8/8 [==============================] - 0s 4ms/step
2242 [D loss: 0.692935, acc.: 48.83%] [G loss: 0.697988]
8/8 [==============================] - 0s 4ms/step
2243 [D loss: 0.692995, acc.: 50.00%] [G loss: 0.698083]
8/8 [==============================] - 0s 4ms/step
2244 [D loss: 0.692837, acc.: 50.78%] [G loss: 0.699234]
8/8 [==============================] - 0s 4ms/step
2245 [D loss: 0.693852, acc.: 49.80%] [G loss: 0.697436]
8/8 [==============================] - 0s 4ms/step
2246 [D loss: 0.696141, acc.: 45.31%] [G loss: 0.696536]
8/8 [==============================] - 0s 4ms/step
2247 [D loss: 0.694023, acc.: 48.83%] [G loss: 0.697111]
8/8 [==============================] - 0s 4ms/step
2248 [D loss: 0.693005, acc.: 49.61%] [G loss: 0.697858]
8/8 [==============================] - 0s 4ms/step
2249 [D loss: 0.695451, acc.: 44.92%] [G loss: 0.694288]
8/8 [==============================] - 0s 4ms/step
2250 [D loss: 0.694710, acc.: 47.07%] [G loss: 0.695800]
1/1 [==============================] - 0s 20ms/step
8/8 [==============================] - 0s 4ms/step
2251 [D loss: 0.694808, acc.: 47.27%] [G loss: 0.696443]
8/8 [==============================] - 0s 4ms/step
2252 [D loss: 0.694702, acc.: 46.09%] [G loss: 0.696152]
8/8 [==============================] - 0s 4ms/step
2253 [D loss: 0.694172, acc.: 50.59%] [G loss: 0.696495]
8/8 [==============================] - 0s 4ms/step
2254 [D loss: 0.693851, acc.: 50.00%] [G loss: 0.696950]
8/8 [==============================] - 0s 4ms/step
2255 [D loss: 0.696044, acc.: 43.95%] [G loss: 0.697732]
8/8 [==============================] - 0s 4ms/step
2256 [D loss: 0.693035, acc.: 48.63%] [G loss: 0.700092]
8/8 [==============================] - 0s 4ms/step
2257 [D loss: 0.694391, acc.: 48.83%] [G loss: 0.699252]
8/8 [==============================] - 0s 4ms/step
2258 [D loss: 0.693453, acc.: 49.22%] [G loss: 0.696642]
8/8 [==============================] - 0s 4ms/step
2259 [D loss: 0.692189, acc.: 49.02%] [G loss: 0.696577]
8/8 [==============================] - 0s 4ms/step
2260 [D loss: 0.692587, acc.: 49.80%] [G loss: 0.700679]
8/8 [==============================] - 0s 4ms/step
2261 [D loss: 0.694537, acc.: 49.22%] [G loss: 0.698227]
8/8 [==============================] - 0s 4ms/step
2262 [D loss: 0.691221, acc.: 55.27%] [G loss: 0.699712]
8/8 [==============================] - 0s 4ms/step
2263 [D loss: 0.691832, acc.: 51.56%] [G loss: 0.698305]
8/8 [==============================] - 0s 4ms/step
2264 [D loss: 0.692887, acc.: 51.37%] [G loss: 0.697031]
8/8 [==============================] - 0s 4ms/step
2265 [D loss: 0.692828, acc.: 50.59%] [G loss: 0.696818]
8/8 [==============================] - 0s 4ms/step
2266 [D loss: 0.693608, acc.: 51.17%] [G loss: 0.697346]
8/8 [==============================] - 0s 4ms/step
2267 [D loss: 0.693397, acc.: 48.44%] [G loss: 0.696161]
8/8 [==============================] - 0s 4ms/step
2268 [D loss: 0.694390, acc.: 45.90%] [G loss: 0.696211]
8/8 [==============================] - 0s 4ms/step
2269 [D loss: 0.693788, acc.: 46.29%] [G loss: 0.696192]
8/8 [==============================] - 0s 4ms/step
2270 [D loss: 0.691885, acc.: 55.86%] [G loss: 0.697199]
8/8 [==============================] - 0s 4ms/step
2271 [D loss: 0.693048, acc.: 51.95%] [G loss: 0.697800]
8/8 [==============================] - 0s 4ms/step
2272 [D loss: 0.693459, acc.: 49.61%] [G loss: 0.696205]
8/8 [==============================] - 0s 4ms/step
2273 [D loss: 0.693340, acc.: 49.61%] [G loss: 0.698722]
8/8 [==============================] - 0s 4ms/step
2274 [D loss: 0.693585, acc.: 49.22%] [G loss: 0.699026]
8/8 [==============================] - 0s 4ms/step
2275 [D loss: 0.692520, acc.: 52.15%] [G loss: 0.697996]
8/8 [==============================] - 0s 4ms/step
2276 [D loss: 0.693056, acc.: 50.00%] [G loss: 0.698034]
8/8 [==============================] - 0s 4ms/step
2277 [D loss: 0.693896, acc.: 50.00%] [G loss: 0.701746]
8/8 [==============================] - 0s 4ms/step
2278 [D loss: 0.693193, acc.: 47.85%] [G loss: 0.699269]
8/8 [==============================] - 0s 4ms/step
2279 [D loss: 0.694218, acc.: 45.31%] [G loss: 0.697661]
8/8 [==============================] - 0s 4ms/step
2280 [D loss: 0.693391, acc.: 50.39%] [G loss: 0.700850]
8/8 [==============================] - 0s 4ms/step
2281 [D loss: 0.692306, acc.: 54.10%] [G loss: 0.699965]
8/8 [==============================] - 0s 4ms/step
2282 [D loss: 0.692498, acc.: 51.56%] [G loss: 0.699760]
8/8 [==============================] - 0s 4ms/step
2283 [D loss: 0.691842, acc.: 52.34%] [G loss: 0.699136]
8/8 [==============================] - 0s 4ms/step
2284 [D loss: 0.694084, acc.: 48.24%] [G loss: 0.701030]
8/8 [==============================] - 0s 4ms/step
2285 [D loss: 0.693527, acc.: 50.00%] [G loss: 0.704171]
8/8 [==============================] - 0s 4ms/step
2286 [D loss: 0.691743, acc.: 52.15%] [G loss: 0.702371]
8/8 [==============================] - 0s 4ms/step
2287 [D loss: 0.692021, acc.: 53.52%] [G loss: 0.702341]
8/8 [==============================] - 0s 4ms/step
2288 [D loss: 0.693418, acc.: 49.22%] [G loss: 0.701043]
8/8 [==============================] - 0s 4ms/step
2289 [D loss: 0.692495, acc.: 50.78%] [G loss: 0.702731]
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2290 [D loss: 0.691283, acc.: 53.71%] [G loss: 0.702942]
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2291 [D loss: 0.693064, acc.: 49.41%] [G loss: 0.700609]
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2292 [D loss: 0.694391, acc.: 50.00%] [G loss: 0.699720]
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2293 [D loss: 0.692076, acc.: 52.93%] [G loss: 0.701484]
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2294 [D loss: 0.691974, acc.: 53.32%] [G loss: 0.699834]
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2295 [D loss: 0.692780, acc.: 51.76%] [G loss: 0.700168]
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2296 [D loss: 0.694013, acc.: 48.05%] [G loss: 0.699877]
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2297 [D loss: 0.692357, acc.: 54.30%] [G loss: 0.700565]
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2298 [D loss: 0.691645, acc.: 52.93%] [G loss: 0.700772]
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2299 [D loss: 0.692965, acc.: 50.00%] [G loss: 0.699379]
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2300 [D loss: 0.693536, acc.: 50.78%] [G loss: 0.697994]
1/1 [==============================] - 0s 16ms/step
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2301 [D loss: 0.694025, acc.: 51.17%] [G loss: 0.698470]
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2302 [D loss: 0.693145, acc.: 50.20%] [G loss: 0.698535]
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2303 [D loss: 0.695382, acc.: 45.90%] [G loss: 0.694502]
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2304 [D loss: 0.695093, acc.: 45.51%] [G loss: 0.693051]
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2305 [D loss: 0.695924, acc.: 44.73%] [G loss: 0.692890]
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2306 [D loss: 0.695884, acc.: 46.88%] [G loss: 0.694047]
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2307 [D loss: 0.695399, acc.: 44.53%] [G loss: 0.692855]
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2308 [D loss: 0.695046, acc.: 43.95%] [G loss: 0.693736]
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2309 [D loss: 0.695741, acc.: 43.55%] [G loss: 0.692432]
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2310 [D loss: 0.695216, acc.: 47.66%] [G loss: 0.693299]
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2311 [D loss: 0.694156, acc.: 46.29%] [G loss: 0.694807]
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2312 [D loss: 0.693694, acc.: 47.07%] [G loss: 0.695839]
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2313 [D loss: 0.694013, acc.: 47.46%] [G loss: 0.695548]
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2314 [D loss: 0.691835, acc.: 53.12%] [G loss: 0.693610]
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2315 [D loss: 0.693365, acc.: 50.98%] [G loss: 0.693831]
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2316 [D loss: 0.692781, acc.: 50.00%] [G loss: 0.696896]
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2317 [D loss: 0.691425, acc.: 54.49%] [G loss: 0.697240]
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2318 [D loss: 0.692742, acc.: 50.39%] [G loss: 0.696352]
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2319 [D loss: 0.692037, acc.: 53.12%] [G loss: 0.696759]
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2320 [D loss: 0.692280, acc.: 51.95%] [G loss: 0.696134]
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2321 [D loss: 0.691618, acc.: 52.93%] [G loss: 0.694732]
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2322 [D loss: 0.690956, acc.: 55.08%] [G loss: 0.694764]
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2323 [D loss: 0.692365, acc.: 52.93%] [G loss: 0.695795]
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2324 [D loss: 0.692535, acc.: 49.41%] [G loss: 0.693709]
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2325 [D loss: 0.694262, acc.: 47.07%] [G loss: 0.694396]
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2326 [D loss: 0.693251, acc.: 48.63%] [G loss: 0.693132]
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2327 [D loss: 0.693190, acc.: 50.78%] [G loss: 0.695238]
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2328 [D loss: 0.695156, acc.: 45.70%] [G loss: 0.694633]
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2329 [D loss: 0.693094, acc.: 51.17%] [G loss: 0.693187]
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2330 [D loss: 0.694382, acc.: 45.90%] [G loss: 0.695438]
8/8 [==============================] - 0s 4ms/step
2331 [D loss: 0.693398, acc.: 48.83%] [G loss: 0.695838]
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2332 [D loss: 0.693115, acc.: 52.54%] [G loss: 0.694816]
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2333 [D loss: 0.691359, acc.: 53.12%] [G loss: 0.695274]
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2334 [D loss: 0.692810, acc.: 49.02%] [G loss: 0.697735]
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2335 [D loss: 0.692242, acc.: 52.34%] [G loss: 0.697936]
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2336 [D loss: 0.691896, acc.: 52.73%] [G loss: 0.698145]
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2337 [D loss: 0.695160, acc.: 44.73%] [G loss: 0.697424]
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2338 [D loss: 0.691009, acc.: 57.42%] [G loss: 0.698614]
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2339 [D loss: 0.693219, acc.: 50.20%] [G loss: 0.698260]
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2340 [D loss: 0.692058, acc.: 54.69%] [G loss: 0.696112]
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2341 [D loss: 0.692975, acc.: 51.76%] [G loss: 0.700524]
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2342 [D loss: 0.694800, acc.: 46.88%] [G loss: 0.696070]
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2343 [D loss: 0.694313, acc.: 46.48%] [G loss: 0.695420]
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2344 [D loss: 0.692846, acc.: 54.10%] [G loss: 0.694171]
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2345 [D loss: 0.693703, acc.: 48.83%] [G loss: 0.693202]
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2346 [D loss: 0.695327, acc.: 44.92%] [G loss: 0.693392]
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2347 [D loss: 0.695345, acc.: 44.53%] [G loss: 0.694371]
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2348 [D loss: 0.693559, acc.: 48.83%] [G loss: 0.692654]
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2349 [D loss: 0.695422, acc.: 44.92%] [G loss: 0.695314]
8/8 [==============================] - 0s 4ms/step
2350 [D loss: 0.695650, acc.: 46.48%] [G loss: 0.692704]
1/1 [==============================] - 0s 16ms/step
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2351 [D loss: 0.695064, acc.: 43.95%] [G loss: 0.694149]
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2352 [D loss: 0.694421, acc.: 46.29%] [G loss: 0.695904]
8/8 [==============================] - 0s 4ms/step
2353 [D loss: 0.692352, acc.: 52.15%] [G loss: 0.695524]
8/8 [==============================] - 0s 4ms/step
2354 [D loss: 0.691804, acc.: 52.34%] [G loss: 0.696358]
8/8 [==============================] - 0s 4ms/step
2355 [D loss: 0.694014, acc.: 48.83%] [G loss: 0.696459]
8/8 [==============================] - 0s 4ms/step
2356 [D loss: 0.692177, acc.: 50.59%] [G loss: 0.695764]
8/8 [==============================] - 0s 4ms/step
2357 [D loss: 0.691317, acc.: 55.27%] [G loss: 0.698203]
8/8 [==============================] - 0s 4ms/step
2358 [D loss: 0.691576, acc.: 55.47%] [G loss: 0.696697]
8/8 [==============================] - 0s 4ms/step
2359 [D loss: 0.691973, acc.: 51.76%] [G loss: 0.696913]
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2360 [D loss: 0.690533, acc.: 56.25%] [G loss: 0.699253]
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2361 [D loss: 0.690935, acc.: 55.27%] [G loss: 0.700071]
8/8 [==============================] - 0s 4ms/step
2362 [D loss: 0.690930, acc.: 54.30%] [G loss: 0.698157]
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2363 [D loss: 0.691365, acc.: 53.91%] [G loss: 0.695642]
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2364 [D loss: 0.693221, acc.: 53.12%] [G loss: 0.696227]
8/8 [==============================] - 0s 4ms/step
2365 [D loss: 0.692714, acc.: 54.69%] [G loss: 0.691945]
8/8 [==============================] - 0s 4ms/step
2366 [D loss: 0.694253, acc.: 49.61%] [G loss: 0.693354]
8/8 [==============================] - 0s 4ms/step
2367 [D loss: 0.695289, acc.: 45.51%] [G loss: 0.692549]
8/8 [==============================] - 0s 4ms/step
2368 [D loss: 0.694392, acc.: 48.83%] [G loss: 0.693394]
8/8 [==============================] - 0s 4ms/step
2369 [D loss: 0.695674, acc.: 45.51%] [G loss: 0.693173]
8/8 [==============================] - 0s 4ms/step
2370 [D loss: 0.693315, acc.: 50.00%] [G loss: 0.692447]
8/8 [==============================] - 0s 4ms/step
2371 [D loss: 0.694379, acc.: 48.24%] [G loss: 0.696018]
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2372 [D loss: 0.694950, acc.: 45.90%] [G loss: 0.694781]
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2373 [D loss: 0.691205, acc.: 55.66%] [G loss: 0.695835]
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2374 [D loss: 0.693553, acc.: 50.00%] [G loss: 0.695501]
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2375 [D loss: 0.692841, acc.: 50.59%] [G loss: 0.693938]
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2376 [D loss: 0.693447, acc.: 49.61%] [G loss: 0.693583]
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2377 [D loss: 0.693877, acc.: 50.98%] [G loss: 0.691644]
8/8 [==============================] - 0s 4ms/step
2378 [D loss: 0.694367, acc.: 48.44%] [G loss: 0.692324]
8/8 [==============================] - 0s 4ms/step
2379 [D loss: 0.695215, acc.: 49.02%] [G loss: 0.690973]
8/8 [==============================] - 0s 4ms/step
2380 [D loss: 0.696129, acc.: 41.60%] [G loss: 0.692095]
8/8 [==============================] - 0s 4ms/step
2381 [D loss: 0.693484, acc.: 48.05%] [G loss: 0.691296]
8/8 [==============================] - 0s 4ms/step
2382 [D loss: 0.694798, acc.: 45.51%] [G loss: 0.692516]
8/8 [==============================] - 0s 4ms/step
2383 [D loss: 0.694616, acc.: 43.16%] [G loss: 0.692376]
8/8 [==============================] - 0s 4ms/step
2384 [D loss: 0.693779, acc.: 46.88%] [G loss: 0.694129]
8/8 [==============================] - 0s 4ms/step
2385 [D loss: 0.694794, acc.: 44.92%] [G loss: 0.694175]
8/8 [==============================] - 0s 4ms/step
2386 [D loss: 0.693334, acc.: 49.61%] [G loss: 0.697751]
8/8 [==============================] - 0s 4ms/step
2387 [D loss: 0.693870, acc.: 50.00%] [G loss: 0.695230]
8/8 [==============================] - 0s 4ms/step
2388 [D loss: 0.694085, acc.: 49.61%] [G loss: 0.695696]
8/8 [==============================] - 0s 4ms/step
2389 [D loss: 0.695103, acc.: 44.73%] [G loss: 0.692473]
8/8 [==============================] - 0s 4ms/step
2390 [D loss: 0.693155, acc.: 50.98%] [G loss: 0.694573]
8/8 [==============================] - 0s 4ms/step
2391 [D loss: 0.692895, acc.: 48.63%] [G loss: 0.695283]
8/8 [==============================] - 0s 4ms/step
2392 [D loss: 0.691506, acc.: 54.88%] [G loss: 0.695025]
8/8 [==============================] - 0s 4ms/step
2393 [D loss: 0.694112, acc.: 49.80%] [G loss: 0.698047]
8/8 [==============================] - 0s 4ms/step
2394 [D loss: 0.691613, acc.: 54.30%] [G loss: 0.698657]
8/8 [==============================] - 0s 4ms/step
2395 [D loss: 0.690480, acc.: 55.66%] [G loss: 0.700154]
8/8 [==============================] - 0s 4ms/step
2396 [D loss: 0.691616, acc.: 53.32%] [G loss: 0.701125]
8/8 [==============================] - 0s 4ms/step
2397 [D loss: 0.690610, acc.: 56.64%] [G loss: 0.701100]
8/8 [==============================] - 0s 4ms/step
2398 [D loss: 0.690587, acc.: 57.62%] [G loss: 0.702736]
8/8 [==============================] - 0s 4ms/step
2399 [D loss: 0.688336, acc.: 61.33%] [G loss: 0.705550]
8/8 [==============================] - 0s 4ms/step
2400 [D loss: 0.689650, acc.: 57.23%] [G loss: 0.704378]
1/1 [==============================] - 0s 17ms/step
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2401 [D loss: 0.689566, acc.: 55.86%] [G loss: 0.702530]
8/8 [==============================] - 0s 4ms/step
2402 [D loss: 0.693285, acc.: 48.83%] [G loss: 0.697436]
8/8 [==============================] - 0s 4ms/step
2403 [D loss: 0.693380, acc.: 51.17%] [G loss: 0.700409]
8/8 [==============================] - 0s 4ms/step
2404 [D loss: 0.692987, acc.: 51.37%] [G loss: 0.700725]
8/8 [==============================] - 0s 4ms/step
2405 [D loss: 0.692344, acc.: 51.95%] [G loss: 0.697158]
8/8 [==============================] - 0s 4ms/step
2406 [D loss: 0.695492, acc.: 46.88%] [G loss: 0.694830]
8/8 [==============================] - 0s 4ms/step
2407 [D loss: 0.696840, acc.: 44.73%] [G loss: 0.693269]
8/8 [==============================] - 0s 4ms/step
2408 [D loss: 0.695499, acc.: 47.46%] [G loss: 0.693267]
8/8 [==============================] - 0s 4ms/step
2409 [D loss: 0.694397, acc.: 47.85%] [G loss: 0.694429]
8/8 [==============================] - 0s 4ms/step
2410 [D loss: 0.693990, acc.: 48.83%] [G loss: 0.695525]
8/8 [==============================] - 0s 4ms/step
2411 [D loss: 0.694217, acc.: 49.02%] [G loss: 0.697145]
8/8 [==============================] - 0s 4ms/step
2412 [D loss: 0.695105, acc.: 45.70%] [G loss: 0.692970]
8/8 [==============================] - 0s 4ms/step
2413 [D loss: 0.696032, acc.: 44.34%] [G loss: 0.695630]
8/8 [==============================] - 0s 4ms/step
2414 [D loss: 0.694385, acc.: 47.07%] [G loss: 0.692414]
8/8 [==============================] - 0s 4ms/step
2415 [D loss: 0.695573, acc.: 45.12%] [G loss: 0.694821]
8/8 [==============================] - 0s 4ms/step
2416 [D loss: 0.695283, acc.: 44.53%] [G loss: 0.693561]
8/8 [==============================] - 0s 4ms/step
2417 [D loss: 0.694751, acc.: 44.73%] [G loss: 0.695471]
8/8 [==============================] - 0s 4ms/step
2418 [D loss: 0.693866, acc.: 46.88%] [G loss: 0.696531]
8/8 [==============================] - 0s 4ms/step
2419 [D loss: 0.693741, acc.: 48.05%] [G loss: 0.696839]
8/8 [==============================] - 0s 4ms/step
2420 [D loss: 0.692994, acc.: 49.80%] [G loss: 0.698088]
8/8 [==============================] - 0s 4ms/step
2421 [D loss: 0.692363, acc.: 52.15%] [G loss: 0.699418]
8/8 [==============================] - 0s 4ms/step
2422 [D loss: 0.692472, acc.: 53.52%] [G loss: 0.700273]
8/8 [==============================] - 0s 4ms/step
2423 [D loss: 0.692413, acc.: 52.54%] [G loss: 0.701209]
8/8 [==============================] - 0s 4ms/step
2424 [D loss: 0.692526, acc.: 50.59%] [G loss: 0.701910]
8/8 [==============================] - 0s 4ms/step
2425 [D loss: 0.692174, acc.: 51.17%] [G loss: 0.704496]
8/8 [==============================] - 0s 4ms/step
2426 [D loss: 0.690590, acc.: 54.49%] [G loss: 0.703685]
8/8 [==============================] - 0s 4ms/step
2427 [D loss: 0.690658, acc.: 54.49%] [G loss: 0.703632]
8/8 [==============================] - 0s 4ms/step
2428 [D loss: 0.690113, acc.: 57.23%] [G loss: 0.704589]
8/8 [==============================] - 0s 4ms/step
2429 [D loss: 0.692760, acc.: 50.78%] [G loss: 0.702881]
8/8 [==============================] - 0s 4ms/step
2430 [D loss: 0.690064, acc.: 56.25%] [G loss: 0.702941]
8/8 [==============================] - 0s 4ms/step
2431 [D loss: 0.693482, acc.: 49.22%] [G loss: 0.701113]
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2432 [D loss: 0.694177, acc.: 46.48%] [G loss: 0.701117]
8/8 [==============================] - 0s 4ms/step
2433 [D loss: 0.691873, acc.: 50.98%] [G loss: 0.698803]
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2434 [D loss: 0.693329, acc.: 51.37%] [G loss: 0.699703]
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2435 [D loss: 0.696188, acc.: 45.51%] [G loss: 0.697092]
8/8 [==============================] - 0s 4ms/step
2436 [D loss: 0.693494, acc.: 50.78%] [G loss: 0.696740]
8/8 [==============================] - 0s 4ms/step
2437 [D loss: 0.695018, acc.: 49.61%] [G loss: 0.697971]
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2438 [D loss: 0.695513, acc.: 43.75%] [G loss: 0.696991]
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2439 [D loss: 0.694135, acc.: 50.20%] [G loss: 0.698667]
8/8 [==============================] - 0s 4ms/step
2440 [D loss: 0.695709, acc.: 46.88%] [G loss: 0.697220]
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2441 [D loss: 0.692884, acc.: 50.39%] [G loss: 0.697659]
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2442 [D loss: 0.693152, acc.: 50.00%] [G loss: 0.697686]
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2443 [D loss: 0.693875, acc.: 49.61%] [G loss: 0.697977]
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2444 [D loss: 0.693066, acc.: 49.80%] [G loss: 0.698293]
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2445 [D loss: 0.693525, acc.: 48.83%] [G loss: 0.696485]
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2446 [D loss: 0.693802, acc.: 48.83%] [G loss: 0.700493]
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2447 [D loss: 0.693230, acc.: 51.56%] [G loss: 0.700452]
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2448 [D loss: 0.693164, acc.: 52.54%] [G loss: 0.700325]
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2449 [D loss: 0.692642, acc.: 51.95%] [G loss: 0.700110]
8/8 [==============================] - 0s 4ms/step
2450 [D loss: 0.690524, acc.: 57.03%] [G loss: 0.699862]
1/1 [==============================] - 0s 15ms/step
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2451 [D loss: 0.692068, acc.: 54.69%] [G loss: 0.698628]
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2452 [D loss: 0.692754, acc.: 50.78%] [G loss: 0.698224]
8/8 [==============================] - 0s 4ms/step
2453 [D loss: 0.690644, acc.: 57.81%] [G loss: 0.696578]
8/8 [==============================] - 0s 4ms/step
2454 [D loss: 0.692140, acc.: 52.93%] [G loss: 0.696520]
8/8 [==============================] - 0s 4ms/step
2455 [D loss: 0.692457, acc.: 50.20%] [G loss: 0.697237]
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2456 [D loss: 0.691723, acc.: 53.32%] [G loss: 0.695086]
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2457 [D loss: 0.693038, acc.: 51.37%] [G loss: 0.697731]
8/8 [==============================] - 0s 4ms/step
2458 [D loss: 0.692949, acc.: 49.61%] [G loss: 0.692982]
8/8 [==============================] - 0s 4ms/step
2459 [D loss: 0.691596, acc.: 52.93%] [G loss: 0.693733]
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2460 [D loss: 0.693307, acc.: 48.63%] [G loss: 0.694396]
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2461 [D loss: 0.694597, acc.: 46.29%] [G loss: 0.691873]
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2462 [D loss: 0.693701, acc.: 50.59%] [G loss: 0.693215]
8/8 [==============================] - 0s 4ms/step
2463 [D loss: 0.695461, acc.: 44.53%] [G loss: 0.695486]
8/8 [==============================] - 0s 4ms/step
2464 [D loss: 0.692700, acc.: 51.95%] [G loss: 0.693304]
8/8 [==============================] - 0s 4ms/step
2465 [D loss: 0.694386, acc.: 47.46%] [G loss: 0.692808]
8/8 [==============================] - 0s 4ms/step
2466 [D loss: 0.693798, acc.: 47.46%] [G loss: 0.690224]
8/8 [==============================] - 0s 4ms/step
2467 [D loss: 0.696335, acc.: 44.73%] [G loss: 0.693707]
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2468 [D loss: 0.693683, acc.: 46.09%] [G loss: 0.692833]
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2469 [D loss: 0.694136, acc.: 46.09%] [G loss: 0.693894]
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2470 [D loss: 0.693462, acc.: 47.66%] [G loss: 0.690566]
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2471 [D loss: 0.693915, acc.: 46.48%] [G loss: 0.693410]
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2472 [D loss: 0.692884, acc.: 49.80%] [G loss: 0.692357]
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2473 [D loss: 0.693851, acc.: 47.85%] [G loss: 0.694634]
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2474 [D loss: 0.694180, acc.: 48.24%] [G loss: 0.695794]
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2475 [D loss: 0.694664, acc.: 47.27%] [G loss: 0.693998]
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2476 [D loss: 0.691158, acc.: 53.71%] [G loss: 0.697048]
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2477 [D loss: 0.691642, acc.: 54.69%] [G loss: 0.695694]
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2478 [D loss: 0.693519, acc.: 51.76%] [G loss: 0.698124]
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2479 [D loss: 0.692296, acc.: 51.95%] [G loss: 0.695852]
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2480 [D loss: 0.694321, acc.: 46.68%] [G loss: 0.699597]
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2481 [D loss: 0.694374, acc.: 47.85%] [G loss: 0.699200]
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2482 [D loss: 0.691689, acc.: 52.73%] [G loss: 0.699568]
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2483 [D loss: 0.692641, acc.: 50.78%] [G loss: 0.697950]
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2484 [D loss: 0.691922, acc.: 51.76%] [G loss: 0.698667]
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2485 [D loss: 0.689515, acc.: 59.38%] [G loss: 0.700851]
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2486 [D loss: 0.692052, acc.: 52.34%] [G loss: 0.699383]
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2487 [D loss: 0.692956, acc.: 49.22%] [G loss: 0.701260]
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2488 [D loss: 0.691215, acc.: 51.76%] [G loss: 0.697924]
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2489 [D loss: 0.694394, acc.: 47.27%] [G loss: 0.697507]
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2490 [D loss: 0.694401, acc.: 47.07%] [G loss: 0.698137]
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2491 [D loss: 0.691822, acc.: 51.95%] [G loss: 0.698736]
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2492 [D loss: 0.693288, acc.: 50.78%] [G loss: 0.699564]
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2493 [D loss: 0.694019, acc.: 48.44%] [G loss: 0.699860]
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2494 [D loss: 0.692609, acc.: 48.83%] [G loss: 0.700123]
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2495 [D loss: 0.692691, acc.: 50.39%] [G loss: 0.697059]
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2496 [D loss: 0.691428, acc.: 52.34%] [G loss: 0.697565]
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2497 [D loss: 0.693813, acc.: 50.20%] [G loss: 0.695175]
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2498 [D loss: 0.695130, acc.: 48.63%] [G loss: 0.695843]
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2499 [D loss: 0.694383, acc.: 52.34%] [G loss: 0.695511]
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2500 [D loss: 0.694895, acc.: 46.68%] [G loss: 0.699878]
1/1 [==============================] - 0s 16ms/step
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2501 [D loss: 0.694240, acc.: 49.80%] [G loss: 0.697519]
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2502 [D loss: 0.693530, acc.: 52.15%] [G loss: 0.697247]
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2503 [D loss: 0.692401, acc.: 52.54%] [G loss: 0.700267]
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2504 [D loss: 0.694305, acc.: 48.83%] [G loss: 0.701065]
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2505 [D loss: 0.690906, acc.: 53.52%] [G loss: 0.701678]
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2506 [D loss: 0.692893, acc.: 51.37%] [G loss: 0.701093]
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2507 [D loss: 0.692215, acc.: 52.34%] [G loss: 0.698381]
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2508 [D loss: 0.690913, acc.: 54.69%] [G loss: 0.699358]
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2509 [D loss: 0.692146, acc.: 53.32%] [G loss: 0.695954]
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2510 [D loss: 0.692772, acc.: 52.73%] [G loss: 0.698215]
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2511 [D loss: 0.691607, acc.: 52.15%] [G loss: 0.696888]
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2512 [D loss: 0.692289, acc.: 50.39%] [G loss: 0.695300]
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2513 [D loss: 0.694362, acc.: 47.85%] [G loss: 0.694287]
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2514 [D loss: 0.692299, acc.: 52.54%] [G loss: 0.694649]
8/8 [==============================] - 0s 4ms/step
2515 [D loss: 0.694232, acc.: 48.44%] [G loss: 0.694362]
8/8 [==============================] - 0s 4ms/step
2516 [D loss: 0.694457, acc.: 48.24%] [G loss: 0.694279]
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2517 [D loss: 0.693557, acc.: 50.00%] [G loss: 0.691233]
8/8 [==============================] - 0s 4ms/step
2518 [D loss: 0.693095, acc.: 55.08%] [G loss: 0.694095]
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2519 [D loss: 0.693911, acc.: 50.00%] [G loss: 0.693585]
8/8 [==============================] - 0s 4ms/step
2520 [D loss: 0.693091, acc.: 50.98%] [G loss: 0.693481]
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2521 [D loss: 0.691789, acc.: 52.54%] [G loss: 0.695052]
8/8 [==============================] - 0s 4ms/step
2522 [D loss: 0.692309, acc.: 50.00%] [G loss: 0.693234]
8/8 [==============================] - 0s 4ms/step
2523 [D loss: 0.692915, acc.: 50.78%] [G loss: 0.692356]
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2524 [D loss: 0.693649, acc.: 48.63%] [G loss: 0.695010]
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2525 [D loss: 0.691456, acc.: 50.98%] [G loss: 0.692815]
8/8 [==============================] - 0s 4ms/step
2526 [D loss: 0.692834, acc.: 48.83%] [G loss: 0.692914]
8/8 [==============================] - 0s 4ms/step
2527 [D loss: 0.692924, acc.: 48.63%] [G loss: 0.692046]
8/8 [==============================] - 0s 4ms/step
2528 [D loss: 0.693884, acc.: 48.83%] [G loss: 0.692705]
8/8 [==============================] - 0s 4ms/step
2529 [D loss: 0.693300, acc.: 51.76%] [G loss: 0.690883]
8/8 [==============================] - 0s 4ms/step
2530 [D loss: 0.692890, acc.: 48.83%] [G loss: 0.693180]
8/8 [==============================] - 0s 4ms/step
2531 [D loss: 0.693391, acc.: 50.78%] [G loss: 0.695287]
8/8 [==============================] - 0s 4ms/step
2532 [D loss: 0.693305, acc.: 48.63%] [G loss: 0.695036]
8/8 [==============================] - 0s 4ms/step
2533 [D loss: 0.693862, acc.: 49.41%] [G loss: 0.694905]
8/8 [==============================] - 0s 4ms/step
2534 [D loss: 0.691989, acc.: 52.73%] [G loss: 0.694077]
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2535 [D loss: 0.693224, acc.: 50.20%] [G loss: 0.691669]
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2536 [D loss: 0.693540, acc.: 50.39%] [G loss: 0.692609]
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2537 [D loss: 0.696700, acc.: 43.55%] [G loss: 0.691288]
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2538 [D loss: 0.695011, acc.: 44.73%] [G loss: 0.691034]
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2539 [D loss: 0.694838, acc.: 46.68%] [G loss: 0.691978]
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2540 [D loss: 0.694944, acc.: 49.22%] [G loss: 0.696844]
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2541 [D loss: 0.693200, acc.: 49.22%] [G loss: 0.699103]
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2542 [D loss: 0.693850, acc.: 50.59%] [G loss: 0.700065]
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2543 [D loss: 0.693037, acc.: 47.46%] [G loss: 0.701560]
8/8 [==============================] - 0s 4ms/step
2544 [D loss: 0.692240, acc.: 53.32%] [G loss: 0.699056]
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2545 [D loss: 0.691746, acc.: 54.49%] [G loss: 0.701768]
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2546 [D loss: 0.691516, acc.: 51.76%] [G loss: 0.704065]
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2547 [D loss: 0.691045, acc.: 53.71%] [G loss: 0.705207]
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2548 [D loss: 0.690810, acc.: 53.71%] [G loss: 0.704581]
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2549 [D loss: 0.690447, acc.: 52.15%] [G loss: 0.702575]
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2550 [D loss: 0.691575, acc.: 53.12%] [G loss: 0.701373]
1/1 [==============================] - 0s 17ms/step
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2551 [D loss: 0.690927, acc.: 49.80%] [G loss: 0.700111]
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2552 [D loss: 0.692836, acc.: 48.83%] [G loss: 0.701790]
8/8 [==============================] - 0s 4ms/step
2553 [D loss: 0.692474, acc.: 50.59%] [G loss: 0.699501]
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2554 [D loss: 0.693275, acc.: 51.76%] [G loss: 0.700686]
8/8 [==============================] - 0s 4ms/step
2555 [D loss: 0.690957, acc.: 55.08%] [G loss: 0.701386]
8/8 [==============================] - 0s 4ms/step
2556 [D loss: 0.694309, acc.: 46.68%] [G loss: 0.699768]
8/8 [==============================] - 0s 4ms/step
2557 [D loss: 0.692835, acc.: 49.02%] [G loss: 0.699933]
8/8 [==============================] - 0s 4ms/step
2558 [D loss: 0.693783, acc.: 48.83%] [G loss: 0.697405]
8/8 [==============================] - 0s 4ms/step
2559 [D loss: 0.692557, acc.: 53.12%] [G loss: 0.697893]
8/8 [==============================] - 0s 4ms/step
2560 [D loss: 0.693312, acc.: 50.78%] [G loss: 0.697806]
8/8 [==============================] - 0s 4ms/step
2561 [D loss: 0.692178, acc.: 51.95%] [G loss: 0.699345]
8/8 [==============================] - 0s 4ms/step
2562 [D loss: 0.694422, acc.: 46.88%] [G loss: 0.696670]
8/8 [==============================] - 0s 4ms/step
2563 [D loss: 0.692552, acc.: 51.17%] [G loss: 0.697873]
8/8 [==============================] - 0s 4ms/step
2564 [D loss: 0.694743, acc.: 48.05%] [G loss: 0.696586]
8/8 [==============================] - 0s 4ms/step
2565 [D loss: 0.694433, acc.: 50.20%] [G loss: 0.696324]
8/8 [==============================] - 0s 4ms/step
2566 [D loss: 0.693116, acc.: 51.17%] [G loss: 0.693984]
8/8 [==============================] - 0s 4ms/step
2567 [D loss: 0.694607, acc.: 49.41%] [G loss: 0.695657]
8/8 [==============================] - 0s 4ms/step
2568 [D loss: 0.693664, acc.: 50.20%] [G loss: 0.693691]
8/8 [==============================] - 0s 4ms/step
2569 [D loss: 0.695472, acc.: 49.61%] [G loss: 0.692626]
8/8 [==============================] - 0s 4ms/step
2570 [D loss: 0.692643, acc.: 50.20%] [G loss: 0.692254]
8/8 [==============================] - 0s 4ms/step
2571 [D loss: 0.694044, acc.: 50.20%] [G loss: 0.692721]
8/8 [==============================] - 0s 4ms/step
2572 [D loss: 0.693457, acc.: 49.22%] [G loss: 0.693443]
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2573 [D loss: 0.694198, acc.: 48.83%] [G loss: 0.696236]
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2574 [D loss: 0.695911, acc.: 45.70%] [G loss: 0.697970]
8/8 [==============================] - 0s 4ms/step
2575 [D loss: 0.693019, acc.: 52.34%] [G loss: 0.696824]
8/8 [==============================] - 0s 4ms/step
2576 [D loss: 0.691738, acc.: 52.15%] [G loss: 0.697698]
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2577 [D loss: 0.692311, acc.: 52.93%] [G loss: 0.696078]
8/8 [==============================] - 0s 4ms/step
2578 [D loss: 0.691646, acc.: 53.71%] [G loss: 0.697229]
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2579 [D loss: 0.690900, acc.: 55.86%] [G loss: 0.694204]
8/8 [==============================] - 0s 4ms/step
2580 [D loss: 0.691247, acc.: 53.71%] [G loss: 0.695100]
8/8 [==============================] - 0s 4ms/step
2581 [D loss: 0.691768, acc.: 52.54%] [G loss: 0.694713]
8/8 [==============================] - 0s 4ms/step
2582 [D loss: 0.692309, acc.: 55.86%] [G loss: 0.694939]
8/8 [==============================] - 0s 4ms/step
2583 [D loss: 0.692188, acc.: 52.54%] [G loss: 0.695458]
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2584 [D loss: 0.692751, acc.: 52.15%] [G loss: 0.693964]
8/8 [==============================] - 0s 4ms/step
2585 [D loss: 0.694246, acc.: 49.02%] [G loss: 0.695166]
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2586 [D loss: 0.692725, acc.: 51.56%] [G loss: 0.695681]
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2587 [D loss: 0.693765, acc.: 49.80%] [G loss: 0.696473]
8/8 [==============================] - 0s 4ms/step
2588 [D loss: 0.693695, acc.: 51.76%] [G loss: 0.695494]
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2589 [D loss: 0.694709, acc.: 49.41%] [G loss: 0.698053]
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2590 [D loss: 0.691386, acc.: 51.56%] [G loss: 0.696811]
8/8 [==============================] - 0s 4ms/step
2591 [D loss: 0.692575, acc.: 50.39%] [G loss: 0.697596]
8/8 [==============================] - 0s 4ms/step
2592 [D loss: 0.692020, acc.: 53.52%] [G loss: 0.696418]
8/8 [==============================] - 0s 4ms/step
2593 [D loss: 0.692976, acc.: 47.46%] [G loss: 0.696422]
8/8 [==============================] - 0s 4ms/step
2594 [D loss: 0.691454, acc.: 52.54%] [G loss: 0.698335]
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2595 [D loss: 0.691657, acc.: 49.41%] [G loss: 0.695407]
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2596 [D loss: 0.694388, acc.: 47.07%] [G loss: 0.699065]
8/8 [==============================] - 0s 4ms/step
2597 [D loss: 0.693749, acc.: 48.05%] [G loss: 0.695418]
8/8 [==============================] - 0s 4ms/step
2598 [D loss: 0.692496, acc.: 48.63%] [G loss: 0.694765]
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2599 [D loss: 0.694864, acc.: 50.59%] [G loss: 0.695686]
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2600 [D loss: 0.693206, acc.: 48.44%] [G loss: 0.696950]
1/1 [==============================] - 0s 18ms/step
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2601 [D loss: 0.694407, acc.: 48.24%] [G loss: 0.699304]
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2602 [D loss: 0.695161, acc.: 48.05%] [G loss: 0.699198]
8/8 [==============================] - 0s 4ms/step
2603 [D loss: 0.693356, acc.: 49.61%] [G loss: 0.701327]
8/8 [==============================] - 0s 4ms/step
2604 [D loss: 0.693358, acc.: 50.78%] [G loss: 0.699838]
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2605 [D loss: 0.692733, acc.: 47.66%] [G loss: 0.702108]
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2606 [D loss: 0.691860, acc.: 50.78%] [G loss: 0.702857]
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2607 [D loss: 0.693417, acc.: 48.83%] [G loss: 0.704142]
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2608 [D loss: 0.690965, acc.: 54.10%] [G loss: 0.704977]
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2609 [D loss: 0.690764, acc.: 54.10%] [G loss: 0.705993]
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2610 [D loss: 0.692374, acc.: 50.00%] [G loss: 0.705673]
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2611 [D loss: 0.691837, acc.: 51.56%] [G loss: 0.703007]
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2612 [D loss: 0.691871, acc.: 50.78%] [G loss: 0.703473]
8/8 [==============================] - 0s 4ms/step
2613 [D loss: 0.692024, acc.: 53.52%] [G loss: 0.702247]
8/8 [==============================] - 0s 4ms/step
2614 [D loss: 0.691308, acc.: 52.54%] [G loss: 0.701848]
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2615 [D loss: 0.691882, acc.: 54.10%] [G loss: 0.700754]
8/8 [==============================] - 0s 4ms/step
2616 [D loss: 0.692250, acc.: 50.59%] [G loss: 0.697073]
8/8 [==============================] - 0s 4ms/step
2617 [D loss: 0.694052, acc.: 49.02%] [G loss: 0.699421]
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2618 [D loss: 0.694960, acc.: 46.68%] [G loss: 0.699359]
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2619 [D loss: 0.695230, acc.: 45.90%] [G loss: 0.696181]
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2620 [D loss: 0.694904, acc.: 47.27%] [G loss: 0.698311]
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2621 [D loss: 0.694954, acc.: 46.48%] [G loss: 0.695540]
8/8 [==============================] - 0s 4ms/step
2622 [D loss: 0.694092, acc.: 48.63%] [G loss: 0.699584]
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2623 [D loss: 0.693483, acc.: 50.39%] [G loss: 0.697139]
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2624 [D loss: 0.692563, acc.: 52.93%] [G loss: 0.695776]
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2625 [D loss: 0.693928, acc.: 48.44%] [G loss: 0.696165]
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2626 [D loss: 0.692770, acc.: 50.00%] [G loss: 0.698337]
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2627 [D loss: 0.692595, acc.: 51.17%] [G loss: 0.695472]
8/8 [==============================] - 0s 4ms/step
2628 [D loss: 0.694001, acc.: 45.70%] [G loss: 0.694671]
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2629 [D loss: 0.693140, acc.: 50.20%] [G loss: 0.694253]
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2630 [D loss: 0.694367, acc.: 47.66%] [G loss: 0.694151]
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2631 [D loss: 0.694978, acc.: 48.05%] [G loss: 0.694168]
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2632 [D loss: 0.694606, acc.: 45.70%] [G loss: 0.693949]
8/8 [==============================] - 0s 4ms/step
2633 [D loss: 0.694029, acc.: 50.78%] [G loss: 0.694200]
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2634 [D loss: 0.693079, acc.: 50.00%] [G loss: 0.692088]
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2635 [D loss: 0.694403, acc.: 48.24%] [G loss: 0.696519]
8/8 [==============================] - 0s 4ms/step
2636 [D loss: 0.691827, acc.: 51.95%] [G loss: 0.698025]
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2637 [D loss: 0.691948, acc.: 53.71%] [G loss: 0.692270]
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2638 [D loss: 0.695329, acc.: 47.46%] [G loss: 0.696402]
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2639 [D loss: 0.691531, acc.: 51.95%] [G loss: 0.694502]
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2640 [D loss: 0.691846, acc.: 53.91%] [G loss: 0.693357]
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2641 [D loss: 0.693229, acc.: 51.37%] [G loss: 0.696112]
8/8 [==============================] - 0s 4ms/step
2642 [D loss: 0.691587, acc.: 54.10%] [G loss: 0.696083]
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2643 [D loss: 0.692571, acc.: 51.37%] [G loss: 0.694937]
8/8 [==============================] - 0s 4ms/step
2644 [D loss: 0.691615, acc.: 55.27%] [G loss: 0.692695]
8/8 [==============================] - 0s 4ms/step
2645 [D loss: 0.691829, acc.: 52.73%] [G loss: 0.695090]
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2646 [D loss: 0.694330, acc.: 47.46%] [G loss: 0.695718]
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2647 [D loss: 0.693260, acc.: 49.80%] [G loss: 0.694068]
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2648 [D loss: 0.694692, acc.: 47.27%] [G loss: 0.695961]
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2649 [D loss: 0.693062, acc.: 47.66%] [G loss: 0.693740]
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2650 [D loss: 0.693711, acc.: 52.34%] [G loss: 0.695766]
1/1 [==============================] - 0s 17ms/step
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2651 [D loss: 0.693430, acc.: 48.83%] [G loss: 0.696843]
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2652 [D loss: 0.692541, acc.: 49.61%] [G loss: 0.694023]
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2653 [D loss: 0.691607, acc.: 51.95%] [G loss: 0.696162]
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2654 [D loss: 0.693507, acc.: 47.85%] [G loss: 0.697025]
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2655 [D loss: 0.692704, acc.: 49.61%] [G loss: 0.695878]
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2656 [D loss: 0.691594, acc.: 53.32%] [G loss: 0.697396]
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2657 [D loss: 0.693083, acc.: 49.80%] [G loss: 0.696493]
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2658 [D loss: 0.689987, acc.: 54.88%] [G loss: 0.696103]
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2659 [D loss: 0.693202, acc.: 49.02%] [G loss: 0.696466]
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2660 [D loss: 0.691761, acc.: 52.15%] [G loss: 0.696071]
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2661 [D loss: 0.690491, acc.: 56.45%] [G loss: 0.696363]
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2662 [D loss: 0.693213, acc.: 51.76%] [G loss: 0.695540]
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2663 [D loss: 0.693525, acc.: 49.02%] [G loss: 0.698312]
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2664 [D loss: 0.694482, acc.: 46.09%] [G loss: 0.696115]
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2665 [D loss: 0.692634, acc.: 48.63%] [G loss: 0.697425]
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2666 [D loss: 0.695149, acc.: 47.07%] [G loss: 0.698225]
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2667 [D loss: 0.694840, acc.: 46.29%] [G loss: 0.698339]
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2668 [D loss: 0.693117, acc.: 52.34%] [G loss: 0.698142]
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2669 [D loss: 0.694191, acc.: 47.85%] [G loss: 0.697763]
8/8 [==============================] - 0s 4ms/step
2670 [D loss: 0.692920, acc.: 51.37%] [G loss: 0.702464]
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2671 [D loss: 0.693102, acc.: 48.44%] [G loss: 0.699325]
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2672 [D loss: 0.694473, acc.: 48.63%] [G loss: 0.699952]
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2673 [D loss: 0.692382, acc.: 53.52%] [G loss: 0.697885]
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2674 [D loss: 0.691828, acc.: 52.15%] [G loss: 0.698014]
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2675 [D loss: 0.694793, acc.: 45.31%] [G loss: 0.697585]
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2676 [D loss: 0.692787, acc.: 49.61%] [G loss: 0.697884]
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2677 [D loss: 0.694009, acc.: 48.44%] [G loss: 0.695903]
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2678 [D loss: 0.693945, acc.: 47.66%] [G loss: 0.697146]
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2679 [D loss: 0.694347, acc.: 45.70%] [G loss: 0.697110]
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2680 [D loss: 0.693250, acc.: 48.44%] [G loss: 0.698364]
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2681 [D loss: 0.694232, acc.: 48.63%] [G loss: 0.697836]
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2682 [D loss: 0.694234, acc.: 45.31%] [G loss: 0.694381]
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2683 [D loss: 0.693828, acc.: 50.20%] [G loss: 0.697532]
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2684 [D loss: 0.695048, acc.: 47.07%] [G loss: 0.696936]
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2685 [D loss: 0.693313, acc.: 52.54%] [G loss: 0.694796]
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2686 [D loss: 0.693349, acc.: 51.56%] [G loss: 0.693824]
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2687 [D loss: 0.693483, acc.: 48.83%] [G loss: 0.698299]
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2688 [D loss: 0.693617, acc.: 47.27%] [G loss: 0.699059]
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2689 [D loss: 0.693043, acc.: 51.56%] [G loss: 0.699140]
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2690 [D loss: 0.691919, acc.: 51.76%] [G loss: 0.699306]
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2691 [D loss: 0.691409, acc.: 53.71%] [G loss: 0.702319]
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2692 [D loss: 0.693339, acc.: 49.61%] [G loss: 0.698790]
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2693 [D loss: 0.693451, acc.: 52.54%] [G loss: 0.700121]
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2694 [D loss: 0.692167, acc.: 52.34%] [G loss: 0.701259]
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2695 [D loss: 0.691663, acc.: 52.93%] [G loss: 0.698025]
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2696 [D loss: 0.692562, acc.: 50.39%] [G loss: 0.699406]
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2697 [D loss: 0.692463, acc.: 52.34%] [G loss: 0.699686]
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2698 [D loss: 0.692515, acc.: 50.78%] [G loss: 0.698377]
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2699 [D loss: 0.689673, acc.: 54.30%] [G loss: 0.700273]
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2700 [D loss: 0.690631, acc.: 55.66%] [G loss: 0.698853]
1/1 [==============================] - 0s 16ms/step
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2701 [D loss: 0.692493, acc.: 50.00%] [G loss: 0.698063]
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2702 [D loss: 0.691254, acc.: 54.10%] [G loss: 0.699919]
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2703 [D loss: 0.693596, acc.: 48.44%] [G loss: 0.699234]
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2704 [D loss: 0.691363, acc.: 54.30%] [G loss: 0.697618]
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2705 [D loss: 0.693622, acc.: 49.80%] [G loss: 0.699759]
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2706 [D loss: 0.692935, acc.: 52.73%] [G loss: 0.697199]
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2707 [D loss: 0.693134, acc.: 46.68%] [G loss: 0.698295]
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2708 [D loss: 0.693931, acc.: 50.00%] [G loss: 0.697022]
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2709 [D loss: 0.692767, acc.: 50.39%] [G loss: 0.695555]
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2710 [D loss: 0.695303, acc.: 48.05%] [G loss: 0.694369]
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2711 [D loss: 0.693636, acc.: 50.98%] [G loss: 0.695745]
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2712 [D loss: 0.694499, acc.: 46.88%] [G loss: 0.692043]
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2713 [D loss: 0.694804, acc.: 45.90%] [G loss: 0.692721]
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2714 [D loss: 0.695758, acc.: 46.29%] [G loss: 0.694281]
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2715 [D loss: 0.694708, acc.: 48.05%] [G loss: 0.694781]
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2716 [D loss: 0.692950, acc.: 51.56%] [G loss: 0.696857]
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2717 [D loss: 0.694164, acc.: 46.29%] [G loss: 0.696522]
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2718 [D loss: 0.692029, acc.: 51.17%] [G loss: 0.697949]
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2719 [D loss: 0.691479, acc.: 52.93%] [G loss: 0.697200]
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2720 [D loss: 0.692200, acc.: 52.54%] [G loss: 0.695701]
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2721 [D loss: 0.690340, acc.: 56.25%] [G loss: 0.699112]
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2722 [D loss: 0.692240, acc.: 53.52%] [G loss: 0.697555]
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2723 [D loss: 0.691878, acc.: 54.30%] [G loss: 0.698990]
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2724 [D loss: 0.691757, acc.: 54.69%] [G loss: 0.694672]
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2725 [D loss: 0.694160, acc.: 44.73%] [G loss: 0.695204]
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2726 [D loss: 0.693077, acc.: 50.20%] [G loss: 0.695140]
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2727 [D loss: 0.693206, acc.: 50.78%] [G loss: 0.693077]
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2728 [D loss: 0.693024, acc.: 52.15%] [G loss: 0.693317]
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2729 [D loss: 0.693489, acc.: 51.37%] [G loss: 0.696239]
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2730 [D loss: 0.692519, acc.: 53.32%] [G loss: 0.691903]
8/8 [==============================] - 0s 4ms/step
2731 [D loss: 0.692592, acc.: 51.95%] [G loss: 0.693212]
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2732 [D loss: 0.693351, acc.: 49.41%] [G loss: 0.691781]
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2733 [D loss: 0.693040, acc.: 51.76%] [G loss: 0.691370]
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2734 [D loss: 0.693069, acc.: 47.85%] [G loss: 0.693784]
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2735 [D loss: 0.695461, acc.: 44.92%] [G loss: 0.692819]
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2736 [D loss: 0.695594, acc.: 46.48%] [G loss: 0.691808]
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2737 [D loss: 0.694801, acc.: 45.90%] [G loss: 0.695940]
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2738 [D loss: 0.693418, acc.: 48.44%] [G loss: 0.695223]
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2739 [D loss: 0.692476, acc.: 50.59%] [G loss: 0.694476]
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2740 [D loss: 0.693887, acc.: 48.24%] [G loss: 0.695842]
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2741 [D loss: 0.693725, acc.: 48.83%] [G loss: 0.696032]
8/8 [==============================] - 0s 4ms/step
2742 [D loss: 0.691737, acc.: 55.27%] [G loss: 0.697115]
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2743 [D loss: 0.692281, acc.: 53.32%] [G loss: 0.696872]
8/8 [==============================] - 0s 4ms/step
2744 [D loss: 0.692182, acc.: 51.56%] [G loss: 0.697297]
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2745 [D loss: 0.691841, acc.: 54.69%] [G loss: 0.696857]
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2746 [D loss: 0.691708, acc.: 54.69%] [G loss: 0.700548]
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2747 [D loss: 0.690521, acc.: 55.08%] [G loss: 0.699397]
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2748 [D loss: 0.691186, acc.: 54.69%] [G loss: 0.701785]
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2749 [D loss: 0.691366, acc.: 54.69%] [G loss: 0.704359]
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2750 [D loss: 0.690562, acc.: 54.69%] [G loss: 0.703102]
1/1 [==============================] - 0s 16ms/step
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2751 [D loss: 0.690542, acc.: 50.98%] [G loss: 0.702254]
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2752 [D loss: 0.688865, acc.: 59.77%] [G loss: 0.704035]
8/8 [==============================] - 0s 4ms/step
2753 [D loss: 0.691756, acc.: 51.17%] [G loss: 0.699606]
8/8 [==============================] - 0s 4ms/step
2754 [D loss: 0.690619, acc.: 54.69%] [G loss: 0.698908]
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2755 [D loss: 0.692088, acc.: 53.32%] [G loss: 0.696446]
8/8 [==============================] - 0s 4ms/step
2756 [D loss: 0.693703, acc.: 49.61%] [G loss: 0.693186]
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2757 [D loss: 0.694330, acc.: 48.24%] [G loss: 0.690650]
8/8 [==============================] - 0s 4ms/step
2758 [D loss: 0.696200, acc.: 43.95%] [G loss: 0.691494]
8/8 [==============================] - 0s 4ms/step
2759 [D loss: 0.697188, acc.: 47.27%] [G loss: 0.691508]
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2760 [D loss: 0.696924, acc.: 44.73%] [G loss: 0.691065]
8/8 [==============================] - 0s 4ms/step
2761 [D loss: 0.695301, acc.: 46.88%] [G loss: 0.692627]
8/8 [==============================] - 0s 4ms/step
2762 [D loss: 0.698002, acc.: 40.82%] [G loss: 0.693407]
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2763 [D loss: 0.694546, acc.: 45.70%] [G loss: 0.691105]
8/8 [==============================] - 0s 4ms/step
2764 [D loss: 0.694349, acc.: 46.29%] [G loss: 0.694112]
8/8 [==============================] - 0s 4ms/step
2765 [D loss: 0.693829, acc.: 47.66%] [G loss: 0.694341]
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2766 [D loss: 0.693700, acc.: 47.85%] [G loss: 0.694174]
8/8 [==============================] - 0s 4ms/step
2767 [D loss: 0.693442, acc.: 49.80%] [G loss: 0.694328]
8/8 [==============================] - 0s 4ms/step
2768 [D loss: 0.693219, acc.: 50.20%] [G loss: 0.695230]
8/8 [==============================] - 0s 4ms/step
2769 [D loss: 0.692211, acc.: 52.93%] [G loss: 0.695570]
8/8 [==============================] - 0s 4ms/step
2770 [D loss: 0.693568, acc.: 50.20%] [G loss: 0.698652]
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2771 [D loss: 0.691601, acc.: 56.84%] [G loss: 0.696869]
8/8 [==============================] - 0s 4ms/step
2772 [D loss: 0.689067, acc.: 59.38%] [G loss: 0.694785]
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2773 [D loss: 0.689612, acc.: 57.23%] [G loss: 0.697330]
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2774 [D loss: 0.692062, acc.: 54.69%] [G loss: 0.695625]
8/8 [==============================] - 0s 4ms/step
2775 [D loss: 0.691668, acc.: 54.49%] [G loss: 0.694616]
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2776 [D loss: 0.693600, acc.: 50.00%] [G loss: 0.695652]
8/8 [==============================] - 0s 4ms/step
2777 [D loss: 0.690817, acc.: 54.30%] [G loss: 0.694345]
8/8 [==============================] - 0s 4ms/step
2778 [D loss: 0.693211, acc.: 48.83%] [G loss: 0.693679]
8/8 [==============================] - 0s 4ms/step
2779 [D loss: 0.694342, acc.: 47.46%] [G loss: 0.693028]
8/8 [==============================] - 0s 4ms/step
2780 [D loss: 0.692532, acc.: 49.61%] [G loss: 0.694877]
8/8 [==============================] - 0s 4ms/step
2781 [D loss: 0.694586, acc.: 46.68%] [G loss: 0.691443]
8/8 [==============================] - 0s 4ms/step
2782 [D loss: 0.694462, acc.: 47.66%] [G loss: 0.693273]
8/8 [==============================] - 0s 4ms/step
2783 [D loss: 0.696012, acc.: 48.63%] [G loss: 0.689339]
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2784 [D loss: 0.693902, acc.: 48.24%] [G loss: 0.689568]
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2785 [D loss: 0.693559, acc.: 49.22%] [G loss: 0.691028]
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2786 [D loss: 0.694156, acc.: 49.02%] [G loss: 0.691296]
8/8 [==============================] - 0s 4ms/step
2787 [D loss: 0.694976, acc.: 45.51%] [G loss: 0.689973]
8/8 [==============================] - 0s 4ms/step
2788 [D loss: 0.694014, acc.: 46.29%] [G loss: 0.691706]
8/8 [==============================] - 0s 4ms/step
2789 [D loss: 0.694018, acc.: 47.66%] [G loss: 0.696394]
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2790 [D loss: 0.691999, acc.: 54.88%] [G loss: 0.698163]
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2791 [D loss: 0.692145, acc.: 52.15%] [G loss: 0.696164]
8/8 [==============================] - 0s 4ms/step
2792 [D loss: 0.691577, acc.: 51.95%] [G loss: 0.698913]
8/8 [==============================] - 0s 4ms/step
2793 [D loss: 0.694831, acc.: 46.29%] [G loss: 0.699175]
8/8 [==============================] - 0s 4ms/step
2794 [D loss: 0.693183, acc.: 51.76%] [G loss: 0.697781]
8/8 [==============================] - 0s 4ms/step
2795 [D loss: 0.691783, acc.: 51.17%] [G loss: 0.697201]
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2796 [D loss: 0.690617, acc.: 56.84%] [G loss: 0.697107]
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2797 [D loss: 0.690350, acc.: 53.52%] [G loss: 0.699661]
8/8 [==============================] - 0s 4ms/step
2798 [D loss: 0.690835, acc.: 54.69%] [G loss: 0.696711]
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2799 [D loss: 0.692444, acc.: 51.95%] [G loss: 0.696383]
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2800 [D loss: 0.694122, acc.: 47.85%] [G loss: 0.695986]
1/1 [==============================] - 0s 17ms/step
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2801 [D loss: 0.691806, acc.: 53.71%] [G loss: 0.696745]
8/8 [==============================] - 0s 4ms/step
2802 [D loss: 0.693942, acc.: 50.98%] [G loss: 0.694934]
8/8 [==============================] - 0s 4ms/step
2803 [D loss: 0.694312, acc.: 48.05%] [G loss: 0.696077]
8/8 [==============================] - 0s 4ms/step
2804 [D loss: 0.691579, acc.: 56.25%] [G loss: 0.696335]
8/8 [==============================] - 0s 4ms/step
2805 [D loss: 0.693830, acc.: 48.63%] [G loss: 0.695421]
8/8 [==============================] - 0s 4ms/step
2806 [D loss: 0.693373, acc.: 46.29%] [G loss: 0.694562]
8/8 [==============================] - 0s 4ms/step
2807 [D loss: 0.693129, acc.: 48.83%] [G loss: 0.696218]
8/8 [==============================] - 0s 4ms/step
2808 [D loss: 0.691256, acc.: 50.59%] [G loss: 0.699198]
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2809 [D loss: 0.692679, acc.: 50.78%] [G loss: 0.694071]
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2810 [D loss: 0.692302, acc.: 50.59%] [G loss: 0.699304]
8/8 [==============================] - 0s 4ms/step
2811 [D loss: 0.693594, acc.: 50.20%] [G loss: 0.698047]
8/8 [==============================] - 0s 4ms/step
2812 [D loss: 0.692295, acc.: 54.69%] [G loss: 0.700816]
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2813 [D loss: 0.693375, acc.: 49.80%] [G loss: 0.696255]
8/8 [==============================] - 0s 4ms/step
2814 [D loss: 0.694564, acc.: 50.39%] [G loss: 0.694552]
8/8 [==============================] - 0s 4ms/step
2815 [D loss: 0.693440, acc.: 50.59%] [G loss: 0.695414]
8/8 [==============================] - 0s 4ms/step
2816 [D loss: 0.696255, acc.: 45.51%] [G loss: 0.698842]
8/8 [==============================] - 0s 4ms/step
2817 [D loss: 0.694249, acc.: 49.80%] [G loss: 0.696968]
8/8 [==============================] - 0s 4ms/step
2818 [D loss: 0.694149, acc.: 47.85%] [G loss: 0.692758]
8/8 [==============================] - 0s 4ms/step
2819 [D loss: 0.694448, acc.: 48.44%] [G loss: 0.696202]
8/8 [==============================] - 0s 4ms/step
2820 [D loss: 0.694104, acc.: 49.61%] [G loss: 0.696350]
8/8 [==============================] - 0s 4ms/step
2821 [D loss: 0.695447, acc.: 45.90%] [G loss: 0.695849]
8/8 [==============================] - 0s 4ms/step
2822 [D loss: 0.694172, acc.: 47.85%] [G loss: 0.698090]
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2823 [D loss: 0.691862, acc.: 52.93%] [G loss: 0.695283]
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2824 [D loss: 0.692796, acc.: 51.37%] [G loss: 0.698390]
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2825 [D loss: 0.693719, acc.: 47.66%] [G loss: 0.698676]
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2826 [D loss: 0.692445, acc.: 50.98%] [G loss: 0.699380]
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2827 [D loss: 0.692618, acc.: 52.93%] [G loss: 0.698441]
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2828 [D loss: 0.692079, acc.: 52.73%] [G loss: 0.699909]
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2829 [D loss: 0.692758, acc.: 50.00%] [G loss: 0.701508]
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2830 [D loss: 0.693794, acc.: 48.63%] [G loss: 0.701955]
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2831 [D loss: 0.689803, acc.: 58.01%] [G loss: 0.701998]
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2832 [D loss: 0.691879, acc.: 51.95%] [G loss: 0.700813]
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2833 [D loss: 0.691801, acc.: 50.00%] [G loss: 0.702693]
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2834 [D loss: 0.690692, acc.: 54.10%] [G loss: 0.704686]
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2835 [D loss: 0.692286, acc.: 51.17%] [G loss: 0.702459]
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2836 [D loss: 0.690366, acc.: 52.73%] [G loss: 0.704932]
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2837 [D loss: 0.691648, acc.: 54.88%] [G loss: 0.699135]
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2838 [D loss: 0.692675, acc.: 50.39%] [G loss: 0.700324]
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2839 [D loss: 0.692854, acc.: 48.44%] [G loss: 0.699775]
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2840 [D loss: 0.694896, acc.: 46.29%] [G loss: 0.696920]
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2841 [D loss: 0.692602, acc.: 50.20%] [G loss: 0.700545]
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2842 [D loss: 0.693009, acc.: 50.39%] [G loss: 0.696281]
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2843 [D loss: 0.692379, acc.: 48.05%] [G loss: 0.695235]
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2844 [D loss: 0.693151, acc.: 49.41%] [G loss: 0.697582]
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2845 [D loss: 0.692014, acc.: 51.17%] [G loss: 0.693632]
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2846 [D loss: 0.693569, acc.: 49.02%] [G loss: 0.695215]
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2847 [D loss: 0.694069, acc.: 46.68%] [G loss: 0.693626]
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2848 [D loss: 0.695553, acc.: 48.83%] [G loss: 0.693719]
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2849 [D loss: 0.694122, acc.: 49.61%] [G loss: 0.696336]
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2850 [D loss: 0.692980, acc.: 49.22%] [G loss: 0.695832]
1/1 [==============================] - 0s 18ms/step
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2851 [D loss: 0.692963, acc.: 49.22%] [G loss: 0.692320]
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2852 [D loss: 0.692299, acc.: 52.34%] [G loss: 0.691966]
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2853 [D loss: 0.693631, acc.: 48.83%] [G loss: 0.692616]
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2854 [D loss: 0.695313, acc.: 46.09%] [G loss: 0.692069]
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2855 [D loss: 0.694343, acc.: 49.41%] [G loss: 0.695386]
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2856 [D loss: 0.693919, acc.: 48.44%] [G loss: 0.695222]
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2857 [D loss: 0.694423, acc.: 47.27%] [G loss: 0.697575]
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2858 [D loss: 0.692728, acc.: 53.91%] [G loss: 0.698302]
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2859 [D loss: 0.691187, acc.: 56.05%] [G loss: 0.696450]
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2860 [D loss: 0.691670, acc.: 55.08%] [G loss: 0.700085]
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2861 [D loss: 0.689766, acc.: 55.27%] [G loss: 0.698103]
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2862 [D loss: 0.690594, acc.: 55.66%] [G loss: 0.702470]
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2863 [D loss: 0.689934, acc.: 56.45%] [G loss: 0.701478]
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2864 [D loss: 0.689374, acc.: 54.10%] [G loss: 0.700803]
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2865 [D loss: 0.688417, acc.: 58.98%] [G loss: 0.700117]
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2866 [D loss: 0.691869, acc.: 54.30%] [G loss: 0.699478]
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2867 [D loss: 0.691483, acc.: 51.95%] [G loss: 0.697845]
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2868 [D loss: 0.692511, acc.: 51.56%] [G loss: 0.698418]
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2869 [D loss: 0.693049, acc.: 50.00%] [G loss: 0.696302]
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2870 [D loss: 0.693350, acc.: 49.22%] [G loss: 0.697052]
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2871 [D loss: 0.694982, acc.: 48.44%] [G loss: 0.693324]
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2872 [D loss: 0.693832, acc.: 51.56%] [G loss: 0.695578]
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2873 [D loss: 0.693534, acc.: 49.02%] [G loss: 0.694538]
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2874 [D loss: 0.691539, acc.: 51.56%] [G loss: 0.693469]
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2875 [D loss: 0.694791, acc.: 45.31%] [G loss: 0.690768]
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2876 [D loss: 0.693867, acc.: 47.27%] [G loss: 0.691344]
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2877 [D loss: 0.695215, acc.: 47.66%] [G loss: 0.691068]
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2878 [D loss: 0.694363, acc.: 49.02%] [G loss: 0.693029]
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2879 [D loss: 0.692515, acc.: 48.63%] [G loss: 0.695801]
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2880 [D loss: 0.694693, acc.: 47.07%] [G loss: 0.694056]
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2881 [D loss: 0.691535, acc.: 51.37%] [G loss: 0.694820]
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2882 [D loss: 0.694018, acc.: 47.46%] [G loss: 0.694735]
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2883 [D loss: 0.693570, acc.: 47.66%] [G loss: 0.696901]
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2884 [D loss: 0.692316, acc.: 52.93%] [G loss: 0.699719]
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2885 [D loss: 0.689874, acc.: 54.88%] [G loss: 0.700304]
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2886 [D loss: 0.691811, acc.: 53.52%] [G loss: 0.698287]
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2887 [D loss: 0.692461, acc.: 48.63%] [G loss: 0.700121]
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2888 [D loss: 0.691751, acc.: 53.91%] [G loss: 0.697139]
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2889 [D loss: 0.692519, acc.: 48.44%] [G loss: 0.698900]
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2890 [D loss: 0.691439, acc.: 53.12%] [G loss: 0.698659]
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2891 [D loss: 0.692618, acc.: 51.37%] [G loss: 0.700668]
8/8 [==============================] - 0s 4ms/step
2892 [D loss: 0.690760, acc.: 56.25%] [G loss: 0.699941]
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2893 [D loss: 0.690090, acc.: 53.91%] [G loss: 0.697854]
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2894 [D loss: 0.690052, acc.: 56.84%] [G loss: 0.699675]
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2895 [D loss: 0.692214, acc.: 51.56%] [G loss: 0.703521]
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2896 [D loss: 0.692406, acc.: 50.20%] [G loss: 0.697709]
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2897 [D loss: 0.693183, acc.: 51.37%] [G loss: 0.695943]
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2898 [D loss: 0.692369, acc.: 50.59%] [G loss: 0.696854]
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2899 [D loss: 0.692256, acc.: 50.78%] [G loss: 0.695044]
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2900 [D loss: 0.692801, acc.: 51.17%] [G loss: 0.693447]
1/1 [==============================] - 0s 16ms/step
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2901 [D loss: 0.693803, acc.: 48.44%] [G loss: 0.689034]
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2902 [D loss: 0.695033, acc.: 48.05%] [G loss: 0.693554]
8/8 [==============================] - 0s 4ms/step
2903 [D loss: 0.694882, acc.: 49.61%] [G loss: 0.692642]
8/8 [==============================] - 0s 4ms/step
2904 [D loss: 0.694255, acc.: 48.05%] [G loss: 0.694422]
8/8 [==============================] - 0s 4ms/step
2905 [D loss: 0.692270, acc.: 51.17%] [G loss: 0.692900]
8/8 [==============================] - 0s 4ms/step
2906 [D loss: 0.693715, acc.: 49.61%] [G loss: 0.695003]
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2907 [D loss: 0.693204, acc.: 49.80%] [G loss: 0.696101]
8/8 [==============================] - 0s 4ms/step
2908 [D loss: 0.693096, acc.: 49.61%] [G loss: 0.698188]
8/8 [==============================] - 0s 4ms/step
2909 [D loss: 0.690558, acc.: 53.52%] [G loss: 0.697817]
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2910 [D loss: 0.691328, acc.: 54.49%] [G loss: 0.699891]
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2911 [D loss: 0.690575, acc.: 53.91%] [G loss: 0.701385]
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2912 [D loss: 0.689986, acc.: 57.62%] [G loss: 0.699069]
8/8 [==============================] - 0s 4ms/step
2913 [D loss: 0.690700, acc.: 52.54%] [G loss: 0.699364]
8/8 [==============================] - 0s 4ms/step
2914 [D loss: 0.693369, acc.: 49.02%] [G loss: 0.697422]
8/8 [==============================] - 0s 4ms/step
2915 [D loss: 0.692345, acc.: 52.34%] [G loss: 0.698050]
8/8 [==============================] - 0s 4ms/step
2916 [D loss: 0.693230, acc.: 49.61%] [G loss: 0.692856]
8/8 [==============================] - 0s 4ms/step
2917 [D loss: 0.693424, acc.: 50.39%] [G loss: 0.691767]
8/8 [==============================] - 0s 4ms/step
2918 [D loss: 0.696546, acc.: 47.27%] [G loss: 0.691914]
8/8 [==============================] - 0s 4ms/step
2919 [D loss: 0.695954, acc.: 46.68%] [G loss: 0.697281]
8/8 [==============================] - 0s 4ms/step
2920 [D loss: 0.694899, acc.: 48.63%] [G loss: 0.696709]
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2921 [D loss: 0.692585, acc.: 52.15%] [G loss: 0.699375]
8/8 [==============================] - 0s 4ms/step
2922 [D loss: 0.692990, acc.: 50.59%] [G loss: 0.698644]
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2923 [D loss: 0.692710, acc.: 49.61%] [G loss: 0.699804]
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2924 [D loss: 0.693034, acc.: 49.02%] [G loss: 0.698399]
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2925 [D loss: 0.690636, acc.: 54.10%] [G loss: 0.700699]
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2926 [D loss: 0.691644, acc.: 55.08%] [G loss: 0.699183]
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2927 [D loss: 0.689869, acc.: 56.45%] [G loss: 0.699042]
8/8 [==============================] - 0s 4ms/step
2928 [D loss: 0.690813, acc.: 54.88%] [G loss: 0.697064]
8/8 [==============================] - 0s 4ms/step
2929 [D loss: 0.691843, acc.: 51.76%] [G loss: 0.701197]
8/8 [==============================] - 0s 4ms/step
2930 [D loss: 0.693340, acc.: 49.80%] [G loss: 0.699165]
8/8 [==============================] - 0s 4ms/step
2931 [D loss: 0.693144, acc.: 51.37%] [G loss: 0.697740]
8/8 [==============================] - 0s 4ms/step
2932 [D loss: 0.692145, acc.: 49.80%] [G loss: 0.699169]
8/8 [==============================] - 0s 4ms/step
2933 [D loss: 0.691055, acc.: 53.32%] [G loss: 0.696050]
8/8 [==============================] - 0s 4ms/step
2934 [D loss: 0.693309, acc.: 50.20%] [G loss: 0.699544]
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2935 [D loss: 0.692978, acc.: 47.46%] [G loss: 0.699358]
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2936 [D loss: 0.689503, acc.: 55.27%] [G loss: 0.701411]
8/8 [==============================] - 0s 4ms/step
2937 [D loss: 0.691999, acc.: 51.17%] [G loss: 0.699084]
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2938 [D loss: 0.693278, acc.: 49.41%] [G loss: 0.700516]
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2939 [D loss: 0.695144, acc.: 47.66%] [G loss: 0.698997]
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2940 [D loss: 0.694486, acc.: 48.44%] [G loss: 0.692580]
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2941 [D loss: 0.695910, acc.: 42.77%] [G loss: 0.695915]
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2942 [D loss: 0.694330, acc.: 45.51%] [G loss: 0.696666]
8/8 [==============================] - 0s 4ms/step
2943 [D loss: 0.694802, acc.: 47.07%] [G loss: 0.696470]
8/8 [==============================] - 0s 4ms/step
2944 [D loss: 0.694141, acc.: 50.59%] [G loss: 0.697660]
8/8 [==============================] - 0s 4ms/step
2945 [D loss: 0.694227, acc.: 47.46%] [G loss: 0.698635]
8/8 [==============================] - 0s 4ms/step
2946 [D loss: 0.691063, acc.: 51.76%] [G loss: 0.699432]
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2947 [D loss: 0.691084, acc.: 54.88%] [G loss: 0.699910]
8/8 [==============================] - 0s 4ms/step
2948 [D loss: 0.692025, acc.: 52.93%] [G loss: 0.700544]
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2949 [D loss: 0.692773, acc.: 52.93%] [G loss: 0.701352]
8/8 [==============================] - 0s 4ms/step
2950 [D loss: 0.693178, acc.: 49.02%] [G loss: 0.698826]
1/1 [==============================] - 0s 17ms/step
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2951 [D loss: 0.692477, acc.: 48.83%] [G loss: 0.701612]
8/8 [==============================] - 0s 4ms/step
2952 [D loss: 0.691925, acc.: 53.12%] [G loss: 0.700033]
8/8 [==============================] - 0s 4ms/step
2953 [D loss: 0.690525, acc.: 55.86%] [G loss: 0.699189]
8/8 [==============================] - 0s 4ms/step
2954 [D loss: 0.690545, acc.: 53.71%] [G loss: 0.699439]
8/8 [==============================] - 0s 4ms/step
2955 [D loss: 0.689710, acc.: 55.47%] [G loss: 0.696693]
8/8 [==============================] - 0s 4ms/step
2956 [D loss: 0.691442, acc.: 52.54%] [G loss: 0.696865]
8/8 [==============================] - 0s 4ms/step
2957 [D loss: 0.689417, acc.: 55.47%] [G loss: 0.695296]
8/8 [==============================] - 0s 4ms/step
2958 [D loss: 0.693379, acc.: 48.24%] [G loss: 0.694980]
8/8 [==============================] - 0s 4ms/step
2959 [D loss: 0.692507, acc.: 50.78%] [G loss: 0.690006]
8/8 [==============================] - 0s 4ms/step
2960 [D loss: 0.691454, acc.: 54.49%] [G loss: 0.690139]
8/8 [==============================] - 0s 4ms/step
2961 [D loss: 0.692503, acc.: 50.59%] [G loss: 0.688933]
8/8 [==============================] - 0s 4ms/step
2962 [D loss: 0.694086, acc.: 48.63%] [G loss: 0.687172]
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2963 [D loss: 0.693579, acc.: 48.44%] [G loss: 0.687470]
8/8 [==============================] - 0s 4ms/step
2964 [D loss: 0.694136, acc.: 50.00%] [G loss: 0.688844]
8/8 [==============================] - 0s 4ms/step
2965 [D loss: 0.694002, acc.: 49.02%] [G loss: 0.688981]
8/8 [==============================] - 0s 4ms/step
2966 [D loss: 0.693290, acc.: 49.80%] [G loss: 0.691286]
8/8 [==============================] - 0s 4ms/step
2967 [D loss: 0.692394, acc.: 49.61%] [G loss: 0.692508]
8/8 [==============================] - 0s 4ms/step
2968 [D loss: 0.693765, acc.: 48.44%] [G loss: 0.692935]
8/8 [==============================] - 0s 4ms/step
2969 [D loss: 0.690962, acc.: 54.30%] [G loss: 0.692179]
8/8 [==============================] - 0s 4ms/step
2970 [D loss: 0.692432, acc.: 51.37%] [G loss: 0.695878]
8/8 [==============================] - 0s 4ms/step
2971 [D loss: 0.694017, acc.: 51.17%] [G loss: 0.692206]
8/8 [==============================] - 0s 4ms/step
2972 [D loss: 0.693516, acc.: 50.20%] [G loss: 0.695368]
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2973 [D loss: 0.691831, acc.: 53.91%] [G loss: 0.694457]
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2974 [D loss: 0.691912, acc.: 54.69%] [G loss: 0.692901]
8/8 [==============================] - 0s 4ms/step
2975 [D loss: 0.692694, acc.: 52.73%] [G loss: 0.688875]
8/8 [==============================] - 0s 4ms/step
2976 [D loss: 0.694598, acc.: 49.61%] [G loss: 0.694180]
8/8 [==============================] - 0s 4ms/step
2977 [D loss: 0.695083, acc.: 46.68%] [G loss: 0.694747]
8/8 [==============================] - 0s 4ms/step
2978 [D loss: 0.693150, acc.: 49.61%] [G loss: 0.697168]
8/8 [==============================] - 0s 4ms/step
2979 [D loss: 0.693120, acc.: 51.56%] [G loss: 0.695515]
8/8 [==============================] - 0s 4ms/step
2980 [D loss: 0.692737, acc.: 50.00%] [G loss: 0.699022]
8/8 [==============================] - 0s 4ms/step
2981 [D loss: 0.689292, acc.: 59.18%] [G loss: 0.701117]
8/8 [==============================] - 0s 4ms/step
2982 [D loss: 0.690479, acc.: 53.32%] [G loss: 0.698883]
8/8 [==============================] - 0s 4ms/step
2983 [D loss: 0.692521, acc.: 48.24%] [G loss: 0.701503]
8/8 [==============================] - 0s 4ms/step
2984 [D loss: 0.690555, acc.: 51.76%] [G loss: 0.699840]
8/8 [==============================] - 0s 4ms/step
2985 [D loss: 0.692721, acc.: 52.15%] [G loss: 0.696694]
8/8 [==============================] - 0s 4ms/step
2986 [D loss: 0.693370, acc.: 49.22%] [G loss: 0.695490]
8/8 [==============================] - 0s 4ms/step
2987 [D loss: 0.692907, acc.: 51.17%] [G loss: 0.696396]
8/8 [==============================] - 0s 4ms/step
2988 [D loss: 0.694137, acc.: 48.05%] [G loss: 0.693654]
8/8 [==============================] - 0s 4ms/step
2989 [D loss: 0.694658, acc.: 49.61%] [G loss: 0.695023]
8/8 [==============================] - 0s 4ms/step
2990 [D loss: 0.695195, acc.: 47.85%] [G loss: 0.696706]
8/8 [==============================] - 0s 4ms/step
2991 [D loss: 0.692092, acc.: 53.12%] [G loss: 0.698982]
8/8 [==============================] - 0s 4ms/step
2992 [D loss: 0.693403, acc.: 50.98%] [G loss: 0.697769]
8/8 [==============================] - 0s 4ms/step
2993 [D loss: 0.691377, acc.: 56.84%] [G loss: 0.697209]
8/8 [==============================] - 0s 4ms/step
2994 [D loss: 0.693754, acc.: 49.41%] [G loss: 0.699059]
8/8 [==============================] - 0s 4ms/step
2995 [D loss: 0.692199, acc.: 50.59%] [G loss: 0.699609]
8/8 [==============================] - 0s 4ms/step
2996 [D loss: 0.692527, acc.: 49.61%] [G loss: 0.698760]
8/8 [==============================] - 0s 4ms/step
2997 [D loss: 0.690477, acc.: 51.37%] [G loss: 0.697391]
8/8 [==============================] - 0s 4ms/step
2998 [D loss: 0.692954, acc.: 51.37%] [G loss: 0.698569]
8/8 [==============================] - 0s 4ms/step
2999 [D loss: 0.691331, acc.: 53.32%] [G loss: 0.698338]
8/8 [==============================] - 0s 4ms/step
3000 [D loss: 0.693909, acc.: 45.90%] [G loss: 0.697237]
1/1 [==============================] - 0s 17ms/step
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3001 [D loss: 0.693462, acc.: 49.22%] [G loss: 0.698707]
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3002 [D loss: 0.691775, acc.: 53.12%] [G loss: 0.698242]
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3003 [D loss: 0.692663, acc.: 50.59%] [G loss: 0.696881]
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3004 [D loss: 0.694061, acc.: 50.20%] [G loss: 0.696468]
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3005 [D loss: 0.694730, acc.: 47.46%] [G loss: 0.697574]
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3006 [D loss: 0.693107, acc.: 52.54%] [G loss: 0.700156]
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3007 [D loss: 0.690853, acc.: 52.15%] [G loss: 0.697887]
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3008 [D loss: 0.692727, acc.: 51.17%] [G loss: 0.701365]
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3009 [D loss: 0.691358, acc.: 54.88%] [G loss: 0.697679]
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3010 [D loss: 0.690676, acc.: 55.66%] [G loss: 0.699945]
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3011 [D loss: 0.691380, acc.: 52.34%] [G loss: 0.699227]
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3012 [D loss: 0.690580, acc.: 54.30%] [G loss: 0.701375]
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3013 [D loss: 0.691812, acc.: 53.32%] [G loss: 0.701476]
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3014 [D loss: 0.690329, acc.: 53.91%] [G loss: 0.698870]
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3015 [D loss: 0.693073, acc.: 50.98%] [G loss: 0.694582]
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3016 [D loss: 0.691542, acc.: 52.15%] [G loss: 0.695400]
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3017 [D loss: 0.691679, acc.: 53.32%] [G loss: 0.697594]
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3018 [D loss: 0.692164, acc.: 54.69%] [G loss: 0.694456]
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3019 [D loss: 0.692278, acc.: 52.93%] [G loss: 0.696248]
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3020 [D loss: 0.691728, acc.: 51.76%] [G loss: 0.695616]
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3021 [D loss: 0.694367, acc.: 48.24%] [G loss: 0.695463]
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3022 [D loss: 0.695771, acc.: 46.29%] [G loss: 0.698348]
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3023 [D loss: 0.693117, acc.: 52.34%] [G loss: 0.694713]
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3024 [D loss: 0.693746, acc.: 47.85%] [G loss: 0.697475]
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3025 [D loss: 0.692578, acc.: 50.20%] [G loss: 0.699314]
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3026 [D loss: 0.692667, acc.: 49.22%] [G loss: 0.694524]
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3027 [D loss: 0.694078, acc.: 47.07%] [G loss: 0.699626]
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3028 [D loss: 0.692475, acc.: 51.17%] [G loss: 0.699924]
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3029 [D loss: 0.693366, acc.: 50.39%] [G loss: 0.702393]
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3030 [D loss: 0.692346, acc.: 50.20%] [G loss: 0.700889]
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3031 [D loss: 0.693534, acc.: 50.98%] [G loss: 0.698068]
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3032 [D loss: 0.691472, acc.: 51.56%] [G loss: 0.698754]
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3033 [D loss: 0.692860, acc.: 49.80%] [G loss: 0.698886]
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3034 [D loss: 0.694611, acc.: 46.68%] [G loss: 0.699457]
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3035 [D loss: 0.693387, acc.: 52.15%] [G loss: 0.700038]
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3036 [D loss: 0.693200, acc.: 50.59%] [G loss: 0.694642]
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3037 [D loss: 0.693711, acc.: 49.02%] [G loss: 0.696536]
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3038 [D loss: 0.694094, acc.: 49.02%] [G loss: 0.696947]
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3039 [D loss: 0.692271, acc.: 52.15%] [G loss: 0.696294]
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3040 [D loss: 0.691412, acc.: 50.98%] [G loss: 0.697519]
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3041 [D loss: 0.691305, acc.: 54.69%] [G loss: 0.698984]
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3042 [D loss: 0.690804, acc.: 53.12%] [G loss: 0.696689]
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3043 [D loss: 0.689752, acc.: 55.27%] [G loss: 0.696786]
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3044 [D loss: 0.691260, acc.: 50.59%] [G loss: 0.697005]
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3045 [D loss: 0.689510, acc.: 54.69%] [G loss: 0.694234]
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3046 [D loss: 0.690674, acc.: 53.12%] [G loss: 0.694044]
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3047 [D loss: 0.691315, acc.: 52.34%] [G loss: 0.691822]
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3048 [D loss: 0.693393, acc.: 51.17%] [G loss: 0.689750]
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3049 [D loss: 0.691230, acc.: 49.61%] [G loss: 0.687876]
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3050 [D loss: 0.693042, acc.: 45.90%] [G loss: 0.687447]
1/1 [==============================] - 0s 16ms/step
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3051 [D loss: 0.694884, acc.: 46.88%] [G loss: 0.688781]
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3052 [D loss: 0.694481, acc.: 46.68%] [G loss: 0.688858]
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3053 [D loss: 0.694843, acc.: 45.51%] [G loss: 0.688938]
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3054 [D loss: 0.694098, acc.: 47.46%] [G loss: 0.690777]
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3055 [D loss: 0.693948, acc.: 51.37%] [G loss: 0.695640]
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3056 [D loss: 0.691672, acc.: 54.10%] [G loss: 0.696374]
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3057 [D loss: 0.691932, acc.: 58.01%] [G loss: 0.697973]
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3058 [D loss: 0.691577, acc.: 53.12%] [G loss: 0.697072]
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3059 [D loss: 0.691840, acc.: 52.34%] [G loss: 0.702067]
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3060 [D loss: 0.689457, acc.: 56.45%] [G loss: 0.700958]
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3061 [D loss: 0.691947, acc.: 50.98%] [G loss: 0.698900]
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3062 [D loss: 0.692230, acc.: 52.34%] [G loss: 0.702992]
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3063 [D loss: 0.691404, acc.: 52.54%] [G loss: 0.700283]
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3064 [D loss: 0.693985, acc.: 46.88%] [G loss: 0.699078]
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3065 [D loss: 0.695363, acc.: 47.07%] [G loss: 0.698767]
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3066 [D loss: 0.691868, acc.: 52.93%] [G loss: 0.695604]
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3067 [D loss: 0.690506, acc.: 53.32%] [G loss: 0.699045]
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3068 [D loss: 0.692015, acc.: 52.54%] [G loss: 0.696727]
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3069 [D loss: 0.693934, acc.: 48.05%] [G loss: 0.691980]
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3070 [D loss: 0.693639, acc.: 48.24%] [G loss: 0.689635]
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3071 [D loss: 0.696689, acc.: 45.31%] [G loss: 0.692748]
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3072 [D loss: 0.694778, acc.: 45.51%] [G loss: 0.693723]
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3073 [D loss: 0.693349, acc.: 51.95%] [G loss: 0.694728]
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3074 [D loss: 0.694430, acc.: 47.66%] [G loss: 0.696967]
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3075 [D loss: 0.691450, acc.: 55.27%] [G loss: 0.698897]
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3076 [D loss: 0.690248, acc.: 52.34%] [G loss: 0.696435]
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3077 [D loss: 0.691419, acc.: 53.32%] [G loss: 0.699531]
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3078 [D loss: 0.692437, acc.: 51.76%] [G loss: 0.698032]
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3079 [D loss: 0.691451, acc.: 53.52%] [G loss: 0.698063]
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3080 [D loss: 0.689097, acc.: 57.23%] [G loss: 0.697100]
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3081 [D loss: 0.692387, acc.: 54.10%] [G loss: 0.698449]
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3082 [D loss: 0.691890, acc.: 50.39%] [G loss: 0.694929]
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3083 [D loss: 0.693793, acc.: 48.24%] [G loss: 0.695953]
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3084 [D loss: 0.693743, acc.: 47.27%] [G loss: 0.694736]
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3085 [D loss: 0.693712, acc.: 50.39%] [G loss: 0.698615]
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3086 [D loss: 0.692142, acc.: 50.00%] [G loss: 0.699220]
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3087 [D loss: 0.690633, acc.: 53.91%] [G loss: 0.699606]
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3088 [D loss: 0.691830, acc.: 51.56%] [G loss: 0.701865]
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3089 [D loss: 0.690041, acc.: 54.49%] [G loss: 0.702519]
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3090 [D loss: 0.692797, acc.: 51.17%] [G loss: 0.698108]
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3091 [D loss: 0.694201, acc.: 46.68%] [G loss: 0.696880]
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3092 [D loss: 0.693548, acc.: 49.80%] [G loss: 0.693054]
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3093 [D loss: 0.693797, acc.: 50.98%] [G loss: 0.691714]
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3094 [D loss: 0.693018, acc.: 49.22%] [G loss: 0.693171]
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3095 [D loss: 0.695589, acc.: 47.85%] [G loss: 0.691346]
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3096 [D loss: 0.694214, acc.: 48.05%] [G loss: 0.690833]
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3097 [D loss: 0.694140, acc.: 49.22%] [G loss: 0.693642]
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3098 [D loss: 0.693165, acc.: 51.56%] [G loss: 0.689818]
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3099 [D loss: 0.692114, acc.: 52.93%] [G loss: 0.692411]
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3100 [D loss: 0.693888, acc.: 50.20%] [G loss: 0.693189]
1/1 [==============================] - 0s 16ms/step
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3101 [D loss: 0.693712, acc.: 51.37%] [G loss: 0.694215]
8/8 [==============================] - 0s 4ms/step
3102 [D loss: 0.691456, acc.: 53.32%] [G loss: 0.699682]
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3103 [D loss: 0.692950, acc.: 52.15%] [G loss: 0.698311]
8/8 [==============================] - 0s 4ms/step
3104 [D loss: 0.689511, acc.: 57.62%] [G loss: 0.698772]
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3105 [D loss: 0.692805, acc.: 52.34%] [G loss: 0.698572]
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3106 [D loss: 0.690156, acc.: 55.27%] [G loss: 0.702935]
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3107 [D loss: 0.689043, acc.: 59.18%] [G loss: 0.703214]
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3108 [D loss: 0.689373, acc.: 55.47%] [G loss: 0.697851]
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3109 [D loss: 0.689718, acc.: 57.03%] [G loss: 0.701978]
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3110 [D loss: 0.689479, acc.: 54.10%] [G loss: 0.700476]
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3111 [D loss: 0.689234, acc.: 56.84%] [G loss: 0.701707]
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3112 [D loss: 0.691049, acc.: 51.17%] [G loss: 0.699160]
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3113 [D loss: 0.693603, acc.: 52.54%] [G loss: 0.695423]
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3114 [D loss: 0.695686, acc.: 47.46%] [G loss: 0.694616]
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3115 [D loss: 0.693664, acc.: 51.56%] [G loss: 0.694677]
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3116 [D loss: 0.695070, acc.: 49.02%] [G loss: 0.692178]
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3117 [D loss: 0.696174, acc.: 48.44%] [G loss: 0.691285]
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3118 [D loss: 0.695463, acc.: 47.46%] [G loss: 0.695838]
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3119 [D loss: 0.695498, acc.: 48.63%] [G loss: 0.693445]
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3120 [D loss: 0.695690, acc.: 44.73%] [G loss: 0.695124]
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3121 [D loss: 0.696182, acc.: 48.05%] [G loss: 0.695223]
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3122 [D loss: 0.693178, acc.: 50.39%] [G loss: 0.695045]
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3123 [D loss: 0.691290, acc.: 54.49%] [G loss: 0.693154]
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3124 [D loss: 0.692454, acc.: 50.59%] [G loss: 0.695976]
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3125 [D loss: 0.690824, acc.: 54.30%] [G loss: 0.699563]
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3126 [D loss: 0.690630, acc.: 56.45%] [G loss: 0.697154]
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3127 [D loss: 0.691179, acc.: 54.49%] [G loss: 0.697928]
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3128 [D loss: 0.688553, acc.: 57.62%] [G loss: 0.702700]
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3129 [D loss: 0.688149, acc.: 56.45%] [G loss: 0.698617]
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3130 [D loss: 0.689556, acc.: 56.84%] [G loss: 0.699906]
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3131 [D loss: 0.690214, acc.: 54.49%] [G loss: 0.697163]
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3132 [D loss: 0.692637, acc.: 51.76%] [G loss: 0.696534]
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3133 [D loss: 0.693124, acc.: 51.76%] [G loss: 0.701254]
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3134 [D loss: 0.691799, acc.: 51.76%] [G loss: 0.695971]
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3135 [D loss: 0.693348, acc.: 49.80%] [G loss: 0.692899]
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3136 [D loss: 0.692747, acc.: 49.22%] [G loss: 0.697293]
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3137 [D loss: 0.690756, acc.: 53.71%] [G loss: 0.694142]
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3138 [D loss: 0.691188, acc.: 53.71%] [G loss: 0.696604]
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3139 [D loss: 0.691886, acc.: 51.76%] [G loss: 0.694006]
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3140 [D loss: 0.691005, acc.: 53.12%] [G loss: 0.693512]
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3141 [D loss: 0.692602, acc.: 50.39%] [G loss: 0.695798]
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3142 [D loss: 0.695610, acc.: 49.02%] [G loss: 0.694124]
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3143 [D loss: 0.692839, acc.: 48.05%] [G loss: 0.694841]
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3144 [D loss: 0.693392, acc.: 49.80%] [G loss: 0.694729]
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3145 [D loss: 0.693796, acc.: 49.02%] [G loss: 0.693059]
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3146 [D loss: 0.695111, acc.: 46.09%] [G loss: 0.691363]
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3147 [D loss: 0.693142, acc.: 47.27%] [G loss: 0.694483]
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3148 [D loss: 0.695014, acc.: 49.41%] [G loss: 0.693328]
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3149 [D loss: 0.694421, acc.: 47.46%] [G loss: 0.693417]
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3150 [D loss: 0.695025, acc.: 48.05%] [G loss: 0.693771]
1/1 [==============================] - 0s 18ms/step
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3151 [D loss: 0.695172, acc.: 48.83%] [G loss: 0.697921]
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3152 [D loss: 0.690797, acc.: 54.88%] [G loss: 0.695414]
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3153 [D loss: 0.690240, acc.: 56.25%] [G loss: 0.697987]
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3154 [D loss: 0.688791, acc.: 57.42%] [G loss: 0.702188]
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3155 [D loss: 0.690954, acc.: 56.05%] [G loss: 0.700726]
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3156 [D loss: 0.691578, acc.: 53.52%] [G loss: 0.698278]
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3157 [D loss: 0.691315, acc.: 52.34%] [G loss: 0.697430]
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3158 [D loss: 0.691833, acc.: 48.83%] [G loss: 0.700238]
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3159 [D loss: 0.691802, acc.: 52.93%] [G loss: 0.698173]
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3160 [D loss: 0.689998, acc.: 56.25%] [G loss: 0.700117]
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3161 [D loss: 0.693163, acc.: 51.17%] [G loss: 0.697163]
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3162 [D loss: 0.691661, acc.: 52.73%] [G loss: 0.699057]
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3163 [D loss: 0.693297, acc.: 51.17%] [G loss: 0.694466]
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3164 [D loss: 0.692593, acc.: 51.17%] [G loss: 0.693518]
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3165 [D loss: 0.694148, acc.: 52.93%] [G loss: 0.694775]
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3166 [D loss: 0.693002, acc.: 52.15%] [G loss: 0.693814]
8/8 [==============================] - 0s 4ms/step
3167 [D loss: 0.692607, acc.: 51.95%] [G loss: 0.694489]
8/8 [==============================] - 0s 4ms/step
3168 [D loss: 0.693272, acc.: 49.02%] [G loss: 0.694667]
8/8 [==============================] - 0s 4ms/step
3169 [D loss: 0.692590, acc.: 50.39%] [G loss: 0.691783]
8/8 [==============================] - 0s 4ms/step
3170 [D loss: 0.693092, acc.: 49.22%] [G loss: 0.695309]
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3171 [D loss: 0.694214, acc.: 48.63%] [G loss: 0.693533]
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3172 [D loss: 0.691143, acc.: 51.95%] [G loss: 0.694615]
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3173 [D loss: 0.692366, acc.: 50.78%] [G loss: 0.695989]
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3174 [D loss: 0.690892, acc.: 53.32%] [G loss: 0.694919]
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3175 [D loss: 0.689940, acc.: 57.42%] [G loss: 0.698213]
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3176 [D loss: 0.691216, acc.: 54.69%] [G loss: 0.696107]
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3177 [D loss: 0.690985, acc.: 55.86%] [G loss: 0.698879]
8/8 [==============================] - 0s 4ms/step
3178 [D loss: 0.689772, acc.: 56.25%] [G loss: 0.698343]
8/8 [==============================] - 0s 4ms/step
3179 [D loss: 0.692060, acc.: 54.30%] [G loss: 0.694009]
8/8 [==============================] - 0s 4ms/step
3180 [D loss: 0.693697, acc.: 47.07%] [G loss: 0.696570]
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3181 [D loss: 0.694425, acc.: 49.02%] [G loss: 0.698739]
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3182 [D loss: 0.691909, acc.: 52.15%] [G loss: 0.697709]
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3183 [D loss: 0.690311, acc.: 56.64%] [G loss: 0.698314]
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3184 [D loss: 0.694035, acc.: 46.48%] [G loss: 0.695631]
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3185 [D loss: 0.692154, acc.: 53.52%] [G loss: 0.699445]
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3186 [D loss: 0.691833, acc.: 52.73%] [G loss: 0.702365]
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3187 [D loss: 0.690409, acc.: 53.91%] [G loss: 0.699706]
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3188 [D loss: 0.690116, acc.: 56.64%] [G loss: 0.700070]
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3189 [D loss: 0.690797, acc.: 54.10%] [G loss: 0.699015]
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3190 [D loss: 0.692108, acc.: 53.71%] [G loss: 0.698393]
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3191 [D loss: 0.690089, acc.: 53.32%] [G loss: 0.699696]
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3192 [D loss: 0.690466, acc.: 54.10%] [G loss: 0.701909]
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3193 [D loss: 0.691460, acc.: 55.27%] [G loss: 0.700771]
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3194 [D loss: 0.688927, acc.: 55.27%] [G loss: 0.700695]
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3195 [D loss: 0.694465, acc.: 47.46%] [G loss: 0.697590]
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3196 [D loss: 0.692649, acc.: 53.12%] [G loss: 0.698070]
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3197 [D loss: 0.692099, acc.: 50.00%] [G loss: 0.699266]
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3198 [D loss: 0.691668, acc.: 51.76%] [G loss: 0.701942]
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3199 [D loss: 0.688359, acc.: 56.05%] [G loss: 0.701412]
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3200 [D loss: 0.688403, acc.: 56.84%] [G loss: 0.704062]
1/1 [==============================] - 0s 17ms/step
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3201 [D loss: 0.691905, acc.: 50.59%] [G loss: 0.709448]
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3202 [D loss: 0.689680, acc.: 52.34%] [G loss: 0.701196]
8/8 [==============================] - 0s 4ms/step
3203 [D loss: 0.689825, acc.: 54.69%] [G loss: 0.700588]
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3204 [D loss: 0.690637, acc.: 53.52%] [G loss: 0.702384]
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3205 [D loss: 0.694542, acc.: 46.29%] [G loss: 0.692449]
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3206 [D loss: 0.694340, acc.: 46.88%] [G loss: 0.693117]
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3207 [D loss: 0.694080, acc.: 51.76%] [G loss: 0.690987]
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3208 [D loss: 0.694416, acc.: 49.80%] [G loss: 0.692511]
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3209 [D loss: 0.694814, acc.: 48.24%] [G loss: 0.692444]
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3210 [D loss: 0.692619, acc.: 49.61%] [G loss: 0.695177]
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3211 [D loss: 0.692783, acc.: 51.95%] [G loss: 0.696128]
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3212 [D loss: 0.695255, acc.: 47.85%] [G loss: 0.692716]
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3213 [D loss: 0.694977, acc.: 47.27%] [G loss: 0.694486]
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3214 [D loss: 0.693879, acc.: 50.59%] [G loss: 0.693431]
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3215 [D loss: 0.692141, acc.: 47.07%] [G loss: 0.692488]
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3216 [D loss: 0.694344, acc.: 49.80%] [G loss: 0.692902]
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3217 [D loss: 0.692920, acc.: 49.61%] [G loss: 0.693501]
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3218 [D loss: 0.692226, acc.: 50.20%] [G loss: 0.698623]
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3219 [D loss: 0.693140, acc.: 50.98%] [G loss: 0.695937]
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3220 [D loss: 0.691547, acc.: 51.17%] [G loss: 0.699681]
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3221 [D loss: 0.691357, acc.: 52.15%] [G loss: 0.702139]
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3222 [D loss: 0.688957, acc.: 58.40%] [G loss: 0.701681]
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3223 [D loss: 0.689533, acc.: 56.45%] [G loss: 0.700594]
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3224 [D loss: 0.689045, acc.: 58.20%] [G loss: 0.700147]
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3225 [D loss: 0.692025, acc.: 54.10%] [G loss: 0.702706]
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3226 [D loss: 0.693402, acc.: 50.20%] [G loss: 0.699665]
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3227 [D loss: 0.694686, acc.: 48.44%] [G loss: 0.697443]
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3228 [D loss: 0.693407, acc.: 50.00%] [G loss: 0.698870]
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3229 [D loss: 0.691650, acc.: 53.71%] [G loss: 0.700080]
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3230 [D loss: 0.692115, acc.: 53.32%] [G loss: 0.695543]
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3231 [D loss: 0.692488, acc.: 53.12%] [G loss: 0.700813]
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3232 [D loss: 0.691871, acc.: 51.17%] [G loss: 0.693778]
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3233 [D loss: 0.696061, acc.: 46.09%] [G loss: 0.692692]
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3234 [D loss: 0.693137, acc.: 49.80%] [G loss: 0.696920]
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3235 [D loss: 0.691437, acc.: 53.91%] [G loss: 0.694876]
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3236 [D loss: 0.692022, acc.: 50.39%] [G loss: 0.693425]
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3237 [D loss: 0.691773, acc.: 53.12%] [G loss: 0.693916]
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3238 [D loss: 0.692512, acc.: 50.98%] [G loss: 0.694426]
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3239 [D loss: 0.694367, acc.: 48.05%] [G loss: 0.693766]
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3240 [D loss: 0.692484, acc.: 51.95%] [G loss: 0.691095]
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3241 [D loss: 0.695706, acc.: 47.27%] [G loss: 0.689844]
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3242 [D loss: 0.696931, acc.: 45.51%] [G loss: 0.688920]
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3243 [D loss: 0.696220, acc.: 48.83%] [G loss: 0.690816]
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3244 [D loss: 0.693458, acc.: 51.17%] [G loss: 0.695000]
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3245 [D loss: 0.693132, acc.: 50.78%] [G loss: 0.694631]
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3246 [D loss: 0.693143, acc.: 51.17%] [G loss: 0.694939]
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3247 [D loss: 0.692239, acc.: 49.22%] [G loss: 0.694947]
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3248 [D loss: 0.692664, acc.: 50.98%] [G loss: 0.697966]
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3249 [D loss: 0.690590, acc.: 54.69%] [G loss: 0.697392]
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3250 [D loss: 0.688719, acc.: 56.84%] [G loss: 0.699664]
1/1 [==============================] - 0s 17ms/step
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3251 [D loss: 0.690314, acc.: 54.88%] [G loss: 0.698488]
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3252 [D loss: 0.690010, acc.: 57.23%] [G loss: 0.698991]
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3253 [D loss: 0.689321, acc.: 58.59%] [G loss: 0.699565]
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3254 [D loss: 0.690310, acc.: 56.45%] [G loss: 0.699138]
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3255 [D loss: 0.692645, acc.: 53.52%] [G loss: 0.698840]
8/8 [==============================] - 0s 4ms/step
3256 [D loss: 0.690000, acc.: 55.47%] [G loss: 0.698821]
8/8 [==============================] - 0s 4ms/step
3257 [D loss: 0.690691, acc.: 52.93%] [G loss: 0.703403]
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3258 [D loss: 0.688514, acc.: 57.03%] [G loss: 0.703459]
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3259 [D loss: 0.686273, acc.: 62.50%] [G loss: 0.700467]
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3260 [D loss: 0.690347, acc.: 54.30%] [G loss: 0.704620]
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3261 [D loss: 0.691086, acc.: 53.32%] [G loss: 0.700545]
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3262 [D loss: 0.692340, acc.: 52.54%] [G loss: 0.701144]
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3263 [D loss: 0.693261, acc.: 50.59%] [G loss: 0.697547]
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3264 [D loss: 0.693820, acc.: 48.63%] [G loss: 0.692111]
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3265 [D loss: 0.692519, acc.: 49.02%] [G loss: 0.693440]
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3266 [D loss: 0.691860, acc.: 50.59%] [G loss: 0.695127]
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3267 [D loss: 0.693459, acc.: 50.78%] [G loss: 0.697042]
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3268 [D loss: 0.693972, acc.: 48.24%] [G loss: 0.692152]
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3269 [D loss: 0.692325, acc.: 54.30%] [G loss: 0.694530]
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3270 [D loss: 0.692606, acc.: 51.17%] [G loss: 0.691772]
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3271 [D loss: 0.696073, acc.: 48.05%] [G loss: 0.697356]
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3272 [D loss: 0.695851, acc.: 43.75%] [G loss: 0.693792]
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3273 [D loss: 0.692516, acc.: 52.54%] [G loss: 0.695954]
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3274 [D loss: 0.692005, acc.: 51.17%] [G loss: 0.697086]
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3275 [D loss: 0.691429, acc.: 52.34%] [G loss: 0.699099]
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3276 [D loss: 0.690560, acc.: 51.95%] [G loss: 0.698471]
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3277 [D loss: 0.692140, acc.: 52.15%] [G loss: 0.700684]
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3278 [D loss: 0.690505, acc.: 54.30%] [G loss: 0.699112]
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3279 [D loss: 0.690725, acc.: 53.91%] [G loss: 0.699924]
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3280 [D loss: 0.690530, acc.: 55.27%] [G loss: 0.696762]
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3281 [D loss: 0.693090, acc.: 52.34%] [G loss: 0.697111]
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3282 [D loss: 0.690351, acc.: 56.05%] [G loss: 0.696961]
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3283 [D loss: 0.690758, acc.: 54.49%] [G loss: 0.696334]
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3284 [D loss: 0.690383, acc.: 53.32%] [G loss: 0.697322]
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3285 [D loss: 0.691697, acc.: 54.10%] [G loss: 0.696365]
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3286 [D loss: 0.693294, acc.: 52.34%] [G loss: 0.696948]
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3287 [D loss: 0.692579, acc.: 52.54%] [G loss: 0.694955]
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3288 [D loss: 0.692502, acc.: 47.66%] [G loss: 0.695249]
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3289 [D loss: 0.694727, acc.: 47.46%] [G loss: 0.695940]
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3290 [D loss: 0.694886, acc.: 46.29%] [G loss: 0.693499]
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3291 [D loss: 0.691597, acc.: 53.12%] [G loss: 0.692597]
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3292 [D loss: 0.694556, acc.: 47.07%] [G loss: 0.692100]
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3293 [D loss: 0.694018, acc.: 47.66%] [G loss: 0.690490]
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3294 [D loss: 0.694084, acc.: 50.00%] [G loss: 0.695054]
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3295 [D loss: 0.691889, acc.: 53.52%] [G loss: 0.691982]
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3296 [D loss: 0.693491, acc.: 49.22%] [G loss: 0.693072]
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3297 [D loss: 0.693619, acc.: 51.76%] [G loss: 0.696165]
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3298 [D loss: 0.690294, acc.: 55.08%] [G loss: 0.694819]
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3299 [D loss: 0.692047, acc.: 52.54%] [G loss: 0.698095]
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3300 [D loss: 0.691279, acc.: 54.10%] [G loss: 0.694963]
1/1 [==============================] - 0s 16ms/step
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3301 [D loss: 0.691876, acc.: 53.71%] [G loss: 0.695009]
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3302 [D loss: 0.692204, acc.: 52.73%] [G loss: 0.697801]
8/8 [==============================] - 0s 4ms/step
3303 [D loss: 0.689832, acc.: 58.59%] [G loss: 0.698422]
8/8 [==============================] - 0s 4ms/step
3304 [D loss: 0.690266, acc.: 56.45%] [G loss: 0.701018]
8/8 [==============================] - 0s 4ms/step
3305 [D loss: 0.689073, acc.: 57.03%] [G loss: 0.699815]
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3306 [D loss: 0.688932, acc.: 57.42%] [G loss: 0.701796]
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3307 [D loss: 0.689160, acc.: 57.62%] [G loss: 0.698920]
8/8 [==============================] - 0s 4ms/step
3308 [D loss: 0.691651, acc.: 48.83%] [G loss: 0.696142]
8/8 [==============================] - 0s 4ms/step
3309 [D loss: 0.691494, acc.: 53.12%] [G loss: 0.696725]
8/8 [==============================] - 0s 4ms/step
3310 [D loss: 0.693062, acc.: 50.78%] [G loss: 0.696753]
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3311 [D loss: 0.691896, acc.: 52.15%] [G loss: 0.697963]
8/8 [==============================] - 0s 4ms/step
3312 [D loss: 0.691003, acc.: 50.78%] [G loss: 0.700365]
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3313 [D loss: 0.692697, acc.: 52.73%] [G loss: 0.695726]
8/8 [==============================] - 0s 4ms/step
3314 [D loss: 0.691808, acc.: 52.54%] [G loss: 0.693079]
8/8 [==============================] - 0s 4ms/step
3315 [D loss: 0.692069, acc.: 51.17%] [G loss: 0.699207]
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3316 [D loss: 0.692365, acc.: 51.17%] [G loss: 0.697880]
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3317 [D loss: 0.693858, acc.: 48.83%] [G loss: 0.698916]
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3318 [D loss: 0.693116, acc.: 50.98%] [G loss: 0.697139]
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3319 [D loss: 0.693004, acc.: 49.80%] [G loss: 0.695202]
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3320 [D loss: 0.695781, acc.: 48.05%] [G loss: 0.694770]
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3321 [D loss: 0.693723, acc.: 48.44%] [G loss: 0.695044]
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3322 [D loss: 0.694720, acc.: 48.63%] [G loss: 0.696371]
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3323 [D loss: 0.691933, acc.: 54.30%] [G loss: 0.699816]
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3324 [D loss: 0.690117, acc.: 56.64%] [G loss: 0.703192]
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3325 [D loss: 0.688956, acc.: 56.45%] [G loss: 0.703014]
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3326 [D loss: 0.690233, acc.: 55.08%] [G loss: 0.703693]
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3327 [D loss: 0.689713, acc.: 58.40%] [G loss: 0.705789]
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3328 [D loss: 0.692604, acc.: 54.30%] [G loss: 0.703283]
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3329 [D loss: 0.691714, acc.: 50.00%] [G loss: 0.701951]
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3330 [D loss: 0.691827, acc.: 52.73%] [G loss: 0.700200]
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3331 [D loss: 0.689543, acc.: 53.91%] [G loss: 0.701007]
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3332 [D loss: 0.687631, acc.: 57.03%] [G loss: 0.699189]
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3333 [D loss: 0.687189, acc.: 59.38%] [G loss: 0.705898]
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3334 [D loss: 0.689982, acc.: 53.12%] [G loss: 0.702807]
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3335 [D loss: 0.689919, acc.: 51.76%] [G loss: 0.697890]
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3336 [D loss: 0.691677, acc.: 50.00%] [G loss: 0.694724]
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3337 [D loss: 0.696726, acc.: 45.90%] [G loss: 0.690911]
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3338 [D loss: 0.691675, acc.: 50.98%] [G loss: 0.696087]
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3339 [D loss: 0.693262, acc.: 49.80%] [G loss: 0.691324]
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3340 [D loss: 0.689521, acc.: 53.12%] [G loss: 0.689413]
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3341 [D loss: 0.691872, acc.: 49.80%] [G loss: 0.691569]
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3342 [D loss: 0.692484, acc.: 49.41%] [G loss: 0.691434]
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3343 [D loss: 0.695973, acc.: 46.68%] [G loss: 0.689459]
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3344 [D loss: 0.695105, acc.: 49.80%] [G loss: 0.690251]
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3345 [D loss: 0.695262, acc.: 45.70%] [G loss: 0.691928]
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3346 [D loss: 0.694112, acc.: 48.05%] [G loss: 0.691200]
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3347 [D loss: 0.691800, acc.: 52.93%] [G loss: 0.690103]
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3348 [D loss: 0.693627, acc.: 50.39%] [G loss: 0.694908]
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3349 [D loss: 0.691665, acc.: 54.49%] [G loss: 0.695735]
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3350 [D loss: 0.690447, acc.: 52.73%] [G loss: 0.694765]
1/1 [==============================] - 0s 16ms/step
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3351 [D loss: 0.691207, acc.: 52.73%] [G loss: 0.696221]
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3352 [D loss: 0.691205, acc.: 51.76%] [G loss: 0.697854]
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3353 [D loss: 0.689546, acc.: 57.81%] [G loss: 0.698239]
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3354 [D loss: 0.688223, acc.: 59.18%] [G loss: 0.698910]
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3355 [D loss: 0.691982, acc.: 53.91%] [G loss: 0.700703]
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3356 [D loss: 0.688429, acc.: 57.42%] [G loss: 0.700039]
8/8 [==============================] - 0s 4ms/step
3357 [D loss: 0.692411, acc.: 51.76%] [G loss: 0.695380]
8/8 [==============================] - 0s 4ms/step
3358 [D loss: 0.693351, acc.: 50.98%] [G loss: 0.701265]
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3359 [D loss: 0.690130, acc.: 52.73%] [G loss: 0.703273]
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3360 [D loss: 0.693792, acc.: 48.63%] [G loss: 0.698738]
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3361 [D loss: 0.692852, acc.: 50.39%] [G loss: 0.704187]
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3362 [D loss: 0.693801, acc.: 47.07%] [G loss: 0.703257]
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3363 [D loss: 0.691778, acc.: 52.54%] [G loss: 0.701731]
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3364 [D loss: 0.694184, acc.: 48.05%] [G loss: 0.699843]
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3365 [D loss: 0.692182, acc.: 52.34%] [G loss: 0.699657]
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3366 [D loss: 0.691653, acc.: 52.93%] [G loss: 0.700585]
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3367 [D loss: 0.690718, acc.: 52.34%] [G loss: 0.699064]
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3368 [D loss: 0.691599, acc.: 54.49%] [G loss: 0.700806]
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3369 [D loss: 0.691264, acc.: 52.54%] [G loss: 0.698183]
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3370 [D loss: 0.692868, acc.: 51.95%] [G loss: 0.699774]
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3371 [D loss: 0.693209, acc.: 47.85%] [G loss: 0.695304]
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3372 [D loss: 0.693680, acc.: 51.95%] [G loss: 0.694087]
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3373 [D loss: 0.693855, acc.: 52.34%] [G loss: 0.696415]
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3374 [D loss: 0.691234, acc.: 53.52%] [G loss: 0.701182]
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3375 [D loss: 0.692401, acc.: 51.17%] [G loss: 0.696021]
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3376 [D loss: 0.691888, acc.: 55.08%] [G loss: 0.699508]
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3377 [D loss: 0.687971, acc.: 56.64%] [G loss: 0.699101]
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3378 [D loss: 0.691901, acc.: 51.56%] [G loss: 0.698222]
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3379 [D loss: 0.695000, acc.: 49.22%] [G loss: 0.697574]
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3380 [D loss: 0.690166, acc.: 56.05%] [G loss: 0.700779]
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3381 [D loss: 0.691283, acc.: 56.05%] [G loss: 0.698249]
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3382 [D loss: 0.690154, acc.: 54.49%] [G loss: 0.697289]
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3383 [D loss: 0.689583, acc.: 54.10%] [G loss: 0.700281]
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3384 [D loss: 0.691986, acc.: 52.15%] [G loss: 0.698715]
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3385 [D loss: 0.691625, acc.: 52.73%] [G loss: 0.699030]
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3386 [D loss: 0.694192, acc.: 49.41%] [G loss: 0.697004]
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3387 [D loss: 0.693142, acc.: 51.37%] [G loss: 0.696110]
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3388 [D loss: 0.692607, acc.: 50.78%] [G loss: 0.698045]
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3389 [D loss: 0.695652, acc.: 46.48%] [G loss: 0.696717]
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3390 [D loss: 0.691792, acc.: 54.30%] [G loss: 0.702774]
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3391 [D loss: 0.690264, acc.: 53.52%] [G loss: 0.698961]
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3392 [D loss: 0.690396, acc.: 54.49%] [G loss: 0.705316]
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3393 [D loss: 0.690860, acc.: 53.32%] [G loss: 0.699642]
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3394 [D loss: 0.690007, acc.: 54.69%] [G loss: 0.701308]
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3395 [D loss: 0.691815, acc.: 52.15%] [G loss: 0.701330]
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3396 [D loss: 0.690990, acc.: 51.17%] [G loss: 0.699160]
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3397 [D loss: 0.693342, acc.: 50.39%] [G loss: 0.698394]
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3398 [D loss: 0.689722, acc.: 55.86%] [G loss: 0.695443]
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3399 [D loss: 0.693418, acc.: 50.39%] [G loss: 0.698342]
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3400 [D loss: 0.691016, acc.: 53.32%] [G loss: 0.695268]
1/1 [==============================] - 0s 19ms/step
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3401 [D loss: 0.692602, acc.: 49.80%] [G loss: 0.695623]
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3402 [D loss: 0.691310, acc.: 54.88%] [G loss: 0.698758]
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3403 [D loss: 0.691986, acc.: 53.71%] [G loss: 0.699255]
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3404 [D loss: 0.692422, acc.: 51.17%] [G loss: 0.695112]
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3405 [D loss: 0.694084, acc.: 51.56%] [G loss: 0.697798]
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3406 [D loss: 0.692985, acc.: 50.20%] [G loss: 0.695578]
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3407 [D loss: 0.694705, acc.: 47.07%] [G loss: 0.694289]
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3408 [D loss: 0.693275, acc.: 48.83%] [G loss: 0.694848]
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3409 [D loss: 0.693856, acc.: 50.00%] [G loss: 0.694976]
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3410 [D loss: 0.692148, acc.: 52.15%] [G loss: 0.693806]
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3411 [D loss: 0.694308, acc.: 47.07%] [G loss: 0.698402]
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3412 [D loss: 0.692627, acc.: 50.00%] [G loss: 0.695345]
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3413 [D loss: 0.692825, acc.: 50.78%] [G loss: 0.702389]
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3414 [D loss: 0.691323, acc.: 52.54%] [G loss: 0.698843]
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3415 [D loss: 0.689411, acc.: 55.86%] [G loss: 0.702598]
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3416 [D loss: 0.688765, acc.: 58.20%] [G loss: 0.702186]
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3417 [D loss: 0.687138, acc.: 59.57%] [G loss: 0.706076]
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3418 [D loss: 0.687336, acc.: 58.79%] [G loss: 0.703617]
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3419 [D loss: 0.688605, acc.: 57.42%] [G loss: 0.701731]
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3420 [D loss: 0.689357, acc.: 55.27%] [G loss: 0.699388]
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3421 [D loss: 0.692115, acc.: 50.39%] [G loss: 0.698403]
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3422 [D loss: 0.688002, acc.: 57.23%] [G loss: 0.699451]
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3423 [D loss: 0.690948, acc.: 53.71%] [G loss: 0.698349]
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3424 [D loss: 0.692092, acc.: 51.56%] [G loss: 0.691571]
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3425 [D loss: 0.697397, acc.: 43.55%] [G loss: 0.688813]
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3426 [D loss: 0.698516, acc.: 44.53%] [G loss: 0.693222]
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3427 [D loss: 0.694278, acc.: 52.54%] [G loss: 0.694352]
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3428 [D loss: 0.694012, acc.: 50.59%] [G loss: 0.695994]
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3429 [D loss: 0.688820, acc.: 58.40%] [G loss: 0.698514]
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3430 [D loss: 0.690137, acc.: 57.23%] [G loss: 0.702148]
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3431 [D loss: 0.689295, acc.: 54.10%] [G loss: 0.698948]
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3432 [D loss: 0.689471, acc.: 52.93%] [G loss: 0.696406]
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3433 [D loss: 0.693766, acc.: 47.07%] [G loss: 0.695512]
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3434 [D loss: 0.694567, acc.: 48.63%] [G loss: 0.693053]
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3435 [D loss: 0.691927, acc.: 52.34%] [G loss: 0.699373]
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3436 [D loss: 0.691318, acc.: 50.39%] [G loss: 0.696993]
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3437 [D loss: 0.689224, acc.: 57.62%] [G loss: 0.700665]
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3438 [D loss: 0.694486, acc.: 49.22%] [G loss: 0.700872]
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3439 [D loss: 0.692560, acc.: 52.34%] [G loss: 0.696022]
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3440 [D loss: 0.692038, acc.: 49.02%] [G loss: 0.693089]
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3441 [D loss: 0.693891, acc.: 50.39%] [G loss: 0.698870]
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3442 [D loss: 0.690463, acc.: 54.10%] [G loss: 0.695227]
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3443 [D loss: 0.690648, acc.: 53.12%] [G loss: 0.698646]
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3444 [D loss: 0.688218, acc.: 57.03%] [G loss: 0.708299]
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3445 [D loss: 0.688821, acc.: 57.03%] [G loss: 0.707933]
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3446 [D loss: 0.689313, acc.: 56.64%] [G loss: 0.703691]
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3447 [D loss: 0.692656, acc.: 49.22%] [G loss: 0.698740]
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3448 [D loss: 0.694044, acc.: 47.66%] [G loss: 0.697733]
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3449 [D loss: 0.695462, acc.: 48.24%] [G loss: 0.697711]
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3450 [D loss: 0.691337, acc.: 50.78%] [G loss: 0.700260]
1/1 [==============================] - 0s 17ms/step
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3451 [D loss: 0.692092, acc.: 50.39%] [G loss: 0.699124]
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3452 [D loss: 0.689783, acc.: 53.12%] [G loss: 0.702722]
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3453 [D loss: 0.692804, acc.: 52.73%] [G loss: 0.697017]
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3454 [D loss: 0.690134, acc.: 52.93%] [G loss: 0.699633]
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3455 [D loss: 0.692402, acc.: 53.12%] [G loss: 0.703421]
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3456 [D loss: 0.694478, acc.: 45.90%] [G loss: 0.701512]
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3457 [D loss: 0.693093, acc.: 50.39%] [G loss: 0.704836]
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3458 [D loss: 0.690583, acc.: 55.27%] [G loss: 0.704954]
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3459 [D loss: 0.688119, acc.: 56.25%] [G loss: 0.705490]
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3460 [D loss: 0.686902, acc.: 58.01%] [G loss: 0.706431]
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3461 [D loss: 0.687270, acc.: 57.03%] [G loss: 0.707429]
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3462 [D loss: 0.688866, acc.: 55.27%] [G loss: 0.709417]
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3463 [D loss: 0.691503, acc.: 52.73%] [G loss: 0.703556]
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3464 [D loss: 0.692911, acc.: 50.78%] [G loss: 0.698595]
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3465 [D loss: 0.689763, acc.: 53.32%] [G loss: 0.699782]
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3466 [D loss: 0.693356, acc.: 50.59%] [G loss: 0.697258]
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3467 [D loss: 0.693956, acc.: 50.98%] [G loss: 0.695780]
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3468 [D loss: 0.692926, acc.: 50.78%] [G loss: 0.693158]
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3469 [D loss: 0.693347, acc.: 52.34%] [G loss: 0.688828]
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3470 [D loss: 0.694468, acc.: 48.63%] [G loss: 0.690548]
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3471 [D loss: 0.692104, acc.: 50.20%] [G loss: 0.691031]
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3472 [D loss: 0.692082, acc.: 51.95%] [G loss: 0.696865]
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3473 [D loss: 0.691152, acc.: 54.49%] [G loss: 0.693647]
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3474 [D loss: 0.689490, acc.: 58.01%] [G loss: 0.696528]
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3475 [D loss: 0.690942, acc.: 55.86%] [G loss: 0.698492]
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3476 [D loss: 0.689551, acc.: 52.73%] [G loss: 0.695423]
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3477 [D loss: 0.691202, acc.: 50.00%] [G loss: 0.697905]
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3478 [D loss: 0.691641, acc.: 52.15%] [G loss: 0.695077]
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3479 [D loss: 0.688179, acc.: 58.20%] [G loss: 0.693006]
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3480 [D loss: 0.688087, acc.: 56.05%] [G loss: 0.699299]
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3481 [D loss: 0.686255, acc.: 59.18%] [G loss: 0.699802]
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3482 [D loss: 0.689391, acc.: 55.66%] [G loss: 0.701491]
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3483 [D loss: 0.690417, acc.: 55.66%] [G loss: 0.694490]
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3484 [D loss: 0.693250, acc.: 49.80%] [G loss: 0.691602]
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3485 [D loss: 0.695400, acc.: 48.83%] [G loss: 0.692596]
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3486 [D loss: 0.694394, acc.: 51.56%] [G loss: 0.697227]
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3487 [D loss: 0.693441, acc.: 51.95%] [G loss: 0.702944]
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3488 [D loss: 0.688501, acc.: 55.27%] [G loss: 0.703280]
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3489 [D loss: 0.691219, acc.: 51.37%] [G loss: 0.705056]
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3490 [D loss: 0.692507, acc.: 52.34%] [G loss: 0.698977]
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3491 [D loss: 0.693827, acc.: 50.59%] [G loss: 0.702054]
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3492 [D loss: 0.694954, acc.: 49.02%] [G loss: 0.700773]
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3493 [D loss: 0.693804, acc.: 49.22%] [G loss: 0.698754]
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3494 [D loss: 0.693951, acc.: 49.41%] [G loss: 0.693395]
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3495 [D loss: 0.693735, acc.: 49.02%] [G loss: 0.694850]
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3496 [D loss: 0.690640, acc.: 55.08%] [G loss: 0.697637]
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3497 [D loss: 0.691318, acc.: 52.93%] [G loss: 0.700979]
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3498 [D loss: 0.698383, acc.: 46.68%] [G loss: 0.701500]
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3499 [D loss: 0.689128, acc.: 56.45%] [G loss: 0.702499]
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3500 [D loss: 0.691124, acc.: 50.39%] [G loss: 0.703059]
1/1 [==============================] - 0s 17ms/step
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3501 [D loss: 0.693730, acc.: 48.05%] [G loss: 0.703607]
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3502 [D loss: 0.692505, acc.: 50.59%] [G loss: 0.699074]
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3503 [D loss: 0.690544, acc.: 54.30%] [G loss: 0.704469]
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3504 [D loss: 0.693248, acc.: 52.34%] [G loss: 0.702082]
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3505 [D loss: 0.690435, acc.: 53.12%] [G loss: 0.703917]
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3506 [D loss: 0.688438, acc.: 55.86%] [G loss: 0.703550]
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3507 [D loss: 0.692165, acc.: 52.93%] [G loss: 0.704238]
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3508 [D loss: 0.688046, acc.: 55.27%] [G loss: 0.704351]
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3509 [D loss: 0.691955, acc.: 52.93%] [G loss: 0.706904]
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3510 [D loss: 0.688961, acc.: 58.79%] [G loss: 0.700471]
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3511 [D loss: 0.688364, acc.: 53.91%] [G loss: 0.701970]
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3512 [D loss: 0.690609, acc.: 55.47%] [G loss: 0.697463]
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3513 [D loss: 0.693772, acc.: 48.44%] [G loss: 0.701320]
8/8 [==============================] - 0s 4ms/step
3514 [D loss: 0.694279, acc.: 50.20%] [G loss: 0.702962]
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3515 [D loss: 0.691625, acc.: 50.98%] [G loss: 0.700160]
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3516 [D loss: 0.690867, acc.: 53.12%] [G loss: 0.701645]
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3517 [D loss: 0.690768, acc.: 53.71%] [G loss: 0.696924]
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3518 [D loss: 0.692187, acc.: 50.20%] [G loss: 0.699751]
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3519 [D loss: 0.689115, acc.: 55.27%] [G loss: 0.701601]
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3520 [D loss: 0.688745, acc.: 54.10%] [G loss: 0.705272]
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3521 [D loss: 0.691767, acc.: 52.93%] [G loss: 0.702966]
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3522 [D loss: 0.692692, acc.: 50.39%] [G loss: 0.703207]
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3523 [D loss: 0.691670, acc.: 52.93%] [G loss: 0.702350]
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3524 [D loss: 0.692094, acc.: 50.59%] [G loss: 0.704409]
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3525 [D loss: 0.689263, acc.: 55.27%] [G loss: 0.707124]
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3526 [D loss: 0.692604, acc.: 52.73%] [G loss: 0.699697]
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3527 [D loss: 0.693826, acc.: 52.34%] [G loss: 0.703471]
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3528 [D loss: 0.690971, acc.: 54.10%] [G loss: 0.704767]
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3529 [D loss: 0.692581, acc.: 50.59%] [G loss: 0.702570]
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3530 [D loss: 0.692626, acc.: 51.95%] [G loss: 0.700126]
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3531 [D loss: 0.690059, acc.: 54.49%] [G loss: 0.694276]
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3532 [D loss: 0.694626, acc.: 48.44%] [G loss: 0.693522]
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3533 [D loss: 0.695810, acc.: 49.61%] [G loss: 0.693738]
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3534 [D loss: 0.690683, acc.: 54.49%] [G loss: 0.695414]
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3535 [D loss: 0.692559, acc.: 49.02%] [G loss: 0.696877]
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3536 [D loss: 0.690371, acc.: 52.73%] [G loss: 0.696802]
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3537 [D loss: 0.690122, acc.: 53.71%] [G loss: 0.696510]
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3538 [D loss: 0.692285, acc.: 52.73%] [G loss: 0.698819]
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3539 [D loss: 0.688783, acc.: 57.23%] [G loss: 0.698103]
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3540 [D loss: 0.691450, acc.: 52.15%] [G loss: 0.703705]
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3541 [D loss: 0.692422, acc.: 50.39%] [G loss: 0.696221]
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3542 [D loss: 0.689164, acc.: 54.30%] [G loss: 0.703024]
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3543 [D loss: 0.689288, acc.: 54.69%] [G loss: 0.701293]
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3544 [D loss: 0.691906, acc.: 50.59%] [G loss: 0.705283]
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3545 [D loss: 0.691976, acc.: 51.56%] [G loss: 0.703732]
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3546 [D loss: 0.694198, acc.: 46.48%] [G loss: 0.699529]
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3547 [D loss: 0.692559, acc.: 50.00%] [G loss: 0.696380]
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3548 [D loss: 0.694805, acc.: 46.48%] [G loss: 0.696308]
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3549 [D loss: 0.693442, acc.: 49.02%] [G loss: 0.696385]
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3550 [D loss: 0.690384, acc.: 54.88%] [G loss: 0.693425]
1/1 [==============================] - 0s 16ms/step
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3551 [D loss: 0.692237, acc.: 52.73%] [G loss: 0.696471]
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3552 [D loss: 0.692531, acc.: 50.39%] [G loss: 0.693366]
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3553 [D loss: 0.695711, acc.: 45.90%] [G loss: 0.696367]
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3554 [D loss: 0.690432, acc.: 51.37%] [G loss: 0.695952]
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3555 [D loss: 0.688485, acc.: 56.05%] [G loss: 0.699383]
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3556 [D loss: 0.692032, acc.: 52.54%] [G loss: 0.699588]
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3557 [D loss: 0.689552, acc.: 55.66%] [G loss: 0.702643]
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3558 [D loss: 0.689028, acc.: 55.66%] [G loss: 0.703500]
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3559 [D loss: 0.691285, acc.: 52.15%] [G loss: 0.702376]
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3560 [D loss: 0.691722, acc.: 52.73%] [G loss: 0.701019]
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3561 [D loss: 0.696070, acc.: 45.51%] [G loss: 0.696606]
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3562 [D loss: 0.689650, acc.: 55.86%] [G loss: 0.701143]
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3563 [D loss: 0.691534, acc.: 51.76%] [G loss: 0.702412]
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3564 [D loss: 0.692187, acc.: 50.78%] [G loss: 0.700716]
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3565 [D loss: 0.689785, acc.: 57.42%] [G loss: 0.703727]
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3566 [D loss: 0.691719, acc.: 53.52%] [G loss: 0.703217]
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3567 [D loss: 0.691270, acc.: 54.10%] [G loss: 0.700539]
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3568 [D loss: 0.692381, acc.: 52.93%] [G loss: 0.702939]
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3569 [D loss: 0.690237, acc.: 50.59%] [G loss: 0.700087]
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3570 [D loss: 0.691446, acc.: 52.15%] [G loss: 0.705465]
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3571 [D loss: 0.685764, acc.: 60.35%] [G loss: 0.700535]
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3572 [D loss: 0.690428, acc.: 54.69%] [G loss: 0.704566]
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3573 [D loss: 0.690802, acc.: 53.71%] [G loss: 0.695639]
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3574 [D loss: 0.693655, acc.: 50.78%] [G loss: 0.696821]
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3575 [D loss: 0.691412, acc.: 52.73%] [G loss: 0.697873]
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3576 [D loss: 0.690982, acc.: 52.15%] [G loss: 0.696335]
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3577 [D loss: 0.691994, acc.: 50.98%] [G loss: 0.698293]
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3578 [D loss: 0.689551, acc.: 53.71%] [G loss: 0.701034]
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3579 [D loss: 0.693287, acc.: 51.76%] [G loss: 0.699881]
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3580 [D loss: 0.691642, acc.: 49.02%] [G loss: 0.694284]
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3581 [D loss: 0.691963, acc.: 50.39%] [G loss: 0.701587]
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3582 [D loss: 0.692310, acc.: 51.37%] [G loss: 0.699301]
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3583 [D loss: 0.694563, acc.: 50.59%] [G loss: 0.703075]
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3584 [D loss: 0.693275, acc.: 49.61%] [G loss: 0.701043]
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3585 [D loss: 0.690951, acc.: 52.15%] [G loss: 0.698510]
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3586 [D loss: 0.691907, acc.: 52.54%] [G loss: 0.701097]
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3587 [D loss: 0.693921, acc.: 49.80%] [G loss: 0.702271]
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3588 [D loss: 0.692874, acc.: 48.05%] [G loss: 0.700225]
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3589 [D loss: 0.688267, acc.: 55.86%] [G loss: 0.701118]
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3590 [D loss: 0.690497, acc.: 53.32%] [G loss: 0.700195]
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3591 [D loss: 0.693808, acc.: 50.00%] [G loss: 0.703717]
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3592 [D loss: 0.686579, acc.: 57.03%] [G loss: 0.699009]
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3593 [D loss: 0.693530, acc.: 49.22%] [G loss: 0.700023]
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3594 [D loss: 0.691702, acc.: 52.34%] [G loss: 0.694864]
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3595 [D loss: 0.690605, acc.: 53.12%] [G loss: 0.692850]
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3596 [D loss: 0.692195, acc.: 50.59%] [G loss: 0.696600]
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3597 [D loss: 0.687254, acc.: 56.84%] [G loss: 0.701246]
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3598 [D loss: 0.684904, acc.: 59.18%] [G loss: 0.707266]
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3599 [D loss: 0.684429, acc.: 59.38%] [G loss: 0.706326]
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3600 [D loss: 0.690864, acc.: 52.34%] [G loss: 0.704282]
1/1 [==============================] - 0s 20ms/step
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3601 [D loss: 0.692237, acc.: 52.93%] [G loss: 0.697406]
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3602 [D loss: 0.691979, acc.: 50.00%] [G loss: 0.694564]
8/8 [==============================] - 0s 4ms/step
3603 [D loss: 0.690997, acc.: 50.98%] [G loss: 0.696714]
8/8 [==============================] - 0s 4ms/step
3604 [D loss: 0.693061, acc.: 50.98%] [G loss: 0.695119]
8/8 [==============================] - 0s 4ms/step
3605 [D loss: 0.690261, acc.: 57.81%] [G loss: 0.694087]
8/8 [==============================] - 0s 4ms/step
3606 [D loss: 0.692676, acc.: 49.61%] [G loss: 0.696143]
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3607 [D loss: 0.696998, acc.: 45.70%] [G loss: 0.695793]
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3608 [D loss: 0.694223, acc.: 49.02%] [G loss: 0.699279]
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3609 [D loss: 0.692396, acc.: 51.56%] [G loss: 0.693966]
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3610 [D loss: 0.694833, acc.: 48.05%] [G loss: 0.699316]
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3611 [D loss: 0.690535, acc.: 53.71%] [G loss: 0.693420]
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3612 [D loss: 0.689997, acc.: 52.73%] [G loss: 0.699309]
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3613 [D loss: 0.688337, acc.: 58.40%] [G loss: 0.697545]
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3614 [D loss: 0.691856, acc.: 50.59%] [G loss: 0.701736]
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3615 [D loss: 0.688793, acc.: 55.27%] [G loss: 0.702305]
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3616 [D loss: 0.691431, acc.: 51.95%] [G loss: 0.701754]
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3617 [D loss: 0.686413, acc.: 60.16%] [G loss: 0.704185]
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3618 [D loss: 0.682050, acc.: 64.06%] [G loss: 0.706686]
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3619 [D loss: 0.684749, acc.: 58.79%] [G loss: 0.699692]
8/8 [==============================] - 0s 4ms/step
3620 [D loss: 0.693219, acc.: 51.37%] [G loss: 0.687459]
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3621 [D loss: 0.701595, acc.: 45.70%] [G loss: 0.696214]
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3622 [D loss: 0.698146, acc.: 43.16%] [G loss: 0.694226]
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3623 [D loss: 0.691685, acc.: 51.37%] [G loss: 0.696278]
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3624 [D loss: 0.686629, acc.: 57.81%] [G loss: 0.702341]
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3625 [D loss: 0.689470, acc.: 55.08%] [G loss: 0.702633]
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3626 [D loss: 0.690532, acc.: 51.76%] [G loss: 0.699829]
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3627 [D loss: 0.691005, acc.: 51.37%] [G loss: 0.697870]
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3628 [D loss: 0.694945, acc.: 45.90%] [G loss: 0.695498]
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3629 [D loss: 0.693995, acc.: 48.05%] [G loss: 0.695154]
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3630 [D loss: 0.693675, acc.: 53.32%] [G loss: 0.697689]
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3631 [D loss: 0.690637, acc.: 54.30%] [G loss: 0.693573]
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3632 [D loss: 0.692710, acc.: 51.37%] [G loss: 0.693457]
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3633 [D loss: 0.697225, acc.: 47.85%] [G loss: 0.689505]
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3634 [D loss: 0.695929, acc.: 48.24%] [G loss: 0.691414]
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3635 [D loss: 0.695590, acc.: 48.05%] [G loss: 0.694842]
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3636 [D loss: 0.692311, acc.: 50.78%] [G loss: 0.699976]
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3637 [D loss: 0.688797, acc.: 53.52%] [G loss: 0.701207]
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3638 [D loss: 0.687030, acc.: 57.23%] [G loss: 0.701399]
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3639 [D loss: 0.691167, acc.: 55.66%] [G loss: 0.698005]
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3640 [D loss: 0.691673, acc.: 54.10%] [G loss: 0.697580]
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3641 [D loss: 0.690103, acc.: 54.88%] [G loss: 0.699349]
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3642 [D loss: 0.693878, acc.: 49.41%] [G loss: 0.701349]
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3643 [D loss: 0.691178, acc.: 52.93%] [G loss: 0.700555]
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3644 [D loss: 0.689502, acc.: 55.08%] [G loss: 0.708354]
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3645 [D loss: 0.685804, acc.: 57.81%] [G loss: 0.712648]
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3646 [D loss: 0.688305, acc.: 58.20%] [G loss: 0.709859]
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3647 [D loss: 0.689506, acc.: 55.08%] [G loss: 0.708671]
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3648 [D loss: 0.690995, acc.: 50.20%] [G loss: 0.709910]
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3649 [D loss: 0.694550, acc.: 48.44%] [G loss: 0.707022]
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3650 [D loss: 0.691008, acc.: 50.59%] [G loss: 0.705078]
1/1 [==============================] - 0s 16ms/step
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3651 [D loss: 0.690413, acc.: 54.49%] [G loss: 0.707065]
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3652 [D loss: 0.684972, acc.: 62.11%] [G loss: 0.704929]
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3653 [D loss: 0.686791, acc.: 55.86%] [G loss: 0.702847]
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3654 [D loss: 0.691868, acc.: 51.76%] [G loss: 0.695130]
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3655 [D loss: 0.694349, acc.: 47.27%] [G loss: 0.696571]
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3656 [D loss: 0.695126, acc.: 47.27%] [G loss: 0.694094]
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3657 [D loss: 0.696680, acc.: 43.36%] [G loss: 0.691972]
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3658 [D loss: 0.693052, acc.: 50.00%] [G loss: 0.697116]
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3659 [D loss: 0.691520, acc.: 52.93%] [G loss: 0.697483]
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3660 [D loss: 0.691459, acc.: 52.73%] [G loss: 0.699983]
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3661 [D loss: 0.688491, acc.: 53.71%] [G loss: 0.699026]
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3662 [D loss: 0.693311, acc.: 49.22%] [G loss: 0.701639]
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3663 [D loss: 0.693782, acc.: 48.44%] [G loss: 0.702987]
8/8 [==============================] - 0s 4ms/step
3664 [D loss: 0.689382, acc.: 56.84%] [G loss: 0.704578]
8/8 [==============================] - 0s 4ms/step
3665 [D loss: 0.690695, acc.: 50.78%] [G loss: 0.703641]
8/8 [==============================] - 0s 4ms/step
3666 [D loss: 0.690407, acc.: 51.56%] [G loss: 0.701115]
8/8 [==============================] - 0s 4ms/step
3667 [D loss: 0.687228, acc.: 56.25%] [G loss: 0.703084]
8/8 [==============================] - 0s 4ms/step
3668 [D loss: 0.691651, acc.: 50.39%] [G loss: 0.700225]
8/8 [==============================] - 0s 4ms/step
3669 [D loss: 0.689389, acc.: 56.45%] [G loss: 0.694760]
8/8 [==============================] - 0s 4ms/step
3670 [D loss: 0.690214, acc.: 55.47%] [G loss: 0.699836]
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3671 [D loss: 0.690759, acc.: 56.05%] [G loss: 0.698764]
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3672 [D loss: 0.690034, acc.: 54.69%] [G loss: 0.696605]
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3673 [D loss: 0.686973, acc.: 57.42%] [G loss: 0.697892]
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3674 [D loss: 0.691018, acc.: 52.73%] [G loss: 0.694571]
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3675 [D loss: 0.688834, acc.: 55.86%] [G loss: 0.698135]
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3676 [D loss: 0.693565, acc.: 49.41%] [G loss: 0.696392]
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3677 [D loss: 0.691520, acc.: 52.54%] [G loss: 0.695481]
8/8 [==============================] - 0s 4ms/step
3678 [D loss: 0.689472, acc.: 56.84%] [G loss: 0.694944]
8/8 [==============================] - 0s 4ms/step
3679 [D loss: 0.690531, acc.: 52.93%] [G loss: 0.699149]
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3680 [D loss: 0.692477, acc.: 53.32%] [G loss: 0.703463]
8/8 [==============================] - 0s 4ms/step
3681 [D loss: 0.687563, acc.: 56.84%] [G loss: 0.696252]
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3682 [D loss: 0.690031, acc.: 52.15%] [G loss: 0.697462]
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3683 [D loss: 0.694769, acc.: 49.02%] [G loss: 0.698411]
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3684 [D loss: 0.693573, acc.: 44.92%] [G loss: 0.692653]
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3685 [D loss: 0.695115, acc.: 48.05%] [G loss: 0.699625]
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3686 [D loss: 0.695561, acc.: 47.07%] [G loss: 0.691724]
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3687 [D loss: 0.692374, acc.: 53.32%] [G loss: 0.698399]
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3688 [D loss: 0.693379, acc.: 48.63%] [G loss: 0.701048]
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3689 [D loss: 0.691089, acc.: 52.93%] [G loss: 0.698892]
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3690 [D loss: 0.692736, acc.: 51.17%] [G loss: 0.697550]
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3691 [D loss: 0.691809, acc.: 51.95%] [G loss: 0.702418]
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3692 [D loss: 0.690184, acc.: 51.17%] [G loss: 0.703966]
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3693 [D loss: 0.688375, acc.: 54.88%] [G loss: 0.704696]
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3694 [D loss: 0.691141, acc.: 53.32%] [G loss: 0.705522]
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3695 [D loss: 0.690242, acc.: 57.81%] [G loss: 0.705843]
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3696 [D loss: 0.692392, acc.: 51.76%] [G loss: 0.704479]
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3697 [D loss: 0.692530, acc.: 51.56%] [G loss: 0.707147]
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3698 [D loss: 0.692183, acc.: 52.93%] [G loss: 0.706047]
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3699 [D loss: 0.690467, acc.: 51.17%] [G loss: 0.702938]
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3700 [D loss: 0.690501, acc.: 53.12%] [G loss: 0.702187]
1/1 [==============================] - 0s 18ms/step
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3701 [D loss: 0.688613, acc.: 55.47%] [G loss: 0.699968]
8/8 [==============================] - 0s 4ms/step
3702 [D loss: 0.695085, acc.: 49.80%] [G loss: 0.699664]
8/8 [==============================] - 0s 4ms/step
3703 [D loss: 0.694527, acc.: 50.20%] [G loss: 0.701490]
8/8 [==============================] - 0s 4ms/step
3704 [D loss: 0.696368, acc.: 47.07%] [G loss: 0.699173]
8/8 [==============================] - 0s 4ms/step
3705 [D loss: 0.690053, acc.: 55.08%] [G loss: 0.704352]
8/8 [==============================] - 0s 4ms/step
3706 [D loss: 0.690132, acc.: 54.10%] [G loss: 0.699455]
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3707 [D loss: 0.687213, acc.: 56.84%] [G loss: 0.704836]
8/8 [==============================] - 0s 4ms/step
3708 [D loss: 0.691478, acc.: 51.56%] [G loss: 0.700687]
8/8 [==============================] - 0s 4ms/step
3709 [D loss: 0.688591, acc.: 56.84%] [G loss: 0.698777]
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3710 [D loss: 0.691261, acc.: 50.98%] [G loss: 0.700954]
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3711 [D loss: 0.688876, acc.: 56.84%] [G loss: 0.696477]
8/8 [==============================] - 0s 4ms/step
3712 [D loss: 0.691303, acc.: 55.47%] [G loss: 0.697502]
8/8 [==============================] - 0s 4ms/step
3713 [D loss: 0.690422, acc.: 53.71%] [G loss: 0.697633]
8/8 [==============================] - 0s 4ms/step
3714 [D loss: 0.689357, acc.: 55.27%] [G loss: 0.699583]
8/8 [==============================] - 0s 4ms/step
3715 [D loss: 0.687679, acc.: 54.49%] [G loss: 0.695938]
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3716 [D loss: 0.688709, acc.: 54.30%] [G loss: 0.697293]
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3717 [D loss: 0.692572, acc.: 50.20%] [G loss: 0.696492]
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3718 [D loss: 0.691324, acc.: 53.52%] [G loss: 0.700517]
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3719 [D loss: 0.686141, acc.: 58.01%] [G loss: 0.699292]
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3720 [D loss: 0.687280, acc.: 57.42%] [G loss: 0.696994]
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3721 [D loss: 0.690795, acc.: 53.32%] [G loss: 0.694949]
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3722 [D loss: 0.693880, acc.: 49.22%] [G loss: 0.695191]
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3723 [D loss: 0.693044, acc.: 51.95%] [G loss: 0.695740]
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3724 [D loss: 0.692255, acc.: 48.05%] [G loss: 0.697405]
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3725 [D loss: 0.692698, acc.: 48.83%] [G loss: 0.698461]
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3726 [D loss: 0.689943, acc.: 54.49%] [G loss: 0.702305]
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3727 [D loss: 0.692477, acc.: 49.02%] [G loss: 0.698253]
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3728 [D loss: 0.691159, acc.: 53.12%] [G loss: 0.701370]
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3729 [D loss: 0.693374, acc.: 49.22%] [G loss: 0.693799]
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3730 [D loss: 0.690976, acc.: 51.17%] [G loss: 0.698491]
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3731 [D loss: 0.691890, acc.: 51.76%] [G loss: 0.699638]
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3732 [D loss: 0.689656, acc.: 55.86%] [G loss: 0.704788]
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3733 [D loss: 0.689320, acc.: 56.45%] [G loss: 0.700206]
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3734 [D loss: 0.689613, acc.: 54.88%] [G loss: 0.700778]
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3735 [D loss: 0.692070, acc.: 52.15%] [G loss: 0.699940]
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3736 [D loss: 0.692973, acc.: 51.56%] [G loss: 0.695926]
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3737 [D loss: 0.692871, acc.: 50.20%] [G loss: 0.697511]
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3738 [D loss: 0.694402, acc.: 49.41%] [G loss: 0.697259]
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3739 [D loss: 0.690414, acc.: 52.34%] [G loss: 0.700857]
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3740 [D loss: 0.689110, acc.: 55.86%] [G loss: 0.701744]
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3741 [D loss: 0.686695, acc.: 58.01%] [G loss: 0.703017]
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3742 [D loss: 0.687606, acc.: 57.23%] [G loss: 0.703564]
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3743 [D loss: 0.696190, acc.: 48.83%] [G loss: 0.701160]
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3744 [D loss: 0.694001, acc.: 50.98%] [G loss: 0.699219]
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3745 [D loss: 0.691118, acc.: 50.78%] [G loss: 0.698529]
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3746 [D loss: 0.688592, acc.: 57.03%] [G loss: 0.699409]
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3747 [D loss: 0.688856, acc.: 55.66%] [G loss: 0.698404]
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3748 [D loss: 0.689105, acc.: 52.93%] [G loss: 0.704455]
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3749 [D loss: 0.688942, acc.: 51.37%] [G loss: 0.692579]
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3750 [D loss: 0.692551, acc.: 53.71%] [G loss: 0.693105]
1/1 [==============================] - 0s 17ms/step
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3751 [D loss: 0.693981, acc.: 50.00%] [G loss: 0.694344]
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3752 [D loss: 0.690264, acc.: 54.69%] [G loss: 0.700730]
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3753 [D loss: 0.687066, acc.: 56.64%] [G loss: 0.703337]
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3754 [D loss: 0.691609, acc.: 54.30%] [G loss: 0.702658]
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3755 [D loss: 0.689186, acc.: 55.86%] [G loss: 0.706010]
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3756 [D loss: 0.691849, acc.: 49.61%] [G loss: 0.702236]
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3757 [D loss: 0.693226, acc.: 50.20%] [G loss: 0.701985]
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3758 [D loss: 0.695195, acc.: 46.68%] [G loss: 0.703395]
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3759 [D loss: 0.692785, acc.: 48.83%] [G loss: 0.706352]
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3760 [D loss: 0.688438, acc.: 55.08%] [G loss: 0.706626]
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3761 [D loss: 0.684439, acc.: 59.96%] [G loss: 0.710371]
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3762 [D loss: 0.689580, acc.: 53.32%] [G loss: 0.706992]
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3763 [D loss: 0.692816, acc.: 51.76%] [G loss: 0.703830]
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3764 [D loss: 0.694138, acc.: 47.66%] [G loss: 0.701056]
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3765 [D loss: 0.694791, acc.: 46.09%] [G loss: 0.700020]
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3766 [D loss: 0.689589, acc.: 56.64%] [G loss: 0.703598]
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3767 [D loss: 0.685700, acc.: 58.59%] [G loss: 0.709672]
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3768 [D loss: 0.688058, acc.: 56.45%] [G loss: 0.707029]
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3769 [D loss: 0.688109, acc.: 58.20%] [G loss: 0.704553]
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3770 [D loss: 0.693988, acc.: 50.00%] [G loss: 0.695326]
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3771 [D loss: 0.694852, acc.: 47.66%] [G loss: 0.696397]
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3772 [D loss: 0.698082, acc.: 45.12%] [G loss: 0.697972]
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3773 [D loss: 0.690651, acc.: 53.52%] [G loss: 0.697154]
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3774 [D loss: 0.688806, acc.: 54.30%] [G loss: 0.702007]
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3775 [D loss: 0.689704, acc.: 53.71%] [G loss: 0.706880]
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3776 [D loss: 0.687300, acc.: 55.47%] [G loss: 0.706300]
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3777 [D loss: 0.689329, acc.: 55.27%] [G loss: 0.706691]
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3778 [D loss: 0.690268, acc.: 51.56%] [G loss: 0.696067]
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3779 [D loss: 0.690925, acc.: 51.95%] [G loss: 0.688516]
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3780 [D loss: 0.691271, acc.: 54.30%] [G loss: 0.694468]
8/8 [==============================] - 0s 4ms/step
3781 [D loss: 0.692773, acc.: 51.76%] [G loss: 0.698199]
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3782 [D loss: 0.690412, acc.: 52.54%] [G loss: 0.703269]
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3783 [D loss: 0.690865, acc.: 53.12%] [G loss: 0.701205]
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3784 [D loss: 0.692463, acc.: 49.41%] [G loss: 0.700197]
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3785 [D loss: 0.692818, acc.: 48.44%] [G loss: 0.701316]
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3786 [D loss: 0.689883, acc.: 51.76%] [G loss: 0.700824]
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3787 [D loss: 0.687658, acc.: 54.88%] [G loss: 0.700723]
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3788 [D loss: 0.687524, acc.: 55.86%] [G loss: 0.697791]
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3789 [D loss: 0.685144, acc.: 58.20%] [G loss: 0.698413]
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3790 [D loss: 0.690119, acc.: 54.49%] [G loss: 0.699196]
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3791 [D loss: 0.690472, acc.: 53.71%] [G loss: 0.699008]
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3792 [D loss: 0.691660, acc.: 51.76%] [G loss: 0.700773]
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3793 [D loss: 0.692417, acc.: 49.22%] [G loss: 0.697338]
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3794 [D loss: 0.696734, acc.: 47.46%] [G loss: 0.700597]
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3795 [D loss: 0.688182, acc.: 58.98%] [G loss: 0.706818]
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3796 [D loss: 0.689558, acc.: 56.05%] [G loss: 0.715050]
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3797 [D loss: 0.685644, acc.: 56.84%] [G loss: 0.717938]
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3798 [D loss: 0.685373, acc.: 58.79%] [G loss: 0.715453]
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3799 [D loss: 0.691481, acc.: 53.91%] [G loss: 0.712624]
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3800 [D loss: 0.694179, acc.: 49.41%] [G loss: 0.705876]
1/1 [==============================] - 0s 18ms/step
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3801 [D loss: 0.691145, acc.: 54.30%] [G loss: 0.703133]
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3802 [D loss: 0.691857, acc.: 54.69%] [G loss: 0.695796]
8/8 [==============================] - 0s 4ms/step
3803 [D loss: 0.688983, acc.: 56.64%] [G loss: 0.692332]
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3804 [D loss: 0.694198, acc.: 48.83%] [G loss: 0.695433]
8/8 [==============================] - 0s 4ms/step
3805 [D loss: 0.692894, acc.: 52.34%] [G loss: 0.694773]
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3806 [D loss: 0.692957, acc.: 51.76%] [G loss: 0.689603]
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3807 [D loss: 0.692347, acc.: 51.37%] [G loss: 0.689354]
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3808 [D loss: 0.690386, acc.: 54.69%] [G loss: 0.688626]
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3809 [D loss: 0.688920, acc.: 54.69%] [G loss: 0.692337]
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3810 [D loss: 0.690252, acc.: 52.15%] [G loss: 0.695228]
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3811 [D loss: 0.690775, acc.: 52.15%] [G loss: 0.694416]
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3812 [D loss: 0.693036, acc.: 50.20%] [G loss: 0.699172]
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3813 [D loss: 0.692257, acc.: 54.30%] [G loss: 0.698705]
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3814 [D loss: 0.692323, acc.: 52.93%] [G loss: 0.700948]
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3815 [D loss: 0.686172, acc.: 58.01%] [G loss: 0.705969]
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3816 [D loss: 0.686454, acc.: 60.16%] [G loss: 0.706710]
8/8 [==============================] - 0s 4ms/step
3817 [D loss: 0.688014, acc.: 54.30%] [G loss: 0.702849]
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3818 [D loss: 0.689123, acc.: 55.47%] [G loss: 0.702959]
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3819 [D loss: 0.689281, acc.: 54.30%] [G loss: 0.702384]
8/8 [==============================] - 0s 4ms/step
3820 [D loss: 0.692572, acc.: 51.76%] [G loss: 0.704838]
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3821 [D loss: 0.692671, acc.: 51.37%] [G loss: 0.708558]
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3822 [D loss: 0.688521, acc.: 53.91%] [G loss: 0.706828]
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3823 [D loss: 0.685545, acc.: 56.84%] [G loss: 0.714113]
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3824 [D loss: 0.688901, acc.: 53.32%] [G loss: 0.709672]
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3825 [D loss: 0.690677, acc.: 53.32%] [G loss: 0.704677]
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3826 [D loss: 0.690169, acc.: 54.30%] [G loss: 0.703604]
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3827 [D loss: 0.695192, acc.: 51.76%] [G loss: 0.705999]
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3828 [D loss: 0.690397, acc.: 53.71%] [G loss: 0.703396]
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3829 [D loss: 0.692401, acc.: 53.32%] [G loss: 0.709762]
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3830 [D loss: 0.689519, acc.: 54.88%] [G loss: 0.707769]
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3831 [D loss: 0.689848, acc.: 54.49%] [G loss: 0.707928]
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3832 [D loss: 0.691337, acc.: 54.69%] [G loss: 0.708212]
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3833 [D loss: 0.688571, acc.: 54.88%] [G loss: 0.707711]
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3834 [D loss: 0.690362, acc.: 51.56%] [G loss: 0.712411]
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3835 [D loss: 0.687195, acc.: 57.62%] [G loss: 0.713640]
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3836 [D loss: 0.688306, acc.: 57.42%] [G loss: 0.710846]
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3837 [D loss: 0.690244, acc.: 53.91%] [G loss: 0.706034]
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3838 [D loss: 0.693173, acc.: 51.17%] [G loss: 0.700058]
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3839 [D loss: 0.690193, acc.: 51.76%] [G loss: 0.705243]
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3840 [D loss: 0.692718, acc.: 51.95%] [G loss: 0.705709]
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3841 [D loss: 0.691015, acc.: 53.91%] [G loss: 0.701055]
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3842 [D loss: 0.690005, acc.: 52.34%] [G loss: 0.703193]
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3843 [D loss: 0.693611, acc.: 50.98%] [G loss: 0.698095]
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3844 [D loss: 0.692762, acc.: 50.39%] [G loss: 0.699541]
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3845 [D loss: 0.690153, acc.: 53.32%] [G loss: 0.702352]
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3846 [D loss: 0.689472, acc.: 55.08%] [G loss: 0.699567]
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3847 [D loss: 0.687809, acc.: 57.23%] [G loss: 0.711954]
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3848 [D loss: 0.683819, acc.: 60.74%] [G loss: 0.705229]
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3849 [D loss: 0.685830, acc.: 56.25%] [G loss: 0.706044]
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3850 [D loss: 0.693581, acc.: 52.34%] [G loss: 0.704985]
1/1 [==============================] - 0s 18ms/step
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3851 [D loss: 0.692881, acc.: 49.22%] [G loss: 0.694605]
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3852 [D loss: 0.692980, acc.: 50.00%] [G loss: 0.699372]
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3853 [D loss: 0.692726, acc.: 52.34%] [G loss: 0.696706]
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3854 [D loss: 0.690484, acc.: 54.69%] [G loss: 0.704060]
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3855 [D loss: 0.688709, acc.: 57.23%] [G loss: 0.707246]
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3856 [D loss: 0.685859, acc.: 55.86%] [G loss: 0.709588]
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3857 [D loss: 0.685811, acc.: 58.40%] [G loss: 0.708221]
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3858 [D loss: 0.688254, acc.: 56.84%] [G loss: 0.701807]
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3859 [D loss: 0.692651, acc.: 48.63%] [G loss: 0.703791]
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3860 [D loss: 0.688821, acc.: 53.71%] [G loss: 0.703576]
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3861 [D loss: 0.689491, acc.: 53.32%] [G loss: 0.704330]
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3862 [D loss: 0.692799, acc.: 47.46%] [G loss: 0.705485]
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3863 [D loss: 0.690997, acc.: 51.37%] [G loss: 0.697810]
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3864 [D loss: 0.698162, acc.: 47.27%] [G loss: 0.696433]
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3865 [D loss: 0.694379, acc.: 49.80%] [G loss: 0.695636]
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3866 [D loss: 0.692614, acc.: 51.56%] [G loss: 0.698421]
8/8 [==============================] - 0s 4ms/step
3867 [D loss: 0.689751, acc.: 52.93%] [G loss: 0.704948]
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3868 [D loss: 0.690456, acc.: 52.15%] [G loss: 0.703214]
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3869 [D loss: 0.694692, acc.: 48.63%] [G loss: 0.698519]
8/8 [==============================] - 0s 4ms/step
3870 [D loss: 0.690995, acc.: 53.32%] [G loss: 0.702972]
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3871 [D loss: 0.692320, acc.: 53.12%] [G loss: 0.700674]
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3872 [D loss: 0.690143, acc.: 52.73%] [G loss: 0.706893]
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3873 [D loss: 0.688646, acc.: 53.71%] [G loss: 0.706188]
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3874 [D loss: 0.689516, acc.: 58.59%] [G loss: 0.717712]
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3875 [D loss: 0.687232, acc.: 56.45%] [G loss: 0.717776]
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3876 [D loss: 0.687625, acc.: 56.25%] [G loss: 0.709132]
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3877 [D loss: 0.693363, acc.: 51.56%] [G loss: 0.707895]
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3878 [D loss: 0.692261, acc.: 54.10%] [G loss: 0.706592]
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3879 [D loss: 0.688285, acc.: 56.25%] [G loss: 0.702359]
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3880 [D loss: 0.688074, acc.: 54.69%] [G loss: 0.700228]
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3881 [D loss: 0.684842, acc.: 58.98%] [G loss: 0.702105]
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3882 [D loss: 0.688187, acc.: 55.27%] [G loss: 0.696833]
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3883 [D loss: 0.690966, acc.: 53.32%] [G loss: 0.696590]
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3884 [D loss: 0.697096, acc.: 47.07%] [G loss: 0.690861]
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3885 [D loss: 0.694509, acc.: 50.20%] [G loss: 0.684146]
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3886 [D loss: 0.692700, acc.: 50.59%] [G loss: 0.696587]
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3887 [D loss: 0.692214, acc.: 51.17%] [G loss: 0.698112]
8/8 [==============================] - 0s 4ms/step
3888 [D loss: 0.688497, acc.: 57.03%] [G loss: 0.702453]
8/8 [==============================] - 0s 4ms/step
3889 [D loss: 0.685651, acc.: 58.01%] [G loss: 0.704655]
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3890 [D loss: 0.688692, acc.: 54.30%] [G loss: 0.702033]
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3891 [D loss: 0.691840, acc.: 52.15%] [G loss: 0.705036]
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3892 [D loss: 0.690568, acc.: 52.93%] [G loss: 0.700184]
8/8 [==============================] - 0s 4ms/step
3893 [D loss: 0.691218, acc.: 51.56%] [G loss: 0.700633]
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3894 [D loss: 0.688849, acc.: 54.69%] [G loss: 0.707437]
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3895 [D loss: 0.689213, acc.: 56.84%] [G loss: 0.710015]
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3896 [D loss: 0.684776, acc.: 58.79%] [G loss: 0.710119]
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3897 [D loss: 0.689054, acc.: 53.52%] [G loss: 0.709776]
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3898 [D loss: 0.687514, acc.: 55.08%] [G loss: 0.705330]
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3899 [D loss: 0.689285, acc.: 53.52%] [G loss: 0.706398]
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3900 [D loss: 0.682701, acc.: 60.35%] [G loss: 0.709660]
1/1 [==============================] - 0s 17ms/step
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3901 [D loss: 0.687072, acc.: 57.23%] [G loss: 0.708532]
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3902 [D loss: 0.691616, acc.: 52.93%] [G loss: 0.703166]
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3903 [D loss: 0.688440, acc.: 56.05%] [G loss: 0.702667]
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3904 [D loss: 0.697420, acc.: 47.27%] [G loss: 0.691716]
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3905 [D loss: 0.695020, acc.: 49.61%] [G loss: 0.693848]
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3906 [D loss: 0.693327, acc.: 50.98%] [G loss: 0.694708]
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3907 [D loss: 0.696372, acc.: 50.39%] [G loss: 0.689111]
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3908 [D loss: 0.695273, acc.: 48.63%] [G loss: 0.689163]
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3909 [D loss: 0.692273, acc.: 49.80%] [G loss: 0.695704]
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3910 [D loss: 0.693087, acc.: 51.56%] [G loss: 0.695616]
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3911 [D loss: 0.692697, acc.: 52.34%] [G loss: 0.698975]
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3912 [D loss: 0.691256, acc.: 51.95%] [G loss: 0.697744]
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3913 [D loss: 0.689567, acc.: 54.69%] [G loss: 0.699490]
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3914 [D loss: 0.689010, acc.: 53.52%] [G loss: 0.701249]
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3915 [D loss: 0.690483, acc.: 57.03%] [G loss: 0.714502]
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3916 [D loss: 0.688255, acc.: 57.23%] [G loss: 0.708358]
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3917 [D loss: 0.687926, acc.: 55.27%] [G loss: 0.708411]
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3918 [D loss: 0.688271, acc.: 55.08%] [G loss: 0.714085]
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3919 [D loss: 0.686785, acc.: 57.23%] [G loss: 0.714444]
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3920 [D loss: 0.682881, acc.: 61.13%] [G loss: 0.711626]
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3921 [D loss: 0.688179, acc.: 55.47%] [G loss: 0.708561]
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3922 [D loss: 0.689260, acc.: 53.32%] [G loss: 0.705898]
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3923 [D loss: 0.689946, acc.: 54.30%] [G loss: 0.703333]
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3924 [D loss: 0.693085, acc.: 50.20%] [G loss: 0.700793]
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3925 [D loss: 0.691259, acc.: 52.15%] [G loss: 0.706495]
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3926 [D loss: 0.692727, acc.: 48.83%] [G loss: 0.700095]
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3927 [D loss: 0.691631, acc.: 52.34%] [G loss: 0.695811]
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3928 [D loss: 0.693842, acc.: 49.41%] [G loss: 0.698144]
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3929 [D loss: 0.693577, acc.: 47.85%] [G loss: 0.700770]
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3930 [D loss: 0.692709, acc.: 53.32%] [G loss: 0.699992]
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3931 [D loss: 0.691347, acc.: 52.54%] [G loss: 0.700736]
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3932 [D loss: 0.690830, acc.: 52.34%] [G loss: 0.699555]
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3933 [D loss: 0.692658, acc.: 51.17%] [G loss: 0.697244]
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3934 [D loss: 0.688378, acc.: 56.64%] [G loss: 0.702747]
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3935 [D loss: 0.689855, acc.: 54.10%] [G loss: 0.699039]
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3936 [D loss: 0.689116, acc.: 56.45%] [G loss: 0.701774]
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3937 [D loss: 0.687483, acc.: 53.71%] [G loss: 0.702201]
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3938 [D loss: 0.687313, acc.: 58.01%] [G loss: 0.696901]
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3939 [D loss: 0.688120, acc.: 56.45%] [G loss: 0.704363]
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3940 [D loss: 0.685854, acc.: 54.49%] [G loss: 0.698075]
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3941 [D loss: 0.690151, acc.: 51.76%] [G loss: 0.701472]
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3942 [D loss: 0.689999, acc.: 55.66%] [G loss: 0.700267]
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3943 [D loss: 0.690569, acc.: 55.86%] [G loss: 0.696222]
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3944 [D loss: 0.692758, acc.: 50.78%] [G loss: 0.698461]
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3945 [D loss: 0.692118, acc.: 52.15%] [G loss: 0.696408]
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3946 [D loss: 0.693417, acc.: 49.22%] [G loss: 0.702156]
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3947 [D loss: 0.689970, acc.: 51.76%] [G loss: 0.695422]
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3948 [D loss: 0.691571, acc.: 53.52%] [G loss: 0.697290]
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3949 [D loss: 0.687306, acc.: 55.66%] [G loss: 0.698356]
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3950 [D loss: 0.689864, acc.: 51.76%] [G loss: 0.697218]
1/1 [==============================] - 0s 17ms/step
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3951 [D loss: 0.689986, acc.: 51.37%] [G loss: 0.699539]
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3952 [D loss: 0.689615, acc.: 53.91%] [G loss: 0.693249]
8/8 [==============================] - 0s 4ms/step
3953 [D loss: 0.693668, acc.: 50.98%] [G loss: 0.695775]
8/8 [==============================] - 0s 4ms/step
3954 [D loss: 0.692012, acc.: 53.71%] [G loss: 0.706205]
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3955 [D loss: 0.688437, acc.: 56.05%] [G loss: 0.701795]
8/8 [==============================] - 0s 4ms/step
3956 [D loss: 0.688781, acc.: 55.47%] [G loss: 0.701176]
8/8 [==============================] - 0s 4ms/step
3957 [D loss: 0.690069, acc.: 53.52%] [G loss: 0.703675]
8/8 [==============================] - 0s 4ms/step
3958 [D loss: 0.691952, acc.: 49.80%] [G loss: 0.695669]
8/8 [==============================] - 0s 4ms/step
3959 [D loss: 0.689539, acc.: 55.86%] [G loss: 0.696770]
8/8 [==============================] - 0s 4ms/step
3960 [D loss: 0.690586, acc.: 51.17%] [G loss: 0.702785]
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3961 [D loss: 0.689090, acc.: 54.30%] [G loss: 0.704582]
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3962 [D loss: 0.691920, acc.: 50.78%] [G loss: 0.699205]
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3963 [D loss: 0.688499, acc.: 55.27%] [G loss: 0.697906]
8/8 [==============================] - 0s 4ms/step
3964 [D loss: 0.691836, acc.: 53.12%] [G loss: 0.699934]
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3965 [D loss: 0.691283, acc.: 51.56%] [G loss: 0.702391]
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3966 [D loss: 0.687162, acc.: 56.64%] [G loss: 0.708106]
8/8 [==============================] - 0s 4ms/step
3967 [D loss: 0.687697, acc.: 55.47%] [G loss: 0.706733]
8/8 [==============================] - 0s 4ms/step
3968 [D loss: 0.687070, acc.: 54.88%] [G loss: 0.709158]
8/8 [==============================] - 0s 4ms/step
3969 [D loss: 0.686670, acc.: 55.86%] [G loss: 0.704845]
8/8 [==============================] - 0s 4ms/step
3970 [D loss: 0.692438, acc.: 52.93%] [G loss: 0.703825]
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3971 [D loss: 0.691379, acc.: 52.15%] [G loss: 0.698061]
8/8 [==============================] - 0s 4ms/step
3972 [D loss: 0.689113, acc.: 55.27%] [G loss: 0.693606]
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3973 [D loss: 0.692436, acc.: 51.95%] [G loss: 0.699817]
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3974 [D loss: 0.689355, acc.: 53.52%] [G loss: 0.703552]
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3975 [D loss: 0.688778, acc.: 52.93%] [G loss: 0.701272]
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3976 [D loss: 0.695889, acc.: 49.41%] [G loss: 0.695638]
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3977 [D loss: 0.694660, acc.: 49.61%] [G loss: 0.700890]
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3978 [D loss: 0.695506, acc.: 48.24%] [G loss: 0.699201]
8/8 [==============================] - 0s 4ms/step
3979 [D loss: 0.690872, acc.: 52.34%] [G loss: 0.703811]
8/8 [==============================] - 0s 4ms/step
3980 [D loss: 0.688770, acc.: 57.42%] [G loss: 0.709204]
8/8 [==============================] - 0s 4ms/step
3981 [D loss: 0.690670, acc.: 53.12%] [G loss: 0.705086]
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3982 [D loss: 0.692207, acc.: 52.73%] [G loss: 0.707334]
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3983 [D loss: 0.695971, acc.: 49.61%] [G loss: 0.707758]
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3984 [D loss: 0.693109, acc.: 52.93%] [G loss: 0.707174]
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3985 [D loss: 0.689081, acc.: 55.27%] [G loss: 0.703831]
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3986 [D loss: 0.685158, acc.: 59.77%] [G loss: 0.713612]
8/8 [==============================] - 0s 4ms/step
3987 [D loss: 0.684027, acc.: 57.42%] [G loss: 0.716185]
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3988 [D loss: 0.687364, acc.: 56.05%] [G loss: 0.711804]
8/8 [==============================] - 0s 4ms/step
3989 [D loss: 0.690402, acc.: 54.10%] [G loss: 0.709567]
8/8 [==============================] - 0s 4ms/step
3990 [D loss: 0.689993, acc.: 51.95%] [G loss: 0.707212]
8/8 [==============================] - 0s 4ms/step
3991 [D loss: 0.689133, acc.: 55.27%] [G loss: 0.706823]
8/8 [==============================] - 0s 4ms/step
3992 [D loss: 0.689094, acc.: 55.66%] [G loss: 0.713751]
8/8 [==============================] - 0s 4ms/step
3993 [D loss: 0.684183, acc.: 59.38%] [G loss: 0.710578]
8/8 [==============================] - 0s 4ms/step
3994 [D loss: 0.683083, acc.: 58.20%] [G loss: 0.711158]
8/8 [==============================] - 0s 4ms/step
3995 [D loss: 0.692908, acc.: 49.61%] [G loss: 0.708875]
8/8 [==============================] - 0s 4ms/step
3996 [D loss: 0.695692, acc.: 48.63%] [G loss: 0.694296]
8/8 [==============================] - 0s 4ms/step
3997 [D loss: 0.694175, acc.: 53.32%] [G loss: 0.698514]
8/8 [==============================] - 0s 4ms/step
3998 [D loss: 0.689962, acc.: 53.91%] [G loss: 0.696853]
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3999 [D loss: 0.687820, acc.: 54.69%] [G loss: 0.701968]
8/8 [==============================] - 0s 4ms/step
4000 [D loss: 0.687841, acc.: 56.25%] [G loss: 0.699714]
1/1 [==============================] - 0s 17ms/step
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4001 [D loss: 0.686366, acc.: 54.49%] [G loss: 0.701298]
8/8 [==============================] - 0s 4ms/step
4002 [D loss: 0.693567, acc.: 51.17%] [G loss: 0.698087]
8/8 [==============================] - 0s 4ms/step
4003 [D loss: 0.692175, acc.: 52.15%] [G loss: 0.698726]
8/8 [==============================] - 0s 4ms/step
4004 [D loss: 0.691298, acc.: 51.17%] [G loss: 0.705122]
8/8 [==============================] - 0s 4ms/step
4005 [D loss: 0.689646, acc.: 53.32%] [G loss: 0.703547]
8/8 [==============================] - 0s 4ms/step
4006 [D loss: 0.689624, acc.: 54.30%] [G loss: 0.700448]
8/8 [==============================] - 0s 4ms/step
4007 [D loss: 0.686424, acc.: 59.18%] [G loss: 0.698761]
8/8 [==============================] - 0s 4ms/step
4008 [D loss: 0.688384, acc.: 54.69%] [G loss: 0.708217]
8/8 [==============================] - 0s 4ms/step
4009 [D loss: 0.689552, acc.: 54.88%] [G loss: 0.707120]
8/8 [==============================] - 0s 4ms/step
4010 [D loss: 0.688249, acc.: 57.42%] [G loss: 0.705577]
8/8 [==============================] - 0s 4ms/step
4011 [D loss: 0.691813, acc.: 49.41%] [G loss: 0.704771]
8/8 [==============================] - 0s 4ms/step
4012 [D loss: 0.688873, acc.: 54.30%] [G loss: 0.707826]
8/8 [==============================] - 0s 4ms/step
4013 [D loss: 0.688627, acc.: 53.91%] [G loss: 0.710095]
8/8 [==============================] - 0s 4ms/step
4014 [D loss: 0.688998, acc.: 56.05%] [G loss: 0.712223]
8/8 [==============================] - 0s 4ms/step
4015 [D loss: 0.689476, acc.: 53.12%] [G loss: 0.703869]
8/8 [==============================] - 0s 4ms/step
4016 [D loss: 0.693346, acc.: 49.02%] [G loss: 0.698072]
8/8 [==============================] - 0s 4ms/step
4017 [D loss: 0.689244, acc.: 52.73%] [G loss: 0.702946]
8/8 [==============================] - 0s 4ms/step
4018 [D loss: 0.690065, acc.: 54.69%] [G loss: 0.703122]
8/8 [==============================] - 0s 4ms/step
4019 [D loss: 0.685134, acc.: 59.57%] [G loss: 0.706727]
8/8 [==============================] - 0s 4ms/step
4020 [D loss: 0.687713, acc.: 54.88%] [G loss: 0.707163]
8/8 [==============================] - 0s 4ms/step
4021 [D loss: 0.685129, acc.: 57.03%] [G loss: 0.711044]
8/8 [==============================] - 0s 4ms/step
4022 [D loss: 0.690694, acc.: 52.73%] [G loss: 0.703294]
8/8 [==============================] - 0s 4ms/step
4023 [D loss: 0.698466, acc.: 48.24%] [G loss: 0.702040]
8/8 [==============================] - 0s 4ms/step
4024 [D loss: 0.692914, acc.: 50.98%] [G loss: 0.705029]
8/8 [==============================] - 0s 4ms/step
4025 [D loss: 0.686834, acc.: 53.91%] [G loss: 0.703961]
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4026 [D loss: 0.684877, acc.: 58.01%] [G loss: 0.698323]
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4027 [D loss: 0.686926, acc.: 59.18%] [G loss: 0.707626]
8/8 [==============================] - 0s 4ms/step
4028 [D loss: 0.690351, acc.: 54.49%] [G loss: 0.705200]
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4029 [D loss: 0.695419, acc.: 50.59%] [G loss: 0.700400]
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4030 [D loss: 0.696544, acc.: 50.98%] [G loss: 0.707235]
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4031 [D loss: 0.688249, acc.: 56.05%] [G loss: 0.707865]
8/8 [==============================] - 0s 4ms/step
4032 [D loss: 0.684920, acc.: 57.23%] [G loss: 0.710985]
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4033 [D loss: 0.683289, acc.: 59.38%] [G loss: 0.712675]
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4034 [D loss: 0.686574, acc.: 57.42%] [G loss: 0.710938]
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4035 [D loss: 0.692203, acc.: 53.32%] [G loss: 0.702279]
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4036 [D loss: 0.692371, acc.: 50.59%] [G loss: 0.689788]
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4037 [D loss: 0.693671, acc.: 51.76%] [G loss: 0.685237]
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4038 [D loss: 0.692788, acc.: 53.32%] [G loss: 0.695984]
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4039 [D loss: 0.688879, acc.: 55.27%] [G loss: 0.697664]
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4040 [D loss: 0.690988, acc.: 53.91%] [G loss: 0.705745]
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4041 [D loss: 0.687081, acc.: 53.91%] [G loss: 0.713001]
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4042 [D loss: 0.689730, acc.: 55.08%] [G loss: 0.705097]
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4043 [D loss: 0.687355, acc.: 55.86%] [G loss: 0.707775]
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4044 [D loss: 0.687799, acc.: 54.10%] [G loss: 0.709942]
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4045 [D loss: 0.686957, acc.: 54.69%] [G loss: 0.707913]
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4046 [D loss: 0.687408, acc.: 56.05%] [G loss: 0.702993]
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4047 [D loss: 0.688767, acc.: 54.30%] [G loss: 0.702189]
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4048 [D loss: 0.689882, acc.: 54.30%] [G loss: 0.703287]
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4049 [D loss: 0.692745, acc.: 50.59%] [G loss: 0.701134]
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4050 [D loss: 0.691205, acc.: 48.05%] [G loss: 0.705381]
1/1 [==============================] - 0s 17ms/step
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4051 [D loss: 0.687996, acc.: 55.86%] [G loss: 0.708006]
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4052 [D loss: 0.687895, acc.: 54.30%] [G loss: 0.707527]
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4053 [D loss: 0.688850, acc.: 54.30%] [G loss: 0.706351]
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4054 [D loss: 0.692520, acc.: 51.76%] [G loss: 0.705026]
8/8 [==============================] - 0s 4ms/step
4055 [D loss: 0.692840, acc.: 52.15%] [G loss: 0.698768]
8/8 [==============================] - 0s 4ms/step
4056 [D loss: 0.695179, acc.: 48.63%] [G loss: 0.705759]
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4057 [D loss: 0.695990, acc.: 49.41%] [G loss: 0.706857]
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4058 [D loss: 0.690164, acc.: 53.32%] [G loss: 0.704849]
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4059 [D loss: 0.694380, acc.: 47.85%] [G loss: 0.702514]
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4060 [D loss: 0.690832, acc.: 53.32%] [G loss: 0.710749]
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4061 [D loss: 0.690337, acc.: 55.47%] [G loss: 0.710104]
8/8 [==============================] - 0s 4ms/step
4062 [D loss: 0.692610, acc.: 53.52%] [G loss: 0.712333]
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4063 [D loss: 0.686739, acc.: 58.20%] [G loss: 0.705061]
8/8 [==============================] - 0s 4ms/step
4064 [D loss: 0.690801, acc.: 50.98%] [G loss: 0.708597]
8/8 [==============================] - 0s 4ms/step
4065 [D loss: 0.688011, acc.: 56.25%] [G loss: 0.708854]
8/8 [==============================] - 0s 4ms/step
4066 [D loss: 0.690452, acc.: 52.93%] [G loss: 0.704836]
8/8 [==============================] - 0s 4ms/step
4067 [D loss: 0.684990, acc.: 57.42%] [G loss: 0.705538]
8/8 [==============================] - 0s 4ms/step
4068 [D loss: 0.688409, acc.: 55.47%] [G loss: 0.706045]
8/8 [==============================] - 0s 4ms/step
4069 [D loss: 0.687399, acc.: 56.84%] [G loss: 0.711392]
8/8 [==============================] - 0s 4ms/step
4070 [D loss: 0.689009, acc.: 55.08%] [G loss: 0.708046]
8/8 [==============================] - 0s 4ms/step
4071 [D loss: 0.687211, acc.: 52.93%] [G loss: 0.711811]
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4072 [D loss: 0.685654, acc.: 56.25%] [G loss: 0.703510]
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4073 [D loss: 0.687835, acc.: 54.49%] [G loss: 0.703229]
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4074 [D loss: 0.688869, acc.: 55.86%] [G loss: 0.706788]
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4075 [D loss: 0.692104, acc.: 53.71%] [G loss: 0.700577]
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4076 [D loss: 0.690772, acc.: 51.56%] [G loss: 0.694035]
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4077 [D loss: 0.689193, acc.: 53.91%] [G loss: 0.693953]
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4078 [D loss: 0.688451, acc.: 55.08%] [G loss: 0.697788]
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4079 [D loss: 0.691595, acc.: 52.34%] [G loss: 0.700091]
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4080 [D loss: 0.688574, acc.: 55.27%] [G loss: 0.695393]
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4081 [D loss: 0.688903, acc.: 54.88%] [G loss: 0.700019]
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4082 [D loss: 0.689943, acc.: 53.91%] [G loss: 0.700962]
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4083 [D loss: 0.691239, acc.: 50.20%] [G loss: 0.693575]
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4084 [D loss: 0.686669, acc.: 56.64%] [G loss: 0.698960]
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4085 [D loss: 0.691819, acc.: 51.37%] [G loss: 0.701083]
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4086 [D loss: 0.692965, acc.: 50.20%] [G loss: 0.699134]
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4087 [D loss: 0.690220, acc.: 52.15%] [G loss: 0.700193]
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4088 [D loss: 0.688354, acc.: 53.52%] [G loss: 0.702747]
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4089 [D loss: 0.687242, acc.: 54.49%] [G loss: 0.700565]
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4090 [D loss: 0.689273, acc.: 54.69%] [G loss: 0.702725]
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4091 [D loss: 0.690876, acc.: 53.71%] [G loss: 0.703635]
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4092 [D loss: 0.690504, acc.: 50.39%] [G loss: 0.702047]
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4093 [D loss: 0.689396, acc.: 54.10%] [G loss: 0.702382]
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4094 [D loss: 0.690158, acc.: 56.05%] [G loss: 0.704296]
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4095 [D loss: 0.694093, acc.: 51.37%] [G loss: 0.710073]
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4096 [D loss: 0.691675, acc.: 49.41%] [G loss: 0.703625]
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4097 [D loss: 0.692842, acc.: 50.20%] [G loss: 0.708993]
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4098 [D loss: 0.687206, acc.: 57.23%] [G loss: 0.715898]
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4099 [D loss: 0.690641, acc.: 53.12%] [G loss: 0.712340]
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4100 [D loss: 0.689653, acc.: 55.08%] [G loss: 0.714094]
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4101 [D loss: 0.689800, acc.: 54.49%] [G loss: 0.713928]
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4102 [D loss: 0.688075, acc.: 53.52%] [G loss: 0.709358]
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4103 [D loss: 0.690094, acc.: 52.73%] [G loss: 0.709110]
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4104 [D loss: 0.687931, acc.: 54.10%] [G loss: 0.705347]
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4105 [D loss: 0.685138, acc.: 58.20%] [G loss: 0.706554]
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4106 [D loss: 0.688755, acc.: 56.05%] [G loss: 0.706630]
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4107 [D loss: 0.690806, acc.: 54.10%] [G loss: 0.707621]
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4108 [D loss: 0.689161, acc.: 55.47%] [G loss: 0.696598]
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4109 [D loss: 0.688203, acc.: 56.84%] [G loss: 0.706768]
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4110 [D loss: 0.689395, acc.: 53.52%] [G loss: 0.701789]
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4111 [D loss: 0.684812, acc.: 58.79%] [G loss: 0.699417]
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4112 [D loss: 0.689109, acc.: 52.54%] [G loss: 0.694382]
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4113 [D loss: 0.696755, acc.: 50.00%] [G loss: 0.700761]
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4114 [D loss: 0.694943, acc.: 53.12%] [G loss: 0.694298]
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4115 [D loss: 0.692345, acc.: 50.78%] [G loss: 0.700732]
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4116 [D loss: 0.687376, acc.: 53.52%] [G loss: 0.701356]
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4117 [D loss: 0.693682, acc.: 51.56%] [G loss: 0.703013]
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4118 [D loss: 0.688616, acc.: 52.73%] [G loss: 0.698793]
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4119 [D loss: 0.686956, acc.: 56.25%] [G loss: 0.699418]
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4120 [D loss: 0.688838, acc.: 52.93%] [G loss: 0.699521]
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4121 [D loss: 0.682336, acc.: 58.98%] [G loss: 0.705003]
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4122 [D loss: 0.691705, acc.: 51.56%] [G loss: 0.707955]
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4123 [D loss: 0.686236, acc.: 56.45%] [G loss: 0.702586]
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4124 [D loss: 0.694708, acc.: 47.85%] [G loss: 0.698999]
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4125 [D loss: 0.693396, acc.: 50.78%] [G loss: 0.696321]
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4126 [D loss: 0.693396, acc.: 50.78%] [G loss: 0.697885]
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4127 [D loss: 0.692071, acc.: 52.34%] [G loss: 0.702320]
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4128 [D loss: 0.686221, acc.: 58.79%] [G loss: 0.706648]
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4129 [D loss: 0.691349, acc.: 51.95%] [G loss: 0.706312]
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4130 [D loss: 0.692520, acc.: 52.34%] [G loss: 0.704069]
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4131 [D loss: 0.691100, acc.: 52.34%] [G loss: 0.701655]
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4132 [D loss: 0.686232, acc.: 57.62%] [G loss: 0.710707]
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4133 [D loss: 0.687354, acc.: 57.81%] [G loss: 0.710705]
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4134 [D loss: 0.688921, acc.: 56.64%] [G loss: 0.712276]
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4135 [D loss: 0.683673, acc.: 58.40%] [G loss: 0.714163]
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4136 [D loss: 0.690592, acc.: 52.93%] [G loss: 0.707476]
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4137 [D loss: 0.691438, acc.: 50.59%] [G loss: 0.706948]
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4138 [D loss: 0.690862, acc.: 56.05%] [G loss: 0.709126]
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4139 [D loss: 0.690009, acc.: 50.98%] [G loss: 0.708251]
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4140 [D loss: 0.689255, acc.: 51.56%] [G loss: 0.709237]
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4141 [D loss: 0.686172, acc.: 57.23%] [G loss: 0.708647]
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4142 [D loss: 0.690845, acc.: 50.98%] [G loss: 0.709321]
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4143 [D loss: 0.688918, acc.: 52.15%] [G loss: 0.708325]
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4144 [D loss: 0.693809, acc.: 50.39%] [G loss: 0.702380]
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4145 [D loss: 0.688659, acc.: 54.10%] [G loss: 0.705874]
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4146 [D loss: 0.688470, acc.: 53.12%] [G loss: 0.706312]
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4147 [D loss: 0.686524, acc.: 58.79%] [G loss: 0.709157]
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4148 [D loss: 0.687918, acc.: 54.69%] [G loss: 0.707627]
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4149 [D loss: 0.688308, acc.: 54.49%] [G loss: 0.704296]
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4150 [D loss: 0.693823, acc.: 50.39%] [G loss: 0.701936]
1/1 [==============================] - 0s 21ms/step
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4151 [D loss: 0.691187, acc.: 51.56%] [G loss: 0.699787]
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4152 [D loss: 0.692101, acc.: 52.73%] [G loss: 0.698615]
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4153 [D loss: 0.690774, acc.: 54.69%] [G loss: 0.707344]
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4154 [D loss: 0.685775, acc.: 56.05%] [G loss: 0.712458]
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4155 [D loss: 0.684780, acc.: 58.59%] [G loss: 0.711225]
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4156 [D loss: 0.687103, acc.: 56.84%] [G loss: 0.713938]
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4157 [D loss: 0.685935, acc.: 58.20%] [G loss: 0.702557]
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4158 [D loss: 0.688368, acc.: 53.32%] [G loss: 0.699060]
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4159 [D loss: 0.692554, acc.: 53.32%] [G loss: 0.700847]
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4160 [D loss: 0.691282, acc.: 51.37%] [G loss: 0.705013]
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4161 [D loss: 0.692064, acc.: 50.98%] [G loss: 0.699461]
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4162 [D loss: 0.694339, acc.: 49.61%] [G loss: 0.698012]
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4163 [D loss: 0.691466, acc.: 52.34%] [G loss: 0.707008]
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4164 [D loss: 0.692276, acc.: 52.15%] [G loss: 0.702088]
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4165 [D loss: 0.689647, acc.: 52.34%] [G loss: 0.702839]
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4166 [D loss: 0.689002, acc.: 53.12%] [G loss: 0.698556]
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4167 [D loss: 0.692420, acc.: 53.12%] [G loss: 0.702874]
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4168 [D loss: 0.684673, acc.: 58.98%] [G loss: 0.707131]
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4169 [D loss: 0.689296, acc.: 59.38%] [G loss: 0.705448]
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4170 [D loss: 0.687618, acc.: 51.56%] [G loss: 0.704985]
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4171 [D loss: 0.684415, acc.: 58.20%] [G loss: 0.706539]
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4172 [D loss: 0.691122, acc.: 53.12%] [G loss: 0.703292]
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4173 [D loss: 0.690921, acc.: 54.49%] [G loss: 0.712335]
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4174 [D loss: 0.691453, acc.: 50.39%] [G loss: 0.706629]
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4175 [D loss: 0.686703, acc.: 56.45%] [G loss: 0.706309]
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4176 [D loss: 0.689490, acc.: 54.49%] [G loss: 0.707847]
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4177 [D loss: 0.689483, acc.: 52.73%] [G loss: 0.707541]
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4178 [D loss: 0.688875, acc.: 54.88%] [G loss: 0.701894]
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4179 [D loss: 0.689987, acc.: 53.91%] [G loss: 0.702725]
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4180 [D loss: 0.690781, acc.: 51.56%] [G loss: 0.701145]
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4181 [D loss: 0.691773, acc.: 51.76%] [G loss: 0.703886]
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4182 [D loss: 0.688463, acc.: 54.69%] [G loss: 0.705272]
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4183 [D loss: 0.692148, acc.: 51.17%] [G loss: 0.707784]
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4184 [D loss: 0.689655, acc.: 53.71%] [G loss: 0.698965]
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4185 [D loss: 0.696526, acc.: 46.29%] [G loss: 0.701800]
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4186 [D loss: 0.695292, acc.: 49.41%] [G loss: 0.700407]
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4187 [D loss: 0.694950, acc.: 50.98%] [G loss: 0.709094]
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4188 [D loss: 0.684709, acc.: 56.45%] [G loss: 0.720483]
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4189 [D loss: 0.680441, acc.: 61.91%] [G loss: 0.717173]
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4190 [D loss: 0.682754, acc.: 59.77%] [G loss: 0.722338]
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4191 [D loss: 0.682764, acc.: 58.98%] [G loss: 0.711264]
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4192 [D loss: 0.685219, acc.: 55.86%] [G loss: 0.705402]
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4193 [D loss: 0.694519, acc.: 52.15%] [G loss: 0.695026]
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4194 [D loss: 0.695970, acc.: 50.59%] [G loss: 0.696675]
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4195 [D loss: 0.691953, acc.: 51.95%] [G loss: 0.692929]
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4196 [D loss: 0.691726, acc.: 51.76%] [G loss: 0.699775]
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4197 [D loss: 0.689159, acc.: 54.30%] [G loss: 0.701150]
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4198 [D loss: 0.691343, acc.: 52.54%] [G loss: 0.706106]
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4199 [D loss: 0.691369, acc.: 51.37%] [G loss: 0.705849]
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4200 [D loss: 0.692438, acc.: 54.88%] [G loss: 0.708209]
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4201 [D loss: 0.690460, acc.: 53.71%] [G loss: 0.697705]
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4202 [D loss: 0.692823, acc.: 51.17%] [G loss: 0.704473]
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4203 [D loss: 0.691062, acc.: 50.59%] [G loss: 0.702674]
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4204 [D loss: 0.691595, acc.: 55.86%] [G loss: 0.711834]
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4205 [D loss: 0.691573, acc.: 50.00%] [G loss: 0.707843]
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4206 [D loss: 0.691457, acc.: 53.52%] [G loss: 0.706347]
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4207 [D loss: 0.689602, acc.: 54.69%] [G loss: 0.708694]
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4208 [D loss: 0.689998, acc.: 52.34%] [G loss: 0.708733]
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4209 [D loss: 0.685884, acc.: 55.66%] [G loss: 0.706158]
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4210 [D loss: 0.685072, acc.: 58.01%] [G loss: 0.711075]
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4211 [D loss: 0.683166, acc.: 57.42%] [G loss: 0.711650]
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4212 [D loss: 0.680998, acc.: 59.96%] [G loss: 0.719289]
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4213 [D loss: 0.687956, acc.: 54.30%] [G loss: 0.710310]
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4214 [D loss: 0.688099, acc.: 54.69%] [G loss: 0.716110]
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4215 [D loss: 0.687133, acc.: 57.23%] [G loss: 0.712522]
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4216 [D loss: 0.689072, acc.: 53.12%] [G loss: 0.712655]
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4217 [D loss: 0.688212, acc.: 55.08%] [G loss: 0.710171]
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4218 [D loss: 0.691451, acc.: 51.76%] [G loss: 0.709016]
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4219 [D loss: 0.691934, acc.: 53.52%] [G loss: 0.712244]
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4220 [D loss: 0.688660, acc.: 54.88%] [G loss: 0.714137]
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4221 [D loss: 0.688365, acc.: 54.88%] [G loss: 0.706904]
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4222 [D loss: 0.692462, acc.: 53.71%] [G loss: 0.698681]
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4223 [D loss: 0.685370, acc.: 57.23%] [G loss: 0.700618]
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4224 [D loss: 0.691978, acc.: 50.20%] [G loss: 0.696540]
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4225 [D loss: 0.686776, acc.: 56.64%] [G loss: 0.702245]
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4226 [D loss: 0.684296, acc.: 57.62%] [G loss: 0.704432]
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4227 [D loss: 0.688075, acc.: 56.05%] [G loss: 0.697702]
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4228 [D loss: 0.684698, acc.: 56.45%] [G loss: 0.700403]
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4229 [D loss: 0.691943, acc.: 51.56%] [G loss: 0.703155]
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4230 [D loss: 0.687138, acc.: 57.42%] [G loss: 0.708853]
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4231 [D loss: 0.692065, acc.: 52.93%] [G loss: 0.700044]
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4232 [D loss: 0.697611, acc.: 49.61%] [G loss: 0.698065]
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4233 [D loss: 0.688669, acc.: 55.08%] [G loss: 0.708893]
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4234 [D loss: 0.690540, acc.: 51.17%] [G loss: 0.704200]
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4235 [D loss: 0.687799, acc.: 54.10%] [G loss: 0.708870]
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4236 [D loss: 0.686999, acc.: 56.45%] [G loss: 0.704386]
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4237 [D loss: 0.688260, acc.: 54.49%] [G loss: 0.706859]
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4238 [D loss: 0.695872, acc.: 49.02%] [G loss: 0.710700]
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4239 [D loss: 0.692980, acc.: 49.41%] [G loss: 0.703537]
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4240 [D loss: 0.691664, acc.: 54.10%] [G loss: 0.695441]
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4241 [D loss: 0.692005, acc.: 53.52%] [G loss: 0.703803]
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4242 [D loss: 0.689582, acc.: 52.73%] [G loss: 0.703780]
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4243 [D loss: 0.687053, acc.: 54.88%] [G loss: 0.703874]
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4244 [D loss: 0.689661, acc.: 54.88%] [G loss: 0.707363]
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4245 [D loss: 0.689746, acc.: 54.30%] [G loss: 0.700887]
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4246 [D loss: 0.687714, acc.: 55.47%] [G loss: 0.709539]
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4247 [D loss: 0.690181, acc.: 55.66%] [G loss: 0.706972]
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4248 [D loss: 0.683175, acc.: 57.81%] [G loss: 0.711416]
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4249 [D loss: 0.686283, acc.: 57.62%] [G loss: 0.711175]
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4250 [D loss: 0.690860, acc.: 53.71%] [G loss: 0.710929]
1/1 [==============================] - 0s 16ms/step
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4251 [D loss: 0.690189, acc.: 53.12%] [G loss: 0.703147]
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4252 [D loss: 0.690067, acc.: 52.54%] [G loss: 0.715717]
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4253 [D loss: 0.689392, acc.: 53.12%] [G loss: 0.710922]
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4254 [D loss: 0.691051, acc.: 52.34%] [G loss: 0.714850]
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4255 [D loss: 0.686613, acc.: 55.47%] [G loss: 0.705667]
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4256 [D loss: 0.693150, acc.: 48.83%] [G loss: 0.703666]
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4257 [D loss: 0.691085, acc.: 51.56%] [G loss: 0.697672]
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4258 [D loss: 0.694750, acc.: 50.98%] [G loss: 0.702918]
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4259 [D loss: 0.690107, acc.: 54.88%] [G loss: 0.706711]
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4260 [D loss: 0.686951, acc.: 56.25%] [G loss: 0.705190]
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4261 [D loss: 0.687293, acc.: 56.45%] [G loss: 0.707764]
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4262 [D loss: 0.684901, acc.: 56.45%] [G loss: 0.702998]
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4263 [D loss: 0.687233, acc.: 57.03%] [G loss: 0.705231]
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4264 [D loss: 0.688398, acc.: 55.47%] [G loss: 0.705188]
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4265 [D loss: 0.684837, acc.: 59.18%] [G loss: 0.709447]
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4266 [D loss: 0.686660, acc.: 55.66%] [G loss: 0.713078]
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4267 [D loss: 0.684386, acc.: 57.03%] [G loss: 0.709375]
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4268 [D loss: 0.693871, acc.: 49.80%] [G loss: 0.705535]
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4269 [D loss: 0.683809, acc.: 56.25%] [G loss: 0.711487]
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4270 [D loss: 0.688334, acc.: 52.73%] [G loss: 0.712303]
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4271 [D loss: 0.689990, acc.: 54.49%] [G loss: 0.710522]
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4272 [D loss: 0.687787, acc.: 54.49%] [G loss: 0.710411]
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4273 [D loss: 0.687296, acc.: 57.42%] [G loss: 0.707133]
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4274 [D loss: 0.691376, acc.: 52.54%] [G loss: 0.701411]
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4275 [D loss: 0.686033, acc.: 55.47%] [G loss: 0.701274]
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4276 [D loss: 0.694969, acc.: 50.00%] [G loss: 0.708079]
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4277 [D loss: 0.691532, acc.: 51.17%] [G loss: 0.707401]
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4278 [D loss: 0.689448, acc.: 54.10%] [G loss: 0.703631]
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4279 [D loss: 0.682133, acc.: 59.57%] [G loss: 0.704931]
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4280 [D loss: 0.686767, acc.: 55.47%] [G loss: 0.705852]
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4281 [D loss: 0.687515, acc.: 54.49%] [G loss: 0.709420]
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4282 [D loss: 0.687810, acc.: 54.88%] [G loss: 0.714314]
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4283 [D loss: 0.686736, acc.: 54.10%] [G loss: 0.702933]
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4284 [D loss: 0.689163, acc.: 52.34%] [G loss: 0.707188]
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4285 [D loss: 0.691711, acc.: 48.63%] [G loss: 0.702792]
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4286 [D loss: 0.692317, acc.: 51.95%] [G loss: 0.709838]
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4287 [D loss: 0.686902, acc.: 56.64%] [G loss: 0.702301]
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4288 [D loss: 0.687602, acc.: 54.88%] [G loss: 0.715384]
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4289 [D loss: 0.687243, acc.: 54.49%] [G loss: 0.713025]
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4290 [D loss: 0.689745, acc.: 52.73%] [G loss: 0.704568]
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4291 [D loss: 0.689301, acc.: 55.47%] [G loss: 0.714708]
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4292 [D loss: 0.689314, acc.: 53.91%] [G loss: 0.711408]
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4293 [D loss: 0.689337, acc.: 52.34%] [G loss: 0.704300]
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4294 [D loss: 0.688198, acc.: 53.52%] [G loss: 0.712847]
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4295 [D loss: 0.689843, acc.: 52.54%] [G loss: 0.703554]
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4296 [D loss: 0.687246, acc.: 56.05%] [G loss: 0.703328]
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4297 [D loss: 0.681374, acc.: 57.81%] [G loss: 0.710290]
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4298 [D loss: 0.685440, acc.: 56.25%] [G loss: 0.707277]
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4299 [D loss: 0.689604, acc.: 52.15%] [G loss: 0.710379]
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4300 [D loss: 0.686234, acc.: 57.81%] [G loss: 0.698289]
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4301 [D loss: 0.687258, acc.: 56.05%] [G loss: 0.707465]
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4302 [D loss: 0.685880, acc.: 57.42%] [G loss: 0.709684]
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4303 [D loss: 0.685665, acc.: 57.62%] [G loss: 0.712898]
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4304 [D loss: 0.683031, acc.: 57.03%] [G loss: 0.717780]
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4305 [D loss: 0.687926, acc.: 54.49%] [G loss: 0.709464]
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4306 [D loss: 0.689593, acc.: 54.10%] [G loss: 0.709257]
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4307 [D loss: 0.696336, acc.: 50.98%] [G loss: 0.710805]
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4308 [D loss: 0.698286, acc.: 49.22%] [G loss: 0.698088]
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4309 [D loss: 0.689384, acc.: 56.05%] [G loss: 0.702596]
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4310 [D loss: 0.685965, acc.: 54.69%] [G loss: 0.713981]
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4311 [D loss: 0.690565, acc.: 52.34%] [G loss: 0.701183]
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4312 [D loss: 0.693395, acc.: 51.76%] [G loss: 0.698851]
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4313 [D loss: 0.689842, acc.: 53.32%] [G loss: 0.703905]
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4314 [D loss: 0.690803, acc.: 54.69%] [G loss: 0.698433]
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4315 [D loss: 0.689368, acc.: 50.98%] [G loss: 0.704333]
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4316 [D loss: 0.691632, acc.: 55.66%] [G loss: 0.707958]
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4317 [D loss: 0.682358, acc.: 58.40%] [G loss: 0.711708]
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4318 [D loss: 0.687342, acc.: 56.84%] [G loss: 0.701710]
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4319 [D loss: 0.690235, acc.: 54.10%] [G loss: 0.702284]
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4320 [D loss: 0.692380, acc.: 52.34%] [G loss: 0.707056]
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4321 [D loss: 0.687738, acc.: 52.15%] [G loss: 0.706796]
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4322 [D loss: 0.689556, acc.: 53.91%] [G loss: 0.711620]
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4323 [D loss: 0.687579, acc.: 53.52%] [G loss: 0.720062]
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4324 [D loss: 0.685903, acc.: 54.49%] [G loss: 0.710103]
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4325 [D loss: 0.684939, acc.: 54.88%] [G loss: 0.713806]
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4326 [D loss: 0.688177, acc.: 53.12%] [G loss: 0.710110]
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4327 [D loss: 0.692838, acc.: 51.56%] [G loss: 0.705880]
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4328 [D loss: 0.692507, acc.: 50.00%] [G loss: 0.703735]
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4329 [D loss: 0.686623, acc.: 56.45%] [G loss: 0.713639]
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4330 [D loss: 0.684673, acc.: 58.98%] [G loss: 0.720665]
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4331 [D loss: 0.683845, acc.: 57.42%] [G loss: 0.715504]
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4332 [D loss: 0.686133, acc.: 54.88%] [G loss: 0.710670]
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4333 [D loss: 0.699661, acc.: 50.00%] [G loss: 0.700781]
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4334 [D loss: 0.700116, acc.: 47.66%] [G loss: 0.701309]
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4335 [D loss: 0.693874, acc.: 52.34%] [G loss: 0.711195]
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4336 [D loss: 0.683494, acc.: 59.96%] [G loss: 0.717054]
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4337 [D loss: 0.680905, acc.: 60.16%] [G loss: 0.725503]
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4338 [D loss: 0.681983, acc.: 60.55%] [G loss: 0.718904]
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4339 [D loss: 0.679157, acc.: 60.35%] [G loss: 0.713838]
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4340 [D loss: 0.686625, acc.: 54.69%] [G loss: 0.699234]
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4341 [D loss: 0.690441, acc.: 53.71%] [G loss: 0.702425]
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4342 [D loss: 0.689717, acc.: 54.88%] [G loss: 0.697744]
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4343 [D loss: 0.690238, acc.: 51.56%] [G loss: 0.704275]
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4344 [D loss: 0.690288, acc.: 55.08%] [G loss: 0.714118]
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4345 [D loss: 0.691295, acc.: 50.59%] [G loss: 0.710292]
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4346 [D loss: 0.687121, acc.: 56.25%] [G loss: 0.719004]
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4347 [D loss: 0.687308, acc.: 54.69%] [G loss: 0.723056]
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4348 [D loss: 0.691117, acc.: 52.15%] [G loss: 0.717457]
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4349 [D loss: 0.693928, acc.: 50.20%] [G loss: 0.709231]
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4350 [D loss: 0.694099, acc.: 52.93%] [G loss: 0.703165]
1/1 [==============================] - 0s 17ms/step
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4351 [D loss: 0.686860, acc.: 57.03%] [G loss: 0.710695]
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4352 [D loss: 0.683939, acc.: 59.96%] [G loss: 0.706849]
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4353 [D loss: 0.682430, acc.: 61.13%] [G loss: 0.710185]
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4354 [D loss: 0.683091, acc.: 59.57%] [G loss: 0.710428]
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4355 [D loss: 0.689297, acc.: 53.91%] [G loss: 0.704633]
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4356 [D loss: 0.685100, acc.: 57.03%] [G loss: 0.714347]
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4357 [D loss: 0.683522, acc.: 57.23%] [G loss: 0.715261]
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4358 [D loss: 0.681573, acc.: 60.35%] [G loss: 0.716972]
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4359 [D loss: 0.682665, acc.: 55.66%] [G loss: 0.715606]
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4360 [D loss: 0.683959, acc.: 57.03%] [G loss: 0.714908]
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4361 [D loss: 0.685725, acc.: 57.62%] [G loss: 0.705746]
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4362 [D loss: 0.694076, acc.: 49.02%] [G loss: 0.700955]
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4363 [D loss: 0.692778, acc.: 50.20%] [G loss: 0.707933]
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4364 [D loss: 0.690764, acc.: 55.66%] [G loss: 0.717237]
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4365 [D loss: 0.686641, acc.: 54.30%] [G loss: 0.716056]
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4366 [D loss: 0.691013, acc.: 51.17%] [G loss: 0.707984]
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4367 [D loss: 0.694199, acc.: 51.37%] [G loss: 0.702829]
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4368 [D loss: 0.689682, acc.: 53.32%] [G loss: 0.707644]
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4369 [D loss: 0.699895, acc.: 46.48%] [G loss: 0.706655]
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4370 [D loss: 0.697915, acc.: 48.44%] [G loss: 0.706147]
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4371 [D loss: 0.686355, acc.: 56.84%] [G loss: 0.708458]
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4372 [D loss: 0.686050, acc.: 57.03%] [G loss: 0.715313]
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4373 [D loss: 0.688066, acc.: 53.91%] [G loss: 0.724098]
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4374 [D loss: 0.689420, acc.: 53.32%] [G loss: 0.712100]
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4375 [D loss: 0.688451, acc.: 53.91%] [G loss: 0.712206]
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4376 [D loss: 0.685184, acc.: 58.79%] [G loss: 0.711186]
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4377 [D loss: 0.679513, acc.: 60.74%] [G loss: 0.722967]
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4378 [D loss: 0.682092, acc.: 57.23%] [G loss: 0.726645]
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4379 [D loss: 0.677284, acc.: 61.13%] [G loss: 0.726812]
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4380 [D loss: 0.681363, acc.: 59.96%] [G loss: 0.701277]
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4381 [D loss: 0.690434, acc.: 53.91%] [G loss: 0.703043]
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4382 [D loss: 0.692194, acc.: 51.76%] [G loss: 0.707308]
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4383 [D loss: 0.689672, acc.: 54.88%] [G loss: 0.708395]
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4384 [D loss: 0.687268, acc.: 57.23%] [G loss: 0.715463]
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4385 [D loss: 0.685459, acc.: 57.42%] [G loss: 0.722989]
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4386 [D loss: 0.681192, acc.: 58.40%] [G loss: 0.717232]
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4387 [D loss: 0.683542, acc.: 56.25%] [G loss: 0.713019]
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4388 [D loss: 0.689555, acc.: 53.12%] [G loss: 0.717193]
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4389 [D loss: 0.693752, acc.: 51.37%] [G loss: 0.711205]
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4390 [D loss: 0.691302, acc.: 54.49%] [G loss: 0.711947]
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4391 [D loss: 0.685377, acc.: 57.03%] [G loss: 0.704545]
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4392 [D loss: 0.690990, acc.: 53.52%] [G loss: 0.706310]
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4393 [D loss: 0.689751, acc.: 51.95%] [G loss: 0.708272]
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4394 [D loss: 0.684629, acc.: 56.45%] [G loss: 0.711887]
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4395 [D loss: 0.693076, acc.: 48.83%] [G loss: 0.709131]
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4396 [D loss: 0.689753, acc.: 53.91%] [G loss: 0.713654]
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4397 [D loss: 0.687017, acc.: 54.88%] [G loss: 0.703228]
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4398 [D loss: 0.690191, acc.: 50.98%] [G loss: 0.706266]
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4399 [D loss: 0.691239, acc.: 53.32%] [G loss: 0.713543]
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4400 [D loss: 0.688060, acc.: 55.66%] [G loss: 0.700023]
1/1 [==============================] - 0s 17ms/step
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4401 [D loss: 0.687769, acc.: 56.05%] [G loss: 0.704131]
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4402 [D loss: 0.688605, acc.: 50.78%] [G loss: 0.707118]
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4403 [D loss: 0.691677, acc.: 51.95%] [G loss: 0.711572]
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4404 [D loss: 0.687892, acc.: 53.91%] [G loss: 0.703367]
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4405 [D loss: 0.687239, acc.: 56.64%] [G loss: 0.713204]
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4406 [D loss: 0.685298, acc.: 58.40%] [G loss: 0.717644]
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4407 [D loss: 0.682159, acc.: 59.38%] [G loss: 0.721229]
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4408 [D loss: 0.685625, acc.: 56.25%] [G loss: 0.713684]
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4409 [D loss: 0.686819, acc.: 56.05%] [G loss: 0.716374]
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4410 [D loss: 0.685615, acc.: 57.23%] [G loss: 0.712679]
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4411 [D loss: 0.686134, acc.: 54.49%] [G loss: 0.718288]
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4412 [D loss: 0.686974, acc.: 55.86%] [G loss: 0.697693]
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4413 [D loss: 0.688974, acc.: 53.12%] [G loss: 0.710773]
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4414 [D loss: 0.690109, acc.: 55.66%] [G loss: 0.700673]
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4415 [D loss: 0.691851, acc.: 51.17%] [G loss: 0.703482]
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4416 [D loss: 0.694807, acc.: 51.37%] [G loss: 0.704640]
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4417 [D loss: 0.688100, acc.: 55.08%] [G loss: 0.712044]
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4418 [D loss: 0.686244, acc.: 56.84%] [G loss: 0.702121]
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4419 [D loss: 0.688917, acc.: 54.69%] [G loss: 0.702576]
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4420 [D loss: 0.688582, acc.: 55.27%] [G loss: 0.695203]
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4421 [D loss: 0.694379, acc.: 49.80%] [G loss: 0.694188]
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4422 [D loss: 0.692467, acc.: 53.12%] [G loss: 0.701962]
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4423 [D loss: 0.686219, acc.: 58.01%] [G loss: 0.696793]
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4424 [D loss: 0.690583, acc.: 51.95%] [G loss: 0.709145]
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4425 [D loss: 0.684193, acc.: 57.81%] [G loss: 0.715118]
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4426 [D loss: 0.686069, acc.: 56.25%] [G loss: 0.721486]
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4427 [D loss: 0.687620, acc.: 54.30%] [G loss: 0.725692]
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4428 [D loss: 0.681029, acc.: 57.03%] [G loss: 0.722585]
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4429 [D loss: 0.684191, acc.: 58.01%] [G loss: 0.723781]
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4430 [D loss: 0.677939, acc.: 59.18%] [G loss: 0.716076]
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4431 [D loss: 0.683205, acc.: 57.42%] [G loss: 0.718016]
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4432 [D loss: 0.685546, acc.: 54.69%] [G loss: 0.714598]
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4433 [D loss: 0.685214, acc.: 57.23%] [G loss: 0.713889]
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4434 [D loss: 0.687559, acc.: 55.47%] [G loss: 0.702903]
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4435 [D loss: 0.690217, acc.: 53.91%] [G loss: 0.696746]
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4436 [D loss: 0.694362, acc.: 49.22%] [G loss: 0.708409]
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4437 [D loss: 0.689537, acc.: 53.32%] [G loss: 0.719037]
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4438 [D loss: 0.689635, acc.: 52.93%] [G loss: 0.703396]
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4439 [D loss: 0.695412, acc.: 49.22%] [G loss: 0.702893]
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4440 [D loss: 0.691890, acc.: 53.91%] [G loss: 0.707123]
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4441 [D loss: 0.690780, acc.: 52.93%] [G loss: 0.701589]
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4442 [D loss: 0.689388, acc.: 54.49%] [G loss: 0.704644]
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4443 [D loss: 0.692125, acc.: 54.30%] [G loss: 0.708576]
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4444 [D loss: 0.686805, acc.: 56.45%] [G loss: 0.704493]
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4445 [D loss: 0.685893, acc.: 54.30%] [G loss: 0.717201]
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4446 [D loss: 0.685371, acc.: 55.47%] [G loss: 0.714212]
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4447 [D loss: 0.685165, acc.: 55.27%] [G loss: 0.715642]
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4448 [D loss: 0.684013, acc.: 57.03%] [G loss: 0.711469]
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4449 [D loss: 0.687528, acc.: 53.32%] [G loss: 0.716926]
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4450 [D loss: 0.684844, acc.: 56.05%] [G loss: 0.712781]
1/1 [==============================] - 0s 17ms/step
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4451 [D loss: 0.681336, acc.: 60.16%] [G loss: 0.708886]
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4452 [D loss: 0.688990, acc.: 53.71%] [G loss: 0.713036]
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4453 [D loss: 0.685890, acc.: 54.88%] [G loss: 0.705877]
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4454 [D loss: 0.687971, acc.: 53.52%] [G loss: 0.714720]
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4455 [D loss: 0.683792, acc.: 58.01%] [G loss: 0.708540]
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4456 [D loss: 0.682327, acc.: 55.66%] [G loss: 0.711357]
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4457 [D loss: 0.685131, acc.: 56.64%] [G loss: 0.717011]
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4458 [D loss: 0.688338, acc.: 54.30%] [G loss: 0.705648]
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4459 [D loss: 0.684761, acc.: 53.91%] [G loss: 0.712838]
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4460 [D loss: 0.690706, acc.: 52.34%] [G loss: 0.718693]
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4461 [D loss: 0.689615, acc.: 52.15%] [G loss: 0.715438]
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4462 [D loss: 0.690055, acc.: 55.27%] [G loss: 0.717930]
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4463 [D loss: 0.690227, acc.: 53.52%] [G loss: 0.712797]
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4464 [D loss: 0.687433, acc.: 56.64%] [G loss: 0.712073]
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4465 [D loss: 0.692592, acc.: 50.98%] [G loss: 0.710456]
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4466 [D loss: 0.689681, acc.: 52.93%] [G loss: 0.709815]
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4467 [D loss: 0.692270, acc.: 52.73%] [G loss: 0.704762]
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4468 [D loss: 0.687957, acc.: 55.27%] [G loss: 0.705585]
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4469 [D loss: 0.690682, acc.: 52.15%] [G loss: 0.705907]
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4470 [D loss: 0.690652, acc.: 51.76%] [G loss: 0.706398]
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4471 [D loss: 0.691076, acc.: 56.05%] [G loss: 0.703247]
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4472 [D loss: 0.688759, acc.: 55.27%] [G loss: 0.709201]
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4473 [D loss: 0.688363, acc.: 56.84%] [G loss: 0.711908]
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4474 [D loss: 0.686171, acc.: 53.71%] [G loss: 0.708293]
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4475 [D loss: 0.687120, acc.: 55.66%] [G loss: 0.715861]
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4476 [D loss: 0.685277, acc.: 55.47%] [G loss: 0.714238]
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4477 [D loss: 0.692340, acc.: 53.52%] [G loss: 0.711444]
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4478 [D loss: 0.690317, acc.: 52.54%] [G loss: 0.711057]
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4479 [D loss: 0.686692, acc.: 57.42%] [G loss: 0.706119]
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4480 [D loss: 0.680819, acc.: 58.59%] [G loss: 0.716358]
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4481 [D loss: 0.682366, acc.: 58.79%] [G loss: 0.711850]
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4482 [D loss: 0.682430, acc.: 57.62%] [G loss: 0.710428]
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4483 [D loss: 0.693877, acc.: 50.39%] [G loss: 0.716220]
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4484 [D loss: 0.689960, acc.: 53.12%] [G loss: 0.706080]
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4485 [D loss: 0.692903, acc.: 51.17%] [G loss: 0.695306]
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4486 [D loss: 0.691250, acc.: 52.93%] [G loss: 0.696360]
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4487 [D loss: 0.692297, acc.: 51.56%] [G loss: 0.703360]
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4488 [D loss: 0.694245, acc.: 50.98%] [G loss: 0.708755]
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4489 [D loss: 0.691048, acc.: 53.12%] [G loss: 0.711785]
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4490 [D loss: 0.686486, acc.: 57.62%] [G loss: 0.712331]
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4491 [D loss: 0.687512, acc.: 55.86%] [G loss: 0.712210]
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4492 [D loss: 0.685517, acc.: 56.05%] [G loss: 0.715173]
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4493 [D loss: 0.682007, acc.: 58.01%] [G loss: 0.713315]
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4494 [D loss: 0.682763, acc.: 61.52%] [G loss: 0.716465]
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4495 [D loss: 0.685751, acc.: 55.27%] [G loss: 0.719349]
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4496 [D loss: 0.682792, acc.: 56.64%] [G loss: 0.715220]
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4497 [D loss: 0.687023, acc.: 55.47%] [G loss: 0.713994]
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4498 [D loss: 0.689454, acc.: 53.12%] [G loss: 0.711449]
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4499 [D loss: 0.686422, acc.: 53.32%] [G loss: 0.710823]
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4500 [D loss: 0.686799, acc.: 56.25%] [G loss: 0.700289]
1/1 [==============================] - 0s 16ms/step
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4501 [D loss: 0.689999, acc.: 52.93%] [G loss: 0.699301]
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4502 [D loss: 0.691030, acc.: 54.10%] [G loss: 0.698526]
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4503 [D loss: 0.692557, acc.: 50.59%] [G loss: 0.702931]
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4504 [D loss: 0.694401, acc.: 50.98%] [G loss: 0.702678]
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4505 [D loss: 0.689446, acc.: 54.49%] [G loss: 0.716850]
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4506 [D loss: 0.687527, acc.: 55.47%] [G loss: 0.717840]
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4507 [D loss: 0.688552, acc.: 53.91%] [G loss: 0.715455]
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4508 [D loss: 0.686989, acc.: 54.10%] [G loss: 0.715628]
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4509 [D loss: 0.692845, acc.: 50.59%] [G loss: 0.710771]
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4510 [D loss: 0.686899, acc.: 56.05%] [G loss: 0.712100]
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4511 [D loss: 0.686688, acc.: 55.08%] [G loss: 0.720572]
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4512 [D loss: 0.682541, acc.: 57.42%] [G loss: 0.725028]
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4513 [D loss: 0.679634, acc.: 58.01%] [G loss: 0.720136]
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4514 [D loss: 0.683440, acc.: 56.25%] [G loss: 0.712511]
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4515 [D loss: 0.689271, acc.: 54.69%] [G loss: 0.714373]
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4516 [D loss: 0.689258, acc.: 54.49%] [G loss: 0.712171]
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4517 [D loss: 0.688308, acc.: 52.93%] [G loss: 0.709753]
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4518 [D loss: 0.681150, acc.: 58.59%] [G loss: 0.707040]
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4519 [D loss: 0.681641, acc.: 59.77%] [G loss: 0.722114]
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4520 [D loss: 0.687871, acc.: 53.12%] [G loss: 0.716198]
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4521 [D loss: 0.685919, acc.: 54.10%] [G loss: 0.709108]
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4522 [D loss: 0.687237, acc.: 53.52%] [G loss: 0.705361]
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4523 [D loss: 0.691150, acc.: 48.63%] [G loss: 0.711962]
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4524 [D loss: 0.688630, acc.: 53.32%] [G loss: 0.716137]
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4525 [D loss: 0.688259, acc.: 53.71%] [G loss: 0.714797]
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4526 [D loss: 0.683624, acc.: 58.79%] [G loss: 0.716298]
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4527 [D loss: 0.685430, acc.: 56.45%] [G loss: 0.713454]
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4528 [D loss: 0.685247, acc.: 56.05%] [G loss: 0.712878]
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4529 [D loss: 0.687427, acc.: 54.30%] [G loss: 0.707413]
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4530 [D loss: 0.690176, acc.: 54.10%] [G loss: 0.701969]
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4531 [D loss: 0.689027, acc.: 54.69%] [G loss: 0.703596]
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4532 [D loss: 0.689810, acc.: 56.64%] [G loss: 0.718143]
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4533 [D loss: 0.689812, acc.: 49.61%] [G loss: 0.716998]
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4534 [D loss: 0.693154, acc.: 50.59%] [G loss: 0.709779]
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4535 [D loss: 0.688188, acc.: 52.34%] [G loss: 0.709649]
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4536 [D loss: 0.699140, acc.: 47.85%] [G loss: 0.709239]
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4537 [D loss: 0.691579, acc.: 51.17%] [G loss: 0.713583]
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4538 [D loss: 0.690708, acc.: 51.37%] [G loss: 0.712139]
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4539 [D loss: 0.691317, acc.: 51.17%] [G loss: 0.713548]
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4540 [D loss: 0.681809, acc.: 59.18%] [G loss: 0.714585]
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4541 [D loss: 0.686997, acc.: 54.69%] [G loss: 0.709827]
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4542 [D loss: 0.690873, acc.: 52.73%] [G loss: 0.716536]
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4543 [D loss: 0.685167, acc.: 58.40%] [G loss: 0.707931]
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4544 [D loss: 0.682871, acc.: 55.66%] [G loss: 0.713913]
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4545 [D loss: 0.679493, acc.: 59.96%] [G loss: 0.710350]
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4546 [D loss: 0.687363, acc.: 53.52%] [G loss: 0.718814]
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4547 [D loss: 0.681391, acc.: 56.64%] [G loss: 0.711408]
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4548 [D loss: 0.685420, acc.: 57.81%] [G loss: 0.707781]
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4549 [D loss: 0.693077, acc.: 54.10%] [G loss: 0.707877]
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4550 [D loss: 0.688044, acc.: 55.27%] [G loss: 0.702096]
1/1 [==============================] - 0s 16ms/step
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4551 [D loss: 0.689837, acc.: 53.52%] [G loss: 0.717709]
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4552 [D loss: 0.689308, acc.: 53.52%] [G loss: 0.710567]
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4553 [D loss: 0.689713, acc.: 53.71%] [G loss: 0.715280]
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4554 [D loss: 0.692562, acc.: 52.73%] [G loss: 0.719432]
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4555 [D loss: 0.689834, acc.: 53.32%] [G loss: 0.724640]
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4556 [D loss: 0.693556, acc.: 51.17%] [G loss: 0.720841]
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4557 [D loss: 0.689785, acc.: 54.10%] [G loss: 0.717044]
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4558 [D loss: 0.681834, acc.: 57.42%] [G loss: 0.730985]
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4559 [D loss: 0.686114, acc.: 57.03%] [G loss: 0.726243]
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4560 [D loss: 0.682603, acc.: 58.20%] [G loss: 0.718787]
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4561 [D loss: 0.683465, acc.: 56.84%] [G loss: 0.706344]
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4562 [D loss: 0.693490, acc.: 51.37%] [G loss: 0.705827]
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4563 [D loss: 0.689507, acc.: 52.34%] [G loss: 0.703272]
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4564 [D loss: 0.691165, acc.: 54.49%] [G loss: 0.703642]
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4565 [D loss: 0.688539, acc.: 53.91%] [G loss: 0.711249]
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4566 [D loss: 0.688484, acc.: 55.86%] [G loss: 0.714161]
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4567 [D loss: 0.689218, acc.: 55.66%] [G loss: 0.713790]
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4568 [D loss: 0.696198, acc.: 50.78%] [G loss: 0.716376]
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4569 [D loss: 0.691562, acc.: 49.80%] [G loss: 0.708353]
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4570 [D loss: 0.685734, acc.: 58.01%] [G loss: 0.700380]
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4571 [D loss: 0.687028, acc.: 53.12%] [G loss: 0.718636]
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4572 [D loss: 0.689826, acc.: 52.54%] [G loss: 0.713027]
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4573 [D loss: 0.684200, acc.: 57.03%] [G loss: 0.707035]
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4574 [D loss: 0.683437, acc.: 56.05%] [G loss: 0.710871]
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4575 [D loss: 0.686934, acc.: 52.15%] [G loss: 0.711698]
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4576 [D loss: 0.682234, acc.: 60.94%] [G loss: 0.710248]
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4577 [D loss: 0.683161, acc.: 59.18%] [G loss: 0.703869]
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4578 [D loss: 0.687246, acc.: 55.47%] [G loss: 0.718815]
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4579 [D loss: 0.683466, acc.: 58.40%] [G loss: 0.713548]
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4580 [D loss: 0.689666, acc.: 54.49%] [G loss: 0.711688]
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4581 [D loss: 0.686844, acc.: 56.45%] [G loss: 0.702781]
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4582 [D loss: 0.695311, acc.: 51.56%] [G loss: 0.705468]
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4583 [D loss: 0.683220, acc.: 60.16%] [G loss: 0.708329]
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4584 [D loss: 0.683278, acc.: 58.98%] [G loss: 0.713249]
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4585 [D loss: 0.678461, acc.: 59.77%] [G loss: 0.706864]
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4586 [D loss: 0.684995, acc.: 56.25%] [G loss: 0.716917]
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4587 [D loss: 0.686563, acc.: 56.45%] [G loss: 0.714134]
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4588 [D loss: 0.692443, acc.: 50.78%] [G loss: 0.712075]
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4589 [D loss: 0.689623, acc.: 51.95%] [G loss: 0.701236]
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4590 [D loss: 0.687911, acc.: 56.05%] [G loss: 0.714212]
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4591 [D loss: 0.689064, acc.: 51.56%] [G loss: 0.723668]
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4592 [D loss: 0.692609, acc.: 50.78%] [G loss: 0.716477]
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4593 [D loss: 0.688140, acc.: 55.47%] [G loss: 0.716466]
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4594 [D loss: 0.691300, acc.: 54.10%] [G loss: 0.711080]
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4595 [D loss: 0.691756, acc.: 52.93%] [G loss: 0.703437]
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4596 [D loss: 0.687654, acc.: 54.69%] [G loss: 0.705662]
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4597 [D loss: 0.689027, acc.: 52.73%] [G loss: 0.714880]
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4598 [D loss: 0.686244, acc.: 54.49%] [G loss: 0.716664]
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4599 [D loss: 0.694757, acc.: 50.39%] [G loss: 0.709938]
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4600 [D loss: 0.685611, acc.: 57.62%] [G loss: 0.713474]
1/1 [==============================] - 0s 16ms/step
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4601 [D loss: 0.687987, acc.: 55.66%] [G loss: 0.710804]
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4602 [D loss: 0.687841, acc.: 56.84%] [G loss: 0.715727]
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4603 [D loss: 0.688341, acc.: 52.34%] [G loss: 0.715671]
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4604 [D loss: 0.690847, acc.: 54.69%] [G loss: 0.716370]
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4605 [D loss: 0.685901, acc.: 56.25%] [G loss: 0.715092]
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4606 [D loss: 0.688365, acc.: 55.27%] [G loss: 0.708402]
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4607 [D loss: 0.686786, acc.: 55.08%] [G loss: 0.707622]
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4608 [D loss: 0.689049, acc.: 53.71%] [G loss: 0.711263]
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4609 [D loss: 0.686740, acc.: 53.91%] [G loss: 0.708743]
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4610 [D loss: 0.682602, acc.: 59.38%] [G loss: 0.711570]
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4611 [D loss: 0.687635, acc.: 55.66%] [G loss: 0.702136]
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4612 [D loss: 0.686949, acc.: 54.10%] [G loss: 0.712311]
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4613 [D loss: 0.687989, acc.: 54.30%] [G loss: 0.708518]
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4614 [D loss: 0.693147, acc.: 51.76%] [G loss: 0.716664]
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4615 [D loss: 0.683879, acc.: 55.27%] [G loss: 0.717880]
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4616 [D loss: 0.687400, acc.: 52.73%] [G loss: 0.712779]
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4617 [D loss: 0.689575, acc.: 53.71%] [G loss: 0.716550]
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4618 [D loss: 0.683735, acc.: 59.96%] [G loss: 0.715985]
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4619 [D loss: 0.686115, acc.: 55.47%] [G loss: 0.710941]
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4620 [D loss: 0.690949, acc.: 53.71%] [G loss: 0.710706]
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4621 [D loss: 0.692134, acc.: 53.32%] [G loss: 0.708505]
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4622 [D loss: 0.681349, acc.: 58.59%] [G loss: 0.712195]
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4623 [D loss: 0.684728, acc.: 56.05%] [G loss: 0.714104]
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4624 [D loss: 0.691108, acc.: 53.12%] [G loss: 0.712102]
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4625 [D loss: 0.693493, acc.: 49.41%] [G loss: 0.716995]
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4626 [D loss: 0.688307, acc.: 53.71%] [G loss: 0.706989]
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4627 [D loss: 0.684440, acc.: 55.66%] [G loss: 0.709807]
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4628 [D loss: 0.690767, acc.: 52.34%] [G loss: 0.712626]
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4629 [D loss: 0.689183, acc.: 51.37%] [G loss: 0.708783]
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4630 [D loss: 0.689208, acc.: 54.69%] [G loss: 0.706307]
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4631 [D loss: 0.691037, acc.: 52.15%] [G loss: 0.707025]
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4632 [D loss: 0.686105, acc.: 54.69%] [G loss: 0.710664]
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4633 [D loss: 0.682417, acc.: 56.25%] [G loss: 0.712227]
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4634 [D loss: 0.684204, acc.: 55.86%] [G loss: 0.712883]
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4635 [D loss: 0.685433, acc.: 57.03%] [G loss: 0.711787]
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4636 [D loss: 0.684614, acc.: 55.47%] [G loss: 0.709249]
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4637 [D loss: 0.681766, acc.: 59.77%] [G loss: 0.700432]
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4638 [D loss: 0.687343, acc.: 55.66%] [G loss: 0.709126]
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4639 [D loss: 0.687446, acc.: 50.78%] [G loss: 0.707283]
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4640 [D loss: 0.684049, acc.: 55.08%] [G loss: 0.710359]
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4641 [D loss: 0.687683, acc.: 54.30%] [G loss: 0.723015]
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4642 [D loss: 0.687260, acc.: 53.91%] [G loss: 0.710889]
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4643 [D loss: 0.692614, acc.: 51.76%] [G loss: 0.706618]
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4644 [D loss: 0.692986, acc.: 55.66%] [G loss: 0.708970]
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4645 [D loss: 0.689064, acc.: 53.12%] [G loss: 0.702646]
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4646 [D loss: 0.690398, acc.: 51.37%] [G loss: 0.706274]
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4647 [D loss: 0.685206, acc.: 55.27%] [G loss: 0.712150]
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4648 [D loss: 0.688148, acc.: 57.23%] [G loss: 0.700549]
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4649 [D loss: 0.682963, acc.: 53.71%] [G loss: 0.703407]
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4650 [D loss: 0.689886, acc.: 54.10%] [G loss: 0.705628]
1/1 [==============================] - 0s 17ms/step
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4651 [D loss: 0.682593, acc.: 58.40%] [G loss: 0.711365]
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4652 [D loss: 0.689811, acc.: 53.12%] [G loss: 0.709203]
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4653 [D loss: 0.683948, acc.: 56.84%] [G loss: 0.716921]
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4654 [D loss: 0.692743, acc.: 52.15%] [G loss: 0.716421]
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4655 [D loss: 0.686191, acc.: 56.05%] [G loss: 0.702358]
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4656 [D loss: 0.687476, acc.: 56.64%] [G loss: 0.703390]
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4657 [D loss: 0.693975, acc.: 53.32%] [G loss: 0.705193]
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4658 [D loss: 0.684619, acc.: 54.30%] [G loss: 0.708859]
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4659 [D loss: 0.686218, acc.: 54.69%] [G loss: 0.711864]
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4660 [D loss: 0.688331, acc.: 53.71%] [G loss: 0.711708]
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4661 [D loss: 0.685351, acc.: 55.27%] [G loss: 0.712364]
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4662 [D loss: 0.687966, acc.: 53.91%] [G loss: 0.711482]
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4663 [D loss: 0.686578, acc.: 53.12%] [G loss: 0.713606]
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4664 [D loss: 0.685234, acc.: 56.64%] [G loss: 0.711668]
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4665 [D loss: 0.683284, acc.: 58.79%] [G loss: 0.718971]
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4666 [D loss: 0.684276, acc.: 55.86%] [G loss: 0.720488]
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4667 [D loss: 0.683619, acc.: 56.84%] [G loss: 0.719764]
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4668 [D loss: 0.689458, acc.: 57.23%] [G loss: 0.715612]
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4669 [D loss: 0.687892, acc.: 54.69%] [G loss: 0.704153]
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4670 [D loss: 0.695554, acc.: 50.00%] [G loss: 0.705343]
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4671 [D loss: 0.695186, acc.: 49.80%] [G loss: 0.700324]
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4672 [D loss: 0.687831, acc.: 54.30%] [G loss: 0.707563]
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4673 [D loss: 0.687608, acc.: 54.49%] [G loss: 0.711318]
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4674 [D loss: 0.686247, acc.: 56.64%] [G loss: 0.708212]
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4675 [D loss: 0.686192, acc.: 57.42%] [G loss: 0.719730]
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4676 [D loss: 0.683045, acc.: 58.20%] [G loss: 0.715149]
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4677 [D loss: 0.686900, acc.: 54.10%] [G loss: 0.705962]
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4678 [D loss: 0.687842, acc.: 55.27%] [G loss: 0.710567]
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4679 [D loss: 0.688498, acc.: 55.86%] [G loss: 0.717481]
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4680 [D loss: 0.678641, acc.: 60.16%] [G loss: 0.722293]
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4681 [D loss: 0.690244, acc.: 56.84%] [G loss: 0.726283]
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4682 [D loss: 0.688352, acc.: 53.12%] [G loss: 0.720976]
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4683 [D loss: 0.688763, acc.: 51.76%] [G loss: 0.715769]
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4684 [D loss: 0.687172, acc.: 53.71%] [G loss: 0.714525]
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4685 [D loss: 0.687116, acc.: 53.91%] [G loss: 0.715018]
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4686 [D loss: 0.684111, acc.: 56.45%] [G loss: 0.707299]
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4687 [D loss: 0.686289, acc.: 54.88%] [G loss: 0.717185]
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4688 [D loss: 0.691662, acc.: 50.78%] [G loss: 0.715536]
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4689 [D loss: 0.682111, acc.: 58.98%] [G loss: 0.708933]
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4690 [D loss: 0.690799, acc.: 49.22%] [G loss: 0.708662]
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4691 [D loss: 0.691040, acc.: 50.98%] [G loss: 0.709500]
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4692 [D loss: 0.685721, acc.: 56.45%] [G loss: 0.719564]
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4693 [D loss: 0.685115, acc.: 55.66%] [G loss: 0.710148]
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4694 [D loss: 0.683690, acc.: 54.49%] [G loss: 0.714046]
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4695 [D loss: 0.684265, acc.: 54.10%] [G loss: 0.705507]
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4696 [D loss: 0.686608, acc.: 52.34%] [G loss: 0.701942]
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4697 [D loss: 0.691016, acc.: 51.37%] [G loss: 0.710330]
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4698 [D loss: 0.687357, acc.: 54.88%] [G loss: 0.707409]
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4699 [D loss: 0.689614, acc.: 53.52%] [G loss: 0.710077]
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4700 [D loss: 0.691123, acc.: 53.32%] [G loss: 0.704071]
1/1 [==============================] - 0s 17ms/step
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4701 [D loss: 0.687360, acc.: 53.12%] [G loss: 0.708506]
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4702 [D loss: 0.688760, acc.: 52.54%] [G loss: 0.715044]
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4703 [D loss: 0.692737, acc.: 53.52%] [G loss: 0.725523]
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4704 [D loss: 0.689161, acc.: 51.37%] [G loss: 0.717918]
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4705 [D loss: 0.688010, acc.: 53.12%] [G loss: 0.719350]
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4706 [D loss: 0.688535, acc.: 54.10%] [G loss: 0.723160]
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4707 [D loss: 0.686747, acc.: 55.86%] [G loss: 0.726324]
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4708 [D loss: 0.687569, acc.: 54.10%] [G loss: 0.714723]
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4709 [D loss: 0.688435, acc.: 53.52%] [G loss: 0.715711]
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4710 [D loss: 0.689031, acc.: 52.73%] [G loss: 0.713867]
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4711 [D loss: 0.686658, acc.: 54.49%] [G loss: 0.717796]
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4712 [D loss: 0.683776, acc.: 58.59%] [G loss: 0.717705]
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4713 [D loss: 0.682087, acc.: 53.91%] [G loss: 0.711191]
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4714 [D loss: 0.686928, acc.: 54.69%] [G loss: 0.716219]
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4715 [D loss: 0.690022, acc.: 54.10%] [G loss: 0.700927]
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4716 [D loss: 0.689440, acc.: 53.12%] [G loss: 0.707422]
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4717 [D loss: 0.686568, acc.: 54.49%] [G loss: 0.709492]
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4718 [D loss: 0.684231, acc.: 58.20%] [G loss: 0.701021]
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4719 [D loss: 0.689454, acc.: 52.93%] [G loss: 0.702376]
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4720 [D loss: 0.686436, acc.: 57.42%] [G loss: 0.704070]
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4721 [D loss: 0.691920, acc.: 51.76%] [G loss: 0.706114]
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4722 [D loss: 0.689357, acc.: 54.49%] [G loss: 0.708349]
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4723 [D loss: 0.693294, acc.: 52.93%] [G loss: 0.713076]
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4724 [D loss: 0.687060, acc.: 55.27%] [G loss: 0.719663]
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4725 [D loss: 0.684275, acc.: 56.64%] [G loss: 0.713195]
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4726 [D loss: 0.684869, acc.: 58.01%] [G loss: 0.716984]
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4727 [D loss: 0.685118, acc.: 53.91%] [G loss: 0.707435]
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4728 [D loss: 0.688421, acc.: 53.91%] [G loss: 0.704959]
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4729 [D loss: 0.685049, acc.: 54.69%] [G loss: 0.717458]
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4730 [D loss: 0.685369, acc.: 54.10%] [G loss: 0.716447]
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4731 [D loss: 0.692628, acc.: 51.37%] [G loss: 0.715312]
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4732 [D loss: 0.685983, acc.: 55.47%] [G loss: 0.719301]
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4733 [D loss: 0.686543, acc.: 54.49%] [G loss: 0.714865]
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4734 [D loss: 0.689869, acc.: 51.76%] [G loss: 0.707370]
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4735 [D loss: 0.690162, acc.: 49.80%] [G loss: 0.715431]
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4736 [D loss: 0.690398, acc.: 54.10%] [G loss: 0.710863]
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4737 [D loss: 0.689325, acc.: 54.88%] [G loss: 0.710314]
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4738 [D loss: 0.684557, acc.: 56.25%] [G loss: 0.715235]
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4739 [D loss: 0.687334, acc.: 54.30%] [G loss: 0.719802]
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4740 [D loss: 0.687049, acc.: 53.52%] [G loss: 0.717319]
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4741 [D loss: 0.680018, acc.: 60.35%] [G loss: 0.729295]
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4742 [D loss: 0.685046, acc.: 57.81%] [G loss: 0.720927]
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4743 [D loss: 0.687534, acc.: 56.45%] [G loss: 0.719749]
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4744 [D loss: 0.683649, acc.: 57.81%] [G loss: 0.716741]
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4745 [D loss: 0.682573, acc.: 61.13%] [G loss: 0.717365]
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4746 [D loss: 0.683345, acc.: 56.25%] [G loss: 0.712872]
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4747 [D loss: 0.686225, acc.: 55.08%] [G loss: 0.724042]
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4748 [D loss: 0.691044, acc.: 53.52%] [G loss: 0.725010]
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4749 [D loss: 0.682995, acc.: 57.62%] [G loss: 0.718417]
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4750 [D loss: 0.686585, acc.: 54.10%] [G loss: 0.711814]
1/1 [==============================] - 0s 17ms/step
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4751 [D loss: 0.693243, acc.: 51.76%] [G loss: 0.708279]
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4752 [D loss: 0.688321, acc.: 54.49%] [G loss: 0.707660]
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4753 [D loss: 0.678612, acc.: 58.79%] [G loss: 0.715084]
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4754 [D loss: 0.685753, acc.: 54.88%] [G loss: 0.709338]
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4755 [D loss: 0.694931, acc.: 47.46%] [G loss: 0.706592]
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4756 [D loss: 0.691625, acc.: 51.76%] [G loss: 0.705516]
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4757 [D loss: 0.690305, acc.: 54.49%] [G loss: 0.709519]
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4758 [D loss: 0.689147, acc.: 51.56%] [G loss: 0.707944]
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4759 [D loss: 0.691065, acc.: 51.76%] [G loss: 0.707392]
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4760 [D loss: 0.678724, acc.: 59.96%] [G loss: 0.705569]
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4761 [D loss: 0.687562, acc.: 56.25%] [G loss: 0.708142]
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4762 [D loss: 0.688439, acc.: 55.86%] [G loss: 0.705426]
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4763 [D loss: 0.680460, acc.: 59.57%] [G loss: 0.709686]
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4764 [D loss: 0.687503, acc.: 53.12%] [G loss: 0.716101]
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4765 [D loss: 0.684914, acc.: 52.34%] [G loss: 0.709877]
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4766 [D loss: 0.693156, acc.: 51.37%] [G loss: 0.712225]
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4767 [D loss: 0.685239, acc.: 56.84%] [G loss: 0.717776]
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4768 [D loss: 0.683255, acc.: 55.47%] [G loss: 0.720406]
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4769 [D loss: 0.685588, acc.: 55.27%] [G loss: 0.719824]
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4770 [D loss: 0.684174, acc.: 57.23%] [G loss: 0.718849]
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4771 [D loss: 0.684161, acc.: 57.81%] [G loss: 0.706424]
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4772 [D loss: 0.687945, acc.: 54.88%] [G loss: 0.712955]
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4773 [D loss: 0.688570, acc.: 54.10%] [G loss: 0.704375]
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4774 [D loss: 0.688565, acc.: 53.32%] [G loss: 0.700661]
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4775 [D loss: 0.691756, acc.: 49.02%] [G loss: 0.700474]
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4776 [D loss: 0.686588, acc.: 53.32%] [G loss: 0.704583]
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4777 [D loss: 0.684577, acc.: 54.88%] [G loss: 0.709594]
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4778 [D loss: 0.688155, acc.: 54.69%] [G loss: 0.708009]
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4779 [D loss: 0.685683, acc.: 57.42%] [G loss: 0.717758]
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4780 [D loss: 0.688560, acc.: 53.91%] [G loss: 0.710593]
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4781 [D loss: 0.682521, acc.: 57.23%] [G loss: 0.709550]
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4782 [D loss: 0.685089, acc.: 57.23%] [G loss: 0.722068]
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4783 [D loss: 0.691067, acc.: 53.91%] [G loss: 0.717255]
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4784 [D loss: 0.689932, acc.: 52.15%] [G loss: 0.715229]
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4785 [D loss: 0.687660, acc.: 55.47%] [G loss: 0.711812]
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4786 [D loss: 0.686505, acc.: 55.08%] [G loss: 0.716135]
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4787 [D loss: 0.686483, acc.: 53.71%] [G loss: 0.712348]
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4788 [D loss: 0.686756, acc.: 51.76%] [G loss: 0.717245]
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4789 [D loss: 0.686827, acc.: 54.30%] [G loss: 0.716345]
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4790 [D loss: 0.687260, acc.: 54.69%] [G loss: 0.717061]
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4791 [D loss: 0.692887, acc.: 52.73%] [G loss: 0.716865]
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4792 [D loss: 0.683558, acc.: 57.42%] [G loss: 0.715741]
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4793 [D loss: 0.682705, acc.: 56.84%] [G loss: 0.724613]
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4794 [D loss: 0.687667, acc.: 56.05%] [G loss: 0.722614]
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4795 [D loss: 0.683428, acc.: 54.49%] [G loss: 0.730131]
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4796 [D loss: 0.685410, acc.: 55.86%] [G loss: 0.723370]
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4797 [D loss: 0.686382, acc.: 55.47%] [G loss: 0.727975]
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4798 [D loss: 0.683881, acc.: 57.23%] [G loss: 0.733218]
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4799 [D loss: 0.683311, acc.: 55.66%] [G loss: 0.726732]
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4800 [D loss: 0.678402, acc.: 60.94%] [G loss: 0.722521]
1/1 [==============================] - 0s 17ms/step
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4801 [D loss: 0.685723, acc.: 56.84%] [G loss: 0.717139]
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4802 [D loss: 0.692213, acc.: 52.93%] [G loss: 0.715317]
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4803 [D loss: 0.690105, acc.: 50.98%] [G loss: 0.707378]
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4804 [D loss: 0.690289, acc.: 53.12%] [G loss: 0.710131]
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4805 [D loss: 0.689449, acc.: 52.34%] [G loss: 0.715753]
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4806 [D loss: 0.684670, acc.: 58.20%] [G loss: 0.711283]
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4807 [D loss: 0.681473, acc.: 59.96%] [G loss: 0.707433]
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4808 [D loss: 0.681730, acc.: 56.05%] [G loss: 0.708794]
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4809 [D loss: 0.689543, acc.: 52.73%] [G loss: 0.719628]
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4810 [D loss: 0.697036, acc.: 48.24%] [G loss: 0.709228]
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4811 [D loss: 0.692010, acc.: 50.59%] [G loss: 0.709665]
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4812 [D loss: 0.688007, acc.: 55.27%] [G loss: 0.709250]
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4813 [D loss: 0.686116, acc.: 55.47%] [G loss: 0.717083]
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4814 [D loss: 0.683468, acc.: 60.16%] [G loss: 0.716945]
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4815 [D loss: 0.684542, acc.: 57.23%] [G loss: 0.715870]
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4816 [D loss: 0.689528, acc.: 51.17%] [G loss: 0.720355]
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4817 [D loss: 0.687298, acc.: 53.52%] [G loss: 0.711258]
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4818 [D loss: 0.685840, acc.: 56.25%] [G loss: 0.720461]
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4819 [D loss: 0.687786, acc.: 53.71%] [G loss: 0.717818]
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4820 [D loss: 0.689092, acc.: 54.88%] [G loss: 0.715846]
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4821 [D loss: 0.688534, acc.: 56.84%] [G loss: 0.720278]
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4822 [D loss: 0.690553, acc.: 54.49%] [G loss: 0.709386]
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4823 [D loss: 0.689223, acc.: 54.30%] [G loss: 0.725671]
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4824 [D loss: 0.684782, acc.: 56.05%] [G loss: 0.714375]
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4825 [D loss: 0.685843, acc.: 56.25%] [G loss: 0.717459]
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4826 [D loss: 0.682455, acc.: 55.86%] [G loss: 0.716941]
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4827 [D loss: 0.689719, acc.: 52.54%] [G loss: 0.714845]
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4828 [D loss: 0.687718, acc.: 54.69%] [G loss: 0.706381]
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4829 [D loss: 0.687314, acc.: 52.54%] [G loss: 0.712844]
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4830 [D loss: 0.689950, acc.: 54.30%] [G loss: 0.730991]
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4831 [D loss: 0.678745, acc.: 61.72%] [G loss: 0.726395]
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4832 [D loss: 0.680103, acc.: 57.23%] [G loss: 0.731502]
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4833 [D loss: 0.680496, acc.: 58.40%] [G loss: 0.720344]
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4834 [D loss: 0.687033, acc.: 56.84%] [G loss: 0.708615]
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4835 [D loss: 0.688711, acc.: 53.12%] [G loss: 0.707605]
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4836 [D loss: 0.696186, acc.: 50.98%] [G loss: 0.715098]
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4837 [D loss: 0.683539, acc.: 56.05%] [G loss: 0.718368]
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4838 [D loss: 0.683976, acc.: 55.86%] [G loss: 0.729797]
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4839 [D loss: 0.679795, acc.: 59.77%] [G loss: 0.728863]
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4840 [D loss: 0.678719, acc.: 59.38%] [G loss: 0.734724]
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4841 [D loss: 0.690932, acc.: 53.32%] [G loss: 0.728219]
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4842 [D loss: 0.689167, acc.: 53.71%] [G loss: 0.720782]
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4843 [D loss: 0.692401, acc.: 52.73%] [G loss: 0.727308]
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4844 [D loss: 0.681885, acc.: 56.84%] [G loss: 0.730797]
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4845 [D loss: 0.677485, acc.: 59.77%] [G loss: 0.729495]
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4846 [D loss: 0.683598, acc.: 56.05%] [G loss: 0.735706]
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4847 [D loss: 0.687486, acc.: 55.27%] [G loss: 0.729308]
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4848 [D loss: 0.681506, acc.: 53.12%] [G loss: 0.724687]
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4849 [D loss: 0.688237, acc.: 54.10%] [G loss: 0.713696]
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4850 [D loss: 0.681069, acc.: 57.23%] [G loss: 0.713641]
1/1 [==============================] - 0s 17ms/step
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4851 [D loss: 0.683178, acc.: 53.91%] [G loss: 0.709400]
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4852 [D loss: 0.679355, acc.: 56.45%] [G loss: 0.713773]
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4853 [D loss: 0.690175, acc.: 52.54%] [G loss: 0.708692]
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4854 [D loss: 0.694810, acc.: 49.61%] [G loss: 0.704674]
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4855 [D loss: 0.691535, acc.: 48.24%] [G loss: 0.708415]
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4856 [D loss: 0.690141, acc.: 51.56%] [G loss: 0.710504]
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4857 [D loss: 0.684388, acc.: 56.05%] [G loss: 0.723043]
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4858 [D loss: 0.685028, acc.: 53.52%] [G loss: 0.737338]
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4859 [D loss: 0.674578, acc.: 62.11%] [G loss: 0.735613]
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4860 [D loss: 0.678684, acc.: 58.01%] [G loss: 0.723870]
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4861 [D loss: 0.690240, acc.: 55.47%] [G loss: 0.720831]
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4862 [D loss: 0.695083, acc.: 48.63%] [G loss: 0.712100]
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4863 [D loss: 0.696181, acc.: 51.56%] [G loss: 0.697934]
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4864 [D loss: 0.686272, acc.: 53.71%] [G loss: 0.702974]
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4865 [D loss: 0.682655, acc.: 60.16%] [G loss: 0.711795]
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4866 [D loss: 0.686554, acc.: 56.64%] [G loss: 0.721884]
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4867 [D loss: 0.678650, acc.: 58.79%] [G loss: 0.728993]
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4868 [D loss: 0.683018, acc.: 55.27%] [G loss: 0.714051]
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4869 [D loss: 0.682819, acc.: 59.18%] [G loss: 0.721190]
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4870 [D loss: 0.683012, acc.: 56.25%] [G loss: 0.715958]
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4871 [D loss: 0.683464, acc.: 57.81%] [G loss: 0.713322]
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4872 [D loss: 0.684019, acc.: 55.66%] [G loss: 0.722479]
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4873 [D loss: 0.681246, acc.: 57.42%] [G loss: 0.714084]
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4874 [D loss: 0.683585, acc.: 56.84%] [G loss: 0.714138]
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4875 [D loss: 0.682877, acc.: 55.27%] [G loss: 0.718458]
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4876 [D loss: 0.691520, acc.: 53.91%] [G loss: 0.707789]
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4877 [D loss: 0.684983, acc.: 54.10%] [G loss: 0.714441]
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4878 [D loss: 0.681971, acc.: 60.16%] [G loss: 0.721967]
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4879 [D loss: 0.688447, acc.: 55.66%] [G loss: 0.718790]
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4880 [D loss: 0.688675, acc.: 51.56%] [G loss: 0.720408]
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4881 [D loss: 0.678952, acc.: 60.16%] [G loss: 0.723054]
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4882 [D loss: 0.688092, acc.: 54.88%] [G loss: 0.717609]
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4883 [D loss: 0.689806, acc.: 53.32%] [G loss: 0.718557]
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4884 [D loss: 0.685753, acc.: 55.86%] [G loss: 0.716918]
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4885 [D loss: 0.686834, acc.: 54.30%] [G loss: 0.717876]
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4886 [D loss: 0.685627, acc.: 53.91%] [G loss: 0.718621]
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4887 [D loss: 0.688245, acc.: 55.47%] [G loss: 0.725642]
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4888 [D loss: 0.686961, acc.: 56.25%] [G loss: 0.716230]
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4889 [D loss: 0.683175, acc.: 55.86%] [G loss: 0.722535]
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4890 [D loss: 0.678669, acc.: 58.98%] [G loss: 0.723535]
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4891 [D loss: 0.686056, acc.: 58.79%] [G loss: 0.711807]
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4892 [D loss: 0.688957, acc.: 52.54%] [G loss: 0.706688]
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4893 [D loss: 0.675291, acc.: 64.26%] [G loss: 0.716242]
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4894 [D loss: 0.689425, acc.: 53.32%] [G loss: 0.719032]
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4895 [D loss: 0.688560, acc.: 51.95%] [G loss: 0.707163]
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4896 [D loss: 0.688247, acc.: 52.15%] [G loss: 0.713720]
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4897 [D loss: 0.683185, acc.: 57.03%] [G loss: 0.720210]
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4898 [D loss: 0.687238, acc.: 52.54%] [G loss: 0.718837]
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4899 [D loss: 0.681871, acc.: 58.59%] [G loss: 0.712924]
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4900 [D loss: 0.684496, acc.: 54.30%] [G loss: 0.716864]
1/1 [==============================] - 0s 17ms/step
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4901 [D loss: 0.679023, acc.: 58.20%] [G loss: 0.712408]
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4902 [D loss: 0.689852, acc.: 53.71%] [G loss: 0.713504]
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4903 [D loss: 0.683848, acc.: 55.08%] [G loss: 0.704629]
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4904 [D loss: 0.684499, acc.: 56.05%] [G loss: 0.707921]
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4905 [D loss: 0.688296, acc.: 54.49%] [G loss: 0.721304]
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4906 [D loss: 0.690269, acc.: 53.71%] [G loss: 0.712632]
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4907 [D loss: 0.686546, acc.: 53.32%] [G loss: 0.727786]
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4908 [D loss: 0.686007, acc.: 56.25%] [G loss: 0.722474]
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4909 [D loss: 0.688988, acc.: 54.69%] [G loss: 0.721834]
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4910 [D loss: 0.681871, acc.: 58.20%] [G loss: 0.718770]
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4911 [D loss: 0.690629, acc.: 53.32%] [G loss: 0.720596]
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4912 [D loss: 0.687364, acc.: 55.08%] [G loss: 0.714499]
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4913 [D loss: 0.692409, acc.: 53.12%] [G loss: 0.716967]
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4914 [D loss: 0.688316, acc.: 53.71%] [G loss: 0.727176]
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4915 [D loss: 0.681513, acc.: 55.86%] [G loss: 0.722631]
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4916 [D loss: 0.691491, acc.: 49.80%] [G loss: 0.713248]
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4917 [D loss: 0.688463, acc.: 52.54%] [G loss: 0.721099]
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4918 [D loss: 0.691064, acc.: 55.66%] [G loss: 0.722456]
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4919 [D loss: 0.686738, acc.: 54.10%] [G loss: 0.713308]
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4920 [D loss: 0.687786, acc.: 51.95%] [G loss: 0.711244]
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4921 [D loss: 0.681373, acc.: 59.96%] [G loss: 0.713986]
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4922 [D loss: 0.686701, acc.: 54.88%] [G loss: 0.709224]
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4923 [D loss: 0.689846, acc.: 54.69%] [G loss: 0.706063]
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4924 [D loss: 0.685843, acc.: 53.71%] [G loss: 0.708623]
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4925 [D loss: 0.691877, acc.: 52.34%] [G loss: 0.705377]
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4926 [D loss: 0.692495, acc.: 50.98%] [G loss: 0.715178]
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4927 [D loss: 0.682329, acc.: 58.79%] [G loss: 0.716208]
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4928 [D loss: 0.679020, acc.: 60.35%] [G loss: 0.716583]
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4929 [D loss: 0.682895, acc.: 55.86%] [G loss: 0.710742]
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4930 [D loss: 0.676572, acc.: 61.52%] [G loss: 0.715521]
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4931 [D loss: 0.686875, acc.: 54.88%] [G loss: 0.716388]
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4932 [D loss: 0.688007, acc.: 57.03%] [G loss: 0.718844]
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4933 [D loss: 0.678072, acc.: 59.57%] [G loss: 0.720040]
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4934 [D loss: 0.689222, acc.: 53.52%] [G loss: 0.723971]
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4935 [D loss: 0.688017, acc.: 54.69%] [G loss: 0.721457]
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4936 [D loss: 0.680240, acc.: 56.25%] [G loss: 0.728267]
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4937 [D loss: 0.680920, acc.: 56.84%] [G loss: 0.729853]
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4938 [D loss: 0.680162, acc.: 60.55%] [G loss: 0.710235]
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4939 [D loss: 0.685256, acc.: 54.30%] [G loss: 0.723783]
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4940 [D loss: 0.677323, acc.: 58.59%] [G loss: 0.734946]
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4941 [D loss: 0.683348, acc.: 56.64%] [G loss: 0.716302]
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4942 [D loss: 0.685977, acc.: 55.27%] [G loss: 0.710782]
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4943 [D loss: 0.692807, acc.: 50.59%] [G loss: 0.704782]
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4944 [D loss: 0.696668, acc.: 50.20%] [G loss: 0.701388]
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4945 [D loss: 0.689740, acc.: 55.08%] [G loss: 0.716403]
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4946 [D loss: 0.685927, acc.: 56.05%] [G loss: 0.720504]
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4947 [D loss: 0.686709, acc.: 54.30%] [G loss: 0.725304]
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4948 [D loss: 0.687781, acc.: 53.32%] [G loss: 0.716976]
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4949 [D loss: 0.690531, acc.: 52.54%] [G loss: 0.720125]
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4950 [D loss: 0.687147, acc.: 53.52%] [G loss: 0.725083]
1/1 [==============================] - 0s 17ms/step
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4951 [D loss: 0.686368, acc.: 52.93%] [G loss: 0.725638]
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4952 [D loss: 0.685117, acc.: 57.62%] [G loss: 0.725494]
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4953 [D loss: 0.689137, acc.: 53.71%] [G loss: 0.719941]
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4954 [D loss: 0.678096, acc.: 59.18%] [G loss: 0.726942]
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4955 [D loss: 0.686958, acc.: 54.69%] [G loss: 0.722790]
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4956 [D loss: 0.693296, acc.: 50.98%] [G loss: 0.718431]
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4957 [D loss: 0.690804, acc.: 52.34%] [G loss: 0.720709]
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4958 [D loss: 0.691618, acc.: 52.15%] [G loss: 0.709316]
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4959 [D loss: 0.689941, acc.: 53.91%] [G loss: 0.724975]
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4960 [D loss: 0.685010, acc.: 54.69%] [G loss: 0.717969]
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4961 [D loss: 0.684009, acc.: 56.05%] [G loss: 0.719211]
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4962 [D loss: 0.685516, acc.: 56.05%] [G loss: 0.713850]
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4963 [D loss: 0.685396, acc.: 57.23%] [G loss: 0.719293]
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4964 [D loss: 0.686524, acc.: 54.69%] [G loss: 0.716393]
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4965 [D loss: 0.683792, acc.: 56.64%] [G loss: 0.708645]
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4966 [D loss: 0.681784, acc.: 57.23%] [G loss: 0.726283]
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4967 [D loss: 0.677647, acc.: 59.77%] [G loss: 0.730915]
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4968 [D loss: 0.687105, acc.: 56.45%] [G loss: 0.722729]
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4969 [D loss: 0.677819, acc.: 58.98%] [G loss: 0.717203]
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4970 [D loss: 0.687728, acc.: 52.54%] [G loss: 0.710795]
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4971 [D loss: 0.687374, acc.: 55.47%] [G loss: 0.711902]
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4972 [D loss: 0.683492, acc.: 57.23%] [G loss: 0.717895]
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4973 [D loss: 0.687326, acc.: 54.10%] [G loss: 0.721745]
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4974 [D loss: 0.684502, acc.: 56.05%] [G loss: 0.711863]
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4975 [D loss: 0.687337, acc.: 55.47%] [G loss: 0.700919]
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4976 [D loss: 0.688826, acc.: 56.05%] [G loss: 0.708968]
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4977 [D loss: 0.689143, acc.: 51.76%] [G loss: 0.716092]
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4978 [D loss: 0.689410, acc.: 52.73%] [G loss: 0.705969]
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4979 [D loss: 0.694125, acc.: 50.98%] [G loss: 0.715770]
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4980 [D loss: 0.688877, acc.: 54.88%] [G loss: 0.727243]
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4981 [D loss: 0.690481, acc.: 50.20%] [G loss: 0.724125]
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4982 [D loss: 0.683231, acc.: 56.45%] [G loss: 0.732471]
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4983 [D loss: 0.684835, acc.: 55.86%] [G loss: 0.729351]
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4984 [D loss: 0.691022, acc.: 52.73%] [G loss: 0.721395]
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4985 [D loss: 0.692200, acc.: 50.78%] [G loss: 0.713345]
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4986 [D loss: 0.690019, acc.: 56.45%] [G loss: 0.730372]
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4987 [D loss: 0.688185, acc.: 53.32%] [G loss: 0.721901]
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4988 [D loss: 0.686047, acc.: 54.30%] [G loss: 0.725988]
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4989 [D loss: 0.686597, acc.: 54.10%] [G loss: 0.728534]
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4990 [D loss: 0.687200, acc.: 54.30%] [G loss: 0.715732]
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4991 [D loss: 0.682055, acc.: 59.96%] [G loss: 0.715892]
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4992 [D loss: 0.684118, acc.: 57.03%] [G loss: 0.715203]
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4993 [D loss: 0.686827, acc.: 53.52%] [G loss: 0.721509]
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4994 [D loss: 0.690316, acc.: 52.15%] [G loss: 0.714936]
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4995 [D loss: 0.687848, acc.: 53.32%] [G loss: 0.708279]
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4996 [D loss: 0.688366, acc.: 56.84%] [G loss: 0.711004]
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4997 [D loss: 0.688217, acc.: 53.32%] [G loss: 0.711033]
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4998 [D loss: 0.683042, acc.: 56.64%] [G loss: 0.709061]
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4999 [D loss: 0.684910, acc.: 56.05%] [G loss: 0.711532]
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5000 [D loss: 0.684661, acc.: 58.79%] [G loss: 0.728885]
1/1 [==============================] - 0s 17ms/step
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5001 [D loss: 0.682974, acc.: 56.64%] [G loss: 0.708880]
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5002 [D loss: 0.682785, acc.: 58.59%] [G loss: 0.715636]
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5003 [D loss: 0.692826, acc.: 51.56%] [G loss: 0.707329]
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5004 [D loss: 0.693225, acc.: 50.59%] [G loss: 0.715405]
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5005 [D loss: 0.686660, acc.: 56.25%] [G loss: 0.726683]
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5006 [D loss: 0.688898, acc.: 52.15%] [G loss: 0.716671]
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5007 [D loss: 0.686197, acc.: 53.71%] [G loss: 0.717015]
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5008 [D loss: 0.687348, acc.: 56.05%] [G loss: 0.725447]
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5009 [D loss: 0.686033, acc.: 56.84%] [G loss: 0.711237]
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5010 [D loss: 0.680340, acc.: 58.59%] [G loss: 0.726322]
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5011 [D loss: 0.682648, acc.: 57.81%] [G loss: 0.709908]
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5012 [D loss: 0.681113, acc.: 58.40%] [G loss: 0.715768]
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5013 [D loss: 0.685911, acc.: 54.49%] [G loss: 0.714812]
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5014 [D loss: 0.678687, acc.: 56.05%] [G loss: 0.719243]
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5015 [D loss: 0.690094, acc.: 54.69%] [G loss: 0.715085]
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5016 [D loss: 0.685670, acc.: 54.30%] [G loss: 0.712483]
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5017 [D loss: 0.691479, acc.: 50.59%] [G loss: 0.712968]
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5018 [D loss: 0.687776, acc.: 53.32%] [G loss: 0.717325]
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5019 [D loss: 0.687903, acc.: 52.15%] [G loss: 0.719532]
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5020 [D loss: 0.684003, acc.: 57.03%] [G loss: 0.724563]
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5021 [D loss: 0.680961, acc.: 56.05%] [G loss: 0.731916]
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5022 [D loss: 0.683958, acc.: 57.23%] [G loss: 0.724917]
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5023 [D loss: 0.685158, acc.: 55.66%] [G loss: 0.731927]
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5024 [D loss: 0.688254, acc.: 54.10%] [G loss: 0.727425]
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5025 [D loss: 0.690714, acc.: 54.30%] [G loss: 0.723803]
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5026 [D loss: 0.688648, acc.: 53.91%] [G loss: 0.720463]
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5027 [D loss: 0.684898, acc.: 55.27%] [G loss: 0.714903]
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5028 [D loss: 0.686843, acc.: 55.86%] [G loss: 0.718345]
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5029 [D loss: 0.685832, acc.: 53.91%] [G loss: 0.722962]
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5030 [D loss: 0.688572, acc.: 53.32%] [G loss: 0.714217]
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5031 [D loss: 0.686967, acc.: 56.05%] [G loss: 0.720659]
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5032 [D loss: 0.683389, acc.: 54.88%] [G loss: 0.713553]
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5033 [D loss: 0.688336, acc.: 54.88%] [G loss: 0.719410]
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5034 [D loss: 0.687866, acc.: 54.49%] [G loss: 0.727022]
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5035 [D loss: 0.680705, acc.: 54.69%] [G loss: 0.720651]
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5036 [D loss: 0.685448, acc.: 55.08%] [G loss: 0.723877]
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5037 [D loss: 0.687642, acc.: 56.45%] [G loss: 0.723927]
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5038 [D loss: 0.690199, acc.: 53.52%] [G loss: 0.716871]
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5039 [D loss: 0.686428, acc.: 53.71%] [G loss: 0.723258]
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5040 [D loss: 0.682237, acc.: 58.40%] [G loss: 0.728226]
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5041 [D loss: 0.691781, acc.: 53.32%] [G loss: 0.721941]
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5042 [D loss: 0.687692, acc.: 53.32%] [G loss: 0.721566]
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5043 [D loss: 0.691030, acc.: 53.52%] [G loss: 0.722811]
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5044 [D loss: 0.677569, acc.: 61.13%] [G loss: 0.731592]
8/8 [==============================] - 0s 4ms/step
5045 [D loss: 0.681123, acc.: 60.74%] [G loss: 0.717623]
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5046 [D loss: 0.686958, acc.: 56.05%] [G loss: 0.721071]
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5047 [D loss: 0.690360, acc.: 51.95%] [G loss: 0.720687]
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5048 [D loss: 0.686908, acc.: 56.05%] [G loss: 0.719684]
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5049 [D loss: 0.693841, acc.: 51.56%] [G loss: 0.723330]
8/8 [==============================] - 0s 4ms/step
5050 [D loss: 0.688249, acc.: 53.71%] [G loss: 0.719560]
1/1 [==============================] - 0s 17ms/step
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5051 [D loss: 0.682045, acc.: 57.42%] [G loss: 0.738216]
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5052 [D loss: 0.685684, acc.: 55.27%] [G loss: 0.717363]
8/8 [==============================] - 0s 4ms/step
5053 [D loss: 0.683784, acc.: 55.86%] [G loss: 0.718098]
8/8 [==============================] - 0s 4ms/step
5054 [D loss: 0.688861, acc.: 53.12%] [G loss: 0.709198]
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5055 [D loss: 0.691753, acc.: 51.37%] [G loss: 0.715396]
8/8 [==============================] - 0s 4ms/step
5056 [D loss: 0.689533, acc.: 53.91%] [G loss: 0.717356]
8/8 [==============================] - 0s 4ms/step
5057 [D loss: 0.688477, acc.: 55.47%] [G loss: 0.726803]
8/8 [==============================] - 0s 4ms/step
5058 [D loss: 0.684719, acc.: 55.66%] [G loss: 0.733207]
8/8 [==============================] - 0s 4ms/step
5059 [D loss: 0.682452, acc.: 59.96%] [G loss: 0.724677]
8/8 [==============================] - 0s 4ms/step
5060 [D loss: 0.680558, acc.: 59.38%] [G loss: 0.725549]
8/8 [==============================] - 0s 4ms/step
5061 [D loss: 0.688632, acc.: 53.32%] [G loss: 0.713534]
8/8 [==============================] - 0s 4ms/step
5062 [D loss: 0.697433, acc.: 51.17%] [G loss: 0.714622]
8/8 [==============================] - 0s 4ms/step
5063 [D loss: 0.684272, acc.: 57.81%] [G loss: 0.724944]
8/8 [==============================] - 0s 4ms/step
5064 [D loss: 0.678221, acc.: 56.64%] [G loss: 0.730771]
8/8 [==============================] - 0s 4ms/step
5065 [D loss: 0.684882, acc.: 56.05%] [G loss: 0.721171]
8/8 [==============================] - 0s 4ms/step
5066 [D loss: 0.688273, acc.: 54.30%] [G loss: 0.720894]
8/8 [==============================] - 0s 4ms/step
5067 [D loss: 0.689000, acc.: 52.54%] [G loss: 0.716893]
8/8 [==============================] - 0s 4ms/step
5068 [D loss: 0.691491, acc.: 52.15%] [G loss: 0.715769]
8/8 [==============================] - 0s 4ms/step
5069 [D loss: 0.689268, acc.: 53.32%] [G loss: 0.725615]
8/8 [==============================] - 0s 4ms/step
5070 [D loss: 0.687581, acc.: 55.47%] [G loss: 0.729068]
8/8 [==============================] - 0s 4ms/step
5071 [D loss: 0.682368, acc.: 54.49%] [G loss: 0.726980]
8/8 [==============================] - 0s 4ms/step
5072 [D loss: 0.680927, acc.: 58.01%] [G loss: 0.720687]
8/8 [==============================] - 0s 4ms/step
5073 [D loss: 0.687113, acc.: 56.25%] [G loss: 0.727226]
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5074 [D loss: 0.687343, acc.: 51.56%] [G loss: 0.716526]
8/8 [==============================] - 0s 4ms/step
5075 [D loss: 0.685378, acc.: 54.49%] [G loss: 0.710582]
8/8 [==============================] - 0s 4ms/step
5076 [D loss: 0.680374, acc.: 57.23%] [G loss: 0.715871]
8/8 [==============================] - 0s 4ms/step
5077 [D loss: 0.678267, acc.: 60.74%] [G loss: 0.723017]
8/8 [==============================] - 0s 4ms/step
5078 [D loss: 0.677975, acc.: 62.11%] [G loss: 0.716754]
8/8 [==============================] - 0s 4ms/step
5079 [D loss: 0.687721, acc.: 55.27%] [G loss: 0.724770]
8/8 [==============================] - 0s 4ms/step
5080 [D loss: 0.692440, acc.: 53.32%] [G loss: 0.724982]
8/8 [==============================] - 0s 4ms/step
5081 [D loss: 0.680677, acc.: 58.01%] [G loss: 0.727841]
8/8 [==============================] - 0s 4ms/step
5082 [D loss: 0.685003, acc.: 56.45%] [G loss: 0.730931]
8/8 [==============================] - 0s 4ms/step
5083 [D loss: 0.685471, acc.: 59.57%] [G loss: 0.728211]
8/8 [==============================] - 0s 4ms/step
5084 [D loss: 0.676472, acc.: 58.01%] [G loss: 0.728329]
8/8 [==============================] - 0s 4ms/step
5085 [D loss: 0.682322, acc.: 58.20%] [G loss: 0.719254]
8/8 [==============================] - 0s 4ms/step
5086 [D loss: 0.688335, acc.: 54.88%] [G loss: 0.718309]
8/8 [==============================] - 0s 4ms/step
5087 [D loss: 0.683149, acc.: 56.05%] [G loss: 0.702747]
8/8 [==============================] - 0s 4ms/step
5088 [D loss: 0.687015, acc.: 58.40%] [G loss: 0.712755]
8/8 [==============================] - 0s 4ms/step
5089 [D loss: 0.688375, acc.: 54.88%] [G loss: 0.714709]
8/8 [==============================] - 0s 4ms/step
5090 [D loss: 0.679765, acc.: 56.84%] [G loss: 0.718862]
8/8 [==============================] - 0s 4ms/step
5091 [D loss: 0.683716, acc.: 58.79%] [G loss: 0.708731]
8/8 [==============================] - 0s 4ms/step
5092 [D loss: 0.686725, acc.: 52.54%] [G loss: 0.718918]
8/8 [==============================] - 0s 4ms/step
5093 [D loss: 0.690100, acc.: 52.54%] [G loss: 0.714076]
8/8 [==============================] - 0s 4ms/step
5094 [D loss: 0.689901, acc.: 52.73%] [G loss: 0.710219]
8/8 [==============================] - 0s 4ms/step
5095 [D loss: 0.683770, acc.: 57.03%] [G loss: 0.710055]
8/8 [==============================] - 0s 4ms/step
5096 [D loss: 0.684770, acc.: 53.71%] [G loss: 0.711745]
8/8 [==============================] - 0s 4ms/step
5097 [D loss: 0.685694, acc.: 55.47%] [G loss: 0.714232]
8/8 [==============================] - 0s 4ms/step
5098 [D loss: 0.684436, acc.: 57.42%] [G loss: 0.715724]
8/8 [==============================] - 0s 4ms/step
5099 [D loss: 0.685097, acc.: 55.66%] [G loss: 0.723126]
8/8 [==============================] - 0s 4ms/step
5100 [D loss: 0.690532, acc.: 54.10%] [G loss: 0.721248]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 4ms/step
5101 [D loss: 0.678470, acc.: 58.01%] [G loss: 0.728712]
8/8 [==============================] - 0s 4ms/step
5102 [D loss: 0.680983, acc.: 58.59%] [G loss: 0.725150]
8/8 [==============================] - 0s 4ms/step
5103 [D loss: 0.688970, acc.: 52.93%] [G loss: 0.714601]
8/8 [==============================] - 0s 4ms/step
5104 [D loss: 0.683074, acc.: 54.88%] [G loss: 0.710454]
8/8 [==============================] - 0s 4ms/step
5105 [D loss: 0.684782, acc.: 56.84%] [G loss: 0.716592]
8/8 [==============================] - 0s 4ms/step
5106 [D loss: 0.687329, acc.: 56.05%] [G loss: 0.721709]
8/8 [==============================] - 0s 4ms/step
5107 [D loss: 0.683792, acc.: 54.88%] [G loss: 0.734825]
8/8 [==============================] - 0s 4ms/step
5108 [D loss: 0.686565, acc.: 54.30%] [G loss: 0.724197]
8/8 [==============================] - 0s 4ms/step
5109 [D loss: 0.694085, acc.: 50.59%] [G loss: 0.708210]
8/8 [==============================] - 0s 4ms/step
5110 [D loss: 0.689801, acc.: 53.91%] [G loss: 0.716773]
8/8 [==============================] - 0s 4ms/step
5111 [D loss: 0.691609, acc.: 55.66%] [G loss: 0.715366]
8/8 [==============================] - 0s 4ms/step
5112 [D loss: 0.693322, acc.: 52.93%] [G loss: 0.719888]
8/8 [==============================] - 0s 4ms/step
5113 [D loss: 0.687106, acc.: 54.30%] [G loss: 0.725957]
8/8 [==============================] - 0s 4ms/step
5114 [D loss: 0.681935, acc.: 59.38%] [G loss: 0.731932]
8/8 [==============================] - 0s 4ms/step
5115 [D loss: 0.683130, acc.: 55.47%] [G loss: 0.722022]
8/8 [==============================] - 0s 4ms/step
5116 [D loss: 0.694997, acc.: 52.15%] [G loss: 0.722146]
8/8 [==============================] - 0s 4ms/step
5117 [D loss: 0.687597, acc.: 56.05%] [G loss: 0.720132]
8/8 [==============================] - 0s 4ms/step
5118 [D loss: 0.684952, acc.: 53.91%] [G loss: 0.721132]
8/8 [==============================] - 0s 4ms/step
5119 [D loss: 0.686698, acc.: 55.47%] [G loss: 0.719796]
8/8 [==============================] - 0s 4ms/step
5120 [D loss: 0.682425, acc.: 55.86%] [G loss: 0.720603]
8/8 [==============================] - 0s 4ms/step
5121 [D loss: 0.683383, acc.: 56.84%] [G loss: 0.724581]
8/8 [==============================] - 0s 4ms/step
5122 [D loss: 0.689454, acc.: 53.12%] [G loss: 0.714599]
8/8 [==============================] - 0s 4ms/step
5123 [D loss: 0.680752, acc.: 59.18%] [G loss: 0.729486]
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5124 [D loss: 0.679448, acc.: 58.01%] [G loss: 0.716383]
8/8 [==============================] - 0s 4ms/step
5125 [D loss: 0.678304, acc.: 60.94%] [G loss: 0.736336]
8/8 [==============================] - 0s 4ms/step
5126 [D loss: 0.673378, acc.: 63.28%] [G loss: 0.736420]
8/8 [==============================] - 0s 4ms/step
5127 [D loss: 0.680234, acc.: 59.38%] [G loss: 0.722038]
8/8 [==============================] - 0s 4ms/step
5128 [D loss: 0.689459, acc.: 53.71%] [G loss: 0.698920]
8/8 [==============================] - 0s 4ms/step
5129 [D loss: 0.693827, acc.: 54.88%] [G loss: 0.695307]
8/8 [==============================] - 0s 4ms/step
5130 [D loss: 0.701473, acc.: 49.02%] [G loss: 0.697481]
8/8 [==============================] - 0s 4ms/step
5131 [D loss: 0.685860, acc.: 54.69%] [G loss: 0.702694]
8/8 [==============================] - 0s 4ms/step
5132 [D loss: 0.689583, acc.: 55.08%] [G loss: 0.721840]
8/8 [==============================] - 0s 4ms/step
5133 [D loss: 0.677766, acc.: 56.05%] [G loss: 0.722746]
8/8 [==============================] - 0s 4ms/step
5134 [D loss: 0.680032, acc.: 58.20%] [G loss: 0.734943]
8/8 [==============================] - 0s 4ms/step
5135 [D loss: 0.679466, acc.: 58.01%] [G loss: 0.714367]
8/8 [==============================] - 0s 4ms/step
5136 [D loss: 0.684018, acc.: 53.71%] [G loss: 0.715007]
8/8 [==============================] - 0s 4ms/step
5137 [D loss: 0.692915, acc.: 51.37%] [G loss: 0.706638]
8/8 [==============================] - 0s 4ms/step
5138 [D loss: 0.696354, acc.: 50.78%] [G loss: 0.709164]
8/8 [==============================] - 0s 4ms/step
5139 [D loss: 0.694621, acc.: 52.34%] [G loss: 0.715600]
8/8 [==============================] - 0s 4ms/step
5140 [D loss: 0.686349, acc.: 53.71%] [G loss: 0.730238]
8/8 [==============================] - 0s 4ms/step
5141 [D loss: 0.686637, acc.: 54.10%] [G loss: 0.735352]
8/8 [==============================] - 0s 4ms/step
5142 [D loss: 0.679565, acc.: 56.84%] [G loss: 0.739298]
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5143 [D loss: 0.682433, acc.: 56.84%] [G loss: 0.733195]
8/8 [==============================] - 0s 4ms/step
5144 [D loss: 0.685087, acc.: 54.69%] [G loss: 0.725801]
8/8 [==============================] - 0s 4ms/step
5145 [D loss: 0.692222, acc.: 51.37%] [G loss: 0.718347]
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5146 [D loss: 0.690776, acc.: 55.08%] [G loss: 0.717787]
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5147 [D loss: 0.684172, acc.: 57.03%] [G loss: 0.722585]
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5148 [D loss: 0.686910, acc.: 54.69%] [G loss: 0.747887]
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5149 [D loss: 0.675376, acc.: 59.96%] [G loss: 0.737340]
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5150 [D loss: 0.684720, acc.: 52.15%] [G loss: 0.736196]
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5151 [D loss: 0.678294, acc.: 56.84%] [G loss: 0.734094]
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5152 [D loss: 0.688152, acc.: 54.49%] [G loss: 0.720164]
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5153 [D loss: 0.687509, acc.: 54.49%] [G loss: 0.716507]
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5154 [D loss: 0.692606, acc.: 52.15%] [G loss: 0.721722]
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5155 [D loss: 0.687469, acc.: 55.86%] [G loss: 0.734288]
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5156 [D loss: 0.685874, acc.: 54.88%] [G loss: 0.732134]
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5157 [D loss: 0.677679, acc.: 59.38%] [G loss: 0.727630]
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5158 [D loss: 0.685115, acc.: 52.73%] [G loss: 0.733559]
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5159 [D loss: 0.683577, acc.: 53.32%] [G loss: 0.722214]
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5160 [D loss: 0.681427, acc.: 56.05%] [G loss: 0.708385]
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5161 [D loss: 0.685915, acc.: 56.45%] [G loss: 0.705954]
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5162 [D loss: 0.685766, acc.: 54.69%] [G loss: 0.715686]
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5163 [D loss: 0.680767, acc.: 57.81%] [G loss: 0.720556]
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5164 [D loss: 0.681115, acc.: 57.62%] [G loss: 0.726321]
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5165 [D loss: 0.680421, acc.: 55.86%] [G loss: 0.736912]
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5166 [D loss: 0.682397, acc.: 54.30%] [G loss: 0.722311]
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5167 [D loss: 0.681545, acc.: 56.25%] [G loss: 0.715326]
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5168 [D loss: 0.693320, acc.: 49.61%] [G loss: 0.720934]
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5169 [D loss: 0.678054, acc.: 59.96%] [G loss: 0.728896]
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5170 [D loss: 0.681069, acc.: 57.03%] [G loss: 0.741565]
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5171 [D loss: 0.680576, acc.: 58.59%] [G loss: 0.731628]
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5172 [D loss: 0.678280, acc.: 58.79%] [G loss: 0.718501]
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5173 [D loss: 0.677897, acc.: 57.62%] [G loss: 0.718851]
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5174 [D loss: 0.689562, acc.: 55.47%] [G loss: 0.710135]
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5175 [D loss: 0.699327, acc.: 50.20%] [G loss: 0.694308]
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5176 [D loss: 0.703609, acc.: 46.68%] [G loss: 0.701754]
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5177 [D loss: 0.698324, acc.: 50.39%] [G loss: 0.710464]
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5178 [D loss: 0.684125, acc.: 55.47%] [G loss: 0.737766]
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5179 [D loss: 0.678831, acc.: 57.62%] [G loss: 0.745779]
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5180 [D loss: 0.670260, acc.: 62.11%] [G loss: 0.743731]
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5181 [D loss: 0.680647, acc.: 57.42%] [G loss: 0.741409]
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5182 [D loss: 0.679617, acc.: 57.03%] [G loss: 0.727825]
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5183 [D loss: 0.684772, acc.: 56.64%] [G loss: 0.719120]
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5184 [D loss: 0.685475, acc.: 54.30%] [G loss: 0.718226]
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5185 [D loss: 0.691804, acc.: 55.27%] [G loss: 0.710400]
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5186 [D loss: 0.683936, acc.: 54.69%] [G loss: 0.722686]
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5187 [D loss: 0.683034, acc.: 57.03%] [G loss: 0.732441]
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5188 [D loss: 0.686442, acc.: 55.66%] [G loss: 0.736654]
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5189 [D loss: 0.677638, acc.: 60.16%] [G loss: 0.737129]
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5190 [D loss: 0.688423, acc.: 54.88%] [G loss: 0.737057]
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5191 [D loss: 0.686581, acc.: 53.12%] [G loss: 0.720581]
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5192 [D loss: 0.700401, acc.: 52.15%] [G loss: 0.715671]
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5193 [D loss: 0.694383, acc.: 49.80%] [G loss: 0.723512]
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5194 [D loss: 0.684798, acc.: 53.52%] [G loss: 0.724074]
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5195 [D loss: 0.689418, acc.: 52.73%] [G loss: 0.718934]
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5196 [D loss: 0.683187, acc.: 53.71%] [G loss: 0.720373]
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5197 [D loss: 0.687206, acc.: 57.81%] [G loss: 0.718916]
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5198 [D loss: 0.689054, acc.: 52.34%] [G loss: 0.713552]
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5199 [D loss: 0.684687, acc.: 53.52%] [G loss: 0.713106]
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5200 [D loss: 0.686592, acc.: 54.30%] [G loss: 0.712025]
1/1 [==============================] - 0s 17ms/step
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5201 [D loss: 0.685950, acc.: 54.88%] [G loss: 0.723250]
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5202 [D loss: 0.689668, acc.: 52.34%] [G loss: 0.711520]
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5203 [D loss: 0.681438, acc.: 56.64%] [G loss: 0.721041]
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5204 [D loss: 0.687902, acc.: 55.66%] [G loss: 0.723187]
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5205 [D loss: 0.687971, acc.: 52.34%] [G loss: 0.727490]
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5206 [D loss: 0.687379, acc.: 53.71%] [G loss: 0.724159]
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5207 [D loss: 0.684487, acc.: 57.23%] [G loss: 0.731901]
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5208 [D loss: 0.680575, acc.: 59.77%] [G loss: 0.727294]
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5209 [D loss: 0.678077, acc.: 61.72%] [G loss: 0.731348]
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5210 [D loss: 0.680277, acc.: 57.81%] [G loss: 0.723581]
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5211 [D loss: 0.677611, acc.: 60.35%] [G loss: 0.716382]
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5212 [D loss: 0.684823, acc.: 55.86%] [G loss: 0.725431]
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5213 [D loss: 0.679972, acc.: 57.81%] [G loss: 0.712606]
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5214 [D loss: 0.686954, acc.: 53.91%] [G loss: 0.717925]
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5215 [D loss: 0.681150, acc.: 58.79%] [G loss: 0.718443]
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5216 [D loss: 0.679521, acc.: 58.20%] [G loss: 0.717119]
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5217 [D loss: 0.684375, acc.: 57.42%] [G loss: 0.703884]
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5218 [D loss: 0.695335, acc.: 49.41%] [G loss: 0.707014]
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5219 [D loss: 0.689492, acc.: 53.71%] [G loss: 0.721880]
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5220 [D loss: 0.689531, acc.: 52.93%] [G loss: 0.705823]
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5221 [D loss: 0.687264, acc.: 54.69%] [G loss: 0.721232]
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5222 [D loss: 0.687424, acc.: 54.49%] [G loss: 0.719011]
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5223 [D loss: 0.690032, acc.: 52.34%] [G loss: 0.718001]
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5224 [D loss: 0.678374, acc.: 58.40%] [G loss: 0.721813]
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5225 [D loss: 0.675780, acc.: 59.18%] [G loss: 0.722407]
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5226 [D loss: 0.678120, acc.: 58.20%] [G loss: 0.716601]
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5227 [D loss: 0.697156, acc.: 52.15%] [G loss: 0.712909]
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5228 [D loss: 0.689775, acc.: 52.15%] [G loss: 0.713252]
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5229 [D loss: 0.685136, acc.: 55.27%] [G loss: 0.728670]
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5230 [D loss: 0.682899, acc.: 54.30%] [G loss: 0.739561]
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5231 [D loss: 0.674843, acc.: 60.35%] [G loss: 0.731311]
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5232 [D loss: 0.683828, acc.: 56.05%] [G loss: 0.719490]
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5233 [D loss: 0.684124, acc.: 56.05%] [G loss: 0.724368]
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5234 [D loss: 0.693665, acc.: 50.78%] [G loss: 0.724414]
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5235 [D loss: 0.684437, acc.: 54.49%] [G loss: 0.715407]
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5236 [D loss: 0.682631, acc.: 57.62%] [G loss: 0.722578]
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5237 [D loss: 0.680914, acc.: 58.59%] [G loss: 0.720748]
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5238 [D loss: 0.683892, acc.: 56.25%] [G loss: 0.730681]
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5239 [D loss: 0.689458, acc.: 55.66%] [G loss: 0.735110]
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5240 [D loss: 0.682488, acc.: 58.20%] [G loss: 0.723053]
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5241 [D loss: 0.686063, acc.: 54.88%] [G loss: 0.725301]
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5242 [D loss: 0.684883, acc.: 56.05%] [G loss: 0.717322]
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5243 [D loss: 0.679552, acc.: 57.23%] [G loss: 0.722888]
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5244 [D loss: 0.688798, acc.: 55.86%] [G loss: 0.718914]
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5245 [D loss: 0.687698, acc.: 53.32%] [G loss: 0.719716]
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5246 [D loss: 0.689073, acc.: 55.27%] [G loss: 0.713304]
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5247 [D loss: 0.691711, acc.: 52.93%] [G loss: 0.710013]
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5248 [D loss: 0.686339, acc.: 55.66%] [G loss: 0.715239]
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5249 [D loss: 0.686984, acc.: 55.86%] [G loss: 0.716069]
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5250 [D loss: 0.678527, acc.: 58.98%] [G loss: 0.721528]
1/1 [==============================] - 0s 16ms/step
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5251 [D loss: 0.677483, acc.: 58.20%] [G loss: 0.724078]
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5252 [D loss: 0.685565, acc.: 56.05%] [G loss: 0.717204]
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5253 [D loss: 0.684273, acc.: 58.98%] [G loss: 0.728051]
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5254 [D loss: 0.689085, acc.: 55.08%] [G loss: 0.714939]
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5255 [D loss: 0.686990, acc.: 55.08%] [G loss: 0.727878]
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5256 [D loss: 0.690392, acc.: 53.91%] [G loss: 0.717506]
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5257 [D loss: 0.685795, acc.: 54.49%] [G loss: 0.724358]
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5258 [D loss: 0.684582, acc.: 56.05%] [G loss: 0.719319]
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5259 [D loss: 0.677972, acc.: 60.35%] [G loss: 0.727642]
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5260 [D loss: 0.680357, acc.: 58.59%] [G loss: 0.721777]
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5261 [D loss: 0.684315, acc.: 57.03%] [G loss: 0.725741]
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5262 [D loss: 0.694431, acc.: 51.37%] [G loss: 0.724067]
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5263 [D loss: 0.689099, acc.: 53.71%] [G loss: 0.715807]
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5264 [D loss: 0.689714, acc.: 51.37%] [G loss: 0.717584]
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5265 [D loss: 0.688632, acc.: 52.54%] [G loss: 0.731788]
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5266 [D loss: 0.682303, acc.: 55.66%] [G loss: 0.722744]
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5267 [D loss: 0.681883, acc.: 56.05%] [G loss: 0.728604]
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5268 [D loss: 0.693699, acc.: 52.15%] [G loss: 0.722559]
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5269 [D loss: 0.692523, acc.: 50.98%] [G loss: 0.717516]
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5270 [D loss: 0.686646, acc.: 55.27%] [G loss: 0.720638]
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5271 [D loss: 0.688962, acc.: 52.15%] [G loss: 0.720958]
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5272 [D loss: 0.685412, acc.: 55.08%] [G loss: 0.725865]
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5273 [D loss: 0.681624, acc.: 55.86%] [G loss: 0.751008]
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5274 [D loss: 0.687581, acc.: 53.71%] [G loss: 0.752275]
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5275 [D loss: 0.675659, acc.: 60.55%] [G loss: 0.739302]
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5276 [D loss: 0.682099, acc.: 55.47%] [G loss: 0.725598]
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5277 [D loss: 0.682796, acc.: 58.40%] [G loss: 0.720311]
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5278 [D loss: 0.681348, acc.: 55.27%] [G loss: 0.713736]
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5279 [D loss: 0.694159, acc.: 48.63%] [G loss: 0.716540]
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5280 [D loss: 0.684648, acc.: 58.79%] [G loss: 0.719720]
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5281 [D loss: 0.685102, acc.: 54.69%] [G loss: 0.715126]
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5282 [D loss: 0.685165, acc.: 54.88%] [G loss: 0.731857]
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5283 [D loss: 0.682714, acc.: 54.30%] [G loss: 0.730069]
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5284 [D loss: 0.684220, acc.: 53.91%] [G loss: 0.732401]
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5285 [D loss: 0.684444, acc.: 51.95%] [G loss: 0.719553]
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5286 [D loss: 0.687818, acc.: 50.78%] [G loss: 0.718444]
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5287 [D loss: 0.689254, acc.: 53.52%] [G loss: 0.722632]
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5288 [D loss: 0.684265, acc.: 55.66%] [G loss: 0.720196]
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5289 [D loss: 0.684176, acc.: 56.25%] [G loss: 0.730080]
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5290 [D loss: 0.690687, acc.: 55.66%] [G loss: 0.724218]
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5291 [D loss: 0.679699, acc.: 58.20%] [G loss: 0.727324]
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5292 [D loss: 0.678700, acc.: 58.98%] [G loss: 0.713533]
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5293 [D loss: 0.680971, acc.: 58.01%] [G loss: 0.707947]
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5294 [D loss: 0.670533, acc.: 62.30%] [G loss: 0.712765]
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5295 [D loss: 0.667185, acc.: 60.94%] [G loss: 0.712260]
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5296 [D loss: 0.685939, acc.: 52.54%] [G loss: 0.713707]
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5297 [D loss: 0.685480, acc.: 55.86%] [G loss: 0.713336]
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5298 [D loss: 0.685793, acc.: 54.49%] [G loss: 0.705194]
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5299 [D loss: 0.694073, acc.: 50.20%] [G loss: 0.709129]
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5300 [D loss: 0.688174, acc.: 54.69%] [G loss: 0.710375]
1/1 [==============================] - 0s 17ms/step
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5301 [D loss: 0.686350, acc.: 54.49%] [G loss: 0.723265]
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5302 [D loss: 0.690553, acc.: 55.27%] [G loss: 0.736120]
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5303 [D loss: 0.678580, acc.: 57.42%] [G loss: 0.750098]
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5304 [D loss: 0.675873, acc.: 61.33%] [G loss: 0.749147]
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5305 [D loss: 0.679772, acc.: 59.38%] [G loss: 0.742929]
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5306 [D loss: 0.684687, acc.: 56.25%] [G loss: 0.732133]
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5307 [D loss: 0.685515, acc.: 52.73%] [G loss: 0.729768]
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5308 [D loss: 0.684818, acc.: 55.08%] [G loss: 0.725284]
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5309 [D loss: 0.677117, acc.: 58.20%] [G loss: 0.720897]
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5310 [D loss: 0.682403, acc.: 55.66%] [G loss: 0.721481]
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5311 [D loss: 0.687908, acc.: 55.66%] [G loss: 0.726384]
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5312 [D loss: 0.680113, acc.: 58.79%] [G loss: 0.727238]
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5313 [D loss: 0.684141, acc.: 56.64%] [G loss: 0.728217]
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5314 [D loss: 0.683291, acc.: 56.84%] [G loss: 0.721941]
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5315 [D loss: 0.683819, acc.: 58.59%] [G loss: 0.725492]
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5316 [D loss: 0.685386, acc.: 54.10%] [G loss: 0.724230]
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5317 [D loss: 0.686675, acc.: 57.42%] [G loss: 0.721237]
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5318 [D loss: 0.684843, acc.: 54.30%] [G loss: 0.717169]
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5319 [D loss: 0.682537, acc.: 55.86%] [G loss: 0.718746]
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5320 [D loss: 0.689500, acc.: 53.52%] [G loss: 0.717028]
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5321 [D loss: 0.681932, acc.: 58.40%] [G loss: 0.712547]
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5322 [D loss: 0.690922, acc.: 52.93%] [G loss: 0.713953]
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5323 [D loss: 0.690420, acc.: 50.59%] [G loss: 0.715250]
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5324 [D loss: 0.687060, acc.: 55.47%] [G loss: 0.726779]
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5325 [D loss: 0.679132, acc.: 57.23%] [G loss: 0.725102]
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5326 [D loss: 0.675811, acc.: 57.42%] [G loss: 0.725260]
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5327 [D loss: 0.683443, acc.: 57.23%] [G loss: 0.732234]
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5328 [D loss: 0.685877, acc.: 57.23%] [G loss: 0.731198]
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5329 [D loss: 0.692211, acc.: 51.17%] [G loss: 0.715426]
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5330 [D loss: 0.682272, acc.: 56.45%] [G loss: 0.720425]
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5331 [D loss: 0.686322, acc.: 56.05%] [G loss: 0.717519]
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5332 [D loss: 0.688672, acc.: 53.12%] [G loss: 0.731795]
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5333 [D loss: 0.681599, acc.: 56.84%] [G loss: 0.731192]
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5334 [D loss: 0.686812, acc.: 54.88%] [G loss: 0.729975]
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5335 [D loss: 0.687240, acc.: 54.30%] [G loss: 0.740581]
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5336 [D loss: 0.678689, acc.: 60.55%] [G loss: 0.724223]
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5337 [D loss: 0.679052, acc.: 57.23%] [G loss: 0.716717]
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5338 [D loss: 0.686715, acc.: 55.27%] [G loss: 0.712026]
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5339 [D loss: 0.691658, acc.: 52.73%] [G loss: 0.716348]
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5340 [D loss: 0.687028, acc.: 53.12%] [G loss: 0.712685]
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5341 [D loss: 0.683400, acc.: 54.88%] [G loss: 0.728812]
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5342 [D loss: 0.687330, acc.: 55.08%] [G loss: 0.731426]
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5343 [D loss: 0.681227, acc.: 56.64%] [G loss: 0.721892]
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5344 [D loss: 0.681085, acc.: 56.84%] [G loss: 0.718648]
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5345 [D loss: 0.689954, acc.: 54.10%] [G loss: 0.723734]
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5346 [D loss: 0.680121, acc.: 57.62%] [G loss: 0.724816]
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5347 [D loss: 0.686279, acc.: 57.03%] [G loss: 0.727820]
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5348 [D loss: 0.686352, acc.: 52.73%] [G loss: 0.727363]
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5349 [D loss: 0.685804, acc.: 54.69%] [G loss: 0.732122]
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5350 [D loss: 0.682610, acc.: 59.18%] [G loss: 0.710047]
1/1 [==============================] - 0s 16ms/step
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5351 [D loss: 0.681035, acc.: 56.05%] [G loss: 0.705635]
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5352 [D loss: 0.693380, acc.: 50.59%] [G loss: 0.707207]
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5353 [D loss: 0.699526, acc.: 51.37%] [G loss: 0.709074]
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5354 [D loss: 0.693623, acc.: 52.15%] [G loss: 0.721954]
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5355 [D loss: 0.683376, acc.: 56.84%] [G loss: 0.729624]
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5356 [D loss: 0.678012, acc.: 61.33%] [G loss: 0.726496]
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5357 [D loss: 0.677101, acc.: 60.55%] [G loss: 0.734632]
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5358 [D loss: 0.682348, acc.: 56.25%] [G loss: 0.719768]
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5359 [D loss: 0.686294, acc.: 54.88%] [G loss: 0.727026]
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5360 [D loss: 0.683108, acc.: 55.47%] [G loss: 0.720503]
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5361 [D loss: 0.691973, acc.: 51.17%] [G loss: 0.733271]
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5362 [D loss: 0.677199, acc.: 61.13%] [G loss: 0.729831]
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5363 [D loss: 0.684059, acc.: 57.62%] [G loss: 0.737643]
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5364 [D loss: 0.689205, acc.: 51.56%] [G loss: 0.720977]
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5365 [D loss: 0.681630, acc.: 55.66%] [G loss: 0.727383]
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5366 [D loss: 0.683901, acc.: 56.25%] [G loss: 0.721659]
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5367 [D loss: 0.687516, acc.: 53.71%] [G loss: 0.720202]
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5368 [D loss: 0.686008, acc.: 55.08%] [G loss: 0.703765]
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5369 [D loss: 0.686713, acc.: 55.27%] [G loss: 0.712332]
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5370 [D loss: 0.691657, acc.: 49.80%] [G loss: 0.715826]
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5371 [D loss: 0.690187, acc.: 54.30%] [G loss: 0.715541]
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5372 [D loss: 0.684780, acc.: 54.69%] [G loss: 0.716707]
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5373 [D loss: 0.687113, acc.: 56.84%] [G loss: 0.721867]
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5374 [D loss: 0.684595, acc.: 55.86%] [G loss: 0.724881]
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5375 [D loss: 0.685182, acc.: 57.23%] [G loss: 0.740893]
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5376 [D loss: 0.689193, acc.: 52.34%] [G loss: 0.726239]
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5377 [D loss: 0.680014, acc.: 58.79%] [G loss: 0.739489]
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5378 [D loss: 0.675773, acc.: 60.55%] [G loss: 0.747532]
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5379 [D loss: 0.675199, acc.: 62.89%] [G loss: 0.734447]
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5380 [D loss: 0.683813, acc.: 57.03%] [G loss: 0.728932]
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5381 [D loss: 0.686384, acc.: 53.91%] [G loss: 0.713557]
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5382 [D loss: 0.694351, acc.: 50.98%] [G loss: 0.718801]
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5383 [D loss: 0.688133, acc.: 53.52%] [G loss: 0.710879]
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5384 [D loss: 0.685546, acc.: 53.32%] [G loss: 0.716021]
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5385 [D loss: 0.678910, acc.: 58.98%] [G loss: 0.723864]
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5386 [D loss: 0.683008, acc.: 56.84%] [G loss: 0.727403]
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5387 [D loss: 0.677809, acc.: 59.57%] [G loss: 0.724187]
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5388 [D loss: 0.680699, acc.: 57.62%] [G loss: 0.719180]
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5389 [D loss: 0.686657, acc.: 56.64%] [G loss: 0.718709]
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5390 [D loss: 0.682403, acc.: 58.40%] [G loss: 0.724142]
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5391 [D loss: 0.687130, acc.: 56.05%] [G loss: 0.716182]
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5392 [D loss: 0.684831, acc.: 55.08%] [G loss: 0.715939]
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5393 [D loss: 0.686003, acc.: 55.47%] [G loss: 0.724940]
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5394 [D loss: 0.687049, acc.: 53.52%] [G loss: 0.727551]
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5395 [D loss: 0.672988, acc.: 61.91%] [G loss: 0.717685]
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5396 [D loss: 0.686863, acc.: 54.69%] [G loss: 0.710144]
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5397 [D loss: 0.682709, acc.: 55.86%] [G loss: 0.714146]
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5398 [D loss: 0.684371, acc.: 54.69%] [G loss: 0.721681]
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5399 [D loss: 0.679658, acc.: 57.62%] [G loss: 0.723863]
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5400 [D loss: 0.691786, acc.: 51.37%] [G loss: 0.722022]
1/1 [==============================] - 0s 17ms/step
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5401 [D loss: 0.679075, acc.: 54.10%] [G loss: 0.718731]
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5402 [D loss: 0.685313, acc.: 52.15%] [G loss: 0.712945]
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5403 [D loss: 0.689405, acc.: 53.12%] [G loss: 0.703832]
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5404 [D loss: 0.687669, acc.: 54.88%] [G loss: 0.715604]
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5405 [D loss: 0.693513, acc.: 50.39%] [G loss: 0.716164]
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5406 [D loss: 0.685356, acc.: 55.08%] [G loss: 0.722490]
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5407 [D loss: 0.682719, acc.: 57.62%] [G loss: 0.729055]
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5408 [D loss: 0.682116, acc.: 54.30%] [G loss: 0.735961]
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5409 [D loss: 0.676921, acc.: 58.79%] [G loss: 0.755576]
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5410 [D loss: 0.679349, acc.: 57.62%] [G loss: 0.733401]
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5411 [D loss: 0.687530, acc.: 55.27%] [G loss: 0.726288]
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5412 [D loss: 0.693685, acc.: 49.61%] [G loss: 0.720726]
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5413 [D loss: 0.689091, acc.: 53.12%] [G loss: 0.719647]
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5414 [D loss: 0.688075, acc.: 53.32%] [G loss: 0.724707]
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5415 [D loss: 0.681195, acc.: 57.03%] [G loss: 0.724453]
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5416 [D loss: 0.682988, acc.: 57.03%] [G loss: 0.726694]
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5417 [D loss: 0.686429, acc.: 56.45%] [G loss: 0.719567]
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5418 [D loss: 0.678056, acc.: 55.86%] [G loss: 0.725144]
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5419 [D loss: 0.682255, acc.: 57.23%] [G loss: 0.717579]
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5420 [D loss: 0.690252, acc.: 54.10%] [G loss: 0.712611]
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5421 [D loss: 0.688752, acc.: 54.69%] [G loss: 0.720400]
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5422 [D loss: 0.679764, acc.: 58.59%] [G loss: 0.723211]
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5423 [D loss: 0.681230, acc.: 57.03%] [G loss: 0.712589]
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5424 [D loss: 0.678904, acc.: 58.59%] [G loss: 0.719063]
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5425 [D loss: 0.686070, acc.: 52.93%] [G loss: 0.717806]
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5426 [D loss: 0.686941, acc.: 53.52%] [G loss: 0.720778]
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5427 [D loss: 0.689643, acc.: 53.12%] [G loss: 0.724393]
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5428 [D loss: 0.679734, acc.: 58.01%] [G loss: 0.724286]
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5429 [D loss: 0.685245, acc.: 54.30%] [G loss: 0.732756]
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5430 [D loss: 0.678725, acc.: 57.03%] [G loss: 0.725614]
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5431 [D loss: 0.680878, acc.: 55.86%] [G loss: 0.723600]
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5432 [D loss: 0.694426, acc.: 51.56%] [G loss: 0.709497]
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5433 [D loss: 0.697439, acc.: 50.59%] [G loss: 0.718902]
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5434 [D loss: 0.683741, acc.: 56.64%] [G loss: 0.717300]
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5435 [D loss: 0.685726, acc.: 52.54%] [G loss: 0.724588]
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5436 [D loss: 0.680340, acc.: 59.38%] [G loss: 0.725086]
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5437 [D loss: 0.683872, acc.: 53.32%] [G loss: 0.716215]
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5438 [D loss: 0.679713, acc.: 59.57%] [G loss: 0.720559]
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5439 [D loss: 0.678396, acc.: 57.23%] [G loss: 0.717089]
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5440 [D loss: 0.687033, acc.: 55.08%] [G loss: 0.717861]
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5441 [D loss: 0.686877, acc.: 52.73%] [G loss: 0.717650]
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5442 [D loss: 0.685084, acc.: 52.54%] [G loss: 0.728155]
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5443 [D loss: 0.685273, acc.: 58.01%] [G loss: 0.729696]
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5444 [D loss: 0.685912, acc.: 57.23%] [G loss: 0.729788]
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5445 [D loss: 0.679725, acc.: 58.01%] [G loss: 0.726122]
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5446 [D loss: 0.686473, acc.: 54.88%] [G loss: 0.713210]
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5447 [D loss: 0.688723, acc.: 55.86%] [G loss: 0.719754]
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5448 [D loss: 0.688054, acc.: 56.84%] [G loss: 0.718358]
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5449 [D loss: 0.683715, acc.: 57.03%] [G loss: 0.716837]
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5450 [D loss: 0.687544, acc.: 54.88%] [G loss: 0.724014]
1/1 [==============================] - 0s 18ms/step
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5451 [D loss: 0.679741, acc.: 58.40%] [G loss: 0.739058]
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5452 [D loss: 0.682450, acc.: 56.84%] [G loss: 0.738141]
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5453 [D loss: 0.683508, acc.: 58.40%] [G loss: 0.742784]
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5454 [D loss: 0.678745, acc.: 58.20%] [G loss: 0.727635]
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5455 [D loss: 0.680448, acc.: 58.98%] [G loss: 0.712671]
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5456 [D loss: 0.693288, acc.: 52.34%] [G loss: 0.705973]
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5457 [D loss: 0.688298, acc.: 51.17%] [G loss: 0.715626]
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5458 [D loss: 0.690240, acc.: 52.34%] [G loss: 0.725082]
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5459 [D loss: 0.679198, acc.: 56.64%] [G loss: 0.731751]
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5460 [D loss: 0.680394, acc.: 58.40%] [G loss: 0.735331]
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5461 [D loss: 0.683912, acc.: 56.64%] [G loss: 0.721840]
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5462 [D loss: 0.687072, acc.: 53.52%] [G loss: 0.727692]
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5463 [D loss: 0.682535, acc.: 57.42%] [G loss: 0.723339]
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5464 [D loss: 0.688768, acc.: 54.69%] [G loss: 0.717399]
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5465 [D loss: 0.686144, acc.: 55.27%] [G loss: 0.721026]
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5466 [D loss: 0.687393, acc.: 53.52%] [G loss: 0.724624]
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5467 [D loss: 0.682938, acc.: 56.25%] [G loss: 0.729290]
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5468 [D loss: 0.686667, acc.: 52.15%] [G loss: 0.734039]
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5469 [D loss: 0.689841, acc.: 53.32%] [G loss: 0.739820]
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5470 [D loss: 0.680872, acc.: 56.64%] [G loss: 0.726081]
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5471 [D loss: 0.690360, acc.: 51.76%] [G loss: 0.716732]
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5472 [D loss: 0.683564, acc.: 55.47%] [G loss: 0.723912]
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5473 [D loss: 0.686174, acc.: 55.47%] [G loss: 0.719244]
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5474 [D loss: 0.685350, acc.: 52.15%] [G loss: 0.730781]
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5475 [D loss: 0.682533, acc.: 57.42%] [G loss: 0.730025]
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5476 [D loss: 0.683238, acc.: 57.03%] [G loss: 0.730618]
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5477 [D loss: 0.679334, acc.: 58.20%] [G loss: 0.736204]
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5478 [D loss: 0.686526, acc.: 55.66%] [G loss: 0.735024]
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5479 [D loss: 0.683230, acc.: 56.25%] [G loss: 0.721588]
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5480 [D loss: 0.687455, acc.: 53.32%] [G loss: 0.726991]
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5481 [D loss: 0.688786, acc.: 53.91%] [G loss: 0.727597]
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5482 [D loss: 0.680543, acc.: 58.20%] [G loss: 0.723246]
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5483 [D loss: 0.684320, acc.: 55.27%] [G loss: 0.731104]
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5484 [D loss: 0.686771, acc.: 55.27%] [G loss: 0.724203]
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5485 [D loss: 0.683440, acc.: 55.86%] [G loss: 0.728037]
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5486 [D loss: 0.684677, acc.: 55.47%] [G loss: 0.730718]
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5487 [D loss: 0.684532, acc.: 55.27%] [G loss: 0.725298]
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5488 [D loss: 0.682348, acc.: 55.86%] [G loss: 0.722712]
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5489 [D loss: 0.683232, acc.: 55.47%] [G loss: 0.730944]
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5490 [D loss: 0.673541, acc.: 60.55%] [G loss: 0.711717]
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5491 [D loss: 0.672221, acc.: 61.52%] [G loss: 0.716851]
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5492 [D loss: 0.681709, acc.: 57.03%] [G loss: 0.720540]
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5493 [D loss: 0.688461, acc.: 50.78%] [G loss: 0.710755]
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5494 [D loss: 0.692572, acc.: 52.73%] [G loss: 0.713913]
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5495 [D loss: 0.695420, acc.: 51.95%] [G loss: 0.714815]
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5496 [D loss: 0.689810, acc.: 54.10%] [G loss: 0.720971]
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5497 [D loss: 0.682862, acc.: 57.62%] [G loss: 0.737628]
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5498 [D loss: 0.678856, acc.: 57.23%] [G loss: 0.752661]
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5499 [D loss: 0.679148, acc.: 59.38%] [G loss: 0.750905]
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5500 [D loss: 0.678985, acc.: 57.81%] [G loss: 0.742075]
1/1 [==============================] - 0s 18ms/step
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5501 [D loss: 0.684238, acc.: 54.69%] [G loss: 0.726173]
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5502 [D loss: 0.679630, acc.: 57.03%] [G loss: 0.738044]
8/8 [==============================] - 0s 4ms/step
5503 [D loss: 0.680355, acc.: 58.20%] [G loss: 0.712586]
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5504 [D loss: 0.684548, acc.: 53.91%] [G loss: 0.724288]
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5505 [D loss: 0.688665, acc.: 54.30%] [G loss: 0.719190]
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5506 [D loss: 0.682431, acc.: 56.25%] [G loss: 0.734655]
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5507 [D loss: 0.676353, acc.: 58.59%] [G loss: 0.724157]
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5508 [D loss: 0.673674, acc.: 61.72%] [G loss: 0.716312]
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5509 [D loss: 0.680012, acc.: 58.20%] [G loss: 0.719684]
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5510 [D loss: 0.682888, acc.: 59.18%] [G loss: 0.734247]
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5511 [D loss: 0.682058, acc.: 56.45%] [G loss: 0.730639]
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5512 [D loss: 0.683995, acc.: 55.27%] [G loss: 0.730076]
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5513 [D loss: 0.685246, acc.: 58.59%] [G loss: 0.742392]
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5514 [D loss: 0.680921, acc.: 58.40%] [G loss: 0.726556]
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5515 [D loss: 0.682044, acc.: 58.59%] [G loss: 0.729584]
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5516 [D loss: 0.683865, acc.: 56.25%] [G loss: 0.723212]
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5517 [D loss: 0.684020, acc.: 56.25%] [G loss: 0.723882]
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5518 [D loss: 0.677090, acc.: 59.96%] [G loss: 0.730654]
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5519 [D loss: 0.684324, acc.: 55.86%] [G loss: 0.729201]
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5520 [D loss: 0.678915, acc.: 58.98%] [G loss: 0.721633]
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5521 [D loss: 0.681147, acc.: 57.23%] [G loss: 0.725422]
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5522 [D loss: 0.684124, acc.: 50.98%] [G loss: 0.728203]
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5523 [D loss: 0.689326, acc.: 51.95%] [G loss: 0.723820]
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5524 [D loss: 0.686526, acc.: 55.47%] [G loss: 0.728803]
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5525 [D loss: 0.689111, acc.: 54.69%] [G loss: 0.719208]
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5526 [D loss: 0.686361, acc.: 55.27%] [G loss: 0.732640]
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5527 [D loss: 0.678594, acc.: 57.62%] [G loss: 0.737853]
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5528 [D loss: 0.677550, acc.: 60.55%] [G loss: 0.741115]
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5529 [D loss: 0.673326, acc.: 61.33%] [G loss: 0.729218]
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5530 [D loss: 0.685350, acc.: 57.03%] [G loss: 0.732061]
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5531 [D loss: 0.682577, acc.: 58.40%] [G loss: 0.721571]
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5532 [D loss: 0.685264, acc.: 55.08%] [G loss: 0.725498]
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5533 [D loss: 0.686578, acc.: 53.12%] [G loss: 0.722518]
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5534 [D loss: 0.680065, acc.: 55.86%] [G loss: 0.734371]
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5535 [D loss: 0.687645, acc.: 52.15%] [G loss: 0.722379]
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5536 [D loss: 0.684697, acc.: 54.88%] [G loss: 0.723634]
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5537 [D loss: 0.686414, acc.: 56.45%] [G loss: 0.724345]
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5538 [D loss: 0.679128, acc.: 58.20%] [G loss: 0.723874]
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5539 [D loss: 0.689358, acc.: 51.37%] [G loss: 0.718149]
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5540 [D loss: 0.683829, acc.: 55.08%] [G loss: 0.710388]
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5541 [D loss: 0.678374, acc.: 58.20%] [G loss: 0.729653]
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5542 [D loss: 0.681216, acc.: 58.40%] [G loss: 0.725620]
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5543 [D loss: 0.683973, acc.: 57.23%] [G loss: 0.724105]
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5544 [D loss: 0.688592, acc.: 51.95%] [G loss: 0.725103]
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5545 [D loss: 0.688563, acc.: 52.34%] [G loss: 0.722375]
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5546 [D loss: 0.692539, acc.: 49.22%] [G loss: 0.721248]
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5547 [D loss: 0.687909, acc.: 55.86%] [G loss: 0.717675]
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5548 [D loss: 0.681589, acc.: 52.93%] [G loss: 0.728260]
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5549 [D loss: 0.685745, acc.: 54.69%] [G loss: 0.728000]
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5550 [D loss: 0.680227, acc.: 57.03%] [G loss: 0.721988]
1/1 [==============================] - 0s 18ms/step
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5551 [D loss: 0.679774, acc.: 57.62%] [G loss: 0.713077]
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5552 [D loss: 0.688464, acc.: 53.71%] [G loss: 0.714181]
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5553 [D loss: 0.685913, acc.: 55.27%] [G loss: 0.716825]
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5554 [D loss: 0.691863, acc.: 48.05%] [G loss: 0.723884]
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5555 [D loss: 0.689518, acc.: 54.88%] [G loss: 0.725970]
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5556 [D loss: 0.687805, acc.: 53.52%] [G loss: 0.737198]
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5557 [D loss: 0.681125, acc.: 58.20%] [G loss: 0.739954]
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5558 [D loss: 0.679457, acc.: 58.20%] [G loss: 0.741774]
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5559 [D loss: 0.685897, acc.: 54.88%] [G loss: 0.723388]
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5560 [D loss: 0.685938, acc.: 54.30%] [G loss: 0.722984]
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5561 [D loss: 0.681301, acc.: 57.42%] [G loss: 0.719646]
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5562 [D loss: 0.673834, acc.: 59.57%] [G loss: 0.732463]
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5563 [D loss: 0.681708, acc.: 55.27%] [G loss: 0.725662]
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5564 [D loss: 0.685686, acc.: 56.45%] [G loss: 0.721952]
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5565 [D loss: 0.676645, acc.: 59.18%] [G loss: 0.723633]
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5566 [D loss: 0.681726, acc.: 56.25%] [G loss: 0.724598]
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5567 [D loss: 0.685300, acc.: 56.64%] [G loss: 0.712935]
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5568 [D loss: 0.683709, acc.: 54.69%] [G loss: 0.720281]
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5569 [D loss: 0.688397, acc.: 52.73%] [G loss: 0.725938]
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5570 [D loss: 0.689890, acc.: 54.88%] [G loss: 0.728285]
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5571 [D loss: 0.686751, acc.: 56.05%] [G loss: 0.734047]
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5572 [D loss: 0.682876, acc.: 57.03%] [G loss: 0.728553]
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5573 [D loss: 0.685459, acc.: 54.69%] [G loss: 0.727962]
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5574 [D loss: 0.680551, acc.: 58.59%] [G loss: 0.726284]
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5575 [D loss: 0.683371, acc.: 57.03%] [G loss: 0.729120]
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5576 [D loss: 0.685270, acc.: 53.71%] [G loss: 0.725201]
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5577 [D loss: 0.687198, acc.: 53.91%] [G loss: 0.730459]
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5578 [D loss: 0.679050, acc.: 57.81%] [G loss: 0.730754]
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5579 [D loss: 0.682284, acc.: 55.47%] [G loss: 0.719632]
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5580 [D loss: 0.677474, acc.: 56.84%] [G loss: 0.725585]
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5581 [D loss: 0.676342, acc.: 59.38%] [G loss: 0.734413]
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5582 [D loss: 0.681710, acc.: 55.27%] [G loss: 0.726915]
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5583 [D loss: 0.688678, acc.: 54.69%] [G loss: 0.721532]
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5584 [D loss: 0.685571, acc.: 52.54%] [G loss: 0.723768]
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5585 [D loss: 0.690075, acc.: 52.15%] [G loss: 0.728151]
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5586 [D loss: 0.687894, acc.: 56.25%] [G loss: 0.731244]
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5587 [D loss: 0.678559, acc.: 57.81%] [G loss: 0.736731]
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5588 [D loss: 0.680606, acc.: 58.98%] [G loss: 0.737734]
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5589 [D loss: 0.682529, acc.: 53.91%] [G loss: 0.743855]
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5590 [D loss: 0.691265, acc.: 51.17%] [G loss: 0.723048]
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5591 [D loss: 0.687743, acc.: 56.05%] [G loss: 0.717944]
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5592 [D loss: 0.691045, acc.: 54.30%] [G loss: 0.735695]
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5593 [D loss: 0.679084, acc.: 59.57%] [G loss: 0.724479]
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5594 [D loss: 0.682792, acc.: 57.42%] [G loss: 0.717565]
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5595 [D loss: 0.684316, acc.: 55.66%] [G loss: 0.727514]
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5596 [D loss: 0.677904, acc.: 56.84%] [G loss: 0.732911]
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5597 [D loss: 0.679708, acc.: 57.03%] [G loss: 0.736768]
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5598 [D loss: 0.684330, acc.: 55.66%] [G loss: 0.726369]
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5599 [D loss: 0.689812, acc.: 51.95%] [G loss: 0.730462]
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5600 [D loss: 0.687270, acc.: 56.05%] [G loss: 0.730573]
1/1 [==============================] - 0s 19ms/step
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5601 [D loss: 0.680276, acc.: 58.79%] [G loss: 0.726250]
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5602 [D loss: 0.683407, acc.: 55.08%] [G loss: 0.729405]
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5603 [D loss: 0.673866, acc.: 61.52%] [G loss: 0.733399]
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5604 [D loss: 0.681339, acc.: 56.05%] [G loss: 0.724780]
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5605 [D loss: 0.678738, acc.: 57.42%] [G loss: 0.722547]
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5606 [D loss: 0.688724, acc.: 54.69%] [G loss: 0.722864]
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5607 [D loss: 0.683829, acc.: 56.45%] [G loss: 0.723186]
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5608 [D loss: 0.685243, acc.: 53.91%] [G loss: 0.721383]
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5609 [D loss: 0.683315, acc.: 54.88%] [G loss: 0.716525]
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5610 [D loss: 0.685296, acc.: 58.79%] [G loss: 0.725158]
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5611 [D loss: 0.674812, acc.: 57.42%] [G loss: 0.721017]
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5612 [D loss: 0.682831, acc.: 56.25%] [G loss: 0.720539]
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5613 [D loss: 0.687246, acc.: 52.73%] [G loss: 0.721721]
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5614 [D loss: 0.679072, acc.: 58.79%] [G loss: 0.726976]
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5615 [D loss: 0.685252, acc.: 52.54%] [G loss: 0.723205]
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5616 [D loss: 0.690612, acc.: 52.34%] [G loss: 0.732550]
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5617 [D loss: 0.675100, acc.: 59.77%] [G loss: 0.745249]
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5618 [D loss: 0.674885, acc.: 60.16%] [G loss: 0.743502]
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5619 [D loss: 0.689640, acc.: 50.98%] [G loss: 0.724644]
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5620 [D loss: 0.680639, acc.: 56.05%] [G loss: 0.724268]
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5621 [D loss: 0.695433, acc.: 53.52%] [G loss: 0.709048]
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5622 [D loss: 0.686837, acc.: 55.27%] [G loss: 0.716624]
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5623 [D loss: 0.685772, acc.: 54.49%] [G loss: 0.725841]
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5624 [D loss: 0.675180, acc.: 59.96%] [G loss: 0.737924]
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5625 [D loss: 0.678738, acc.: 59.18%] [G loss: 0.745591]
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5626 [D loss: 0.669363, acc.: 60.74%] [G loss: 0.730287]
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5627 [D loss: 0.673171, acc.: 61.33%] [G loss: 0.728635]
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5628 [D loss: 0.691452, acc.: 51.76%] [G loss: 0.720842]
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5629 [D loss: 0.683123, acc.: 54.30%] [G loss: 0.721619]
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5630 [D loss: 0.696210, acc.: 50.98%] [G loss: 0.732962]
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5631 [D loss: 0.691671, acc.: 52.34%] [G loss: 0.740061]
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5632 [D loss: 0.678880, acc.: 59.38%] [G loss: 0.734450]
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5633 [D loss: 0.678757, acc.: 57.81%] [G loss: 0.753191]
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5634 [D loss: 0.676939, acc.: 60.55%] [G loss: 0.731330]
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5635 [D loss: 0.679972, acc.: 58.40%] [G loss: 0.729944]
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5636 [D loss: 0.694412, acc.: 53.91%] [G loss: 0.720575]
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5637 [D loss: 0.687368, acc.: 52.34%] [G loss: 0.719392]
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5638 [D loss: 0.684009, acc.: 53.12%] [G loss: 0.726278]
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5639 [D loss: 0.681335, acc.: 60.55%] [G loss: 0.737366]
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5640 [D loss: 0.680600, acc.: 57.23%] [G loss: 0.726754]
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5641 [D loss: 0.673173, acc.: 58.01%] [G loss: 0.731144]
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5642 [D loss: 0.678532, acc.: 58.40%] [G loss: 0.734802]
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5643 [D loss: 0.670615, acc.: 60.55%] [G loss: 0.725479]
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5644 [D loss: 0.678978, acc.: 54.88%] [G loss: 0.713932]
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5645 [D loss: 0.682951, acc.: 54.49%] [G loss: 0.708183]
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5646 [D loss: 0.692911, acc.: 50.78%] [G loss: 0.723583]
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5647 [D loss: 0.691050, acc.: 54.10%] [G loss: 0.716576]
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5648 [D loss: 0.692406, acc.: 50.59%] [G loss: 0.726912]
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5649 [D loss: 0.680517, acc.: 55.66%] [G loss: 0.753759]
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5650 [D loss: 0.671801, acc.: 62.50%] [G loss: 0.746304]
1/1 [==============================] - 0s 18ms/step
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5651 [D loss: 0.668148, acc.: 62.30%] [G loss: 0.740834]
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5652 [D loss: 0.674843, acc.: 59.38%] [G loss: 0.730585]
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5653 [D loss: 0.693709, acc.: 51.37%] [G loss: 0.720857]
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5654 [D loss: 0.686564, acc.: 57.62%] [G loss: 0.708938]
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5655 [D loss: 0.681061, acc.: 55.27%] [G loss: 0.710086]
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5656 [D loss: 0.682933, acc.: 56.84%] [G loss: 0.711625]
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5657 [D loss: 0.693248, acc.: 52.15%] [G loss: 0.731047]
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5658 [D loss: 0.676692, acc.: 57.81%] [G loss: 0.740920]
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5659 [D loss: 0.676249, acc.: 58.40%] [G loss: 0.746725]
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5660 [D loss: 0.675006, acc.: 58.01%] [G loss: 0.741558]
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5661 [D loss: 0.675952, acc.: 57.81%] [G loss: 0.733873]
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5662 [D loss: 0.678829, acc.: 57.23%] [G loss: 0.751075]
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5663 [D loss: 0.692823, acc.: 53.52%] [G loss: 0.724521]
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5664 [D loss: 0.688206, acc.: 54.10%] [G loss: 0.712689]
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5665 [D loss: 0.695351, acc.: 50.20%] [G loss: 0.733588]
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5666 [D loss: 0.688667, acc.: 55.08%] [G loss: 0.730348]
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5667 [D loss: 0.687681, acc.: 57.81%] [G loss: 0.735533]
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5668 [D loss: 0.685363, acc.: 56.05%] [G loss: 0.726967]
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5669 [D loss: 0.678106, acc.: 58.01%] [G loss: 0.728616]
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5670 [D loss: 0.688567, acc.: 57.42%] [G loss: 0.729082]
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5671 [D loss: 0.692060, acc.: 53.52%] [G loss: 0.721628]
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5672 [D loss: 0.690374, acc.: 52.73%] [G loss: 0.730206]
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5673 [D loss: 0.691163, acc.: 55.08%] [G loss: 0.723818]
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5674 [D loss: 0.675638, acc.: 59.57%] [G loss: 0.737803]
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5675 [D loss: 0.680127, acc.: 58.59%] [G loss: 0.732326]
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5676 [D loss: 0.683719, acc.: 56.25%] [G loss: 0.739574]
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5677 [D loss: 0.685095, acc.: 54.30%] [G loss: 0.742912]
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5678 [D loss: 0.683477, acc.: 55.08%] [G loss: 0.738535]
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5679 [D loss: 0.680156, acc.: 57.23%] [G loss: 0.747725]
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5680 [D loss: 0.685112, acc.: 54.49%] [G loss: 0.758663]
8/8 [==============================] - 0s 4ms/step
5681 [D loss: 0.677589, acc.: 60.16%] [G loss: 0.744412]
8/8 [==============================] - 0s 4ms/step
5682 [D loss: 0.677390, acc.: 56.84%] [G loss: 0.754814]
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5683 [D loss: 0.668441, acc.: 63.67%] [G loss: 0.752571]
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5684 [D loss: 0.675547, acc.: 56.64%] [G loss: 0.725384]
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5685 [D loss: 0.685623, acc.: 56.84%] [G loss: 0.717911]
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5686 [D loss: 0.691613, acc.: 53.12%] [G loss: 0.688403]
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5687 [D loss: 0.702780, acc.: 50.39%] [G loss: 0.714104]
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5688 [D loss: 0.687333, acc.: 53.91%] [G loss: 0.726772]
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5689 [D loss: 0.678036, acc.: 60.94%] [G loss: 0.745120]
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5690 [D loss: 0.682518, acc.: 55.47%] [G loss: 0.745549]
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5691 [D loss: 0.680556, acc.: 55.86%] [G loss: 0.729368]
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5692 [D loss: 0.670489, acc.: 59.77%] [G loss: 0.728956]
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5693 [D loss: 0.683376, acc.: 55.47%] [G loss: 0.723976]
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5694 [D loss: 0.683923, acc.: 57.42%] [G loss: 0.728850]
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5695 [D loss: 0.686863, acc.: 53.12%] [G loss: 0.729927]
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5696 [D loss: 0.687829, acc.: 53.32%] [G loss: 0.734916]
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5697 [D loss: 0.679964, acc.: 56.25%] [G loss: 0.743163]
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5698 [D loss: 0.677009, acc.: 60.35%] [G loss: 0.743857]
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5699 [D loss: 0.681109, acc.: 54.69%] [G loss: 0.738008]
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5700 [D loss: 0.683701, acc.: 56.45%] [G loss: 0.727109]
1/1 [==============================] - 0s 19ms/step
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5701 [D loss: 0.679567, acc.: 56.25%] [G loss: 0.730912]
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5702 [D loss: 0.689885, acc.: 55.27%] [G loss: 0.719744]
8/8 [==============================] - 0s 4ms/step
5703 [D loss: 0.690312, acc.: 51.95%] [G loss: 0.717148]
8/8 [==============================] - 0s 4ms/step
5704 [D loss: 0.688970, acc.: 55.08%] [G loss: 0.710702]
8/8 [==============================] - 0s 4ms/step
5705 [D loss: 0.675498, acc.: 57.42%] [G loss: 0.723003]
8/8 [==============================] - 0s 4ms/step
5706 [D loss: 0.679958, acc.: 56.05%] [G loss: 0.738202]
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5707 [D loss: 0.677041, acc.: 60.94%] [G loss: 0.717183]
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5708 [D loss: 0.673580, acc.: 61.72%] [G loss: 0.728796]
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5709 [D loss: 0.677030, acc.: 56.84%] [G loss: 0.707395]
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5710 [D loss: 0.676820, acc.: 58.98%] [G loss: 0.720267]
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5711 [D loss: 0.688617, acc.: 53.91%] [G loss: 0.720934]
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5712 [D loss: 0.687504, acc.: 53.32%] [G loss: 0.723982]
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5713 [D loss: 0.680864, acc.: 56.45%] [G loss: 0.720014]
8/8 [==============================] - 0s 4ms/step
5714 [D loss: 0.685873, acc.: 53.91%] [G loss: 0.729370]
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5715 [D loss: 0.690452, acc.: 52.15%] [G loss: 0.734081]
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5716 [D loss: 0.672844, acc.: 60.94%] [G loss: 0.735145]
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5717 [D loss: 0.679451, acc.: 56.05%] [G loss: 0.732087]
8/8 [==============================] - 0s 4ms/step
5718 [D loss: 0.681026, acc.: 58.59%] [G loss: 0.736284]
8/8 [==============================] - 0s 4ms/step
5719 [D loss: 0.670898, acc.: 61.52%] [G loss: 0.736695]
8/8 [==============================] - 0s 4ms/step
5720 [D loss: 0.675530, acc.: 59.77%] [G loss: 0.728511]
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5721 [D loss: 0.690370, acc.: 54.10%] [G loss: 0.708674]
8/8 [==============================] - 0s 4ms/step
5722 [D loss: 0.678347, acc.: 57.62%] [G loss: 0.710948]
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5723 [D loss: 0.681735, acc.: 58.79%] [G loss: 0.710214]
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5724 [D loss: 0.679633, acc.: 58.01%] [G loss: 0.721304]
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5725 [D loss: 0.674262, acc.: 60.55%] [G loss: 0.720354]
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5726 [D loss: 0.682569, acc.: 57.42%] [G loss: 0.731916]
8/8 [==============================] - 0s 4ms/step
5727 [D loss: 0.679596, acc.: 55.27%] [G loss: 0.726243]
8/8 [==============================] - 0s 4ms/step
5728 [D loss: 0.688091, acc.: 54.10%] [G loss: 0.727702]
8/8 [==============================] - 0s 4ms/step
5729 [D loss: 0.683365, acc.: 55.86%] [G loss: 0.715155]
8/8 [==============================] - 0s 4ms/step
5730 [D loss: 0.691971, acc.: 54.10%] [G loss: 0.716318]
8/8 [==============================] - 0s 4ms/step
5731 [D loss: 0.675759, acc.: 58.01%] [G loss: 0.733612]
8/8 [==============================] - 0s 4ms/step
5732 [D loss: 0.684647, acc.: 55.86%] [G loss: 0.729709]
8/8 [==============================] - 0s 4ms/step
5733 [D loss: 0.692391, acc.: 49.80%] [G loss: 0.720989]
8/8 [==============================] - 0s 4ms/step
5734 [D loss: 0.678500, acc.: 59.57%] [G loss: 0.729834]
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5735 [D loss: 0.688672, acc.: 54.10%] [G loss: 0.731013]
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5736 [D loss: 0.676964, acc.: 59.57%] [G loss: 0.711251]
8/8 [==============================] - 0s 4ms/step
5737 [D loss: 0.688986, acc.: 52.93%] [G loss: 0.723510]
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5738 [D loss: 0.673951, acc.: 62.30%] [G loss: 0.712318]
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5739 [D loss: 0.691777, acc.: 51.56%] [G loss: 0.721569]
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5740 [D loss: 0.693937, acc.: 52.34%] [G loss: 0.727073]
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5741 [D loss: 0.678416, acc.: 57.03%] [G loss: 0.720280]
8/8 [==============================] - 0s 4ms/step
5742 [D loss: 0.685674, acc.: 56.84%] [G loss: 0.733927]
8/8 [==============================] - 0s 4ms/step
5743 [D loss: 0.691795, acc.: 52.73%] [G loss: 0.720067]
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5744 [D loss: 0.685390, acc.: 54.88%] [G loss: 0.717457]
8/8 [==============================] - 0s 4ms/step
5745 [D loss: 0.682007, acc.: 55.08%] [G loss: 0.728647]
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5746 [D loss: 0.685943, acc.: 55.08%] [G loss: 0.732720]
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5747 [D loss: 0.675058, acc.: 59.18%] [G loss: 0.725142]
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5748 [D loss: 0.691398, acc.: 52.93%] [G loss: 0.726650]
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5749 [D loss: 0.685188, acc.: 54.88%] [G loss: 0.720806]
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5750 [D loss: 0.685336, acc.: 55.66%] [G loss: 0.719346]
1/1 [==============================] - 0s 17ms/step
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5751 [D loss: 0.688205, acc.: 52.15%] [G loss: 0.719996]
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5752 [D loss: 0.689732, acc.: 53.12%] [G loss: 0.724549]
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5753 [D loss: 0.681429, acc.: 56.45%] [G loss: 0.718363]
8/8 [==============================] - 0s 4ms/step
5754 [D loss: 0.687806, acc.: 52.34%] [G loss: 0.718949]
8/8 [==============================] - 0s 4ms/step
5755 [D loss: 0.680551, acc.: 57.03%] [G loss: 0.707698]
8/8 [==============================] - 0s 4ms/step
5756 [D loss: 0.688258, acc.: 51.95%] [G loss: 0.727314]
8/8 [==============================] - 0s 4ms/step
5757 [D loss: 0.685351, acc.: 54.88%] [G loss: 0.724567]
8/8 [==============================] - 0s 4ms/step
5758 [D loss: 0.685467, acc.: 55.47%] [G loss: 0.730554]
8/8 [==============================] - 0s 4ms/step
5759 [D loss: 0.681108, acc.: 58.40%] [G loss: 0.723540]
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5760 [D loss: 0.679786, acc.: 58.01%] [G loss: 0.737824]
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5761 [D loss: 0.678010, acc.: 56.64%] [G loss: 0.733923]
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5762 [D loss: 0.682430, acc.: 57.03%] [G loss: 0.736199]
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5763 [D loss: 0.678634, acc.: 58.79%] [G loss: 0.748664]
8/8 [==============================] - 0s 4ms/step
5764 [D loss: 0.678886, acc.: 59.57%] [G loss: 0.726714]
8/8 [==============================] - 0s 4ms/step
5765 [D loss: 0.676473, acc.: 56.84%] [G loss: 0.732466]
8/8 [==============================] - 0s 4ms/step
5766 [D loss: 0.689311, acc.: 52.34%] [G loss: 0.741511]
8/8 [==============================] - 0s 4ms/step
5767 [D loss: 0.683447, acc.: 54.49%] [G loss: 0.736569]
8/8 [==============================] - 0s 4ms/step
5768 [D loss: 0.678086, acc.: 58.59%] [G loss: 0.726495]
8/8 [==============================] - 0s 4ms/step
5769 [D loss: 0.684733, acc.: 54.88%] [G loss: 0.729337]
8/8 [==============================] - 0s 4ms/step
5770 [D loss: 0.686239, acc.: 55.27%] [G loss: 0.725775]
8/8 [==============================] - 0s 4ms/step
5771 [D loss: 0.693155, acc.: 52.93%] [G loss: 0.720619]
8/8 [==============================] - 0s 4ms/step
5772 [D loss: 0.700869, acc.: 50.39%] [G loss: 0.712437]
8/8 [==============================] - 0s 4ms/step
5773 [D loss: 0.682541, acc.: 55.66%] [G loss: 0.734020]
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5774 [D loss: 0.684525, acc.: 56.84%] [G loss: 0.721971]
8/8 [==============================] - 0s 4ms/step
5775 [D loss: 0.684687, acc.: 53.71%] [G loss: 0.716735]
8/8 [==============================] - 0s 4ms/step
5776 [D loss: 0.692148, acc.: 52.73%] [G loss: 0.723858]
8/8 [==============================] - 0s 4ms/step
5777 [D loss: 0.687832, acc.: 54.49%] [G loss: 0.716333]
8/8 [==============================] - 0s 4ms/step
5778 [D loss: 0.688489, acc.: 53.52%] [G loss: 0.731063]
8/8 [==============================] - 0s 4ms/step
5779 [D loss: 0.684455, acc.: 55.08%] [G loss: 0.720654]
8/8 [==============================] - 0s 4ms/step
5780 [D loss: 0.687765, acc.: 52.93%] [G loss: 0.722367]
8/8 [==============================] - 0s 4ms/step
5781 [D loss: 0.677256, acc.: 60.74%] [G loss: 0.735152]
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5782 [D loss: 0.679438, acc.: 60.94%] [G loss: 0.735705]
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5783 [D loss: 0.684146, acc.: 57.81%] [G loss: 0.730344]
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5784 [D loss: 0.685207, acc.: 57.03%] [G loss: 0.717775]
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5785 [D loss: 0.682475, acc.: 57.62%] [G loss: 0.722875]
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5786 [D loss: 0.676690, acc.: 61.13%] [G loss: 0.734997]
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5787 [D loss: 0.681306, acc.: 53.71%] [G loss: 0.729873]
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5788 [D loss: 0.679859, acc.: 59.38%] [G loss: 0.714447]
8/8 [==============================] - 0s 4ms/step
5789 [D loss: 0.678268, acc.: 59.38%] [G loss: 0.728758]
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5790 [D loss: 0.681021, acc.: 56.05%] [G loss: 0.723120]
8/8 [==============================] - 0s 4ms/step
5791 [D loss: 0.686607, acc.: 59.77%] [G loss: 0.731344]
8/8 [==============================] - 0s 4ms/step
5792 [D loss: 0.685839, acc.: 54.30%] [G loss: 0.722894]
8/8 [==============================] - 0s 4ms/step
5793 [D loss: 0.678050, acc.: 59.57%] [G loss: 0.728953]
8/8 [==============================] - 0s 4ms/step
5794 [D loss: 0.693103, acc.: 53.32%] [G loss: 0.726502]
8/8 [==============================] - 0s 4ms/step
5795 [D loss: 0.683432, acc.: 58.79%] [G loss: 0.723980]
8/8 [==============================] - 0s 4ms/step
5796 [D loss: 0.686320, acc.: 54.49%] [G loss: 0.727627]
8/8 [==============================] - 0s 4ms/step
5797 [D loss: 0.682108, acc.: 58.20%] [G loss: 0.708875]
8/8 [==============================] - 0s 4ms/step
5798 [D loss: 0.686791, acc.: 56.45%] [G loss: 0.729947]
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5799 [D loss: 0.684770, acc.: 57.42%] [G loss: 0.726899]
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5800 [D loss: 0.680371, acc.: 56.05%] [G loss: 0.712416]
1/1 [==============================] - 0s 18ms/step
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5801 [D loss: 0.681846, acc.: 57.23%] [G loss: 0.723038]
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5802 [D loss: 0.681598, acc.: 56.45%] [G loss: 0.715862]
8/8 [==============================] - 0s 4ms/step
5803 [D loss: 0.680790, acc.: 57.23%] [G loss: 0.717832]
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5804 [D loss: 0.680566, acc.: 55.66%] [G loss: 0.722395]
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5805 [D loss: 0.680224, acc.: 57.62%] [G loss: 0.729394]
8/8 [==============================] - 0s 4ms/step
5806 [D loss: 0.676455, acc.: 58.59%] [G loss: 0.730951]
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5807 [D loss: 0.684026, acc.: 58.01%] [G loss: 0.725789]
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5808 [D loss: 0.683327, acc.: 56.64%] [G loss: 0.735293]
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5809 [D loss: 0.675412, acc.: 57.23%] [G loss: 0.739986]
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5810 [D loss: 0.679669, acc.: 59.77%] [G loss: 0.736298]
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5811 [D loss: 0.680373, acc.: 55.66%] [G loss: 0.721921]
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5812 [D loss: 0.679111, acc.: 58.59%] [G loss: 0.740529]
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5813 [D loss: 0.680255, acc.: 58.20%] [G loss: 0.731401]
8/8 [==============================] - 0s 4ms/step
5814 [D loss: 0.686072, acc.: 54.10%] [G loss: 0.732428]
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5815 [D loss: 0.678594, acc.: 58.40%] [G loss: 0.728819]
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5816 [D loss: 0.690772, acc.: 52.93%] [G loss: 0.710267]
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5817 [D loss: 0.688913, acc.: 55.47%] [G loss: 0.716501]
8/8 [==============================] - 0s 4ms/step
5818 [D loss: 0.675573, acc.: 57.62%] [G loss: 0.721427]
8/8 [==============================] - 0s 4ms/step
5819 [D loss: 0.676705, acc.: 59.96%] [G loss: 0.727991]
8/8 [==============================] - 0s 4ms/step
5820 [D loss: 0.688697, acc.: 53.71%] [G loss: 0.717648]
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5821 [D loss: 0.676340, acc.: 57.23%] [G loss: 0.719838]
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5822 [D loss: 0.683233, acc.: 55.47%] [G loss: 0.722942]
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5823 [D loss: 0.682177, acc.: 54.30%] [G loss: 0.720694]
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5824 [D loss: 0.691683, acc.: 51.76%] [G loss: 0.727810]
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5825 [D loss: 0.682626, acc.: 54.69%] [G loss: 0.726987]
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5826 [D loss: 0.682755, acc.: 56.25%] [G loss: 0.737079]
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5827 [D loss: 0.686013, acc.: 53.91%] [G loss: 0.735004]
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5828 [D loss: 0.684298, acc.: 57.23%] [G loss: 0.732584]
8/8 [==============================] - 0s 4ms/step
5829 [D loss: 0.677082, acc.: 54.88%] [G loss: 0.727797]
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5830 [D loss: 0.683591, acc.: 56.64%] [G loss: 0.733371]
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5831 [D loss: 0.683088, acc.: 57.42%] [G loss: 0.734678]
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5832 [D loss: 0.686212, acc.: 55.27%] [G loss: 0.725649]
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5833 [D loss: 0.682993, acc.: 57.81%] [G loss: 0.728297]
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5834 [D loss: 0.684961, acc.: 57.62%] [G loss: 0.725793]
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5835 [D loss: 0.684032, acc.: 52.73%] [G loss: 0.724995]
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5836 [D loss: 0.682227, acc.: 55.47%] [G loss: 0.729439]
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5837 [D loss: 0.680626, acc.: 55.27%] [G loss: 0.737332]
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5838 [D loss: 0.687013, acc.: 53.12%] [G loss: 0.726969]
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5839 [D loss: 0.680902, acc.: 55.08%] [G loss: 0.725954]
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5840 [D loss: 0.684339, acc.: 55.86%] [G loss: 0.723942]
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5841 [D loss: 0.677653, acc.: 59.38%] [G loss: 0.738742]
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5842 [D loss: 0.670059, acc.: 59.57%] [G loss: 0.713680]
8/8 [==============================] - 0s 4ms/step
5843 [D loss: 0.680191, acc.: 58.20%] [G loss: 0.723939]
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5844 [D loss: 0.691414, acc.: 52.15%] [G loss: 0.717554]
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5845 [D loss: 0.683854, acc.: 57.23%] [G loss: 0.715380]
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5846 [D loss: 0.692679, acc.: 52.15%] [G loss: 0.718841]
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5847 [D loss: 0.684934, acc.: 57.03%] [G loss: 0.725122]
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5848 [D loss: 0.690069, acc.: 54.88%] [G loss: 0.722426]
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5849 [D loss: 0.688049, acc.: 54.88%] [G loss: 0.732181]
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5850 [D loss: 0.687606, acc.: 51.56%] [G loss: 0.727168]
1/1 [==============================] - 0s 17ms/step
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5851 [D loss: 0.679827, acc.: 58.98%] [G loss: 0.717395]
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5852 [D loss: 0.690172, acc.: 52.34%] [G loss: 0.717799]
8/8 [==============================] - 0s 4ms/step
5853 [D loss: 0.682160, acc.: 54.49%] [G loss: 0.717444]
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5854 [D loss: 0.680067, acc.: 57.42%] [G loss: 0.743371]
8/8 [==============================] - 0s 4ms/step
5855 [D loss: 0.683621, acc.: 54.88%] [G loss: 0.726943]
8/8 [==============================] - 0s 4ms/step
5856 [D loss: 0.681801, acc.: 55.66%] [G loss: 0.726925]
8/8 [==============================] - 0s 4ms/step
5857 [D loss: 0.680865, acc.: 56.45%] [G loss: 0.729959]
8/8 [==============================] - 0s 4ms/step
5858 [D loss: 0.686588, acc.: 54.88%] [G loss: 0.723730]
8/8 [==============================] - 0s 4ms/step
5859 [D loss: 0.686001, acc.: 56.45%] [G loss: 0.723214]
8/8 [==============================] - 0s 4ms/step
5860 [D loss: 0.688720, acc.: 50.78%] [G loss: 0.730761]
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5861 [D loss: 0.685510, acc.: 55.47%] [G loss: 0.735474]
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5862 [D loss: 0.689432, acc.: 53.12%] [G loss: 0.733958]
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5863 [D loss: 0.682700, acc.: 55.27%] [G loss: 0.727520]
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5864 [D loss: 0.684304, acc.: 56.25%] [G loss: 0.735812]
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5865 [D loss: 0.683749, acc.: 56.45%] [G loss: 0.728202]
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5866 [D loss: 0.670560, acc.: 58.20%] [G loss: 0.739290]
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5867 [D loss: 0.683809, acc.: 54.30%] [G loss: 0.726801]
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5868 [D loss: 0.685864, acc.: 52.93%] [G loss: 0.717751]
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5869 [D loss: 0.682415, acc.: 57.23%] [G loss: 0.732357]
8/8 [==============================] - 0s 4ms/step
5870 [D loss: 0.684671, acc.: 55.27%] [G loss: 0.728418]
8/8 [==============================] - 0s 4ms/step
5871 [D loss: 0.681475, acc.: 55.47%] [G loss: 0.734037]
8/8 [==============================] - 0s 4ms/step
5872 [D loss: 0.683791, acc.: 54.69%] [G loss: 0.727723]
8/8 [==============================] - 0s 4ms/step
5873 [D loss: 0.684831, acc.: 54.88%] [G loss: 0.731019]
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5874 [D loss: 0.686386, acc.: 54.49%] [G loss: 0.741350]
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5875 [D loss: 0.693726, acc.: 50.78%] [G loss: 0.718089]
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5876 [D loss: 0.680036, acc.: 53.91%] [G loss: 0.741768]
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5877 [D loss: 0.688466, acc.: 52.93%] [G loss: 0.727409]
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5878 [D loss: 0.684402, acc.: 55.08%] [G loss: 0.730121]
8/8 [==============================] - 0s 4ms/step
5879 [D loss: 0.682571, acc.: 55.66%] [G loss: 0.724049]
8/8 [==============================] - 0s 4ms/step
5880 [D loss: 0.681225, acc.: 58.01%] [G loss: 0.739284]
8/8 [==============================] - 0s 4ms/step
5881 [D loss: 0.677844, acc.: 58.20%] [G loss: 0.743780]
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5882 [D loss: 0.679810, acc.: 59.18%] [G loss: 0.733685]
8/8 [==============================] - 0s 4ms/step
5883 [D loss: 0.689405, acc.: 53.91%] [G loss: 0.738615]
8/8 [==============================] - 0s 4ms/step
5884 [D loss: 0.678525, acc.: 56.45%] [G loss: 0.736398]
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5885 [D loss: 0.684978, acc.: 55.27%] [G loss: 0.726440]
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5886 [D loss: 0.679949, acc.: 57.23%] [G loss: 0.733110]
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5887 [D loss: 0.686004, acc.: 55.27%] [G loss: 0.723347]
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5888 [D loss: 0.685092, acc.: 58.20%] [G loss: 0.713755]
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5889 [D loss: 0.671721, acc.: 60.35%] [G loss: 0.719447]
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5890 [D loss: 0.682757, acc.: 54.30%] [G loss: 0.722166]
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5891 [D loss: 0.682317, acc.: 55.66%] [G loss: 0.728803]
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5892 [D loss: 0.681358, acc.: 55.66%] [G loss: 0.727603]
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5893 [D loss: 0.682214, acc.: 55.47%] [G loss: 0.718982]
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5894 [D loss: 0.681614, acc.: 56.84%] [G loss: 0.730062]
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5895 [D loss: 0.683216, acc.: 56.84%] [G loss: 0.725475]
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5896 [D loss: 0.688357, acc.: 53.91%] [G loss: 0.730000]
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5897 [D loss: 0.681747, acc.: 57.23%] [G loss: 0.719913]
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5898 [D loss: 0.681493, acc.: 55.08%] [G loss: 0.723772]
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5899 [D loss: 0.682609, acc.: 58.79%] [G loss: 0.736500]
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5900 [D loss: 0.686434, acc.: 56.64%] [G loss: 0.724209]
1/1 [==============================] - 0s 16ms/step
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5901 [D loss: 0.677965, acc.: 56.25%] [G loss: 0.726366]
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5902 [D loss: 0.687511, acc.: 55.08%] [G loss: 0.721903]
8/8 [==============================] - 0s 4ms/step
5903 [D loss: 0.686957, acc.: 55.86%] [G loss: 0.716751]
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5904 [D loss: 0.686599, acc.: 53.71%] [G loss: 0.731009]
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5905 [D loss: 0.680583, acc.: 56.45%] [G loss: 0.725990]
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5906 [D loss: 0.686288, acc.: 54.30%] [G loss: 0.731772]
8/8 [==============================] - 0s 4ms/step
5907 [D loss: 0.683617, acc.: 53.32%] [G loss: 0.728234]
8/8 [==============================] - 0s 4ms/step
5908 [D loss: 0.685990, acc.: 55.86%] [G loss: 0.725592]
8/8 [==============================] - 0s 4ms/step
5909 [D loss: 0.677600, acc.: 57.03%] [G loss: 0.735194]
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5910 [D loss: 0.681503, acc.: 57.23%] [G loss: 0.733256]
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5911 [D loss: 0.687789, acc.: 52.54%] [G loss: 0.725788]
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5912 [D loss: 0.676307, acc.: 59.96%] [G loss: 0.729779]
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5913 [D loss: 0.683836, acc.: 55.47%] [G loss: 0.718639]
8/8 [==============================] - 0s 4ms/step
5914 [D loss: 0.690186, acc.: 51.76%] [G loss: 0.717615]
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5915 [D loss: 0.683936, acc.: 58.01%] [G loss: 0.722597]
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5916 [D loss: 0.690607, acc.: 51.37%] [G loss: 0.719069]
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5917 [D loss: 0.686899, acc.: 53.91%] [G loss: 0.719332]
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5918 [D loss: 0.678866, acc.: 57.23%] [G loss: 0.724594]
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5919 [D loss: 0.680979, acc.: 55.86%] [G loss: 0.730320]
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5920 [D loss: 0.679916, acc.: 57.23%] [G loss: 0.725902]
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5921 [D loss: 0.689878, acc.: 53.91%] [G loss: 0.735763]
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5922 [D loss: 0.680042, acc.: 56.45%] [G loss: 0.744374]
8/8 [==============================] - 0s 4ms/step
5923 [D loss: 0.685531, acc.: 52.93%] [G loss: 0.725148]
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5924 [D loss: 0.692047, acc.: 53.71%] [G loss: 0.733696]
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5925 [D loss: 0.679602, acc.: 58.40%] [G loss: 0.725398]
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5926 [D loss: 0.686782, acc.: 55.66%] [G loss: 0.724574]
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5927 [D loss: 0.685412, acc.: 53.52%] [G loss: 0.719565]
8/8 [==============================] - 0s 4ms/step
5928 [D loss: 0.676235, acc.: 58.98%] [G loss: 0.729355]
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5929 [D loss: 0.683661, acc.: 55.08%] [G loss: 0.729510]
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5930 [D loss: 0.686556, acc.: 54.49%] [G loss: 0.721148]
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5931 [D loss: 0.686413, acc.: 54.49%] [G loss: 0.724621]
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5932 [D loss: 0.689225, acc.: 54.88%] [G loss: 0.724834]
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5933 [D loss: 0.678012, acc.: 59.57%] [G loss: 0.725051]
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5934 [D loss: 0.677971, acc.: 56.45%] [G loss: 0.728019]
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5935 [D loss: 0.678704, acc.: 58.98%] [G loss: 0.721469]
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5936 [D loss: 0.677459, acc.: 58.59%] [G loss: 0.724376]
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5937 [D loss: 0.681396, acc.: 57.81%] [G loss: 0.713074]
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5938 [D loss: 0.680775, acc.: 56.45%] [G loss: 0.718940]
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5939 [D loss: 0.683796, acc.: 54.69%] [G loss: 0.713497]
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5940 [D loss: 0.687698, acc.: 54.49%] [G loss: 0.706533]
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5941 [D loss: 0.682780, acc.: 54.88%] [G loss: 0.718236]
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5942 [D loss: 0.681842, acc.: 55.47%] [G loss: 0.738482]
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5943 [D loss: 0.685431, acc.: 53.91%] [G loss: 0.734565]
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5944 [D loss: 0.681435, acc.: 56.05%] [G loss: 0.730412]
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5945 [D loss: 0.682978, acc.: 53.71%] [G loss: 0.728420]
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5946 [D loss: 0.681434, acc.: 55.27%] [G loss: 0.730512]
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5947 [D loss: 0.682952, acc.: 56.25%] [G loss: 0.728547]
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5948 [D loss: 0.690657, acc.: 54.49%] [G loss: 0.728031]
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5949 [D loss: 0.677343, acc.: 59.96%] [G loss: 0.740333]
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5950 [D loss: 0.681568, acc.: 56.84%] [G loss: 0.732773]
1/1 [==============================] - 0s 18ms/step
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5951 [D loss: 0.676259, acc.: 56.84%] [G loss: 0.719102]
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5952 [D loss: 0.696544, acc.: 50.98%] [G loss: 0.713965]
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5953 [D loss: 0.690823, acc.: 55.08%] [G loss: 0.724502]
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5954 [D loss: 0.689642, acc.: 53.32%] [G loss: 0.745075]
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5955 [D loss: 0.689553, acc.: 53.71%] [G loss: 0.722977]
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5956 [D loss: 0.682170, acc.: 58.01%] [G loss: 0.737814]
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5957 [D loss: 0.674685, acc.: 59.57%] [G loss: 0.744220]
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5958 [D loss: 0.680715, acc.: 57.62%] [G loss: 0.733168]
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5959 [D loss: 0.677280, acc.: 58.20%] [G loss: 0.734298]
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5960 [D loss: 0.689760, acc.: 53.12%] [G loss: 0.729626]
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5961 [D loss: 0.685646, acc.: 53.12%] [G loss: 0.715923]
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5962 [D loss: 0.694217, acc.: 51.56%] [G loss: 0.713239]
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5963 [D loss: 0.690601, acc.: 52.73%] [G loss: 0.734333]
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5964 [D loss: 0.677877, acc.: 56.45%] [G loss: 0.757900]
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5965 [D loss: 0.680241, acc.: 57.42%] [G loss: 0.759042]
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5966 [D loss: 0.678651, acc.: 58.20%] [G loss: 0.765177]
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5967 [D loss: 0.688316, acc.: 52.93%] [G loss: 0.744811]
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5968 [D loss: 0.673585, acc.: 57.62%] [G loss: 0.740035]
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5969 [D loss: 0.693855, acc.: 51.37%] [G loss: 0.723748]
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5970 [D loss: 0.685686, acc.: 55.27%] [G loss: 0.723197]
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5971 [D loss: 0.689462, acc.: 52.93%] [G loss: 0.731916]
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5972 [D loss: 0.681959, acc.: 56.64%] [G loss: 0.738012]
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5973 [D loss: 0.677500, acc.: 56.05%] [G loss: 0.752879]
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5974 [D loss: 0.676634, acc.: 57.81%] [G loss: 0.747244]
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5975 [D loss: 0.676395, acc.: 58.40%] [G loss: 0.721557]
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5976 [D loss: 0.686021, acc.: 52.54%] [G loss: 0.727931]
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5977 [D loss: 0.685475, acc.: 53.12%] [G loss: 0.707617]
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5978 [D loss: 0.692470, acc.: 52.34%] [G loss: 0.724148]
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5979 [D loss: 0.694936, acc.: 52.15%] [G loss: 0.738106]
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5980 [D loss: 0.687112, acc.: 52.93%] [G loss: 0.747025]
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5981 [D loss: 0.670025, acc.: 58.01%] [G loss: 0.762962]
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5982 [D loss: 0.678414, acc.: 60.55%] [G loss: 0.745113]
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5983 [D loss: 0.686526, acc.: 54.10%] [G loss: 0.729077]
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5984 [D loss: 0.696646, acc.: 50.98%] [G loss: 0.711385]
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5985 [D loss: 0.685573, acc.: 53.71%] [G loss: 0.706721]
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5986 [D loss: 0.695291, acc.: 51.37%] [G loss: 0.716527]
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5987 [D loss: 0.687921, acc.: 55.08%] [G loss: 0.720032]
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5988 [D loss: 0.679925, acc.: 56.45%] [G loss: 0.742343]
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5989 [D loss: 0.673268, acc.: 60.74%] [G loss: 0.750498]
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5990 [D loss: 0.679005, acc.: 57.23%] [G loss: 0.742583]
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5991 [D loss: 0.685121, acc.: 54.10%] [G loss: 0.748710]
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5992 [D loss: 0.682533, acc.: 56.05%] [G loss: 0.725160]
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5993 [D loss: 0.696403, acc.: 49.22%] [G loss: 0.737649]
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5994 [D loss: 0.689791, acc.: 52.93%] [G loss: 0.745482]
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5995 [D loss: 0.680118, acc.: 56.25%] [G loss: 0.741813]
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5996 [D loss: 0.675346, acc.: 56.84%] [G loss: 0.764786]
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5997 [D loss: 0.671406, acc.: 60.16%] [G loss: 0.759286]
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5998 [D loss: 0.672494, acc.: 57.81%] [G loss: 0.741700]
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5999 [D loss: 0.687138, acc.: 55.08%] [G loss: 0.726537]
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6000 [D loss: 0.686992, acc.: 55.08%] [G loss: 0.713957]
1/1 [==============================] - 0s 17ms/step
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6001 [D loss: 0.692668, acc.: 52.34%] [G loss: 0.716416]
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6002 [D loss: 0.688131, acc.: 55.27%] [G loss: 0.716583]
8/8 [==============================] - 0s 4ms/step
6003 [D loss: 0.693581, acc.: 50.00%] [G loss: 0.722001]
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6004 [D loss: 0.686806, acc.: 54.69%] [G loss: 0.731416]
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6005 [D loss: 0.682450, acc.: 55.08%] [G loss: 0.732808]
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6006 [D loss: 0.675475, acc.: 56.84%] [G loss: 0.736924]
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6007 [D loss: 0.680363, acc.: 57.03%] [G loss: 0.727435]
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6008 [D loss: 0.679000, acc.: 57.81%] [G loss: 0.741804]
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6009 [D loss: 0.683052, acc.: 53.91%] [G loss: 0.731874]
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6010 [D loss: 0.687665, acc.: 52.93%] [G loss: 0.747635]
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6011 [D loss: 0.682290, acc.: 58.01%] [G loss: 0.747693]
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6012 [D loss: 0.675446, acc.: 59.18%] [G loss: 0.755715]
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6013 [D loss: 0.679122, acc.: 56.84%] [G loss: 0.748970]
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6014 [D loss: 0.669501, acc.: 62.11%] [G loss: 0.753422]
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6015 [D loss: 0.679740, acc.: 58.59%] [G loss: 0.734845]
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6016 [D loss: 0.685706, acc.: 55.66%] [G loss: 0.723087]
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6017 [D loss: 0.687070, acc.: 55.27%] [G loss: 0.716563]
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6018 [D loss: 0.687083, acc.: 51.95%] [G loss: 0.705377]
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6019 [D loss: 0.687755, acc.: 53.91%] [G loss: 0.713208]
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6020 [D loss: 0.679136, acc.: 56.05%] [G loss: 0.734756]
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6021 [D loss: 0.675080, acc.: 60.35%] [G loss: 0.747865]
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6022 [D loss: 0.678941, acc.: 57.62%] [G loss: 0.734870]
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6023 [D loss: 0.668835, acc.: 59.57%] [G loss: 0.733368]
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6024 [D loss: 0.684861, acc.: 55.27%] [G loss: 0.734523]
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6025 [D loss: 0.677351, acc.: 58.79%] [G loss: 0.724633]
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6026 [D loss: 0.689032, acc.: 53.12%] [G loss: 0.717273]
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6027 [D loss: 0.680342, acc.: 55.08%] [G loss: 0.709304]
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6028 [D loss: 0.684778, acc.: 54.69%] [G loss: 0.719121]
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6029 [D loss: 0.688802, acc.: 51.56%] [G loss: 0.738780]
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6030 [D loss: 0.688917, acc.: 54.49%] [G loss: 0.739804]
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6031 [D loss: 0.677472, acc.: 58.59%] [G loss: 0.753164]
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6032 [D loss: 0.678795, acc.: 57.03%] [G loss: 0.737592]
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6033 [D loss: 0.674737, acc.: 61.13%] [G loss: 0.742537]
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6034 [D loss: 0.675688, acc.: 58.40%] [G loss: 0.738718]
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6035 [D loss: 0.687219, acc.: 57.23%] [G loss: 0.720064]
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6036 [D loss: 0.681403, acc.: 55.08%] [G loss: 0.718480]
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6037 [D loss: 0.686618, acc.: 56.05%] [G loss: 0.732459]
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6038 [D loss: 0.677356, acc.: 57.81%] [G loss: 0.730249]
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6039 [D loss: 0.671828, acc.: 59.57%] [G loss: 0.736897]
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6040 [D loss: 0.676184, acc.: 57.03%] [G loss: 0.737748]
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6041 [D loss: 0.674416, acc.: 60.94%] [G loss: 0.733930]
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6042 [D loss: 0.680753, acc.: 54.88%] [G loss: 0.727457]
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6043 [D loss: 0.677852, acc.: 57.62%] [G loss: 0.724202]
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6044 [D loss: 0.683619, acc.: 54.88%] [G loss: 0.731003]
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6045 [D loss: 0.682905, acc.: 58.20%] [G loss: 0.739362]
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6046 [D loss: 0.679338, acc.: 57.23%] [G loss: 0.726255]
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6047 [D loss: 0.679852, acc.: 57.81%] [G loss: 0.749440]
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6048 [D loss: 0.688883, acc.: 51.56%] [G loss: 0.730960]
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6049 [D loss: 0.673091, acc.: 60.35%] [G loss: 0.731315]
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6050 [D loss: 0.691016, acc.: 50.98%] [G loss: 0.730633]
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6051 [D loss: 0.688529, acc.: 53.91%] [G loss: 0.717197]
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6052 [D loss: 0.687962, acc.: 53.71%] [G loss: 0.712690]
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6053 [D loss: 0.682480, acc.: 56.84%] [G loss: 0.722938]
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6054 [D loss: 0.682783, acc.: 54.49%] [G loss: 0.730648]
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6055 [D loss: 0.682187, acc.: 55.86%] [G loss: 0.730054]
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6056 [D loss: 0.674301, acc.: 57.23%] [G loss: 0.736263]
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6057 [D loss: 0.677285, acc.: 58.40%] [G loss: 0.747781]
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6058 [D loss: 0.665137, acc.: 62.70%] [G loss: 0.727564]
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6059 [D loss: 0.671697, acc.: 61.13%] [G loss: 0.730749]
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6060 [D loss: 0.672387, acc.: 58.20%] [G loss: 0.731395]
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6061 [D loss: 0.682278, acc.: 57.03%] [G loss: 0.715236]
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6062 [D loss: 0.689974, acc.: 53.71%] [G loss: 0.712005]
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6063 [D loss: 0.678531, acc.: 56.64%] [G loss: 0.735686]
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6064 [D loss: 0.679658, acc.: 56.25%] [G loss: 0.729798]
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6065 [D loss: 0.682407, acc.: 55.86%] [G loss: 0.742331]
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6066 [D loss: 0.678004, acc.: 55.47%] [G loss: 0.739356]
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6067 [D loss: 0.676891, acc.: 60.16%] [G loss: 0.728831]
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6068 [D loss: 0.689192, acc.: 52.93%] [G loss: 0.736618]
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6069 [D loss: 0.693442, acc.: 52.34%] [G loss: 0.726011]
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6070 [D loss: 0.675416, acc.: 56.64%] [G loss: 0.729771]
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6071 [D loss: 0.676435, acc.: 57.23%] [G loss: 0.728469]
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6072 [D loss: 0.689815, acc.: 53.32%] [G loss: 0.713607]
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6073 [D loss: 0.683904, acc.: 56.45%] [G loss: 0.727421]
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6074 [D loss: 0.679062, acc.: 56.84%] [G loss: 0.738410]
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6075 [D loss: 0.682847, acc.: 55.27%] [G loss: 0.729109]
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6076 [D loss: 0.686150, acc.: 57.03%] [G loss: 0.731591]
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6077 [D loss: 0.687592, acc.: 53.32%] [G loss: 0.720763]
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6078 [D loss: 0.688860, acc.: 53.91%] [G loss: 0.730554]
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6079 [D loss: 0.691299, acc.: 53.12%] [G loss: 0.728269]
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6080 [D loss: 0.683956, acc.: 58.40%] [G loss: 0.732624]
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6081 [D loss: 0.682610, acc.: 53.91%] [G loss: 0.711858]
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6082 [D loss: 0.683432, acc.: 57.42%] [G loss: 0.733750]
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6083 [D loss: 0.685014, acc.: 54.10%] [G loss: 0.738515]
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6084 [D loss: 0.673262, acc.: 58.01%] [G loss: 0.740551]
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6085 [D loss: 0.690944, acc.: 51.95%] [G loss: 0.741426]
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6086 [D loss: 0.689251, acc.: 54.88%] [G loss: 0.737693]
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6087 [D loss: 0.683189, acc.: 53.32%] [G loss: 0.733578]
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6088 [D loss: 0.685145, acc.: 54.69%] [G loss: 0.731388]
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6089 [D loss: 0.686471, acc.: 53.91%] [G loss: 0.739160]
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6090 [D loss: 0.686151, acc.: 56.64%] [G loss: 0.735286]
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6091 [D loss: 0.680201, acc.: 58.98%] [G loss: 0.741136]
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6092 [D loss: 0.682464, acc.: 56.05%] [G loss: 0.732139]
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6093 [D loss: 0.678095, acc.: 58.79%] [G loss: 0.732517]
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6094 [D loss: 0.692698, acc.: 53.12%] [G loss: 0.736649]
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6095 [D loss: 0.680491, acc.: 57.03%] [G loss: 0.739325]
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6096 [D loss: 0.683957, acc.: 54.49%] [G loss: 0.729143]
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6097 [D loss: 0.676709, acc.: 55.66%] [G loss: 0.734123]
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6098 [D loss: 0.686650, acc.: 55.86%] [G loss: 0.738571]
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6099 [D loss: 0.687572, acc.: 55.27%] [G loss: 0.714876]
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6100 [D loss: 0.686375, acc.: 54.30%] [G loss: 0.726659]
1/1 [==============================] - 0s 17ms/step
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6101 [D loss: 0.676269, acc.: 59.57%] [G loss: 0.726486]
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6102 [D loss: 0.692022, acc.: 53.52%] [G loss: 0.731038]
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6103 [D loss: 0.683566, acc.: 55.66%] [G loss: 0.730734]
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6104 [D loss: 0.676098, acc.: 57.03%] [G loss: 0.717201]
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6105 [D loss: 0.683190, acc.: 56.84%] [G loss: 0.722078]
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6106 [D loss: 0.674963, acc.: 58.98%] [G loss: 0.719987]
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6107 [D loss: 0.683857, acc.: 55.86%] [G loss: 0.716376]
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6108 [D loss: 0.683683, acc.: 54.10%] [G loss: 0.724722]
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6109 [D loss: 0.691195, acc.: 51.95%] [G loss: 0.724538]
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6110 [D loss: 0.684122, acc.: 54.10%] [G loss: 0.724126]
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6111 [D loss: 0.683199, acc.: 54.30%] [G loss: 0.735299]
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6112 [D loss: 0.683050, acc.: 58.59%] [G loss: 0.729279]
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6113 [D loss: 0.678232, acc.: 56.45%] [G loss: 0.735556]
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6114 [D loss: 0.686502, acc.: 58.20%] [G loss: 0.733375]
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6115 [D loss: 0.683862, acc.: 53.52%] [G loss: 0.731700]
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6116 [D loss: 0.687854, acc.: 51.17%] [G loss: 0.712172]
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6117 [D loss: 0.687268, acc.: 53.52%] [G loss: 0.729354]
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6118 [D loss: 0.686642, acc.: 55.27%] [G loss: 0.727243]
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6119 [D loss: 0.680417, acc.: 58.59%] [G loss: 0.720282]
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6120 [D loss: 0.690823, acc.: 51.76%] [G loss: 0.733669]
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6121 [D loss: 0.679745, acc.: 58.01%] [G loss: 0.746687]
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6122 [D loss: 0.676158, acc.: 58.59%] [G loss: 0.746096]
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6123 [D loss: 0.685867, acc.: 53.71%] [G loss: 0.733379]
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6124 [D loss: 0.677044, acc.: 57.03%] [G loss: 0.738962]
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6125 [D loss: 0.686890, acc.: 53.71%] [G loss: 0.741597]
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6126 [D loss: 0.686051, acc.: 53.52%] [G loss: 0.732351]
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6127 [D loss: 0.678409, acc.: 55.86%] [G loss: 0.725852]
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6128 [D loss: 0.676820, acc.: 58.20%] [G loss: 0.727312]
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6129 [D loss: 0.692323, acc.: 54.10%] [G loss: 0.731014]
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6130 [D loss: 0.682115, acc.: 56.45%] [G loss: 0.739090]
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6131 [D loss: 0.679852, acc.: 57.81%] [G loss: 0.736642]
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6132 [D loss: 0.683885, acc.: 55.08%] [G loss: 0.732498]
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6133 [D loss: 0.677333, acc.: 58.98%] [G loss: 0.724351]
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6134 [D loss: 0.678889, acc.: 55.08%] [G loss: 0.738184]
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6135 [D loss: 0.683670, acc.: 58.40%] [G loss: 0.731748]
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6136 [D loss: 0.674983, acc.: 58.40%] [G loss: 0.734131]
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6137 [D loss: 0.687661, acc.: 52.15%] [G loss: 0.719291]
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6138 [D loss: 0.687261, acc.: 58.20%] [G loss: 0.736131]
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6139 [D loss: 0.678752, acc.: 57.62%] [G loss: 0.725789]
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6140 [D loss: 0.691196, acc.: 52.54%] [G loss: 0.729771]
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6141 [D loss: 0.679318, acc.: 58.59%] [G loss: 0.730664]
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6142 [D loss: 0.678113, acc.: 57.42%] [G loss: 0.726136]
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6143 [D loss: 0.685458, acc.: 54.30%] [G loss: 0.720195]
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6144 [D loss: 0.680041, acc.: 57.42%] [G loss: 0.730025]
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6145 [D loss: 0.681633, acc.: 57.81%] [G loss: 0.735994]
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6146 [D loss: 0.681010, acc.: 56.45%] [G loss: 0.727346]
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6147 [D loss: 0.682486, acc.: 56.45%] [G loss: 0.717266]
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6148 [D loss: 0.680410, acc.: 58.01%] [G loss: 0.729397]
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6149 [D loss: 0.691816, acc.: 52.93%] [G loss: 0.731915]
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6150 [D loss: 0.680418, acc.: 55.86%] [G loss: 0.715094]
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6151 [D loss: 0.682162, acc.: 57.81%] [G loss: 0.726318]
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6152 [D loss: 0.680583, acc.: 57.62%] [G loss: 0.727903]
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6153 [D loss: 0.667932, acc.: 59.77%] [G loss: 0.726271]
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6154 [D loss: 0.682373, acc.: 55.66%] [G loss: 0.723454]
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6155 [D loss: 0.678523, acc.: 56.64%] [G loss: 0.737472]
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6156 [D loss: 0.686682, acc.: 55.47%] [G loss: 0.737151]
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6157 [D loss: 0.681799, acc.: 55.86%] [G loss: 0.732867]
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6158 [D loss: 0.686893, acc.: 55.08%] [G loss: 0.725818]
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6159 [D loss: 0.676671, acc.: 57.81%] [G loss: 0.737164]
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6160 [D loss: 0.688431, acc.: 56.05%] [G loss: 0.726082]
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6161 [D loss: 0.676272, acc.: 58.40%] [G loss: 0.743824]
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6162 [D loss: 0.688976, acc.: 54.30%] [G loss: 0.737260]
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6163 [D loss: 0.678811, acc.: 58.59%] [G loss: 0.743352]
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6164 [D loss: 0.687467, acc.: 54.69%] [G loss: 0.741621]
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6165 [D loss: 0.680071, acc.: 57.42%] [G loss: 0.736886]
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6166 [D loss: 0.685338, acc.: 52.73%] [G loss: 0.732644]
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6167 [D loss: 0.686220, acc.: 53.71%] [G loss: 0.732031]
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6168 [D loss: 0.679871, acc.: 55.27%] [G loss: 0.736882]
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6169 [D loss: 0.682377, acc.: 57.03%] [G loss: 0.735291]
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6170 [D loss: 0.685469, acc.: 56.45%] [G loss: 0.727416]
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6171 [D loss: 0.689736, acc.: 54.69%] [G loss: 0.731296]
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6172 [D loss: 0.685082, acc.: 54.49%] [G loss: 0.729957]
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6173 [D loss: 0.684302, acc.: 56.64%] [G loss: 0.728111]
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6174 [D loss: 0.686857, acc.: 53.91%] [G loss: 0.734952]
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6175 [D loss: 0.677525, acc.: 58.01%] [G loss: 0.743785]
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6176 [D loss: 0.686928, acc.: 53.32%] [G loss: 0.723055]
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6177 [D loss: 0.682767, acc.: 52.73%] [G loss: 0.729018]
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6178 [D loss: 0.686015, acc.: 56.84%] [G loss: 0.719299]
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6179 [D loss: 0.681068, acc.: 57.23%] [G loss: 0.726524]
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6180 [D loss: 0.681345, acc.: 56.45%] [G loss: 0.718870]
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6181 [D loss: 0.693209, acc.: 51.56%] [G loss: 0.734456]
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6182 [D loss: 0.675150, acc.: 59.57%] [G loss: 0.732963]
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6183 [D loss: 0.681665, acc.: 54.69%] [G loss: 0.726941]
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6184 [D loss: 0.693635, acc.: 52.15%] [G loss: 0.749439]
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6185 [D loss: 0.673111, acc.: 56.45%] [G loss: 0.743112]
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6186 [D loss: 0.686844, acc.: 53.52%] [G loss: 0.741243]
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6187 [D loss: 0.682305, acc.: 57.81%] [G loss: 0.737966]
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6188 [D loss: 0.680064, acc.: 57.62%] [G loss: 0.737797]
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6189 [D loss: 0.692820, acc.: 54.30%] [G loss: 0.729903]
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6190 [D loss: 0.681457, acc.: 55.86%] [G loss: 0.749242]
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6191 [D loss: 0.682182, acc.: 55.86%] [G loss: 0.731366]
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6192 [D loss: 0.680753, acc.: 58.20%] [G loss: 0.733381]
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6193 [D loss: 0.679161, acc.: 59.57%] [G loss: 0.738606]
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6194 [D loss: 0.671879, acc.: 59.57%] [G loss: 0.715941]
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6195 [D loss: 0.687043, acc.: 56.45%] [G loss: 0.704174]
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6196 [D loss: 0.684813, acc.: 58.40%] [G loss: 0.708571]
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6197 [D loss: 0.693988, acc.: 52.15%] [G loss: 0.728923]
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6198 [D loss: 0.684701, acc.: 57.03%] [G loss: 0.735491]
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6199 [D loss: 0.678356, acc.: 54.88%] [G loss: 0.729255]
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6200 [D loss: 0.674266, acc.: 58.98%] [G loss: 0.739582]
1/1 [==============================] - 0s 17ms/step
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6201 [D loss: 0.677660, acc.: 55.27%] [G loss: 0.746441]
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6202 [D loss: 0.689999, acc.: 53.91%] [G loss: 0.732757]
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6203 [D loss: 0.695878, acc.: 51.76%] [G loss: 0.729628]
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6204 [D loss: 0.687549, acc.: 54.69%] [G loss: 0.734738]
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6205 [D loss: 0.687609, acc.: 52.73%] [G loss: 0.747302]
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6206 [D loss: 0.675291, acc.: 58.59%] [G loss: 0.756240]
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6207 [D loss: 0.670555, acc.: 62.30%] [G loss: 0.751509]
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6208 [D loss: 0.672241, acc.: 59.18%] [G loss: 0.741686]
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6209 [D loss: 0.671962, acc.: 58.40%] [G loss: 0.726184]
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6210 [D loss: 0.696131, acc.: 51.95%] [G loss: 0.727665]
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6211 [D loss: 0.680574, acc.: 59.57%] [G loss: 0.719641]
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6212 [D loss: 0.702348, acc.: 48.63%] [G loss: 0.715694]
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6213 [D loss: 0.683106, acc.: 57.03%] [G loss: 0.743534]
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6214 [D loss: 0.671913, acc.: 59.57%] [G loss: 0.761256]
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6215 [D loss: 0.667563, acc.: 61.52%] [G loss: 0.747935]
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6216 [D loss: 0.660421, acc.: 63.87%] [G loss: 0.757315]
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6217 [D loss: 0.669309, acc.: 59.77%] [G loss: 0.730033]
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6218 [D loss: 0.683834, acc.: 55.27%] [G loss: 0.719530]
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6219 [D loss: 0.696251, acc.: 52.73%] [G loss: 0.711400]
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6220 [D loss: 0.680408, acc.: 56.05%] [G loss: 0.721094]
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6221 [D loss: 0.692406, acc.: 51.95%] [G loss: 0.753648]
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6222 [D loss: 0.667135, acc.: 61.91%] [G loss: 0.781982]
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6223 [D loss: 0.670165, acc.: 58.79%] [G loss: 0.774843]
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6224 [D loss: 0.672850, acc.: 56.45%] [G loss: 0.766621]
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6225 [D loss: 0.671373, acc.: 58.40%] [G loss: 0.740394]
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6226 [D loss: 0.688261, acc.: 53.71%] [G loss: 0.728820]
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6227 [D loss: 0.693477, acc.: 54.88%] [G loss: 0.711350]
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6228 [D loss: 0.686126, acc.: 49.41%] [G loss: 0.714931]
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6229 [D loss: 0.699724, acc.: 48.63%] [G loss: 0.729293]
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6230 [D loss: 0.681876, acc.: 56.25%] [G loss: 0.742295]
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6231 [D loss: 0.674541, acc.: 60.55%] [G loss: 0.746359]
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6232 [D loss: 0.671493, acc.: 60.35%] [G loss: 0.736078]
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6233 [D loss: 0.682939, acc.: 58.59%] [G loss: 0.742651]
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6234 [D loss: 0.677258, acc.: 58.59%] [G loss: 0.747858]
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6235 [D loss: 0.684701, acc.: 55.66%] [G loss: 0.740309]
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6236 [D loss: 0.693023, acc.: 51.95%] [G loss: 0.740504]
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6237 [D loss: 0.690078, acc.: 53.12%] [G loss: 0.753040]
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6238 [D loss: 0.697341, acc.: 50.78%] [G loss: 0.743201]
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6239 [D loss: 0.679103, acc.: 58.40%] [G loss: 0.750676]
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6240 [D loss: 0.682496, acc.: 57.81%] [G loss: 0.753473]
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6241 [D loss: 0.675971, acc.: 60.35%] [G loss: 0.740080]
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6242 [D loss: 0.677198, acc.: 58.79%] [G loss: 0.739390]
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6243 [D loss: 0.674508, acc.: 55.27%] [G loss: 0.727603]
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6244 [D loss: 0.685655, acc.: 53.71%] [G loss: 0.739056]
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6245 [D loss: 0.682588, acc.: 58.98%] [G loss: 0.728600]
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6246 [D loss: 0.687467, acc.: 51.95%] [G loss: 0.735019]
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6247 [D loss: 0.681142, acc.: 55.86%] [G loss: 0.739888]
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6248 [D loss: 0.684140, acc.: 54.49%] [G loss: 0.716552]
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6249 [D loss: 0.679337, acc.: 56.25%] [G loss: 0.732100]
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6250 [D loss: 0.686808, acc.: 55.08%] [G loss: 0.738733]
1/1 [==============================] - 0s 18ms/step
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6251 [D loss: 0.686575, acc.: 54.88%] [G loss: 0.722635]
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6252 [D loss: 0.697513, acc.: 51.17%] [G loss: 0.734303]
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6253 [D loss: 0.688152, acc.: 56.84%] [G loss: 0.736334]
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6254 [D loss: 0.681504, acc.: 54.88%] [G loss: 0.742290]
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6255 [D loss: 0.675072, acc.: 58.59%] [G loss: 0.747287]
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6256 [D loss: 0.682435, acc.: 56.84%] [G loss: 0.733960]
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6257 [D loss: 0.670088, acc.: 62.89%] [G loss: 0.741543]
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6258 [D loss: 0.684725, acc.: 56.05%] [G loss: 0.738015]
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6259 [D loss: 0.678248, acc.: 57.62%] [G loss: 0.720658]
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6260 [D loss: 0.682701, acc.: 58.01%] [G loss: 0.716425]
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6261 [D loss: 0.684873, acc.: 55.86%] [G loss: 0.713651]
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6262 [D loss: 0.687471, acc.: 53.71%] [G loss: 0.701778]
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6263 [D loss: 0.675647, acc.: 56.45%] [G loss: 0.731359]
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6264 [D loss: 0.677574, acc.: 58.20%] [G loss: 0.747307]
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6265 [D loss: 0.679383, acc.: 58.40%] [G loss: 0.755310]
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6266 [D loss: 0.668817, acc.: 61.91%] [G loss: 0.749293]
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6267 [D loss: 0.683872, acc.: 57.62%] [G loss: 0.744171]
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6268 [D loss: 0.675958, acc.: 59.77%] [G loss: 0.732453]
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6269 [D loss: 0.686017, acc.: 51.95%] [G loss: 0.739470]
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6270 [D loss: 0.688562, acc.: 54.30%] [G loss: 0.749935]
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6271 [D loss: 0.692533, acc.: 53.32%] [G loss: 0.736765]
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6272 [D loss: 0.679788, acc.: 55.86%] [G loss: 0.738863]
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6273 [D loss: 0.678980, acc.: 55.47%] [G loss: 0.741502]
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6274 [D loss: 0.684310, acc.: 57.81%] [G loss: 0.746905]
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6275 [D loss: 0.675535, acc.: 56.64%] [G loss: 0.737404]
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6276 [D loss: 0.683874, acc.: 54.49%] [G loss: 0.730689]
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6277 [D loss: 0.682629, acc.: 55.86%] [G loss: 0.716809]
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6278 [D loss: 0.687758, acc.: 51.17%] [G loss: 0.734839]
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6279 [D loss: 0.674488, acc.: 58.79%] [G loss: 0.730147]
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6280 [D loss: 0.676229, acc.: 58.40%] [G loss: 0.731593]
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6281 [D loss: 0.679409, acc.: 55.08%] [G loss: 0.732605]
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6282 [D loss: 0.675845, acc.: 58.40%] [G loss: 0.727664]
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6283 [D loss: 0.682373, acc.: 55.66%] [G loss: 0.732505]
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6284 [D loss: 0.683594, acc.: 57.42%] [G loss: 0.733393]
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6285 [D loss: 0.682180, acc.: 59.38%] [G loss: 0.740452]
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6286 [D loss: 0.682573, acc.: 56.25%] [G loss: 0.735120]
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6287 [D loss: 0.675643, acc.: 57.81%] [G loss: 0.740406]
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6288 [D loss: 0.683574, acc.: 55.66%] [G loss: 0.742106]
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6289 [D loss: 0.689489, acc.: 53.52%] [G loss: 0.740861]
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6290 [D loss: 0.680515, acc.: 56.64%] [G loss: 0.744036]
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6291 [D loss: 0.681522, acc.: 57.81%] [G loss: 0.730123]
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6292 [D loss: 0.685581, acc.: 55.27%] [G loss: 0.718829]
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6293 [D loss: 0.680684, acc.: 55.08%] [G loss: 0.722583]
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6294 [D loss: 0.692338, acc.: 51.56%] [G loss: 0.718384]
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6295 [D loss: 0.685388, acc.: 55.08%] [G loss: 0.728788]
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6296 [D loss: 0.675785, acc.: 58.01%] [G loss: 0.727811]
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6297 [D loss: 0.674631, acc.: 57.81%] [G loss: 0.726913]
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6298 [D loss: 0.675392, acc.: 58.59%] [G loss: 0.736099]
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6299 [D loss: 0.682772, acc.: 56.45%] [G loss: 0.731690]
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6300 [D loss: 0.684268, acc.: 57.03%] [G loss: 0.721889]
1/1 [==============================] - 0s 16ms/step
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6301 [D loss: 0.688441, acc.: 55.66%] [G loss: 0.731068]
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6302 [D loss: 0.684113, acc.: 55.86%] [G loss: 0.744974]
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6303 [D loss: 0.681338, acc.: 55.47%] [G loss: 0.731598]
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6304 [D loss: 0.671698, acc.: 58.59%] [G loss: 0.743210]
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6305 [D loss: 0.683138, acc.: 53.52%] [G loss: 0.736016]
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6306 [D loss: 0.676605, acc.: 57.23%] [G loss: 0.734980]
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6307 [D loss: 0.677802, acc.: 55.86%] [G loss: 0.721905]
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6308 [D loss: 0.679764, acc.: 53.52%] [G loss: 0.723583]
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6309 [D loss: 0.684971, acc.: 55.27%] [G loss: 0.719254]
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6310 [D loss: 0.688223, acc.: 55.86%] [G loss: 0.722693]
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6311 [D loss: 0.679181, acc.: 60.16%] [G loss: 0.727303]
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6312 [D loss: 0.681491, acc.: 54.88%] [G loss: 0.735958]
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6313 [D loss: 0.674507, acc.: 58.79%] [G loss: 0.732908]
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6314 [D loss: 0.679244, acc.: 56.84%] [G loss: 0.742680]
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6315 [D loss: 0.680624, acc.: 58.79%] [G loss: 0.732371]
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6316 [D loss: 0.692011, acc.: 51.17%] [G loss: 0.733305]
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6317 [D loss: 0.687855, acc.: 55.66%] [G loss: 0.720232]
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6318 [D loss: 0.687504, acc.: 53.32%] [G loss: 0.733489]
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6319 [D loss: 0.685872, acc.: 55.66%] [G loss: 0.741628]
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6320 [D loss: 0.679088, acc.: 55.66%] [G loss: 0.748054]
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6321 [D loss: 0.683743, acc.: 54.88%] [G loss: 0.751868]
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6322 [D loss: 0.688153, acc.: 55.86%] [G loss: 0.761157]
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6323 [D loss: 0.679210, acc.: 60.16%] [G loss: 0.751386]
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6324 [D loss: 0.683179, acc.: 55.47%] [G loss: 0.732186]
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6325 [D loss: 0.677755, acc.: 58.98%] [G loss: 0.738177]
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6326 [D loss: 0.683475, acc.: 55.27%] [G loss: 0.742903]
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6327 [D loss: 0.686873, acc.: 54.30%] [G loss: 0.747189]
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6328 [D loss: 0.679392, acc.: 52.93%] [G loss: 0.737935]
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6329 [D loss: 0.683281, acc.: 55.47%] [G loss: 0.729866]
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6330 [D loss: 0.675016, acc.: 57.42%] [G loss: 0.744509]
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6331 [D loss: 0.679663, acc.: 56.84%] [G loss: 0.734891]
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6332 [D loss: 0.683293, acc.: 53.52%] [G loss: 0.720677]
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6333 [D loss: 0.693876, acc.: 52.73%] [G loss: 0.725665]
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6334 [D loss: 0.678355, acc.: 54.49%] [G loss: 0.724163]
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6335 [D loss: 0.682535, acc.: 56.84%] [G loss: 0.726282]
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6336 [D loss: 0.683335, acc.: 53.91%] [G loss: 0.729840]
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6337 [D loss: 0.688752, acc.: 53.12%] [G loss: 0.734835]
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6338 [D loss: 0.684260, acc.: 56.05%] [G loss: 0.733269]
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6339 [D loss: 0.687231, acc.: 56.64%] [G loss: 0.736066]
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6340 [D loss: 0.689589, acc.: 52.15%] [G loss: 0.753490]
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6341 [D loss: 0.687143, acc.: 53.71%] [G loss: 0.751789]
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6342 [D loss: 0.676145, acc.: 58.98%] [G loss: 0.735486]
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6343 [D loss: 0.677784, acc.: 58.20%] [G loss: 0.729056]
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6344 [D loss: 0.675740, acc.: 58.40%] [G loss: 0.732047]
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6345 [D loss: 0.696455, acc.: 53.32%] [G loss: 0.721795]
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6346 [D loss: 0.692559, acc.: 54.49%] [G loss: 0.736712]
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6347 [D loss: 0.680569, acc.: 55.66%] [G loss: 0.736720]
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6348 [D loss: 0.684927, acc.: 57.62%] [G loss: 0.739107]
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6349 [D loss: 0.675480, acc.: 58.20%] [G loss: 0.747199]
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6350 [D loss: 0.683216, acc.: 53.52%] [G loss: 0.744283]
1/1 [==============================] - 0s 18ms/step
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6351 [D loss: 0.680117, acc.: 58.79%] [G loss: 0.731416]
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6352 [D loss: 0.678172, acc.: 57.81%] [G loss: 0.726898]
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6353 [D loss: 0.687735, acc.: 53.52%] [G loss: 0.720519]
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6354 [D loss: 0.685430, acc.: 55.47%] [G loss: 0.720980]
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6355 [D loss: 0.682026, acc.: 59.57%] [G loss: 0.733457]
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6356 [D loss: 0.675535, acc.: 59.57%] [G loss: 0.736944]
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6357 [D loss: 0.681258, acc.: 55.66%] [G loss: 0.731257]
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6358 [D loss: 0.685511, acc.: 55.27%] [G loss: 0.729669]
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6359 [D loss: 0.681722, acc.: 55.47%] [G loss: 0.732882]
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6360 [D loss: 0.681293, acc.: 56.84%] [G loss: 0.730677]
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6361 [D loss: 0.681348, acc.: 57.81%] [G loss: 0.730395]
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6362 [D loss: 0.683567, acc.: 56.84%] [G loss: 0.716298]
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6363 [D loss: 0.688306, acc.: 52.93%] [G loss: 0.731175]
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6364 [D loss: 0.682043, acc.: 58.20%] [G loss: 0.717266]
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6365 [D loss: 0.682479, acc.: 57.62%] [G loss: 0.721580]
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6366 [D loss: 0.683636, acc.: 55.47%] [G loss: 0.737487]
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6367 [D loss: 0.687216, acc.: 55.66%] [G loss: 0.722757]
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6368 [D loss: 0.687730, acc.: 53.91%] [G loss: 0.732740]
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6369 [D loss: 0.687889, acc.: 52.34%] [G loss: 0.736544]
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6370 [D loss: 0.682257, acc.: 58.20%] [G loss: 0.727265]
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6371 [D loss: 0.685121, acc.: 53.91%] [G loss: 0.739947]
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6372 [D loss: 0.681729, acc.: 58.40%] [G loss: 0.729904]
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6373 [D loss: 0.681445, acc.: 54.10%] [G loss: 0.730749]
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6374 [D loss: 0.691586, acc.: 52.73%] [G loss: 0.735600]
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6375 [D loss: 0.680187, acc.: 56.84%] [G loss: 0.738118]
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6376 [D loss: 0.689504, acc.: 53.91%] [G loss: 0.738762]
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6377 [D loss: 0.678756, acc.: 55.86%] [G loss: 0.745298]
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6378 [D loss: 0.682042, acc.: 56.45%] [G loss: 0.740599]
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6379 [D loss: 0.684338, acc.: 54.49%] [G loss: 0.743423]
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6380 [D loss: 0.679623, acc.: 56.25%] [G loss: 0.747267]
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6381 [D loss: 0.681959, acc.: 54.30%] [G loss: 0.746495]
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6382 [D loss: 0.684928, acc.: 56.64%] [G loss: 0.729735]
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6383 [D loss: 0.686336, acc.: 52.93%] [G loss: 0.740819]
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6384 [D loss: 0.673851, acc.: 58.40%] [G loss: 0.745994]
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6385 [D loss: 0.691230, acc.: 50.20%] [G loss: 0.738404]
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6386 [D loss: 0.685581, acc.: 55.66%] [G loss: 0.735365]
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6387 [D loss: 0.686975, acc.: 58.01%] [G loss: 0.744769]
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6388 [D loss: 0.685590, acc.: 54.69%] [G loss: 0.746295]
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6389 [D loss: 0.671758, acc.: 60.74%] [G loss: 0.734136]
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6390 [D loss: 0.684681, acc.: 56.25%] [G loss: 0.733741]
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6391 [D loss: 0.683351, acc.: 56.64%] [G loss: 0.731549]
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6392 [D loss: 0.671034, acc.: 60.94%] [G loss: 0.721039]
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6393 [D loss: 0.680778, acc.: 55.47%] [G loss: 0.729353]
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6394 [D loss: 0.686112, acc.: 53.32%] [G loss: 0.719625]
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6395 [D loss: 0.679099, acc.: 57.62%] [G loss: 0.723698]
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6396 [D loss: 0.682942, acc.: 55.47%] [G loss: 0.735295]
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6397 [D loss: 0.679108, acc.: 56.84%] [G loss: 0.747204]
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6398 [D loss: 0.685833, acc.: 55.08%] [G loss: 0.731758]
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6399 [D loss: 0.689527, acc.: 53.52%] [G loss: 0.723699]
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6400 [D loss: 0.676822, acc.: 57.42%] [G loss: 0.738997]
1/1 [==============================] - 0s 22ms/step
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6401 [D loss: 0.675763, acc.: 56.45%] [G loss: 0.731917]
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6402 [D loss: 0.682355, acc.: 56.45%] [G loss: 0.734749]
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6403 [D loss: 0.681336, acc.: 54.10%] [G loss: 0.746084]
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6404 [D loss: 0.685104, acc.: 53.91%] [G loss: 0.728379]
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6405 [D loss: 0.680847, acc.: 54.88%] [G loss: 0.735651]
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6406 [D loss: 0.677663, acc.: 57.42%] [G loss: 0.728581]
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6407 [D loss: 0.678020, acc.: 56.05%] [G loss: 0.727144]
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6408 [D loss: 0.683183, acc.: 55.08%] [G loss: 0.737607]
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6409 [D loss: 0.681537, acc.: 55.27%] [G loss: 0.730904]
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6410 [D loss: 0.682626, acc.: 56.45%] [G loss: 0.732105]
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6411 [D loss: 0.688247, acc.: 53.32%] [G loss: 0.729469]
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6412 [D loss: 0.682793, acc.: 57.23%] [G loss: 0.738921]
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6413 [D loss: 0.690738, acc.: 52.34%] [G loss: 0.735815]
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6414 [D loss: 0.684134, acc.: 58.20%] [G loss: 0.728443]
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6415 [D loss: 0.683814, acc.: 53.32%] [G loss: 0.740681]
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6416 [D loss: 0.685050, acc.: 56.84%] [G loss: 0.740092]
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6417 [D loss: 0.677396, acc.: 58.01%] [G loss: 0.731663]
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6418 [D loss: 0.679715, acc.: 54.69%] [G loss: 0.723202]
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6419 [D loss: 0.695155, acc.: 53.12%] [G loss: 0.716606]
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6420 [D loss: 0.687379, acc.: 54.10%] [G loss: 0.723351]
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6421 [D loss: 0.683793, acc.: 55.47%] [G loss: 0.730890]
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6422 [D loss: 0.678370, acc.: 58.40%] [G loss: 0.740567]
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6423 [D loss: 0.680049, acc.: 57.81%] [G loss: 0.737031]
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6424 [D loss: 0.677992, acc.: 57.62%] [G loss: 0.724015]
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6425 [D loss: 0.681749, acc.: 54.88%] [G loss: 0.725569]
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6426 [D loss: 0.684678, acc.: 58.01%] [G loss: 0.736193]
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6427 [D loss: 0.685018, acc.: 56.05%] [G loss: 0.740987]
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6428 [D loss: 0.684618, acc.: 56.64%] [G loss: 0.730867]
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6429 [D loss: 0.681073, acc.: 55.47%] [G loss: 0.722110]
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6430 [D loss: 0.681663, acc.: 55.66%] [G loss: 0.725427]
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6431 [D loss: 0.685724, acc.: 51.95%] [G loss: 0.730994]
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6432 [D loss: 0.686664, acc.: 55.08%] [G loss: 0.725403]
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6433 [D loss: 0.682525, acc.: 56.05%] [G loss: 0.735631]
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6434 [D loss: 0.690771, acc.: 51.56%] [G loss: 0.729589]
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6435 [D loss: 0.677995, acc.: 57.03%] [G loss: 0.727443]
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6436 [D loss: 0.682072, acc.: 55.27%] [G loss: 0.730951]
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6437 [D loss: 0.682969, acc.: 55.86%] [G loss: 0.725823]
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6438 [D loss: 0.675727, acc.: 57.62%] [G loss: 0.722973]
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6439 [D loss: 0.685190, acc.: 56.45%] [G loss: 0.714975]
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6440 [D loss: 0.687759, acc.: 53.71%] [G loss: 0.735513]
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6441 [D loss: 0.682006, acc.: 56.45%] [G loss: 0.729271]
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6442 [D loss: 0.687716, acc.: 55.27%] [G loss: 0.720542]
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6443 [D loss: 0.681838, acc.: 55.47%] [G loss: 0.733308]
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6444 [D loss: 0.675229, acc.: 58.01%] [G loss: 0.745004]
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6445 [D loss: 0.681572, acc.: 56.84%] [G loss: 0.742328]
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6446 [D loss: 0.679424, acc.: 58.20%] [G loss: 0.728730]
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6447 [D loss: 0.690402, acc.: 54.88%] [G loss: 0.741723]
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6448 [D loss: 0.685541, acc.: 57.03%] [G loss: 0.728997]
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6449 [D loss: 0.685158, acc.: 53.91%] [G loss: 0.729279]
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6450 [D loss: 0.682068, acc.: 56.64%] [G loss: 0.734413]
1/1 [==============================] - 0s 17ms/step
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6451 [D loss: 0.686386, acc.: 51.95%] [G loss: 0.736456]
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6452 [D loss: 0.679507, acc.: 55.66%] [G loss: 0.740781]
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6453 [D loss: 0.684433, acc.: 56.25%] [G loss: 0.731379]
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6454 [D loss: 0.669559, acc.: 59.57%] [G loss: 0.746207]
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6455 [D loss: 0.671862, acc.: 60.55%] [G loss: 0.739630]
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6456 [D loss: 0.680612, acc.: 57.42%] [G loss: 0.730370]
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6457 [D loss: 0.689048, acc.: 53.91%] [G loss: 0.726125]
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6458 [D loss: 0.683253, acc.: 57.62%] [G loss: 0.739186]
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6459 [D loss: 0.686265, acc.: 52.93%] [G loss: 0.727678]
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6460 [D loss: 0.685158, acc.: 55.86%] [G loss: 0.748223]
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6461 [D loss: 0.682546, acc.: 52.93%] [G loss: 0.727718]
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6462 [D loss: 0.676128, acc.: 56.84%] [G loss: 0.734534]
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6463 [D loss: 0.674935, acc.: 58.59%] [G loss: 0.719841]
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6464 [D loss: 0.685523, acc.: 55.27%] [G loss: 0.715601]
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6465 [D loss: 0.694847, acc.: 53.71%] [G loss: 0.725526]
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6466 [D loss: 0.681032, acc.: 56.45%] [G loss: 0.725165]
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6467 [D loss: 0.690602, acc.: 54.69%] [G loss: 0.724663]
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6468 [D loss: 0.675400, acc.: 58.01%] [G loss: 0.738056]
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6469 [D loss: 0.685243, acc.: 56.45%] [G loss: 0.736324]
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6470 [D loss: 0.676071, acc.: 56.25%] [G loss: 0.744123]
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6471 [D loss: 0.669428, acc.: 60.35%] [G loss: 0.722439]
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6472 [D loss: 0.679168, acc.: 53.91%] [G loss: 0.719175]
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6473 [D loss: 0.687331, acc.: 53.12%] [G loss: 0.736233]
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6474 [D loss: 0.684875, acc.: 57.42%] [G loss: 0.715033]
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6475 [D loss: 0.685518, acc.: 54.10%] [G loss: 0.735016]
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6476 [D loss: 0.677060, acc.: 58.20%] [G loss: 0.751745]
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6477 [D loss: 0.670191, acc.: 60.16%] [G loss: 0.761179]
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6478 [D loss: 0.674980, acc.: 58.01%] [G loss: 0.759676]
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6479 [D loss: 0.674593, acc.: 60.94%] [G loss: 0.731009]
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6480 [D loss: 0.671790, acc.: 59.77%] [G loss: 0.709199]
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6481 [D loss: 0.678307, acc.: 55.66%] [G loss: 0.715379]
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6482 [D loss: 0.688503, acc.: 51.76%] [G loss: 0.704711]
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6483 [D loss: 0.681528, acc.: 52.73%] [G loss: 0.717014]
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6484 [D loss: 0.695077, acc.: 48.44%] [G loss: 0.736028]
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6485 [D loss: 0.682325, acc.: 57.81%] [G loss: 0.734068]
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6486 [D loss: 0.662306, acc.: 63.67%] [G loss: 0.723000]
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6487 [D loss: 0.679717, acc.: 56.84%] [G loss: 0.735732]
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6488 [D loss: 0.685739, acc.: 56.25%] [G loss: 0.715951]
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6489 [D loss: 0.693932, acc.: 48.83%] [G loss: 0.710260]
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6490 [D loss: 0.681375, acc.: 57.42%] [G loss: 0.735259]
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6491 [D loss: 0.679874, acc.: 57.03%] [G loss: 0.737319]
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6492 [D loss: 0.682309, acc.: 58.01%] [G loss: 0.735074]
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6493 [D loss: 0.677946, acc.: 57.42%] [G loss: 0.746578]
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6494 [D loss: 0.671118, acc.: 60.94%] [G loss: 0.745566]
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6495 [D loss: 0.681304, acc.: 56.05%] [G loss: 0.750908]
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6496 [D loss: 0.671705, acc.: 58.79%] [G loss: 0.722794]
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6497 [D loss: 0.684425, acc.: 57.23%] [G loss: 0.715037]
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6498 [D loss: 0.686953, acc.: 53.91%] [G loss: 0.721947]
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6499 [D loss: 0.683339, acc.: 55.47%] [G loss: 0.737116]
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6500 [D loss: 0.680851, acc.: 58.01%] [G loss: 0.725575]
1/1 [==============================] - 0s 19ms/step
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6501 [D loss: 0.676205, acc.: 59.96%] [G loss: 0.755121]
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6502 [D loss: 0.674300, acc.: 61.52%] [G loss: 0.751213]
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6503 [D loss: 0.679298, acc.: 58.98%] [G loss: 0.744686]
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6504 [D loss: 0.678207, acc.: 57.03%] [G loss: 0.743686]
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6505 [D loss: 0.688221, acc.: 53.12%] [G loss: 0.732501]
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6506 [D loss: 0.680683, acc.: 58.79%] [G loss: 0.714442]
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6507 [D loss: 0.679086, acc.: 55.86%] [G loss: 0.733089]
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6508 [D loss: 0.682969, acc.: 59.38%] [G loss: 0.749553]
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6509 [D loss: 0.680112, acc.: 57.42%] [G loss: 0.742227]
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6510 [D loss: 0.682501, acc.: 58.59%] [G loss: 0.734408]
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6511 [D loss: 0.684174, acc.: 56.64%] [G loss: 0.720114]
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6512 [D loss: 0.687596, acc.: 55.08%] [G loss: 0.733657]
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6513 [D loss: 0.679578, acc.: 54.88%] [G loss: 0.723632]
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6514 [D loss: 0.688344, acc.: 52.73%] [G loss: 0.736128]
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6515 [D loss: 0.690719, acc.: 51.95%] [G loss: 0.728927]
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6516 [D loss: 0.681654, acc.: 54.30%] [G loss: 0.731931]
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6517 [D loss: 0.676430, acc.: 58.40%] [G loss: 0.728629]
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6518 [D loss: 0.686497, acc.: 57.42%] [G loss: 0.747345]
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6519 [D loss: 0.681971, acc.: 56.84%] [G loss: 0.747362]
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6520 [D loss: 0.686276, acc.: 55.47%] [G loss: 0.746269]
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6521 [D loss: 0.686380, acc.: 56.25%] [G loss: 0.747403]
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6522 [D loss: 0.684653, acc.: 56.45%] [G loss: 0.745147]
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6523 [D loss: 0.679212, acc.: 57.81%] [G loss: 0.741545]
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6524 [D loss: 0.675879, acc.: 58.40%] [G loss: 0.739515]
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6525 [D loss: 0.675170, acc.: 60.94%] [G loss: 0.735549]
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6526 [D loss: 0.683130, acc.: 56.05%] [G loss: 0.726356]
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6527 [D loss: 0.680015, acc.: 55.86%] [G loss: 0.731664]
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6528 [D loss: 0.683794, acc.: 55.66%] [G loss: 0.728152]
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6529 [D loss: 0.682528, acc.: 56.25%] [G loss: 0.724668]
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6530 [D loss: 0.685068, acc.: 52.15%] [G loss: 0.715941]
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6531 [D loss: 0.689560, acc.: 54.49%] [G loss: 0.732778]
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6532 [D loss: 0.683043, acc.: 57.81%] [G loss: 0.738851]
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6533 [D loss: 0.682494, acc.: 53.71%] [G loss: 0.752349]
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6534 [D loss: 0.679184, acc.: 54.49%] [G loss: 0.743115]
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6535 [D loss: 0.678864, acc.: 60.16%] [G loss: 0.735070]
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6536 [D loss: 0.681038, acc.: 54.69%] [G loss: 0.739303]
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6537 [D loss: 0.686288, acc.: 55.08%] [G loss: 0.735685]
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6538 [D loss: 0.684891, acc.: 56.84%] [G loss: 0.742873]
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6539 [D loss: 0.679272, acc.: 57.42%] [G loss: 0.731880]
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6540 [D loss: 0.687230, acc.: 55.47%] [G loss: 0.728737]
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6541 [D loss: 0.679731, acc.: 55.66%] [G loss: 0.737465]
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6542 [D loss: 0.679684, acc.: 57.81%] [G loss: 0.731394]
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6543 [D loss: 0.687130, acc.: 54.69%] [G loss: 0.749192]
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6544 [D loss: 0.688855, acc.: 56.45%] [G loss: 0.731135]
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6545 [D loss: 0.691087, acc.: 52.54%] [G loss: 0.723033]
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6546 [D loss: 0.683952, acc.: 54.49%] [G loss: 0.744152]
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6547 [D loss: 0.687216, acc.: 52.93%] [G loss: 0.726699]
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6548 [D loss: 0.685286, acc.: 55.08%] [G loss: 0.731798]
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6549 [D loss: 0.689990, acc.: 53.91%] [G loss: 0.732778]
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6550 [D loss: 0.673805, acc.: 59.38%] [G loss: 0.748129]
1/1 [==============================] - 0s 16ms/step
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6551 [D loss: 0.678409, acc.: 57.03%] [G loss: 0.736894]
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6552 [D loss: 0.680295, acc.: 55.66%] [G loss: 0.729928]
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6553 [D loss: 0.682131, acc.: 55.27%] [G loss: 0.750076]
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6554 [D loss: 0.679837, acc.: 55.86%] [G loss: 0.738133]
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6555 [D loss: 0.679986, acc.: 57.23%] [G loss: 0.741003]
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6556 [D loss: 0.687938, acc.: 53.91%] [G loss: 0.739332]
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6557 [D loss: 0.673357, acc.: 58.20%] [G loss: 0.745182]
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6558 [D loss: 0.677670, acc.: 56.45%] [G loss: 0.737899]
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6559 [D loss: 0.680840, acc.: 56.84%] [G loss: 0.753828]
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6560 [D loss: 0.682832, acc.: 57.81%] [G loss: 0.730639]
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6561 [D loss: 0.683879, acc.: 56.25%] [G loss: 0.722515]
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6562 [D loss: 0.680907, acc.: 55.47%] [G loss: 0.736254]
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6563 [D loss: 0.682502, acc.: 56.05%] [G loss: 0.729664]
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6564 [D loss: 0.687092, acc.: 53.91%] [G loss: 0.718337]
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6565 [D loss: 0.675540, acc.: 58.20%] [G loss: 0.731769]
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6566 [D loss: 0.700092, acc.: 50.39%] [G loss: 0.744455]
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6567 [D loss: 0.682628, acc.: 55.66%] [G loss: 0.750281]
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6568 [D loss: 0.679032, acc.: 58.40%] [G loss: 0.731593]
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6569 [D loss: 0.684341, acc.: 55.27%] [G loss: 0.751958]
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6570 [D loss: 0.674118, acc.: 58.01%] [G loss: 0.745384]
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6571 [D loss: 0.684892, acc.: 54.30%] [G loss: 0.741237]
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6572 [D loss: 0.683147, acc.: 55.86%] [G loss: 0.740816]
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6573 [D loss: 0.673783, acc.: 60.55%] [G loss: 0.740537]
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6574 [D loss: 0.680266, acc.: 55.08%] [G loss: 0.743292]
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6575 [D loss: 0.682915, acc.: 56.25%] [G loss: 0.738333]
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6576 [D loss: 0.672637, acc.: 57.62%] [G loss: 0.728211]
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6577 [D loss: 0.686780, acc.: 54.30%] [G loss: 0.736541]
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6578 [D loss: 0.684078, acc.: 55.47%] [G loss: 0.736204]
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6579 [D loss: 0.677319, acc.: 55.27%] [G loss: 0.739004]
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6580 [D loss: 0.693701, acc.: 49.80%] [G loss: 0.711886]
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6581 [D loss: 0.674140, acc.: 57.81%] [G loss: 0.734976]
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6582 [D loss: 0.677841, acc.: 57.23%] [G loss: 0.743414]
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6583 [D loss: 0.678606, acc.: 56.25%] [G loss: 0.738169]
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6584 [D loss: 0.688626, acc.: 53.91%] [G loss: 0.730650]
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6585 [D loss: 0.681791, acc.: 58.40%] [G loss: 0.734227]
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6586 [D loss: 0.689516, acc.: 54.88%] [G loss: 0.733669]
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6587 [D loss: 0.687650, acc.: 53.12%] [G loss: 0.738988]
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6588 [D loss: 0.672020, acc.: 60.55%] [G loss: 0.746250]
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6589 [D loss: 0.678004, acc.: 58.01%] [G loss: 0.729299]
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6590 [D loss: 0.676347, acc.: 58.98%] [G loss: 0.734861]
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6591 [D loss: 0.673393, acc.: 57.81%] [G loss: 0.729923]
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6592 [D loss: 0.683746, acc.: 56.64%] [G loss: 0.729645]
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6593 [D loss: 0.677986, acc.: 55.66%] [G loss: 0.713015]
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6594 [D loss: 0.684030, acc.: 57.62%] [G loss: 0.729459]
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6595 [D loss: 0.682953, acc.: 59.18%] [G loss: 0.733263]
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6596 [D loss: 0.676279, acc.: 59.96%] [G loss: 0.728567]
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6597 [D loss: 0.684297, acc.: 54.49%] [G loss: 0.749580]
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6598 [D loss: 0.680804, acc.: 55.86%] [G loss: 0.752388]
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6599 [D loss: 0.687560, acc.: 54.88%] [G loss: 0.748089]
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6600 [D loss: 0.695396, acc.: 50.59%] [G loss: 0.742145]
1/1 [==============================] - 0s 18ms/step
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6601 [D loss: 0.703151, acc.: 47.66%] [G loss: 0.719446]
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6602 [D loss: 0.686265, acc.: 53.91%] [G loss: 0.730639]
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6603 [D loss: 0.694279, acc.: 54.69%] [G loss: 0.743672]
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6604 [D loss: 0.679020, acc.: 57.03%] [G loss: 0.722633]
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6605 [D loss: 0.687016, acc.: 54.10%] [G loss: 0.745595]
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6606 [D loss: 0.673794, acc.: 60.74%] [G loss: 0.747639]
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6607 [D loss: 0.681268, acc.: 58.79%] [G loss: 0.727474]
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6608 [D loss: 0.667257, acc.: 60.16%] [G loss: 0.729661]
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6609 [D loss: 0.685935, acc.: 54.30%] [G loss: 0.735085]
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6610 [D loss: 0.688396, acc.: 55.08%] [G loss: 0.744312]
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6611 [D loss: 0.680365, acc.: 58.59%] [G loss: 0.746850]
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6612 [D loss: 0.680555, acc.: 56.45%] [G loss: 0.732523]
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6613 [D loss: 0.679810, acc.: 55.86%] [G loss: 0.740128]
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6614 [D loss: 0.676662, acc.: 56.84%] [G loss: 0.743329]
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6615 [D loss: 0.691883, acc.: 52.54%] [G loss: 0.736732]
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6616 [D loss: 0.680718, acc.: 54.49%] [G loss: 0.743553]
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6617 [D loss: 0.680364, acc.: 58.01%] [G loss: 0.734176]
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6618 [D loss: 0.682666, acc.: 55.08%] [G loss: 0.743345]
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6619 [D loss: 0.676615, acc.: 60.55%] [G loss: 0.738631]
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6620 [D loss: 0.677448, acc.: 58.01%] [G loss: 0.732923]
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6621 [D loss: 0.683349, acc.: 55.86%] [G loss: 0.737585]
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6622 [D loss: 0.688687, acc.: 52.93%] [G loss: 0.732146]
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6623 [D loss: 0.680972, acc.: 55.27%] [G loss: 0.723185]
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6624 [D loss: 0.687138, acc.: 54.30%] [G loss: 0.713115]
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6625 [D loss: 0.699266, acc.: 51.56%] [G loss: 0.729884]
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6626 [D loss: 0.685136, acc.: 54.30%] [G loss: 0.734303]
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6627 [D loss: 0.675132, acc.: 58.98%] [G loss: 0.742955]
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6628 [D loss: 0.674391, acc.: 59.38%] [G loss: 0.739843]
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6629 [D loss: 0.689165, acc.: 53.91%] [G loss: 0.742386]
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6630 [D loss: 0.673279, acc.: 58.59%] [G loss: 0.737758]
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6631 [D loss: 0.685260, acc.: 55.86%] [G loss: 0.745587]
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6632 [D loss: 0.686101, acc.: 55.47%] [G loss: 0.748847]
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6633 [D loss: 0.692401, acc.: 51.37%] [G loss: 0.739860]
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6634 [D loss: 0.671522, acc.: 60.74%] [G loss: 0.747199]
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6635 [D loss: 0.675442, acc.: 58.20%] [G loss: 0.760854]
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6636 [D loss: 0.673000, acc.: 61.91%] [G loss: 0.745697]
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6637 [D loss: 0.678342, acc.: 55.47%] [G loss: 0.749213]
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6638 [D loss: 0.685846, acc.: 56.84%] [G loss: 0.729116]
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6639 [D loss: 0.686920, acc.: 52.54%] [G loss: 0.731823]
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6640 [D loss: 0.688738, acc.: 53.91%] [G loss: 0.722118]
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6641 [D loss: 0.692328, acc.: 51.37%] [G loss: 0.734450]
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6642 [D loss: 0.685638, acc.: 53.52%] [G loss: 0.715985]
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6643 [D loss: 0.690323, acc.: 50.39%] [G loss: 0.735641]
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6644 [D loss: 0.675508, acc.: 56.45%] [G loss: 0.747957]
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6645 [D loss: 0.672490, acc.: 59.57%] [G loss: 0.745708]
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6646 [D loss: 0.673276, acc.: 60.74%] [G loss: 0.740931]
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6647 [D loss: 0.681946, acc.: 56.45%] [G loss: 0.733858]
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6648 [D loss: 0.690203, acc.: 51.56%] [G loss: 0.720568]
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6649 [D loss: 0.677107, acc.: 56.25%] [G loss: 0.737416]
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6650 [D loss: 0.694031, acc.: 51.56%] [G loss: 0.721193]
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6651 [D loss: 0.688720, acc.: 52.73%] [G loss: 0.720616]
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6652 [D loss: 0.678823, acc.: 59.38%] [G loss: 0.736089]
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6653 [D loss: 0.674442, acc.: 59.18%] [G loss: 0.734153]
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6654 [D loss: 0.671715, acc.: 59.18%] [G loss: 0.731901]
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6655 [D loss: 0.677131, acc.: 58.01%] [G loss: 0.747733]
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6656 [D loss: 0.673757, acc.: 59.57%] [G loss: 0.731150]
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6657 [D loss: 0.684286, acc.: 55.08%] [G loss: 0.726097]
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6658 [D loss: 0.699340, acc.: 50.00%] [G loss: 0.725079]
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6659 [D loss: 0.679169, acc.: 57.03%] [G loss: 0.728643]
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6660 [D loss: 0.679614, acc.: 58.59%] [G loss: 0.721158]
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6661 [D loss: 0.679069, acc.: 58.40%] [G loss: 0.735609]
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6662 [D loss: 0.683680, acc.: 56.64%] [G loss: 0.743627]
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6663 [D loss: 0.679341, acc.: 57.23%] [G loss: 0.751384]
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6664 [D loss: 0.684752, acc.: 55.86%] [G loss: 0.729775]
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6665 [D loss: 0.681639, acc.: 58.79%] [G loss: 0.733395]
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6666 [D loss: 0.689133, acc.: 52.54%] [G loss: 0.739475]
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6667 [D loss: 0.686166, acc.: 53.12%] [G loss: 0.741159]
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6668 [D loss: 0.684876, acc.: 54.30%] [G loss: 0.732585]
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6669 [D loss: 0.675975, acc.: 56.45%] [G loss: 0.740151]
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6670 [D loss: 0.675581, acc.: 59.77%] [G loss: 0.745396]
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6671 [D loss: 0.687030, acc.: 55.66%] [G loss: 0.753683]
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6672 [D loss: 0.672999, acc.: 57.42%] [G loss: 0.741290]
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6673 [D loss: 0.674588, acc.: 58.79%] [G loss: 0.723972]
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6674 [D loss: 0.682496, acc.: 56.25%] [G loss: 0.738559]
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6675 [D loss: 0.695436, acc.: 52.93%] [G loss: 0.730053]
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6676 [D loss: 0.685133, acc.: 56.25%] [G loss: 0.736187]
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6677 [D loss: 0.686828, acc.: 56.05%] [G loss: 0.743178]
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6678 [D loss: 0.681973, acc.: 56.25%] [G loss: 0.746635]
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6679 [D loss: 0.686220, acc.: 56.25%] [G loss: 0.729025]
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6680 [D loss: 0.683420, acc.: 57.03%] [G loss: 0.745729]
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6681 [D loss: 0.686104, acc.: 59.18%] [G loss: 0.745119]
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6682 [D loss: 0.686969, acc.: 52.34%] [G loss: 0.739446]
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6683 [D loss: 0.687919, acc.: 55.08%] [G loss: 0.743612]
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6684 [D loss: 0.682641, acc.: 57.42%] [G loss: 0.745584]
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6685 [D loss: 0.677572, acc.: 59.38%] [G loss: 0.759844]
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6686 [D loss: 0.680248, acc.: 58.98%] [G loss: 0.751157]
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6687 [D loss: 0.667889, acc.: 61.52%] [G loss: 0.744938]
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6688 [D loss: 0.678521, acc.: 55.86%] [G loss: 0.744820]
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6689 [D loss: 0.683873, acc.: 54.69%] [G loss: 0.717660]
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6690 [D loss: 0.670962, acc.: 60.55%] [G loss: 0.738054]
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6691 [D loss: 0.684102, acc.: 52.34%] [G loss: 0.728389]
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6692 [D loss: 0.678116, acc.: 56.05%] [G loss: 0.723151]
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6693 [D loss: 0.690506, acc.: 52.15%] [G loss: 0.724159]
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6694 [D loss: 0.673159, acc.: 57.81%] [G loss: 0.749066]
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6695 [D loss: 0.681259, acc.: 57.23%] [G loss: 0.742518]
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6696 [D loss: 0.667660, acc.: 61.91%] [G loss: 0.741872]
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6697 [D loss: 0.677095, acc.: 57.42%] [G loss: 0.738115]
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6698 [D loss: 0.688063, acc.: 53.91%] [G loss: 0.736295]
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6699 [D loss: 0.679295, acc.: 58.01%] [G loss: 0.731714]
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6700 [D loss: 0.689290, acc.: 54.49%] [G loss: 0.741284]
1/1 [==============================] - 0s 17ms/step
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6701 [D loss: 0.682792, acc.: 55.66%] [G loss: 0.733013]
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6702 [D loss: 0.677991, acc.: 59.38%] [G loss: 0.742873]
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6703 [D loss: 0.682032, acc.: 58.01%] [G loss: 0.746453]
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6704 [D loss: 0.684569, acc.: 58.01%] [G loss: 0.755095]
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6705 [D loss: 0.679471, acc.: 58.40%] [G loss: 0.743527]
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6706 [D loss: 0.684610, acc.: 55.08%] [G loss: 0.716313]
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6707 [D loss: 0.687660, acc.: 50.78%] [G loss: 0.726139]
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6708 [D loss: 0.687523, acc.: 53.32%] [G loss: 0.733274]
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6709 [D loss: 0.679239, acc.: 57.62%] [G loss: 0.739429]
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6710 [D loss: 0.680948, acc.: 57.03%] [G loss: 0.737400]
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6711 [D loss: 0.679165, acc.: 57.23%] [G loss: 0.741326]
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6712 [D loss: 0.675734, acc.: 58.20%] [G loss: 0.744861]
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6713 [D loss: 0.689191, acc.: 50.98%] [G loss: 0.748526]
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6714 [D loss: 0.679859, acc.: 57.81%] [G loss: 0.734265]
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6715 [D loss: 0.685427, acc.: 54.69%] [G loss: 0.736635]
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6716 [D loss: 0.684600, acc.: 55.47%] [G loss: 0.747665]
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6717 [D loss: 0.686535, acc.: 53.52%] [G loss: 0.746818]
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6718 [D loss: 0.678755, acc.: 57.42%] [G loss: 0.743078]
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6719 [D loss: 0.687115, acc.: 52.54%] [G loss: 0.745001]
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6720 [D loss: 0.675946, acc.: 57.42%] [G loss: 0.737090]
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6721 [D loss: 0.674530, acc.: 58.98%] [G loss: 0.740350]
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6722 [D loss: 0.675123, acc.: 57.23%] [G loss: 0.726796]
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6723 [D loss: 0.682928, acc.: 55.47%] [G loss: 0.726101]
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6724 [D loss: 0.682570, acc.: 54.88%] [G loss: 0.717128]
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6725 [D loss: 0.689261, acc.: 54.10%] [G loss: 0.723962]
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6726 [D loss: 0.685425, acc.: 56.05%] [G loss: 0.735270]
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6727 [D loss: 0.686696, acc.: 51.56%] [G loss: 0.732657]
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6728 [D loss: 0.674567, acc.: 58.79%] [G loss: 0.729214]
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6729 [D loss: 0.678514, acc.: 57.03%] [G loss: 0.733684]
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6730 [D loss: 0.682972, acc.: 54.88%] [G loss: 0.722770]
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6731 [D loss: 0.687814, acc.: 52.73%] [G loss: 0.725413]
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6732 [D loss: 0.686202, acc.: 51.56%] [G loss: 0.740461]
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6733 [D loss: 0.679478, acc.: 59.18%] [G loss: 0.751864]
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6734 [D loss: 0.683664, acc.: 54.49%] [G loss: 0.752902]
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6735 [D loss: 0.681914, acc.: 56.84%] [G loss: 0.739370]
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6736 [D loss: 0.672137, acc.: 61.72%] [G loss: 0.755033]
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6737 [D loss: 0.678945, acc.: 57.03%] [G loss: 0.753120]
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6738 [D loss: 0.671205, acc.: 59.77%] [G loss: 0.742162]
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6739 [D loss: 0.689519, acc.: 53.52%] [G loss: 0.714187]
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6740 [D loss: 0.690952, acc.: 55.86%] [G loss: 0.710837]
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6741 [D loss: 0.690020, acc.: 53.52%] [G loss: 0.729043]
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6742 [D loss: 0.679588, acc.: 58.01%] [G loss: 0.724261]
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6743 [D loss: 0.679146, acc.: 53.91%] [G loss: 0.730509]
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6744 [D loss: 0.674762, acc.: 54.49%] [G loss: 0.728461]
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6745 [D loss: 0.682166, acc.: 56.05%] [G loss: 0.728014]
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6746 [D loss: 0.682997, acc.: 55.86%] [G loss: 0.725999]
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6747 [D loss: 0.684237, acc.: 54.69%] [G loss: 0.731849]
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6748 [D loss: 0.687398, acc.: 53.12%] [G loss: 0.723956]
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6749 [D loss: 0.686118, acc.: 56.64%] [G loss: 0.742229]
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6750 [D loss: 0.675189, acc.: 59.38%] [G loss: 0.750580]
1/1 [==============================] - 0s 18ms/step
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6751 [D loss: 0.671493, acc.: 58.98%] [G loss: 0.750475]
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6752 [D loss: 0.675042, acc.: 58.40%] [G loss: 0.757138]
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6753 [D loss: 0.674314, acc.: 58.59%] [G loss: 0.734484]
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6754 [D loss: 0.686347, acc.: 53.71%] [G loss: 0.728293]
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6755 [D loss: 0.693612, acc.: 53.52%] [G loss: 0.729870]
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6756 [D loss: 0.682759, acc.: 55.47%] [G loss: 0.716552]
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6757 [D loss: 0.685496, acc.: 57.62%] [G loss: 0.721973]
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6758 [D loss: 0.679592, acc.: 58.01%] [G loss: 0.723985]
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6759 [D loss: 0.680947, acc.: 58.59%] [G loss: 0.730510]
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6760 [D loss: 0.676799, acc.: 56.84%] [G loss: 0.731327]
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6761 [D loss: 0.675639, acc.: 58.20%] [G loss: 0.730965]
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6762 [D loss: 0.669835, acc.: 58.79%] [G loss: 0.728934]
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6763 [D loss: 0.683241, acc.: 55.86%] [G loss: 0.727238]
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6764 [D loss: 0.690931, acc.: 51.95%] [G loss: 0.720725]
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6765 [D loss: 0.685958, acc.: 53.32%] [G loss: 0.720650]
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6766 [D loss: 0.677464, acc.: 59.57%] [G loss: 0.724900]
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6767 [D loss: 0.689445, acc.: 52.73%] [G loss: 0.734405]
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6768 [D loss: 0.680890, acc.: 56.45%] [G loss: 0.751998]
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6769 [D loss: 0.682221, acc.: 55.86%] [G loss: 0.747125]
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6770 [D loss: 0.678136, acc.: 58.79%] [G loss: 0.759496]
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6771 [D loss: 0.660903, acc.: 61.13%] [G loss: 0.750706]
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6772 [D loss: 0.684259, acc.: 53.32%] [G loss: 0.735243]
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6773 [D loss: 0.679025, acc.: 58.40%] [G loss: 0.729606]
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6774 [D loss: 0.688969, acc.: 52.93%] [G loss: 0.744118]
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6775 [D loss: 0.682402, acc.: 56.25%] [G loss: 0.737291]
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6776 [D loss: 0.679158, acc.: 57.03%] [G loss: 0.747266]
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6777 [D loss: 0.676388, acc.: 58.40%] [G loss: 0.732069]
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6778 [D loss: 0.678046, acc.: 60.55%] [G loss: 0.744485]
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6779 [D loss: 0.673854, acc.: 57.03%] [G loss: 0.737519]
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6780 [D loss: 0.686944, acc.: 53.91%] [G loss: 0.744640]
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6781 [D loss: 0.686201, acc.: 57.23%] [G loss: 0.723774]
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6782 [D loss: 0.688903, acc.: 53.12%] [G loss: 0.719176]
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6783 [D loss: 0.686153, acc.: 53.32%] [G loss: 0.731331]
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6784 [D loss: 0.688570, acc.: 53.91%] [G loss: 0.746283]
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6785 [D loss: 0.687054, acc.: 52.93%] [G loss: 0.748426]
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6786 [D loss: 0.676427, acc.: 58.01%] [G loss: 0.747600]
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6787 [D loss: 0.689845, acc.: 53.71%] [G loss: 0.741476]
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6788 [D loss: 0.692427, acc.: 53.12%] [G loss: 0.739072]
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6789 [D loss: 0.688664, acc.: 56.84%] [G loss: 0.736332]
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6790 [D loss: 0.685343, acc.: 55.08%] [G loss: 0.743768]
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6791 [D loss: 0.679123, acc.: 53.71%] [G loss: 0.742431]
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6792 [D loss: 0.677017, acc.: 57.23%] [G loss: 0.735774]
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6793 [D loss: 0.674557, acc.: 58.98%] [G loss: 0.738623]
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6794 [D loss: 0.674513, acc.: 60.16%] [G loss: 0.733821]
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6795 [D loss: 0.684174, acc.: 53.71%] [G loss: 0.747473]
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6796 [D loss: 0.673077, acc.: 58.20%] [G loss: 0.733150]
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6797 [D loss: 0.681900, acc.: 55.08%] [G loss: 0.732059]
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6798 [D loss: 0.678865, acc.: 56.05%] [G loss: 0.734571]
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6799 [D loss: 0.681030, acc.: 56.25%] [G loss: 0.738962]
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6800 [D loss: 0.680454, acc.: 58.20%] [G loss: 0.745343]
1/1 [==============================] - 0s 20ms/step
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6801 [D loss: 0.689726, acc.: 55.08%] [G loss: 0.740423]
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6802 [D loss: 0.682511, acc.: 56.05%] [G loss: 0.736410]
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6803 [D loss: 0.682109, acc.: 55.66%] [G loss: 0.722964]
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6804 [D loss: 0.680887, acc.: 57.81%] [G loss: 0.741656]
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6805 [D loss: 0.676829, acc.: 57.03%] [G loss: 0.737160]
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6806 [D loss: 0.690118, acc.: 53.71%] [G loss: 0.727359]
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6807 [D loss: 0.688498, acc.: 53.71%] [G loss: 0.742404]
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6808 [D loss: 0.675740, acc.: 59.38%] [G loss: 0.742285]
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6809 [D loss: 0.674940, acc.: 59.77%] [G loss: 0.748350]
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6810 [D loss: 0.684428, acc.: 56.84%] [G loss: 0.738735]
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6811 [D loss: 0.675974, acc.: 57.81%] [G loss: 0.730686]
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6812 [D loss: 0.681000, acc.: 55.66%] [G loss: 0.737625]
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6813 [D loss: 0.689179, acc.: 53.91%] [G loss: 0.735420]
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6814 [D loss: 0.683816, acc.: 54.30%] [G loss: 0.737506]
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6815 [D loss: 0.691668, acc.: 53.32%] [G loss: 0.747150]
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6816 [D loss: 0.688211, acc.: 55.47%] [G loss: 0.731577]
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6817 [D loss: 0.675964, acc.: 60.16%] [G loss: 0.738116]
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6818 [D loss: 0.683619, acc.: 55.86%] [G loss: 0.744220]
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6819 [D loss: 0.676017, acc.: 57.81%] [G loss: 0.739417]
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6820 [D loss: 0.673437, acc.: 56.84%] [G loss: 0.736397]
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6821 [D loss: 0.678076, acc.: 57.23%] [G loss: 0.723037]
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6822 [D loss: 0.683065, acc.: 58.59%] [G loss: 0.727992]
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6823 [D loss: 0.676893, acc.: 56.84%] [G loss: 0.727304]
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6824 [D loss: 0.673457, acc.: 60.94%] [G loss: 0.735601]
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6825 [D loss: 0.680774, acc.: 60.16%] [G loss: 0.743841]
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6826 [D loss: 0.677886, acc.: 58.20%] [G loss: 0.746910]
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6827 [D loss: 0.690761, acc.: 53.32%] [G loss: 0.742940]
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6828 [D loss: 0.685343, acc.: 56.25%] [G loss: 0.742744]
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6829 [D loss: 0.683636, acc.: 57.03%] [G loss: 0.740534]
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6830 [D loss: 0.681455, acc.: 57.42%] [G loss: 0.741870]
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6831 [D loss: 0.682181, acc.: 54.10%] [G loss: 0.742549]
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6832 [D loss: 0.684920, acc.: 54.10%] [G loss: 0.721289]
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6833 [D loss: 0.684310, acc.: 55.27%] [G loss: 0.747708]
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6834 [D loss: 0.682793, acc.: 54.69%] [G loss: 0.742031]
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6835 [D loss: 0.676669, acc.: 57.23%] [G loss: 0.729623]
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6836 [D loss: 0.688404, acc.: 55.47%] [G loss: 0.742705]
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6837 [D loss: 0.689003, acc.: 53.32%] [G loss: 0.731946]
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6838 [D loss: 0.685642, acc.: 55.86%] [G loss: 0.743784]
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6839 [D loss: 0.676816, acc.: 57.81%] [G loss: 0.741381]
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6840 [D loss: 0.679241, acc.: 56.84%] [G loss: 0.737137]
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6841 [D loss: 0.679411, acc.: 58.20%] [G loss: 0.753028]
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6842 [D loss: 0.681619, acc.: 56.05%] [G loss: 0.732060]
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6843 [D loss: 0.671121, acc.: 61.33%] [G loss: 0.734375]
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6844 [D loss: 0.682915, acc.: 56.45%] [G loss: 0.725214]
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6845 [D loss: 0.675495, acc.: 59.57%] [G loss: 0.738335]
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6846 [D loss: 0.679696, acc.: 55.47%] [G loss: 0.729757]
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6847 [D loss: 0.676456, acc.: 60.35%] [G loss: 0.720368]
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6848 [D loss: 0.680052, acc.: 53.52%] [G loss: 0.743072]
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6849 [D loss: 0.699165, acc.: 49.80%] [G loss: 0.726969]
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6850 [D loss: 0.684088, acc.: 54.69%] [G loss: 0.723053]
1/1 [==============================] - 0s 17ms/step
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6851 [D loss: 0.677240, acc.: 56.25%] [G loss: 0.743702]
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6852 [D loss: 0.673536, acc.: 57.81%] [G loss: 0.731536]
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6853 [D loss: 0.682484, acc.: 54.10%] [G loss: 0.735428]
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6854 [D loss: 0.687434, acc.: 52.93%] [G loss: 0.733033]
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6855 [D loss: 0.678087, acc.: 55.66%] [G loss: 0.743201]
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6856 [D loss: 0.686723, acc.: 53.71%] [G loss: 0.734385]
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6857 [D loss: 0.672066, acc.: 60.55%] [G loss: 0.764658]
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6858 [D loss: 0.675103, acc.: 58.20%] [G loss: 0.764098]
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6859 [D loss: 0.684670, acc.: 54.49%] [G loss: 0.737937]
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6860 [D loss: 0.682302, acc.: 54.49%] [G loss: 0.731839]
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6861 [D loss: 0.679061, acc.: 56.05%] [G loss: 0.739627]
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6862 [D loss: 0.681400, acc.: 54.88%] [G loss: 0.734551]
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6863 [D loss: 0.687377, acc.: 54.69%] [G loss: 0.724408]
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6864 [D loss: 0.682544, acc.: 55.47%] [G loss: 0.743030]
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6865 [D loss: 0.681169, acc.: 55.47%] [G loss: 0.735414]
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6866 [D loss: 0.691502, acc.: 52.34%] [G loss: 0.744108]
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6867 [D loss: 0.674460, acc.: 56.25%] [G loss: 0.724488]
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6868 [D loss: 0.685757, acc.: 51.95%] [G loss: 0.740110]
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6869 [D loss: 0.680730, acc.: 61.72%] [G loss: 0.721033]
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6870 [D loss: 0.683702, acc.: 56.25%] [G loss: 0.731191]
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6871 [D loss: 0.682282, acc.: 56.45%] [G loss: 0.725391]
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6872 [D loss: 0.685540, acc.: 54.30%] [G loss: 0.730220]
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6873 [D loss: 0.676646, acc.: 58.79%] [G loss: 0.731006]
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6874 [D loss: 0.682244, acc.: 58.20%] [G loss: 0.724340]
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6875 [D loss: 0.683459, acc.: 57.62%] [G loss: 0.720464]
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6876 [D loss: 0.695325, acc.: 53.52%] [G loss: 0.751475]
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6877 [D loss: 0.685438, acc.: 55.27%] [G loss: 0.736323]
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6878 [D loss: 0.669669, acc.: 60.16%] [G loss: 0.740274]
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6879 [D loss: 0.678938, acc.: 56.64%] [G loss: 0.734101]
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6880 [D loss: 0.680292, acc.: 57.03%] [G loss: 0.735820]
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6881 [D loss: 0.675368, acc.: 57.81%] [G loss: 0.736413]
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6882 [D loss: 0.681384, acc.: 56.05%] [G loss: 0.726507]
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6883 [D loss: 0.691492, acc.: 50.78%] [G loss: 0.740209]
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6884 [D loss: 0.684996, acc.: 52.93%] [G loss: 0.733805]
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6885 [D loss: 0.686899, acc.: 54.10%] [G loss: 0.733751]
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6886 [D loss: 0.678375, acc.: 61.91%] [G loss: 0.745260]
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6887 [D loss: 0.684969, acc.: 56.25%] [G loss: 0.740596]
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6888 [D loss: 0.676633, acc.: 60.16%] [G loss: 0.748318]
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6889 [D loss: 0.670764, acc.: 58.79%] [G loss: 0.738249]
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6890 [D loss: 0.684951, acc.: 54.88%] [G loss: 0.734818]
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6891 [D loss: 0.674726, acc.: 57.42%] [G loss: 0.728657]
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6892 [D loss: 0.681822, acc.: 54.49%] [G loss: 0.740223]
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6893 [D loss: 0.688710, acc.: 52.93%] [G loss: 0.734783]
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6894 [D loss: 0.684146, acc.: 51.76%] [G loss: 0.742974]
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6895 [D loss: 0.691627, acc.: 51.56%] [G loss: 0.737489]
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6896 [D loss: 0.672633, acc.: 61.52%] [G loss: 0.736151]
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6897 [D loss: 0.675356, acc.: 57.62%] [G loss: 0.733607]
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6898 [D loss: 0.676070, acc.: 54.49%] [G loss: 0.732470]
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6899 [D loss: 0.679824, acc.: 54.88%] [G loss: 0.724070]
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6900 [D loss: 0.685091, acc.: 55.86%] [G loss: 0.737246]
1/1 [==============================] - 0s 24ms/step
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6901 [D loss: 0.678458, acc.: 60.55%] [G loss: 0.724846]
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6902 [D loss: 0.688397, acc.: 54.88%] [G loss: 0.739309]
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6903 [D loss: 0.686200, acc.: 55.47%] [G loss: 0.741427]
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6904 [D loss: 0.682105, acc.: 56.64%] [G loss: 0.745874]
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6905 [D loss: 0.681361, acc.: 57.03%] [G loss: 0.737471]
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6906 [D loss: 0.681562, acc.: 55.86%] [G loss: 0.742837]
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6907 [D loss: 0.686154, acc.: 56.45%] [G loss: 0.729618]
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6908 [D loss: 0.682379, acc.: 55.27%] [G loss: 0.725464]
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6909 [D loss: 0.685469, acc.: 54.88%] [G loss: 0.740376]
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6910 [D loss: 0.674870, acc.: 58.79%] [G loss: 0.728701]
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6911 [D loss: 0.679028, acc.: 59.96%] [G loss: 0.741922]
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6912 [D loss: 0.681551, acc.: 54.69%] [G loss: 0.735942]
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6913 [D loss: 0.672623, acc.: 59.77%] [G loss: 0.736932]
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6914 [D loss: 0.681359, acc.: 55.47%] [G loss: 0.747444]
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6915 [D loss: 0.682976, acc.: 57.03%] [G loss: 0.738424]
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6916 [D loss: 0.689136, acc.: 55.27%] [G loss: 0.742957]
8/8 [==============================] - 0s 4ms/step
6917 [D loss: 0.692513, acc.: 51.56%] [G loss: 0.730545]
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6918 [D loss: 0.682839, acc.: 56.64%] [G loss: 0.736701]
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6919 [D loss: 0.677666, acc.: 54.69%] [G loss: 0.739013]
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6920 [D loss: 0.673965, acc.: 57.81%] [G loss: 0.746177]
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6921 [D loss: 0.685846, acc.: 54.49%] [G loss: 0.741602]
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6922 [D loss: 0.674342, acc.: 57.03%] [G loss: 0.724473]
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6923 [D loss: 0.683162, acc.: 54.49%] [G loss: 0.740374]
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6924 [D loss: 0.691709, acc.: 52.15%] [G loss: 0.733741]
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6925 [D loss: 0.685209, acc.: 56.05%] [G loss: 0.741559]
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6926 [D loss: 0.678489, acc.: 59.38%] [G loss: 0.752161]
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6927 [D loss: 0.683695, acc.: 56.05%] [G loss: 0.751687]
8/8 [==============================] - 0s 4ms/step
6928 [D loss: 0.679812, acc.: 58.40%] [G loss: 0.742240]
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6929 [D loss: 0.679811, acc.: 56.45%] [G loss: 0.755377]
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6930 [D loss: 0.677441, acc.: 54.69%] [G loss: 0.734275]
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6931 [D loss: 0.678149, acc.: 54.69%] [G loss: 0.733750]
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6932 [D loss: 0.681070, acc.: 55.66%] [G loss: 0.750568]
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6933 [D loss: 0.683317, acc.: 58.01%] [G loss: 0.738626]
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6934 [D loss: 0.679243, acc.: 56.45%] [G loss: 0.736855]
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6935 [D loss: 0.682264, acc.: 54.30%] [G loss: 0.740224]
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6936 [D loss: 0.677877, acc.: 58.59%] [G loss: 0.733854]
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6937 [D loss: 0.680944, acc.: 56.84%] [G loss: 0.724121]
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6938 [D loss: 0.682824, acc.: 55.86%] [G loss: 0.726208]
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6939 [D loss: 0.684861, acc.: 53.52%] [G loss: 0.718900]
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6940 [D loss: 0.673838, acc.: 58.20%] [G loss: 0.739040]
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6941 [D loss: 0.675615, acc.: 58.20%] [G loss: 0.740960]
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6942 [D loss: 0.682746, acc.: 57.23%] [G loss: 0.732122]
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6943 [D loss: 0.685688, acc.: 50.98%] [G loss: 0.740292]
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6944 [D loss: 0.672452, acc.: 58.79%] [G loss: 0.737774]
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6945 [D loss: 0.688820, acc.: 51.17%] [G loss: 0.730863]
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6946 [D loss: 0.683900, acc.: 54.10%] [G loss: 0.715223]
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6947 [D loss: 0.676185, acc.: 60.55%] [G loss: 0.720804]
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6948 [D loss: 0.683288, acc.: 55.66%] [G loss: 0.739420]
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6949 [D loss: 0.681733, acc.: 54.49%] [G loss: 0.728804]
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6950 [D loss: 0.678850, acc.: 58.20%] [G loss: 0.748169]
1/1 [==============================] - 0s 18ms/step
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6951 [D loss: 0.682167, acc.: 56.64%] [G loss: 0.733964]
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6952 [D loss: 0.672663, acc.: 58.01%] [G loss: 0.738693]
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6953 [D loss: 0.680001, acc.: 58.01%] [G loss: 0.753631]
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6954 [D loss: 0.683467, acc.: 56.45%] [G loss: 0.743660]
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6955 [D loss: 0.684239, acc.: 54.30%] [G loss: 0.732539]
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6956 [D loss: 0.683105, acc.: 56.05%] [G loss: 0.731224]
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6957 [D loss: 0.687183, acc.: 54.30%] [G loss: 0.736180]
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6958 [D loss: 0.674551, acc.: 57.23%] [G loss: 0.736624]
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6959 [D loss: 0.684691, acc.: 54.30%] [G loss: 0.741366]
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6960 [D loss: 0.681665, acc.: 55.86%] [G loss: 0.737113]
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6961 [D loss: 0.671936, acc.: 60.74%] [G loss: 0.730679]
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6962 [D loss: 0.672389, acc.: 63.09%] [G loss: 0.746890]
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6963 [D loss: 0.679195, acc.: 56.25%] [G loss: 0.715377]
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6964 [D loss: 0.686259, acc.: 52.54%] [G loss: 0.730507]
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6965 [D loss: 0.677580, acc.: 57.42%] [G loss: 0.729305]
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6966 [D loss: 0.673731, acc.: 59.18%] [G loss: 0.754951]
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6967 [D loss: 0.683173, acc.: 58.79%] [G loss: 0.739588]
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6968 [D loss: 0.679151, acc.: 57.62%] [G loss: 0.736511]
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6969 [D loss: 0.683795, acc.: 56.84%] [G loss: 0.733828]
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6970 [D loss: 0.679774, acc.: 55.08%] [G loss: 0.738254]
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6971 [D loss: 0.685714, acc.: 51.95%] [G loss: 0.740079]
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6972 [D loss: 0.680241, acc.: 58.20%] [G loss: 0.737652]
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6973 [D loss: 0.677629, acc.: 58.40%] [G loss: 0.741148]
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6974 [D loss: 0.677293, acc.: 57.42%] [G loss: 0.750669]
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6975 [D loss: 0.683532, acc.: 53.91%] [G loss: 0.748888]
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6976 [D loss: 0.671221, acc.: 61.13%] [G loss: 0.738571]
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6977 [D loss: 0.673650, acc.: 57.81%] [G loss: 0.746448]
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6978 [D loss: 0.675971, acc.: 57.62%] [G loss: 0.737886]
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6979 [D loss: 0.675479, acc.: 58.98%] [G loss: 0.743632]
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6980 [D loss: 0.686296, acc.: 59.38%] [G loss: 0.753188]
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6981 [D loss: 0.680446, acc.: 55.27%] [G loss: 0.734763]
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6982 [D loss: 0.687307, acc.: 54.69%] [G loss: 0.723786]
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6983 [D loss: 0.679790, acc.: 57.81%] [G loss: 0.729481]
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6984 [D loss: 0.678615, acc.: 57.03%] [G loss: 0.735889]
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6985 [D loss: 0.688168, acc.: 54.69%] [G loss: 0.735516]
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6986 [D loss: 0.677298, acc.: 58.20%] [G loss: 0.735348]
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6987 [D loss: 0.684046, acc.: 54.10%] [G loss: 0.731695]
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6988 [D loss: 0.694974, acc.: 50.78%] [G loss: 0.733054]
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6989 [D loss: 0.682937, acc.: 56.05%] [G loss: 0.747585]
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6990 [D loss: 0.679431, acc.: 57.62%] [G loss: 0.726548]
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6991 [D loss: 0.683389, acc.: 52.93%] [G loss: 0.740692]
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6992 [D loss: 0.679122, acc.: 56.84%] [G loss: 0.728084]
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6993 [D loss: 0.685102, acc.: 55.08%] [G loss: 0.749271]
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6994 [D loss: 0.677768, acc.: 56.64%] [G loss: 0.735454]
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6995 [D loss: 0.677993, acc.: 54.88%] [G loss: 0.756882]
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6996 [D loss: 0.685449, acc.: 55.47%] [G loss: 0.747910]
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6997 [D loss: 0.674758, acc.: 57.23%] [G loss: 0.737938]
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6998 [D loss: 0.679046, acc.: 55.86%] [G loss: 0.751715]
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6999 [D loss: 0.681584, acc.: 55.47%] [G loss: 0.735970]
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7000 [D loss: 0.683232, acc.: 57.03%] [G loss: 0.730710]
1/1 [==============================] - 0s 18ms/step
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7001 [D loss: 0.677635, acc.: 58.59%] [G loss: 0.751658]
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7002 [D loss: 0.673072, acc.: 57.62%] [G loss: 0.743235]
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7003 [D loss: 0.682073, acc.: 57.03%] [G loss: 0.738442]
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7004 [D loss: 0.682510, acc.: 55.47%] [G loss: 0.737069]
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7005 [D loss: 0.689388, acc.: 55.08%] [G loss: 0.735003]
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7006 [D loss: 0.685048, acc.: 54.69%] [G loss: 0.744423]
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7007 [D loss: 0.672546, acc.: 60.94%] [G loss: 0.734549]
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7008 [D loss: 0.683795, acc.: 55.66%] [G loss: 0.742278]
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7009 [D loss: 0.670493, acc.: 59.38%] [G loss: 0.734792]
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7010 [D loss: 0.675810, acc.: 58.40%] [G loss: 0.736702]
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7011 [D loss: 0.674170, acc.: 59.38%] [G loss: 0.727627]
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7012 [D loss: 0.681482, acc.: 53.91%] [G loss: 0.728639]
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7013 [D loss: 0.701115, acc.: 50.00%] [G loss: 0.723262]
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7014 [D loss: 0.685783, acc.: 53.12%] [G loss: 0.740300]
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7015 [D loss: 0.676582, acc.: 58.01%] [G loss: 0.745508]
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7016 [D loss: 0.688600, acc.: 53.71%] [G loss: 0.752908]
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7017 [D loss: 0.677504, acc.: 60.35%] [G loss: 0.759299]
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7018 [D loss: 0.680634, acc.: 55.27%] [G loss: 0.740543]
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7019 [D loss: 0.687269, acc.: 52.54%] [G loss: 0.743221]
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7020 [D loss: 0.681722, acc.: 55.27%] [G loss: 0.733777]
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7021 [D loss: 0.678926, acc.: 57.23%] [G loss: 0.720692]
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7022 [D loss: 0.692755, acc.: 52.93%] [G loss: 0.739461]
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7023 [D loss: 0.679422, acc.: 56.84%] [G loss: 0.727222]
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7024 [D loss: 0.679247, acc.: 57.23%] [G loss: 0.736943]
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7025 [D loss: 0.675492, acc.: 57.03%] [G loss: 0.754083]
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7026 [D loss: 0.676636, acc.: 55.47%] [G loss: 0.726544]
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7027 [D loss: 0.678373, acc.: 59.18%] [G loss: 0.741992]
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7028 [D loss: 0.680567, acc.: 55.47%] [G loss: 0.728130]
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7029 [D loss: 0.675767, acc.: 57.62%] [G loss: 0.751434]
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7030 [D loss: 0.685175, acc.: 54.69%] [G loss: 0.753702]
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7031 [D loss: 0.678930, acc.: 58.01%] [G loss: 0.732612]
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7032 [D loss: 0.666266, acc.: 62.30%] [G loss: 0.754558]
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7033 [D loss: 0.678838, acc.: 58.20%] [G loss: 0.748235]
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7034 [D loss: 0.682224, acc.: 57.03%] [G loss: 0.731108]
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7035 [D loss: 0.687388, acc.: 54.10%] [G loss: 0.740473]
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7036 [D loss: 0.683080, acc.: 54.49%] [G loss: 0.731276]
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7037 [D loss: 0.684625, acc.: 55.66%] [G loss: 0.729999]
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7038 [D loss: 0.681861, acc.: 54.88%] [G loss: 0.726873]
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7039 [D loss: 0.680002, acc.: 54.30%] [G loss: 0.751375]
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7040 [D loss: 0.680704, acc.: 56.64%] [G loss: 0.737045]
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7041 [D loss: 0.683506, acc.: 56.05%] [G loss: 0.735200]
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7042 [D loss: 0.677354, acc.: 56.45%] [G loss: 0.748780]
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7043 [D loss: 0.681986, acc.: 56.45%] [G loss: 0.727825]
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7044 [D loss: 0.678977, acc.: 54.30%] [G loss: 0.727569]
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7045 [D loss: 0.692172, acc.: 53.12%] [G loss: 0.724239]
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7046 [D loss: 0.687223, acc.: 52.54%] [G loss: 0.711804]
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7047 [D loss: 0.697927, acc.: 50.78%] [G loss: 0.732965]
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7048 [D loss: 0.679510, acc.: 58.40%] [G loss: 0.750606]
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7049 [D loss: 0.685869, acc.: 53.32%] [G loss: 0.762119]
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7050 [D loss: 0.684745, acc.: 57.23%] [G loss: 0.768442]
1/1 [==============================] - 0s 18ms/step
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7051 [D loss: 0.687981, acc.: 55.27%] [G loss: 0.768976]
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7052 [D loss: 0.670407, acc.: 58.98%] [G loss: 0.767520]
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7053 [D loss: 0.665948, acc.: 61.33%] [G loss: 0.744743]
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7054 [D loss: 0.685228, acc.: 52.73%] [G loss: 0.732585]
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7055 [D loss: 0.676464, acc.: 54.88%] [G loss: 0.736627]
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7056 [D loss: 0.676239, acc.: 56.05%] [G loss: 0.722617]
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7057 [D loss: 0.682086, acc.: 54.88%] [G loss: 0.736778]
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7058 [D loss: 0.679527, acc.: 56.25%] [G loss: 0.732825]
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7059 [D loss: 0.674940, acc.: 58.59%] [G loss: 0.751089]
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7060 [D loss: 0.675421, acc.: 58.59%] [G loss: 0.768381]
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7061 [D loss: 0.673346, acc.: 60.35%] [G loss: 0.752395]
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7062 [D loss: 0.670562, acc.: 60.74%] [G loss: 0.736268]
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7063 [D loss: 0.675658, acc.: 56.84%] [G loss: 0.741450]
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7064 [D loss: 0.674235, acc.: 58.59%] [G loss: 0.741613]
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7065 [D loss: 0.679841, acc.: 55.08%] [G loss: 0.732923]
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7066 [D loss: 0.685990, acc.: 56.64%] [G loss: 0.748951]
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7067 [D loss: 0.680858, acc.: 56.64%] [G loss: 0.743068]
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7068 [D loss: 0.680416, acc.: 56.84%] [G loss: 0.738646]
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7069 [D loss: 0.673721, acc.: 60.16%] [G loss: 0.740994]
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7070 [D loss: 0.683171, acc.: 55.27%] [G loss: 0.733508]
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7071 [D loss: 0.694321, acc.: 51.37%] [G loss: 0.740004]
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7072 [D loss: 0.679976, acc.: 54.49%] [G loss: 0.743131]
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7073 [D loss: 0.676020, acc.: 57.62%] [G loss: 0.731898]
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7074 [D loss: 0.684000, acc.: 54.30%] [G loss: 0.739823]
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7075 [D loss: 0.682828, acc.: 55.47%] [G loss: 0.740095]
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7076 [D loss: 0.685351, acc.: 54.30%] [G loss: 0.742397]
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7077 [D loss: 0.676414, acc.: 57.62%] [G loss: 0.754417]
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7078 [D loss: 0.680751, acc.: 54.49%] [G loss: 0.740193]
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7079 [D loss: 0.684474, acc.: 53.71%] [G loss: 0.733963]
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7080 [D loss: 0.675982, acc.: 58.40%] [G loss: 0.734696]
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7081 [D loss: 0.682548, acc.: 55.66%] [G loss: 0.735305]
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7082 [D loss: 0.692600, acc.: 52.15%] [G loss: 0.746291]
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7083 [D loss: 0.672739, acc.: 58.20%] [G loss: 0.734554]
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7084 [D loss: 0.678026, acc.: 56.84%] [G loss: 0.733537]
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7085 [D loss: 0.673585, acc.: 60.35%] [G loss: 0.743018]
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7086 [D loss: 0.681170, acc.: 55.86%] [G loss: 0.729988]
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7087 [D loss: 0.681654, acc.: 53.52%] [G loss: 0.738286]
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7088 [D loss: 0.695415, acc.: 53.12%] [G loss: 0.714161]
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7089 [D loss: 0.681092, acc.: 58.20%] [G loss: 0.742094]
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7090 [D loss: 0.684826, acc.: 55.08%] [G loss: 0.725856]
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7091 [D loss: 0.678258, acc.: 56.84%] [G loss: 0.734811]
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7092 [D loss: 0.676902, acc.: 57.81%] [G loss: 0.732289]
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7093 [D loss: 0.679993, acc.: 56.05%] [G loss: 0.742490]
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7094 [D loss: 0.675038, acc.: 58.98%] [G loss: 0.740437]
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7095 [D loss: 0.679854, acc.: 56.05%] [G loss: 0.735784]
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7096 [D loss: 0.682082, acc.: 55.47%] [G loss: 0.730859]
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7097 [D loss: 0.688762, acc.: 52.54%] [G loss: 0.737931]
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7098 [D loss: 0.688641, acc.: 53.32%] [G loss: 0.745809]
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7099 [D loss: 0.682232, acc.: 53.52%] [G loss: 0.742935]
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7100 [D loss: 0.677591, acc.: 57.81%] [G loss: 0.750919]
1/1 [==============================] - 0s 19ms/step
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7101 [D loss: 0.678060, acc.: 54.69%] [G loss: 0.752627]
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7102 [D loss: 0.691197, acc.: 54.49%] [G loss: 0.735616]
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7103 [D loss: 0.680499, acc.: 58.59%] [G loss: 0.735975]
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7104 [D loss: 0.677558, acc.: 57.23%] [G loss: 0.725936]
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7105 [D loss: 0.680695, acc.: 55.47%] [G loss: 0.727834]
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7106 [D loss: 0.682433, acc.: 55.27%] [G loss: 0.739065]
8/8 [==============================] - 0s 4ms/step
7107 [D loss: 0.681558, acc.: 57.62%] [G loss: 0.730595]
8/8 [==============================] - 0s 4ms/step
7108 [D loss: 0.674954, acc.: 58.20%] [G loss: 0.741546]
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7109 [D loss: 0.677010, acc.: 58.59%] [G loss: 0.751648]
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7110 [D loss: 0.680400, acc.: 57.42%] [G loss: 0.747913]
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7111 [D loss: 0.671630, acc.: 58.01%] [G loss: 0.738338]
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7112 [D loss: 0.677945, acc.: 57.62%] [G loss: 0.746680]
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7113 [D loss: 0.684954, acc.: 55.86%] [G loss: 0.724510]
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7114 [D loss: 0.672669, acc.: 60.94%] [G loss: 0.725769]
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7115 [D loss: 0.683420, acc.: 56.25%] [G loss: 0.743220]
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7116 [D loss: 0.685586, acc.: 55.47%] [G loss: 0.750297]
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7117 [D loss: 0.675005, acc.: 58.59%] [G loss: 0.748578]
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7118 [D loss: 0.675990, acc.: 56.45%] [G loss: 0.733856]
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7119 [D loss: 0.678665, acc.: 56.45%] [G loss: 0.752217]
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7120 [D loss: 0.678506, acc.: 56.45%] [G loss: 0.743630]
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7121 [D loss: 0.685887, acc.: 54.30%] [G loss: 0.745131]
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7122 [D loss: 0.699590, acc.: 51.37%] [G loss: 0.740105]
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7123 [D loss: 0.662777, acc.: 63.09%] [G loss: 0.761776]
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7124 [D loss: 0.684345, acc.: 55.08%] [G loss: 0.741230]
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7125 [D loss: 0.692017, acc.: 54.10%] [G loss: 0.725665]
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7126 [D loss: 0.693327, acc.: 51.76%] [G loss: 0.731879]
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7127 [D loss: 0.674874, acc.: 57.81%] [G loss: 0.741492]
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7128 [D loss: 0.671929, acc.: 60.55%] [G loss: 0.735250]
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7129 [D loss: 0.686877, acc.: 55.47%] [G loss: 0.743828]
8/8 [==============================] - 0s 4ms/step
7130 [D loss: 0.685201, acc.: 57.42%] [G loss: 0.731639]
8/8 [==============================] - 0s 4ms/step
7131 [D loss: 0.680612, acc.: 58.20%] [G loss: 0.729458]
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7132 [D loss: 0.685025, acc.: 52.93%] [G loss: 0.744092]
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7133 [D loss: 0.682870, acc.: 54.88%] [G loss: 0.737485]
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7134 [D loss: 0.676907, acc.: 57.62%] [G loss: 0.736749]
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7135 [D loss: 0.695810, acc.: 52.93%] [G loss: 0.743176]
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7136 [D loss: 0.685539, acc.: 55.47%] [G loss: 0.749184]
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7137 [D loss: 0.685493, acc.: 57.03%] [G loss: 0.737233]
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7138 [D loss: 0.682989, acc.: 55.08%] [G loss: 0.746911]
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7139 [D loss: 0.686601, acc.: 56.05%] [G loss: 0.744016]
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7140 [D loss: 0.689081, acc.: 51.37%] [G loss: 0.745010]
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7141 [D loss: 0.680100, acc.: 57.81%] [G loss: 0.727849]
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7142 [D loss: 0.687158, acc.: 53.12%] [G loss: 0.722392]
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7143 [D loss: 0.684250, acc.: 53.91%] [G loss: 0.739661]
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7144 [D loss: 0.679356, acc.: 56.84%] [G loss: 0.742633]
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7145 [D loss: 0.683706, acc.: 56.84%] [G loss: 0.743839]
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7146 [D loss: 0.684954, acc.: 53.91%] [G loss: 0.738997]
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7147 [D loss: 0.681779, acc.: 56.45%] [G loss: 0.744212]
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7148 [D loss: 0.684857, acc.: 55.86%] [G loss: 0.745492]
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7149 [D loss: 0.676429, acc.: 57.81%] [G loss: 0.733596]
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7150 [D loss: 0.678328, acc.: 58.20%] [G loss: 0.734127]
1/1 [==============================] - 0s 17ms/step
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7151 [D loss: 0.671693, acc.: 59.57%] [G loss: 0.727707]
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7152 [D loss: 0.691987, acc.: 51.37%] [G loss: 0.745473]
8/8 [==============================] - 0s 4ms/step
7153 [D loss: 0.686379, acc.: 55.27%] [G loss: 0.733993]
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7154 [D loss: 0.682942, acc.: 54.10%] [G loss: 0.725197]
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7155 [D loss: 0.675551, acc.: 56.25%] [G loss: 0.722878]
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7156 [D loss: 0.688740, acc.: 54.30%] [G loss: 0.722323]
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7157 [D loss: 0.684492, acc.: 56.25%] [G loss: 0.735534]
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7158 [D loss: 0.684391, acc.: 56.25%] [G loss: 0.738729]
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7159 [D loss: 0.685606, acc.: 53.71%] [G loss: 0.731146]
8/8 [==============================] - 0s 4ms/step
7160 [D loss: 0.685083, acc.: 55.27%] [G loss: 0.728237]
8/8 [==============================] - 0s 4ms/step
7161 [D loss: 0.684972, acc.: 53.52%] [G loss: 0.743385]
8/8 [==============================] - 0s 4ms/step
7162 [D loss: 0.684204, acc.: 56.64%] [G loss: 0.751084]
8/8 [==============================] - 0s 4ms/step
7163 [D loss: 0.680830, acc.: 57.62%] [G loss: 0.739875]
8/8 [==============================] - 0s 4ms/step
7164 [D loss: 0.675231, acc.: 57.23%] [G loss: 0.722324]
8/8 [==============================] - 0s 4ms/step
7165 [D loss: 0.677074, acc.: 57.23%] [G loss: 0.730859]
8/8 [==============================] - 0s 4ms/step
7166 [D loss: 0.685492, acc.: 55.27%] [G loss: 0.724073]
8/8 [==============================] - 0s 4ms/step
7167 [D loss: 0.685450, acc.: 53.71%] [G loss: 0.749516]
8/8 [==============================] - 0s 4ms/step
7168 [D loss: 0.687460, acc.: 56.05%] [G loss: 0.739914]
8/8 [==============================] - 0s 4ms/step
7169 [D loss: 0.685803, acc.: 55.08%] [G loss: 0.740959]
8/8 [==============================] - 0s 4ms/step
7170 [D loss: 0.681043, acc.: 55.86%] [G loss: 0.739726]
8/8 [==============================] - 0s 4ms/step
7171 [D loss: 0.667386, acc.: 59.96%] [G loss: 0.756731]
8/8 [==============================] - 0s 4ms/step
7172 [D loss: 0.670381, acc.: 62.50%] [G loss: 0.747232]
8/8 [==============================] - 0s 4ms/step
7173 [D loss: 0.669965, acc.: 59.38%] [G loss: 0.736628]
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7174 [D loss: 0.686179, acc.: 54.69%] [G loss: 0.726425]
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7175 [D loss: 0.691026, acc.: 53.52%] [G loss: 0.724890]
8/8 [==============================] - 0s 4ms/step
7176 [D loss: 0.687654, acc.: 54.69%] [G loss: 0.725678]
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7177 [D loss: 0.686990, acc.: 56.05%] [G loss: 0.738217]
8/8 [==============================] - 0s 4ms/step
7178 [D loss: 0.674306, acc.: 57.42%] [G loss: 0.743556]
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7179 [D loss: 0.674724, acc.: 57.81%] [G loss: 0.758996]
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7180 [D loss: 0.676979, acc.: 57.42%] [G loss: 0.741595]
8/8 [==============================] - 0s 4ms/step
7181 [D loss: 0.666757, acc.: 61.13%] [G loss: 0.729301]
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7182 [D loss: 0.680995, acc.: 54.30%] [G loss: 0.720732]
8/8 [==============================] - 0s 4ms/step
7183 [D loss: 0.687956, acc.: 53.91%] [G loss: 0.721730]
8/8 [==============================] - 0s 4ms/step
7184 [D loss: 0.689896, acc.: 52.93%] [G loss: 0.728621]
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7185 [D loss: 0.685795, acc.: 55.27%] [G loss: 0.715018]
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7186 [D loss: 0.677973, acc.: 57.42%] [G loss: 0.744572]
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7187 [D loss: 0.673137, acc.: 57.42%] [G loss: 0.742880]
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7188 [D loss: 0.682466, acc.: 56.64%] [G loss: 0.736024]
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7189 [D loss: 0.677382, acc.: 54.88%] [G loss: 0.744145]
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7190 [D loss: 0.677663, acc.: 56.05%] [G loss: 0.749182]
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7191 [D loss: 0.682439, acc.: 58.98%] [G loss: 0.751291]
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7192 [D loss: 0.688899, acc.: 55.27%] [G loss: 0.743029]
8/8 [==============================] - 0s 4ms/step
7193 [D loss: 0.686223, acc.: 56.05%] [G loss: 0.735249]
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7194 [D loss: 0.678394, acc.: 60.35%] [G loss: 0.759697]
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7195 [D loss: 0.685077, acc.: 58.01%] [G loss: 0.748227]
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7196 [D loss: 0.671614, acc.: 57.62%] [G loss: 0.752184]
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7197 [D loss: 0.674313, acc.: 60.74%] [G loss: 0.752681]
8/8 [==============================] - 0s 4ms/step
7198 [D loss: 0.685908, acc.: 55.86%] [G loss: 0.749243]
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7199 [D loss: 0.678479, acc.: 56.25%] [G loss: 0.731743]
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7200 [D loss: 0.687480, acc.: 52.73%] [G loss: 0.740970]
1/1 [==============================] - 0s 22ms/step
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7201 [D loss: 0.684597, acc.: 56.45%] [G loss: 0.745511]
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7202 [D loss: 0.686295, acc.: 54.88%] [G loss: 0.739088]
8/8 [==============================] - 0s 4ms/step
7203 [D loss: 0.677644, acc.: 56.45%] [G loss: 0.752031]
8/8 [==============================] - 0s 4ms/step
7204 [D loss: 0.667228, acc.: 58.40%] [G loss: 0.743694]
8/8 [==============================] - 0s 4ms/step
7205 [D loss: 0.675504, acc.: 58.98%] [G loss: 0.745528]
8/8 [==============================] - 0s 4ms/step
7206 [D loss: 0.678197, acc.: 58.01%] [G loss: 0.745407]
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7207 [D loss: 0.678858, acc.: 56.45%] [G loss: 0.737194]
8/8 [==============================] - 0s 4ms/step
7208 [D loss: 0.679541, acc.: 57.81%] [G loss: 0.721777]
8/8 [==============================] - 0s 4ms/step
7209 [D loss: 0.676173, acc.: 59.77%] [G loss: 0.727689]
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7210 [D loss: 0.691621, acc.: 53.12%] [G loss: 0.734412]
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7211 [D loss: 0.677951, acc.: 58.01%] [G loss: 0.738181]
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7212 [D loss: 0.679725, acc.: 58.01%] [G loss: 0.742270]
8/8 [==============================] - 0s 4ms/step
7213 [D loss: 0.674111, acc.: 57.81%] [G loss: 0.731626]
8/8 [==============================] - 0s 4ms/step
7214 [D loss: 0.687574, acc.: 53.32%] [G loss: 0.739812]
8/8 [==============================] - 0s 4ms/step
7215 [D loss: 0.695285, acc.: 51.17%] [G loss: 0.738524]
8/8 [==============================] - 0s 4ms/step
7216 [D loss: 0.687750, acc.: 52.15%] [G loss: 0.740724]
8/8 [==============================] - 0s 4ms/step
7217 [D loss: 0.694453, acc.: 53.71%] [G loss: 0.732783]
8/8 [==============================] - 0s 4ms/step
7218 [D loss: 0.678277, acc.: 58.40%] [G loss: 0.743796]
8/8 [==============================] - 0s 4ms/step
7219 [D loss: 0.673359, acc.: 55.86%] [G loss: 0.736684]
8/8 [==============================] - 0s 4ms/step
7220 [D loss: 0.673825, acc.: 58.20%] [G loss: 0.742859]
8/8 [==============================] - 0s 4ms/step
7221 [D loss: 0.680002, acc.: 54.49%] [G loss: 0.735573]
8/8 [==============================] - 0s 4ms/step
7222 [D loss: 0.687840, acc.: 55.66%] [G loss: 0.747013]
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7223 [D loss: 0.682832, acc.: 54.88%] [G loss: 0.743330]
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7224 [D loss: 0.685285, acc.: 59.77%] [G loss: 0.735559]
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7225 [D loss: 0.685496, acc.: 54.10%] [G loss: 0.736093]
8/8 [==============================] - 0s 4ms/step
7226 [D loss: 0.691943, acc.: 52.54%] [G loss: 0.746821]
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7227 [D loss: 0.693573, acc.: 52.73%] [G loss: 0.744182]
8/8 [==============================] - 0s 4ms/step
7228 [D loss: 0.681721, acc.: 55.27%] [G loss: 0.735947]
8/8 [==============================] - 0s 4ms/step
7229 [D loss: 0.670374, acc.: 59.38%] [G loss: 0.744818]
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7230 [D loss: 0.677806, acc.: 57.23%] [G loss: 0.729665]
8/8 [==============================] - 0s 4ms/step
7231 [D loss: 0.679056, acc.: 55.66%] [G loss: 0.740626]
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7232 [D loss: 0.679302, acc.: 56.45%] [G loss: 0.732769]
8/8 [==============================] - 0s 4ms/step
7233 [D loss: 0.679265, acc.: 56.84%] [G loss: 0.746762]
8/8 [==============================] - 0s 4ms/step
7234 [D loss: 0.678230, acc.: 57.42%] [G loss: 0.729782]
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7235 [D loss: 0.687059, acc.: 53.91%] [G loss: 0.752790]
8/8 [==============================] - 0s 4ms/step
7236 [D loss: 0.681767, acc.: 56.84%] [G loss: 0.747689]
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7237 [D loss: 0.682040, acc.: 55.27%] [G loss: 0.741153]
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7238 [D loss: 0.671268, acc.: 59.38%] [G loss: 0.734291]
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7239 [D loss: 0.674306, acc.: 57.23%] [G loss: 0.740467]
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7240 [D loss: 0.684320, acc.: 54.10%] [G loss: 0.744976]
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7241 [D loss: 0.696399, acc.: 51.17%] [G loss: 0.735779]
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7242 [D loss: 0.679436, acc.: 58.20%] [G loss: 0.733919]
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7243 [D loss: 0.690439, acc.: 53.71%] [G loss: 0.740843]
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7244 [D loss: 0.678032, acc.: 58.98%] [G loss: 0.725442]
8/8 [==============================] - 0s 4ms/step
7245 [D loss: 0.677184, acc.: 57.42%] [G loss: 0.732126]
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7246 [D loss: 0.670398, acc.: 62.30%] [G loss: 0.737746]
8/8 [==============================] - 0s 4ms/step
7247 [D loss: 0.674162, acc.: 57.23%] [G loss: 0.711927]
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7248 [D loss: 0.687962, acc.: 53.71%] [G loss: 0.737764]
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7249 [D loss: 0.685347, acc.: 54.88%] [G loss: 0.749779]
8/8 [==============================] - 0s 4ms/step
7250 [D loss: 0.685658, acc.: 55.47%] [G loss: 0.751875]
1/1 [==============================] - 0s 18ms/step
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7251 [D loss: 0.672154, acc.: 59.18%] [G loss: 0.748643]
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7252 [D loss: 0.679197, acc.: 56.45%] [G loss: 0.773748]
8/8 [==============================] - 0s 4ms/step
7253 [D loss: 0.676990, acc.: 56.84%] [G loss: 0.754931]
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7254 [D loss: 0.679213, acc.: 56.25%] [G loss: 0.751544]
8/8 [==============================] - 0s 4ms/step
7255 [D loss: 0.681724, acc.: 56.84%] [G loss: 0.738046]
8/8 [==============================] - 0s 4ms/step
7256 [D loss: 0.693068, acc.: 52.54%] [G loss: 0.735847]
8/8 [==============================] - 0s 4ms/step
7257 [D loss: 0.685372, acc.: 55.08%] [G loss: 0.737590]
8/8 [==============================] - 0s 4ms/step
7258 [D loss: 0.689674, acc.: 53.32%] [G loss: 0.737234]
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7259 [D loss: 0.688542, acc.: 53.71%] [G loss: 0.758346]
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7260 [D loss: 0.677305, acc.: 54.30%] [G loss: 0.761300]
8/8 [==============================] - 0s 4ms/step
7261 [D loss: 0.675838, acc.: 58.40%] [G loss: 0.755644]
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7262 [D loss: 0.678203, acc.: 58.98%] [G loss: 0.751936]
8/8 [==============================] - 0s 4ms/step
7263 [D loss: 0.685919, acc.: 52.34%] [G loss: 0.725435]
8/8 [==============================] - 0s 4ms/step
7264 [D loss: 0.676691, acc.: 57.42%] [G loss: 0.739342]
8/8 [==============================] - 0s 4ms/step
7265 [D loss: 0.691244, acc.: 53.91%] [G loss: 0.729136]
8/8 [==============================] - 0s 4ms/step
7266 [D loss: 0.678212, acc.: 55.47%] [G loss: 0.730011]
8/8 [==============================] - 0s 4ms/step
7267 [D loss: 0.684479, acc.: 55.27%] [G loss: 0.728061]
8/8 [==============================] - 0s 4ms/step
7268 [D loss: 0.684272, acc.: 55.86%] [G loss: 0.736037]
8/8 [==============================] - 0s 4ms/step
7269 [D loss: 0.676627, acc.: 58.59%] [G loss: 0.749719]
8/8 [==============================] - 0s 4ms/step
7270 [D loss: 0.666187, acc.: 60.35%] [G loss: 0.741710]
8/8 [==============================] - 0s 4ms/step
7271 [D loss: 0.677657, acc.: 58.98%] [G loss: 0.737936]
8/8 [==============================] - 0s 4ms/step
7272 [D loss: 0.680581, acc.: 56.25%] [G loss: 0.735430]
8/8 [==============================] - 0s 4ms/step
7273 [D loss: 0.672478, acc.: 60.74%] [G loss: 0.731935]
8/8 [==============================] - 0s 4ms/step
7274 [D loss: 0.691323, acc.: 52.15%] [G loss: 0.722354]
8/8 [==============================] - 0s 4ms/step
7275 [D loss: 0.683367, acc.: 56.45%] [G loss: 0.736025]
8/8 [==============================] - 0s 4ms/step
7276 [D loss: 0.686301, acc.: 53.91%] [G loss: 0.745371]
8/8 [==============================] - 0s 4ms/step
7277 [D loss: 0.684080, acc.: 55.08%] [G loss: 0.750372]
8/8 [==============================] - 0s 4ms/step
7278 [D loss: 0.674137, acc.: 57.42%] [G loss: 0.752905]
8/8 [==============================] - 0s 4ms/step
7279 [D loss: 0.672544, acc.: 60.55%] [G loss: 0.763867]
8/8 [==============================] - 0s 4ms/step
7280 [D loss: 0.670219, acc.: 59.38%] [G loss: 0.740827]
8/8 [==============================] - 0s 4ms/step
7281 [D loss: 0.672383, acc.: 58.20%] [G loss: 0.719378]
8/8 [==============================] - 0s 4ms/step
7282 [D loss: 0.679276, acc.: 58.40%] [G loss: 0.730143]
8/8 [==============================] - 0s 4ms/step
7283 [D loss: 0.692889, acc.: 55.27%] [G loss: 0.724032]
8/8 [==============================] - 0s 4ms/step
7284 [D loss: 0.690970, acc.: 52.73%] [G loss: 0.739426]
8/8 [==============================] - 0s 4ms/step
7285 [D loss: 0.681934, acc.: 54.30%] [G loss: 0.743252]
8/8 [==============================] - 0s 4ms/step
7286 [D loss: 0.674242, acc.: 58.98%] [G loss: 0.764535]
8/8 [==============================] - 0s 4ms/step
7287 [D loss: 0.678529, acc.: 57.81%] [G loss: 0.773450]
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7288 [D loss: 0.676173, acc.: 58.20%] [G loss: 0.748830]
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7289 [D loss: 0.680612, acc.: 58.20%] [G loss: 0.747800]
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7290 [D loss: 0.680029, acc.: 53.52%] [G loss: 0.729672]
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7291 [D loss: 0.691061, acc.: 58.01%] [G loss: 0.738367]
8/8 [==============================] - 0s 4ms/step
7292 [D loss: 0.680374, acc.: 54.10%] [G loss: 0.730682]
8/8 [==============================] - 0s 4ms/step
7293 [D loss: 0.688721, acc.: 57.81%] [G loss: 0.753100]
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7294 [D loss: 0.666089, acc.: 61.33%] [G loss: 0.750868]
8/8 [==============================] - 0s 4ms/step
7295 [D loss: 0.667164, acc.: 60.16%] [G loss: 0.753356]
8/8 [==============================] - 0s 4ms/step
7296 [D loss: 0.669547, acc.: 60.35%] [G loss: 0.747277]
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7297 [D loss: 0.678534, acc.: 58.79%] [G loss: 0.738921]
8/8 [==============================] - 0s 4ms/step
7298 [D loss: 0.690246, acc.: 51.56%] [G loss: 0.712379]
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7299 [D loss: 0.690460, acc.: 53.91%] [G loss: 0.710034]
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7300 [D loss: 0.693918, acc.: 49.22%] [G loss: 0.716071]
1/1 [==============================] - 0s 16ms/step
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7301 [D loss: 0.673783, acc.: 58.59%] [G loss: 0.729704]
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7302 [D loss: 0.682490, acc.: 58.01%] [G loss: 0.741516]
8/8 [==============================] - 0s 4ms/step
7303 [D loss: 0.674827, acc.: 56.05%] [G loss: 0.769361]
8/8 [==============================] - 0s 4ms/step
7304 [D loss: 0.682565, acc.: 56.84%] [G loss: 0.762143]
8/8 [==============================] - 0s 4ms/step
7305 [D loss: 0.668797, acc.: 63.28%] [G loss: 0.762437]
8/8 [==============================] - 0s 4ms/step
7306 [D loss: 0.674117, acc.: 56.64%] [G loss: 0.736858]
8/8 [==============================] - 0s 4ms/step
7307 [D loss: 0.692292, acc.: 52.93%] [G loss: 0.743576]
8/8 [==============================] - 0s 4ms/step
7308 [D loss: 0.686629, acc.: 52.93%] [G loss: 0.729032]
8/8 [==============================] - 0s 4ms/step
7309 [D loss: 0.687565, acc.: 53.71%] [G loss: 0.748344]
8/8 [==============================] - 0s 4ms/step
7310 [D loss: 0.688925, acc.: 52.54%] [G loss: 0.744063]
8/8 [==============================] - 0s 4ms/step
7311 [D loss: 0.673499, acc.: 57.03%] [G loss: 0.749860]
8/8 [==============================] - 0s 4ms/step
7312 [D loss: 0.679740, acc.: 57.23%] [G loss: 0.774971]
8/8 [==============================] - 0s 4ms/step
7313 [D loss: 0.667199, acc.: 59.96%] [G loss: 0.749588]
8/8 [==============================] - 0s 4ms/step
7314 [D loss: 0.679556, acc.: 56.64%] [G loss: 0.748739]
8/8 [==============================] - 0s 4ms/step
7315 [D loss: 0.678862, acc.: 54.69%] [G loss: 0.739943]
8/8 [==============================] - 0s 4ms/step
7316 [D loss: 0.672169, acc.: 59.18%] [G loss: 0.728952]
8/8 [==============================] - 0s 4ms/step
7317 [D loss: 0.697382, acc.: 50.78%] [G loss: 0.737023]
8/8 [==============================] - 0s 4ms/step
7318 [D loss: 0.671897, acc.: 59.57%] [G loss: 0.742775]
8/8 [==============================] - 0s 4ms/step
7319 [D loss: 0.678787, acc.: 57.62%] [G loss: 0.757483]
8/8 [==============================] - 0s 4ms/step
7320 [D loss: 0.677756, acc.: 57.42%] [G loss: 0.747961]
8/8 [==============================] - 0s 4ms/step
7321 [D loss: 0.675953, acc.: 56.25%] [G loss: 0.755476]
8/8 [==============================] - 0s 4ms/step
7322 [D loss: 0.676897, acc.: 58.59%] [G loss: 0.748436]
8/8 [==============================] - 0s 4ms/step
7323 [D loss: 0.679085, acc.: 57.03%] [G loss: 0.747365]
8/8 [==============================] - 0s 4ms/step
7324 [D loss: 0.687085, acc.: 55.66%] [G loss: 0.730347]
8/8 [==============================] - 0s 4ms/step
7325 [D loss: 0.681454, acc.: 55.47%] [G loss: 0.736132]
8/8 [==============================] - 0s 4ms/step
7326 [D loss: 0.688223, acc.: 55.47%] [G loss: 0.751359]
8/8 [==============================] - 0s 4ms/step
7327 [D loss: 0.691646, acc.: 54.10%] [G loss: 0.742946]
8/8 [==============================] - 0s 4ms/step
7328 [D loss: 0.684851, acc.: 53.91%] [G loss: 0.762222]
8/8 [==============================] - 0s 4ms/step
7329 [D loss: 0.671175, acc.: 59.57%] [G loss: 0.760675]
8/8 [==============================] - 0s 4ms/step
7330 [D loss: 0.669607, acc.: 61.52%] [G loss: 0.756791]
8/8 [==============================] - 0s 4ms/step
7331 [D loss: 0.673978, acc.: 60.35%] [G loss: 0.736754]
8/8 [==============================] - 0s 4ms/step
7332 [D loss: 0.676059, acc.: 60.16%] [G loss: 0.728982]
8/8 [==============================] - 0s 4ms/step
7333 [D loss: 0.679390, acc.: 57.62%] [G loss: 0.721878]
8/8 [==============================] - 0s 4ms/step
7334 [D loss: 0.684387, acc.: 55.27%] [G loss: 0.718116]
8/8 [==============================] - 0s 4ms/step
7335 [D loss: 0.690524, acc.: 54.88%] [G loss: 0.722568]
8/8 [==============================] - 0s 4ms/step
7336 [D loss: 0.690099, acc.: 51.37%] [G loss: 0.743640]
8/8 [==============================] - 0s 4ms/step
7337 [D loss: 0.679136, acc.: 59.38%] [G loss: 0.733549]
8/8 [==============================] - 0s 4ms/step
7338 [D loss: 0.677144, acc.: 60.35%] [G loss: 0.759851]
8/8 [==============================] - 0s 4ms/step
7339 [D loss: 0.673946, acc.: 56.05%] [G loss: 0.758694]
8/8 [==============================] - 0s 4ms/step
7340 [D loss: 0.673272, acc.: 59.57%] [G loss: 0.748784]
8/8 [==============================] - 0s 4ms/step
7341 [D loss: 0.680593, acc.: 55.08%] [G loss: 0.757511]
8/8 [==============================] - 0s 4ms/step
7342 [D loss: 0.692460, acc.: 52.54%] [G loss: 0.737355]
8/8 [==============================] - 0s 4ms/step
7343 [D loss: 0.695235, acc.: 50.78%] [G loss: 0.754119]
8/8 [==============================] - 0s 4ms/step
7344 [D loss: 0.686455, acc.: 55.27%] [G loss: 0.748340]
8/8 [==============================] - 0s 4ms/step
7345 [D loss: 0.681171, acc.: 56.05%] [G loss: 0.765534]
8/8 [==============================] - 0s 4ms/step
7346 [D loss: 0.671099, acc.: 57.81%] [G loss: 0.760299]
8/8 [==============================] - 0s 4ms/step
7347 [D loss: 0.682426, acc.: 57.23%] [G loss: 0.746628]
8/8 [==============================] - 0s 4ms/step
7348 [D loss: 0.673497, acc.: 57.81%] [G loss: 0.746914]
8/8 [==============================] - 0s 4ms/step
7349 [D loss: 0.685498, acc.: 55.08%] [G loss: 0.740228]
8/8 [==============================] - 0s 4ms/step
7350 [D loss: 0.680703, acc.: 60.55%] [G loss: 0.718761]
1/1 [==============================] - 0s 19ms/step
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7351 [D loss: 0.690638, acc.: 53.12%] [G loss: 0.734594]
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7352 [D loss: 0.682917, acc.: 55.66%] [G loss: 0.737489]
8/8 [==============================] - 0s 4ms/step
7353 [D loss: 0.680073, acc.: 56.05%] [G loss: 0.755451]
8/8 [==============================] - 0s 4ms/step
7354 [D loss: 0.673093, acc.: 58.79%] [G loss: 0.756296]
8/8 [==============================] - 0s 4ms/step
7355 [D loss: 0.672235, acc.: 59.57%] [G loss: 0.747690]
8/8 [==============================] - 0s 4ms/step
7356 [D loss: 0.687252, acc.: 53.32%] [G loss: 0.744114]
8/8 [==============================] - 0s 4ms/step
7357 [D loss: 0.678648, acc.: 56.25%] [G loss: 0.745240]
8/8 [==============================] - 0s 4ms/step
7358 [D loss: 0.675850, acc.: 56.64%] [G loss: 0.740634]
8/8 [==============================] - 0s 4ms/step
7359 [D loss: 0.682254, acc.: 54.49%] [G loss: 0.749462]
8/8 [==============================] - 0s 4ms/step
7360 [D loss: 0.679192, acc.: 56.05%] [G loss: 0.740503]
8/8 [==============================] - 0s 4ms/step
7361 [D loss: 0.692637, acc.: 51.76%] [G loss: 0.746742]
8/8 [==============================] - 0s 4ms/step
7362 [D loss: 0.674922, acc.: 57.62%] [G loss: 0.727416]
8/8 [==============================] - 0s 4ms/step
7363 [D loss: 0.684974, acc.: 55.86%] [G loss: 0.741981]
8/8 [==============================] - 0s 4ms/step
7364 [D loss: 0.681998, acc.: 56.05%] [G loss: 0.756802]
8/8 [==============================] - 0s 4ms/step
7365 [D loss: 0.676420, acc.: 57.42%] [G loss: 0.736028]
8/8 [==============================] - 0s 4ms/step
7366 [D loss: 0.687660, acc.: 56.05%] [G loss: 0.736659]
8/8 [==============================] - 0s 4ms/step
7367 [D loss: 0.682363, acc.: 54.30%] [G loss: 0.728692]
8/8 [==============================] - 0s 4ms/step
7368 [D loss: 0.681837, acc.: 56.25%] [G loss: 0.723680]
8/8 [==============================] - 0s 4ms/step
7369 [D loss: 0.687160, acc.: 54.88%] [G loss: 0.728928]
8/8 [==============================] - 0s 4ms/step
7370 [D loss: 0.685742, acc.: 54.88%] [G loss: 0.736203]
8/8 [==============================] - 0s 4ms/step
7371 [D loss: 0.681913, acc.: 54.10%] [G loss: 0.740116]
8/8 [==============================] - 0s 4ms/step
7372 [D loss: 0.683315, acc.: 55.66%] [G loss: 0.747937]
8/8 [==============================] - 0s 4ms/step
7373 [D loss: 0.672486, acc.: 58.01%] [G loss: 0.743139]
8/8 [==============================] - 0s 4ms/step
7374 [D loss: 0.680082, acc.: 58.79%] [G loss: 0.740403]
8/8 [==============================] - 0s 4ms/step
7375 [D loss: 0.684337, acc.: 55.86%] [G loss: 0.730600]
8/8 [==============================] - 0s 4ms/step
7376 [D loss: 0.683374, acc.: 55.86%] [G loss: 0.758534]
8/8 [==============================] - 0s 4ms/step
7377 [D loss: 0.682584, acc.: 56.45%] [G loss: 0.752516]
8/8 [==============================] - 0s 4ms/step
7378 [D loss: 0.679550, acc.: 56.25%] [G loss: 0.748716]
8/8 [==============================] - 0s 4ms/step
7379 [D loss: 0.669658, acc.: 58.79%] [G loss: 0.752018]
8/8 [==============================] - 0s 4ms/step
7380 [D loss: 0.669023, acc.: 61.72%] [G loss: 0.756882]
8/8 [==============================] - 0s 4ms/step
7381 [D loss: 0.674718, acc.: 57.23%] [G loss: 0.727531]
8/8 [==============================] - 0s 4ms/step
7382 [D loss: 0.678212, acc.: 58.01%] [G loss: 0.741877]
8/8 [==============================] - 0s 4ms/step
7383 [D loss: 0.686558, acc.: 55.08%] [G loss: 0.730104]
8/8 [==============================] - 0s 4ms/step
7384 [D loss: 0.687848, acc.: 53.91%] [G loss: 0.726774]
8/8 [==============================] - 0s 4ms/step
7385 [D loss: 0.679121, acc.: 57.62%] [G loss: 0.740035]
8/8 [==============================] - 0s 4ms/step
7386 [D loss: 0.679656, acc.: 56.45%] [G loss: 0.766401]
8/8 [==============================] - 0s 4ms/step
7387 [D loss: 0.676935, acc.: 56.64%] [G loss: 0.758960]
8/8 [==============================] - 0s 4ms/step
7388 [D loss: 0.667989, acc.: 60.74%] [G loss: 0.754604]
8/8 [==============================] - 0s 4ms/step
7389 [D loss: 0.678072, acc.: 57.62%] [G loss: 0.753432]
8/8 [==============================] - 0s 4ms/step
7390 [D loss: 0.679322, acc.: 57.42%] [G loss: 0.744947]
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7391 [D loss: 0.682093, acc.: 56.25%] [G loss: 0.745712]
8/8 [==============================] - 0s 4ms/step
7392 [D loss: 0.690538, acc.: 54.88%] [G loss: 0.726721]
8/8 [==============================] - 0s 4ms/step
7393 [D loss: 0.686095, acc.: 54.10%] [G loss: 0.725456]
8/8 [==============================] - 0s 4ms/step
7394 [D loss: 0.682378, acc.: 58.20%] [G loss: 0.750504]
8/8 [==============================] - 0s 4ms/step
7395 [D loss: 0.686050, acc.: 54.69%] [G loss: 0.757471]
8/8 [==============================] - 0s 4ms/step
7396 [D loss: 0.674611, acc.: 58.01%] [G loss: 0.755032]
8/8 [==============================] - 0s 4ms/step
7397 [D loss: 0.684194, acc.: 53.91%] [G loss: 0.760407]
8/8 [==============================] - 0s 4ms/step
7398 [D loss: 0.675535, acc.: 58.20%] [G loss: 0.752292]
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7399 [D loss: 0.671653, acc.: 58.59%] [G loss: 0.735733]
8/8 [==============================] - 0s 4ms/step
7400 [D loss: 0.686219, acc.: 56.45%] [G loss: 0.740191]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 4ms/step
7401 [D loss: 0.680018, acc.: 55.08%] [G loss: 0.724591]
8/8 [==============================] - 0s 4ms/step
7402 [D loss: 0.687939, acc.: 54.69%] [G loss: 0.728694]
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7403 [D loss: 0.670933, acc.: 58.79%] [G loss: 0.747229]
8/8 [==============================] - 0s 4ms/step
7404 [D loss: 0.669358, acc.: 59.96%] [G loss: 0.750905]
8/8 [==============================] - 0s 4ms/step
7405 [D loss: 0.678343, acc.: 56.84%] [G loss: 0.731276]
8/8 [==============================] - 0s 4ms/step
7406 [D loss: 0.672987, acc.: 58.79%] [G loss: 0.748686]
8/8 [==============================] - 0s 4ms/step
7407 [D loss: 0.670717, acc.: 58.98%] [G loss: 0.753034]
8/8 [==============================] - 0s 4ms/step
7408 [D loss: 0.682339, acc.: 54.49%] [G loss: 0.737930]
8/8 [==============================] - 0s 4ms/step
7409 [D loss: 0.687961, acc.: 54.30%] [G loss: 0.736568]
8/8 [==============================] - 0s 4ms/step
7410 [D loss: 0.693489, acc.: 50.78%] [G loss: 0.735563]
8/8 [==============================] - 0s 4ms/step
7411 [D loss: 0.703319, acc.: 50.20%] [G loss: 0.756415]
8/8 [==============================] - 0s 4ms/step
7412 [D loss: 0.675111, acc.: 56.84%] [G loss: 0.757317]
8/8 [==============================] - 0s 4ms/step
7413 [D loss: 0.668385, acc.: 62.30%] [G loss: 0.751161]
8/8 [==============================] - 0s 4ms/step
7414 [D loss: 0.670276, acc.: 58.98%] [G loss: 0.758875]
8/8 [==============================] - 0s 4ms/step
7415 [D loss: 0.669004, acc.: 59.96%] [G loss: 0.770650]
8/8 [==============================] - 0s 4ms/step
7416 [D loss: 0.675047, acc.: 60.16%] [G loss: 0.735887]
8/8 [==============================] - 0s 4ms/step
7417 [D loss: 0.677773, acc.: 55.47%] [G loss: 0.738376]
8/8 [==============================] - 0s 4ms/step
7418 [D loss: 0.682310, acc.: 55.66%] [G loss: 0.703986]
8/8 [==============================] - 0s 4ms/step
7419 [D loss: 0.687884, acc.: 53.52%] [G loss: 0.706374]
8/8 [==============================] - 0s 4ms/step
7420 [D loss: 0.693836, acc.: 52.15%] [G loss: 0.729074]
8/8 [==============================] - 0s 4ms/step
7421 [D loss: 0.669412, acc.: 60.94%] [G loss: 0.736492]
8/8 [==============================] - 0s 4ms/step
7422 [D loss: 0.673384, acc.: 58.40%] [G loss: 0.750418]
8/8 [==============================] - 0s 4ms/step
7423 [D loss: 0.669949, acc.: 58.40%] [G loss: 0.761633]
8/8 [==============================] - 0s 4ms/step
7424 [D loss: 0.663401, acc.: 60.16%] [G loss: 0.744363]
8/8 [==============================] - 0s 4ms/step
7425 [D loss: 0.682249, acc.: 55.47%] [G loss: 0.734565]
8/8 [==============================] - 0s 4ms/step
7426 [D loss: 0.672381, acc.: 58.40%] [G loss: 0.714739]
8/8 [==============================] - 0s 4ms/step
7427 [D loss: 0.690583, acc.: 52.34%] [G loss: 0.738747]
8/8 [==============================] - 0s 4ms/step
7428 [D loss: 0.683312, acc.: 56.64%] [G loss: 0.729030]
8/8 [==============================] - 0s 4ms/step
7429 [D loss: 0.682786, acc.: 56.05%] [G loss: 0.756502]
8/8 [==============================] - 0s 4ms/step
7430 [D loss: 0.673530, acc.: 60.35%] [G loss: 0.764284]
8/8 [==============================] - 0s 4ms/step
7431 [D loss: 0.675267, acc.: 60.35%] [G loss: 0.752938]
8/8 [==============================] - 0s 4ms/step
7432 [D loss: 0.683712, acc.: 56.05%] [G loss: 0.749870]
8/8 [==============================] - 0s 4ms/step
7433 [D loss: 0.684737, acc.: 57.42%] [G loss: 0.743941]
8/8 [==============================] - 0s 4ms/step
7434 [D loss: 0.692345, acc.: 52.93%] [G loss: 0.728062]
8/8 [==============================] - 0s 4ms/step
7435 [D loss: 0.685548, acc.: 52.93%] [G loss: 0.735884]
8/8 [==============================] - 0s 4ms/step
7436 [D loss: 0.693600, acc.: 51.76%] [G loss: 0.726159]
8/8 [==============================] - 0s 4ms/step
7437 [D loss: 0.673757, acc.: 59.18%] [G loss: 0.736538]
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7438 [D loss: 0.678586, acc.: 56.64%] [G loss: 0.750461]
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7439 [D loss: 0.681113, acc.: 56.05%] [G loss: 0.742541]
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7440 [D loss: 0.675952, acc.: 57.42%] [G loss: 0.732998]
8/8 [==============================] - 0s 4ms/step
7441 [D loss: 0.676409, acc.: 58.79%] [G loss: 0.742633]
8/8 [==============================] - 0s 4ms/step
7442 [D loss: 0.684476, acc.: 56.64%] [G loss: 0.739850]
8/8 [==============================] - 0s 4ms/step
7443 [D loss: 0.682844, acc.: 54.69%] [G loss: 0.754568]
8/8 [==============================] - 0s 4ms/step
7444 [D loss: 0.678682, acc.: 58.20%] [G loss: 0.742544]
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7445 [D loss: 0.673274, acc.: 59.38%] [G loss: 0.750895]
8/8 [==============================] - 0s 4ms/step
7446 [D loss: 0.686756, acc.: 55.47%] [G loss: 0.741487]
8/8 [==============================] - 0s 4ms/step
7447 [D loss: 0.680034, acc.: 56.25%] [G loss: 0.751697]
8/8 [==============================] - 0s 4ms/step
7448 [D loss: 0.682202, acc.: 55.27%] [G loss: 0.744796]
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7449 [D loss: 0.683590, acc.: 55.47%] [G loss: 0.739856]
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7450 [D loss: 0.682828, acc.: 53.52%] [G loss: 0.741506]
1/1 [==============================] - 0s 18ms/step
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7451 [D loss: 0.669574, acc.: 59.18%] [G loss: 0.733218]
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7452 [D loss: 0.676145, acc.: 59.96%] [G loss: 0.739686]
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7453 [D loss: 0.679328, acc.: 55.66%] [G loss: 0.743060]
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7454 [D loss: 0.682662, acc.: 58.20%] [G loss: 0.756043]
8/8 [==============================] - 0s 4ms/step
7455 [D loss: 0.692941, acc.: 51.95%] [G loss: 0.745059]
8/8 [==============================] - 0s 4ms/step
7456 [D loss: 0.681483, acc.: 54.69%] [G loss: 0.740363]
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7457 [D loss: 0.677530, acc.: 58.79%] [G loss: 0.746941]
8/8 [==============================] - 0s 4ms/step
7458 [D loss: 0.677933, acc.: 57.62%] [G loss: 0.750879]
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7459 [D loss: 0.679947, acc.: 56.64%] [G loss: 0.727579]
8/8 [==============================] - 0s 4ms/step
7460 [D loss: 0.680666, acc.: 58.01%] [G loss: 0.751456]
8/8 [==============================] - 0s 4ms/step
7461 [D loss: 0.671810, acc.: 57.81%] [G loss: 0.741105]
8/8 [==============================] - 0s 4ms/step
7462 [D loss: 0.696324, acc.: 49.41%] [G loss: 0.742080]
8/8 [==============================] - 0s 4ms/step
7463 [D loss: 0.676951, acc.: 57.62%] [G loss: 0.750915]
8/8 [==============================] - 0s 4ms/step
7464 [D loss: 0.686590, acc.: 56.25%] [G loss: 0.742957]
8/8 [==============================] - 0s 4ms/step
7465 [D loss: 0.693437, acc.: 51.76%] [G loss: 0.735928]
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7466 [D loss: 0.680265, acc.: 59.18%] [G loss: 0.730700]
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7467 [D loss: 0.672371, acc.: 60.35%] [G loss: 0.742027]
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7468 [D loss: 0.685040, acc.: 56.64%] [G loss: 0.736008]
8/8 [==============================] - 0s 4ms/step
7469 [D loss: 0.686255, acc.: 54.69%] [G loss: 0.751307]
8/8 [==============================] - 0s 4ms/step
7470 [D loss: 0.689144, acc.: 52.34%] [G loss: 0.726297]
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7471 [D loss: 0.684275, acc.: 55.66%] [G loss: 0.743032]
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7472 [D loss: 0.682856, acc.: 54.30%] [G loss: 0.727724]
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7473 [D loss: 0.678319, acc.: 58.59%] [G loss: 0.757125]
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7474 [D loss: 0.692415, acc.: 52.54%] [G loss: 0.739188]
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7475 [D loss: 0.674385, acc.: 59.38%] [G loss: 0.733469]
8/8 [==============================] - 0s 4ms/step
7476 [D loss: 0.665064, acc.: 62.50%] [G loss: 0.755316]
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7477 [D loss: 0.676030, acc.: 57.81%] [G loss: 0.738216]
8/8 [==============================] - 0s 4ms/step
7478 [D loss: 0.683864, acc.: 54.69%] [G loss: 0.735492]
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7479 [D loss: 0.681619, acc.: 53.91%] [G loss: 0.741828]
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7480 [D loss: 0.689479, acc.: 54.88%] [G loss: 0.739565]
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7481 [D loss: 0.682918, acc.: 52.54%] [G loss: 0.746415]
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7482 [D loss: 0.686317, acc.: 54.49%] [G loss: 0.743300]
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7483 [D loss: 0.686227, acc.: 52.54%] [G loss: 0.744199]
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7484 [D loss: 0.679469, acc.: 58.20%] [G loss: 0.749975]
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7485 [D loss: 0.671473, acc.: 60.55%] [G loss: 0.742831]
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7486 [D loss: 0.675708, acc.: 58.01%] [G loss: 0.738395]
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7487 [D loss: 0.680336, acc.: 57.42%] [G loss: 0.747693]
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7488 [D loss: 0.687910, acc.: 54.49%] [G loss: 0.721449]
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7489 [D loss: 0.682231, acc.: 58.59%] [G loss: 0.743204]
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7490 [D loss: 0.690625, acc.: 54.30%] [G loss: 0.720316]
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7491 [D loss: 0.671746, acc.: 56.45%] [G loss: 0.741013]
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7492 [D loss: 0.680524, acc.: 54.88%] [G loss: 0.741815]
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7493 [D loss: 0.675061, acc.: 58.59%] [G loss: 0.739806]
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7494 [D loss: 0.674251, acc.: 57.03%] [G loss: 0.751505]
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7495 [D loss: 0.667265, acc.: 62.70%] [G loss: 0.737941]
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7496 [D loss: 0.673942, acc.: 58.40%] [G loss: 0.736012]
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7497 [D loss: 0.682839, acc.: 58.59%] [G loss: 0.739163]
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7498 [D loss: 0.677921, acc.: 56.84%] [G loss: 0.744194]
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7499 [D loss: 0.680730, acc.: 56.05%] [G loss: 0.744249]
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7500 [D loss: 0.682906, acc.: 56.25%] [G loss: 0.748258]
1/1 [==============================] - 0s 17ms/step
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7501 [D loss: 0.675301, acc.: 54.88%] [G loss: 0.742804]
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7502 [D loss: 0.677825, acc.: 57.23%] [G loss: 0.765873]
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7503 [D loss: 0.672892, acc.: 58.98%] [G loss: 0.741667]
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7504 [D loss: 0.671851, acc.: 59.57%] [G loss: 0.736099]
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7505 [D loss: 0.679550, acc.: 55.66%] [G loss: 0.719236]
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7506 [D loss: 0.683784, acc.: 56.25%] [G loss: 0.721275]
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7507 [D loss: 0.685422, acc.: 54.88%] [G loss: 0.724070]
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7508 [D loss: 0.691431, acc.: 53.91%] [G loss: 0.744274]
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7509 [D loss: 0.674191, acc.: 57.81%] [G loss: 0.763147]
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7510 [D loss: 0.676956, acc.: 56.45%] [G loss: 0.746823]
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7511 [D loss: 0.670732, acc.: 60.35%] [G loss: 0.740446]
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7512 [D loss: 0.670542, acc.: 58.20%] [G loss: 0.730590]
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7513 [D loss: 0.679976, acc.: 57.23%] [G loss: 0.722832]
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7514 [D loss: 0.692368, acc.: 51.56%] [G loss: 0.730788]
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7515 [D loss: 0.703366, acc.: 48.83%] [G loss: 0.724125]
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7516 [D loss: 0.693540, acc.: 51.76%] [G loss: 0.760000]
8/8 [==============================] - 0s 4ms/step
7517 [D loss: 0.675925, acc.: 56.64%] [G loss: 0.755911]
8/8 [==============================] - 0s 4ms/step
7518 [D loss: 0.677593, acc.: 55.27%] [G loss: 0.754866]
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7519 [D loss: 0.669412, acc.: 58.59%] [G loss: 0.762279]
8/8 [==============================] - 0s 4ms/step
7520 [D loss: 0.681698, acc.: 54.30%] [G loss: 0.741216]
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7521 [D loss: 0.691150, acc.: 54.30%] [G loss: 0.747234]
8/8 [==============================] - 0s 4ms/step
7522 [D loss: 0.683170, acc.: 53.71%] [G loss: 0.717637]
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7523 [D loss: 0.684738, acc.: 54.10%] [G loss: 0.730307]
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7524 [D loss: 0.683709, acc.: 54.49%] [G loss: 0.739414]
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7525 [D loss: 0.685923, acc.: 54.30%] [G loss: 0.755752]
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7526 [D loss: 0.677053, acc.: 57.62%] [G loss: 0.751148]
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7527 [D loss: 0.680675, acc.: 58.20%] [G loss: 0.741158]
8/8 [==============================] - 0s 4ms/step
7528 [D loss: 0.685810, acc.: 57.03%] [G loss: 0.743825]
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7529 [D loss: 0.664851, acc.: 62.89%] [G loss: 0.735704]
8/8 [==============================] - 0s 4ms/step
7530 [D loss: 0.685011, acc.: 53.91%] [G loss: 0.739839]
8/8 [==============================] - 0s 4ms/step
7531 [D loss: 0.676251, acc.: 57.81%] [G loss: 0.735574]
8/8 [==============================] - 0s 4ms/step
7532 [D loss: 0.677999, acc.: 55.27%] [G loss: 0.755298]
8/8 [==============================] - 0s 4ms/step
7533 [D loss: 0.670599, acc.: 59.57%] [G loss: 0.764141]
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7534 [D loss: 0.669605, acc.: 57.03%] [G loss: 0.759713]
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7535 [D loss: 0.668301, acc.: 60.16%] [G loss: 0.760334]
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7536 [D loss: 0.668049, acc.: 56.84%] [G loss: 0.756688]
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7537 [D loss: 0.674011, acc.: 59.77%] [G loss: 0.734947]
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7538 [D loss: 0.677647, acc.: 58.59%] [G loss: 0.721581]
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7539 [D loss: 0.703818, acc.: 48.44%] [G loss: 0.724485]
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7540 [D loss: 0.674767, acc.: 57.81%] [G loss: 0.725434]
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7541 [D loss: 0.682580, acc.: 54.88%] [G loss: 0.732795]
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7542 [D loss: 0.670344, acc.: 61.52%] [G loss: 0.752325]
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7543 [D loss: 0.678410, acc.: 58.40%] [G loss: 0.747247]
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7544 [D loss: 0.682876, acc.: 56.25%] [G loss: 0.746443]
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7545 [D loss: 0.680127, acc.: 57.81%] [G loss: 0.750513]
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7546 [D loss: 0.680867, acc.: 58.01%] [G loss: 0.746012]
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7547 [D loss: 0.683035, acc.: 53.32%] [G loss: 0.744584]
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7548 [D loss: 0.677409, acc.: 56.25%] [G loss: 0.735697]
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7549 [D loss: 0.687581, acc.: 53.12%] [G loss: 0.742869]
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7550 [D loss: 0.672526, acc.: 57.81%] [G loss: 0.751966]
1/1 [==============================] - 0s 19ms/step
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7551 [D loss: 0.677264, acc.: 58.20%] [G loss: 0.754668]
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7552 [D loss: 0.672292, acc.: 58.20%] [G loss: 0.770259]
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7553 [D loss: 0.669585, acc.: 58.20%] [G loss: 0.738447]
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7554 [D loss: 0.680078, acc.: 55.66%] [G loss: 0.738948]
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7555 [D loss: 0.682766, acc.: 54.88%] [G loss: 0.725919]
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7556 [D loss: 0.683274, acc.: 52.15%] [G loss: 0.746262]
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7557 [D loss: 0.678254, acc.: 56.05%] [G loss: 0.720908]
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7558 [D loss: 0.684822, acc.: 55.66%] [G loss: 0.738544]
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7559 [D loss: 0.688955, acc.: 53.52%] [G loss: 0.754083]
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7560 [D loss: 0.692084, acc.: 52.73%] [G loss: 0.753227]
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7561 [D loss: 0.667540, acc.: 58.98%] [G loss: 0.763791]
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7562 [D loss: 0.678967, acc.: 56.45%] [G loss: 0.754569]
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7563 [D loss: 0.673777, acc.: 57.03%] [G loss: 0.746515]
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7564 [D loss: 0.676809, acc.: 57.03%] [G loss: 0.729112]
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7565 [D loss: 0.684153, acc.: 53.52%] [G loss: 0.737104]
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7566 [D loss: 0.694432, acc.: 50.39%] [G loss: 0.736939]
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7567 [D loss: 0.685010, acc.: 52.54%] [G loss: 0.753981]
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7568 [D loss: 0.667334, acc.: 59.77%] [G loss: 0.763325]
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7569 [D loss: 0.686134, acc.: 53.91%] [G loss: 0.765206]
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7570 [D loss: 0.682519, acc.: 56.05%] [G loss: 0.751547]
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7571 [D loss: 0.684798, acc.: 56.25%] [G loss: 0.737664]
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7572 [D loss: 0.680733, acc.: 55.86%] [G loss: 0.737960]
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7573 [D loss: 0.685920, acc.: 55.27%] [G loss: 0.736916]
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7574 [D loss: 0.691301, acc.: 52.15%] [G loss: 0.734311]
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7575 [D loss: 0.676620, acc.: 58.98%] [G loss: 0.746349]
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7576 [D loss: 0.680343, acc.: 55.47%] [G loss: 0.741776]
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7577 [D loss: 0.681478, acc.: 54.49%] [G loss: 0.747952]
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7578 [D loss: 0.690657, acc.: 53.91%] [G loss: 0.754428]
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7579 [D loss: 0.674010, acc.: 60.55%] [G loss: 0.744723]
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7580 [D loss: 0.685692, acc.: 54.69%] [G loss: 0.754049]
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7581 [D loss: 0.690682, acc.: 52.93%] [G loss: 0.743759]
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7582 [D loss: 0.678141, acc.: 56.64%] [G loss: 0.739350]
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7583 [D loss: 0.675593, acc.: 56.45%] [G loss: 0.748273]
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7584 [D loss: 0.683941, acc.: 54.10%] [G loss: 0.758024]
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7585 [D loss: 0.673009, acc.: 57.03%] [G loss: 0.731190]
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7586 [D loss: 0.687220, acc.: 52.15%] [G loss: 0.744538]
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7587 [D loss: 0.684183, acc.: 56.45%] [G loss: 0.745072]
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7588 [D loss: 0.679073, acc.: 58.98%] [G loss: 0.741927]
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7589 [D loss: 0.683525, acc.: 57.81%] [G loss: 0.737706]
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7590 [D loss: 0.681503, acc.: 56.45%] [G loss: 0.748830]
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7591 [D loss: 0.686950, acc.: 54.49%] [G loss: 0.734592]
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7592 [D loss: 0.675648, acc.: 58.40%] [G loss: 0.739660]
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7593 [D loss: 0.662417, acc.: 61.91%] [G loss: 0.738854]
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7594 [D loss: 0.675513, acc.: 57.62%] [G loss: 0.744337]
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7595 [D loss: 0.682461, acc.: 55.66%] [G loss: 0.741127]
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7596 [D loss: 0.681504, acc.: 57.03%] [G loss: 0.739731]
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7597 [D loss: 0.685016, acc.: 54.30%] [G loss: 0.740060]
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7598 [D loss: 0.684734, acc.: 56.25%] [G loss: 0.733781]
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7599 [D loss: 0.691412, acc.: 51.95%] [G loss: 0.753765]
8/8 [==============================] - 0s 4ms/step
7600 [D loss: 0.678519, acc.: 57.62%] [G loss: 0.753033]
1/1 [==============================] - 0s 17ms/step
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7601 [D loss: 0.682378, acc.: 59.18%] [G loss: 0.755103]
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7602 [D loss: 0.678259, acc.: 56.64%] [G loss: 0.754250]
8/8 [==============================] - 0s 4ms/step
7603 [D loss: 0.678572, acc.: 58.79%] [G loss: 0.752277]
8/8 [==============================] - 0s 4ms/step
7604 [D loss: 0.677576, acc.: 56.84%] [G loss: 0.737157]
8/8 [==============================] - 0s 4ms/step
7605 [D loss: 0.686510, acc.: 54.49%] [G loss: 0.732454]
8/8 [==============================] - 0s 4ms/step
7606 [D loss: 0.678978, acc.: 56.25%] [G loss: 0.743378]
8/8 [==============================] - 0s 4ms/step
7607 [D loss: 0.670651, acc.: 58.79%] [G loss: 0.741210]
8/8 [==============================] - 0s 4ms/step
7608 [D loss: 0.681708, acc.: 51.56%] [G loss: 0.723925]
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7609 [D loss: 0.683369, acc.: 53.52%] [G loss: 0.740647]
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7610 [D loss: 0.660248, acc.: 64.06%] [G loss: 0.746008]
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7611 [D loss: 0.682393, acc.: 54.69%] [G loss: 0.756651]
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7612 [D loss: 0.670229, acc.: 57.62%] [G loss: 0.740598]
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7613 [D loss: 0.674398, acc.: 57.81%] [G loss: 0.736825]
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7614 [D loss: 0.679630, acc.: 57.23%] [G loss: 0.742306]
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7615 [D loss: 0.683814, acc.: 55.86%] [G loss: 0.722190]
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7616 [D loss: 0.686865, acc.: 54.30%] [G loss: 0.750980]
8/8 [==============================] - 0s 4ms/step
7617 [D loss: 0.694265, acc.: 51.76%] [G loss: 0.734723]
8/8 [==============================] - 0s 4ms/step
7618 [D loss: 0.680228, acc.: 54.69%] [G loss: 0.753180]
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7619 [D loss: 0.674720, acc.: 60.16%] [G loss: 0.743448]
8/8 [==============================] - 0s 4ms/step
7620 [D loss: 0.678042, acc.: 56.25%] [G loss: 0.752777]
8/8 [==============================] - 0s 4ms/step
7621 [D loss: 0.669049, acc.: 59.57%] [G loss: 0.740509]
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7622 [D loss: 0.680051, acc.: 56.84%] [G loss: 0.745381]
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7623 [D loss: 0.681809, acc.: 56.05%] [G loss: 0.739127]
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7624 [D loss: 0.680361, acc.: 54.49%] [G loss: 0.747458]
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7625 [D loss: 0.688151, acc.: 54.10%] [G loss: 0.745163]
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7626 [D loss: 0.675485, acc.: 58.01%] [G loss: 0.738494]
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7627 [D loss: 0.679856, acc.: 55.86%] [G loss: 0.735793]
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7628 [D loss: 0.691837, acc.: 54.69%] [G loss: 0.737479]
8/8 [==============================] - 0s 4ms/step
7629 [D loss: 0.688455, acc.: 55.08%] [G loss: 0.741456]
8/8 [==============================] - 0s 4ms/step
7630 [D loss: 0.685012, acc.: 54.10%] [G loss: 0.744262]
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7631 [D loss: 0.677671, acc.: 56.05%] [G loss: 0.737476]
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7632 [D loss: 0.671653, acc.: 60.94%] [G loss: 0.724998]
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7633 [D loss: 0.671632, acc.: 59.96%] [G loss: 0.739759]
8/8 [==============================] - 0s 4ms/step
7634 [D loss: 0.681625, acc.: 57.42%] [G loss: 0.742301]
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7635 [D loss: 0.678688, acc.: 56.64%] [G loss: 0.751973]
8/8 [==============================] - 0s 4ms/step
7636 [D loss: 0.678127, acc.: 58.01%] [G loss: 0.748665]
8/8 [==============================] - 0s 4ms/step
7637 [D loss: 0.675903, acc.: 58.79%] [G loss: 0.730722]
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7638 [D loss: 0.674216, acc.: 58.01%] [G loss: 0.741255]
8/8 [==============================] - 0s 4ms/step
7639 [D loss: 0.683473, acc.: 53.32%] [G loss: 0.727120]
8/8 [==============================] - 0s 4ms/step
7640 [D loss: 0.672824, acc.: 57.62%] [G loss: 0.739025]
8/8 [==============================] - 0s 4ms/step
7641 [D loss: 0.677606, acc.: 57.81%] [G loss: 0.722537]
8/8 [==============================] - 0s 4ms/step
7642 [D loss: 0.682475, acc.: 55.47%] [G loss: 0.733007]
8/8 [==============================] - 0s 4ms/step
7643 [D loss: 0.681182, acc.: 56.45%] [G loss: 0.727396]
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7644 [D loss: 0.682399, acc.: 56.25%] [G loss: 0.735116]
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7645 [D loss: 0.679750, acc.: 56.25%] [G loss: 0.738461]
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7646 [D loss: 0.684660, acc.: 56.05%] [G loss: 0.742157]
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7647 [D loss: 0.667182, acc.: 59.77%] [G loss: 0.752027]
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7648 [D loss: 0.672963, acc.: 62.50%] [G loss: 0.739707]
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7649 [D loss: 0.680595, acc.: 55.27%] [G loss: 0.745702]
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7650 [D loss: 0.679821, acc.: 55.66%] [G loss: 0.732555]
1/1 [==============================] - 0s 18ms/step
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7651 [D loss: 0.671349, acc.: 58.01%] [G loss: 0.721260]
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7652 [D loss: 0.687289, acc.: 55.47%] [G loss: 0.749768]
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7653 [D loss: 0.687436, acc.: 55.66%] [G loss: 0.736899]
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7654 [D loss: 0.685960, acc.: 53.71%] [G loss: 0.746127]
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7655 [D loss: 0.686980, acc.: 53.12%] [G loss: 0.760931]
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7656 [D loss: 0.667367, acc.: 60.74%] [G loss: 0.772941]
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7657 [D loss: 0.678496, acc.: 55.08%] [G loss: 0.779537]
8/8 [==============================] - 0s 4ms/step
7658 [D loss: 0.680905, acc.: 54.69%] [G loss: 0.769707]
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7659 [D loss: 0.670159, acc.: 59.38%] [G loss: 0.744789]
8/8 [==============================] - 0s 4ms/step
7660 [D loss: 0.684329, acc.: 57.23%] [G loss: 0.729282]
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7661 [D loss: 0.692129, acc.: 51.37%] [G loss: 0.725679]
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7662 [D loss: 0.699350, acc.: 49.22%] [G loss: 0.725763]
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7663 [D loss: 0.685977, acc.: 52.73%] [G loss: 0.731350]
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7664 [D loss: 0.678113, acc.: 57.42%] [G loss: 0.756312]
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7665 [D loss: 0.682175, acc.: 55.47%] [G loss: 0.754814]
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7666 [D loss: 0.668500, acc.: 60.55%] [G loss: 0.753500]
8/8 [==============================] - 0s 4ms/step
7667 [D loss: 0.676202, acc.: 56.45%] [G loss: 0.745683]
8/8 [==============================] - 0s 4ms/step
7668 [D loss: 0.669952, acc.: 57.62%] [G loss: 0.728391]
8/8 [==============================] - 0s 4ms/step
7669 [D loss: 0.691939, acc.: 51.95%] [G loss: 0.726393]
8/8 [==============================] - 0s 4ms/step
7670 [D loss: 0.669728, acc.: 59.57%] [G loss: 0.744710]
8/8 [==============================] - 0s 4ms/step
7671 [D loss: 0.688365, acc.: 55.27%] [G loss: 0.728982]
8/8 [==============================] - 0s 4ms/step
7672 [D loss: 0.683743, acc.: 55.66%] [G loss: 0.753999]
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7673 [D loss: 0.675085, acc.: 57.81%] [G loss: 0.770287]
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7674 [D loss: 0.682378, acc.: 57.23%] [G loss: 0.773252]
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7675 [D loss: 0.667213, acc.: 60.94%] [G loss: 0.764416]
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7676 [D loss: 0.674418, acc.: 57.81%] [G loss: 0.740514]
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7677 [D loss: 0.679897, acc.: 58.98%] [G loss: 0.739674]
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7678 [D loss: 0.672233, acc.: 57.62%] [G loss: 0.731371]
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7679 [D loss: 0.692448, acc.: 51.56%] [G loss: 0.718176]
8/8 [==============================] - 0s 4ms/step
7680 [D loss: 0.684223, acc.: 52.93%] [G loss: 0.747862]
8/8 [==============================] - 0s 4ms/step
7681 [D loss: 0.674391, acc.: 57.03%] [G loss: 0.758856]
8/8 [==============================] - 0s 4ms/step
7682 [D loss: 0.655497, acc.: 63.87%] [G loss: 0.763726]
8/8 [==============================] - 0s 4ms/step
7683 [D loss: 0.677505, acc.: 57.81%] [G loss: 0.754938]
8/8 [==============================] - 0s 4ms/step
7684 [D loss: 0.669516, acc.: 58.79%] [G loss: 0.749651]
8/8 [==============================] - 0s 4ms/step
7685 [D loss: 0.667543, acc.: 63.28%] [G loss: 0.718859]
8/8 [==============================] - 0s 4ms/step
7686 [D loss: 0.702415, acc.: 50.20%] [G loss: 0.726090]
8/8 [==============================] - 0s 4ms/step
7687 [D loss: 0.694515, acc.: 51.37%] [G loss: 0.735631]
8/8 [==============================] - 0s 4ms/step
7688 [D loss: 0.688984, acc.: 53.52%] [G loss: 0.733020]
8/8 [==============================] - 0s 4ms/step
7689 [D loss: 0.683573, acc.: 56.45%] [G loss: 0.754236]
8/8 [==============================] - 0s 4ms/step
7690 [D loss: 0.673674, acc.: 60.55%] [G loss: 0.789629]
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7691 [D loss: 0.671559, acc.: 56.64%] [G loss: 0.777432]
8/8 [==============================] - 0s 4ms/step
7692 [D loss: 0.658073, acc.: 63.48%] [G loss: 0.762873]
8/8 [==============================] - 0s 4ms/step
7693 [D loss: 0.673929, acc.: 60.74%] [G loss: 0.732920]
8/8 [==============================] - 0s 4ms/step
7694 [D loss: 0.659388, acc.: 60.16%] [G loss: 0.741573]
8/8 [==============================] - 0s 4ms/step
7695 [D loss: 0.671199, acc.: 60.55%] [G loss: 0.721501]
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7696 [D loss: 0.696173, acc.: 53.52%] [G loss: 0.704389]
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7697 [D loss: 0.682140, acc.: 53.91%] [G loss: 0.686310]
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7698 [D loss: 0.681465, acc.: 56.84%] [G loss: 0.721032]
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7699 [D loss: 0.683599, acc.: 56.64%] [G loss: 0.741293]
8/8 [==============================] - 0s 4ms/step
7700 [D loss: 0.682710, acc.: 57.42%] [G loss: 0.748402]
1/1 [==============================] - 0s 20ms/step
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7701 [D loss: 0.673533, acc.: 59.18%] [G loss: 0.752174]
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7702 [D loss: 0.672999, acc.: 58.59%] [G loss: 0.741309]
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7703 [D loss: 0.685077, acc.: 55.08%] [G loss: 0.748543]
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7704 [D loss: 0.684427, acc.: 54.49%] [G loss: 0.743567]
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7705 [D loss: 0.686222, acc.: 52.34%] [G loss: 0.739484]
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7706 [D loss: 0.679932, acc.: 55.08%] [G loss: 0.747646]
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7707 [D loss: 0.679241, acc.: 55.08%] [G loss: 0.758923]
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7708 [D loss: 0.677592, acc.: 56.64%] [G loss: 0.760704]
8/8 [==============================] - 0s 4ms/step
7709 [D loss: 0.680501, acc.: 55.27%] [G loss: 0.766354]
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7710 [D loss: 0.678416, acc.: 56.45%] [G loss: 0.748547]
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7711 [D loss: 0.677382, acc.: 59.77%] [G loss: 0.745420]
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7712 [D loss: 0.679593, acc.: 55.66%] [G loss: 0.745034]
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7713 [D loss: 0.685599, acc.: 54.30%] [G loss: 0.744636]
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7714 [D loss: 0.684539, acc.: 58.20%] [G loss: 0.747608]
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7715 [D loss: 0.666385, acc.: 62.89%] [G loss: 0.751999]
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7716 [D loss: 0.677542, acc.: 56.64%] [G loss: 0.760430]
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7717 [D loss: 0.676222, acc.: 56.45%] [G loss: 0.741958]
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7718 [D loss: 0.664701, acc.: 60.16%] [G loss: 0.738189]
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7719 [D loss: 0.688497, acc.: 55.27%] [G loss: 0.744444]
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7720 [D loss: 0.689574, acc.: 54.10%] [G loss: 0.752358]
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7721 [D loss: 0.689376, acc.: 52.34%] [G loss: 0.737045]
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7722 [D loss: 0.678962, acc.: 58.20%] [G loss: 0.742721]
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7723 [D loss: 0.680255, acc.: 56.64%] [G loss: 0.744245]
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7724 [D loss: 0.678447, acc.: 58.98%] [G loss: 0.761479]
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7725 [D loss: 0.681536, acc.: 54.69%] [G loss: 0.741410]
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7726 [D loss: 0.670103, acc.: 60.16%] [G loss: 0.741060]
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7727 [D loss: 0.672079, acc.: 60.94%] [G loss: 0.734289]
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7728 [D loss: 0.673424, acc.: 61.72%] [G loss: 0.737761]
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7729 [D loss: 0.681477, acc.: 57.23%] [G loss: 0.725989]
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7730 [D loss: 0.674904, acc.: 58.40%] [G loss: 0.748230]
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7731 [D loss: 0.678598, acc.: 56.64%] [G loss: 0.755711]
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7732 [D loss: 0.684669, acc.: 55.08%] [G loss: 0.748486]
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7733 [D loss: 0.678644, acc.: 56.45%] [G loss: 0.751281]
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7734 [D loss: 0.685612, acc.: 55.08%] [G loss: 0.748853]
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7735 [D loss: 0.678838, acc.: 55.47%] [G loss: 0.727081]
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7736 [D loss: 0.689812, acc.: 52.73%] [G loss: 0.734743]
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7737 [D loss: 0.680991, acc.: 55.86%] [G loss: 0.740095]
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7738 [D loss: 0.679016, acc.: 55.47%] [G loss: 0.743615]
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7739 [D loss: 0.680263, acc.: 56.25%] [G loss: 0.743616]
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7740 [D loss: 0.676490, acc.: 57.62%] [G loss: 0.754323]
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7741 [D loss: 0.679372, acc.: 55.27%] [G loss: 0.728572]
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7742 [D loss: 0.679587, acc.: 58.01%] [G loss: 0.766879]
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7743 [D loss: 0.671589, acc.: 60.16%] [G loss: 0.766155]
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7744 [D loss: 0.671000, acc.: 57.23%] [G loss: 0.750483]
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7745 [D loss: 0.684278, acc.: 53.91%] [G loss: 0.745605]
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7746 [D loss: 0.680467, acc.: 57.03%] [G loss: 0.724097]
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7747 [D loss: 0.676104, acc.: 57.42%] [G loss: 0.724602]
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7748 [D loss: 0.674964, acc.: 59.18%] [G loss: 0.747964]
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7749 [D loss: 0.682696, acc.: 54.49%] [G loss: 0.734396]
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7750 [D loss: 0.684947, acc.: 56.45%] [G loss: 0.738555]
1/1 [==============================] - 0s 17ms/step
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7751 [D loss: 0.674222, acc.: 58.20%] [G loss: 0.743080]
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7752 [D loss: 0.677723, acc.: 56.25%] [G loss: 0.727013]
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7753 [D loss: 0.676072, acc.: 56.84%] [G loss: 0.729226]
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7754 [D loss: 0.676850, acc.: 58.79%] [G loss: 0.736680]
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7755 [D loss: 0.698602, acc.: 48.44%] [G loss: 0.738332]
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7756 [D loss: 0.686027, acc.: 53.12%] [G loss: 0.751379]
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7757 [D loss: 0.682586, acc.: 56.45%] [G loss: 0.749447]
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7758 [D loss: 0.672179, acc.: 58.59%] [G loss: 0.753273]
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7759 [D loss: 0.677785, acc.: 57.03%] [G loss: 0.762142]
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7760 [D loss: 0.664465, acc.: 60.55%] [G loss: 0.745279]
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7761 [D loss: 0.680069, acc.: 58.01%] [G loss: 0.750053]
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7762 [D loss: 0.679543, acc.: 56.05%] [G loss: 0.752796]
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7763 [D loss: 0.684593, acc.: 57.81%] [G loss: 0.726083]
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7764 [D loss: 0.682782, acc.: 54.69%] [G loss: 0.714374]
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7765 [D loss: 0.678955, acc.: 57.03%] [G loss: 0.743836]
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7766 [D loss: 0.673200, acc.: 57.81%] [G loss: 0.742922]
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7767 [D loss: 0.667420, acc.: 58.20%] [G loss: 0.752810]
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7768 [D loss: 0.668690, acc.: 59.57%] [G loss: 0.742463]
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7769 [D loss: 0.678965, acc.: 57.81%] [G loss: 0.737445]
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7770 [D loss: 0.683640, acc.: 53.91%] [G loss: 0.726556]
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7771 [D loss: 0.672194, acc.: 58.40%] [G loss: 0.728134]
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7772 [D loss: 0.673541, acc.: 59.77%] [G loss: 0.723259]
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7773 [D loss: 0.681578, acc.: 56.25%] [G loss: 0.745938]
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7774 [D loss: 0.684029, acc.: 55.08%] [G loss: 0.750130]
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7775 [D loss: 0.662958, acc.: 60.94%] [G loss: 0.771582]
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7776 [D loss: 0.664061, acc.: 62.11%] [G loss: 0.770543]
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7777 [D loss: 0.663469, acc.: 60.35%] [G loss: 0.754393]
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7778 [D loss: 0.679330, acc.: 58.20%] [G loss: 0.724721]
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7779 [D loss: 0.677976, acc.: 56.45%] [G loss: 0.707213]
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7780 [D loss: 0.696974, acc.: 51.37%] [G loss: 0.720835]
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7781 [D loss: 0.680383, acc.: 55.27%] [G loss: 0.713453]
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7782 [D loss: 0.683302, acc.: 57.62%] [G loss: 0.730488]
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7783 [D loss: 0.679713, acc.: 56.84%] [G loss: 0.768829]
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7784 [D loss: 0.666691, acc.: 59.77%] [G loss: 0.756134]
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7785 [D loss: 0.662204, acc.: 59.18%] [G loss: 0.752257]
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7786 [D loss: 0.665494, acc.: 59.77%] [G loss: 0.749587]
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7787 [D loss: 0.675107, acc.: 58.01%] [G loss: 0.722345]
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7788 [D loss: 0.681337, acc.: 56.84%] [G loss: 0.729309]
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7789 [D loss: 0.684153, acc.: 55.86%] [G loss: 0.732474]
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7790 [D loss: 0.687890, acc.: 54.10%] [G loss: 0.744186]
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7791 [D loss: 0.689983, acc.: 52.54%] [G loss: 0.761006]
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7792 [D loss: 0.675630, acc.: 60.16%] [G loss: 0.778519]
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7793 [D loss: 0.678485, acc.: 57.42%] [G loss: 0.794354]
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7794 [D loss: 0.661969, acc.: 62.50%] [G loss: 0.792230]
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7795 [D loss: 0.656640, acc.: 64.26%] [G loss: 0.758794]
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7796 [D loss: 0.662528, acc.: 60.16%] [G loss: 0.730133]
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7797 [D loss: 0.675528, acc.: 58.98%] [G loss: 0.708329]
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7798 [D loss: 0.691224, acc.: 54.49%] [G loss: 0.725707]
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7799 [D loss: 0.670897, acc.: 59.77%] [G loss: 0.739171]
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7800 [D loss: 0.690412, acc.: 54.49%] [G loss: 0.744357]
1/1 [==============================] - 0s 19ms/step
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7801 [D loss: 0.672107, acc.: 57.81%] [G loss: 0.762789]
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7802 [D loss: 0.674965, acc.: 56.84%] [G loss: 0.804331]
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7803 [D loss: 0.667495, acc.: 60.74%] [G loss: 0.761495]
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7804 [D loss: 0.670152, acc.: 57.03%] [G loss: 0.768458]
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7805 [D loss: 0.684103, acc.: 56.45%] [G loss: 0.728305]
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7806 [D loss: 0.684895, acc.: 52.93%] [G loss: 0.725841]
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7807 [D loss: 0.678958, acc.: 56.64%] [G loss: 0.718862]
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7808 [D loss: 0.674767, acc.: 56.45%] [G loss: 0.735589]
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7809 [D loss: 0.681523, acc.: 58.79%] [G loss: 0.753137]
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7810 [D loss: 0.668827, acc.: 58.40%] [G loss: 0.774505]
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7811 [D loss: 0.663543, acc.: 59.38%] [G loss: 0.773036]
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7812 [D loss: 0.660736, acc.: 58.98%] [G loss: 0.763561]
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7813 [D loss: 0.682565, acc.: 57.42%] [G loss: 0.748144]
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7814 [D loss: 0.652217, acc.: 63.28%] [G loss: 0.744940]
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7815 [D loss: 0.681723, acc.: 58.01%] [G loss: 0.738026]
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7816 [D loss: 0.671292, acc.: 59.57%] [G loss: 0.733554]
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7817 [D loss: 0.694223, acc.: 53.52%] [G loss: 0.732092]
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7818 [D loss: 0.674750, acc.: 58.40%] [G loss: 0.746426]
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7819 [D loss: 0.680908, acc.: 57.03%] [G loss: 0.749285]
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7820 [D loss: 0.670972, acc.: 57.62%] [G loss: 0.739402]
8/8 [==============================] - 0s 4ms/step
7821 [D loss: 0.678428, acc.: 58.20%] [G loss: 0.766534]
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7822 [D loss: 0.675619, acc.: 57.23%] [G loss: 0.768032]
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7823 [D loss: 0.678427, acc.: 56.84%] [G loss: 0.733105]
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7824 [D loss: 0.689391, acc.: 54.69%] [G loss: 0.737306]
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7825 [D loss: 0.680018, acc.: 58.79%] [G loss: 0.749845]
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7826 [D loss: 0.677643, acc.: 56.64%] [G loss: 0.758172]
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7827 [D loss: 0.678132, acc.: 57.42%] [G loss: 0.768377]
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7828 [D loss: 0.673626, acc.: 56.45%] [G loss: 0.779523]
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7829 [D loss: 0.677976, acc.: 54.30%] [G loss: 0.782359]
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7830 [D loss: 0.677029, acc.: 54.88%] [G loss: 0.773069]
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7831 [D loss: 0.678845, acc.: 53.71%] [G loss: 0.733555]
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7832 [D loss: 0.675214, acc.: 58.98%] [G loss: 0.734697]
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7833 [D loss: 0.683948, acc.: 54.30%] [G loss: 0.740096]
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7834 [D loss: 0.686283, acc.: 53.91%] [G loss: 0.735738]
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7835 [D loss: 0.690852, acc.: 53.12%] [G loss: 0.747666]
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7836 [D loss: 0.665333, acc.: 61.72%] [G loss: 0.746917]
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7837 [D loss: 0.668716, acc.: 60.35%] [G loss: 0.742576]
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7838 [D loss: 0.681097, acc.: 55.86%] [G loss: 0.762650]
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7839 [D loss: 0.678491, acc.: 57.81%] [G loss: 0.736379]
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7840 [D loss: 0.677284, acc.: 57.81%] [G loss: 0.749535]
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7841 [D loss: 0.683590, acc.: 55.08%] [G loss: 0.738596]
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7842 [D loss: 0.679208, acc.: 56.05%] [G loss: 0.743910]
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7843 [D loss: 0.679188, acc.: 58.20%] [G loss: 0.745215]
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7844 [D loss: 0.675598, acc.: 58.59%] [G loss: 0.744416]
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7845 [D loss: 0.680453, acc.: 56.05%] [G loss: 0.730928]
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7846 [D loss: 0.670266, acc.: 59.18%] [G loss: 0.739702]
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7847 [D loss: 0.671383, acc.: 58.79%] [G loss: 0.743827]
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7848 [D loss: 0.678149, acc.: 57.62%] [G loss: 0.754159]
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7849 [D loss: 0.671313, acc.: 58.98%] [G loss: 0.748608]
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7850 [D loss: 0.677006, acc.: 55.66%] [G loss: 0.736815]
1/1 [==============================] - 0s 20ms/step
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7851 [D loss: 0.682602, acc.: 55.66%] [G loss: 0.736211]
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7852 [D loss: 0.687136, acc.: 53.71%] [G loss: 0.753935]
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7853 [D loss: 0.678124, acc.: 55.47%] [G loss: 0.753101]
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7854 [D loss: 0.683425, acc.: 55.66%] [G loss: 0.748016]
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7855 [D loss: 0.670375, acc.: 61.72%] [G loss: 0.751561]
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7856 [D loss: 0.673928, acc.: 56.05%] [G loss: 0.745814]
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7857 [D loss: 0.676864, acc.: 55.08%] [G loss: 0.745121]
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7858 [D loss: 0.672062, acc.: 59.77%] [G loss: 0.732563]
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7859 [D loss: 0.671804, acc.: 58.98%] [G loss: 0.752754]
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7860 [D loss: 0.678661, acc.: 59.96%] [G loss: 0.745041]
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7861 [D loss: 0.687043, acc.: 55.86%] [G loss: 0.750975]
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7862 [D loss: 0.674952, acc.: 57.03%] [G loss: 0.758403]
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7863 [D loss: 0.675034, acc.: 56.84%] [G loss: 0.751507]
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7864 [D loss: 0.688180, acc.: 54.88%] [G loss: 0.749176]
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7865 [D loss: 0.685517, acc.: 53.12%] [G loss: 0.754072]
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7866 [D loss: 0.682129, acc.: 55.66%] [G loss: 0.746406]
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7867 [D loss: 0.660260, acc.: 61.33%] [G loss: 0.734828]
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7868 [D loss: 0.673202, acc.: 59.77%] [G loss: 0.734147]
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7869 [D loss: 0.683211, acc.: 55.27%] [G loss: 0.743711]
8/8 [==============================] - 0s 4ms/step
7870 [D loss: 0.689917, acc.: 53.32%] [G loss: 0.742883]
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7871 [D loss: 0.679677, acc.: 54.88%] [G loss: 0.742275]
8/8 [==============================] - 0s 4ms/step
7872 [D loss: 0.679104, acc.: 55.66%] [G loss: 0.752087]
8/8 [==============================] - 0s 4ms/step
7873 [D loss: 0.685093, acc.: 54.49%] [G loss: 0.758239]
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7874 [D loss: 0.663167, acc.: 63.48%] [G loss: 0.759183]
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7875 [D loss: 0.684306, acc.: 55.27%] [G loss: 0.760139]
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7876 [D loss: 0.675824, acc.: 58.01%] [G loss: 0.732453]
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7877 [D loss: 0.684518, acc.: 56.25%] [G loss: 0.736857]
8/8 [==============================] - 0s 4ms/step
7878 [D loss: 0.675408, acc.: 58.20%] [G loss: 0.751263]
8/8 [==============================] - 0s 4ms/step
7879 [D loss: 0.686153, acc.: 55.08%] [G loss: 0.746473]
8/8 [==============================] - 0s 4ms/step
7880 [D loss: 0.671100, acc.: 58.40%] [G loss: 0.741970]
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7881 [D loss: 0.687957, acc.: 54.49%] [G loss: 0.748877]
8/8 [==============================] - 0s 4ms/step
7882 [D loss: 0.673940, acc.: 57.62%] [G loss: 0.750868]
8/8 [==============================] - 0s 4ms/step
7883 [D loss: 0.671402, acc.: 58.79%] [G loss: 0.744528]
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7884 [D loss: 0.675693, acc.: 57.03%] [G loss: 0.741650]
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7885 [D loss: 0.681441, acc.: 55.66%] [G loss: 0.746235]
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7886 [D loss: 0.679225, acc.: 56.84%] [G loss: 0.750108]
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7887 [D loss: 0.680754, acc.: 56.84%] [G loss: 0.749518]
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7888 [D loss: 0.672057, acc.: 56.64%] [G loss: 0.744874]
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7889 [D loss: 0.682193, acc.: 53.12%] [G loss: 0.758178]
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7890 [D loss: 0.696398, acc.: 51.37%] [G loss: 0.747511]
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7891 [D loss: 0.674591, acc.: 57.81%] [G loss: 0.743271]
8/8 [==============================] - 0s 4ms/step
7892 [D loss: 0.676642, acc.: 54.30%] [G loss: 0.749235]
8/8 [==============================] - 0s 4ms/step
7893 [D loss: 0.677184, acc.: 60.16%] [G loss: 0.750506]
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7894 [D loss: 0.674890, acc.: 57.42%] [G loss: 0.750527]
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7895 [D loss: 0.688702, acc.: 54.49%] [G loss: 0.749465]
8/8 [==============================] - 0s 4ms/step
7896 [D loss: 0.676780, acc.: 56.64%] [G loss: 0.740957]
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7897 [D loss: 0.678779, acc.: 55.27%] [G loss: 0.735755]
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7898 [D loss: 0.690236, acc.: 53.32%] [G loss: 0.756459]
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7899 [D loss: 0.672673, acc.: 57.81%] [G loss: 0.754842]
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7900 [D loss: 0.669629, acc.: 58.20%] [G loss: 0.764691]
1/1 [==============================] - 0s 20ms/step
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7901 [D loss: 0.669839, acc.: 60.55%] [G loss: 0.740564]
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7902 [D loss: 0.681550, acc.: 55.08%] [G loss: 0.745506]
8/8 [==============================] - 0s 4ms/step
7903 [D loss: 0.680059, acc.: 54.69%] [G loss: 0.745475]
8/8 [==============================] - 0s 4ms/step
7904 [D loss: 0.683800, acc.: 52.93%] [G loss: 0.740953]
8/8 [==============================] - 0s 4ms/step
7905 [D loss: 0.677709, acc.: 60.35%] [G loss: 0.749909]
8/8 [==============================] - 0s 4ms/step
7906 [D loss: 0.685229, acc.: 57.23%] [G loss: 0.755694]
8/8 [==============================] - 0s 4ms/step
7907 [D loss: 0.687399, acc.: 54.10%] [G loss: 0.743710]
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7908 [D loss: 0.679047, acc.: 58.20%] [G loss: 0.744718]
8/8 [==============================] - 0s 4ms/step
7909 [D loss: 0.682530, acc.: 54.30%] [G loss: 0.746450]
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7910 [D loss: 0.686785, acc.: 54.30%] [G loss: 0.748438]
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7911 [D loss: 0.679267, acc.: 55.86%] [G loss: 0.748773]
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7912 [D loss: 0.686454, acc.: 55.66%] [G loss: 0.733146]
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7913 [D loss: 0.685083, acc.: 55.47%] [G loss: 0.747240]
8/8 [==============================] - 0s 4ms/step
7914 [D loss: 0.688102, acc.: 55.66%] [G loss: 0.731747]
8/8 [==============================] - 0s 4ms/step
7915 [D loss: 0.678382, acc.: 56.84%] [G loss: 0.745943]
8/8 [==============================] - 0s 4ms/step
7916 [D loss: 0.667582, acc.: 59.18%] [G loss: 0.736891]
8/8 [==============================] - 0s 4ms/step
7917 [D loss: 0.683615, acc.: 55.86%] [G loss: 0.736949]
8/8 [==============================] - 0s 4ms/step
7918 [D loss: 0.681987, acc.: 57.42%] [G loss: 0.755657]
8/8 [==============================] - 0s 4ms/step
7919 [D loss: 0.677005, acc.: 55.47%] [G loss: 0.742506]
8/8 [==============================] - 0s 4ms/step
7920 [D loss: 0.682204, acc.: 56.64%] [G loss: 0.741699]
8/8 [==============================] - 0s 4ms/step
7921 [D loss: 0.678757, acc.: 56.64%] [G loss: 0.742747]
8/8 [==============================] - 0s 4ms/step
7922 [D loss: 0.669028, acc.: 60.35%] [G loss: 0.744277]
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7923 [D loss: 0.678556, acc.: 59.18%] [G loss: 0.757714]
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7924 [D loss: 0.672695, acc.: 59.18%] [G loss: 0.746528]
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7925 [D loss: 0.680109, acc.: 56.05%] [G loss: 0.754332]
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7926 [D loss: 0.684556, acc.: 53.91%] [G loss: 0.744016]
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7927 [D loss: 0.668977, acc.: 60.35%] [G loss: 0.744975]
8/8 [==============================] - 0s 4ms/step
7928 [D loss: 0.681201, acc.: 56.05%] [G loss: 0.745699]
8/8 [==============================] - 0s 4ms/step
7929 [D loss: 0.686605, acc.: 55.27%] [G loss: 0.747073]
8/8 [==============================] - 0s 4ms/step
7930 [D loss: 0.675476, acc.: 58.01%] [G loss: 0.742335]
8/8 [==============================] - 0s 4ms/step
7931 [D loss: 0.679240, acc.: 56.05%] [G loss: 0.747117]
8/8 [==============================] - 0s 4ms/step
7932 [D loss: 0.688279, acc.: 54.30%] [G loss: 0.743445]
8/8 [==============================] - 0s 4ms/step
7933 [D loss: 0.673884, acc.: 57.23%] [G loss: 0.741821]
8/8 [==============================] - 0s 4ms/step
7934 [D loss: 0.675268, acc.: 59.57%] [G loss: 0.730663]
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7935 [D loss: 0.685738, acc.: 53.71%] [G loss: 0.767559]
8/8 [==============================] - 0s 4ms/step
7936 [D loss: 0.691119, acc.: 55.47%] [G loss: 0.760694]
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7937 [D loss: 0.682467, acc.: 58.01%] [G loss: 0.758042]
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7938 [D loss: 0.684472, acc.: 55.47%] [G loss: 0.757710]
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7939 [D loss: 0.678054, acc.: 57.42%] [G loss: 0.752270]
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7940 [D loss: 0.680725, acc.: 56.25%] [G loss: 0.753289]
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7941 [D loss: 0.673823, acc.: 58.20%] [G loss: 0.756297]
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7942 [D loss: 0.690151, acc.: 53.91%] [G loss: 0.738492]
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7943 [D loss: 0.681260, acc.: 55.08%] [G loss: 0.743091]
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7944 [D loss: 0.685894, acc.: 52.34%] [G loss: 0.741365]
8/8 [==============================] - 0s 4ms/step
7945 [D loss: 0.679769, acc.: 56.45%] [G loss: 0.748752]
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7946 [D loss: 0.678437, acc.: 57.23%] [G loss: 0.751216]
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7947 [D loss: 0.673635, acc.: 57.62%] [G loss: 0.762740]
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7948 [D loss: 0.688413, acc.: 51.76%] [G loss: 0.741821]
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7949 [D loss: 0.676132, acc.: 58.59%] [G loss: 0.743599]
8/8 [==============================] - 0s 4ms/step
7950 [D loss: 0.681375, acc.: 56.64%] [G loss: 0.741715]
1/1 [==============================] - 0s 17ms/step
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7951 [D loss: 0.677941, acc.: 55.47%] [G loss: 0.755730]
8/8 [==============================] - 0s 4ms/step
7952 [D loss: 0.687034, acc.: 55.66%] [G loss: 0.764733]
8/8 [==============================] - 0s 4ms/step
7953 [D loss: 0.682293, acc.: 54.49%] [G loss: 0.747162]
8/8 [==============================] - 0s 4ms/step
7954 [D loss: 0.685062, acc.: 53.52%] [G loss: 0.742303]
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7955 [D loss: 0.686548, acc.: 52.93%] [G loss: 0.748563]
8/8 [==============================] - 0s 4ms/step
7956 [D loss: 0.681802, acc.: 56.45%] [G loss: 0.753811]
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7957 [D loss: 0.677905, acc.: 58.01%] [G loss: 0.751913]
8/8 [==============================] - 0s 4ms/step
7958 [D loss: 0.682268, acc.: 55.08%] [G loss: 0.756299]
8/8 [==============================] - 0s 4ms/step
7959 [D loss: 0.678279, acc.: 56.45%] [G loss: 0.764646]
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7960 [D loss: 0.676974, acc.: 56.84%] [G loss: 0.755278]
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7961 [D loss: 0.677241, acc.: 56.45%] [G loss: 0.757114]
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7962 [D loss: 0.682408, acc.: 57.42%] [G loss: 0.756232]
8/8 [==============================] - 0s 4ms/step
7963 [D loss: 0.680102, acc.: 57.23%] [G loss: 0.741778]
8/8 [==============================] - 0s 4ms/step
7964 [D loss: 0.675810, acc.: 58.01%] [G loss: 0.733919]
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7965 [D loss: 0.675858, acc.: 58.98%] [G loss: 0.737766]
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7966 [D loss: 0.677710, acc.: 58.59%] [G loss: 0.742100]
8/8 [==============================] - 0s 4ms/step
7967 [D loss: 0.680922, acc.: 56.05%] [G loss: 0.755194]
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7968 [D loss: 0.683385, acc.: 55.08%] [G loss: 0.745938]
8/8 [==============================] - 0s 4ms/step
7969 [D loss: 0.670869, acc.: 61.13%] [G loss: 0.750629]
8/8 [==============================] - 0s 4ms/step
7970 [D loss: 0.687586, acc.: 53.52%] [G loss: 0.744550]
8/8 [==============================] - 0s 4ms/step
7971 [D loss: 0.676435, acc.: 56.05%] [G loss: 0.740486]
8/8 [==============================] - 0s 4ms/step
7972 [D loss: 0.687366, acc.: 52.93%] [G loss: 0.732649]
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7973 [D loss: 0.673900, acc.: 57.42%] [G loss: 0.738854]
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7974 [D loss: 0.682271, acc.: 54.10%] [G loss: 0.727022]
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7975 [D loss: 0.676531, acc.: 57.42%] [G loss: 0.743591]
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7976 [D loss: 0.686152, acc.: 55.08%] [G loss: 0.776673]
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7977 [D loss: 0.676176, acc.: 57.62%] [G loss: 0.756145]
8/8 [==============================] - 0s 4ms/step
7978 [D loss: 0.669126, acc.: 61.72%] [G loss: 0.761201]
8/8 [==============================] - 0s 4ms/step
7979 [D loss: 0.672516, acc.: 57.62%] [G loss: 0.729409]
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7980 [D loss: 0.666988, acc.: 58.79%] [G loss: 0.724510]
8/8 [==============================] - 0s 4ms/step
7981 [D loss: 0.684461, acc.: 52.73%] [G loss: 0.725548]
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7982 [D loss: 0.694545, acc.: 54.30%] [G loss: 0.744187]
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7983 [D loss: 0.679858, acc.: 56.84%] [G loss: 0.741455]
8/8 [==============================] - 0s 4ms/step
7984 [D loss: 0.674168, acc.: 58.20%] [G loss: 0.747031]
8/8 [==============================] - 0s 4ms/step
7985 [D loss: 0.669084, acc.: 57.62%] [G loss: 0.761216]
8/8 [==============================] - 0s 4ms/step
7986 [D loss: 0.668004, acc.: 59.96%] [G loss: 0.766711]
8/8 [==============================] - 0s 4ms/step
7987 [D loss: 0.667824, acc.: 56.84%] [G loss: 0.759265]
8/8 [==============================] - 0s 4ms/step
7988 [D loss: 0.681665, acc.: 56.05%] [G loss: 0.742474]
8/8 [==============================] - 0s 4ms/step
7989 [D loss: 0.677736, acc.: 54.69%] [G loss: 0.734100]
8/8 [==============================] - 0s 4ms/step
7990 [D loss: 0.681402, acc.: 56.05%] [G loss: 0.739263]
8/8 [==============================] - 0s 4ms/step
7991 [D loss: 0.673466, acc.: 58.20%] [G loss: 0.742214]
8/8 [==============================] - 0s 4ms/step
7992 [D loss: 0.685187, acc.: 55.66%] [G loss: 0.751295]
8/8 [==============================] - 0s 4ms/step
7993 [D loss: 0.677583, acc.: 57.03%] [G loss: 0.760973]
8/8 [==============================] - 0s 4ms/step
7994 [D loss: 0.670872, acc.: 60.35%] [G loss: 0.762081]
8/8 [==============================] - 0s 4ms/step
7995 [D loss: 0.668249, acc.: 59.18%] [G loss: 0.764985]
8/8 [==============================] - 0s 4ms/step
7996 [D loss: 0.686171, acc.: 57.23%] [G loss: 0.766193]
8/8 [==============================] - 0s 4ms/step
7997 [D loss: 0.676954, acc.: 58.01%] [G loss: 0.753660]
8/8 [==============================] - 0s 4ms/step
7998 [D loss: 0.681249, acc.: 56.25%] [G loss: 0.754531]
8/8 [==============================] - 0s 4ms/step
7999 [D loss: 0.677332, acc.: 56.25%] [G loss: 0.726821]
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8000 [D loss: 0.688606, acc.: 52.34%] [G loss: 0.743323]
1/1 [==============================] - 0s 22ms/step
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8001 [D loss: 0.682059, acc.: 55.27%] [G loss: 0.743894]
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8002 [D loss: 0.673001, acc.: 58.98%] [G loss: 0.752976]
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8003 [D loss: 0.677462, acc.: 58.01%] [G loss: 0.746368]
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8004 [D loss: 0.678620, acc.: 56.84%] [G loss: 0.767661]
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8005 [D loss: 0.673681, acc.: 57.42%] [G loss: 0.758735]
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8006 [D loss: 0.670166, acc.: 60.16%] [G loss: 0.757113]
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8007 [D loss: 0.686617, acc.: 54.49%] [G loss: 0.738941]
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8008 [D loss: 0.682940, acc.: 55.47%] [G loss: 0.742468]
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8009 [D loss: 0.693140, acc.: 50.00%] [G loss: 0.743807]
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8010 [D loss: 0.692162, acc.: 54.10%] [G loss: 0.737109]
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8011 [D loss: 0.684376, acc.: 53.52%] [G loss: 0.770015]
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8012 [D loss: 0.666151, acc.: 61.72%] [G loss: 0.779317]
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8013 [D loss: 0.667712, acc.: 57.23%] [G loss: 0.773552]
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8014 [D loss: 0.659183, acc.: 62.89%] [G loss: 0.776844]
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8015 [D loss: 0.674508, acc.: 60.55%] [G loss: 0.739732]
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8016 [D loss: 0.666140, acc.: 58.20%] [G loss: 0.734262]
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8017 [D loss: 0.689589, acc.: 55.66%] [G loss: 0.726273]
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8018 [D loss: 0.694764, acc.: 54.49%] [G loss: 0.727924]
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8019 [D loss: 0.696392, acc.: 51.17%] [G loss: 0.749672]
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8020 [D loss: 0.671080, acc.: 57.62%] [G loss: 0.736329]
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8021 [D loss: 0.672366, acc.: 59.96%] [G loss: 0.779907]
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8022 [D loss: 0.654682, acc.: 66.80%] [G loss: 0.759347]
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8023 [D loss: 0.663438, acc.: 64.06%] [G loss: 0.753000]
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8024 [D loss: 0.670527, acc.: 59.96%] [G loss: 0.728597]
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8025 [D loss: 0.674241, acc.: 57.81%] [G loss: 0.708565]
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8026 [D loss: 0.688858, acc.: 54.10%] [G loss: 0.728951]
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8027 [D loss: 0.693107, acc.: 53.32%] [G loss: 0.738198]
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8028 [D loss: 0.695463, acc.: 50.98%] [G loss: 0.785683]
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8029 [D loss: 0.685634, acc.: 55.27%] [G loss: 0.779968]
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8030 [D loss: 0.664954, acc.: 60.55%] [G loss: 0.819014]
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8031 [D loss: 0.669367, acc.: 60.74%] [G loss: 0.793751]
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8032 [D loss: 0.671942, acc.: 58.20%] [G loss: 0.761280]
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8033 [D loss: 0.664131, acc.: 58.59%] [G loss: 0.727369]
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8034 [D loss: 0.677360, acc.: 57.42%] [G loss: 0.709369]
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8035 [D loss: 0.673220, acc.: 55.66%] [G loss: 0.706920]
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8036 [D loss: 0.693273, acc.: 53.12%] [G loss: 0.708707]
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8037 [D loss: 0.674131, acc.: 58.79%] [G loss: 0.725437]
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8038 [D loss: 0.672195, acc.: 59.38%] [G loss: 0.765884]
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8039 [D loss: 0.655051, acc.: 63.48%] [G loss: 0.762994]
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8040 [D loss: 0.669008, acc.: 60.94%] [G loss: 0.755349]
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8041 [D loss: 0.671811, acc.: 58.40%] [G loss: 0.768646]
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8042 [D loss: 0.652181, acc.: 64.26%] [G loss: 0.742689]
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8043 [D loss: 0.680903, acc.: 55.86%] [G loss: 0.737983]
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8044 [D loss: 0.674940, acc.: 58.79%] [G loss: 0.720498]
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8045 [D loss: 0.698291, acc.: 48.83%] [G loss: 0.728509]
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8046 [D loss: 0.686380, acc.: 52.73%] [G loss: 0.758868]
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8047 [D loss: 0.673320, acc.: 59.96%] [G loss: 0.758848]
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8048 [D loss: 0.675674, acc.: 56.64%] [G loss: 0.761167]
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8049 [D loss: 0.671436, acc.: 58.01%] [G loss: 0.760441]
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8050 [D loss: 0.677629, acc.: 56.25%] [G loss: 0.754370]
1/1 [==============================] - 0s 18ms/step
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8051 [D loss: 0.676134, acc.: 56.45%] [G loss: 0.740067]
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8052 [D loss: 0.668541, acc.: 59.18%] [G loss: 0.755813]
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8053 [D loss: 0.683808, acc.: 56.25%] [G loss: 0.723687]
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8054 [D loss: 0.681064, acc.: 54.30%] [G loss: 0.744116]
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8055 [D loss: 0.686225, acc.: 53.32%] [G loss: 0.761939]
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8056 [D loss: 0.679448, acc.: 54.88%] [G loss: 0.755557]
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8057 [D loss: 0.691138, acc.: 55.66%] [G loss: 0.757934]
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8058 [D loss: 0.673668, acc.: 57.03%] [G loss: 0.764788]
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8059 [D loss: 0.659806, acc.: 63.87%] [G loss: 0.760843]
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8060 [D loss: 0.669413, acc.: 61.13%] [G loss: 0.771330]
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8061 [D loss: 0.673865, acc.: 55.47%] [G loss: 0.759502]
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8062 [D loss: 0.662949, acc.: 59.57%] [G loss: 0.752706]
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8063 [D loss: 0.672834, acc.: 57.81%] [G loss: 0.745576]
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8064 [D loss: 0.683930, acc.: 56.05%] [G loss: 0.741983]
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8065 [D loss: 0.688399, acc.: 55.27%] [G loss: 0.756230]
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8066 [D loss: 0.674932, acc.: 58.40%] [G loss: 0.772108]
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8067 [D loss: 0.675105, acc.: 57.23%] [G loss: 0.775026]
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8068 [D loss: 0.685386, acc.: 55.66%] [G loss: 0.783109]
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8069 [D loss: 0.678540, acc.: 56.25%] [G loss: 0.778206]
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8070 [D loss: 0.686359, acc.: 54.88%] [G loss: 0.753766]
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8071 [D loss: 0.690819, acc.: 53.71%] [G loss: 0.756038]
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8072 [D loss: 0.677432, acc.: 56.64%] [G loss: 0.752643]
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8073 [D loss: 0.680037, acc.: 59.18%] [G loss: 0.731130]
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8074 [D loss: 0.680639, acc.: 55.47%] [G loss: 0.758081]
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8075 [D loss: 0.672009, acc.: 57.81%] [G loss: 0.743009]
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8076 [D loss: 0.687267, acc.: 52.54%] [G loss: 0.760533]
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8077 [D loss: 0.677147, acc.: 59.38%] [G loss: 0.762512]
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8078 [D loss: 0.683056, acc.: 52.73%] [G loss: 0.749192]
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8079 [D loss: 0.670113, acc.: 58.98%] [G loss: 0.761167]
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8080 [D loss: 0.678826, acc.: 57.62%] [G loss: 0.764583]
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8081 [D loss: 0.678630, acc.: 55.47%] [G loss: 0.742338]
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8082 [D loss: 0.684942, acc.: 54.49%] [G loss: 0.750004]
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8083 [D loss: 0.691230, acc.: 52.73%] [G loss: 0.753643]
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8084 [D loss: 0.683219, acc.: 55.66%] [G loss: 0.754922]
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8085 [D loss: 0.674574, acc.: 57.42%] [G loss: 0.756150]
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8086 [D loss: 0.683945, acc.: 56.64%] [G loss: 0.754696]
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8087 [D loss: 0.683303, acc.: 58.01%] [G loss: 0.755554]
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8088 [D loss: 0.678444, acc.: 58.98%] [G loss: 0.751916]
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8089 [D loss: 0.665134, acc.: 60.35%] [G loss: 0.745124]
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8090 [D loss: 0.677017, acc.: 56.25%] [G loss: 0.748750]
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8091 [D loss: 0.679542, acc.: 56.25%] [G loss: 0.744108]
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8092 [D loss: 0.677427, acc.: 57.23%] [G loss: 0.735640]
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8093 [D loss: 0.689637, acc.: 55.27%] [G loss: 0.740722]
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8094 [D loss: 0.682373, acc.: 57.62%] [G loss: 0.752069]
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8095 [D loss: 0.675378, acc.: 58.59%] [G loss: 0.751395]
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8096 [D loss: 0.675610, acc.: 55.66%] [G loss: 0.749720]
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8097 [D loss: 0.663779, acc.: 60.16%] [G loss: 0.759804]
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8098 [D loss: 0.670703, acc.: 58.20%] [G loss: 0.739741]
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8099 [D loss: 0.680818, acc.: 56.25%] [G loss: 0.734426]
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8100 [D loss: 0.681046, acc.: 56.05%] [G loss: 0.746594]
1/1 [==============================] - 0s 18ms/step
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8101 [D loss: 0.674076, acc.: 58.40%] [G loss: 0.738548]
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8102 [D loss: 0.689705, acc.: 56.25%] [G loss: 0.738528]
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8103 [D loss: 0.676912, acc.: 57.23%] [G loss: 0.760430]
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8104 [D loss: 0.692246, acc.: 51.95%] [G loss: 0.745880]
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8105 [D loss: 0.666762, acc.: 57.81%] [G loss: 0.763896]
8/8 [==============================] - 0s 4ms/step
8106 [D loss: 0.686767, acc.: 50.98%] [G loss: 0.769533]
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8107 [D loss: 0.684303, acc.: 55.86%] [G loss: 0.760550]
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8108 [D loss: 0.669442, acc.: 58.59%] [G loss: 0.765259]
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8109 [D loss: 0.682560, acc.: 55.27%] [G loss: 0.740429]
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8110 [D loss: 0.667934, acc.: 60.55%] [G loss: 0.757908]
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8111 [D loss: 0.678338, acc.: 54.49%] [G loss: 0.747170]
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8112 [D loss: 0.664948, acc.: 57.81%] [G loss: 0.759810]
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8113 [D loss: 0.670715, acc.: 61.33%] [G loss: 0.760519]
8/8 [==============================] - 0s 4ms/step
8114 [D loss: 0.678321, acc.: 55.27%] [G loss: 0.750542]
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8115 [D loss: 0.674491, acc.: 56.64%] [G loss: 0.743233]
8/8 [==============================] - 0s 4ms/step
8116 [D loss: 0.689553, acc.: 54.49%] [G loss: 0.738201]
8/8 [==============================] - 0s 4ms/step
8117 [D loss: 0.669349, acc.: 58.40%] [G loss: 0.731079]
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8118 [D loss: 0.676385, acc.: 55.27%] [G loss: 0.750405]
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8119 [D loss: 0.683270, acc.: 56.84%] [G loss: 0.757039]
8/8 [==============================] - 0s 4ms/step
8120 [D loss: 0.676200, acc.: 56.45%] [G loss: 0.749805]
8/8 [==============================] - 0s 4ms/step
8121 [D loss: 0.673234, acc.: 58.20%] [G loss: 0.759260]
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8122 [D loss: 0.675796, acc.: 55.86%] [G loss: 0.759459]
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8123 [D loss: 0.679935, acc.: 56.45%] [G loss: 0.749665]
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8124 [D loss: 0.683526, acc.: 53.71%] [G loss: 0.740100]
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8125 [D loss: 0.683260, acc.: 54.88%] [G loss: 0.748390]
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8126 [D loss: 0.681933, acc.: 55.08%] [G loss: 0.745151]
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8127 [D loss: 0.672380, acc.: 59.77%] [G loss: 0.733719]
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8128 [D loss: 0.681561, acc.: 57.23%] [G loss: 0.752186]
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8129 [D loss: 0.687447, acc.: 53.71%] [G loss: 0.765168]
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8130 [D loss: 0.673455, acc.: 59.77%] [G loss: 0.751416]
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8131 [D loss: 0.671576, acc.: 58.40%] [G loss: 0.765495]
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8132 [D loss: 0.674988, acc.: 58.20%] [G loss: 0.775272]
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8133 [D loss: 0.677443, acc.: 56.05%] [G loss: 0.741967]
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8134 [D loss: 0.680134, acc.: 57.03%] [G loss: 0.742260]
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8135 [D loss: 0.687050, acc.: 52.15%] [G loss: 0.744579]
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8136 [D loss: 0.678560, acc.: 56.05%] [G loss: 0.736586]
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8137 [D loss: 0.671284, acc.: 58.98%] [G loss: 0.732640]
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8138 [D loss: 0.675024, acc.: 61.33%] [G loss: 0.758661]
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8139 [D loss: 0.674063, acc.: 59.18%] [G loss: 0.779487]
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8140 [D loss: 0.670871, acc.: 59.77%] [G loss: 0.742092]
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8141 [D loss: 0.677155, acc.: 56.84%] [G loss: 0.756001]
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8142 [D loss: 0.680936, acc.: 55.86%] [G loss: 0.755255]
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8143 [D loss: 0.682706, acc.: 56.05%] [G loss: 0.741341]
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8144 [D loss: 0.696671, acc.: 50.78%] [G loss: 0.727786]
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8145 [D loss: 0.676728, acc.: 58.40%] [G loss: 0.733842]
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8146 [D loss: 0.685077, acc.: 54.69%] [G loss: 0.742823]
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8147 [D loss: 0.671792, acc.: 58.79%] [G loss: 0.754473]
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8148 [D loss: 0.678803, acc.: 57.03%] [G loss: 0.762137]
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8149 [D loss: 0.675198, acc.: 56.84%] [G loss: 0.743895]
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8150 [D loss: 0.671646, acc.: 56.25%] [G loss: 0.737007]
1/1 [==============================] - 0s 29ms/step
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8151 [D loss: 0.678577, acc.: 57.42%] [G loss: 0.716245]
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8152 [D loss: 0.693693, acc.: 52.54%] [G loss: 0.746053]
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8153 [D loss: 0.675425, acc.: 60.16%] [G loss: 0.742191]
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8154 [D loss: 0.677799, acc.: 57.42%] [G loss: 0.771743]
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8155 [D loss: 0.674964, acc.: 57.42%] [G loss: 0.752307]
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8156 [D loss: 0.663458, acc.: 63.28%] [G loss: 0.764337]
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8157 [D loss: 0.684593, acc.: 53.71%] [G loss: 0.772544]
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8158 [D loss: 0.663290, acc.: 63.28%] [G loss: 0.749125]
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8159 [D loss: 0.672019, acc.: 59.18%] [G loss: 0.757549]
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8160 [D loss: 0.680929, acc.: 54.88%] [G loss: 0.738989]
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8161 [D loss: 0.682282, acc.: 57.62%] [G loss: 0.709317]
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8162 [D loss: 0.690786, acc.: 53.91%] [G loss: 0.734147]
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8163 [D loss: 0.682457, acc.: 54.88%] [G loss: 0.724520]
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8164 [D loss: 0.669539, acc.: 58.98%] [G loss: 0.744448]
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8165 [D loss: 0.679361, acc.: 54.30%] [G loss: 0.754561]
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8166 [D loss: 0.671736, acc.: 58.01%] [G loss: 0.753691]
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8167 [D loss: 0.670819, acc.: 59.18%] [G loss: 0.762070]
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8168 [D loss: 0.680514, acc.: 55.66%] [G loss: 0.774350]
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8169 [D loss: 0.685741, acc.: 53.32%] [G loss: 0.749876]
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8170 [D loss: 0.675565, acc.: 57.23%] [G loss: 0.758450]
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8171 [D loss: 0.674955, acc.: 56.25%] [G loss: 0.769988]
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8172 [D loss: 0.687191, acc.: 52.15%] [G loss: 0.744792]
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8173 [D loss: 0.680774, acc.: 57.23%] [G loss: 0.751146]
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8174 [D loss: 0.677605, acc.: 57.03%] [G loss: 0.757312]
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8175 [D loss: 0.672965, acc.: 59.18%] [G loss: 0.761243]
8/8 [==============================] - 0s 4ms/step
8176 [D loss: 0.676691, acc.: 54.30%] [G loss: 0.760138]
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8177 [D loss: 0.678453, acc.: 54.49%] [G loss: 0.761829]
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8178 [D loss: 0.667514, acc.: 59.57%] [G loss: 0.741937]
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8179 [D loss: 0.705157, acc.: 51.76%] [G loss: 0.747698]
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8180 [D loss: 0.681741, acc.: 55.27%] [G loss: 0.756230]
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8181 [D loss: 0.682761, acc.: 55.86%] [G loss: 0.759194]
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8182 [D loss: 0.684129, acc.: 53.32%] [G loss: 0.759194]
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8183 [D loss: 0.659634, acc.: 60.55%] [G loss: 0.749332]
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8184 [D loss: 0.670774, acc.: 58.79%] [G loss: 0.745869]
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8185 [D loss: 0.675498, acc.: 57.81%] [G loss: 0.748709]
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8186 [D loss: 0.674470, acc.: 61.72%] [G loss: 0.755447]
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8187 [D loss: 0.680621, acc.: 57.23%] [G loss: 0.745993]
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8188 [D loss: 0.677823, acc.: 58.79%] [G loss: 0.758427]
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8189 [D loss: 0.681772, acc.: 57.62%] [G loss: 0.748923]
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8190 [D loss: 0.683436, acc.: 56.05%] [G loss: 0.736137]
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8191 [D loss: 0.679258, acc.: 57.42%] [G loss: 0.748025]
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8192 [D loss: 0.687725, acc.: 54.49%] [G loss: 0.749272]
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8193 [D loss: 0.677272, acc.: 55.27%] [G loss: 0.742638]
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8194 [D loss: 0.677632, acc.: 55.66%] [G loss: 0.742488]
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8195 [D loss: 0.674119, acc.: 58.59%] [G loss: 0.739995]
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8196 [D loss: 0.683953, acc.: 56.05%] [G loss: 0.760208]
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8197 [D loss: 0.679403, acc.: 57.62%] [G loss: 0.733224]
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8198 [D loss: 0.683364, acc.: 55.27%] [G loss: 0.733797]
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8199 [D loss: 0.686186, acc.: 54.88%] [G loss: 0.742071]
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8200 [D loss: 0.682516, acc.: 53.52%] [G loss: 0.756787]
1/1 [==============================] - 0s 17ms/step
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8201 [D loss: 0.667586, acc.: 59.38%] [G loss: 0.762042]
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8202 [D loss: 0.679538, acc.: 57.03%] [G loss: 0.761043]
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8203 [D loss: 0.684621, acc.: 54.88%] [G loss: 0.747291]
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8204 [D loss: 0.673313, acc.: 55.86%] [G loss: 0.753557]
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8205 [D loss: 0.685240, acc.: 58.01%] [G loss: 0.745022]
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8206 [D loss: 0.676114, acc.: 56.84%] [G loss: 0.742702]
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8207 [D loss: 0.672260, acc.: 58.79%] [G loss: 0.755368]
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8208 [D loss: 0.673695, acc.: 58.40%] [G loss: 0.749617]
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8209 [D loss: 0.684738, acc.: 56.25%] [G loss: 0.758747]
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8210 [D loss: 0.684964, acc.: 57.81%] [G loss: 0.745287]
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8211 [D loss: 0.671740, acc.: 58.98%] [G loss: 0.759315]
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8212 [D loss: 0.677726, acc.: 56.05%] [G loss: 0.771131]
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8213 [D loss: 0.678794, acc.: 56.45%] [G loss: 0.770640]
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8214 [D loss: 0.667140, acc.: 57.81%] [G loss: 0.754179]
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8215 [D loss: 0.675850, acc.: 57.62%] [G loss: 0.750951]
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8216 [D loss: 0.682814, acc.: 54.30%] [G loss: 0.736578]
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8217 [D loss: 0.681068, acc.: 55.86%] [G loss: 0.742120]
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8218 [D loss: 0.681258, acc.: 56.45%] [G loss: 0.748018]
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8219 [D loss: 0.674294, acc.: 55.47%] [G loss: 0.748679]
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8220 [D loss: 0.671096, acc.: 60.16%] [G loss: 0.762014]
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8221 [D loss: 0.662129, acc.: 64.45%] [G loss: 0.764937]
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8222 [D loss: 0.668370, acc.: 58.79%] [G loss: 0.765110]
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8223 [D loss: 0.672801, acc.: 57.62%] [G loss: 0.744968]
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8224 [D loss: 0.691826, acc.: 52.93%] [G loss: 0.719600]
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8225 [D loss: 0.693773, acc.: 52.93%] [G loss: 0.737979]
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8226 [D loss: 0.681648, acc.: 55.08%] [G loss: 0.738083]
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8227 [D loss: 0.688458, acc.: 54.10%] [G loss: 0.738032]
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8228 [D loss: 0.671241, acc.: 58.59%] [G loss: 0.766442]
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8229 [D loss: 0.677970, acc.: 54.69%] [G loss: 0.790205]
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8230 [D loss: 0.664404, acc.: 61.13%] [G loss: 0.780178]
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8231 [D loss: 0.669621, acc.: 58.40%] [G loss: 0.767025]
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8232 [D loss: 0.674356, acc.: 59.38%] [G loss: 0.776853]
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8233 [D loss: 0.682097, acc.: 54.49%] [G loss: 0.758097]
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8234 [D loss: 0.672808, acc.: 57.03%] [G loss: 0.750425]
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8235 [D loss: 0.683755, acc.: 57.42%] [G loss: 0.745661]
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8236 [D loss: 0.677534, acc.: 55.47%] [G loss: 0.713684]
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8237 [D loss: 0.686194, acc.: 58.01%] [G loss: 0.743392]
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8238 [D loss: 0.685067, acc.: 55.66%] [G loss: 0.749494]
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8239 [D loss: 0.681623, acc.: 54.88%] [G loss: 0.765172]
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8240 [D loss: 0.668301, acc.: 59.77%] [G loss: 0.777982]
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8241 [D loss: 0.678560, acc.: 56.84%] [G loss: 0.768299]
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8242 [D loss: 0.684099, acc.: 56.25%] [G loss: 0.758419]
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8243 [D loss: 0.676793, acc.: 57.42%] [G loss: 0.759990]
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8244 [D loss: 0.685603, acc.: 54.30%] [G loss: 0.743623]
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8245 [D loss: 0.681244, acc.: 54.69%] [G loss: 0.742093]
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8246 [D loss: 0.681776, acc.: 57.23%] [G loss: 0.752171]
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8247 [D loss: 0.678640, acc.: 56.64%] [G loss: 0.757281]
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8248 [D loss: 0.672106, acc.: 60.74%] [G loss: 0.741402]
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8249 [D loss: 0.680254, acc.: 55.47%] [G loss: 0.759629]
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8250 [D loss: 0.669297, acc.: 58.01%] [G loss: 0.753277]
1/1 [==============================] - 0s 18ms/step
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8251 [D loss: 0.682900, acc.: 55.66%] [G loss: 0.747159]
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8252 [D loss: 0.675414, acc.: 55.86%] [G loss: 0.748570]
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8253 [D loss: 0.677375, acc.: 56.84%] [G loss: 0.739086]
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8254 [D loss: 0.674606, acc.: 60.16%] [G loss: 0.746084]
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8255 [D loss: 0.678371, acc.: 56.84%] [G loss: 0.735610]
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8256 [D loss: 0.663454, acc.: 60.74%] [G loss: 0.763610]
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8257 [D loss: 0.683574, acc.: 55.08%] [G loss: 0.754645]
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8258 [D loss: 0.673024, acc.: 58.98%] [G loss: 0.749407]
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8259 [D loss: 0.668718, acc.: 58.20%] [G loss: 0.737244]
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8260 [D loss: 0.677069, acc.: 57.23%] [G loss: 0.723285]
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8261 [D loss: 0.685732, acc.: 57.42%] [G loss: 0.749603]
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8262 [D loss: 0.674419, acc.: 59.77%] [G loss: 0.729578]
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8263 [D loss: 0.692083, acc.: 55.08%] [G loss: 0.739170]
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8264 [D loss: 0.667812, acc.: 60.35%] [G loss: 0.776880]
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8265 [D loss: 0.682383, acc.: 54.88%] [G loss: 0.774240]
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8266 [D loss: 0.670834, acc.: 58.20%] [G loss: 0.780576]
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8267 [D loss: 0.679498, acc.: 56.45%] [G loss: 0.789148]
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8268 [D loss: 0.670311, acc.: 57.23%] [G loss: 0.767027]
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8269 [D loss: 0.674432, acc.: 55.66%] [G loss: 0.745606]
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8270 [D loss: 0.687268, acc.: 56.84%] [G loss: 0.719171]
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8271 [D loss: 0.683925, acc.: 54.69%] [G loss: 0.737836]
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8272 [D loss: 0.672220, acc.: 60.16%] [G loss: 0.759610]
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8273 [D loss: 0.669785, acc.: 56.45%] [G loss: 0.762088]
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8274 [D loss: 0.673571, acc.: 59.38%] [G loss: 0.780431]
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8275 [D loss: 0.676963, acc.: 55.66%] [G loss: 0.775394]
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8276 [D loss: 0.663579, acc.: 61.91%] [G loss: 0.760160]
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8277 [D loss: 0.670344, acc.: 59.38%] [G loss: 0.754268]
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8278 [D loss: 0.681015, acc.: 56.25%] [G loss: 0.749723]
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8279 [D loss: 0.688418, acc.: 55.86%] [G loss: 0.745705]
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8280 [D loss: 0.689143, acc.: 53.71%] [G loss: 0.743302]
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8281 [D loss: 0.679313, acc.: 59.18%] [G loss: 0.736993]
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8282 [D loss: 0.682941, acc.: 57.81%] [G loss: 0.777240]
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8283 [D loss: 0.662436, acc.: 61.13%] [G loss: 0.780725]
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8284 [D loss: 0.676205, acc.: 60.16%] [G loss: 0.759427]
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8285 [D loss: 0.671596, acc.: 60.16%] [G loss: 0.753850]
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8286 [D loss: 0.688691, acc.: 54.69%] [G loss: 0.740731]
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8287 [D loss: 0.683000, acc.: 56.84%] [G loss: 0.744176]
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8288 [D loss: 0.678045, acc.: 57.42%] [G loss: 0.744413]
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8289 [D loss: 0.673419, acc.: 56.05%] [G loss: 0.738924]
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8290 [D loss: 0.684150, acc.: 55.47%] [G loss: 0.775406]
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8291 [D loss: 0.675808, acc.: 58.01%] [G loss: 0.763933]
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8292 [D loss: 0.661200, acc.: 62.50%] [G loss: 0.767621]
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8293 [D loss: 0.681217, acc.: 58.98%] [G loss: 0.757251]
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8294 [D loss: 0.667525, acc.: 60.74%] [G loss: 0.757823]
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8295 [D loss: 0.678407, acc.: 58.79%] [G loss: 0.753685]
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8296 [D loss: 0.687966, acc.: 53.71%] [G loss: 0.758848]
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8297 [D loss: 0.690375, acc.: 56.64%] [G loss: 0.747630]
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8298 [D loss: 0.680178, acc.: 56.64%] [G loss: 0.773404]
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8299 [D loss: 0.667733, acc.: 61.91%] [G loss: 0.794342]
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8300 [D loss: 0.667485, acc.: 58.98%] [G loss: 0.770074]
1/1 [==============================] - 0s 19ms/step
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8301 [D loss: 0.664467, acc.: 58.01%] [G loss: 0.766454]
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8302 [D loss: 0.671000, acc.: 60.74%] [G loss: 0.753621]
8/8 [==============================] - 0s 4ms/step
8303 [D loss: 0.680018, acc.: 57.03%] [G loss: 0.769319]
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8304 [D loss: 0.693113, acc.: 52.34%] [G loss: 0.753895]
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8305 [D loss: 0.684676, acc.: 54.69%] [G loss: 0.745353]
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8306 [D loss: 0.673165, acc.: 59.18%] [G loss: 0.768328]
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8307 [D loss: 0.679162, acc.: 56.25%] [G loss: 0.773731]
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8308 [D loss: 0.667074, acc.: 61.52%] [G loss: 0.777136]
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8309 [D loss: 0.662923, acc.: 62.50%] [G loss: 0.745164]
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8310 [D loss: 0.660900, acc.: 59.96%] [G loss: 0.756082]
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8311 [D loss: 0.666403, acc.: 59.96%] [G loss: 0.706636]
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8312 [D loss: 0.694678, acc.: 51.17%] [G loss: 0.726857]
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8313 [D loss: 0.691603, acc.: 50.78%] [G loss: 0.733347]
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8314 [D loss: 0.694794, acc.: 51.37%] [G loss: 0.747012]
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8315 [D loss: 0.674095, acc.: 57.62%] [G loss: 0.770238]
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8316 [D loss: 0.678026, acc.: 55.27%] [G loss: 0.776941]
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8317 [D loss: 0.682409, acc.: 53.52%] [G loss: 0.781026]
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8318 [D loss: 0.677382, acc.: 57.03%] [G loss: 0.769147]
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8319 [D loss: 0.674515, acc.: 56.25%] [G loss: 0.748403]
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8320 [D loss: 0.664352, acc.: 60.74%] [G loss: 0.716638]
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8321 [D loss: 0.681108, acc.: 55.66%] [G loss: 0.722681]
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8322 [D loss: 0.674056, acc.: 57.03%] [G loss: 0.747388]
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8323 [D loss: 0.680445, acc.: 55.47%] [G loss: 0.734436]
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8324 [D loss: 0.677315, acc.: 59.38%] [G loss: 0.751010]
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8325 [D loss: 0.674651, acc.: 58.20%] [G loss: 0.759858]
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8326 [D loss: 0.667232, acc.: 60.55%] [G loss: 0.767691]
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8327 [D loss: 0.657772, acc.: 63.48%] [G loss: 0.739549]
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8328 [D loss: 0.670726, acc.: 57.81%] [G loss: 0.721497]
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8329 [D loss: 0.684512, acc.: 54.88%] [G loss: 0.744450]
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8330 [D loss: 0.677252, acc.: 59.96%] [G loss: 0.733986]
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8331 [D loss: 0.674214, acc.: 56.64%] [G loss: 0.735681]
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8332 [D loss: 0.693667, acc.: 52.93%] [G loss: 0.748774]
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8333 [D loss: 0.673836, acc.: 58.40%] [G loss: 0.768045]
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8334 [D loss: 0.671946, acc.: 57.62%] [G loss: 0.783622]
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8335 [D loss: 0.665830, acc.: 56.64%] [G loss: 0.784068]
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8336 [D loss: 0.667321, acc.: 60.55%] [G loss: 0.776416]
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8337 [D loss: 0.682509, acc.: 56.25%] [G loss: 0.754944]
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8338 [D loss: 0.681786, acc.: 55.47%] [G loss: 0.737059]
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8339 [D loss: 0.682470, acc.: 55.86%] [G loss: 0.738375]
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8340 [D loss: 0.667579, acc.: 58.20%] [G loss: 0.751977]
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8341 [D loss: 0.700850, acc.: 48.44%] [G loss: 0.749714]
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8342 [D loss: 0.662674, acc.: 62.50%] [G loss: 0.751626]
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8343 [D loss: 0.678031, acc.: 55.47%] [G loss: 0.760544]
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8344 [D loss: 0.676410, acc.: 56.64%] [G loss: 0.746696]
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8345 [D loss: 0.677062, acc.: 58.01%] [G loss: 0.737144]
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8346 [D loss: 0.678010, acc.: 57.42%] [G loss: 0.751093]
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8347 [D loss: 0.679103, acc.: 56.84%] [G loss: 0.738137]
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8348 [D loss: 0.677934, acc.: 55.27%] [G loss: 0.738940]
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8349 [D loss: 0.685188, acc.: 53.32%] [G loss: 0.731015]
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8350 [D loss: 0.681341, acc.: 57.81%] [G loss: 0.742907]
1/1 [==============================] - 0s 17ms/step
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8351 [D loss: 0.677572, acc.: 56.64%] [G loss: 0.775335]
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8352 [D loss: 0.671657, acc.: 58.79%] [G loss: 0.777725]
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8353 [D loss: 0.669213, acc.: 58.40%] [G loss: 0.772598]
8/8 [==============================] - 0s 4ms/step
8354 [D loss: 0.679452, acc.: 56.64%] [G loss: 0.757850]
8/8 [==============================] - 0s 4ms/step
8355 [D loss: 0.671118, acc.: 58.01%] [G loss: 0.741787]
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8356 [D loss: 0.686693, acc.: 53.52%] [G loss: 0.768887]
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8357 [D loss: 0.675554, acc.: 56.05%] [G loss: 0.732970]
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8358 [D loss: 0.682974, acc.: 56.84%] [G loss: 0.739490]
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8359 [D loss: 0.688109, acc.: 52.73%] [G loss: 0.753488]
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8360 [D loss: 0.669811, acc.: 59.57%] [G loss: 0.770776]
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8361 [D loss: 0.663063, acc.: 62.11%] [G loss: 0.755829]
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8362 [D loss: 0.678093, acc.: 56.45%] [G loss: 0.749851]
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8363 [D loss: 0.694271, acc.: 52.93%] [G loss: 0.743196]
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8364 [D loss: 0.668899, acc.: 56.25%] [G loss: 0.742133]
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8365 [D loss: 0.681210, acc.: 56.25%] [G loss: 0.733212]
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8366 [D loss: 0.673767, acc.: 55.86%] [G loss: 0.745628]
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8367 [D loss: 0.683277, acc.: 56.25%] [G loss: 0.738164]
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8368 [D loss: 0.678244, acc.: 56.64%] [G loss: 0.732526]
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8369 [D loss: 0.677704, acc.: 58.59%] [G loss: 0.757311]
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8370 [D loss: 0.682860, acc.: 54.88%] [G loss: 0.766258]
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8371 [D loss: 0.679566, acc.: 57.62%] [G loss: 0.763093]
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8372 [D loss: 0.666597, acc.: 59.18%] [G loss: 0.755651]
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8373 [D loss: 0.680185, acc.: 55.27%] [G loss: 0.742142]
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8374 [D loss: 0.689689, acc.: 55.27%] [G loss: 0.751014]
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8375 [D loss: 0.683862, acc.: 53.52%] [G loss: 0.750264]
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8376 [D loss: 0.676820, acc.: 53.32%] [G loss: 0.737645]
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8377 [D loss: 0.671618, acc.: 58.59%] [G loss: 0.753556]
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8378 [D loss: 0.673588, acc.: 57.42%] [G loss: 0.751753]
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8379 [D loss: 0.673975, acc.: 61.72%] [G loss: 0.752735]
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8380 [D loss: 0.671960, acc.: 59.18%] [G loss: 0.742251]
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8381 [D loss: 0.670435, acc.: 59.18%] [G loss: 0.741574]
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8382 [D loss: 0.685277, acc.: 54.10%] [G loss: 0.744451]
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8383 [D loss: 0.680889, acc.: 55.86%] [G loss: 0.732859]
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8384 [D loss: 0.672195, acc.: 59.38%] [G loss: 0.734711]
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8385 [D loss: 0.698497, acc.: 50.78%] [G loss: 0.753438]
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8386 [D loss: 0.672334, acc.: 59.38%] [G loss: 0.754290]
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8387 [D loss: 0.680943, acc.: 55.86%] [G loss: 0.777898]
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8388 [D loss: 0.678858, acc.: 56.45%] [G loss: 0.771602]
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8389 [D loss: 0.682959, acc.: 57.62%] [G loss: 0.771520]
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8390 [D loss: 0.680431, acc.: 56.64%] [G loss: 0.750288]
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8391 [D loss: 0.674126, acc.: 56.25%] [G loss: 0.761257]
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8392 [D loss: 0.673685, acc.: 58.98%] [G loss: 0.759720]
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8393 [D loss: 0.672930, acc.: 58.79%] [G loss: 0.740649]
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8394 [D loss: 0.681136, acc.: 56.25%] [G loss: 0.741739]
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8395 [D loss: 0.673359, acc.: 59.38%] [G loss: 0.744585]
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8396 [D loss: 0.675644, acc.: 56.84%] [G loss: 0.746498]
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8397 [D loss: 0.672266, acc.: 58.59%] [G loss: 0.739633]
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8398 [D loss: 0.673194, acc.: 57.81%] [G loss: 0.753982]
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8399 [D loss: 0.673975, acc.: 57.42%] [G loss: 0.747536]
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8400 [D loss: 0.673797, acc.: 58.79%] [G loss: 0.737911]
1/1 [==============================] - 0s 17ms/step
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8401 [D loss: 0.668689, acc.: 60.55%] [G loss: 0.745260]
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8402 [D loss: 0.681483, acc.: 56.25%] [G loss: 0.731884]
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8403 [D loss: 0.674748, acc.: 55.27%] [G loss: 0.738870]
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8404 [D loss: 0.684046, acc.: 55.08%] [G loss: 0.746540]
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8405 [D loss: 0.681616, acc.: 54.49%] [G loss: 0.744222]
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8406 [D loss: 0.679624, acc.: 57.62%] [G loss: 0.782520]
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8407 [D loss: 0.662118, acc.: 60.94%] [G loss: 0.762140]
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8408 [D loss: 0.668566, acc.: 56.45%] [G loss: 0.780695]
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8409 [D loss: 0.666465, acc.: 59.96%] [G loss: 0.751213]
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8410 [D loss: 0.676009, acc.: 55.08%] [G loss: 0.730341]
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8411 [D loss: 0.677724, acc.: 54.69%] [G loss: 0.738525]
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8412 [D loss: 0.680069, acc.: 56.25%] [G loss: 0.753138]
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8413 [D loss: 0.678758, acc.: 57.81%] [G loss: 0.747880]
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8414 [D loss: 0.677341, acc.: 57.42%] [G loss: 0.751879]
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8415 [D loss: 0.671873, acc.: 58.79%] [G loss: 0.754446]
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8416 [D loss: 0.672131, acc.: 56.64%] [G loss: 0.742219]
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8417 [D loss: 0.667280, acc.: 60.55%] [G loss: 0.765593]
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8418 [D loss: 0.674304, acc.: 58.98%] [G loss: 0.765115]
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8419 [D loss: 0.679733, acc.: 55.66%] [G loss: 0.740683]
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8420 [D loss: 0.674020, acc.: 59.38%] [G loss: 0.741499]
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8421 [D loss: 0.670384, acc.: 60.35%] [G loss: 0.745521]
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8422 [D loss: 0.681251, acc.: 55.86%] [G loss: 0.764490]
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8423 [D loss: 0.680290, acc.: 56.05%] [G loss: 0.756630]
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8424 [D loss: 0.672394, acc.: 57.42%] [G loss: 0.768624]
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8425 [D loss: 0.683076, acc.: 55.66%] [G loss: 0.749029]
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8426 [D loss: 0.670472, acc.: 59.96%] [G loss: 0.746258]
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8427 [D loss: 0.680505, acc.: 55.86%] [G loss: 0.733734]
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8428 [D loss: 0.676221, acc.: 59.57%] [G loss: 0.743193]
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8429 [D loss: 0.679911, acc.: 57.81%] [G loss: 0.758105]
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8430 [D loss: 0.674915, acc.: 59.77%] [G loss: 0.752807]
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8431 [D loss: 0.677232, acc.: 57.62%] [G loss: 0.767088]
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8432 [D loss: 0.679747, acc.: 59.38%] [G loss: 0.747498]
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8433 [D loss: 0.675279, acc.: 54.49%] [G loss: 0.743464]
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8434 [D loss: 0.686519, acc.: 55.86%] [G loss: 0.731272]
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8435 [D loss: 0.668082, acc.: 61.13%] [G loss: 0.754307]
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8436 [D loss: 0.679620, acc.: 55.08%] [G loss: 0.750009]
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8437 [D loss: 0.679643, acc.: 56.84%] [G loss: 0.744313]
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8438 [D loss: 0.683361, acc.: 54.30%] [G loss: 0.759616]
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8439 [D loss: 0.666200, acc.: 58.20%] [G loss: 0.764557]
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8440 [D loss: 0.675408, acc.: 55.66%] [G loss: 0.767645]
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8441 [D loss: 0.672944, acc.: 58.79%] [G loss: 0.758598]
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8442 [D loss: 0.686766, acc.: 54.10%] [G loss: 0.729498]
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8443 [D loss: 0.667573, acc.: 61.33%] [G loss: 0.745434]
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8444 [D loss: 0.686329, acc.: 53.52%] [G loss: 0.752452]
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8445 [D loss: 0.680642, acc.: 58.20%] [G loss: 0.753893]
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8446 [D loss: 0.690422, acc.: 52.54%] [G loss: 0.739194]
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8447 [D loss: 0.689319, acc.: 51.76%] [G loss: 0.743627]
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8448 [D loss: 0.683902, acc.: 53.52%] [G loss: 0.768771]
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8449 [D loss: 0.677363, acc.: 56.25%] [G loss: 0.767253]
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8450 [D loss: 0.682434, acc.: 56.64%] [G loss: 0.763975]
1/1 [==============================] - 0s 17ms/step
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8451 [D loss: 0.680290, acc.: 53.71%] [G loss: 0.740838]
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8452 [D loss: 0.674840, acc.: 58.59%] [G loss: 0.738899]
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8453 [D loss: 0.688156, acc.: 56.25%] [G loss: 0.737069]
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8454 [D loss: 0.683753, acc.: 53.71%] [G loss: 0.747368]
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8455 [D loss: 0.662427, acc.: 62.70%] [G loss: 0.742035]
8/8 [==============================] - 0s 4ms/step
8456 [D loss: 0.687398, acc.: 55.86%] [G loss: 0.757297]
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8457 [D loss: 0.674579, acc.: 58.79%] [G loss: 0.752468]
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8458 [D loss: 0.665543, acc.: 59.18%] [G loss: 0.730288]
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8459 [D loss: 0.679549, acc.: 58.40%] [G loss: 0.741477]
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8460 [D loss: 0.680746, acc.: 56.64%] [G loss: 0.749305]
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8461 [D loss: 0.678487, acc.: 57.81%] [G loss: 0.739016]
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8462 [D loss: 0.685228, acc.: 53.12%] [G loss: 0.760982]
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8463 [D loss: 0.676430, acc.: 57.62%] [G loss: 0.756315]
8/8 [==============================] - 0s 4ms/step
8464 [D loss: 0.671585, acc.: 56.25%] [G loss: 0.757846]
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8465 [D loss: 0.672303, acc.: 59.57%] [G loss: 0.752828]
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8466 [D loss: 0.685588, acc.: 54.69%] [G loss: 0.756617]
8/8 [==============================] - 0s 4ms/step
8467 [D loss: 0.672458, acc.: 55.86%] [G loss: 0.731841]
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8468 [D loss: 0.672542, acc.: 54.88%] [G loss: 0.756033]
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8469 [D loss: 0.683681, acc.: 54.69%] [G loss: 0.734062]
8/8 [==============================] - 0s 4ms/step
8470 [D loss: 0.679933, acc.: 56.25%] [G loss: 0.730207]
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8471 [D loss: 0.666180, acc.: 60.16%] [G loss: 0.741780]
8/8 [==============================] - 0s 4ms/step
8472 [D loss: 0.686131, acc.: 53.32%] [G loss: 0.733507]
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8473 [D loss: 0.686400, acc.: 54.49%] [G loss: 0.751284]
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8474 [D loss: 0.685300, acc.: 54.69%] [G loss: 0.761424]
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8475 [D loss: 0.675708, acc.: 59.77%] [G loss: 0.765358]
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8476 [D loss: 0.683640, acc.: 55.86%] [G loss: 0.764137]
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8477 [D loss: 0.683683, acc.: 55.27%] [G loss: 0.740986]
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8478 [D loss: 0.683567, acc.: 54.69%] [G loss: 0.765126]
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8479 [D loss: 0.669018, acc.: 59.38%] [G loss: 0.758223]
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8480 [D loss: 0.685292, acc.: 52.73%] [G loss: 0.754478]
8/8 [==============================] - 0s 4ms/step
8481 [D loss: 0.683716, acc.: 57.62%] [G loss: 0.761283]
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8482 [D loss: 0.674075, acc.: 58.40%] [G loss: 0.751664]
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8483 [D loss: 0.670080, acc.: 59.18%] [G loss: 0.760782]
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8484 [D loss: 0.680220, acc.: 57.62%] [G loss: 0.766267]
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8485 [D loss: 0.669259, acc.: 61.13%] [G loss: 0.753548]
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8486 [D loss: 0.674542, acc.: 56.25%] [G loss: 0.741039]
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8487 [D loss: 0.674221, acc.: 58.59%] [G loss: 0.750369]
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8488 [D loss: 0.680648, acc.: 55.86%] [G loss: 0.747338]
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8489 [D loss: 0.679630, acc.: 56.64%] [G loss: 0.761606]
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8490 [D loss: 0.687461, acc.: 52.93%] [G loss: 0.756258]
8/8 [==============================] - 0s 4ms/step
8491 [D loss: 0.680576, acc.: 57.23%] [G loss: 0.737233]
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8492 [D loss: 0.679804, acc.: 57.23%] [G loss: 0.752655]
8/8 [==============================] - 0s 4ms/step
8493 [D loss: 0.665818, acc.: 59.38%] [G loss: 0.762176]
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8494 [D loss: 0.685649, acc.: 55.08%] [G loss: 0.755921]
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8495 [D loss: 0.664221, acc.: 61.72%] [G loss: 0.749897]
8/8 [==============================] - 0s 4ms/step
8496 [D loss: 0.682418, acc.: 56.64%] [G loss: 0.759059]
8/8 [==============================] - 0s 4ms/step
8497 [D loss: 0.688457, acc.: 52.93%] [G loss: 0.750125]
8/8 [==============================] - 0s 4ms/step
8498 [D loss: 0.679884, acc.: 57.03%] [G loss: 0.765914]
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8499 [D loss: 0.674370, acc.: 57.42%] [G loss: 0.782338]
8/8 [==============================] - 0s 4ms/step
8500 [D loss: 0.682085, acc.: 56.05%] [G loss: 0.763399]
1/1 [==============================] - 0s 19ms/step
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8501 [D loss: 0.672684, acc.: 59.57%] [G loss: 0.761783]
8/8 [==============================] - 0s 4ms/step
8502 [D loss: 0.668089, acc.: 60.35%] [G loss: 0.753438]
8/8 [==============================] - 0s 4ms/step
8503 [D loss: 0.682720, acc.: 56.64%] [G loss: 0.747144]
8/8 [==============================] - 0s 4ms/step
8504 [D loss: 0.674503, acc.: 58.40%] [G loss: 0.756786]
8/8 [==============================] - 0s 4ms/step
8505 [D loss: 0.684310, acc.: 55.86%] [G loss: 0.747146]
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8506 [D loss: 0.681438, acc.: 58.40%] [G loss: 0.737396]
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8507 [D loss: 0.685380, acc.: 53.52%] [G loss: 0.760053]
8/8 [==============================] - 0s 4ms/step
8508 [D loss: 0.675090, acc.: 58.20%] [G loss: 0.744321]
8/8 [==============================] - 0s 4ms/step
8509 [D loss: 0.679662, acc.: 55.08%] [G loss: 0.750289]
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8510 [D loss: 0.674188, acc.: 57.62%] [G loss: 0.755663]
8/8 [==============================] - 0s 4ms/step
8511 [D loss: 0.679789, acc.: 55.86%] [G loss: 0.742313]
8/8 [==============================] - 0s 4ms/step
8512 [D loss: 0.681581, acc.: 56.25%] [G loss: 0.735798]
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8513 [D loss: 0.668802, acc.: 58.40%] [G loss: 0.726825]
8/8 [==============================] - 0s 4ms/step
8514 [D loss: 0.671695, acc.: 56.45%] [G loss: 0.722599]
8/8 [==============================] - 0s 4ms/step
8515 [D loss: 0.680257, acc.: 56.05%] [G loss: 0.751523]
8/8 [==============================] - 0s 4ms/step
8516 [D loss: 0.683980, acc.: 51.76%] [G loss: 0.738931]
8/8 [==============================] - 0s 4ms/step
8517 [D loss: 0.684393, acc.: 54.88%] [G loss: 0.752478]
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8518 [D loss: 0.675734, acc.: 56.25%] [G loss: 0.748172]
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8519 [D loss: 0.672951, acc.: 57.03%] [G loss: 0.761270]
8/8 [==============================] - 0s 4ms/step
8520 [D loss: 0.679576, acc.: 55.86%] [G loss: 0.753824]
8/8 [==============================] - 0s 4ms/step
8521 [D loss: 0.673389, acc.: 57.23%] [G loss: 0.755841]
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8522 [D loss: 0.672161, acc.: 57.23%] [G loss: 0.735192]
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8523 [D loss: 0.690326, acc.: 53.52%] [G loss: 0.755156]
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8524 [D loss: 0.682173, acc.: 56.45%] [G loss: 0.746719]
8/8 [==============================] - 0s 4ms/step
8525 [D loss: 0.686202, acc.: 53.52%] [G loss: 0.738705]
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8526 [D loss: 0.678640, acc.: 57.03%] [G loss: 0.754410]
8/8 [==============================] - 0s 4ms/step
8527 [D loss: 0.681695, acc.: 56.05%] [G loss: 0.756058]
8/8 [==============================] - 0s 4ms/step
8528 [D loss: 0.678243, acc.: 56.05%] [G loss: 0.764914]
8/8 [==============================] - 0s 4ms/step
8529 [D loss: 0.673904, acc.: 55.66%] [G loss: 0.749424]
8/8 [==============================] - 0s 4ms/step
8530 [D loss: 0.666965, acc.: 59.77%] [G loss: 0.756337]
8/8 [==============================] - 0s 4ms/step
8531 [D loss: 0.680916, acc.: 56.05%] [G loss: 0.723646]
8/8 [==============================] - 0s 4ms/step
8532 [D loss: 0.680477, acc.: 56.05%] [G loss: 0.739608]
8/8 [==============================] - 0s 4ms/step
8533 [D loss: 0.677072, acc.: 55.86%] [G loss: 0.747480]
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8534 [D loss: 0.668535, acc.: 58.40%] [G loss: 0.757480]
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8535 [D loss: 0.676703, acc.: 59.18%] [G loss: 0.743662]
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8536 [D loss: 0.682332, acc.: 55.86%] [G loss: 0.748884]
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8537 [D loss: 0.682344, acc.: 56.25%] [G loss: 0.751424]
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8538 [D loss: 0.688274, acc.: 55.86%] [G loss: 0.755030]
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8539 [D loss: 0.685607, acc.: 58.01%] [G loss: 0.736506]
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8540 [D loss: 0.667202, acc.: 59.18%] [G loss: 0.749882]
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8541 [D loss: 0.692254, acc.: 51.95%] [G loss: 0.753170]
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8542 [D loss: 0.686851, acc.: 53.71%] [G loss: 0.765968]
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8543 [D loss: 0.682140, acc.: 55.47%] [G loss: 0.779462]
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8544 [D loss: 0.669005, acc.: 58.20%] [G loss: 0.783502]
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8545 [D loss: 0.678396, acc.: 53.71%] [G loss: 0.786676]
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8546 [D loss: 0.683192, acc.: 54.10%] [G loss: 0.774007]
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8547 [D loss: 0.671549, acc.: 57.42%] [G loss: 0.742747]
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8548 [D loss: 0.663909, acc.: 59.77%] [G loss: 0.735941]
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8549 [D loss: 0.680001, acc.: 52.93%] [G loss: 0.723463]
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8550 [D loss: 0.683102, acc.: 55.86%] [G loss: 0.747046]
1/1 [==============================] - 0s 20ms/step
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8551 [D loss: 0.682062, acc.: 55.86%] [G loss: 0.720597]
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8552 [D loss: 0.671150, acc.: 57.42%] [G loss: 0.771123]
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8553 [D loss: 0.667001, acc.: 58.01%] [G loss: 0.775839]
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8554 [D loss: 0.676315, acc.: 56.84%] [G loss: 0.757540]
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8555 [D loss: 0.675622, acc.: 55.66%] [G loss: 0.750927]
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8556 [D loss: 0.666509, acc.: 58.98%] [G loss: 0.736316]
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8557 [D loss: 0.681031, acc.: 57.03%] [G loss: 0.743370]
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8558 [D loss: 0.670910, acc.: 57.62%] [G loss: 0.730786]
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8559 [D loss: 0.683569, acc.: 54.49%] [G loss: 0.718782]
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8560 [D loss: 0.682578, acc.: 56.64%] [G loss: 0.737074]
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8561 [D loss: 0.686842, acc.: 55.47%] [G loss: 0.752003]
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8562 [D loss: 0.681952, acc.: 56.45%] [G loss: 0.771303]
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8563 [D loss: 0.674099, acc.: 61.72%] [G loss: 0.769603]
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8564 [D loss: 0.670878, acc.: 60.35%] [G loss: 0.779296]
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8565 [D loss: 0.673989, acc.: 57.42%] [G loss: 0.770696]
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8566 [D loss: 0.660795, acc.: 62.30%] [G loss: 0.764526]
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8567 [D loss: 0.684639, acc.: 55.27%] [G loss: 0.743734]
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8568 [D loss: 0.676817, acc.: 57.23%] [G loss: 0.753406]
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8569 [D loss: 0.675929, acc.: 57.03%] [G loss: 0.738064]
8/8 [==============================] - 0s 4ms/step
8570 [D loss: 0.680879, acc.: 54.69%] [G loss: 0.764360]
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8571 [D loss: 0.672607, acc.: 59.38%] [G loss: 0.750943]
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8572 [D loss: 0.684653, acc.: 56.45%] [G loss: 0.744622]
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8573 [D loss: 0.665813, acc.: 62.50%] [G loss: 0.774093]
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8574 [D loss: 0.680335, acc.: 55.86%] [G loss: 0.754539]
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8575 [D loss: 0.687325, acc.: 54.69%] [G loss: 0.745941]
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8576 [D loss: 0.676699, acc.: 55.66%] [G loss: 0.760314]
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8577 [D loss: 0.667175, acc.: 61.52%] [G loss: 0.728956]
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8578 [D loss: 0.679198, acc.: 54.10%] [G loss: 0.745323]
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8579 [D loss: 0.675746, acc.: 56.25%] [G loss: 0.766744]
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8580 [D loss: 0.675035, acc.: 59.18%] [G loss: 0.750762]
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8581 [D loss: 0.681428, acc.: 56.25%] [G loss: 0.754263]
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8582 [D loss: 0.667255, acc.: 59.18%] [G loss: 0.751170]
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8583 [D loss: 0.678547, acc.: 56.25%] [G loss: 0.751176]
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8584 [D loss: 0.681021, acc.: 55.66%] [G loss: 0.756512]
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8585 [D loss: 0.687525, acc.: 55.27%] [G loss: 0.738221]
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8586 [D loss: 0.680085, acc.: 57.03%] [G loss: 0.736091]
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8587 [D loss: 0.682359, acc.: 54.30%] [G loss: 0.750120]
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8588 [D loss: 0.682290, acc.: 57.23%] [G loss: 0.758983]
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8589 [D loss: 0.680679, acc.: 56.25%] [G loss: 0.750200]
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8590 [D loss: 0.670836, acc.: 59.38%] [G loss: 0.772666]
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8591 [D loss: 0.679344, acc.: 56.45%] [G loss: 0.761041]
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8592 [D loss: 0.659248, acc.: 62.89%] [G loss: 0.750506]
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8593 [D loss: 0.671352, acc.: 55.86%] [G loss: 0.748680]
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8594 [D loss: 0.672030, acc.: 57.62%] [G loss: 0.756916]
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8595 [D loss: 0.679271, acc.: 55.66%] [G loss: 0.752479]
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8596 [D loss: 0.673002, acc.: 57.03%] [G loss: 0.750280]
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8597 [D loss: 0.678097, acc.: 57.42%] [G loss: 0.736717]
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8598 [D loss: 0.680044, acc.: 55.47%] [G loss: 0.767649]
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8599 [D loss: 0.681436, acc.: 54.30%] [G loss: 0.762450]
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8600 [D loss: 0.673775, acc.: 58.79%] [G loss: 0.760664]
1/1 [==============================] - 0s 17ms/step
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8601 [D loss: 0.676761, acc.: 57.03%] [G loss: 0.772762]
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8602 [D loss: 0.673145, acc.: 58.98%] [G loss: 0.762185]
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8603 [D loss: 0.669875, acc.: 57.62%] [G loss: 0.754425]
8/8 [==============================] - 0s 4ms/step
8604 [D loss: 0.682263, acc.: 57.03%] [G loss: 0.749639]
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8605 [D loss: 0.686304, acc.: 54.10%] [G loss: 0.746644]
8/8 [==============================] - 0s 4ms/step
8606 [D loss: 0.674599, acc.: 56.45%] [G loss: 0.755014]
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8607 [D loss: 0.663259, acc.: 60.55%] [G loss: 0.753124]
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8608 [D loss: 0.682837, acc.: 56.45%] [G loss: 0.769969]
8/8 [==============================] - 0s 4ms/step
8609 [D loss: 0.675725, acc.: 57.81%] [G loss: 0.763518]
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8610 [D loss: 0.673846, acc.: 58.59%] [G loss: 0.762022]
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8611 [D loss: 0.670532, acc.: 57.81%] [G loss: 0.782665]
8/8 [==============================] - 0s 4ms/step
8612 [D loss: 0.673974, acc.: 55.27%] [G loss: 0.732472]
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8613 [D loss: 0.679896, acc.: 58.01%] [G loss: 0.762324]
8/8 [==============================] - 0s 4ms/step
8614 [D loss: 0.679218, acc.: 57.62%] [G loss: 0.753356]
8/8 [==============================] - 0s 4ms/step
8615 [D loss: 0.682734, acc.: 56.05%] [G loss: 0.751222]
8/8 [==============================] - 0s 4ms/step
8616 [D loss: 0.674773, acc.: 55.27%] [G loss: 0.740465]
8/8 [==============================] - 0s 4ms/step
8617 [D loss: 0.684369, acc.: 56.64%] [G loss: 0.739092]
8/8 [==============================] - 0s 4ms/step
8618 [D loss: 0.676292, acc.: 55.47%] [G loss: 0.737092]
8/8 [==============================] - 0s 4ms/step
8619 [D loss: 0.675558, acc.: 56.84%] [G loss: 0.749233]
8/8 [==============================] - 0s 4ms/step
8620 [D loss: 0.679872, acc.: 54.30%] [G loss: 0.761580]
8/8 [==============================] - 0s 4ms/step
8621 [D loss: 0.691032, acc.: 52.34%] [G loss: 0.758309]
8/8 [==============================] - 0s 4ms/step
8622 [D loss: 0.675920, acc.: 57.62%] [G loss: 0.754141]
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8623 [D loss: 0.665276, acc.: 59.96%] [G loss: 0.759481]
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8624 [D loss: 0.670730, acc.: 58.40%] [G loss: 0.753012]
8/8 [==============================] - 0s 4ms/step
8625 [D loss: 0.680555, acc.: 57.81%] [G loss: 0.757338]
8/8 [==============================] - 0s 4ms/step
8626 [D loss: 0.671490, acc.: 59.18%] [G loss: 0.747362]
8/8 [==============================] - 0s 4ms/step
8627 [D loss: 0.683631, acc.: 56.84%] [G loss: 0.730062]
8/8 [==============================] - 0s 4ms/step
8628 [D loss: 0.680324, acc.: 54.88%] [G loss: 0.751839]
8/8 [==============================] - 0s 4ms/step
8629 [D loss: 0.677054, acc.: 55.27%] [G loss: 0.752425]
8/8 [==============================] - 0s 4ms/step
8630 [D loss: 0.682631, acc.: 54.30%] [G loss: 0.762404]
8/8 [==============================] - 0s 4ms/step
8631 [D loss: 0.669070, acc.: 56.25%] [G loss: 0.769069]
8/8 [==============================] - 0s 4ms/step
8632 [D loss: 0.678673, acc.: 56.84%] [G loss: 0.740497]
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8633 [D loss: 0.677634, acc.: 59.57%] [G loss: 0.753748]
8/8 [==============================] - 0s 4ms/step
8634 [D loss: 0.677973, acc.: 55.27%] [G loss: 0.747958]
8/8 [==============================] - 0s 4ms/step
8635 [D loss: 0.671591, acc.: 58.01%] [G loss: 0.741952]
8/8 [==============================] - 0s 4ms/step
8636 [D loss: 0.675012, acc.: 57.62%] [G loss: 0.738497]
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8637 [D loss: 0.675637, acc.: 57.62%] [G loss: 0.739629]
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8638 [D loss: 0.679828, acc.: 55.27%] [G loss: 0.743306]
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8639 [D loss: 0.683013, acc.: 54.88%] [G loss: 0.747453]
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8640 [D loss: 0.683009, acc.: 56.45%] [G loss: 0.748283]
8/8 [==============================] - 0s 4ms/step
8641 [D loss: 0.668566, acc.: 60.35%] [G loss: 0.755495]
8/8 [==============================] - 0s 4ms/step
8642 [D loss: 0.671208, acc.: 58.59%] [G loss: 0.754573]
8/8 [==============================] - 0s 4ms/step
8643 [D loss: 0.674864, acc.: 58.40%] [G loss: 0.754964]
8/8 [==============================] - 0s 4ms/step
8644 [D loss: 0.681595, acc.: 56.05%] [G loss: 0.763325]
8/8 [==============================] - 0s 4ms/step
8645 [D loss: 0.677228, acc.: 55.47%] [G loss: 0.741052]
8/8 [==============================] - 0s 4ms/step
8646 [D loss: 0.681056, acc.: 55.66%] [G loss: 0.758701]
8/8 [==============================] - 0s 4ms/step
8647 [D loss: 0.678875, acc.: 57.03%] [G loss: 0.756825]
8/8 [==============================] - 0s 4ms/step
8648 [D loss: 0.686990, acc.: 54.88%] [G loss: 0.766795]
8/8 [==============================] - 0s 4ms/step
8649 [D loss: 0.673783, acc.: 58.79%] [G loss: 0.766857]
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8650 [D loss: 0.672175, acc.: 58.20%] [G loss: 0.774482]
1/1 [==============================] - 0s 22ms/step
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8651 [D loss: 0.675004, acc.: 58.01%] [G loss: 0.750606]
8/8 [==============================] - 0s 4ms/step
8652 [D loss: 0.674820, acc.: 56.25%] [G loss: 0.764017]
8/8 [==============================] - 0s 4ms/step
8653 [D loss: 0.678589, acc.: 55.47%] [G loss: 0.774626]
8/8 [==============================] - 0s 4ms/step
8654 [D loss: 0.675786, acc.: 55.86%] [G loss: 0.738465]
8/8 [==============================] - 0s 4ms/step
8655 [D loss: 0.666391, acc.: 61.72%] [G loss: 0.749923]
8/8 [==============================] - 0s 4ms/step
8656 [D loss: 0.676820, acc.: 56.84%] [G loss: 0.738820]
8/8 [==============================] - 0s 4ms/step
8657 [D loss: 0.682248, acc.: 54.10%] [G loss: 0.749853]
8/8 [==============================] - 0s 4ms/step
8658 [D loss: 0.672139, acc.: 55.66%] [G loss: 0.756494]
8/8 [==============================] - 0s 4ms/step
8659 [D loss: 0.683249, acc.: 53.91%] [G loss: 0.766487]
8/8 [==============================] - 0s 4ms/step
8660 [D loss: 0.670437, acc.: 58.98%] [G loss: 0.755086]
8/8 [==============================] - 0s 4ms/step
8661 [D loss: 0.673065, acc.: 56.05%] [G loss: 0.753610]
8/8 [==============================] - 0s 4ms/step
8662 [D loss: 0.684649, acc.: 54.30%] [G loss: 0.774054]
8/8 [==============================] - 0s 4ms/step
8663 [D loss: 0.680583, acc.: 54.30%] [G loss: 0.746816]
8/8 [==============================] - 0s 4ms/step
8664 [D loss: 0.683275, acc.: 56.25%] [G loss: 0.764811]
8/8 [==============================] - 0s 4ms/step
8665 [D loss: 0.670586, acc.: 58.59%] [G loss: 0.757217]
8/8 [==============================] - 0s 4ms/step
8666 [D loss: 0.674329, acc.: 56.64%] [G loss: 0.752190]
8/8 [==============================] - 0s 4ms/step
8667 [D loss: 0.675205, acc.: 55.86%] [G loss: 0.764994]
8/8 [==============================] - 0s 4ms/step
8668 [D loss: 0.671889, acc.: 58.40%] [G loss: 0.754604]
8/8 [==============================] - 0s 4ms/step
8669 [D loss: 0.684471, acc.: 56.05%] [G loss: 0.755391]
8/8 [==============================] - 0s 4ms/step
8670 [D loss: 0.675953, acc.: 59.38%] [G loss: 0.746651]
8/8 [==============================] - 0s 4ms/step
8671 [D loss: 0.676547, acc.: 57.62%] [G loss: 0.751887]
8/8 [==============================] - 0s 4ms/step
8672 [D loss: 0.677837, acc.: 57.03%] [G loss: 0.741179]
8/8 [==============================] - 0s 4ms/step
8673 [D loss: 0.680232, acc.: 58.20%] [G loss: 0.749326]
8/8 [==============================] - 0s 4ms/step
8674 [D loss: 0.684070, acc.: 54.69%] [G loss: 0.746781]
8/8 [==============================] - 0s 4ms/step
8675 [D loss: 0.674462, acc.: 58.20%] [G loss: 0.744451]
8/8 [==============================] - 0s 4ms/step
8676 [D loss: 0.680173, acc.: 58.79%] [G loss: 0.737904]
8/8 [==============================] - 0s 4ms/step
8677 [D loss: 0.679102, acc.: 58.20%] [G loss: 0.741775]
8/8 [==============================] - 0s 4ms/step
8678 [D loss: 0.676928, acc.: 56.64%] [G loss: 0.750917]
8/8 [==============================] - 0s 4ms/step
8679 [D loss: 0.676927, acc.: 59.57%] [G loss: 0.738573]
8/8 [==============================] - 0s 4ms/step
8680 [D loss: 0.681352, acc.: 55.66%] [G loss: 0.735349]
8/8 [==============================] - 0s 4ms/step
8681 [D loss: 0.674459, acc.: 59.38%] [G loss: 0.737450]
8/8 [==============================] - 0s 4ms/step
8682 [D loss: 0.681420, acc.: 56.64%] [G loss: 0.746006]
8/8 [==============================] - 0s 4ms/step
8683 [D loss: 0.670582, acc.: 58.98%] [G loss: 0.743938]
8/8 [==============================] - 0s 4ms/step
8684 [D loss: 0.686011, acc.: 51.56%] [G loss: 0.746534]
8/8 [==============================] - 0s 4ms/step
8685 [D loss: 0.681041, acc.: 54.88%] [G loss: 0.754316]
8/8 [==============================] - 0s 4ms/step
8686 [D loss: 0.683769, acc.: 55.86%] [G loss: 0.740152]
8/8 [==============================] - 0s 4ms/step
8687 [D loss: 0.678789, acc.: 56.05%] [G loss: 0.757657]
8/8 [==============================] - 0s 4ms/step
8688 [D loss: 0.676342, acc.: 58.01%] [G loss: 0.758194]
8/8 [==============================] - 0s 4ms/step
8689 [D loss: 0.675029, acc.: 57.81%] [G loss: 0.754005]
8/8 [==============================] - 0s 4ms/step
8690 [D loss: 0.651874, acc.: 63.48%] [G loss: 0.770512]
8/8 [==============================] - 0s 4ms/step
8691 [D loss: 0.667034, acc.: 61.52%] [G loss: 0.763532]
8/8 [==============================] - 0s 4ms/step
8692 [D loss: 0.666543, acc.: 58.01%] [G loss: 0.752984]
8/8 [==============================] - 0s 4ms/step
8693 [D loss: 0.691664, acc.: 54.30%] [G loss: 0.748104]
8/8 [==============================] - 0s 4ms/step
8694 [D loss: 0.674973, acc.: 58.01%] [G loss: 0.749269]
8/8 [==============================] - 0s 4ms/step
8695 [D loss: 0.684619, acc.: 55.27%] [G loss: 0.736777]
8/8 [==============================] - 0s 4ms/step
8696 [D loss: 0.683569, acc.: 53.91%] [G loss: 0.742195]
8/8 [==============================] - 0s 4ms/step
8697 [D loss: 0.675419, acc.: 60.16%] [G loss: 0.766189]
8/8 [==============================] - 0s 4ms/step
8698 [D loss: 0.671903, acc.: 58.01%] [G loss: 0.769116]
8/8 [==============================] - 0s 4ms/step
8699 [D loss: 0.684116, acc.: 54.88%] [G loss: 0.750276]
8/8 [==============================] - 0s 4ms/step
8700 [D loss: 0.684532, acc.: 52.93%] [G loss: 0.766930]
1/1 [==============================] - 0s 17ms/step
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8701 [D loss: 0.676897, acc.: 56.64%] [G loss: 0.744496]
8/8 [==============================] - 0s 4ms/step
8702 [D loss: 0.681533, acc.: 54.88%] [G loss: 0.750941]
8/8 [==============================] - 0s 4ms/step
8703 [D loss: 0.683701, acc.: 56.64%] [G loss: 0.743497]
8/8 [==============================] - 0s 4ms/step
8704 [D loss: 0.678657, acc.: 55.66%] [G loss: 0.747165]
8/8 [==============================] - 0s 4ms/step
8705 [D loss: 0.668571, acc.: 59.77%] [G loss: 0.756551]
8/8 [==============================] - 0s 4ms/step
8706 [D loss: 0.681281, acc.: 55.66%] [G loss: 0.749740]
8/8 [==============================] - 0s 4ms/step
8707 [D loss: 0.673245, acc.: 56.45%] [G loss: 0.752226]
8/8 [==============================] - 0s 4ms/step
8708 [D loss: 0.678717, acc.: 55.47%] [G loss: 0.748094]
8/8 [==============================] - 0s 4ms/step
8709 [D loss: 0.677780, acc.: 58.01%] [G loss: 0.772506]
8/8 [==============================] - 0s 4ms/step
8710 [D loss: 0.675990, acc.: 57.03%] [G loss: 0.753346]
8/8 [==============================] - 0s 4ms/step
8711 [D loss: 0.678000, acc.: 57.42%] [G loss: 0.742402]
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8712 [D loss: 0.672521, acc.: 58.79%] [G loss: 0.748914]
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8713 [D loss: 0.677431, acc.: 56.64%] [G loss: 0.747857]
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8714 [D loss: 0.672105, acc.: 59.77%] [G loss: 0.744772]
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8715 [D loss: 0.676540, acc.: 57.42%] [G loss: 0.745659]
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8716 [D loss: 0.686780, acc.: 54.88%] [G loss: 0.750133]
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8717 [D loss: 0.661022, acc.: 58.20%] [G loss: 0.751625]
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8718 [D loss: 0.687259, acc.: 53.12%] [G loss: 0.767058]
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8719 [D loss: 0.677513, acc.: 56.84%] [G loss: 0.747665]
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8720 [D loss: 0.671511, acc.: 58.59%] [G loss: 0.748092]
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8721 [D loss: 0.680292, acc.: 57.42%] [G loss: 0.744132]
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8722 [D loss: 0.667371, acc.: 58.98%] [G loss: 0.747928]
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8723 [D loss: 0.679091, acc.: 55.66%] [G loss: 0.744224]
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8724 [D loss: 0.684885, acc.: 53.52%] [G loss: 0.740781]
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8725 [D loss: 0.680215, acc.: 57.81%] [G loss: 0.765697]
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8726 [D loss: 0.675173, acc.: 59.96%] [G loss: 0.749686]
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8727 [D loss: 0.681654, acc.: 56.64%] [G loss: 0.740959]
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8728 [D loss: 0.670530, acc.: 59.77%] [G loss: 0.783959]
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8729 [D loss: 0.670660, acc.: 60.55%] [G loss: 0.743585]
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8730 [D loss: 0.674888, acc.: 56.25%] [G loss: 0.749709]
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8731 [D loss: 0.688496, acc.: 53.52%] [G loss: 0.769416]
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8732 [D loss: 0.676400, acc.: 56.25%] [G loss: 0.751323]
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8733 [D loss: 0.674647, acc.: 57.23%] [G loss: 0.751322]
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8734 [D loss: 0.680551, acc.: 56.45%] [G loss: 0.745985]
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8735 [D loss: 0.688723, acc.: 51.95%] [G loss: 0.753014]
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8736 [D loss: 0.672149, acc.: 61.52%] [G loss: 0.765181]
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8737 [D loss: 0.679733, acc.: 57.42%] [G loss: 0.769621]
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8738 [D loss: 0.671619, acc.: 58.79%] [G loss: 0.746801]
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8739 [D loss: 0.687435, acc.: 55.08%] [G loss: 0.747892]
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8740 [D loss: 0.682341, acc.: 54.88%] [G loss: 0.740952]
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8741 [D loss: 0.678123, acc.: 54.69%] [G loss: 0.739398]
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8742 [D loss: 0.684442, acc.: 57.23%] [G loss: 0.746816]
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8743 [D loss: 0.671838, acc.: 57.23%] [G loss: 0.731527]
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8744 [D loss: 0.680213, acc.: 55.86%] [G loss: 0.751138]
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8745 [D loss: 0.674668, acc.: 57.62%] [G loss: 0.743828]
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8746 [D loss: 0.671830, acc.: 60.94%] [G loss: 0.743178]
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8747 [D loss: 0.673791, acc.: 59.38%] [G loss: 0.747406]
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8748 [D loss: 0.671063, acc.: 58.98%] [G loss: 0.742624]
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8749 [D loss: 0.685147, acc.: 56.25%] [G loss: 0.727558]
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8750 [D loss: 0.680791, acc.: 57.23%] [G loss: 0.759265]
1/1 [==============================] - 0s 19ms/step
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8751 [D loss: 0.691460, acc.: 51.17%] [G loss: 0.747980]
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8752 [D loss: 0.683391, acc.: 54.30%] [G loss: 0.755864]
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8753 [D loss: 0.673906, acc.: 57.23%] [G loss: 0.752677]
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8754 [D loss: 0.679098, acc.: 59.57%] [G loss: 0.754853]
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8755 [D loss: 0.672671, acc.: 62.70%] [G loss: 0.752531]
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8756 [D loss: 0.681060, acc.: 56.84%] [G loss: 0.759714]
8/8 [==============================] - 0s 4ms/step
8757 [D loss: 0.678486, acc.: 58.01%] [G loss: 0.748781]
8/8 [==============================] - 0s 4ms/step
8758 [D loss: 0.673818, acc.: 58.59%] [G loss: 0.761355]
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8759 [D loss: 0.680042, acc.: 55.66%] [G loss: 0.762657]
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8760 [D loss: 0.677276, acc.: 55.86%] [G loss: 0.748665]
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8761 [D loss: 0.676573, acc.: 56.84%] [G loss: 0.750708]
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8762 [D loss: 0.678893, acc.: 56.45%] [G loss: 0.756565]
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8763 [D loss: 0.671472, acc.: 58.79%] [G loss: 0.762157]
8/8 [==============================] - 0s 4ms/step
8764 [D loss: 0.685203, acc.: 54.69%] [G loss: 0.749744]
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8765 [D loss: 0.666318, acc.: 60.74%] [G loss: 0.743370]
8/8 [==============================] - 0s 4ms/step
8766 [D loss: 0.683235, acc.: 57.03%] [G loss: 0.770207]
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8767 [D loss: 0.674373, acc.: 58.01%] [G loss: 0.756289]
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8768 [D loss: 0.670828, acc.: 61.13%] [G loss: 0.741988]
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8769 [D loss: 0.671289, acc.: 60.94%] [G loss: 0.753107]
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8770 [D loss: 0.674170, acc.: 58.40%] [G loss: 0.763374]
8/8 [==============================] - 0s 4ms/step
8771 [D loss: 0.685080, acc.: 56.05%] [G loss: 0.767336]
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8772 [D loss: 0.672798, acc.: 58.40%] [G loss: 0.766755]
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8773 [D loss: 0.672739, acc.: 59.18%] [G loss: 0.742669]
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8774 [D loss: 0.679847, acc.: 54.88%] [G loss: 0.750007]
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8775 [D loss: 0.677977, acc.: 58.40%] [G loss: 0.732761]
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8776 [D loss: 0.686246, acc.: 54.88%] [G loss: 0.756846]
8/8 [==============================] - 0s 4ms/step
8777 [D loss: 0.681969, acc.: 55.66%] [G loss: 0.741529]
8/8 [==============================] - 0s 4ms/step
8778 [D loss: 0.688699, acc.: 53.91%] [G loss: 0.757750]
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8779 [D loss: 0.677917, acc.: 58.01%] [G loss: 0.741230]
8/8 [==============================] - 0s 4ms/step
8780 [D loss: 0.676123, acc.: 55.47%] [G loss: 0.750342]
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8781 [D loss: 0.673478, acc.: 58.79%] [G loss: 0.730604]
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8782 [D loss: 0.672460, acc.: 57.81%] [G loss: 0.751139]
8/8 [==============================] - 0s 4ms/step
8783 [D loss: 0.685906, acc.: 51.76%] [G loss: 0.747377]
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8784 [D loss: 0.672294, acc.: 59.77%] [G loss: 0.744220]
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8785 [D loss: 0.659840, acc.: 63.28%] [G loss: 0.763863]
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8786 [D loss: 0.656053, acc.: 64.84%] [G loss: 0.751414]
8/8 [==============================] - 0s 4ms/step
8787 [D loss: 0.681183, acc.: 54.30%] [G loss: 0.732587]
8/8 [==============================] - 0s 4ms/step
8788 [D loss: 0.684737, acc.: 54.49%] [G loss: 0.736150]
8/8 [==============================] - 0s 4ms/step
8789 [D loss: 0.675635, acc.: 57.42%] [G loss: 0.716363]
8/8 [==============================] - 0s 4ms/step
8790 [D loss: 0.685538, acc.: 54.88%] [G loss: 0.740984]
8/8 [==============================] - 0s 4ms/step
8791 [D loss: 0.686043, acc.: 56.84%] [G loss: 0.745448]
8/8 [==============================] - 0s 4ms/step
8792 [D loss: 0.673141, acc.: 59.38%] [G loss: 0.769270]
8/8 [==============================] - 0s 4ms/step
8793 [D loss: 0.660983, acc.: 61.13%] [G loss: 0.785157]
8/8 [==============================] - 0s 4ms/step
8794 [D loss: 0.684766, acc.: 54.49%] [G loss: 0.797443]
8/8 [==============================] - 0s 4ms/step
8795 [D loss: 0.667119, acc.: 60.16%] [G loss: 0.800389]
8/8 [==============================] - 0s 4ms/step
8796 [D loss: 0.673382, acc.: 59.38%] [G loss: 0.771210]
8/8 [==============================] - 0s 4ms/step
8797 [D loss: 0.687989, acc.: 54.69%] [G loss: 0.737271]
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8798 [D loss: 0.675718, acc.: 55.66%] [G loss: 0.754782]
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8799 [D loss: 0.686533, acc.: 51.37%] [G loss: 0.733152]
8/8 [==============================] - 0s 4ms/step
8800 [D loss: 0.681397, acc.: 55.66%] [G loss: 0.759256]
1/1 [==============================] - 0s 19ms/step
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8801 [D loss: 0.674210, acc.: 60.35%] [G loss: 0.770743]
8/8 [==============================] - 0s 4ms/step
8802 [D loss: 0.663187, acc.: 62.30%] [G loss: 0.763480]
8/8 [==============================] - 0s 4ms/step
8803 [D loss: 0.668970, acc.: 58.20%] [G loss: 0.770100]
8/8 [==============================] - 0s 4ms/step
8804 [D loss: 0.676856, acc.: 57.62%] [G loss: 0.754750]
8/8 [==============================] - 0s 4ms/step
8805 [D loss: 0.683520, acc.: 55.47%] [G loss: 0.746957]
8/8 [==============================] - 0s 4ms/step
8806 [D loss: 0.681932, acc.: 55.86%] [G loss: 0.737861]
8/8 [==============================] - 0s 4ms/step
8807 [D loss: 0.692230, acc.: 51.17%] [G loss: 0.741539]
8/8 [==============================] - 0s 4ms/step
8808 [D loss: 0.678742, acc.: 57.23%] [G loss: 0.744706]
8/8 [==============================] - 0s 4ms/step
8809 [D loss: 0.671654, acc.: 58.79%] [G loss: 0.771217]
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8810 [D loss: 0.672182, acc.: 58.01%] [G loss: 0.763054]
8/8 [==============================] - 0s 4ms/step
8811 [D loss: 0.680964, acc.: 54.30%] [G loss: 0.773689]
8/8 [==============================] - 0s 4ms/step
8812 [D loss: 0.680538, acc.: 54.30%] [G loss: 0.763411]
8/8 [==============================] - 0s 4ms/step
8813 [D loss: 0.664679, acc.: 62.50%] [G loss: 0.777082]
8/8 [==============================] - 0s 4ms/step
8814 [D loss: 0.678735, acc.: 55.86%] [G loss: 0.756362]
8/8 [==============================] - 0s 4ms/step
8815 [D loss: 0.683380, acc.: 56.25%] [G loss: 0.767217]
8/8 [==============================] - 0s 4ms/step
8816 [D loss: 0.669797, acc.: 59.38%] [G loss: 0.751642]
8/8 [==============================] - 0s 4ms/step
8817 [D loss: 0.683971, acc.: 55.27%] [G loss: 0.735625]
8/8 [==============================] - 0s 4ms/step
8818 [D loss: 0.669587, acc.: 58.98%] [G loss: 0.740413]
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8819 [D loss: 0.676578, acc.: 57.81%] [G loss: 0.738232]
8/8 [==============================] - 0s 4ms/step
8820 [D loss: 0.671034, acc.: 57.42%] [G loss: 0.760969]
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8821 [D loss: 0.669205, acc.: 59.18%] [G loss: 0.767060]
8/8 [==============================] - 0s 4ms/step
8822 [D loss: 0.674155, acc.: 57.62%] [G loss: 0.756891]
8/8 [==============================] - 0s 4ms/step
8823 [D loss: 0.670195, acc.: 60.35%] [G loss: 0.765677]
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8824 [D loss: 0.689129, acc.: 51.95%] [G loss: 0.751522]
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8825 [D loss: 0.675764, acc.: 55.86%] [G loss: 0.765657]
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8826 [D loss: 0.673809, acc.: 56.64%] [G loss: 0.754976]
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8827 [D loss: 0.677117, acc.: 56.64%] [G loss: 0.741970]
8/8 [==============================] - 0s 4ms/step
8828 [D loss: 0.686814, acc.: 53.71%] [G loss: 0.745927]
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8829 [D loss: 0.672974, acc.: 58.01%] [G loss: 0.751212]
8/8 [==============================] - 0s 4ms/step
8830 [D loss: 0.676835, acc.: 54.10%] [G loss: 0.762777]
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8831 [D loss: 0.669324, acc.: 60.94%] [G loss: 0.770193]
8/8 [==============================] - 0s 4ms/step
8832 [D loss: 0.672001, acc.: 55.27%] [G loss: 0.751033]
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8833 [D loss: 0.679759, acc.: 55.47%] [G loss: 0.738192]
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8834 [D loss: 0.692699, acc.: 52.54%] [G loss: 0.760267]
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8835 [D loss: 0.685672, acc.: 54.69%] [G loss: 0.751536]
8/8 [==============================] - 0s 4ms/step
8836 [D loss: 0.678529, acc.: 55.08%] [G loss: 0.749486]
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8837 [D loss: 0.673204, acc.: 55.66%] [G loss: 0.760141]
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8838 [D loss: 0.682280, acc.: 55.47%] [G loss: 0.762022]
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8839 [D loss: 0.690052, acc.: 53.52%] [G loss: 0.754609]
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8840 [D loss: 0.689965, acc.: 51.95%] [G loss: 0.761301]
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8841 [D loss: 0.675730, acc.: 59.18%] [G loss: 0.748609]
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8842 [D loss: 0.679542, acc.: 56.25%] [G loss: 0.748829]
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8843 [D loss: 0.677072, acc.: 58.20%] [G loss: 0.755286]
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8844 [D loss: 0.677371, acc.: 57.03%] [G loss: 0.753785]
8/8 [==============================] - 0s 4ms/step
8845 [D loss: 0.682216, acc.: 54.49%] [G loss: 0.761746]
8/8 [==============================] - 0s 4ms/step
8846 [D loss: 0.679001, acc.: 56.45%] [G loss: 0.756691]
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8847 [D loss: 0.673553, acc.: 54.30%] [G loss: 0.755338]
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8848 [D loss: 0.680286, acc.: 57.42%] [G loss: 0.766657]
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8849 [D loss: 0.682709, acc.: 55.86%] [G loss: 0.758189]
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8850 [D loss: 0.675006, acc.: 58.59%] [G loss: 0.757240]
1/1 [==============================] - 0s 17ms/step
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8851 [D loss: 0.683146, acc.: 54.10%] [G loss: 0.754698]
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8852 [D loss: 0.671302, acc.: 60.55%] [G loss: 0.747828]
8/8 [==============================] - 0s 4ms/step
8853 [D loss: 0.676809, acc.: 57.23%] [G loss: 0.742039]
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8854 [D loss: 0.677331, acc.: 54.88%] [G loss: 0.749075]
8/8 [==============================] - 0s 4ms/step
8855 [D loss: 0.681774, acc.: 55.27%] [G loss: 0.753227]
8/8 [==============================] - 0s 4ms/step
8856 [D loss: 0.676173, acc.: 55.08%] [G loss: 0.748090]
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8857 [D loss: 0.675946, acc.: 57.03%] [G loss: 0.768413]
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8858 [D loss: 0.674031, acc.: 57.42%] [G loss: 0.760313]
8/8 [==============================] - 0s 4ms/step
8859 [D loss: 0.686052, acc.: 53.12%] [G loss: 0.731688]
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8860 [D loss: 0.679393, acc.: 58.98%] [G loss: 0.747893]
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8861 [D loss: 0.683518, acc.: 56.25%] [G loss: 0.758282]
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8862 [D loss: 0.676176, acc.: 56.45%] [G loss: 0.748629]
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8863 [D loss: 0.677475, acc.: 56.25%] [G loss: 0.744378]
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8864 [D loss: 0.692602, acc.: 53.91%] [G loss: 0.764544]
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8865 [D loss: 0.683613, acc.: 54.69%] [G loss: 0.758641]
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8866 [D loss: 0.680643, acc.: 55.47%] [G loss: 0.783043]
8/8 [==============================] - 0s 4ms/step
8867 [D loss: 0.686543, acc.: 55.08%] [G loss: 0.760575]
8/8 [==============================] - 0s 4ms/step
8868 [D loss: 0.679699, acc.: 57.42%] [G loss: 0.780434]
8/8 [==============================] - 0s 4ms/step
8869 [D loss: 0.666423, acc.: 58.40%] [G loss: 0.761039]
8/8 [==============================] - 0s 4ms/step
8870 [D loss: 0.663638, acc.: 60.55%] [G loss: 0.766374]
8/8 [==============================] - 0s 4ms/step
8871 [D loss: 0.677319, acc.: 57.42%] [G loss: 0.776671]
8/8 [==============================] - 0s 4ms/step
8872 [D loss: 0.679537, acc.: 58.01%] [G loss: 0.753806]
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8873 [D loss: 0.681139, acc.: 58.01%] [G loss: 0.758314]
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8874 [D loss: 0.681688, acc.: 56.64%] [G loss: 0.760083]
8/8 [==============================] - 0s 4ms/step
8875 [D loss: 0.681790, acc.: 55.27%] [G loss: 0.742033]
8/8 [==============================] - 0s 4ms/step
8876 [D loss: 0.688058, acc.: 54.88%] [G loss: 0.765092]
8/8 [==============================] - 0s 4ms/step
8877 [D loss: 0.671755, acc.: 59.77%] [G loss: 0.765453]
8/8 [==============================] - 0s 4ms/step
8878 [D loss: 0.680798, acc.: 56.05%] [G loss: 0.756982]
8/8 [==============================] - 0s 4ms/step
8879 [D loss: 0.686451, acc.: 54.88%] [G loss: 0.747192]
8/8 [==============================] - 0s 4ms/step
8880 [D loss: 0.671932, acc.: 57.42%] [G loss: 0.731075]
8/8 [==============================] - 0s 4ms/step
8881 [D loss: 0.676434, acc.: 57.23%] [G loss: 0.745793]
8/8 [==============================] - 0s 4ms/step
8882 [D loss: 0.684258, acc.: 56.45%] [G loss: 0.740589]
8/8 [==============================] - 0s 4ms/step
8883 [D loss: 0.674684, acc.: 58.40%] [G loss: 0.733416]
8/8 [==============================] - 0s 4ms/step
8884 [D loss: 0.682404, acc.: 55.27%] [G loss: 0.748240]
8/8 [==============================] - 0s 4ms/step
8885 [D loss: 0.671283, acc.: 58.40%] [G loss: 0.741200]
8/8 [==============================] - 0s 4ms/step
8886 [D loss: 0.680941, acc.: 54.49%] [G loss: 0.756966]
8/8 [==============================] - 0s 4ms/step
8887 [D loss: 0.677345, acc.: 58.98%] [G loss: 0.745737]
8/8 [==============================] - 0s 4ms/step
8888 [D loss: 0.685202, acc.: 56.64%] [G loss: 0.755044]
8/8 [==============================] - 0s 4ms/step
8889 [D loss: 0.669175, acc.: 59.77%] [G loss: 0.729774]
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8890 [D loss: 0.675427, acc.: 56.25%] [G loss: 0.752784]
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8891 [D loss: 0.675124, acc.: 54.49%] [G loss: 0.759990]
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8892 [D loss: 0.681232, acc.: 57.23%] [G loss: 0.747159]
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8893 [D loss: 0.669991, acc.: 57.81%] [G loss: 0.748998]
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8894 [D loss: 0.677951, acc.: 58.01%] [G loss: 0.745379]
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8895 [D loss: 0.676726, acc.: 58.40%] [G loss: 0.727909]
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8896 [D loss: 0.674847, acc.: 56.45%] [G loss: 0.738438]
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8897 [D loss: 0.673681, acc.: 58.59%] [G loss: 0.753255]
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8898 [D loss: 0.675975, acc.: 56.64%] [G loss: 0.738433]
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8899 [D loss: 0.679574, acc.: 58.20%] [G loss: 0.754393]
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8900 [D loss: 0.675960, acc.: 55.86%] [G loss: 0.753616]
1/1 [==============================] - 0s 18ms/step
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8901 [D loss: 0.673174, acc.: 55.86%] [G loss: 0.752862]
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8902 [D loss: 0.685954, acc.: 54.30%] [G loss: 0.747179]
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8903 [D loss: 0.693763, acc.: 51.17%] [G loss: 0.772606]
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8904 [D loss: 0.680755, acc.: 57.42%] [G loss: 0.767959]
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8905 [D loss: 0.681381, acc.: 55.86%] [G loss: 0.760680]
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8906 [D loss: 0.685806, acc.: 56.84%] [G loss: 0.793476]
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8907 [D loss: 0.685155, acc.: 54.69%] [G loss: 0.767178]
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8908 [D loss: 0.688647, acc.: 53.91%] [G loss: 0.763126]
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8909 [D loss: 0.673045, acc.: 57.81%] [G loss: 0.744221]
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8910 [D loss: 0.678532, acc.: 56.05%] [G loss: 0.745532]
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8911 [D loss: 0.664981, acc.: 62.50%] [G loss: 0.762436]
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8912 [D loss: 0.678633, acc.: 56.64%] [G loss: 0.737760]
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8913 [D loss: 0.682429, acc.: 55.27%] [G loss: 0.736148]
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8914 [D loss: 0.682561, acc.: 58.20%] [G loss: 0.768492]
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8915 [D loss: 0.669506, acc.: 59.18%] [G loss: 0.759513]
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8916 [D loss: 0.674136, acc.: 57.03%] [G loss: 0.759911]
8/8 [==============================] - 0s 4ms/step
8917 [D loss: 0.669490, acc.: 57.42%] [G loss: 0.764539]
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8918 [D loss: 0.670196, acc.: 59.38%] [G loss: 0.759804]
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8919 [D loss: 0.673770, acc.: 55.47%] [G loss: 0.751050]
8/8 [==============================] - 0s 4ms/step
8920 [D loss: 0.695383, acc.: 52.73%] [G loss: 0.749830]
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8921 [D loss: 0.684164, acc.: 53.52%] [G loss: 0.776465]
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8922 [D loss: 0.668850, acc.: 58.59%] [G loss: 0.769763]
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8923 [D loss: 0.669751, acc.: 59.38%] [G loss: 0.777012]
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8924 [D loss: 0.672093, acc.: 58.59%] [G loss: 0.747472]
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8925 [D loss: 0.670090, acc.: 58.40%] [G loss: 0.741499]
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8926 [D loss: 0.673060, acc.: 58.59%] [G loss: 0.765908]
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8927 [D loss: 0.673911, acc.: 56.25%] [G loss: 0.754246]
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8928 [D loss: 0.687184, acc.: 52.73%] [G loss: 0.755391]
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8929 [D loss: 0.668171, acc.: 58.40%] [G loss: 0.781909]
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8930 [D loss: 0.669924, acc.: 59.38%] [G loss: 0.766733]
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8931 [D loss: 0.668671, acc.: 58.98%] [G loss: 0.758432]
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8932 [D loss: 0.670485, acc.: 58.40%] [G loss: 0.760041]
8/8 [==============================] - 0s 4ms/step
8933 [D loss: 0.674964, acc.: 56.25%] [G loss: 0.735249]
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8934 [D loss: 0.676778, acc.: 56.05%] [G loss: 0.749148]
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8935 [D loss: 0.686937, acc.: 56.84%] [G loss: 0.740290]
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8936 [D loss: 0.680163, acc.: 56.25%] [G loss: 0.750873]
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8937 [D loss: 0.681723, acc.: 56.84%] [G loss: 0.744899]
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8938 [D loss: 0.684086, acc.: 54.30%] [G loss: 0.776105]
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8939 [D loss: 0.671288, acc.: 58.20%] [G loss: 0.775579]
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8940 [D loss: 0.658900, acc.: 62.50%] [G loss: 0.770670]
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8941 [D loss: 0.659454, acc.: 59.57%] [G loss: 0.755332]
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8942 [D loss: 0.678016, acc.: 55.47%] [G loss: 0.754440]
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8943 [D loss: 0.688904, acc.: 54.49%] [G loss: 0.754375]
8/8 [==============================] - 0s 4ms/step
8944 [D loss: 0.686438, acc.: 55.47%] [G loss: 0.745005]
8/8 [==============================] - 0s 4ms/step
8945 [D loss: 0.667104, acc.: 57.03%] [G loss: 0.745801]
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8946 [D loss: 0.692882, acc.: 55.27%] [G loss: 0.737902]
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8947 [D loss: 0.668255, acc.: 59.38%] [G loss: 0.754474]
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8948 [D loss: 0.664263, acc.: 60.55%] [G loss: 0.775427]
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8949 [D loss: 0.679606, acc.: 55.66%] [G loss: 0.756458]
8/8 [==============================] - 0s 4ms/step
8950 [D loss: 0.659972, acc.: 63.28%] [G loss: 0.756191]
1/1 [==============================] - 0s 21ms/step
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8951 [D loss: 0.683516, acc.: 54.49%] [G loss: 0.741696]
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8952 [D loss: 0.687111, acc.: 53.12%] [G loss: 0.752514]
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8953 [D loss: 0.674938, acc.: 58.98%] [G loss: 0.753320]
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8954 [D loss: 0.670157, acc.: 58.01%] [G loss: 0.763991]
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8955 [D loss: 0.671110, acc.: 60.35%] [G loss: 0.756570]
8/8 [==============================] - 0s 4ms/step
8956 [D loss: 0.661351, acc.: 62.30%] [G loss: 0.748797]
8/8 [==============================] - 0s 4ms/step
8957 [D loss: 0.674930, acc.: 58.01%] [G loss: 0.764483]
8/8 [==============================] - 0s 4ms/step
8958 [D loss: 0.679945, acc.: 55.66%] [G loss: 0.746936]
8/8 [==============================] - 0s 4ms/step
8959 [D loss: 0.666253, acc.: 58.79%] [G loss: 0.758162]
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8960 [D loss: 0.676678, acc.: 58.01%] [G loss: 0.741033]
8/8 [==============================] - 0s 4ms/step
8961 [D loss: 0.669657, acc.: 56.25%] [G loss: 0.761936]
8/8 [==============================] - 0s 4ms/step
8962 [D loss: 0.668923, acc.: 58.01%] [G loss: 0.736389]
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8963 [D loss: 0.691900, acc.: 55.66%] [G loss: 0.748040]
8/8 [==============================] - 0s 4ms/step
8964 [D loss: 0.677734, acc.: 55.86%] [G loss: 0.752345]
8/8 [==============================] - 0s 4ms/step
8965 [D loss: 0.684935, acc.: 57.03%] [G loss: 0.740194]
8/8 [==============================] - 0s 4ms/step
8966 [D loss: 0.690022, acc.: 52.34%] [G loss: 0.749045]
8/8 [==============================] - 0s 4ms/step
8967 [D loss: 0.667284, acc.: 61.52%] [G loss: 0.745333]
8/8 [==============================] - 0s 4ms/step
8968 [D loss: 0.690856, acc.: 55.08%] [G loss: 0.746965]
8/8 [==============================] - 0s 4ms/step
8969 [D loss: 0.678396, acc.: 55.08%] [G loss: 0.752669]
8/8 [==============================] - 0s 4ms/step
8970 [D loss: 0.679951, acc.: 56.84%] [G loss: 0.756930]
8/8 [==============================] - 0s 4ms/step
8971 [D loss: 0.670294, acc.: 59.18%] [G loss: 0.749312]
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8972 [D loss: 0.681875, acc.: 54.88%] [G loss: 0.753492]
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8973 [D loss: 0.665822, acc.: 57.23%] [G loss: 0.750937]
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8974 [D loss: 0.684509, acc.: 51.76%] [G loss: 0.764173]
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8975 [D loss: 0.676021, acc.: 58.20%] [G loss: 0.760103]
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8976 [D loss: 0.674853, acc.: 56.84%] [G loss: 0.746859]
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8977 [D loss: 0.696245, acc.: 51.76%] [G loss: 0.743058]
8/8 [==============================] - 0s 4ms/step
8978 [D loss: 0.677684, acc.: 56.84%] [G loss: 0.746217]
8/8 [==============================] - 0s 4ms/step
8979 [D loss: 0.681331, acc.: 59.57%] [G loss: 0.762464]
8/8 [==============================] - 0s 4ms/step
8980 [D loss: 0.681697, acc.: 55.08%] [G loss: 0.751923]
8/8 [==============================] - 0s 4ms/step
8981 [D loss: 0.679310, acc.: 57.62%] [G loss: 0.756847]
8/8 [==============================] - 0s 4ms/step
8982 [D loss: 0.676283, acc.: 57.42%] [G loss: 0.758924]
8/8 [==============================] - 0s 4ms/step
8983 [D loss: 0.676715, acc.: 53.32%] [G loss: 0.750562]
8/8 [==============================] - 0s 4ms/step
8984 [D loss: 0.692639, acc.: 51.56%] [G loss: 0.754969]
8/8 [==============================] - 0s 4ms/step
8985 [D loss: 0.677854, acc.: 56.25%] [G loss: 0.745091]
8/8 [==============================] - 0s 4ms/step
8986 [D loss: 0.680688, acc.: 59.18%] [G loss: 0.747781]
8/8 [==============================] - 0s 4ms/step
8987 [D loss: 0.674969, acc.: 60.55%] [G loss: 0.753477]
8/8 [==============================] - 0s 4ms/step
8988 [D loss: 0.673231, acc.: 55.08%] [G loss: 0.743330]
8/8 [==============================] - 0s 4ms/step
8989 [D loss: 0.667493, acc.: 58.40%] [G loss: 0.742832]
8/8 [==============================] - 0s 4ms/step
8990 [D loss: 0.670508, acc.: 56.05%] [G loss: 0.733611]
8/8 [==============================] - 0s 4ms/step
8991 [D loss: 0.659117, acc.: 62.11%] [G loss: 0.747695]
8/8 [==============================] - 0s 4ms/step
8992 [D loss: 0.675122, acc.: 58.40%] [G loss: 0.748468]
8/8 [==============================] - 0s 4ms/step
8993 [D loss: 0.688431, acc.: 55.66%] [G loss: 0.755024]
8/8 [==============================] - 0s 4ms/step
8994 [D loss: 0.682973, acc.: 54.69%] [G loss: 0.745017]
8/8 [==============================] - 0s 4ms/step
8995 [D loss: 0.673215, acc.: 59.77%] [G loss: 0.761794]
8/8 [==============================] - 0s 4ms/step
8996 [D loss: 0.680297, acc.: 57.23%] [G loss: 0.768244]
8/8 [==============================] - 0s 4ms/step
8997 [D loss: 0.669885, acc.: 58.20%] [G loss: 0.771925]
8/8 [==============================] - 0s 4ms/step
8998 [D loss: 0.681178, acc.: 56.25%] [G loss: 0.766731]
8/8 [==============================] - 0s 4ms/step
8999 [D loss: 0.676695, acc.: 56.84%] [G loss: 0.746444]
8/8 [==============================] - 0s 4ms/step
9000 [D loss: 0.681502, acc.: 56.45%] [G loss: 0.756088]
1/1 [==============================] - 0s 19ms/step
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9001 [D loss: 0.681136, acc.: 55.66%] [G loss: 0.757400]
8/8 [==============================] - 0s 4ms/step
9002 [D loss: 0.667759, acc.: 60.35%] [G loss: 0.753601]
8/8 [==============================] - 0s 4ms/step
9003 [D loss: 0.683731, acc.: 56.84%] [G loss: 0.774643]
8/8 [==============================] - 0s 4ms/step
9004 [D loss: 0.674377, acc.: 58.01%] [G loss: 0.756371]
8/8 [==============================] - 0s 4ms/step
9005 [D loss: 0.678177, acc.: 58.20%] [G loss: 0.768000]
8/8 [==============================] - 0s 4ms/step
9006 [D loss: 0.678335, acc.: 56.05%] [G loss: 0.758918]
8/8 [==============================] - 0s 4ms/step
9007 [D loss: 0.675966, acc.: 55.66%] [G loss: 0.748399]
8/8 [==============================] - 0s 4ms/step
9008 [D loss: 0.660150, acc.: 62.30%] [G loss: 0.748162]
8/8 [==============================] - 0s 4ms/step
9009 [D loss: 0.679964, acc.: 53.12%] [G loss: 0.741379]
8/8 [==============================] - 0s 4ms/step
9010 [D loss: 0.682633, acc.: 57.03%] [G loss: 0.747805]
8/8 [==============================] - 0s 4ms/step
9011 [D loss: 0.685353, acc.: 57.03%] [G loss: 0.763250]
8/8 [==============================] - 0s 4ms/step
9012 [D loss: 0.687237, acc.: 55.27%] [G loss: 0.745906]
8/8 [==============================] - 0s 4ms/step
9013 [D loss: 0.669163, acc.: 57.62%] [G loss: 0.764591]
8/8 [==============================] - 0s 4ms/step
9014 [D loss: 0.677615, acc.: 56.45%] [G loss: 0.756563]
8/8 [==============================] - 0s 4ms/step
9015 [D loss: 0.677720, acc.: 55.27%] [G loss: 0.740332]
8/8 [==============================] - 0s 4ms/step
9016 [D loss: 0.678348, acc.: 58.40%] [G loss: 0.757218]
8/8 [==============================] - 0s 4ms/step
9017 [D loss: 0.678902, acc.: 58.79%] [G loss: 0.770150]
8/8 [==============================] - 0s 4ms/step
9018 [D loss: 0.682284, acc.: 56.64%] [G loss: 0.744158]
8/8 [==============================] - 0s 4ms/step
9019 [D loss: 0.681809, acc.: 55.47%] [G loss: 0.746670]
8/8 [==============================] - 0s 4ms/step
9020 [D loss: 0.674033, acc.: 57.62%] [G loss: 0.776032]
8/8 [==============================] - 0s 4ms/step
9021 [D loss: 0.675107, acc.: 57.62%] [G loss: 0.757740]
8/8 [==============================] - 0s 4ms/step
9022 [D loss: 0.675551, acc.: 58.79%] [G loss: 0.742112]
8/8 [==============================] - 0s 4ms/step
9023 [D loss: 0.684476, acc.: 54.69%] [G loss: 0.751758]
8/8 [==============================] - 0s 4ms/step
9024 [D loss: 0.686539, acc.: 56.25%] [G loss: 0.747097]
8/8 [==============================] - 0s 4ms/step
9025 [D loss: 0.670822, acc.: 59.57%] [G loss: 0.767171]
8/8 [==============================] - 0s 4ms/step
9026 [D loss: 0.668409, acc.: 60.16%] [G loss: 0.774119]
8/8 [==============================] - 0s 4ms/step
9027 [D loss: 0.677504, acc.: 57.62%] [G loss: 0.772688]
8/8 [==============================] - 0s 4ms/step
9028 [D loss: 0.670952, acc.: 57.62%] [G loss: 0.751759]
8/8 [==============================] - 0s 4ms/step
9029 [D loss: 0.679237, acc.: 55.86%] [G loss: 0.741607]
8/8 [==============================] - 0s 4ms/step
9030 [D loss: 0.681205, acc.: 55.86%] [G loss: 0.756278]
8/8 [==============================] - 0s 4ms/step
9031 [D loss: 0.680246, acc.: 55.27%] [G loss: 0.755619]
8/8 [==============================] - 0s 4ms/step
9032 [D loss: 0.681222, acc.: 53.71%] [G loss: 0.755674]
8/8 [==============================] - 0s 4ms/step
9033 [D loss: 0.671688, acc.: 57.23%] [G loss: 0.763710]
8/8 [==============================] - 0s 4ms/step
9034 [D loss: 0.672430, acc.: 58.40%] [G loss: 0.774327]
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9035 [D loss: 0.666574, acc.: 57.81%] [G loss: 0.759323]
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9036 [D loss: 0.679579, acc.: 55.47%] [G loss: 0.758977]
8/8 [==============================] - 0s 4ms/step
9037 [D loss: 0.670188, acc.: 60.55%] [G loss: 0.744315]
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9038 [D loss: 0.677552, acc.: 58.01%] [G loss: 0.738392]
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9039 [D loss: 0.693176, acc.: 53.91%] [G loss: 0.733126]
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9040 [D loss: 0.683372, acc.: 56.64%] [G loss: 0.738013]
8/8 [==============================] - 0s 4ms/step
9041 [D loss: 0.676184, acc.: 55.86%] [G loss: 0.757702]
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9042 [D loss: 0.685968, acc.: 55.08%] [G loss: 0.774426]
8/8 [==============================] - 0s 4ms/step
9043 [D loss: 0.674215, acc.: 56.45%] [G loss: 0.777452]
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9044 [D loss: 0.658098, acc.: 63.28%] [G loss: 0.786815]
8/8 [==============================] - 0s 4ms/step
9045 [D loss: 0.677535, acc.: 57.03%] [G loss: 0.779284]
8/8 [==============================] - 0s 4ms/step
9046 [D loss: 0.680335, acc.: 58.20%] [G loss: 0.771858]
8/8 [==============================] - 0s 4ms/step
9047 [D loss: 0.667062, acc.: 57.42%] [G loss: 0.750521]
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9048 [D loss: 0.669691, acc.: 60.35%] [G loss: 0.737159]
8/8 [==============================] - 0s 4ms/step
9049 [D loss: 0.686284, acc.: 55.27%] [G loss: 0.766956]
8/8 [==============================] - 0s 4ms/step
9050 [D loss: 0.679879, acc.: 54.69%] [G loss: 0.763016]
1/1 [==============================] - 0s 17ms/step
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9051 [D loss: 0.674102, acc.: 57.62%] [G loss: 0.764573]
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9052 [D loss: 0.671149, acc.: 57.62%] [G loss: 0.770824]
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9053 [D loss: 0.676760, acc.: 59.57%] [G loss: 0.786212]
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9054 [D loss: 0.676795, acc.: 57.23%] [G loss: 0.750842]
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9055 [D loss: 0.667097, acc.: 62.11%] [G loss: 0.742679]
8/8 [==============================] - 0s 4ms/step
9056 [D loss: 0.682713, acc.: 54.30%] [G loss: 0.733423]
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9057 [D loss: 0.677692, acc.: 56.05%] [G loss: 0.729808]
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9058 [D loss: 0.692916, acc.: 51.56%] [G loss: 0.729109]
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9059 [D loss: 0.669394, acc.: 61.13%] [G loss: 0.757434]
8/8 [==============================] - 0s 4ms/step
9060 [D loss: 0.673434, acc.: 56.45%] [G loss: 0.759026]
8/8 [==============================] - 0s 4ms/step
9061 [D loss: 0.665900, acc.: 61.72%] [G loss: 0.789430]
8/8 [==============================] - 0s 4ms/step
9062 [D loss: 0.680529, acc.: 57.03%] [G loss: 0.791580]
8/8 [==============================] - 0s 4ms/step
9063 [D loss: 0.673300, acc.: 58.59%] [G loss: 0.773174]
8/8 [==============================] - 0s 4ms/step
9064 [D loss: 0.661686, acc.: 59.96%] [G loss: 0.739294]
8/8 [==============================] - 0s 4ms/step
9065 [D loss: 0.676861, acc.: 55.66%] [G loss: 0.746468]
8/8 [==============================] - 0s 4ms/step
9066 [D loss: 0.670775, acc.: 59.57%] [G loss: 0.744786]
8/8 [==============================] - 0s 4ms/step
9067 [D loss: 0.680889, acc.: 54.88%] [G loss: 0.758989]
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9068 [D loss: 0.662066, acc.: 61.13%] [G loss: 0.758786]
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9069 [D loss: 0.669714, acc.: 56.84%] [G loss: 0.746318]
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9070 [D loss: 0.683084, acc.: 55.47%] [G loss: 0.764866]
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9071 [D loss: 0.664053, acc.: 57.62%] [G loss: 0.751645]
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9072 [D loss: 0.680904, acc.: 57.81%] [G loss: 0.758105]
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9073 [D loss: 0.676629, acc.: 57.23%] [G loss: 0.757431]
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9074 [D loss: 0.674807, acc.: 58.20%] [G loss: 0.744198]
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9075 [D loss: 0.682776, acc.: 55.08%] [G loss: 0.742600]
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9076 [D loss: 0.679056, acc.: 56.05%] [G loss: 0.748585]
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9077 [D loss: 0.664022, acc.: 59.57%] [G loss: 0.740699]
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9078 [D loss: 0.674692, acc.: 58.79%] [G loss: 0.766270]
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9079 [D loss: 0.680123, acc.: 56.05%] [G loss: 0.748858]
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9080 [D loss: 0.688607, acc.: 53.52%] [G loss: 0.760679]
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9081 [D loss: 0.678666, acc.: 58.01%] [G loss: 0.740044]
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9082 [D loss: 0.676343, acc.: 58.98%] [G loss: 0.729694]
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9083 [D loss: 0.682033, acc.: 56.25%] [G loss: 0.758894]
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9084 [D loss: 0.677771, acc.: 54.49%] [G loss: 0.739567]
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9085 [D loss: 0.675853, acc.: 59.77%] [G loss: 0.740771]
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9086 [D loss: 0.678563, acc.: 55.27%] [G loss: 0.740625]
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9087 [D loss: 0.670783, acc.: 59.57%] [G loss: 0.760701]
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9088 [D loss: 0.670876, acc.: 56.84%] [G loss: 0.742503]
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9089 [D loss: 0.668385, acc.: 58.98%] [G loss: 0.772866]
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9090 [D loss: 0.683524, acc.: 54.69%] [G loss: 0.754539]
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9091 [D loss: 0.669154, acc.: 58.59%] [G loss: 0.758391]
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9092 [D loss: 0.673494, acc.: 57.42%] [G loss: 0.756992]
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9093 [D loss: 0.683215, acc.: 53.52%] [G loss: 0.744958]
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9094 [D loss: 0.659479, acc.: 61.72%] [G loss: 0.754991]
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9095 [D loss: 0.669187, acc.: 59.96%] [G loss: 0.751230]
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9096 [D loss: 0.675231, acc.: 57.81%] [G loss: 0.734323]
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9097 [D loss: 0.680749, acc.: 52.93%] [G loss: 0.765520]
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9098 [D loss: 0.681502, acc.: 55.86%] [G loss: 0.774426]
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9099 [D loss: 0.675501, acc.: 57.62%] [G loss: 0.750770]
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9100 [D loss: 0.677426, acc.: 57.03%] [G loss: 0.746261]
1/1 [==============================] - 0s 19ms/step
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9101 [D loss: 0.679044, acc.: 59.38%] [G loss: 0.768160]
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9102 [D loss: 0.686902, acc.: 55.08%] [G loss: 0.767231]
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9103 [D loss: 0.677165, acc.: 58.20%] [G loss: 0.762044]
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9104 [D loss: 0.674183, acc.: 58.20%] [G loss: 0.752826]
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9105 [D loss: 0.681548, acc.: 56.64%] [G loss: 0.761800]
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9106 [D loss: 0.672309, acc.: 56.45%] [G loss: 0.757650]
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9107 [D loss: 0.675178, acc.: 58.40%] [G loss: 0.755380]
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9108 [D loss: 0.671984, acc.: 58.40%] [G loss: 0.737410]
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9109 [D loss: 0.675608, acc.: 57.42%] [G loss: 0.747136]
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9110 [D loss: 0.665402, acc.: 59.77%] [G loss: 0.740352]
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9111 [D loss: 0.678011, acc.: 56.45%] [G loss: 0.728815]
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9112 [D loss: 0.677050, acc.: 56.45%] [G loss: 0.751128]
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9113 [D loss: 0.675454, acc.: 56.84%] [G loss: 0.744165]
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9114 [D loss: 0.676942, acc.: 55.66%] [G loss: 0.762196]
8/8 [==============================] - 0s 4ms/step
9115 [D loss: 0.681814, acc.: 54.30%] [G loss: 0.756333]
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9116 [D loss: 0.680912, acc.: 55.27%] [G loss: 0.743800]
8/8 [==============================] - 0s 4ms/step
9117 [D loss: 0.672544, acc.: 58.01%] [G loss: 0.742651]
8/8 [==============================] - 0s 4ms/step
9118 [D loss: 0.664755, acc.: 60.16%] [G loss: 0.758681]
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9119 [D loss: 0.666538, acc.: 60.16%] [G loss: 0.765696]
8/8 [==============================] - 0s 4ms/step
9120 [D loss: 0.672835, acc.: 55.27%] [G loss: 0.737274]
8/8 [==============================] - 0s 4ms/step
9121 [D loss: 0.683185, acc.: 57.81%] [G loss: 0.757934]
8/8 [==============================] - 0s 4ms/step
9122 [D loss: 0.685077, acc.: 53.52%] [G loss: 0.751867]
8/8 [==============================] - 0s 4ms/step
9123 [D loss: 0.678586, acc.: 58.40%] [G loss: 0.750827]
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9124 [D loss: 0.677846, acc.: 57.03%] [G loss: 0.769839]
8/8 [==============================] - 0s 4ms/step
9125 [D loss: 0.683448, acc.: 54.49%] [G loss: 0.772969]
8/8 [==============================] - 0s 4ms/step
9126 [D loss: 0.673998, acc.: 57.81%] [G loss: 0.763216]
8/8 [==============================] - 0s 4ms/step
9127 [D loss: 0.675861, acc.: 57.03%] [G loss: 0.769776]
8/8 [==============================] - 0s 4ms/step
9128 [D loss: 0.669242, acc.: 61.52%] [G loss: 0.747257]
8/8 [==============================] - 0s 4ms/step
9129 [D loss: 0.688474, acc.: 53.32%] [G loss: 0.723777]
8/8 [==============================] - 0s 4ms/step
9130 [D loss: 0.675889, acc.: 57.81%] [G loss: 0.758735]
8/8 [==============================] - 0s 4ms/step
9131 [D loss: 0.686744, acc.: 53.71%] [G loss: 0.762122]
8/8 [==============================] - 0s 4ms/step
9132 [D loss: 0.666754, acc.: 60.16%] [G loss: 0.759573]
8/8 [==============================] - 0s 4ms/step
9133 [D loss: 0.673085, acc.: 56.25%] [G loss: 0.739215]
8/8 [==============================] - 0s 4ms/step
9134 [D loss: 0.676278, acc.: 55.86%] [G loss: 0.755305]
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9135 [D loss: 0.679522, acc.: 53.91%] [G loss: 0.770054]
8/8 [==============================] - 0s 4ms/step
9136 [D loss: 0.684281, acc.: 56.05%] [G loss: 0.753448]
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9137 [D loss: 0.685849, acc.: 52.93%] [G loss: 0.759542]
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9138 [D loss: 0.687709, acc.: 54.10%] [G loss: 0.769623]
8/8 [==============================] - 0s 4ms/step
9139 [D loss: 0.670658, acc.: 59.18%] [G loss: 0.753588]
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9140 [D loss: 0.665070, acc.: 57.42%] [G loss: 0.744739]
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9141 [D loss: 0.687014, acc.: 55.27%] [G loss: 0.750061]
8/8 [==============================] - 0s 4ms/step
9142 [D loss: 0.668859, acc.: 61.91%] [G loss: 0.746485]
8/8 [==============================] - 0s 4ms/step
9143 [D loss: 0.669590, acc.: 57.62%] [G loss: 0.762690]
8/8 [==============================] - 0s 4ms/step
9144 [D loss: 0.682941, acc.: 52.93%] [G loss: 0.749584]
8/8 [==============================] - 0s 4ms/step
9145 [D loss: 0.670828, acc.: 60.35%] [G loss: 0.751721]
8/8 [==============================] - 0s 4ms/step
9146 [D loss: 0.680434, acc.: 55.27%] [G loss: 0.746516]
8/8 [==============================] - 0s 4ms/step
9147 [D loss: 0.662299, acc.: 61.13%] [G loss: 0.760060]
8/8 [==============================] - 0s 4ms/step
9148 [D loss: 0.676833, acc.: 57.23%] [G loss: 0.756744]
8/8 [==============================] - 0s 4ms/step
9149 [D loss: 0.680732, acc.: 55.47%] [G loss: 0.747949]
8/8 [==============================] - 0s 4ms/step
9150 [D loss: 0.678091, acc.: 56.25%] [G loss: 0.738484]
1/1 [==============================] - 0s 22ms/step
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9151 [D loss: 0.669507, acc.: 57.23%] [G loss: 0.760001]
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9152 [D loss: 0.682073, acc.: 54.69%] [G loss: 0.759791]
8/8 [==============================] - 0s 4ms/step
9153 [D loss: 0.683413, acc.: 56.64%] [G loss: 0.770337]
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9154 [D loss: 0.682269, acc.: 59.57%] [G loss: 0.776942]
8/8 [==============================] - 0s 4ms/step
9155 [D loss: 0.677355, acc.: 57.03%] [G loss: 0.752151]
8/8 [==============================] - 0s 4ms/step
9156 [D loss: 0.683668, acc.: 54.69%] [G loss: 0.760962]
8/8 [==============================] - 0s 4ms/step
9157 [D loss: 0.675144, acc.: 58.98%] [G loss: 0.754164]
8/8 [==============================] - 0s 4ms/step
9158 [D loss: 0.668610, acc.: 60.74%] [G loss: 0.745840]
8/8 [==============================] - 0s 4ms/step
9159 [D loss: 0.682600, acc.: 53.91%] [G loss: 0.762422]
8/8 [==============================] - 0s 4ms/step
9160 [D loss: 0.670888, acc.: 58.98%] [G loss: 0.752794]
8/8 [==============================] - 0s 4ms/step
9161 [D loss: 0.682984, acc.: 55.47%] [G loss: 0.769644]
8/8 [==============================] - 0s 4ms/step
9162 [D loss: 0.673254, acc.: 58.79%] [G loss: 0.778756]
8/8 [==============================] - 0s 4ms/step
9163 [D loss: 0.674787, acc.: 55.86%] [G loss: 0.755369]
8/8 [==============================] - 0s 4ms/step
9164 [D loss: 0.674309, acc.: 58.59%] [G loss: 0.777747]
8/8 [==============================] - 0s 4ms/step
9165 [D loss: 0.665781, acc.: 59.38%] [G loss: 0.772342]
8/8 [==============================] - 0s 4ms/step
9166 [D loss: 0.687110, acc.: 54.30%] [G loss: 0.764555]
8/8 [==============================] - 0s 4ms/step
9167 [D loss: 0.670126, acc.: 57.81%] [G loss: 0.742553]
8/8 [==============================] - 0s 4ms/step
9168 [D loss: 0.679427, acc.: 53.71%] [G loss: 0.741933]
8/8 [==============================] - 0s 4ms/step
9169 [D loss: 0.677941, acc.: 57.42%] [G loss: 0.755127]
8/8 [==============================] - 0s 4ms/step
9170 [D loss: 0.680285, acc.: 57.42%] [G loss: 0.763011]
8/8 [==============================] - 0s 4ms/step
9171 [D loss: 0.684185, acc.: 57.03%] [G loss: 0.730850]
8/8 [==============================] - 0s 4ms/step
9172 [D loss: 0.681867, acc.: 54.88%] [G loss: 0.750956]
8/8 [==============================] - 0s 4ms/step
9173 [D loss: 0.684201, acc.: 53.91%] [G loss: 0.758656]
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9174 [D loss: 0.676246, acc.: 56.25%] [G loss: 0.749769]
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9175 [D loss: 0.678878, acc.: 57.03%] [G loss: 0.763341]
8/8 [==============================] - 0s 4ms/step
9176 [D loss: 0.668700, acc.: 60.55%] [G loss: 0.744533]
8/8 [==============================] - 0s 4ms/step
9177 [D loss: 0.673014, acc.: 59.77%] [G loss: 0.755559]
8/8 [==============================] - 0s 4ms/step
9178 [D loss: 0.673704, acc.: 59.18%] [G loss: 0.757462]
8/8 [==============================] - 0s 4ms/step
9179 [D loss: 0.679084, acc.: 57.42%] [G loss: 0.760571]
8/8 [==============================] - 0s 4ms/step
9180 [D loss: 0.687705, acc.: 52.34%] [G loss: 0.759301]
8/8 [==============================] - 0s 4ms/step
9181 [D loss: 0.675521, acc.: 58.40%] [G loss: 0.759087]
8/8 [==============================] - 0s 4ms/step
9182 [D loss: 0.671550, acc.: 57.42%] [G loss: 0.752237]
8/8 [==============================] - 0s 4ms/step
9183 [D loss: 0.680082, acc.: 56.45%] [G loss: 0.766198]
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9184 [D loss: 0.674762, acc.: 56.25%] [G loss: 0.759933]
8/8 [==============================] - 0s 4ms/step
9185 [D loss: 0.666631, acc.: 58.40%] [G loss: 0.771303]
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9186 [D loss: 0.675617, acc.: 58.98%] [G loss: 0.791839]
8/8 [==============================] - 0s 4ms/step
9187 [D loss: 0.673606, acc.: 58.20%] [G loss: 0.741423]
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9188 [D loss: 0.669749, acc.: 59.18%] [G loss: 0.742812]
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9189 [D loss: 0.672411, acc.: 59.18%] [G loss: 0.756206]
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9190 [D loss: 0.671642, acc.: 57.62%] [G loss: 0.759725]
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9191 [D loss: 0.663460, acc.: 61.13%] [G loss: 0.746191]
8/8 [==============================] - 0s 4ms/step
9192 [D loss: 0.681730, acc.: 51.76%] [G loss: 0.743544]
8/8 [==============================] - 0s 4ms/step
9193 [D loss: 0.683936, acc.: 54.30%] [G loss: 0.772707]
8/8 [==============================] - 0s 4ms/step
9194 [D loss: 0.681584, acc.: 54.49%] [G loss: 0.776952]
8/8 [==============================] - 0s 4ms/step
9195 [D loss: 0.685461, acc.: 56.05%] [G loss: 0.764243]
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9196 [D loss: 0.670879, acc.: 58.79%] [G loss: 0.755970]
8/8 [==============================] - 0s 4ms/step
9197 [D loss: 0.658501, acc.: 63.09%] [G loss: 0.741427]
8/8 [==============================] - 0s 4ms/step
9198 [D loss: 0.682397, acc.: 54.88%] [G loss: 0.759227]
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9199 [D loss: 0.674186, acc.: 58.79%] [G loss: 0.751011]
8/8 [==============================] - 0s 4ms/step
9200 [D loss: 0.680250, acc.: 55.27%] [G loss: 0.759078]
1/1 [==============================] - 0s 18ms/step
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9201 [D loss: 0.676029, acc.: 58.20%] [G loss: 0.774782]
8/8 [==============================] - 0s 4ms/step
9202 [D loss: 0.679917, acc.: 58.01%] [G loss: 0.774292]
8/8 [==============================] - 0s 4ms/step
9203 [D loss: 0.669859, acc.: 57.62%] [G loss: 0.748833]
8/8 [==============================] - 0s 4ms/step
9204 [D loss: 0.684304, acc.: 53.71%] [G loss: 0.765962]
8/8 [==============================] - 0s 4ms/step
9205 [D loss: 0.671086, acc.: 60.16%] [G loss: 0.762324]
8/8 [==============================] - 0s 4ms/step
9206 [D loss: 0.666847, acc.: 58.79%] [G loss: 0.757001]
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9207 [D loss: 0.680027, acc.: 54.69%] [G loss: 0.748754]
8/8 [==============================] - 0s 4ms/step
9208 [D loss: 0.681867, acc.: 55.47%] [G loss: 0.751052]
8/8 [==============================] - 0s 4ms/step
9209 [D loss: 0.684200, acc.: 55.47%] [G loss: 0.772915]
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9210 [D loss: 0.679170, acc.: 58.20%] [G loss: 0.762036]
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9211 [D loss: 0.668716, acc.: 59.77%] [G loss: 0.746304]
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9212 [D loss: 0.673979, acc.: 61.13%] [G loss: 0.756960]
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9213 [D loss: 0.683612, acc.: 55.08%] [G loss: 0.766316]
8/8 [==============================] - 0s 4ms/step
9214 [D loss: 0.677465, acc.: 58.40%] [G loss: 0.766826]
8/8 [==============================] - 0s 4ms/step
9215 [D loss: 0.680755, acc.: 54.49%] [G loss: 0.769317]
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9216 [D loss: 0.679103, acc.: 54.30%] [G loss: 0.765615]
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9217 [D loss: 0.677925, acc.: 55.27%] [G loss: 0.780509]
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9218 [D loss: 0.683114, acc.: 56.25%] [G loss: 0.770339]
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9219 [D loss: 0.675418, acc.: 57.03%] [G loss: 0.766054]
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9220 [D loss: 0.675301, acc.: 57.42%] [G loss: 0.769254]
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9221 [D loss: 0.677023, acc.: 54.49%] [G loss: 0.761816]
8/8 [==============================] - 0s 4ms/step
9222 [D loss: 0.682766, acc.: 52.73%] [G loss: 0.764632]
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9223 [D loss: 0.672463, acc.: 56.45%] [G loss: 0.744785]
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9224 [D loss: 0.670655, acc.: 58.98%] [G loss: 0.759891]
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9225 [D loss: 0.670770, acc.: 59.38%] [G loss: 0.769442]
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9226 [D loss: 0.688444, acc.: 55.66%] [G loss: 0.749326]
8/8 [==============================] - 0s 4ms/step
9227 [D loss: 0.680012, acc.: 57.81%] [G loss: 0.766474]
8/8 [==============================] - 0s 4ms/step
9228 [D loss: 0.673907, acc.: 57.03%] [G loss: 0.746725]
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9229 [D loss: 0.673639, acc.: 57.81%] [G loss: 0.764610]
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9230 [D loss: 0.681781, acc.: 55.66%] [G loss: 0.765218]
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9231 [D loss: 0.690325, acc.: 51.56%] [G loss: 0.760975]
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9232 [D loss: 0.680677, acc.: 55.86%] [G loss: 0.762265]
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9233 [D loss: 0.671568, acc.: 56.84%] [G loss: 0.734487]
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9234 [D loss: 0.672820, acc.: 58.98%] [G loss: 0.742827]
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9235 [D loss: 0.673111, acc.: 57.42%] [G loss: 0.750722]
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9236 [D loss: 0.685733, acc.: 55.47%] [G loss: 0.745572]
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9237 [D loss: 0.671382, acc.: 59.77%] [G loss: 0.777360]
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9238 [D loss: 0.663994, acc.: 58.59%] [G loss: 0.782721]
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9239 [D loss: 0.666958, acc.: 58.98%] [G loss: 0.768730]
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9240 [D loss: 0.682972, acc.: 53.91%] [G loss: 0.766957]
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9241 [D loss: 0.681557, acc.: 56.05%] [G loss: 0.766747]
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9242 [D loss: 0.674664, acc.: 58.01%] [G loss: 0.771499]
8/8 [==============================] - 0s 4ms/step
9243 [D loss: 0.688066, acc.: 55.27%] [G loss: 0.748952]
8/8 [==============================] - 0s 4ms/step
9244 [D loss: 0.680334, acc.: 57.62%] [G loss: 0.763807]
8/8 [==============================] - 0s 4ms/step
9245 [D loss: 0.675631, acc.: 58.40%] [G loss: 0.762390]
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9246 [D loss: 0.674430, acc.: 56.84%] [G loss: 0.756833]
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9247 [D loss: 0.675299, acc.: 58.20%] [G loss: 0.762978]
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9248 [D loss: 0.675707, acc.: 57.42%] [G loss: 0.752353]
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9249 [D loss: 0.675482, acc.: 58.40%] [G loss: 0.751110]
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9250 [D loss: 0.683125, acc.: 55.08%] [G loss: 0.753958]
1/1 [==============================] - 0s 17ms/step
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9251 [D loss: 0.677778, acc.: 59.18%] [G loss: 0.755068]
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9252 [D loss: 0.674194, acc.: 55.47%] [G loss: 0.753763]
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9253 [D loss: 0.668782, acc.: 58.40%] [G loss: 0.752039]
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9254 [D loss: 0.672461, acc.: 57.81%] [G loss: 0.755862]
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9255 [D loss: 0.672381, acc.: 56.05%] [G loss: 0.750705]
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9256 [D loss: 0.665961, acc.: 59.77%] [G loss: 0.755724]
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9257 [D loss: 0.674447, acc.: 58.40%] [G loss: 0.758296]
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9258 [D loss: 0.673612, acc.: 58.40%] [G loss: 0.744244]
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9259 [D loss: 0.678465, acc.: 57.42%] [G loss: 0.746251]
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9260 [D loss: 0.672862, acc.: 56.64%] [G loss: 0.752789]
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9261 [D loss: 0.669045, acc.: 56.25%] [G loss: 0.744882]
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9262 [D loss: 0.665347, acc.: 57.23%] [G loss: 0.759017]
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9263 [D loss: 0.675484, acc.: 56.25%] [G loss: 0.756242]
8/8 [==============================] - 0s 4ms/step
9264 [D loss: 0.690985, acc.: 52.93%] [G loss: 0.743464]
8/8 [==============================] - 0s 4ms/step
9265 [D loss: 0.666617, acc.: 61.33%] [G loss: 0.754517]
8/8 [==============================] - 0s 4ms/step
9266 [D loss: 0.674529, acc.: 57.81%] [G loss: 0.760296]
8/8 [==============================] - 0s 4ms/step
9267 [D loss: 0.681562, acc.: 55.47%] [G loss: 0.761482]
8/8 [==============================] - 0s 4ms/step
9268 [D loss: 0.680075, acc.: 54.69%] [G loss: 0.757438]
8/8 [==============================] - 0s 4ms/step
9269 [D loss: 0.671729, acc.: 59.38%] [G loss: 0.767790]
8/8 [==============================] - 0s 4ms/step
9270 [D loss: 0.672018, acc.: 59.77%] [G loss: 0.768850]
8/8 [==============================] - 0s 4ms/step
9271 [D loss: 0.680388, acc.: 56.25%] [G loss: 0.758989]
8/8 [==============================] - 0s 4ms/step
9272 [D loss: 0.670260, acc.: 57.62%] [G loss: 0.751394]
8/8 [==============================] - 0s 4ms/step
9273 [D loss: 0.682405, acc.: 54.10%] [G loss: 0.764282]
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9274 [D loss: 0.673798, acc.: 57.62%] [G loss: 0.752384]
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9275 [D loss: 0.666367, acc.: 59.38%] [G loss: 0.768772]
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9276 [D loss: 0.668645, acc.: 59.18%] [G loss: 0.745173]
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9277 [D loss: 0.666508, acc.: 58.20%] [G loss: 0.761660]
8/8 [==============================] - 0s 4ms/step
9278 [D loss: 0.667348, acc.: 60.16%] [G loss: 0.731437]
8/8 [==============================] - 0s 4ms/step
9279 [D loss: 0.672356, acc.: 58.20%] [G loss: 0.737299]
8/8 [==============================] - 0s 4ms/step
9280 [D loss: 0.674077, acc.: 57.42%] [G loss: 0.716949]
8/8 [==============================] - 0s 4ms/step
9281 [D loss: 0.684879, acc.: 53.32%] [G loss: 0.721264]
8/8 [==============================] - 0s 4ms/step
9282 [D loss: 0.677461, acc.: 55.86%] [G loss: 0.737875]
8/8 [==============================] - 0s 4ms/step
9283 [D loss: 0.670672, acc.: 58.79%] [G loss: 0.780898]
8/8 [==============================] - 0s 4ms/step
9284 [D loss: 0.689324, acc.: 53.32%] [G loss: 0.791286]
8/8 [==============================] - 0s 4ms/step
9285 [D loss: 0.662079, acc.: 61.13%] [G loss: 0.786115]
8/8 [==============================] - 0s 4ms/step
9286 [D loss: 0.652435, acc.: 62.89%] [G loss: 0.785293]
8/8 [==============================] - 0s 4ms/step
9287 [D loss: 0.665324, acc.: 58.59%] [G loss: 0.777568]
8/8 [==============================] - 0s 4ms/step
9288 [D loss: 0.665961, acc.: 59.96%] [G loss: 0.767387]
8/8 [==============================] - 0s 4ms/step
9289 [D loss: 0.673621, acc.: 56.84%] [G loss: 0.737134]
8/8 [==============================] - 0s 4ms/step
9290 [D loss: 0.685636, acc.: 54.30%] [G loss: 0.750079]
8/8 [==============================] - 0s 4ms/step
9291 [D loss: 0.664352, acc.: 59.18%] [G loss: 0.749553]
8/8 [==============================] - 0s 4ms/step
9292 [D loss: 0.673665, acc.: 56.05%] [G loss: 0.782949]
8/8 [==============================] - 0s 4ms/step
9293 [D loss: 0.674035, acc.: 59.57%] [G loss: 0.769772]
8/8 [==============================] - 0s 4ms/step
9294 [D loss: 0.669550, acc.: 58.20%] [G loss: 0.795590]
8/8 [==============================] - 0s 4ms/step
9295 [D loss: 0.668646, acc.: 60.74%] [G loss: 0.774592]
8/8 [==============================] - 0s 4ms/step
9296 [D loss: 0.675102, acc.: 58.40%] [G loss: 0.785682]
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9297 [D loss: 0.668644, acc.: 60.16%] [G loss: 0.756789]
8/8 [==============================] - 0s 4ms/step
9298 [D loss: 0.692143, acc.: 53.91%] [G loss: 0.732172]
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9299 [D loss: 0.688223, acc.: 55.08%] [G loss: 0.745032]
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9300 [D loss: 0.669538, acc.: 58.01%] [G loss: 0.775182]
1/1 [==============================] - 0s 28ms/step
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9301 [D loss: 0.678660, acc.: 56.05%] [G loss: 0.781450]
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9302 [D loss: 0.675229, acc.: 58.40%] [G loss: 0.786357]
8/8 [==============================] - 0s 4ms/step
9303 [D loss: 0.676223, acc.: 55.66%] [G loss: 0.745211]
8/8 [==============================] - 0s 4ms/step
9304 [D loss: 0.672773, acc.: 56.64%] [G loss: 0.769698]
8/8 [==============================] - 0s 4ms/step
9305 [D loss: 0.680417, acc.: 54.69%] [G loss: 0.763081]
8/8 [==============================] - 0s 4ms/step
9306 [D loss: 0.675967, acc.: 56.05%] [G loss: 0.777243]
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9307 [D loss: 0.668518, acc.: 59.38%] [G loss: 0.765506]
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9308 [D loss: 0.672874, acc.: 59.38%] [G loss: 0.775468]
8/8 [==============================] - 0s 4ms/step
9309 [D loss: 0.673183, acc.: 58.98%] [G loss: 0.763001]
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9310 [D loss: 0.674351, acc.: 58.79%] [G loss: 0.762712]
8/8 [==============================] - 0s 4ms/step
9311 [D loss: 0.666368, acc.: 58.59%] [G loss: 0.749225]
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9312 [D loss: 0.665857, acc.: 58.01%] [G loss: 0.767733]
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9313 [D loss: 0.685681, acc.: 54.10%] [G loss: 0.759639]
8/8 [==============================] - 0s 4ms/step
9314 [D loss: 0.672624, acc.: 55.27%] [G loss: 0.755648]
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9315 [D loss: 0.681586, acc.: 58.20%] [G loss: 0.761294]
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9316 [D loss: 0.675905, acc.: 57.81%] [G loss: 0.752381]
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9317 [D loss: 0.687108, acc.: 56.84%] [G loss: 0.768727]
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9318 [D loss: 0.665437, acc.: 59.96%] [G loss: 0.767138]
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9319 [D loss: 0.665700, acc.: 57.42%] [G loss: 0.757646]
8/8 [==============================] - 0s 4ms/step
9320 [D loss: 0.680230, acc.: 56.05%] [G loss: 0.773933]
8/8 [==============================] - 0s 4ms/step
9321 [D loss: 0.674893, acc.: 57.81%] [G loss: 0.770495]
8/8 [==============================] - 0s 4ms/step
9322 [D loss: 0.677306, acc.: 55.47%] [G loss: 0.747699]
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9323 [D loss: 0.677291, acc.: 56.64%] [G loss: 0.737608]
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9324 [D loss: 0.671757, acc.: 55.27%] [G loss: 0.737214]
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9325 [D loss: 0.673955, acc.: 58.20%] [G loss: 0.761096]
8/8 [==============================] - 0s 4ms/step
9326 [D loss: 0.680172, acc.: 54.49%] [G loss: 0.775423]
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9327 [D loss: 0.672697, acc.: 56.84%] [G loss: 0.756854]
8/8 [==============================] - 0s 4ms/step
9328 [D loss: 0.667878, acc.: 58.40%] [G loss: 0.784848]
8/8 [==============================] - 0s 4ms/step
9329 [D loss: 0.677715, acc.: 57.62%] [G loss: 0.781358]
8/8 [==============================] - 0s 4ms/step
9330 [D loss: 0.666082, acc.: 60.35%] [G loss: 0.792041]
8/8 [==============================] - 0s 4ms/step
9331 [D loss: 0.675802, acc.: 59.38%] [G loss: 0.744665]
8/8 [==============================] - 0s 4ms/step
9332 [D loss: 0.675825, acc.: 57.03%] [G loss: 0.736522]
8/8 [==============================] - 0s 4ms/step
9333 [D loss: 0.677572, acc.: 57.62%] [G loss: 0.749915]
8/8 [==============================] - 0s 4ms/step
9334 [D loss: 0.666079, acc.: 60.35%] [G loss: 0.744699]
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9335 [D loss: 0.667076, acc.: 61.72%] [G loss: 0.760425]
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9336 [D loss: 0.673553, acc.: 55.66%] [G loss: 0.769132]
8/8 [==============================] - 0s 4ms/step
9337 [D loss: 0.679365, acc.: 56.84%] [G loss: 0.781807]
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9338 [D loss: 0.662224, acc.: 59.57%] [G loss: 0.768362]
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9339 [D loss: 0.683778, acc.: 53.71%] [G loss: 0.754006]
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9340 [D loss: 0.679183, acc.: 55.86%] [G loss: 0.750605]
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9341 [D loss: 0.678138, acc.: 55.66%] [G loss: 0.734508]
8/8 [==============================] - 0s 4ms/step
9342 [D loss: 0.680145, acc.: 52.93%] [G loss: 0.755875]
8/8 [==============================] - 0s 4ms/step
9343 [D loss: 0.658282, acc.: 63.28%] [G loss: 0.785317]
8/8 [==============================] - 0s 4ms/step
9344 [D loss: 0.676361, acc.: 54.10%] [G loss: 0.770436]
8/8 [==============================] - 0s 4ms/step
9345 [D loss: 0.674149, acc.: 56.84%] [G loss: 0.760057]
8/8 [==============================] - 0s 4ms/step
9346 [D loss: 0.674427, acc.: 57.42%] [G loss: 0.762427]
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9347 [D loss: 0.675818, acc.: 56.05%] [G loss: 0.742180]
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9348 [D loss: 0.684600, acc.: 56.64%] [G loss: 0.751668]
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9349 [D loss: 0.678231, acc.: 55.27%] [G loss: 0.759826]
8/8 [==============================] - 0s 4ms/step
9350 [D loss: 0.680192, acc.: 56.64%] [G loss: 0.756601]
1/1 [==============================] - 0s 20ms/step
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9351 [D loss: 0.668534, acc.: 58.79%] [G loss: 0.763025]
8/8 [==============================] - 0s 4ms/step
9352 [D loss: 0.662270, acc.: 63.09%] [G loss: 0.814687]
8/8 [==============================] - 0s 4ms/step
9353 [D loss: 0.675692, acc.: 56.25%] [G loss: 0.754465]
8/8 [==============================] - 0s 4ms/step
9354 [D loss: 0.674163, acc.: 58.98%] [G loss: 0.773059]
8/8 [==============================] - 0s 4ms/step
9355 [D loss: 0.696253, acc.: 54.10%] [G loss: 0.751404]
8/8 [==============================] - 0s 4ms/step
9356 [D loss: 0.682356, acc.: 56.84%] [G loss: 0.740572]
8/8 [==============================] - 0s 4ms/step
9357 [D loss: 0.684662, acc.: 55.66%] [G loss: 0.772710]
8/8 [==============================] - 0s 4ms/step
9358 [D loss: 0.673487, acc.: 56.25%] [G loss: 0.764400]
8/8 [==============================] - 0s 4ms/step
9359 [D loss: 0.665458, acc.: 58.59%] [G loss: 0.770463]
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9360 [D loss: 0.665962, acc.: 61.13%] [G loss: 0.779661]
8/8 [==============================] - 0s 4ms/step
9361 [D loss: 0.676155, acc.: 54.30%] [G loss: 0.764148]
8/8 [==============================] - 0s 4ms/step
9362 [D loss: 0.666978, acc.: 60.94%] [G loss: 0.770476]
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9363 [D loss: 0.677530, acc.: 59.57%] [G loss: 0.753121]
8/8 [==============================] - 0s 4ms/step
9364 [D loss: 0.679402, acc.: 53.91%] [G loss: 0.739559]
8/8 [==============================] - 0s 4ms/step
9365 [D loss: 0.683758, acc.: 54.49%] [G loss: 0.735745]
8/8 [==============================] - 0s 4ms/step
9366 [D loss: 0.674732, acc.: 57.81%] [G loss: 0.757319]
8/8 [==============================] - 0s 4ms/step
9367 [D loss: 0.689066, acc.: 56.84%] [G loss: 0.760675]
8/8 [==============================] - 0s 4ms/step
9368 [D loss: 0.667741, acc.: 59.57%] [G loss: 0.758744]
8/8 [==============================] - 0s 4ms/step
9369 [D loss: 0.687239, acc.: 53.32%] [G loss: 0.754539]
8/8 [==============================] - 0s 4ms/step
9370 [D loss: 0.676168, acc.: 56.25%] [G loss: 0.760844]
8/8 [==============================] - 0s 4ms/step
9371 [D loss: 0.678337, acc.: 56.84%] [G loss: 0.760348]
8/8 [==============================] - 0s 4ms/step
9372 [D loss: 0.666417, acc.: 59.38%] [G loss: 0.785260]
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9373 [D loss: 0.681068, acc.: 58.98%] [G loss: 0.775537]
8/8 [==============================] - 0s 4ms/step
9374 [D loss: 0.676357, acc.: 55.66%] [G loss: 0.787594]
8/8 [==============================] - 0s 4ms/step
9375 [D loss: 0.675007, acc.: 57.23%] [G loss: 0.771042]
8/8 [==============================] - 0s 4ms/step
9376 [D loss: 0.683637, acc.: 56.05%] [G loss: 0.758675]
8/8 [==============================] - 0s 4ms/step
9377 [D loss: 0.678342, acc.: 58.40%] [G loss: 0.748771]
8/8 [==============================] - 0s 4ms/step
9378 [D loss: 0.673780, acc.: 56.64%] [G loss: 0.754467]
8/8 [==============================] - 0s 4ms/step
9379 [D loss: 0.685455, acc.: 56.64%] [G loss: 0.774145]
8/8 [==============================] - 0s 4ms/step
9380 [D loss: 0.680889, acc.: 53.52%] [G loss: 0.756778]
8/8 [==============================] - 0s 4ms/step
9381 [D loss: 0.677873, acc.: 58.01%] [G loss: 0.772547]
8/8 [==============================] - 0s 4ms/step
9382 [D loss: 0.679528, acc.: 54.88%] [G loss: 0.761640]
8/8 [==============================] - 0s 4ms/step
9383 [D loss: 0.673820, acc.: 58.98%] [G loss: 0.764963]
8/8 [==============================] - 0s 4ms/step
9384 [D loss: 0.679927, acc.: 56.45%] [G loss: 0.760687]
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9385 [D loss: 0.665845, acc.: 59.38%] [G loss: 0.759176]
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9386 [D loss: 0.678661, acc.: 56.05%] [G loss: 0.753819]
8/8 [==============================] - 0s 4ms/step
9387 [D loss: 0.672126, acc.: 57.42%] [G loss: 0.757643]
8/8 [==============================] - 0s 4ms/step
9388 [D loss: 0.673005, acc.: 58.20%] [G loss: 0.767787]
8/8 [==============================] - 0s 4ms/step
9389 [D loss: 0.672389, acc.: 57.23%] [G loss: 0.771571]
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9390 [D loss: 0.673803, acc.: 59.18%] [G loss: 0.763926]
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9391 [D loss: 0.681304, acc.: 56.25%] [G loss: 0.751887]
8/8 [==============================] - 0s 4ms/step
9392 [D loss: 0.668157, acc.: 57.62%] [G loss: 0.767825]
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9393 [D loss: 0.668838, acc.: 60.35%] [G loss: 0.777001]
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9394 [D loss: 0.669390, acc.: 57.81%] [G loss: 0.769864]
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9395 [D loss: 0.677899, acc.: 58.59%] [G loss: 0.780552]
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9396 [D loss: 0.678505, acc.: 57.81%] [G loss: 0.765462]
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9397 [D loss: 0.675727, acc.: 57.03%] [G loss: 0.757699]
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9398 [D loss: 0.679070, acc.: 54.69%] [G loss: 0.752615]
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9399 [D loss: 0.664563, acc.: 62.11%] [G loss: 0.756700]
8/8 [==============================] - 0s 4ms/step
9400 [D loss: 0.673805, acc.: 56.84%] [G loss: 0.754236]
1/1 [==============================] - 0s 21ms/step
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9401 [D loss: 0.690481, acc.: 51.76%] [G loss: 0.754288]
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9402 [D loss: 0.674944, acc.: 57.23%] [G loss: 0.736610]
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9403 [D loss: 0.679442, acc.: 58.79%] [G loss: 0.762015]
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9404 [D loss: 0.681194, acc.: 57.42%] [G loss: 0.765520]
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9405 [D loss: 0.669521, acc.: 57.42%] [G loss: 0.767076]
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9406 [D loss: 0.664181, acc.: 59.96%] [G loss: 0.774702]
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9407 [D loss: 0.691561, acc.: 53.91%] [G loss: 0.755620]
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9408 [D loss: 0.682604, acc.: 54.88%] [G loss: 0.744457]
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9409 [D loss: 0.673070, acc.: 58.98%] [G loss: 0.735088]
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9410 [D loss: 0.667703, acc.: 58.59%] [G loss: 0.749067]
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9411 [D loss: 0.681771, acc.: 54.30%] [G loss: 0.752171]
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9412 [D loss: 0.683208, acc.: 58.98%] [G loss: 0.752624]
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9413 [D loss: 0.674283, acc.: 57.23%] [G loss: 0.781081]
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9414 [D loss: 0.679382, acc.: 56.25%] [G loss: 0.759912]
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9415 [D loss: 0.670310, acc.: 58.98%] [G loss: 0.765870]
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9416 [D loss: 0.679341, acc.: 56.25%] [G loss: 0.748983]
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9417 [D loss: 0.691099, acc.: 52.54%] [G loss: 0.754242]
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9418 [D loss: 0.670463, acc.: 58.59%] [G loss: 0.755287]
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9419 [D loss: 0.677949, acc.: 57.42%] [G loss: 0.758793]
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9420 [D loss: 0.685973, acc.: 56.84%] [G loss: 0.754871]
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9421 [D loss: 0.674741, acc.: 58.79%] [G loss: 0.756006]
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9422 [D loss: 0.679646, acc.: 57.62%] [G loss: 0.755037]
8/8 [==============================] - 0s 4ms/step
9423 [D loss: 0.673593, acc.: 58.01%] [G loss: 0.745716]
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9424 [D loss: 0.673582, acc.: 57.81%] [G loss: 0.759533]
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9425 [D loss: 0.670022, acc.: 60.35%] [G loss: 0.762231]
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9426 [D loss: 0.680558, acc.: 57.23%] [G loss: 0.762074]
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9427 [D loss: 0.673902, acc.: 57.81%] [G loss: 0.762462]
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9428 [D loss: 0.670766, acc.: 60.35%] [G loss: 0.759566]
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9429 [D loss: 0.670229, acc.: 58.98%] [G loss: 0.768966]
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9430 [D loss: 0.663706, acc.: 60.16%] [G loss: 0.739545]
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9431 [D loss: 0.669430, acc.: 58.01%] [G loss: 0.750281]
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9432 [D loss: 0.678749, acc.: 58.01%] [G loss: 0.761582]
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9433 [D loss: 0.689056, acc.: 53.12%] [G loss: 0.751969]
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9434 [D loss: 0.670410, acc.: 58.79%] [G loss: 0.753089]
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9435 [D loss: 0.678123, acc.: 57.42%] [G loss: 0.748035]
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9436 [D loss: 0.675279, acc.: 56.84%] [G loss: 0.762504]
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9437 [D loss: 0.675462, acc.: 57.62%] [G loss: 0.770025]
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9438 [D loss: 0.678675, acc.: 54.88%] [G loss: 0.750441]
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9439 [D loss: 0.677979, acc.: 58.01%] [G loss: 0.747988]
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9440 [D loss: 0.679895, acc.: 56.84%] [G loss: 0.745071]
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9441 [D loss: 0.674331, acc.: 57.81%] [G loss: 0.769227]
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9442 [D loss: 0.684587, acc.: 57.03%] [G loss: 0.758198]
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9443 [D loss: 0.673830, acc.: 58.79%] [G loss: 0.761240]
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9444 [D loss: 0.664554, acc.: 58.79%] [G loss: 0.759839]
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9445 [D loss: 0.679216, acc.: 57.42%] [G loss: 0.748162]
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9446 [D loss: 0.685218, acc.: 55.86%] [G loss: 0.756600]
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9447 [D loss: 0.678897, acc.: 55.47%] [G loss: 0.748140]
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9448 [D loss: 0.672470, acc.: 58.01%] [G loss: 0.779324]
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9449 [D loss: 0.665098, acc.: 58.98%] [G loss: 0.758878]
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9450 [D loss: 0.683852, acc.: 56.25%] [G loss: 0.778705]
1/1 [==============================] - 0s 17ms/step
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9451 [D loss: 0.680958, acc.: 57.03%] [G loss: 0.779226]
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9452 [D loss: 0.679071, acc.: 55.66%] [G loss: 0.778613]
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9453 [D loss: 0.681373, acc.: 59.38%] [G loss: 0.768389]
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9454 [D loss: 0.686234, acc.: 54.30%] [G loss: 0.758659]
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9455 [D loss: 0.672723, acc.: 58.20%] [G loss: 0.745250]
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9456 [D loss: 0.666743, acc.: 60.35%] [G loss: 0.763111]
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9457 [D loss: 0.673906, acc.: 58.98%] [G loss: 0.745881]
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9458 [D loss: 0.670991, acc.: 57.42%] [G loss: 0.776426]
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9459 [D loss: 0.674862, acc.: 58.98%] [G loss: 0.763487]
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9460 [D loss: 0.673580, acc.: 57.42%] [G loss: 0.759784]
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9461 [D loss: 0.661196, acc.: 62.50%] [G loss: 0.764069]
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9462 [D loss: 0.661729, acc.: 61.72%] [G loss: 0.777371]
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9463 [D loss: 0.672578, acc.: 56.84%] [G loss: 0.761764]
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9464 [D loss: 0.670948, acc.: 57.81%] [G loss: 0.751483]
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9465 [D loss: 0.685580, acc.: 55.86%] [G loss: 0.770426]
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9466 [D loss: 0.681973, acc.: 54.10%] [G loss: 0.763506]
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9467 [D loss: 0.694831, acc.: 50.20%] [G loss: 0.755760]
8/8 [==============================] - 0s 4ms/step
9468 [D loss: 0.676283, acc.: 54.10%] [G loss: 0.765794]
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9469 [D loss: 0.681858, acc.: 55.47%] [G loss: 0.772714]
8/8 [==============================] - 0s 4ms/step
9470 [D loss: 0.671840, acc.: 57.03%] [G loss: 0.756203]
8/8 [==============================] - 0s 4ms/step
9471 [D loss: 0.668113, acc.: 60.16%] [G loss: 0.760158]
8/8 [==============================] - 0s 4ms/step
9472 [D loss: 0.673167, acc.: 56.05%] [G loss: 0.764001]
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9473 [D loss: 0.677592, acc.: 56.84%] [G loss: 0.742051]
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9474 [D loss: 0.685616, acc.: 56.84%] [G loss: 0.716509]
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9475 [D loss: 0.684824, acc.: 55.27%] [G loss: 0.750820]
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9476 [D loss: 0.673377, acc.: 55.47%] [G loss: 0.743869]
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9477 [D loss: 0.666219, acc.: 61.33%] [G loss: 0.746238]
8/8 [==============================] - 0s 4ms/step
9478 [D loss: 0.666641, acc.: 59.96%] [G loss: 0.771132]
8/8 [==============================] - 0s 4ms/step
9479 [D loss: 0.677137, acc.: 56.84%] [G loss: 0.743121]
8/8 [==============================] - 0s 4ms/step
9480 [D loss: 0.677649, acc.: 57.81%] [G loss: 0.762233]
8/8 [==============================] - 0s 4ms/step
9481 [D loss: 0.666668, acc.: 60.94%] [G loss: 0.768621]
8/8 [==============================] - 0s 4ms/step
9482 [D loss: 0.674704, acc.: 57.62%] [G loss: 0.754668]
8/8 [==============================] - 0s 4ms/step
9483 [D loss: 0.673499, acc.: 56.64%] [G loss: 0.745519]
8/8 [==============================] - 0s 4ms/step
9484 [D loss: 0.682883, acc.: 54.49%] [G loss: 0.746148]
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9485 [D loss: 0.676413, acc.: 58.01%] [G loss: 0.761757]
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9486 [D loss: 0.685525, acc.: 54.49%] [G loss: 0.767681]
8/8 [==============================] - 0s 4ms/step
9487 [D loss: 0.667668, acc.: 57.23%] [G loss: 0.768622]
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9488 [D loss: 0.675065, acc.: 56.05%] [G loss: 0.763753]
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9489 [D loss: 0.679743, acc.: 56.45%] [G loss: 0.764179]
8/8 [==============================] - 0s 4ms/step
9490 [D loss: 0.670715, acc.: 59.18%] [G loss: 0.744954]
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9491 [D loss: 0.665476, acc.: 61.13%] [G loss: 0.733598]
8/8 [==============================] - 0s 4ms/step
9492 [D loss: 0.673950, acc.: 55.86%] [G loss: 0.775419]
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9493 [D loss: 0.664786, acc.: 60.74%] [G loss: 0.764489]
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9494 [D loss: 0.678317, acc.: 55.86%] [G loss: 0.751206]
8/8 [==============================] - 0s 4ms/step
9495 [D loss: 0.674765, acc.: 55.66%] [G loss: 0.759196]
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9496 [D loss: 0.672181, acc.: 58.59%] [G loss: 0.758292]
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9497 [D loss: 0.668395, acc.: 59.77%] [G loss: 0.754111]
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9498 [D loss: 0.679839, acc.: 55.47%] [G loss: 0.731058]
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9499 [D loss: 0.670982, acc.: 55.86%] [G loss: 0.743767]
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9500 [D loss: 0.664133, acc.: 62.11%] [G loss: 0.755846]
1/1 [==============================] - 0s 19ms/step
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9501 [D loss: 0.681000, acc.: 52.73%] [G loss: 0.758289]
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9502 [D loss: 0.682178, acc.: 55.08%] [G loss: 0.748128]
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9503 [D loss: 0.674227, acc.: 59.96%] [G loss: 0.766647]
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9504 [D loss: 0.673886, acc.: 57.03%] [G loss: 0.754010]
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9505 [D loss: 0.674956, acc.: 58.40%] [G loss: 0.772578]
8/8 [==============================] - 0s 4ms/step
9506 [D loss: 0.685038, acc.: 55.47%] [G loss: 0.762114]
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9507 [D loss: 0.674364, acc.: 57.42%] [G loss: 0.740214]
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9508 [D loss: 0.671039, acc.: 59.57%] [G loss: 0.749245]
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9509 [D loss: 0.685893, acc.: 55.47%] [G loss: 0.727195]
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9510 [D loss: 0.681951, acc.: 58.40%] [G loss: 0.745175]
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9511 [D loss: 0.683584, acc.: 56.45%] [G loss: 0.744957]
8/8 [==============================] - 0s 4ms/step
9512 [D loss: 0.671978, acc.: 59.77%] [G loss: 0.768029]
8/8 [==============================] - 0s 4ms/step
9513 [D loss: 0.691273, acc.: 54.69%] [G loss: 0.771738]
8/8 [==============================] - 0s 4ms/step
9514 [D loss: 0.676459, acc.: 57.42%] [G loss: 0.778507]
8/8 [==============================] - 0s 4ms/step
9515 [D loss: 0.665360, acc.: 60.16%] [G loss: 0.783812]
8/8 [==============================] - 0s 4ms/step
9516 [D loss: 0.667034, acc.: 59.38%] [G loss: 0.764924]
8/8 [==============================] - 0s 4ms/step
9517 [D loss: 0.679074, acc.: 57.42%] [G loss: 0.761895]
8/8 [==============================] - 0s 4ms/step
9518 [D loss: 0.676125, acc.: 58.01%] [G loss: 0.765664]
8/8 [==============================] - 0s 4ms/step
9519 [D loss: 0.678360, acc.: 55.66%] [G loss: 0.754699]
8/8 [==============================] - 0s 4ms/step
9520 [D loss: 0.658725, acc.: 59.57%] [G loss: 0.764485]
8/8 [==============================] - 0s 4ms/step
9521 [D loss: 0.669804, acc.: 60.94%] [G loss: 0.756721]
8/8 [==============================] - 0s 4ms/step
9522 [D loss: 0.668763, acc.: 59.57%] [G loss: 0.766441]
8/8 [==============================] - 0s 4ms/step
9523 [D loss: 0.675397, acc.: 55.27%] [G loss: 0.762119]
8/8 [==============================] - 0s 4ms/step
9524 [D loss: 0.676574, acc.: 58.20%] [G loss: 0.766035]
8/8 [==============================] - 0s 4ms/step
9525 [D loss: 0.687740, acc.: 54.69%] [G loss: 0.769954]
8/8 [==============================] - 0s 4ms/step
9526 [D loss: 0.682368, acc.: 58.59%] [G loss: 0.756269]
8/8 [==============================] - 0s 4ms/step
9527 [D loss: 0.678049, acc.: 57.23%] [G loss: 0.735343]
8/8 [==============================] - 0s 4ms/step
9528 [D loss: 0.663348, acc.: 60.94%] [G loss: 0.727175]
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9529 [D loss: 0.682891, acc.: 55.08%] [G loss: 0.745356]
8/8 [==============================] - 0s 4ms/step
9530 [D loss: 0.677182, acc.: 57.23%] [G loss: 0.742022]
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9531 [D loss: 0.678872, acc.: 57.23%] [G loss: 0.749440]
8/8 [==============================] - 0s 4ms/step
9532 [D loss: 0.683838, acc.: 55.66%] [G loss: 0.775943]
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9533 [D loss: 0.668130, acc.: 62.11%] [G loss: 0.773599]
8/8 [==============================] - 0s 4ms/step
9534 [D loss: 0.674526, acc.: 57.81%] [G loss: 0.794655]
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9535 [D loss: 0.684977, acc.: 54.10%] [G loss: 0.778457]
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9536 [D loss: 0.669065, acc.: 58.79%] [G loss: 0.773384]
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9537 [D loss: 0.675751, acc.: 56.25%] [G loss: 0.769412]
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9538 [D loss: 0.687078, acc.: 53.32%] [G loss: 0.768977]
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9539 [D loss: 0.681296, acc.: 57.81%] [G loss: 0.744475]
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9540 [D loss: 0.664627, acc.: 60.35%] [G loss: 0.753240]
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9541 [D loss: 0.676552, acc.: 57.42%] [G loss: 0.784666]
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9542 [D loss: 0.659695, acc.: 60.55%] [G loss: 0.766572]
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9543 [D loss: 0.676145, acc.: 58.79%] [G loss: 0.789983]
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9544 [D loss: 0.673494, acc.: 56.84%] [G loss: 0.760189]
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9545 [D loss: 0.681819, acc.: 56.45%] [G loss: 0.765159]
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9546 [D loss: 0.674222, acc.: 59.77%] [G loss: 0.752028]
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9547 [D loss: 0.670093, acc.: 61.13%] [G loss: 0.778688]
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9548 [D loss: 0.671563, acc.: 59.57%] [G loss: 0.770817]
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9549 [D loss: 0.675301, acc.: 56.64%] [G loss: 0.784735]
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9550 [D loss: 0.682185, acc.: 56.45%] [G loss: 0.756460]
1/1 [==============================] - 0s 18ms/step
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9551 [D loss: 0.667228, acc.: 57.62%] [G loss: 0.768063]
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9552 [D loss: 0.689225, acc.: 55.86%] [G loss: 0.765723]
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9553 [D loss: 0.685663, acc.: 52.73%] [G loss: 0.758408]
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9554 [D loss: 0.678034, acc.: 55.08%] [G loss: 0.764499]
8/8 [==============================] - 0s 4ms/step
9555 [D loss: 0.680194, acc.: 54.69%] [G loss: 0.752062]
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9556 [D loss: 0.679881, acc.: 55.86%] [G loss: 0.776853]
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9557 [D loss: 0.666236, acc.: 59.57%] [G loss: 0.787808]
8/8 [==============================] - 0s 4ms/step
9558 [D loss: 0.692098, acc.: 52.34%] [G loss: 0.762629]
8/8 [==============================] - 0s 4ms/step
9559 [D loss: 0.678504, acc.: 56.84%] [G loss: 0.788509]
8/8 [==============================] - 0s 4ms/step
9560 [D loss: 0.672684, acc.: 58.40%] [G loss: 0.772264]
8/8 [==============================] - 0s 4ms/step
9561 [D loss: 0.680296, acc.: 54.10%] [G loss: 0.759199]
8/8 [==============================] - 0s 4ms/step
9562 [D loss: 0.671014, acc.: 58.01%] [G loss: 0.763258]
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9563 [D loss: 0.664414, acc.: 58.59%] [G loss: 0.753017]
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9564 [D loss: 0.674518, acc.: 56.84%] [G loss: 0.760270]
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9565 [D loss: 0.686095, acc.: 54.49%] [G loss: 0.762506]
8/8 [==============================] - 0s 4ms/step
9566 [D loss: 0.673664, acc.: 55.86%] [G loss: 0.743178]
8/8 [==============================] - 0s 4ms/step
9567 [D loss: 0.681867, acc.: 55.86%] [G loss: 0.762245]
8/8 [==============================] - 0s 4ms/step
9568 [D loss: 0.678268, acc.: 56.84%] [G loss: 0.739487]
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9569 [D loss: 0.668391, acc.: 59.38%] [G loss: 0.767289]
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9570 [D loss: 0.672341, acc.: 61.13%] [G loss: 0.760550]
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9571 [D loss: 0.678019, acc.: 60.55%] [G loss: 0.753747]
8/8 [==============================] - 0s 4ms/step
9572 [D loss: 0.663291, acc.: 61.33%] [G loss: 0.762032]
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9573 [D loss: 0.679835, acc.: 55.47%] [G loss: 0.759587]
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9574 [D loss: 0.669127, acc.: 59.18%] [G loss: 0.764319]
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9575 [D loss: 0.679003, acc.: 56.05%] [G loss: 0.768459]
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9576 [D loss: 0.674344, acc.: 58.01%] [G loss: 0.750364]
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9577 [D loss: 0.674762, acc.: 56.05%] [G loss: 0.739697]
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9578 [D loss: 0.669575, acc.: 60.35%] [G loss: 0.738113]
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9579 [D loss: 0.672396, acc.: 54.88%] [G loss: 0.760154]
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9580 [D loss: 0.675383, acc.: 55.86%] [G loss: 0.753789]
8/8 [==============================] - 0s 4ms/step
9581 [D loss: 0.677273, acc.: 56.84%] [G loss: 0.766501]
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9582 [D loss: 0.681912, acc.: 56.64%] [G loss: 0.752081]
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9583 [D loss: 0.673243, acc.: 56.84%] [G loss: 0.756026]
8/8 [==============================] - 0s 4ms/step
9584 [D loss: 0.667244, acc.: 59.38%] [G loss: 0.770728]
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9585 [D loss: 0.664552, acc.: 61.33%] [G loss: 0.755382]
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9586 [D loss: 0.683897, acc.: 51.17%] [G loss: 0.750847]
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9587 [D loss: 0.677993, acc.: 57.42%] [G loss: 0.767885]
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9588 [D loss: 0.671234, acc.: 58.79%] [G loss: 0.747532]
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9589 [D loss: 0.676276, acc.: 58.98%] [G loss: 0.767723]
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9590 [D loss: 0.669151, acc.: 58.40%] [G loss: 0.742150]
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9591 [D loss: 0.678318, acc.: 55.08%] [G loss: 0.760218]
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9592 [D loss: 0.675550, acc.: 54.69%] [G loss: 0.760123]
8/8 [==============================] - 0s 4ms/step
9593 [D loss: 0.665950, acc.: 58.98%] [G loss: 0.769070]
8/8 [==============================] - 0s 4ms/step
9594 [D loss: 0.662398, acc.: 60.55%] [G loss: 0.778359]
8/8 [==============================] - 0s 4ms/step
9595 [D loss: 0.668825, acc.: 57.81%] [G loss: 0.776933]
8/8 [==============================] - 0s 4ms/step
9596 [D loss: 0.669702, acc.: 58.01%] [G loss: 0.764875]
8/8 [==============================] - 0s 4ms/step
9597 [D loss: 0.667989, acc.: 57.23%] [G loss: 0.731074]
8/8 [==============================] - 0s 4ms/step
9598 [D loss: 0.672763, acc.: 58.98%] [G loss: 0.725602]
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9599 [D loss: 0.696538, acc.: 55.27%] [G loss: 0.739673]
8/8 [==============================] - 0s 4ms/step
9600 [D loss: 0.669673, acc.: 60.35%] [G loss: 0.738940]
1/1 [==============================] - 0s 22ms/step
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9601 [D loss: 0.674884, acc.: 58.20%] [G loss: 0.789198]
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9602 [D loss: 0.674718, acc.: 55.08%] [G loss: 0.796571]
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9603 [D loss: 0.659685, acc.: 62.30%] [G loss: 0.795451]
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9604 [D loss: 0.664927, acc.: 59.38%] [G loss: 0.788006]
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9605 [D loss: 0.656278, acc.: 59.96%] [G loss: 0.766137]
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9606 [D loss: 0.668308, acc.: 57.81%] [G loss: 0.739172]
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9607 [D loss: 0.677461, acc.: 56.84%] [G loss: 0.740146]
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9608 [D loss: 0.671734, acc.: 59.57%] [G loss: 0.741699]
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9609 [D loss: 0.664678, acc.: 60.55%] [G loss: 0.736961]
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9610 [D loss: 0.675006, acc.: 58.20%] [G loss: 0.759893]
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9611 [D loss: 0.663534, acc.: 61.52%] [G loss: 0.762162]
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9612 [D loss: 0.674549, acc.: 57.62%] [G loss: 0.790131]
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9613 [D loss: 0.668997, acc.: 57.03%] [G loss: 0.815258]
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9614 [D loss: 0.665057, acc.: 62.70%] [G loss: 0.768429]
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9615 [D loss: 0.667902, acc.: 58.01%] [G loss: 0.744327]
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9616 [D loss: 0.684801, acc.: 54.49%] [G loss: 0.740005]
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9617 [D loss: 0.672910, acc.: 57.62%] [G loss: 0.751133]
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9618 [D loss: 0.673670, acc.: 58.98%] [G loss: 0.738822]
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9619 [D loss: 0.662726, acc.: 61.72%] [G loss: 0.769458]
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9620 [D loss: 0.672845, acc.: 58.20%] [G loss: 0.762599]
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9621 [D loss: 0.685978, acc.: 54.10%] [G loss: 0.767632]
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9622 [D loss: 0.662446, acc.: 59.38%] [G loss: 0.774494]
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9623 [D loss: 0.670210, acc.: 56.45%] [G loss: 0.755497]
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9624 [D loss: 0.670708, acc.: 59.57%] [G loss: 0.749963]
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9625 [D loss: 0.665426, acc.: 58.01%] [G loss: 0.762702]
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9626 [D loss: 0.676809, acc.: 58.79%] [G loss: 0.779820]
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9627 [D loss: 0.677592, acc.: 54.10%] [G loss: 0.787571]
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9628 [D loss: 0.671407, acc.: 57.23%] [G loss: 0.763291]
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9629 [D loss: 0.669657, acc.: 57.42%] [G loss: 0.779408]
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9630 [D loss: 0.692265, acc.: 54.10%] [G loss: 0.762628]
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9631 [D loss: 0.680308, acc.: 56.64%] [G loss: 0.745315]
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9632 [D loss: 0.683064, acc.: 54.69%] [G loss: 0.737638]
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9633 [D loss: 0.680216, acc.: 57.23%] [G loss: 0.770726]
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9634 [D loss: 0.669850, acc.: 59.77%] [G loss: 0.758332]
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9635 [D loss: 0.683150, acc.: 54.88%] [G loss: 0.778319]
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9636 [D loss: 0.673380, acc.: 58.20%] [G loss: 0.775551]
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9637 [D loss: 0.667855, acc.: 58.98%] [G loss: 0.771516]
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9638 [D loss: 0.676293, acc.: 57.81%] [G loss: 0.754596]
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9639 [D loss: 0.679222, acc.: 58.98%] [G loss: 0.756806]
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9640 [D loss: 0.664331, acc.: 61.13%] [G loss: 0.771826]
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9641 [D loss: 0.685417, acc.: 55.08%] [G loss: 0.778568]
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9642 [D loss: 0.684144, acc.: 56.05%] [G loss: 0.762581]
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9643 [D loss: 0.675756, acc.: 56.25%] [G loss: 0.759223]
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9644 [D loss: 0.665468, acc.: 58.59%] [G loss: 0.778762]
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9645 [D loss: 0.667189, acc.: 58.79%] [G loss: 0.755187]
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9646 [D loss: 0.666734, acc.: 60.16%] [G loss: 0.777039]
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9647 [D loss: 0.685549, acc.: 54.69%] [G loss: 0.763526]
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9648 [D loss: 0.660579, acc.: 62.50%] [G loss: 0.754920]
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9649 [D loss: 0.671423, acc.: 58.01%] [G loss: 0.773890]
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9650 [D loss: 0.679015, acc.: 57.42%] [G loss: 0.764975]
1/1 [==============================] - 0s 19ms/step
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9651 [D loss: 0.684910, acc.: 55.66%] [G loss: 0.755502]
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9652 [D loss: 0.682408, acc.: 54.10%] [G loss: 0.750495]
8/8 [==============================] - 0s 4ms/step
9653 [D loss: 0.672099, acc.: 57.62%] [G loss: 0.760491]
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9654 [D loss: 0.679971, acc.: 58.59%] [G loss: 0.763365]
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9655 [D loss: 0.676539, acc.: 54.69%] [G loss: 0.759922]
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9656 [D loss: 0.679285, acc.: 55.66%] [G loss: 0.756939]
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9657 [D loss: 0.675125, acc.: 58.59%] [G loss: 0.757494]
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9658 [D loss: 0.677100, acc.: 57.23%] [G loss: 0.773407]
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9659 [D loss: 0.670640, acc.: 59.77%] [G loss: 0.774695]
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9660 [D loss: 0.678905, acc.: 53.91%] [G loss: 0.761706]
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9661 [D loss: 0.677292, acc.: 56.84%] [G loss: 0.767625]
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9662 [D loss: 0.660817, acc.: 61.91%] [G loss: 0.780835]
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9663 [D loss: 0.666728, acc.: 60.16%] [G loss: 0.772954]
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9664 [D loss: 0.685131, acc.: 55.47%] [G loss: 0.769480]
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9665 [D loss: 0.680378, acc.: 55.47%] [G loss: 0.758575]
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9666 [D loss: 0.679676, acc.: 55.66%] [G loss: 0.765995]
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9667 [D loss: 0.668455, acc.: 58.20%] [G loss: 0.752409]
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9668 [D loss: 0.664517, acc.: 60.16%] [G loss: 0.746522]
8/8 [==============================] - 0s 4ms/step
9669 [D loss: 0.675627, acc.: 56.84%] [G loss: 0.756122]
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9670 [D loss: 0.671026, acc.: 59.38%] [G loss: 0.757005]
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9671 [D loss: 0.660922, acc.: 61.52%] [G loss: 0.776636]
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9672 [D loss: 0.673796, acc.: 58.01%] [G loss: 0.760116]
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9673 [D loss: 0.681954, acc.: 57.62%] [G loss: 0.760225]
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9674 [D loss: 0.675603, acc.: 54.88%] [G loss: 0.761120]
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9675 [D loss: 0.680623, acc.: 54.69%] [G loss: 0.748597]
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9676 [D loss: 0.677279, acc.: 55.47%] [G loss: 0.754196]
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9677 [D loss: 0.680138, acc.: 57.62%] [G loss: 0.767577]
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9678 [D loss: 0.691284, acc.: 54.49%] [G loss: 0.765829]
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9679 [D loss: 0.664418, acc.: 61.52%] [G loss: 0.759374]
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9680 [D loss: 0.680348, acc.: 57.03%] [G loss: 0.765175]
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9681 [D loss: 0.677817, acc.: 57.03%] [G loss: 0.769058]
8/8 [==============================] - 0s 4ms/step
9682 [D loss: 0.687405, acc.: 53.71%] [G loss: 0.764599]
8/8 [==============================] - 0s 4ms/step
9683 [D loss: 0.671565, acc.: 58.79%] [G loss: 0.769030]
8/8 [==============================] - 0s 4ms/step
9684 [D loss: 0.668967, acc.: 56.05%] [G loss: 0.780005]
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9685 [D loss: 0.678800, acc.: 56.45%] [G loss: 0.753839]
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9686 [D loss: 0.675477, acc.: 56.45%] [G loss: 0.764211]
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9687 [D loss: 0.679414, acc.: 55.47%] [G loss: 0.765085]
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9688 [D loss: 0.662372, acc.: 60.35%] [G loss: 0.770351]
8/8 [==============================] - 0s 4ms/step
9689 [D loss: 0.674205, acc.: 59.57%] [G loss: 0.761619]
8/8 [==============================] - 0s 4ms/step
9690 [D loss: 0.670917, acc.: 58.01%] [G loss: 0.758473]
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9691 [D loss: 0.677380, acc.: 55.66%] [G loss: 0.758247]
8/8 [==============================] - 0s 4ms/step
9692 [D loss: 0.683454, acc.: 53.12%] [G loss: 0.743521]
8/8 [==============================] - 0s 4ms/step
9693 [D loss: 0.688486, acc.: 55.08%] [G loss: 0.739976]
8/8 [==============================] - 0s 4ms/step
9694 [D loss: 0.671576, acc.: 60.16%] [G loss: 0.753671]
8/8 [==============================] - 0s 4ms/step
9695 [D loss: 0.670378, acc.: 58.01%] [G loss: 0.746742]
8/8 [==============================] - 0s 4ms/step
9696 [D loss: 0.672129, acc.: 61.33%] [G loss: 0.753751]
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9697 [D loss: 0.665485, acc.: 58.79%] [G loss: 0.754535]
8/8 [==============================] - 0s 4ms/step
9698 [D loss: 0.673795, acc.: 58.59%] [G loss: 0.756845]
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9699 [D loss: 0.686509, acc.: 54.69%] [G loss: 0.767250]
8/8 [==============================] - 0s 4ms/step
9700 [D loss: 0.667584, acc.: 58.79%] [G loss: 0.769874]
1/1 [==============================] - 0s 19ms/step
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9701 [D loss: 0.683416, acc.: 57.23%] [G loss: 0.749220]
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9702 [D loss: 0.674925, acc.: 59.38%] [G loss: 0.751166]
8/8 [==============================] - 0s 4ms/step
9703 [D loss: 0.672528, acc.: 56.64%] [G loss: 0.764568]
8/8 [==============================] - 0s 4ms/step
9704 [D loss: 0.670249, acc.: 58.20%] [G loss: 0.768342]
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9705 [D loss: 0.679763, acc.: 53.52%] [G loss: 0.762082]
8/8 [==============================] - 0s 4ms/step
9706 [D loss: 0.667323, acc.: 58.98%] [G loss: 0.760753]
8/8 [==============================] - 0s 4ms/step
9707 [D loss: 0.685053, acc.: 55.86%] [G loss: 0.755509]
8/8 [==============================] - 0s 4ms/step
9708 [D loss: 0.678220, acc.: 54.69%] [G loss: 0.791804]
8/8 [==============================] - 0s 4ms/step
9709 [D loss: 0.677735, acc.: 57.81%] [G loss: 0.734851]
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9710 [D loss: 0.680515, acc.: 57.03%] [G loss: 0.740496]
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9711 [D loss: 0.664713, acc.: 56.64%] [G loss: 0.728867]
8/8 [==============================] - 0s 4ms/step
9712 [D loss: 0.679425, acc.: 57.81%] [G loss: 0.749967]
8/8 [==============================] - 0s 4ms/step
9713 [D loss: 0.684830, acc.: 54.10%] [G loss: 0.751700]
8/8 [==============================] - 0s 4ms/step
9714 [D loss: 0.663628, acc.: 60.74%] [G loss: 0.754873]
8/8 [==============================] - 0s 4ms/step
9715 [D loss: 0.669399, acc.: 58.59%] [G loss: 0.791589]
8/8 [==============================] - 0s 4ms/step
9716 [D loss: 0.661531, acc.: 61.72%] [G loss: 0.802193]
8/8 [==============================] - 0s 4ms/step
9717 [D loss: 0.669154, acc.: 58.40%] [G loss: 0.788698]
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9718 [D loss: 0.671737, acc.: 56.64%] [G loss: 0.789782]
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9719 [D loss: 0.683405, acc.: 55.47%] [G loss: 0.776106]
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9720 [D loss: 0.664914, acc.: 58.01%] [G loss: 0.757438]
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9721 [D loss: 0.685164, acc.: 54.49%] [G loss: 0.771306]
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9722 [D loss: 0.675819, acc.: 57.23%] [G loss: 0.773538]
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9723 [D loss: 0.672306, acc.: 58.59%] [G loss: 0.796440]
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9724 [D loss: 0.676933, acc.: 57.81%] [G loss: 0.770894]
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9725 [D loss: 0.674246, acc.: 56.25%] [G loss: 0.767497]
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9726 [D loss: 0.678064, acc.: 58.79%] [G loss: 0.784451]
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9727 [D loss: 0.680436, acc.: 57.81%] [G loss: 0.753934]
8/8 [==============================] - 0s 4ms/step
9728 [D loss: 0.683800, acc.: 56.45%] [G loss: 0.744402]
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9729 [D loss: 0.664259, acc.: 59.57%] [G loss: 0.768048]
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9730 [D loss: 0.665241, acc.: 59.57%] [G loss: 0.756865]
8/8 [==============================] - 0s 4ms/step
9731 [D loss: 0.685410, acc.: 55.66%] [G loss: 0.779349]
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9732 [D loss: 0.675836, acc.: 56.05%] [G loss: 0.766633]
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9733 [D loss: 0.673695, acc.: 59.18%] [G loss: 0.748828]
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9734 [D loss: 0.674185, acc.: 55.86%] [G loss: 0.773840]
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9735 [D loss: 0.673474, acc.: 59.18%] [G loss: 0.754555]
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9736 [D loss: 0.685527, acc.: 53.52%] [G loss: 0.756401]
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9737 [D loss: 0.677887, acc.: 55.86%] [G loss: 0.759173]
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9738 [D loss: 0.672927, acc.: 54.88%] [G loss: 0.763182]
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9739 [D loss: 0.677808, acc.: 58.01%] [G loss: 0.758517]
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9740 [D loss: 0.674114, acc.: 58.79%] [G loss: 0.780893]
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9741 [D loss: 0.669101, acc.: 61.33%] [G loss: 0.764958]
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9742 [D loss: 0.663684, acc.: 59.18%] [G loss: 0.764809]
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9743 [D loss: 0.678098, acc.: 60.16%] [G loss: 0.752339]
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9744 [D loss: 0.681729, acc.: 56.84%] [G loss: 0.749856]
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9745 [D loss: 0.670544, acc.: 58.79%] [G loss: 0.755520]
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9746 [D loss: 0.672215, acc.: 60.35%] [G loss: 0.763347]
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9747 [D loss: 0.673417, acc.: 58.98%] [G loss: 0.737441]
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9748 [D loss: 0.677920, acc.: 57.62%] [G loss: 0.768782]
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9749 [D loss: 0.678926, acc.: 58.01%] [G loss: 0.761097]
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9750 [D loss: 0.681851, acc.: 54.88%] [G loss: 0.758250]
1/1 [==============================] - 0s 18ms/step
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9751 [D loss: 0.672521, acc.: 58.20%] [G loss: 0.745729]
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9752 [D loss: 0.671278, acc.: 58.40%] [G loss: 0.759890]
8/8 [==============================] - 0s 4ms/step
9753 [D loss: 0.683040, acc.: 55.47%] [G loss: 0.759691]
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9754 [D loss: 0.679360, acc.: 54.88%] [G loss: 0.764941]
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9755 [D loss: 0.667599, acc.: 57.81%] [G loss: 0.750548]
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9756 [D loss: 0.666884, acc.: 58.20%] [G loss: 0.769831]
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9757 [D loss: 0.670605, acc.: 59.18%] [G loss: 0.760685]
8/8 [==============================] - 0s 4ms/step
9758 [D loss: 0.665697, acc.: 61.33%] [G loss: 0.769832]
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9759 [D loss: 0.678860, acc.: 56.25%] [G loss: 0.774256]
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9760 [D loss: 0.671803, acc.: 57.42%] [G loss: 0.778260]
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9761 [D loss: 0.669964, acc.: 58.01%] [G loss: 0.784537]
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9762 [D loss: 0.678863, acc.: 56.45%] [G loss: 0.751141]
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9763 [D loss: 0.675375, acc.: 56.64%] [G loss: 0.736219]
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9764 [D loss: 0.670658, acc.: 59.38%] [G loss: 0.771486]
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9765 [D loss: 0.673842, acc.: 56.84%] [G loss: 0.757095]
8/8 [==============================] - 0s 4ms/step
9766 [D loss: 0.670837, acc.: 57.62%] [G loss: 0.756756]
8/8 [==============================] - 0s 4ms/step
9767 [D loss: 0.671248, acc.: 56.64%] [G loss: 0.772433]
8/8 [==============================] - 0s 4ms/step
9768 [D loss: 0.675939, acc.: 55.86%] [G loss: 0.747901]
8/8 [==============================] - 0s 4ms/step
9769 [D loss: 0.679517, acc.: 56.84%] [G loss: 0.770760]
8/8 [==============================] - 0s 4ms/step
9770 [D loss: 0.665169, acc.: 58.79%] [G loss: 0.773966]
8/8 [==============================] - 0s 4ms/step
9771 [D loss: 0.679989, acc.: 55.08%] [G loss: 0.771349]
8/8 [==============================] - 0s 4ms/step
9772 [D loss: 0.678996, acc.: 57.42%] [G loss: 0.770388]
8/8 [==============================] - 0s 4ms/step
9773 [D loss: 0.676652, acc.: 56.45%] [G loss: 0.767868]
8/8 [==============================] - 0s 4ms/step
9774 [D loss: 0.665521, acc.: 59.77%] [G loss: 0.773158]
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9775 [D loss: 0.674572, acc.: 57.42%] [G loss: 0.764420]
8/8 [==============================] - 0s 4ms/step
9776 [D loss: 0.670431, acc.: 60.74%] [G loss: 0.765861]
8/8 [==============================] - 0s 4ms/step
9777 [D loss: 0.677227, acc.: 57.03%] [G loss: 0.755347]
8/8 [==============================] - 0s 4ms/step
9778 [D loss: 0.661120, acc.: 60.16%] [G loss: 0.767417]
8/8 [==============================] - 0s 4ms/step
9779 [D loss: 0.668872, acc.: 56.05%] [G loss: 0.770298]
8/8 [==============================] - 0s 4ms/step
9780 [D loss: 0.681031, acc.: 53.52%] [G loss: 0.785739]
8/8 [==============================] - 0s 4ms/step
9781 [D loss: 0.667540, acc.: 60.35%] [G loss: 0.780223]
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9782 [D loss: 0.663046, acc.: 58.40%] [G loss: 0.763341]
8/8 [==============================] - 0s 4ms/step
9783 [D loss: 0.672334, acc.: 59.18%] [G loss: 0.747797]
8/8 [==============================] - 0s 4ms/step
9784 [D loss: 0.675933, acc.: 57.62%] [G loss: 0.739233]
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9785 [D loss: 0.669750, acc.: 58.20%] [G loss: 0.758280]
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9786 [D loss: 0.675689, acc.: 55.86%] [G loss: 0.743374]
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9787 [D loss: 0.674776, acc.: 59.18%] [G loss: 0.761976]
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9788 [D loss: 0.671647, acc.: 59.57%] [G loss: 0.764271]
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9789 [D loss: 0.662439, acc.: 61.13%] [G loss: 0.769051]
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9790 [D loss: 0.655405, acc.: 62.30%] [G loss: 0.772948]
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9791 [D loss: 0.685336, acc.: 54.69%] [G loss: 0.768937]
8/8 [==============================] - 0s 4ms/step
9792 [D loss: 0.672120, acc.: 54.69%] [G loss: 0.762094]
8/8 [==============================] - 0s 4ms/step
9793 [D loss: 0.681570, acc.: 55.66%] [G loss: 0.754430]
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9794 [D loss: 0.678204, acc.: 56.25%] [G loss: 0.752244]
8/8 [==============================] - 0s 4ms/step
9795 [D loss: 0.684981, acc.: 53.91%] [G loss: 0.750546]
8/8 [==============================] - 0s 4ms/step
9796 [D loss: 0.667025, acc.: 57.62%] [G loss: 0.766245]
8/8 [==============================] - 0s 4ms/step
9797 [D loss: 0.677408, acc.: 58.40%] [G loss: 0.775418]
8/8 [==============================] - 0s 4ms/step
9798 [D loss: 0.663943, acc.: 58.98%] [G loss: 0.776178]
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9799 [D loss: 0.675972, acc.: 56.45%] [G loss: 0.774888]
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9800 [D loss: 0.679373, acc.: 59.18%] [G loss: 0.778396]
1/1 [==============================] - 0s 19ms/step
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9801 [D loss: 0.672509, acc.: 57.62%] [G loss: 0.764876]
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9802 [D loss: 0.678680, acc.: 57.42%] [G loss: 0.737942]
8/8 [==============================] - 0s 4ms/step
9803 [D loss: 0.672483, acc.: 56.84%] [G loss: 0.745844]
8/8 [==============================] - 0s 4ms/step
9804 [D loss: 0.670632, acc.: 56.84%] [G loss: 0.763163]
8/8 [==============================] - 0s 4ms/step
9805 [D loss: 0.674616, acc.: 59.57%] [G loss: 0.770215]
8/8 [==============================] - 0s 4ms/step
9806 [D loss: 0.671270, acc.: 57.42%] [G loss: 0.769452]
8/8 [==============================] - 0s 4ms/step
9807 [D loss: 0.676170, acc.: 58.01%] [G loss: 0.758888]
8/8 [==============================] - 0s 4ms/step
9808 [D loss: 0.683933, acc.: 55.47%] [G loss: 0.758000]
8/8 [==============================] - 0s 4ms/step
9809 [D loss: 0.667335, acc.: 60.74%] [G loss: 0.734805]
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9810 [D loss: 0.667151, acc.: 57.23%] [G loss: 0.751643]
8/8 [==============================] - 0s 4ms/step
9811 [D loss: 0.668096, acc.: 60.55%] [G loss: 0.751549]
8/8 [==============================] - 0s 4ms/step
9812 [D loss: 0.677694, acc.: 55.27%] [G loss: 0.763737]
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9813 [D loss: 0.671385, acc.: 59.77%] [G loss: 0.768355]
8/8 [==============================] - 0s 4ms/step
9814 [D loss: 0.677801, acc.: 54.30%] [G loss: 0.759267]
8/8 [==============================] - 0s 4ms/step
9815 [D loss: 0.671166, acc.: 58.59%] [G loss: 0.753499]
8/8 [==============================] - 0s 4ms/step
9816 [D loss: 0.663849, acc.: 59.96%] [G loss: 0.760450]
8/8 [==============================] - 0s 4ms/step
9817 [D loss: 0.683486, acc.: 54.49%] [G loss: 0.757051]
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9818 [D loss: 0.688401, acc.: 55.47%] [G loss: 0.755908]
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9819 [D loss: 0.673448, acc.: 57.03%] [G loss: 0.763154]
8/8 [==============================] - 0s 4ms/step
9820 [D loss: 0.666552, acc.: 57.62%] [G loss: 0.763417]
8/8 [==============================] - 0s 4ms/step
9821 [D loss: 0.665589, acc.: 59.57%] [G loss: 0.779649]
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9822 [D loss: 0.665957, acc.: 60.55%] [G loss: 0.746642]
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9823 [D loss: 0.679283, acc.: 55.47%] [G loss: 0.767747]
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9824 [D loss: 0.679540, acc.: 55.86%] [G loss: 0.758989]
8/8 [==============================] - 0s 4ms/step
9825 [D loss: 0.668343, acc.: 58.40%] [G loss: 0.756448]
8/8 [==============================] - 0s 4ms/step
9826 [D loss: 0.677614, acc.: 56.64%] [G loss: 0.747141]
8/8 [==============================] - 0s 4ms/step
9827 [D loss: 0.668186, acc.: 61.72%] [G loss: 0.751800]
8/8 [==============================] - 0s 4ms/step
9828 [D loss: 0.678527, acc.: 56.64%] [G loss: 0.755501]
8/8 [==============================] - 0s 4ms/step
9829 [D loss: 0.676069, acc.: 56.45%] [G loss: 0.764372]
8/8 [==============================] - 0s 4ms/step
9830 [D loss: 0.675817, acc.: 58.79%] [G loss: 0.763326]
8/8 [==============================] - 0s 4ms/step
9831 [D loss: 0.674605, acc.: 56.84%] [G loss: 0.776944]
8/8 [==============================] - 0s 4ms/step
9832 [D loss: 0.679323, acc.: 56.64%] [G loss: 0.757646]
8/8 [==============================] - 0s 4ms/step
9833 [D loss: 0.678587, acc.: 56.25%] [G loss: 0.759583]
8/8 [==============================] - 0s 4ms/step
9834 [D loss: 0.667177, acc.: 58.01%] [G loss: 0.748232]
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9835 [D loss: 0.673628, acc.: 57.42%] [G loss: 0.742981]
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9836 [D loss: 0.676956, acc.: 56.64%] [G loss: 0.766578]
8/8 [==============================] - 0s 4ms/step
9837 [D loss: 0.677729, acc.: 54.88%] [G loss: 0.755914]
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9838 [D loss: 0.678025, acc.: 55.08%] [G loss: 0.739236]
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9839 [D loss: 0.679196, acc.: 55.66%] [G loss: 0.772082]
8/8 [==============================] - 0s 4ms/step
9840 [D loss: 0.672195, acc.: 56.05%] [G loss: 0.760346]
8/8 [==============================] - 0s 4ms/step
9841 [D loss: 0.672213, acc.: 59.18%] [G loss: 0.760048]
8/8 [==============================] - 0s 4ms/step
9842 [D loss: 0.667076, acc.: 57.23%] [G loss: 0.769912]
8/8 [==============================] - 0s 4ms/step
9843 [D loss: 0.669447, acc.: 61.72%] [G loss: 0.761061]
8/8 [==============================] - 0s 4ms/step
9844 [D loss: 0.661876, acc.: 61.13%] [G loss: 0.748721]
8/8 [==============================] - 0s 4ms/step
9845 [D loss: 0.659667, acc.: 62.50%] [G loss: 0.754518]
8/8 [==============================] - 0s 4ms/step
9846 [D loss: 0.672474, acc.: 57.62%] [G loss: 0.738217]
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9847 [D loss: 0.670064, acc.: 55.27%] [G loss: 0.740678]
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9848 [D loss: 0.666239, acc.: 58.01%] [G loss: 0.748115]
8/8 [==============================] - 0s 4ms/step
9849 [D loss: 0.679590, acc.: 57.23%] [G loss: 0.778380]
8/8 [==============================] - 0s 4ms/step
9850 [D loss: 0.662447, acc.: 59.96%] [G loss: 0.762871]
1/1 [==============================] - 0s 21ms/step
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9851 [D loss: 0.664783, acc.: 58.79%] [G loss: 0.779280]
8/8 [==============================] - 0s 4ms/step
9852 [D loss: 0.674592, acc.: 58.40%] [G loss: 0.765299]
8/8 [==============================] - 0s 4ms/step
9853 [D loss: 0.677973, acc.: 58.79%] [G loss: 0.760693]
8/8 [==============================] - 0s 4ms/step
9854 [D loss: 0.678741, acc.: 55.86%] [G loss: 0.755301]
8/8 [==============================] - 0s 4ms/step
9855 [D loss: 0.679391, acc.: 59.38%] [G loss: 0.773572]
8/8 [==============================] - 0s 4ms/step
9856 [D loss: 0.665415, acc.: 57.62%] [G loss: 0.745976]
8/8 [==============================] - 0s 4ms/step
9857 [D loss: 0.674703, acc.: 57.23%] [G loss: 0.754404]
8/8 [==============================] - 0s 4ms/step
9858 [D loss: 0.666755, acc.: 59.96%] [G loss: 0.768643]
8/8 [==============================] - 0s 4ms/step
9859 [D loss: 0.677875, acc.: 59.57%] [G loss: 0.780299]
8/8 [==============================] - 0s 4ms/step
9860 [D loss: 0.669645, acc.: 57.23%] [G loss: 0.772814]
8/8 [==============================] - 0s 4ms/step
9861 [D loss: 0.674044, acc.: 56.05%] [G loss: 0.793244]
8/8 [==============================] - 0s 4ms/step
9862 [D loss: 0.672358, acc.: 57.03%] [G loss: 0.763848]
8/8 [==============================] - 0s 4ms/step
9863 [D loss: 0.684588, acc.: 52.93%] [G loss: 0.742279]
8/8 [==============================] - 0s 4ms/step
9864 [D loss: 0.675231, acc.: 59.57%] [G loss: 0.740376]
8/8 [==============================] - 0s 4ms/step
9865 [D loss: 0.664557, acc.: 56.84%] [G loss: 0.752693]
8/8 [==============================] - 0s 4ms/step
9866 [D loss: 0.673764, acc.: 59.38%] [G loss: 0.778127]
8/8 [==============================] - 0s 4ms/step
9867 [D loss: 0.670791, acc.: 57.81%] [G loss: 0.753169]
8/8 [==============================] - 0s 4ms/step
9868 [D loss: 0.677831, acc.: 59.18%] [G loss: 0.762811]
8/8 [==============================] - 0s 4ms/step
9869 [D loss: 0.672945, acc.: 58.20%] [G loss: 0.743742]
8/8 [==============================] - 0s 4ms/step
9870 [D loss: 0.681863, acc.: 57.23%] [G loss: 0.739899]
8/8 [==============================] - 0s 4ms/step
9871 [D loss: 0.680881, acc.: 56.25%] [G loss: 0.744848]
8/8 [==============================] - 0s 4ms/step
9872 [D loss: 0.684504, acc.: 54.10%] [G loss: 0.739939]
8/8 [==============================] - 0s 4ms/step
9873 [D loss: 0.674127, acc.: 57.03%] [G loss: 0.797770]
8/8 [==============================] - 0s 4ms/step
9874 [D loss: 0.658935, acc.: 60.94%] [G loss: 0.787870]
8/8 [==============================] - 0s 4ms/step
9875 [D loss: 0.669248, acc.: 55.47%] [G loss: 0.779407]
8/8 [==============================] - 0s 4ms/step
9876 [D loss: 0.671281, acc.: 58.40%] [G loss: 0.753619]
8/8 [==============================] - 0s 4ms/step
9877 [D loss: 0.667145, acc.: 58.59%] [G loss: 0.730678]
8/8 [==============================] - 0s 4ms/step
9878 [D loss: 0.671915, acc.: 57.81%] [G loss: 0.730471]
8/8 [==============================] - 0s 4ms/step
9879 [D loss: 0.680870, acc.: 57.81%] [G loss: 0.754410]
8/8 [==============================] - 0s 4ms/step
9880 [D loss: 0.664935, acc.: 57.42%] [G loss: 0.733624]
8/8 [==============================] - 0s 4ms/step
9881 [D loss: 0.671624, acc.: 58.40%] [G loss: 0.766865]
8/8 [==============================] - 0s 4ms/step
9882 [D loss: 0.679645, acc.: 58.40%] [G loss: 0.770456]
8/8 [==============================] - 0s 4ms/step
9883 [D loss: 0.685831, acc.: 55.08%] [G loss: 0.778810]
8/8 [==============================] - 0s 4ms/step
9884 [D loss: 0.654129, acc.: 62.50%] [G loss: 0.793056]
8/8 [==============================] - 0s 4ms/step
9885 [D loss: 0.675074, acc.: 56.64%] [G loss: 0.775210]
8/8 [==============================] - 0s 4ms/step
9886 [D loss: 0.675731, acc.: 56.25%] [G loss: 0.781838]
8/8 [==============================] - 0s 4ms/step
9887 [D loss: 0.670745, acc.: 57.81%] [G loss: 0.765909]
8/8 [==============================] - 0s 4ms/step
9888 [D loss: 0.671179, acc.: 56.45%] [G loss: 0.774663]
8/8 [==============================] - 0s 4ms/step
9889 [D loss: 0.671311, acc.: 57.42%] [G loss: 0.759242]
8/8 [==============================] - 0s 4ms/step
9890 [D loss: 0.675872, acc.: 54.88%] [G loss: 0.770390]
8/8 [==============================] - 0s 4ms/step
9891 [D loss: 0.681235, acc.: 53.71%] [G loss: 0.796740]
8/8 [==============================] - 0s 4ms/step
9892 [D loss: 0.677795, acc.: 56.05%] [G loss: 0.765877]
8/8 [==============================] - 0s 4ms/step
9893 [D loss: 0.665957, acc.: 58.40%] [G loss: 0.789734]
8/8 [==============================] - 0s 4ms/step
9894 [D loss: 0.677633, acc.: 57.62%] [G loss: 0.752823]
8/8 [==============================] - 0s 4ms/step
9895 [D loss: 0.672301, acc.: 58.01%] [G loss: 0.744507]
8/8 [==============================] - 0s 4ms/step
9896 [D loss: 0.676532, acc.: 56.25%] [G loss: 0.749622]
8/8 [==============================] - 0s 4ms/step
9897 [D loss: 0.683681, acc.: 53.71%] [G loss: 0.745616]
8/8 [==============================] - 0s 4ms/step
9898 [D loss: 0.671035, acc.: 57.62%] [G loss: 0.761645]
8/8 [==============================] - 0s 4ms/step
9899 [D loss: 0.671095, acc.: 58.79%] [G loss: 0.752548]
8/8 [==============================] - 0s 4ms/step
9900 [D loss: 0.670220, acc.: 56.64%] [G loss: 0.777909]
1/1 [==============================] - 0s 20ms/step
8/8 [==============================] - 0s 4ms/step
9901 [D loss: 0.663037, acc.: 58.40%] [G loss: 0.764333]
8/8 [==============================] - 0s 4ms/step
9902 [D loss: 0.673740, acc.: 56.84%] [G loss: 0.769874]
8/8 [==============================] - 0s 4ms/step
9903 [D loss: 0.676292, acc.: 56.45%] [G loss: 0.768154]
8/8 [==============================] - 0s 4ms/step
9904 [D loss: 0.669849, acc.: 58.40%] [G loss: 0.766816]
8/8 [==============================] - 0s 4ms/step
9905 [D loss: 0.678120, acc.: 56.05%] [G loss: 0.764875]
8/8 [==============================] - 0s 4ms/step
9906 [D loss: 0.668487, acc.: 58.59%] [G loss: 0.760975]
8/8 [==============================] - 0s 4ms/step
9907 [D loss: 0.662829, acc.: 59.96%] [G loss: 0.780739]
8/8 [==============================] - 0s 4ms/step
9908 [D loss: 0.667764, acc.: 60.35%] [G loss: 0.770819]
8/8 [==============================] - 0s 4ms/step
9909 [D loss: 0.661313, acc.: 57.42%] [G loss: 0.770573]
8/8 [==============================] - 0s 4ms/step
9910 [D loss: 0.662315, acc.: 62.50%] [G loss: 0.772882]
8/8 [==============================] - 0s 4ms/step
9911 [D loss: 0.675673, acc.: 58.98%] [G loss: 0.760372]
8/8 [==============================] - 0s 4ms/step
9912 [D loss: 0.665047, acc.: 58.59%] [G loss: 0.760978]
8/8 [==============================] - 0s 4ms/step
9913 [D loss: 0.668442, acc.: 57.62%] [G loss: 0.743821]
8/8 [==============================] - 0s 4ms/step
9914 [D loss: 0.678164, acc.: 57.42%] [G loss: 0.751778]
8/8 [==============================] - 0s 4ms/step
9915 [D loss: 0.679552, acc.: 55.08%] [G loss: 0.770692]
8/8 [==============================] - 0s 4ms/step
9916 [D loss: 0.674995, acc.: 55.47%] [G loss: 0.796726]
8/8 [==============================] - 0s 4ms/step
9917 [D loss: 0.670411, acc.: 59.57%] [G loss: 0.803210]
8/8 [==============================] - 0s 4ms/step
9918 [D loss: 0.676662, acc.: 55.08%] [G loss: 0.797726]
8/8 [==============================] - 0s 4ms/step
9919 [D loss: 0.677148, acc.: 56.64%] [G loss: 0.794934]
8/8 [==============================] - 0s 4ms/step
9920 [D loss: 0.663189, acc.: 60.16%] [G loss: 0.785285]
8/8 [==============================] - 0s 4ms/step
9921 [D loss: 0.667062, acc.: 59.77%] [G loss: 0.790748]
8/8 [==============================] - 0s 4ms/step
9922 [D loss: 0.674148, acc.: 58.98%] [G loss: 0.759640]
8/8 [==============================] - 0s 4ms/step
9923 [D loss: 0.678888, acc.: 58.01%] [G loss: 0.756774]
8/8 [==============================] - 0s 4ms/step
9924 [D loss: 0.665251, acc.: 60.74%] [G loss: 0.758123]
8/8 [==============================] - 0s 4ms/step
9925 [D loss: 0.674986, acc.: 57.03%] [G loss: 0.768338]
8/8 [==============================] - 0s 4ms/step
9926 [D loss: 0.672663, acc.: 61.72%] [G loss: 0.768110]
8/8 [==============================] - 0s 4ms/step
9927 [D loss: 0.675152, acc.: 57.81%] [G loss: 0.763997]
8/8 [==============================] - 0s 4ms/step
9928 [D loss: 0.671867, acc.: 60.16%] [G loss: 0.755313]
8/8 [==============================] - 0s 4ms/step
9929 [D loss: 0.676392, acc.: 57.42%] [G loss: 0.765719]
8/8 [==============================] - 0s 4ms/step
9930 [D loss: 0.668541, acc.: 59.18%] [G loss: 0.775902]
8/8 [==============================] - 0s 4ms/step
9931 [D loss: 0.676815, acc.: 57.42%] [G loss: 0.761086]
8/8 [==============================] - 0s 4ms/step
9932 [D loss: 0.665951, acc.: 59.77%] [G loss: 0.753959]
8/8 [==============================] - 0s 4ms/step
9933 [D loss: 0.679345, acc.: 58.01%] [G loss: 0.742195]
8/8 [==============================] - 0s 4ms/step
9934 [D loss: 0.669624, acc.: 63.28%] [G loss: 0.746523]
8/8 [==============================] - 0s 4ms/step
9935 [D loss: 0.670760, acc.: 58.98%] [G loss: 0.752027]
8/8 [==============================] - 0s 4ms/step
9936 [D loss: 0.666527, acc.: 58.98%] [G loss: 0.760170]
8/8 [==============================] - 0s 4ms/step
9937 [D loss: 0.691319, acc.: 54.69%] [G loss: 0.744143]
8/8 [==============================] - 0s 4ms/step
9938 [D loss: 0.676537, acc.: 57.62%] [G loss: 0.758219]
8/8 [==============================] - 0s 4ms/step
9939 [D loss: 0.669081, acc.: 59.18%] [G loss: 0.759504]
8/8 [==============================] - 0s 4ms/step
9940 [D loss: 0.669659, acc.: 61.52%] [G loss: 0.773498]
8/8 [==============================] - 0s 4ms/step
9941 [D loss: 0.694209, acc.: 51.17%] [G loss: 0.765616]
8/8 [==============================] - 0s 4ms/step
9942 [D loss: 0.668355, acc.: 57.23%] [G loss: 0.765607]
8/8 [==============================] - 0s 4ms/step
9943 [D loss: 0.676370, acc.: 57.23%] [G loss: 0.770380]
8/8 [==============================] - 0s 4ms/step
9944 [D loss: 0.674485, acc.: 59.38%] [G loss: 0.754043]
8/8 [==============================] - 0s 4ms/step
9945 [D loss: 0.673033, acc.: 57.81%] [G loss: 0.772256]
8/8 [==============================] - 0s 4ms/step
9946 [D loss: 0.668790, acc.: 59.57%] [G loss: 0.768026]
8/8 [==============================] - 0s 4ms/step
9947 [D loss: 0.679040, acc.: 56.25%] [G loss: 0.767203]
8/8 [==============================] - 0s 4ms/step
9948 [D loss: 0.663181, acc.: 62.70%] [G loss: 0.779098]
8/8 [==============================] - 0s 4ms/step
9949 [D loss: 0.668487, acc.: 58.40%] [G loss: 0.732005]
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9950 [D loss: 0.666383, acc.: 60.74%] [G loss: 0.757933]
1/1 [==============================] - 0s 19ms/step
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9951 [D loss: 0.667521, acc.: 59.18%] [G loss: 0.763411]
8/8 [==============================] - 0s 4ms/step
9952 [D loss: 0.676342, acc.: 54.49%] [G loss: 0.763226]
8/8 [==============================] - 0s 4ms/step
9953 [D loss: 0.685603, acc.: 54.30%] [G loss: 0.765105]
8/8 [==============================] - 0s 4ms/step
9954 [D loss: 0.676845, acc.: 54.49%] [G loss: 0.765793]
8/8 [==============================] - 0s 4ms/step
9955 [D loss: 0.678912, acc.: 58.79%] [G loss: 0.779553]
8/8 [==============================] - 0s 4ms/step
9956 [D loss: 0.676434, acc.: 56.05%] [G loss: 0.784916]
8/8 [==============================] - 0s 4ms/step
9957 [D loss: 0.676496, acc.: 56.45%] [G loss: 0.774643]
8/8 [==============================] - 0s 4ms/step
9958 [D loss: 0.678940, acc.: 55.86%] [G loss: 0.780744]
8/8 [==============================] - 0s 4ms/step
9959 [D loss: 0.681813, acc.: 55.66%] [G loss: 0.769862]
8/8 [==============================] - 0s 4ms/step
9960 [D loss: 0.678469, acc.: 56.25%] [G loss: 0.762432]
8/8 [==============================] - 0s 4ms/step
9961 [D loss: 0.678722, acc.: 58.79%] [G loss: 0.770176]
8/8 [==============================] - 0s 4ms/step
9962 [D loss: 0.681445, acc.: 55.27%] [G loss: 0.764198]
8/8 [==============================] - 0s 4ms/step
9963 [D loss: 0.673010, acc.: 56.64%] [G loss: 0.761728]
8/8 [==============================] - 0s 4ms/step
9964 [D loss: 0.668534, acc.: 59.57%] [G loss: 0.780050]
8/8 [==============================] - 0s 4ms/step
9965 [D loss: 0.679259, acc.: 57.23%] [G loss: 0.773221]
8/8 [==============================] - 0s 4ms/step
9966 [D loss: 0.669702, acc.: 58.40%] [G loss: 0.766837]
8/8 [==============================] - 0s 4ms/step
9967 [D loss: 0.677715, acc.: 54.30%] [G loss: 0.761156]
8/8 [==============================] - 0s 4ms/step
9968 [D loss: 0.656590, acc.: 61.72%] [G loss: 0.760792]
8/8 [==============================] - 0s 4ms/step
9969 [D loss: 0.679644, acc.: 58.01%] [G loss: 0.738797]
8/8 [==============================] - 0s 4ms/step
9970 [D loss: 0.669883, acc.: 58.01%] [G loss: 0.758873]
8/8 [==============================] - 0s 4ms/step
9971 [D loss: 0.672342, acc.: 58.01%] [G loss: 0.749031]
8/8 [==============================] - 0s 4ms/step
9972 [D loss: 0.681915, acc.: 55.47%] [G loss: 0.779249]
8/8 [==============================] - 0s 4ms/step
9973 [D loss: 0.664252, acc.: 55.66%] [G loss: 0.778066]
8/8 [==============================] - 0s 4ms/step
9974 [D loss: 0.661728, acc.: 58.20%] [G loss: 0.776837]
8/8 [==============================] - 0s 4ms/step
9975 [D loss: 0.672676, acc.: 59.57%] [G loss: 0.767413]
8/8 [==============================] - 0s 4ms/step
9976 [D loss: 0.690279, acc.: 54.30%] [G loss: 0.765090]
8/8 [==============================] - 0s 4ms/step
9977 [D loss: 0.695157, acc.: 54.30%] [G loss: 0.772283]
8/8 [==============================] - 0s 4ms/step
9978 [D loss: 0.664879, acc.: 59.77%] [G loss: 0.761757]
8/8 [==============================] - 0s 4ms/step
9979 [D loss: 0.682988, acc.: 54.88%] [G loss: 0.759293]
8/8 [==============================] - 0s 4ms/step
9980 [D loss: 0.675652, acc.: 57.42%] [G loss: 0.759335]
8/8 [==============================] - 0s 4ms/step
9981 [D loss: 0.686153, acc.: 54.49%] [G loss: 0.788133]
8/8 [==============================] - 0s 4ms/step
9982 [D loss: 0.678411, acc.: 54.30%] [G loss: 0.789130]
8/8 [==============================] - 0s 4ms/step
9983 [D loss: 0.653060, acc.: 61.91%] [G loss: 0.770131]
8/8 [==============================] - 0s 4ms/step
9984 [D loss: 0.672138, acc.: 56.84%] [G loss: 0.751844]
8/8 [==============================] - 0s 4ms/step
9985 [D loss: 0.689188, acc.: 55.08%] [G loss: 0.748775]
8/8 [==============================] - 0s 4ms/step
9986 [D loss: 0.668928, acc.: 57.62%] [G loss: 0.763104]
8/8 [==============================] - 0s 4ms/step
9987 [D loss: 0.681037, acc.: 57.62%] [G loss: 0.743940]
8/8 [==============================] - 0s 4ms/step
9988 [D loss: 0.685098, acc.: 52.54%] [G loss: 0.766950]
8/8 [==============================] - 0s 4ms/step
9989 [D loss: 0.664466, acc.: 62.70%] [G loss: 0.765837]
8/8 [==============================] - 0s 4ms/step
9990 [D loss: 0.672231, acc.: 58.20%] [G loss: 0.780913]
8/8 [==============================] - 0s 4ms/step
9991 [D loss: 0.680794, acc.: 53.91%] [G loss: 0.763052]
8/8 [==============================] - 0s 4ms/step
9992 [D loss: 0.680773, acc.: 54.10%] [G loss: 0.756305]
8/8 [==============================] - 0s 4ms/step
9993 [D loss: 0.679753, acc.: 57.23%] [G loss: 0.745330]
8/8 [==============================] - 0s 4ms/step
9994 [D loss: 0.672253, acc.: 58.01%] [G loss: 0.753365]
8/8 [==============================] - 0s 4ms/step
9995 [D loss: 0.679905, acc.: 56.05%] [G loss: 0.764355]
8/8 [==============================] - 0s 4ms/step
9996 [D loss: 0.667832, acc.: 61.13%] [G loss: 0.766654]
8/8 [==============================] - 0s 4ms/step
9997 [D loss: 0.671735, acc.: 57.81%] [G loss: 0.760553]
8/8 [==============================] - 0s 4ms/step
9998 [D loss: 0.675624, acc.: 57.81%] [G loss: 0.765219]
8/8 [==============================] - 0s 4ms/step
9999 [D loss: 0.669828, acc.: 58.01%] [G loss: 0.764074]

Plot Loss

plot_losses(dcgan.d_losses, dcgan.g_losses)

Plot Accuracy

plot_accuracy(dcgan.d_accuracy)

Generated Images at Different Epochs (Adding More Dense Units to The Generator)

At 100 Epochs

At 1000 Epochs

At 2950 Epochs

At 9950 Epochs

Results

The training loss curve reveals that the generator's loss starts very high, around 2.5, while the discriminator's loss begins relatively low at approximately 0.3. As training progresses, both losses converge to around 0.7. However, after 4000 epochs, the generator's loss begins to increase, while the discriminator's loss decreases significantly. Eventually, the generator's loss stabilizes around 0.8, and the discriminator's loss flattens at about 0.6.

The accuracy curve shows that the discriminator begins with a very high accuracy of about 99%, which then drops and fluctuates between 40% and 60%. After 4000 epochs, the accuracy improves slightly and stabilizes around 50% to 60%.

After adding more dense units to the generator and increasing the number of epochs, the generated images have become sharper, making more classes easily identifiable. In the generated images, we can clearly see classes like T, E, Z, W, A, Y, H, I, U, B, O, M, and Z. This improvement demonstrates that the adjustments have enhanced the quality and diversity of the generated samples, making it easier to distinguish between different classes.

Conditional GAN

What is Conditional GAN

---

CGANs is a type of Generative Adversarial Network that adds additional information into both the generator and the discriminator to condition the generation process. This additional information can be any type of label or structured data such as class labels, images or other data that helps the generation process.

It allows the generator to create more controlled and contextually appropriate outputs by using the additional information given to it.

Difference between CGANs and DCGANs

---

• CGANs uses additional information as conditions into the generation process while DCGANs focus on using convolutional networks for better performance in image data.

• CGANs are used for tasks that need controlled generated based on the input conditions while DCGANs are used for generating high-quality, realistic images.

• CGANs defining feature is the conditioning mechanism while DCGANs specifically use deep convolutional networks for both the generator and discriminator, emphasizing the architecture rather than conditioning.

How Conditional GAN Works

---

In a CGAN, both the generator and the discriminator receive additional information, such as class labels or attributes, which guide the image generation process. This allows the model to create images that not only resemble real data but also match specified conditions, providing greater control over the output.

The generator in a cGAN takes two inputs: random noise, typically sampled from a normal distribution, and a conditioning variable that represents the desired outcome, such as a class label. This generator learns to produce synthetic images that correspond to the given condition.

Similarly the discriminator also receives both real images and generated images, along with their respective conditions. Its role is to determine whether an image is real or fake, taking the condition into account, and it outputs a probability indicating how likely the image is to be real given that condition.

Training Process of Conditional GAN

---

During each training iteration, the discriminator is trained using a mixed batch containing both real images from the training dataset and generated images produced by the generator, along with their corresponding condition labels. This mixed batch allows the discriminator to simultaneously evaluate and compare real and synthetic samples. After calculating the loss for both real and generated samples, the discriminator's weights are updated to improve its classification accuracy in distinguishing between authentic and generated images while considering the conditional inputs.

Next, the generator is trained by feeding it random noise and the conditional inputs, aiming to maximize the discriminator’s error on the generated images. To facilitate this process, it is common to freeze the weights of the discriminator while training the generator, preventing it from adapting too quickly and allowing the generator to learn more effectively from the feedback. Conversely, when the discriminator is being trained, the generator's weights are frozen. This alternating training helps stabilize the learning dynamics, ensuring that neither component overpowers the other.

Over multiple iterations, both networks improve, ultimately resulting in high-quality, class-specific image generation.

References

https://medium.com/analytics-vidhya/dcgan-cgan-and-sagan-the-cifar-10-dataset-206cbb851327

https://www.geeksforgeeks.org/conditional-generative-adversarial-network/

Base Model

class CGAN():
    def __init__(self):
        # Input shape
        self.img_rows = 28
        self.img_cols = 28
        self.channels = 1
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.num_classes = 26
        self.latent_dim = 100

        optimizer = Adam(0.001, 0.5)

        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss=['binary_crossentropy'],
            optimizer=optimizer,
            metrics=['accuracy'])

        # Build the generator
        self.generator = self.build_generator()

        # The generator takes noise and the target label as input
        # and generates the corresponding digit of that label
        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,))
        img = self.generator([noise, label])

        # For the combined model we will only train the generator
        self.discriminator.trainable = False

        # The discriminator takes generated image as input and determines validity
        # and the label of that image
        valid = self.discriminator([img, label])

        # The combined model  (stacked generator and discriminator)
        # Trains generator to fool discriminator
        self.combined = Model([noise, label], valid)
        self.combined.compile(loss=['binary_crossentropy'],
            optimizer=optimizer)

        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []

    def build_generator(self):

        model = Sequential()

        model.add(Dense(256 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 256)))
        
        model.add(Conv2DTranspose(128, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(self.channels, kernel_size=4, strides=(2,2), padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,), dtype='int32')
        label_embedding = Flatten()(Embedding(self.num_classes, self.latent_dim)(label))

        model_input = multiply([noise, label_embedding])
        img = model(model_input)

        return Model([noise, label], img)

    def build_discriminator(self):
        model = Sequential()

        model.add(Conv2D(64, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))

        
        model.add(Flatten())
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        # Image input and label input
        img = Input(shape=self.img_shape)
        label = Input(shape=(1,), dtype='int32')

        # Embedding for label
        label_embedding = Flatten()(Embedding(self.num_classes, np.prod(self.img_shape))(label))
        label_embedding = Dense(np.prod(self.img_shape))(label_embedding)
        label_embedding = Reshape(self.img_shape)(label_embedding)

        # Multiply image and label embeddings
        combined = multiply([img, label_embedding])

        # Validity prediction
        validity = model(combined)

        return Model([img, label], validity)

    def train(self, epochs, batch_size=128, sample_interval=50):


        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values
        y_train = preprocessed_df.iloc[:, 0].values
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)

        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))

        for epoch in range(epochs):

            # ---------------------
            #  Train Discriminator
            # ---------------------

            # Select a random half batch of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs, labels = X_train[idx], y_train[idx]
            # Sample noise as generator input
            noise = np.random.normal(0, 1, (batch_size, 100))

            # Generate a half batch of new images
            gen_imgs = self.generator.predict([noise, labels])

            # Train the discriminator
            d_loss_real = self.discriminator.train_on_batch([imgs, labels], valid)
            d_loss_fake = self.discriminator.train_on_batch([gen_imgs, labels], fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)

            # ---------------------
            #  Train Generator
            # ---------------------

            # Condition on labels (Generate random samples)
            sampled_labels = np.random.randint(1, 27, batch_size).reshape(-1, 1)

            # Train the generator
            g_loss = self.combined.train_on_batch([noise, sampled_labels], valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            
            # Plot the progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100*d_loss[1], g_loss))

            # If at save interval => save generated image samples
            if epoch % sample_interval == 0:
                self.sample_images(epoch)

    def sample_images(self, epoch):
        r, c = 5, 6
        num_samples = 26
        # Generate noise based on the number of samples
        noise = np.random.normal(0, 1, (num_samples, 100))
        sampled_labels = np.arange(1, 27).reshape(-1, 1)

        gen_imgs = self.generator.predict([noise, sampled_labels])

        # Rescale images 0 - 1
        gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0  # Counter for the images
        for i in range(r):
            for j in range(c):
                if cnt < num_samples:  # Ensure we don't go out of bounds
                    axs[i,j].imshow(gen_imgs[cnt,:,:,0], cmap='gray')  # Display image

                    mapped_label = map_labels(sampled_labels[cnt][0])  # Map label to its corresponding class name
                    axs[i,j].set_title("Class: %s" % mapped_label)  # Set title of the subplot
                    axs[i,j].axis('off')  # Turn off axis
                    cnt += 1  # Increment counter
                else:
                    axs[i,j].axis('off')  # Turn off axis if there's no image to display
                    
        # Adjust the spacing between subplots
        plt.subplots_adjust(wspace=0.2, hspace=0.6)
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/cgan/base', exist_ok=True)
        fig.savefig("generated_images/cgan/base/cgan_{:d}.png".format(epoch))
        plt.close()

cgan = CGAN()
cgan.train(epochs=3000, batch_size=256, sample_interval=50)

Model: "sequential_4"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_23 (Conv2D)          (None, 14, 14, 64)        640       
                                                                 
 leaky_re_lu_18 (LeakyReLU)  (None, 14, 14, 64)        0         
                                                                 
 conv2d_24 (Conv2D)          (None, 7, 7, 128)         73856     
                                                                 
 leaky_re_lu_19 (LeakyReLU)  (None, 7, 7, 128)         0         
                                                                 
 conv2d_25 (Conv2D)          (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_20 (LeakyReLU)  (None, 4, 4, 256)         0         
                                                                 
 flatten_4 (Flatten)         (None, 4096)              0         
                                                                 
 dense_11 (Dense)            (None, 1)                 4097      
                                                                 
=================================================================
Total params: 373,761
Trainable params: 373,761
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_5"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_13 (Dense)            (None, 12544)             1266944   
                                                                 
 reshape_5 (Reshape)         (None, 7, 7, 256)         0         
                                                                 
 conv2d_transpose (Conv2DTra  (None, 14, 14, 128)      524416    
 nspose)                                                         
                                                                 
 batch_normalization_8 (Batc  (None, 14, 14, 128)      512       
 hNormalization)                                                 
                                                                 
 leaky_re_lu_21 (LeakyReLU)  (None, 14, 14, 128)       0         
                                                                 
 conv2d_transpose_1 (Conv2DT  (None, 28, 28, 64)       131136    
 ranspose)                                                       
                                                                 
 batch_normalization_9 (Batc  (None, 28, 28, 64)       256       
 hNormalization)                                                 
                                                                 
 leaky_re_lu_22 (LeakyReLU)  (None, 28, 28, 64)        0         
                                                                 
 conv2d_transpose_2 (Conv2DT  (None, 56, 56, 64)       65600     
 ranspose)                                                       
                                                                 
 batch_normalization_10 (Bat  (None, 56, 56, 64)       256       
 chNormalization)                                                
                                                                 
 leaky_re_lu_23 (LeakyReLU)  (None, 56, 56, 64)        0         
                                                                 
 conv2d_26 (Conv2D)          (None, 28, 28, 1)         1025      
                                                                 
 activation_8 (Activation)   (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 1,990,145
Trainable params: 1,989,633
Non-trainable params: 512
_________________________________________________________________
8/8 [==============================] - 0s 4ms/step
0 [D loss: 0.698601, acc.: 11.72%] [G loss: 0.691174]
1/1 [==============================] - 0s 250ms/step
8/8 [==============================] - 0s 4ms/step
1 [D loss: 0.693890, acc.: 50.00%] [G loss: 0.692150]
8/8 [==============================] - 0s 4ms/step
2 [D loss: 0.693377, acc.: 50.00%] [G loss: 0.693045]
8/8 [==============================] - 0s 4ms/step
3 [D loss: 0.692826, acc.: 50.00%] [G loss: 0.693619]
8/8 [==============================] - 0s 4ms/step
4 [D loss: 0.691771, acc.: 89.84%] [G loss: 0.688330]
8/8 [==============================] - 0s 4ms/step
5 [D loss: 0.688145, acc.: 94.92%] [G loss: 0.681155]
8/8 [==============================] - 0s 4ms/step
6 [D loss: 0.676198, acc.: 87.70%] [G loss: 0.663539]
8/8 [==============================] - 0s 4ms/step
7 [D loss: 0.649778, acc.: 86.52%] [G loss: 0.618151]
8/8 [==============================] - 0s 4ms/step
8 [D loss: 0.576201, acc.: 95.31%] [G loss: 0.631453]
8/8 [==============================] - 0s 4ms/step
9 [D loss: 0.618627, acc.: 70.31%] [G loss: 0.360312]
8/8 [==============================] - 0s 4ms/step
10 [D loss: 0.665653, acc.: 48.24%] [G loss: 0.317643]
8/8 [==============================] - 0s 4ms/step
11 [D loss: 0.650361, acc.: 45.70%] [G loss: 0.363741]
8/8 [==============================] - 0s 4ms/step
12 [D loss: 0.648421, acc.: 43.95%] [G loss: 0.239940]
8/8 [==============================] - 0s 4ms/step
13 [D loss: 0.623080, acc.: 47.46%] [G loss: 0.145565]
8/8 [==============================] - 0s 4ms/step
14 [D loss: 0.699220, acc.: 48.83%] [G loss: 0.235396]
8/8 [==============================] - 0s 4ms/step
15 [D loss: 0.725984, acc.: 48.05%] [G loss: 1.052137]
8/8 [==============================] - 0s 4ms/step
16 [D loss: 1.193618, acc.: 39.06%] [G loss: 1.554098]
8/8 [==============================] - 0s 4ms/step
17 [D loss: 0.638730, acc.: 56.05%] [G loss: 1.774543]
8/8 [==============================] - 0s 4ms/step
18 [D loss: 0.629752, acc.: 51.37%] [G loss: 1.612349]
8/8 [==============================] - 0s 4ms/step
19 [D loss: 0.593641, acc.: 56.84%] [G loss: 1.549523]
8/8 [==============================] - 0s 4ms/step
20 [D loss: 0.599129, acc.: 57.42%] [G loss: 1.679803]
8/8 [==============================] - 0s 4ms/step
21 [D loss: 0.591200, acc.: 59.96%] [G loss: 1.619450]
8/8 [==============================] - 0s 4ms/step
22 [D loss: 0.540552, acc.: 61.33%] [G loss: 1.767461]
8/8 [==============================] - 0s 4ms/step
23 [D loss: 0.505830, acc.: 70.90%] [G loss: 2.231458]
8/8 [==============================] - 0s 4ms/step
24 [D loss: 0.453197, acc.: 75.39%] [G loss: 2.603585]
8/8 [==============================] - 0s 4ms/step
25 [D loss: 0.375784, acc.: 84.77%] [G loss: 2.455316]
8/8 [==============================] - 0s 4ms/step
26 [D loss: 0.339821, acc.: 90.04%] [G loss: 0.806157]
8/8 [==============================] - 0s 4ms/step
27 [D loss: 0.344677, acc.: 91.99%] [G loss: 0.615964]
8/8 [==============================] - 0s 4ms/step
28 [D loss: 0.273649, acc.: 93.55%] [G loss: 0.523308]
8/8 [==============================] - 0s 4ms/step
29 [D loss: 0.287230, acc.: 93.16%] [G loss: 0.308745]
8/8 [==============================] - 0s 4ms/step
30 [D loss: 0.238686, acc.: 93.16%] [G loss: 0.372511]
8/8 [==============================] - 0s 4ms/step
31 [D loss: 0.497698, acc.: 72.85%] [G loss: 0.983333]
8/8 [==============================] - 0s 4ms/step
32 [D loss: 0.548706, acc.: 72.07%] [G loss: 1.086097]
8/8 [==============================] - 0s 4ms/step
33 [D loss: 0.617617, acc.: 38.87%] [G loss: 0.684179]
8/8 [==============================] - 0s 4ms/step
34 [D loss: 0.491349, acc.: 44.92%] [G loss: 0.739256]
8/8 [==============================] - 0s 4ms/step
35 [D loss: 0.411976, acc.: 98.24%] [G loss: 0.856148]
8/8 [==============================] - 0s 4ms/step
36 [D loss: 0.327100, acc.: 98.83%] [G loss: 1.199020]
8/8 [==============================] - 0s 4ms/step
37 [D loss: 0.243920, acc.: 97.07%] [G loss: 1.965228]
8/8 [==============================] - 0s 4ms/step
38 [D loss: 0.163471, acc.: 95.70%] [G loss: 2.678281]
8/8 [==============================] - 0s 4ms/step
39 [D loss: 0.159079, acc.: 94.92%] [G loss: 2.771056]
8/8 [==============================] - 0s 4ms/step
40 [D loss: 0.131515, acc.: 96.09%] [G loss: 2.804594]
8/8 [==============================] - 0s 4ms/step
41 [D loss: 0.078384, acc.: 97.46%] [G loss: 3.233043]
8/8 [==============================] - 0s 4ms/step
42 [D loss: 0.068923, acc.: 97.85%] [G loss: 3.471447]
8/8 [==============================] - 0s 4ms/step
43 [D loss: 0.075580, acc.: 97.85%] [G loss: 3.433554]
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44 [D loss: 0.051540, acc.: 98.44%] [G loss: 3.637367]
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45 [D loss: 0.059404, acc.: 97.66%] [G loss: 3.589997]
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46 [D loss: 0.048898, acc.: 98.44%] [G loss: 3.736653]
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47 [D loss: 0.035168, acc.: 99.22%] [G loss: 3.904994]
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48 [D loss: 0.049340, acc.: 99.02%] [G loss: 4.003319]
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49 [D loss: 0.056527, acc.: 97.66%] [G loss: 3.738339]
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50 [D loss: 0.033528, acc.: 98.83%] [G loss: 3.964633]
1/1 [==============================] - 0s 22ms/step
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51 [D loss: 0.024994, acc.: 99.22%] [G loss: 4.202330]
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52 [D loss: 0.037319, acc.: 98.44%] [G loss: 4.062027]
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53 [D loss: 0.029800, acc.: 99.02%] [G loss: 4.156511]
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54 [D loss: 0.021161, acc.: 99.02%] [G loss: 4.358858]
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55 [D loss: 0.028442, acc.: 98.83%] [G loss: 4.293622]
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56 [D loss: 0.035057, acc.: 99.02%] [G loss: 4.156117]
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57 [D loss: 0.013255, acc.: 99.80%] [G loss: 4.505867]
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58 [D loss: 0.019727, acc.: 99.61%] [G loss: 4.552774]
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59 [D loss: 1.498051, acc.: 52.15%] [G loss: 13.062838]
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60 [D loss: 2.943760, acc.: 31.64%] [G loss: 7.724355]
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61 [D loss: 0.408322, acc.: 83.01%] [G loss: 9.080703]
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62 [D loss: 8.756820, acc.: 28.12%] [G loss: 10.728514]
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63 [D loss: 1.821312, acc.: 50.59%] [G loss: 2.228942]
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64 [D loss: 0.686331, acc.: 66.99%] [G loss: 0.229900]
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65 [D loss: 0.428056, acc.: 80.27%] [G loss: 0.137692]
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66 [D loss: 0.236417, acc.: 90.04%] [G loss: 0.092939]
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67 [D loss: 0.283336, acc.: 87.70%] [G loss: 0.094019]
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68 [D loss: 0.342954, acc.: 84.57%] [G loss: 0.127582]
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69 [D loss: 0.387822, acc.: 83.79%] [G loss: 0.282720]
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70 [D loss: 0.764988, acc.: 61.91%] [G loss: 0.762257]
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71 [D loss: 1.293594, acc.: 27.93%] [G loss: 0.728752]
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72 [D loss: 1.112882, acc.: 26.95%] [G loss: 0.848251]
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73 [D loss: 0.973628, acc.: 44.73%] [G loss: 0.888713]
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74 [D loss: 0.829857, acc.: 47.85%] [G loss: 0.921223]
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75 [D loss: 0.704590, acc.: 54.88%] [G loss: 0.996841]
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76 [D loss: 0.641590, acc.: 67.77%] [G loss: 1.079310]
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77 [D loss: 0.571931, acc.: 77.93%] [G loss: 1.153665]
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78 [D loss: 0.513932, acc.: 84.38%] [G loss: 1.278679]
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79 [D loss: 0.499808, acc.: 83.79%] [G loss: 1.406086]
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80 [D loss: 0.469122, acc.: 83.59%] [G loss: 1.456543]
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81 [D loss: 0.449351, acc.: 85.94%] [G loss: 1.559739]
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82 [D loss: 0.438655, acc.: 84.77%] [G loss: 1.786809]
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83 [D loss: 0.357222, acc.: 89.84%] [G loss: 1.772829]
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84 [D loss: 0.360592, acc.: 88.67%] [G loss: 1.868944]
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85 [D loss: 0.281971, acc.: 94.14%] [G loss: 1.782187]
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86 [D loss: 0.279411, acc.: 92.97%] [G loss: 1.905126]
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87 [D loss: 0.285748, acc.: 93.16%] [G loss: 1.746150]
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88 [D loss: 0.273634, acc.: 93.55%] [G loss: 1.839354]
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89 [D loss: 0.212097, acc.: 94.53%] [G loss: 2.041848]
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90 [D loss: 0.194758, acc.: 94.92%] [G loss: 2.198607]
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91 [D loss: 0.171185, acc.: 95.70%] [G loss: 2.330649]
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92 [D loss: 0.145023, acc.: 97.27%] [G loss: 2.480000]
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93 [D loss: 0.138452, acc.: 96.48%] [G loss: 2.558432]
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94 [D loss: 0.126413, acc.: 95.90%] [G loss: 2.634586]
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95 [D loss: 0.108487, acc.: 97.07%] [G loss: 2.751618]
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96 [D loss: 0.117368, acc.: 96.29%] [G loss: 2.785830]
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97 [D loss: 0.129483, acc.: 94.73%] [G loss: 2.737781]
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98 [D loss: 0.094605, acc.: 97.66%] [G loss: 2.828083]
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99 [D loss: 0.087890, acc.: 97.46%] [G loss: 2.944497]
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100 [D loss: 0.071423, acc.: 97.85%] [G loss: 3.081672]
1/1 [==============================] - 0s 22ms/step
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101 [D loss: 0.078175, acc.: 97.46%] [G loss: 3.154414]
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102 [D loss: 0.070883, acc.: 97.46%] [G loss: 3.217041]
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103 [D loss: 0.062654, acc.: 98.24%] [G loss: 3.300090]
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104 [D loss: 0.054917, acc.: 98.05%] [G loss: 3.386891]
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105 [D loss: 0.081997, acc.: 96.68%] [G loss: 3.278726]
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106 [D loss: 0.059158, acc.: 98.05%] [G loss: 3.311784]
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107 [D loss: 0.050451, acc.: 98.44%] [G loss: 3.434850]
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108 [D loss: 0.094256, acc.: 96.29%] [G loss: 3.303218]
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109 [D loss: 0.054071, acc.: 98.05%] [G loss: 3.346542]
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110 [D loss: 0.035844, acc.: 99.02%] [G loss: 3.542528]
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111 [D loss: 0.054442, acc.: 98.05%] [G loss: 3.577630]
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112 [D loss: 0.034238, acc.: 99.02%] [G loss: 3.684711]
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113 [D loss: 0.043647, acc.: 98.63%] [G loss: 3.701535]
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114 [D loss: 0.050149, acc.: 98.24%] [G loss: 3.666279]
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115 [D loss: 0.025447, acc.: 99.41%] [G loss: 3.823497]
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116 [D loss: 0.056857, acc.: 98.24%] [G loss: 3.729225]
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117 [D loss: 0.035251, acc.: 98.83%] [G loss: 3.768497]
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118 [D loss: 0.028178, acc.: 99.02%] [G loss: 3.880834]
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119 [D loss: 0.036578, acc.: 98.44%] [G loss: 3.880704]
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120 [D loss: 0.028657, acc.: 98.83%] [G loss: 3.936812]
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121 [D loss: 0.036439, acc.: 98.44%] [G loss: 3.913567]
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122 [D loss: 0.032167, acc.: 98.63%] [G loss: 3.915215]
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123 [D loss: 0.024133, acc.: 99.41%] [G loss: 4.011320]
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124 [D loss: 0.026171, acc.: 99.22%] [G loss: 4.072401]
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125 [D loss: 0.029821, acc.: 98.83%] [G loss: 4.100913]
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126 [D loss: 0.017236, acc.: 99.61%] [G loss: 4.228714]
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127 [D loss: 0.022310, acc.: 99.22%] [G loss: 4.291604]
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128 [D loss: 0.017989, acc.: 99.61%] [G loss: 4.366920]
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129 [D loss: 0.014731, acc.: 99.61%] [G loss: 4.462317]
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130 [D loss: 0.021795, acc.: 99.02%] [G loss: 4.422867]
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131 [D loss: 0.019550, acc.: 99.22%] [G loss: 4.406123]
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132 [D loss: 0.025860, acc.: 99.61%] [G loss: 4.407138]
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133 [D loss: 0.028917, acc.: 99.41%] [G loss: 4.395261]
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134 [D loss: 0.024230, acc.: 99.02%] [G loss: 4.346714]
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135 [D loss: 0.016099, acc.: 99.41%] [G loss: 4.403516]
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136 [D loss: 0.014367, acc.: 99.80%] [G loss: 4.481310]
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137 [D loss: 0.015909, acc.: 99.61%] [G loss: 4.540719]
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138 [D loss: 0.016975, acc.: 99.80%] [G loss: 4.563193]
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139 [D loss: 0.019147, acc.: 99.02%] [G loss: 4.515863]
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140 [D loss: 0.027585, acc.: 99.61%] [G loss: 4.469495]
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141 [D loss: 0.014642, acc.: 99.41%] [G loss: 4.518531]
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142 [D loss: 0.023125, acc.: 99.22%] [G loss: 4.451804]
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143 [D loss: 0.012848, acc.: 99.61%] [G loss: 4.536754]
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144 [D loss: 0.007898, acc.: 100.00%] [G loss: 4.714324]
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145 [D loss: 0.015323, acc.: 99.61%] [G loss: 4.726277]
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146 [D loss: 0.019534, acc.: 99.41%] [G loss: 4.677224]
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147 [D loss: 0.006104, acc.: 100.00%] [G loss: 4.837720]
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148 [D loss: 0.012318, acc.: 99.80%] [G loss: 4.882573]
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149 [D loss: 0.017177, acc.: 99.41%] [G loss: 4.829443]
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150 [D loss: 0.011564, acc.: 99.61%] [G loss: 4.830708]
1/1 [==============================] - 0s 19ms/step
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151 [D loss: 0.011494, acc.: 100.00%] [G loss: 4.828063]
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152 [D loss: 0.007083, acc.: 99.80%] [G loss: 4.941644]
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153 [D loss: 0.008232, acc.: 99.80%] [G loss: 5.031123]
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154 [D loss: 0.006237, acc.: 99.80%] [G loss: 5.131747]
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155 [D loss: 0.013868, acc.: 99.61%] [G loss: 5.072174]
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156 [D loss: 0.017063, acc.: 99.22%] [G loss: 4.917390]
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157 [D loss: 0.022176, acc.: 99.61%] [G loss: 4.341928]
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158 [D loss: 0.294355, acc.: 81.84%] [G loss: 9.200730]
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159 [D loss: 0.364393, acc.: 85.94%] [G loss: 16.101379]
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160 [D loss: 1.096227, acc.: 74.41%] [G loss: 5.081173]
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161 [D loss: 1.220204, acc.: 62.89%] [G loss: 7.852302]
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162 [D loss: 1.737200, acc.: 54.30%] [G loss: 11.417192]
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163 [D loss: 2.038442, acc.: 48.44%] [G loss: 3.495761]
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164 [D loss: 0.700706, acc.: 62.11%] [G loss: 3.761796]
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165 [D loss: 0.611666, acc.: 69.14%] [G loss: 3.311340]
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166 [D loss: 0.486354, acc.: 77.93%] [G loss: 2.821199]
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167 [D loss: 0.437898, acc.: 84.96%] [G loss: 2.589413]
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168 [D loss: 0.302946, acc.: 87.50%] [G loss: 2.886491]
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169 [D loss: 0.338732, acc.: 86.13%] [G loss: 2.908515]
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170 [D loss: 0.341678, acc.: 85.35%] [G loss: 3.113094]
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171 [D loss: 0.326187, acc.: 87.70%] [G loss: 3.306794]
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172 [D loss: 0.321730, acc.: 87.70%] [G loss: 3.248309]
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173 [D loss: 0.434944, acc.: 81.84%] [G loss: 3.362900]
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174 [D loss: 0.334178, acc.: 88.09%] [G loss: 3.682240]
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175 [D loss: 0.330213, acc.: 87.70%] [G loss: 3.782189]
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176 [D loss: 0.334455, acc.: 85.94%] [G loss: 3.790225]
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177 [D loss: 0.303567, acc.: 89.65%] [G loss: 3.288105]
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178 [D loss: 0.337595, acc.: 85.16%] [G loss: 3.546271]
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179 [D loss: 0.549167, acc.: 77.93%] [G loss: 2.627825]
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180 [D loss: 0.438674, acc.: 81.84%] [G loss: 2.844500]
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181 [D loss: 0.509830, acc.: 79.69%] [G loss: 2.674591]
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182 [D loss: 0.445895, acc.: 82.81%] [G loss: 1.932620]
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183 [D loss: 0.346952, acc.: 92.97%] [G loss: 1.805362]
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184 [D loss: 0.337537, acc.: 93.16%] [G loss: 1.787197]
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185 [D loss: 0.313566, acc.: 88.67%] [G loss: 1.874765]
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186 [D loss: 0.315489, acc.: 91.60%] [G loss: 2.499368]
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187 [D loss: 0.268249, acc.: 89.65%] [G loss: 2.652253]
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188 [D loss: 0.369361, acc.: 86.72%] [G loss: 3.095266]
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189 [D loss: 0.384176, acc.: 84.57%] [G loss: 4.070409]
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190 [D loss: 0.400593, acc.: 83.79%] [G loss: 3.879927]
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191 [D loss: 0.624141, acc.: 72.85%] [G loss: 4.112757]
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192 [D loss: 0.499028, acc.: 78.91%] [G loss: 3.717262]
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193 [D loss: 0.390301, acc.: 83.79%] [G loss: 4.225968]
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194 [D loss: 0.304152, acc.: 89.26%] [G loss: 3.869302]
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195 [D loss: 0.331898, acc.: 86.13%] [G loss: 4.052877]
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196 [D loss: 0.328748, acc.: 87.89%] [G loss: 3.348567]
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197 [D loss: 0.378944, acc.: 81.64%] [G loss: 3.258458]
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198 [D loss: 0.321041, acc.: 86.91%] [G loss: 3.059596]
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199 [D loss: 0.480945, acc.: 79.30%] [G loss: 3.036980]
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200 [D loss: 0.473442, acc.: 80.08%] [G loss: 3.163386]
1/1 [==============================] - 0s 21ms/step
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201 [D loss: 0.479763, acc.: 80.86%] [G loss: 2.376914]
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202 [D loss: 0.586705, acc.: 71.09%] [G loss: 2.198665]
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203 [D loss: 0.471133, acc.: 79.10%] [G loss: 2.097260]
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204 [D loss: 0.560700, acc.: 72.66%] [G loss: 1.637668]
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205 [D loss: 0.529139, acc.: 74.61%] [G loss: 1.486691]
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206 [D loss: 0.502872, acc.: 77.54%] [G loss: 1.298907]
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207 [D loss: 0.480757, acc.: 83.59%] [G loss: 1.562411]
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208 [D loss: 0.405131, acc.: 87.11%] [G loss: 1.694680]
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209 [D loss: 0.392656, acc.: 87.89%] [G loss: 1.913391]
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210 [D loss: 0.389998, acc.: 85.16%] [G loss: 2.237621]
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211 [D loss: 0.346431, acc.: 88.28%] [G loss: 2.397421]
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212 [D loss: 0.376349, acc.: 87.11%] [G loss: 2.304745]
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213 [D loss: 0.321837, acc.: 90.04%] [G loss: 2.681232]
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214 [D loss: 0.365421, acc.: 87.30%] [G loss: 2.701190]
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215 [D loss: 0.302893, acc.: 87.11%] [G loss: 2.770096]
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216 [D loss: 0.509826, acc.: 75.00%] [G loss: 2.644682]
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217 [D loss: 0.589309, acc.: 72.07%] [G loss: 3.148025]
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218 [D loss: 0.633279, acc.: 71.48%] [G loss: 2.452772]
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219 [D loss: 0.679334, acc.: 68.95%] [G loss: 2.322552]
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220 [D loss: 0.526040, acc.: 75.78%] [G loss: 2.602677]
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221 [D loss: 0.520167, acc.: 77.93%] [G loss: 2.223679]
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222 [D loss: 0.487628, acc.: 78.32%] [G loss: 2.007645]
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223 [D loss: 0.430684, acc.: 83.20%] [G loss: 2.160080]
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224 [D loss: 0.428952, acc.: 81.45%] [G loss: 2.160167]
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225 [D loss: 0.376080, acc.: 85.16%] [G loss: 2.039006]
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226 [D loss: 0.472726, acc.: 78.91%] [G loss: 1.922434]
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227 [D loss: 0.501812, acc.: 76.95%] [G loss: 1.836257]
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228 [D loss: 0.526047, acc.: 74.22%] [G loss: 1.903438]
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229 [D loss: 0.607420, acc.: 69.53%] [G loss: 2.011587]
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230 [D loss: 0.593024, acc.: 71.88%] [G loss: 2.074078]
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231 [D loss: 0.591630, acc.: 70.70%] [G loss: 2.168937]
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232 [D loss: 0.631741, acc.: 71.48%] [G loss: 2.027570]
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233 [D loss: 0.633813, acc.: 71.09%] [G loss: 1.786075]
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234 [D loss: 0.559384, acc.: 70.90%] [G loss: 1.695749]
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235 [D loss: 0.563900, acc.: 74.22%] [G loss: 1.784502]
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236 [D loss: 0.471583, acc.: 79.10%] [G loss: 1.765290]
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237 [D loss: 0.542168, acc.: 75.98%] [G loss: 1.792944]
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238 [D loss: 0.514172, acc.: 73.63%] [G loss: 1.833735]
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239 [D loss: 0.473087, acc.: 78.12%] [G loss: 1.809988]
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240 [D loss: 0.493181, acc.: 80.47%] [G loss: 1.842882]
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241 [D loss: 0.498503, acc.: 79.30%] [G loss: 1.814955]
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242 [D loss: 0.611616, acc.: 71.29%] [G loss: 1.630410]
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243 [D loss: 0.490713, acc.: 77.15%] [G loss: 1.508246]
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244 [D loss: 0.495588, acc.: 80.27%] [G loss: 1.713462]
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245 [D loss: 0.421576, acc.: 81.64%] [G loss: 1.668822]
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246 [D loss: 0.465578, acc.: 79.88%] [G loss: 1.811150]
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247 [D loss: 0.551301, acc.: 71.29%] [G loss: 2.040694]
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248 [D loss: 0.550338, acc.: 75.59%] [G loss: 1.995653]
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249 [D loss: 0.662972, acc.: 67.77%] [G loss: 2.036047]
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250 [D loss: 0.585959, acc.: 73.44%] [G loss: 1.907704]
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251 [D loss: 0.708675, acc.: 65.23%] [G loss: 1.684427]
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252 [D loss: 0.636283, acc.: 64.26%] [G loss: 1.434435]
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253 [D loss: 0.789360, acc.: 52.54%] [G loss: 1.198905]
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254 [D loss: 0.661502, acc.: 63.67%] [G loss: 1.268208]
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255 [D loss: 0.731961, acc.: 59.96%] [G loss: 1.048874]
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256 [D loss: 0.697543, acc.: 60.35%] [G loss: 1.006690]
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257 [D loss: 0.632912, acc.: 67.77%] [G loss: 1.094547]
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258 [D loss: 0.623149, acc.: 67.19%] [G loss: 1.106807]
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259 [D loss: 0.611300, acc.: 66.02%] [G loss: 1.295069]
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260 [D loss: 0.627548, acc.: 67.77%] [G loss: 1.290866]
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261 [D loss: 0.611211, acc.: 68.16%] [G loss: 1.290471]
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262 [D loss: 0.599817, acc.: 69.53%] [G loss: 1.324596]
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263 [D loss: 0.589071, acc.: 68.55%] [G loss: 1.351267]
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264 [D loss: 0.613901, acc.: 68.16%] [G loss: 1.323531]
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265 [D loss: 0.638618, acc.: 66.02%] [G loss: 1.300565]
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266 [D loss: 0.659486, acc.: 67.19%] [G loss: 1.260335]
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267 [D loss: 0.692241, acc.: 62.11%] [G loss: 1.180939]
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268 [D loss: 0.720433, acc.: 59.18%] [G loss: 1.159669]
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269 [D loss: 0.688728, acc.: 63.09%] [G loss: 1.136716]
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270 [D loss: 0.669318, acc.: 62.50%] [G loss: 1.018227]
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271 [D loss: 0.672752, acc.: 64.65%] [G loss: 1.073664]
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272 [D loss: 0.682584, acc.: 62.50%] [G loss: 1.054143]
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273 [D loss: 0.688970, acc.: 61.91%] [G loss: 1.051100]
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274 [D loss: 0.661072, acc.: 64.06%] [G loss: 0.999836]
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275 [D loss: 0.646328, acc.: 64.26%] [G loss: 1.007950]
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276 [D loss: 0.646737, acc.: 62.70%] [G loss: 1.014238]
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277 [D loss: 0.650931, acc.: 65.04%] [G loss: 1.056698]
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278 [D loss: 0.591324, acc.: 68.36%] [G loss: 0.977893]
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279 [D loss: 0.626506, acc.: 68.36%] [G loss: 1.016227]
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280 [D loss: 0.620633, acc.: 66.80%] [G loss: 0.969792]
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281 [D loss: 0.696695, acc.: 61.91%] [G loss: 0.963024]
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282 [D loss: 0.707638, acc.: 58.20%] [G loss: 1.009537]
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283 [D loss: 0.714315, acc.: 55.66%] [G loss: 0.941377]
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284 [D loss: 0.706952, acc.: 57.23%] [G loss: 0.939840]
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285 [D loss: 0.712666, acc.: 55.08%] [G loss: 0.959676]
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286 [D loss: 0.705384, acc.: 53.71%] [G loss: 0.946151]
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287 [D loss: 0.686911, acc.: 53.12%] [G loss: 0.975931]
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288 [D loss: 0.682523, acc.: 62.11%] [G loss: 0.942221]
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289 [D loss: 0.688841, acc.: 56.05%] [G loss: 0.886662]
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290 [D loss: 0.682702, acc.: 57.42%] [G loss: 0.857190]
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291 [D loss: 0.674836, acc.: 57.81%] [G loss: 0.812897]
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292 [D loss: 0.726765, acc.: 50.98%] [G loss: 0.892662]
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293 [D loss: 0.706601, acc.: 54.88%] [G loss: 0.835747]
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294 [D loss: 0.700259, acc.: 54.30%] [G loss: 0.846151]
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295 [D loss: 0.685481, acc.: 58.98%] [G loss: 0.825536]
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296 [D loss: 0.697615, acc.: 55.86%] [G loss: 0.806999]
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297 [D loss: 0.680784, acc.: 58.79%] [G loss: 0.824735]
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298 [D loss: 0.670169, acc.: 58.79%] [G loss: 0.844352]
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299 [D loss: 0.688861, acc.: 56.64%] [G loss: 0.869602]
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300 [D loss: 0.671230, acc.: 56.84%] [G loss: 0.863957]
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301 [D loss: 0.708128, acc.: 57.03%] [G loss: 0.809808]
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302 [D loss: 0.691516, acc.: 54.69%] [G loss: 0.834827]
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303 [D loss: 0.718778, acc.: 50.59%] [G loss: 0.817927]
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304 [D loss: 0.697981, acc.: 55.27%] [G loss: 0.839296]
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305 [D loss: 0.689929, acc.: 51.76%] [G loss: 0.859773]
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306 [D loss: 0.697246, acc.: 54.69%] [G loss: 0.840649]
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307 [D loss: 0.696365, acc.: 54.88%] [G loss: 0.875846]
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308 [D loss: 0.688309, acc.: 56.84%] [G loss: 0.873105]
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309 [D loss: 0.674340, acc.: 58.01%] [G loss: 0.882293]
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310 [D loss: 0.702193, acc.: 55.86%] [G loss: 0.870741]
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311 [D loss: 0.676778, acc.: 57.23%] [G loss: 0.826789]
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312 [D loss: 0.703710, acc.: 55.27%] [G loss: 0.841529]
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313 [D loss: 0.695982, acc.: 55.08%] [G loss: 0.821942]
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314 [D loss: 0.691668, acc.: 53.91%] [G loss: 0.827565]
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315 [D loss: 0.698817, acc.: 54.49%] [G loss: 0.811368]
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316 [D loss: 0.689876, acc.: 54.88%] [G loss: 0.820527]
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317 [D loss: 0.696786, acc.: 53.91%] [G loss: 0.796683]
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318 [D loss: 0.682261, acc.: 55.66%] [G loss: 0.823257]
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319 [D loss: 0.708268, acc.: 51.37%] [G loss: 0.811570]
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320 [D loss: 0.696988, acc.: 53.32%] [G loss: 0.829379]
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321 [D loss: 0.703614, acc.: 52.34%] [G loss: 0.802589]
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322 [D loss: 0.715187, acc.: 53.71%] [G loss: 0.769852]
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323 [D loss: 0.691288, acc.: 53.52%] [G loss: 0.761721]
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324 [D loss: 0.696446, acc.: 53.32%] [G loss: 0.764234]
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325 [D loss: 0.692459, acc.: 53.71%] [G loss: 0.771591]
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326 [D loss: 0.720172, acc.: 48.63%] [G loss: 0.771627]
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327 [D loss: 0.702865, acc.: 50.78%] [G loss: 0.749461]
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328 [D loss: 0.707382, acc.: 52.73%] [G loss: 0.728344]
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329 [D loss: 0.689412, acc.: 56.45%] [G loss: 0.741576]
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330 [D loss: 0.711627, acc.: 52.54%] [G loss: 0.769825]
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331 [D loss: 0.717112, acc.: 48.05%] [G loss: 0.768975]
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332 [D loss: 0.705985, acc.: 50.98%] [G loss: 0.750054]
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333 [D loss: 0.702690, acc.: 51.17%] [G loss: 0.753451]
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334 [D loss: 0.711563, acc.: 50.20%] [G loss: 0.741675]
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335 [D loss: 0.709685, acc.: 51.37%] [G loss: 0.726158]
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336 [D loss: 0.706914, acc.: 47.27%] [G loss: 0.714350]
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337 [D loss: 0.708005, acc.: 50.20%] [G loss: 0.728663]
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338 [D loss: 0.701345, acc.: 50.59%] [G loss: 0.732124]
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339 [D loss: 0.717523, acc.: 48.24%] [G loss: 0.745763]
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340 [D loss: 0.691051, acc.: 55.27%] [G loss: 0.759569]
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341 [D loss: 0.688702, acc.: 51.95%] [G loss: 0.780048]
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342 [D loss: 0.697905, acc.: 49.61%] [G loss: 0.771512]
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343 [D loss: 0.700986, acc.: 49.41%] [G loss: 0.764394]
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344 [D loss: 0.693366, acc.: 52.93%] [G loss: 0.773339]
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345 [D loss: 0.693579, acc.: 52.15%] [G loss: 0.761646]
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346 [D loss: 0.686948, acc.: 54.69%] [G loss: 0.768348]
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347 [D loss: 0.679552, acc.: 55.08%] [G loss: 0.780009]
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348 [D loss: 0.702297, acc.: 51.56%] [G loss: 0.747994]
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349 [D loss: 0.686077, acc.: 55.47%] [G loss: 0.747811]
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350 [D loss: 0.695919, acc.: 52.34%] [G loss: 0.745891]
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351 [D loss: 0.687226, acc.: 54.30%] [G loss: 0.768910]
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352 [D loss: 0.676998, acc.: 58.01%] [G loss: 0.756196]
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353 [D loss: 0.685966, acc.: 55.66%] [G loss: 0.786673]
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354 [D loss: 0.693400, acc.: 50.59%] [G loss: 0.773187]
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355 [D loss: 0.697208, acc.: 51.17%] [G loss: 0.768586]
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356 [D loss: 0.692477, acc.: 53.91%] [G loss: 0.750816]
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357 [D loss: 0.701540, acc.: 49.80%] [G loss: 0.755458]
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358 [D loss: 0.684696, acc.: 54.10%] [G loss: 0.763117]
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359 [D loss: 0.702083, acc.: 48.63%] [G loss: 0.747269]
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360 [D loss: 0.687441, acc.: 51.56%] [G loss: 0.761809]
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361 [D loss: 0.685914, acc.: 51.95%] [G loss: 0.741118]
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362 [D loss: 0.691503, acc.: 53.71%] [G loss: 0.742659]
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363 [D loss: 0.704275, acc.: 45.70%] [G loss: 0.729524]
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364 [D loss: 0.692442, acc.: 50.39%] [G loss: 0.731447]
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365 [D loss: 0.695964, acc.: 51.76%] [G loss: 0.728837]
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366 [D loss: 0.683907, acc.: 56.25%] [G loss: 0.725034]
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367 [D loss: 0.688903, acc.: 52.73%] [G loss: 0.765800]
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368 [D loss: 0.682014, acc.: 55.08%] [G loss: 0.733030]
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369 [D loss: 0.691367, acc.: 50.59%] [G loss: 0.736347]
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370 [D loss: 0.690664, acc.: 56.64%] [G loss: 0.737797]
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371 [D loss: 0.702279, acc.: 52.15%] [G loss: 0.746529]
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372 [D loss: 0.689727, acc.: 52.34%] [G loss: 0.733978]
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373 [D loss: 0.690973, acc.: 53.52%] [G loss: 0.742113]
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374 [D loss: 0.692756, acc.: 51.76%] [G loss: 0.737016]
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375 [D loss: 0.703758, acc.: 50.39%] [G loss: 0.745545]
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376 [D loss: 0.699388, acc.: 53.32%] [G loss: 0.717413]
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377 [D loss: 0.700496, acc.: 49.80%] [G loss: 0.737974]
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378 [D loss: 0.700239, acc.: 49.02%] [G loss: 0.722337]
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379 [D loss: 0.706162, acc.: 48.63%] [G loss: 0.709808]
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380 [D loss: 0.705108, acc.: 49.22%] [G loss: 0.707035]
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381 [D loss: 0.701005, acc.: 50.59%] [G loss: 0.716904]
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382 [D loss: 0.697880, acc.: 53.91%] [G loss: 0.717116]
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383 [D loss: 0.697440, acc.: 50.98%] [G loss: 0.705332]
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384 [D loss: 0.702849, acc.: 46.09%] [G loss: 0.715165]
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385 [D loss: 0.698147, acc.: 52.73%] [G loss: 0.716182]
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386 [D loss: 0.699472, acc.: 48.44%] [G loss: 0.707212]
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387 [D loss: 0.690042, acc.: 52.93%] [G loss: 0.704516]
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388 [D loss: 0.693493, acc.: 53.71%] [G loss: 0.723783]
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389 [D loss: 0.700230, acc.: 48.24%] [G loss: 0.717158]
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390 [D loss: 0.695762, acc.: 50.59%] [G loss: 0.719903]
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391 [D loss: 0.698173, acc.: 49.02%] [G loss: 0.731742]
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392 [D loss: 0.693076, acc.: 53.71%] [G loss: 0.742570]
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393 [D loss: 0.691005, acc.: 54.88%] [G loss: 0.738764]
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394 [D loss: 0.698470, acc.: 50.98%] [G loss: 0.753327]
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395 [D loss: 0.688451, acc.: 52.73%] [G loss: 0.763170]
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396 [D loss: 0.695728, acc.: 53.52%] [G loss: 0.754317]
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397 [D loss: 0.684374, acc.: 59.38%] [G loss: 0.774465]
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398 [D loss: 0.692651, acc.: 57.81%] [G loss: 0.768444]
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399 [D loss: 0.682958, acc.: 58.79%] [G loss: 0.752162]
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401 [D loss: 0.690168, acc.: 52.54%] [G loss: 0.746877]
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402 [D loss: 0.686265, acc.: 59.18%] [G loss: 0.745868]
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403 [D loss: 0.687428, acc.: 56.25%] [G loss: 0.733722]
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404 [D loss: 0.678687, acc.: 62.11%] [G loss: 0.737094]
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405 [D loss: 0.684865, acc.: 56.84%] [G loss: 0.734700]
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406 [D loss: 0.687683, acc.: 56.05%] [G loss: 0.731334]
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407 [D loss: 0.682374, acc.: 52.93%] [G loss: 0.726966]
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408 [D loss: 0.683856, acc.: 56.84%] [G loss: 0.736028]
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409 [D loss: 0.691249, acc.: 53.71%] [G loss: 0.724732]
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410 [D loss: 0.690420, acc.: 53.71%] [G loss: 0.739687]
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411 [D loss: 0.699268, acc.: 50.20%] [G loss: 0.746780]
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412 [D loss: 0.687291, acc.: 54.88%] [G loss: 0.741334]
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413 [D loss: 0.682404, acc.: 55.47%] [G loss: 0.748510]
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414 [D loss: 0.691302, acc.: 53.91%] [G loss: 0.767310]
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415 [D loss: 0.689453, acc.: 52.54%] [G loss: 0.758264]
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416 [D loss: 0.687823, acc.: 55.86%] [G loss: 0.756604]
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417 [D loss: 0.682726, acc.: 56.84%] [G loss: 0.735430]
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418 [D loss: 0.684732, acc.: 58.79%] [G loss: 0.735437]
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419 [D loss: 0.683668, acc.: 56.84%] [G loss: 0.728220]
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420 [D loss: 0.679490, acc.: 58.59%] [G loss: 0.723237]
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421 [D loss: 0.675424, acc.: 58.01%] [G loss: 0.723446]
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422 [D loss: 0.683358, acc.: 58.98%] [G loss: 0.726201]
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423 [D loss: 0.676027, acc.: 60.55%] [G loss: 0.728313]
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424 [D loss: 0.684856, acc.: 55.47%] [G loss: 0.724930]
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425 [D loss: 0.681475, acc.: 54.88%] [G loss: 0.717465]
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426 [D loss: 0.685721, acc.: 55.66%] [G loss: 0.724736]
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427 [D loss: 0.687266, acc.: 57.03%] [G loss: 0.730656]
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428 [D loss: 0.692119, acc.: 53.32%] [G loss: 0.715334]
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429 [D loss: 0.702073, acc.: 52.73%] [G loss: 0.715217]
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430 [D loss: 0.690580, acc.: 54.88%] [G loss: 0.724878]
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431 [D loss: 0.696547, acc.: 52.34%] [G loss: 0.728370]
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432 [D loss: 0.697292, acc.: 51.37%] [G loss: 0.728844]
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433 [D loss: 0.704296, acc.: 49.02%] [G loss: 0.743245]
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434 [D loss: 0.686617, acc.: 53.91%] [G loss: 0.728513]
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435 [D loss: 0.687078, acc.: 55.86%] [G loss: 0.736962]
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436 [D loss: 0.692241, acc.: 53.91%] [G loss: 0.738756]
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437 [D loss: 0.687630, acc.: 58.59%] [G loss: 0.735675]
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438 [D loss: 0.688614, acc.: 51.95%] [G loss: 0.738956]
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439 [D loss: 0.689205, acc.: 52.73%] [G loss: 0.754294]
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440 [D loss: 0.684894, acc.: 56.05%] [G loss: 0.747733]
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441 [D loss: 0.687677, acc.: 52.93%] [G loss: 0.754321]
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442 [D loss: 0.691215, acc.: 48.05%] [G loss: 0.750024]
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443 [D loss: 0.684593, acc.: 55.08%] [G loss: 0.739466]
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444 [D loss: 0.694315, acc.: 50.98%] [G loss: 0.736122]
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445 [D loss: 0.692176, acc.: 51.37%] [G loss: 0.734344]
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446 [D loss: 0.686155, acc.: 55.08%] [G loss: 0.732459]
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447 [D loss: 0.683164, acc.: 55.86%] [G loss: 0.731122]
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448 [D loss: 0.685020, acc.: 55.66%] [G loss: 0.735020]
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449 [D loss: 0.683040, acc.: 57.03%] [G loss: 0.731225]
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450 [D loss: 0.684108, acc.: 53.71%] [G loss: 0.748466]
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451 [D loss: 0.685361, acc.: 55.08%] [G loss: 0.735803]
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452 [D loss: 0.686198, acc.: 54.69%] [G loss: 0.742667]
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453 [D loss: 0.691790, acc.: 52.73%] [G loss: 0.748587]
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454 [D loss: 0.689719, acc.: 55.27%] [G loss: 0.738733]
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455 [D loss: 0.704165, acc.: 49.22%] [G loss: 0.732387]
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456 [D loss: 0.700349, acc.: 49.22%] [G loss: 0.725615]
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457 [D loss: 0.697150, acc.: 50.78%] [G loss: 0.726725]
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458 [D loss: 0.691269, acc.: 54.30%] [G loss: 0.728474]
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459 [D loss: 0.697375, acc.: 49.22%] [G loss: 0.726311]
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460 [D loss: 0.689851, acc.: 54.30%] [G loss: 0.729955]
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461 [D loss: 0.691466, acc.: 51.95%] [G loss: 0.743398]
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462 [D loss: 0.680763, acc.: 60.16%] [G loss: 0.739276]
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463 [D loss: 0.687460, acc.: 53.32%] [G loss: 0.727523]
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464 [D loss: 0.684575, acc.: 58.98%] [G loss: 0.736298]
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465 [D loss: 0.684660, acc.: 58.20%] [G loss: 0.717319]
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466 [D loss: 0.692246, acc.: 51.95%] [G loss: 0.722073]
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467 [D loss: 0.690541, acc.: 53.32%] [G loss: 0.711117]
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468 [D loss: 0.696575, acc.: 51.56%] [G loss: 0.707695]
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469 [D loss: 0.697286, acc.: 49.61%] [G loss: 0.713756]
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470 [D loss: 0.689938, acc.: 54.30%] [G loss: 0.708605]
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471 [D loss: 0.696252, acc.: 50.00%] [G loss: 0.707699]
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472 [D loss: 0.698931, acc.: 53.12%] [G loss: 0.714724]
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473 [D loss: 0.691856, acc.: 56.25%] [G loss: 0.720681]
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474 [D loss: 0.691353, acc.: 55.27%] [G loss: 0.726617]
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475 [D loss: 0.688427, acc.: 56.64%] [G loss: 0.731849]
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476 [D loss: 0.692199, acc.: 54.10%] [G loss: 0.726722]
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477 [D loss: 0.678046, acc.: 58.98%] [G loss: 0.741358]
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478 [D loss: 0.690296, acc.: 55.66%] [G loss: 0.717872]
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479 [D loss: 0.690260, acc.: 54.88%] [G loss: 0.717583]
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480 [D loss: 0.699075, acc.: 48.63%] [G loss: 0.713151]
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481 [D loss: 0.704327, acc.: 49.02%] [G loss: 0.709499]
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482 [D loss: 0.692842, acc.: 53.32%] [G loss: 0.716506]
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483 [D loss: 0.696325, acc.: 50.98%] [G loss: 0.727000]
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484 [D loss: 0.691625, acc.: 51.76%] [G loss: 0.720864]
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485 [D loss: 0.695481, acc.: 52.15%] [G loss: 0.736438]
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486 [D loss: 0.692621, acc.: 49.80%] [G loss: 0.743426]
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487 [D loss: 0.686035, acc.: 61.13%] [G loss: 0.759974]
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488 [D loss: 0.696949, acc.: 53.12%] [G loss: 0.754716]
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489 [D loss: 0.695546, acc.: 54.30%] [G loss: 0.760010]
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490 [D loss: 0.688183, acc.: 54.69%] [G loss: 0.751119]
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491 [D loss: 0.690921, acc.: 53.91%] [G loss: 0.739242]
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492 [D loss: 0.687052, acc.: 56.84%] [G loss: 0.737488]
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493 [D loss: 0.688466, acc.: 56.45%] [G loss: 0.721570]
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494 [D loss: 0.691567, acc.: 54.88%] [G loss: 0.717608]
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495 [D loss: 0.689845, acc.: 53.71%] [G loss: 0.703165]
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496 [D loss: 0.692960, acc.: 50.98%] [G loss: 0.714502]
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497 [D loss: 0.696185, acc.: 49.61%] [G loss: 0.698315]
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498 [D loss: 0.697564, acc.: 50.78%] [G loss: 0.711644]
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499 [D loss: 0.695192, acc.: 52.93%] [G loss: 0.703179]
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500 [D loss: 0.688185, acc.: 56.25%] [G loss: 0.714800]
1/1 [==============================] - 0s 21ms/step
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501 [D loss: 0.685537, acc.: 54.69%] [G loss: 0.725694]
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502 [D loss: 0.691244, acc.: 54.88%] [G loss: 0.728532]
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503 [D loss: 0.690970, acc.: 54.88%] [G loss: 0.735183]
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504 [D loss: 0.695551, acc.: 50.20%] [G loss: 0.731615]
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505 [D loss: 0.689282, acc.: 53.71%] [G loss: 0.729619]
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506 [D loss: 0.695264, acc.: 52.15%] [G loss: 0.728041]
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507 [D loss: 0.692420, acc.: 54.88%] [G loss: 0.733603]
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508 [D loss: 0.691056, acc.: 51.95%] [G loss: 0.730640]
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509 [D loss: 0.691512, acc.: 56.25%] [G loss: 0.728709]
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510 [D loss: 0.688573, acc.: 54.10%] [G loss: 0.721006]
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511 [D loss: 0.691719, acc.: 55.86%] [G loss: 0.725157]
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512 [D loss: 0.687460, acc.: 56.05%] [G loss: 0.719497]
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513 [D loss: 0.691445, acc.: 51.56%] [G loss: 0.714695]
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514 [D loss: 0.698030, acc.: 48.24%] [G loss: 0.703878]
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515 [D loss: 0.694425, acc.: 50.78%] [G loss: 0.706997]
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516 [D loss: 0.691447, acc.: 55.66%] [G loss: 0.708416]
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517 [D loss: 0.694107, acc.: 50.98%] [G loss: 0.717758]
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518 [D loss: 0.691630, acc.: 53.91%] [G loss: 0.736913]
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519 [D loss: 0.691969, acc.: 54.30%] [G loss: 0.752409]
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520 [D loss: 0.695597, acc.: 53.12%] [G loss: 0.742339]
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521 [D loss: 0.695114, acc.: 49.80%] [G loss: 0.749888]
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522 [D loss: 0.698248, acc.: 50.20%] [G loss: 0.751996]
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523 [D loss: 0.696690, acc.: 52.93%] [G loss: 0.748296]
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524 [D loss: 0.695574, acc.: 51.17%] [G loss: 0.741248]
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525 [D loss: 0.694532, acc.: 52.93%] [G loss: 0.732486]
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526 [D loss: 0.691576, acc.: 55.27%] [G loss: 0.735764]
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527 [D loss: 0.692704, acc.: 49.61%] [G loss: 0.735577]
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528 [D loss: 0.695299, acc.: 51.76%] [G loss: 0.720098]
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529 [D loss: 0.693543, acc.: 52.73%] [G loss: 0.721887]
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530 [D loss: 0.694069, acc.: 52.73%] [G loss: 0.730336]
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531 [D loss: 0.691467, acc.: 52.93%] [G loss: 0.731449]
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532 [D loss: 0.691358, acc.: 53.32%] [G loss: 0.719810]
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533 [D loss: 0.691665, acc.: 56.25%] [G loss: 0.713802]
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534 [D loss: 0.690212, acc.: 55.66%] [G loss: 0.718466]
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535 [D loss: 0.691471, acc.: 51.56%] [G loss: 0.710870]
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536 [D loss: 0.689247, acc.: 54.49%] [G loss: 0.699854]
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537 [D loss: 0.686970, acc.: 57.23%] [G loss: 0.704168]
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538 [D loss: 0.695537, acc.: 50.78%] [G loss: 0.683801]
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539 [D loss: 0.693541, acc.: 53.32%] [G loss: 0.683290]
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540 [D loss: 0.694929, acc.: 51.17%] [G loss: 0.692257]
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541 [D loss: 0.696504, acc.: 51.56%] [G loss: 0.692273]
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542 [D loss: 0.698188, acc.: 52.54%] [G loss: 0.699684]
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543 [D loss: 0.692327, acc.: 53.52%] [G loss: 0.705145]
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544 [D loss: 0.699937, acc.: 51.76%] [G loss: 0.719842]
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545 [D loss: 0.698293, acc.: 48.63%] [G loss: 0.735910]
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546 [D loss: 0.689614, acc.: 55.66%] [G loss: 0.748794]
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547 [D loss: 0.694249, acc.: 54.10%] [G loss: 0.737115]
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548 [D loss: 0.693107, acc.: 50.98%] [G loss: 0.732930]
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549 [D loss: 0.697571, acc.: 48.44%] [G loss: 0.732327]
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550 [D loss: 0.693923, acc.: 51.56%] [G loss: 0.726946]
1/1 [==============================] - 0s 19ms/step
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551 [D loss: 0.697957, acc.: 48.83%] [G loss: 0.724587]
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552 [D loss: 0.702985, acc.: 45.90%] [G loss: 0.723656]
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553 [D loss: 0.686709, acc.: 54.69%] [G loss: 0.723193]
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554 [D loss: 0.690648, acc.: 52.93%] [G loss: 0.726889]
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555 [D loss: 0.691813, acc.: 52.73%] [G loss: 0.728107]
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556 [D loss: 0.688130, acc.: 51.95%] [G loss: 0.715607]
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557 [D loss: 0.695663, acc.: 53.91%] [G loss: 0.717986]
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558 [D loss: 0.699664, acc.: 45.31%] [G loss: 0.719173]
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559 [D loss: 0.691826, acc.: 51.56%] [G loss: 0.708312]
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560 [D loss: 0.693846, acc.: 49.80%] [G loss: 0.713265]
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561 [D loss: 0.689209, acc.: 54.88%] [G loss: 0.699543]
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562 [D loss: 0.693555, acc.: 52.34%] [G loss: 0.695699]
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563 [D loss: 0.690660, acc.: 52.93%] [G loss: 0.693953]
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564 [D loss: 0.692975, acc.: 50.78%] [G loss: 0.689655]
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565 [D loss: 0.694958, acc.: 51.95%] [G loss: 0.680564]
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566 [D loss: 0.692152, acc.: 53.12%] [G loss: 0.680537]
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567 [D loss: 0.688416, acc.: 52.73%] [G loss: 0.683619]
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568 [D loss: 0.694412, acc.: 51.17%] [G loss: 0.687589]
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569 [D loss: 0.700320, acc.: 49.80%] [G loss: 0.702197]
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570 [D loss: 0.698750, acc.: 47.85%] [G loss: 0.709945]
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571 [D loss: 0.692120, acc.: 55.08%] [G loss: 0.729937]
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572 [D loss: 0.690105, acc.: 54.88%] [G loss: 0.750375]
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573 [D loss: 0.689262, acc.: 53.71%] [G loss: 0.757472]
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574 [D loss: 0.696164, acc.: 50.78%] [G loss: 0.752123]
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575 [D loss: 0.698577, acc.: 48.83%] [G loss: 0.745827]
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576 [D loss: 0.696699, acc.: 50.98%] [G loss: 0.738397]
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577 [D loss: 0.692166, acc.: 53.52%] [G loss: 0.729796]
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578 [D loss: 0.693984, acc.: 54.69%] [G loss: 0.730772]
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579 [D loss: 0.691342, acc.: 54.88%] [G loss: 0.731786]
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580 [D loss: 0.687220, acc.: 56.45%] [G loss: 0.729054]
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581 [D loss: 0.692320, acc.: 53.71%] [G loss: 0.721616]
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582 [D loss: 0.691697, acc.: 51.95%] [G loss: 0.720808]
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583 [D loss: 0.693283, acc.: 53.12%] [G loss: 0.712961]
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584 [D loss: 0.695294, acc.: 50.78%] [G loss: 0.704252]
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585 [D loss: 0.686554, acc.: 56.45%] [G loss: 0.714965]
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586 [D loss: 0.686522, acc.: 53.71%] [G loss: 0.720916]
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587 [D loss: 0.688404, acc.: 57.42%] [G loss: 0.725510]
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588 [D loss: 0.687112, acc.: 55.27%] [G loss: 0.715972]
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589 [D loss: 0.686609, acc.: 57.81%] [G loss: 0.722053]
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590 [D loss: 0.688481, acc.: 54.30%] [G loss: 0.715380]
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591 [D loss: 0.686614, acc.: 55.66%] [G loss: 0.720543]
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592 [D loss: 0.686209, acc.: 54.49%] [G loss: 0.717195]
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593 [D loss: 0.689818, acc.: 54.10%] [G loss: 0.720319]
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594 [D loss: 0.688132, acc.: 53.32%] [G loss: 0.725564]
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595 [D loss: 0.692733, acc.: 51.56%] [G loss: 0.722627]
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596 [D loss: 0.691209, acc.: 54.10%] [G loss: 0.722308]
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597 [D loss: 0.696327, acc.: 50.00%] [G loss: 0.718535]
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598 [D loss: 0.690549, acc.: 55.47%] [G loss: 0.718542]
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599 [D loss: 0.696104, acc.: 49.22%] [G loss: 0.722876]
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600 [D loss: 0.693182, acc.: 51.37%] [G loss: 0.720385]
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601 [D loss: 0.696017, acc.: 51.17%] [G loss: 0.720375]
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602 [D loss: 0.692781, acc.: 56.05%] [G loss: 0.721463]
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603 [D loss: 0.689529, acc.: 54.49%] [G loss: 0.728434]
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604 [D loss: 0.696650, acc.: 50.20%] [G loss: 0.728403]
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605 [D loss: 0.690138, acc.: 55.66%] [G loss: 0.722199]
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606 [D loss: 0.691949, acc.: 53.71%] [G loss: 0.721361]
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607 [D loss: 0.688583, acc.: 56.05%] [G loss: 0.718868]
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608 [D loss: 0.695392, acc.: 48.44%] [G loss: 0.706724]
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609 [D loss: 0.691476, acc.: 50.78%] [G loss: 0.710101]
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610 [D loss: 0.693589, acc.: 53.12%] [G loss: 0.716029]
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611 [D loss: 0.693659, acc.: 52.34%] [G loss: 0.716572]
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612 [D loss: 0.690366, acc.: 54.49%] [G loss: 0.721686]
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613 [D loss: 0.691267, acc.: 56.64%] [G loss: 0.722327]
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614 [D loss: 0.686856, acc.: 56.45%] [G loss: 0.724437]
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615 [D loss: 0.690383, acc.: 56.25%] [G loss: 0.721979]
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616 [D loss: 0.689567, acc.: 54.30%] [G loss: 0.717061]
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617 [D loss: 0.686359, acc.: 56.84%] [G loss: 0.721065]
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618 [D loss: 0.689869, acc.: 54.69%] [G loss: 0.710774]
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619 [D loss: 0.687780, acc.: 55.86%] [G loss: 0.708072]
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620 [D loss: 0.688994, acc.: 55.47%] [G loss: 0.708969]
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621 [D loss: 0.695161, acc.: 51.17%] [G loss: 0.701672]
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622 [D loss: 0.691936, acc.: 52.34%] [G loss: 0.699744]
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623 [D loss: 0.690258, acc.: 52.93%] [G loss: 0.691987]
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624 [D loss: 0.690489, acc.: 50.20%] [G loss: 0.684927]
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625 [D loss: 0.688332, acc.: 55.66%] [G loss: 0.689084]
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626 [D loss: 0.692344, acc.: 51.56%] [G loss: 0.685189]
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627 [D loss: 0.693239, acc.: 50.98%] [G loss: 0.701560]
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628 [D loss: 0.695291, acc.: 49.02%] [G loss: 0.700836]
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629 [D loss: 0.691362, acc.: 51.76%] [G loss: 0.715720]
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630 [D loss: 0.693473, acc.: 52.54%] [G loss: 0.718756]
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631 [D loss: 0.692655, acc.: 53.32%] [G loss: 0.725552]
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632 [D loss: 0.690970, acc.: 54.88%] [G loss: 0.735337]
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633 [D loss: 0.691157, acc.: 51.37%] [G loss: 0.734885]
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634 [D loss: 0.694370, acc.: 52.34%] [G loss: 0.732207]
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635 [D loss: 0.693371, acc.: 53.91%] [G loss: 0.732294]
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636 [D loss: 0.695815, acc.: 52.93%] [G loss: 0.729341]
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637 [D loss: 0.692402, acc.: 52.54%] [G loss: 0.727074]
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638 [D loss: 0.693833, acc.: 50.00%] [G loss: 0.728853]
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639 [D loss: 0.694880, acc.: 53.12%] [G loss: 0.726748]
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640 [D loss: 0.690055, acc.: 55.86%] [G loss: 0.725521]
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641 [D loss: 0.687431, acc.: 55.27%] [G loss: 0.728540]
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642 [D loss: 0.690655, acc.: 53.32%] [G loss: 0.728461]
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643 [D loss: 0.687231, acc.: 57.81%] [G loss: 0.725794]
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644 [D loss: 0.689110, acc.: 54.88%] [G loss: 0.715718]
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645 [D loss: 0.688218, acc.: 55.27%] [G loss: 0.717761]
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646 [D loss: 0.692368, acc.: 53.32%] [G loss: 0.701491]
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647 [D loss: 0.693638, acc.: 52.34%] [G loss: 0.701979]
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648 [D loss: 0.692837, acc.: 53.12%] [G loss: 0.693633]
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649 [D loss: 0.691101, acc.: 53.12%] [G loss: 0.696427]
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650 [D loss: 0.694726, acc.: 51.95%] [G loss: 0.696900]
1/1 [==============================] - 0s 20ms/step
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651 [D loss: 0.690352, acc.: 53.52%] [G loss: 0.702850]
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652 [D loss: 0.694639, acc.: 50.20%] [G loss: 0.704045]
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653 [D loss: 0.692875, acc.: 52.54%] [G loss: 0.711381]
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654 [D loss: 0.686299, acc.: 55.86%] [G loss: 0.719490]
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655 [D loss: 0.687442, acc.: 56.05%] [G loss: 0.724494]
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656 [D loss: 0.682451, acc.: 59.38%] [G loss: 0.740024]
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657 [D loss: 0.686198, acc.: 54.88%] [G loss: 0.741361]
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658 [D loss: 0.689654, acc.: 55.08%] [G loss: 0.741678]
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659 [D loss: 0.690233, acc.: 55.86%] [G loss: 0.726840]
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660 [D loss: 0.695661, acc.: 50.39%] [G loss: 0.723031]
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661 [D loss: 0.692146, acc.: 57.03%] [G loss: 0.710011]
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662 [D loss: 0.693711, acc.: 53.91%] [G loss: 0.708441]
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663 [D loss: 0.689526, acc.: 56.25%] [G loss: 0.704356]
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664 [D loss: 0.693029, acc.: 50.98%] [G loss: 0.704520]
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665 [D loss: 0.689480, acc.: 58.01%] [G loss: 0.699870]
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666 [D loss: 0.693100, acc.: 53.12%] [G loss: 0.696630]
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667 [D loss: 0.696517, acc.: 51.17%] [G loss: 0.689347]
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668 [D loss: 0.689773, acc.: 54.69%] [G loss: 0.698882]
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669 [D loss: 0.693697, acc.: 50.39%] [G loss: 0.697878]
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670 [D loss: 0.689742, acc.: 56.25%] [G loss: 0.701560]
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671 [D loss: 0.690087, acc.: 52.54%] [G loss: 0.711598]
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672 [D loss: 0.691130, acc.: 50.78%] [G loss: 0.712524]
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673 [D loss: 0.688841, acc.: 52.54%] [G loss: 0.721661]
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674 [D loss: 0.689264, acc.: 53.91%] [G loss: 0.730452]
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675 [D loss: 0.690344, acc.: 52.34%] [G loss: 0.728896]
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676 [D loss: 0.687348, acc.: 56.25%] [G loss: 0.731106]
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677 [D loss: 0.689327, acc.: 53.71%] [G loss: 0.730015]
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678 [D loss: 0.693454, acc.: 51.95%] [G loss: 0.731586]
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679 [D loss: 0.689216, acc.: 55.08%] [G loss: 0.724803]
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680 [D loss: 0.688913, acc.: 55.47%] [G loss: 0.726379]
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681 [D loss: 0.691560, acc.: 52.93%] [G loss: 0.724203]
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682 [D loss: 0.689682, acc.: 52.34%] [G loss: 0.723462]
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683 [D loss: 0.687393, acc.: 55.86%] [G loss: 0.718660]
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684 [D loss: 0.686757, acc.: 55.47%] [G loss: 0.713651]
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685 [D loss: 0.689545, acc.: 54.88%] [G loss: 0.706293]
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686 [D loss: 0.686936, acc.: 53.91%] [G loss: 0.706227]
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687 [D loss: 0.692244, acc.: 52.34%] [G loss: 0.699342]
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688 [D loss: 0.692746, acc.: 52.73%] [G loss: 0.699170]
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689 [D loss: 0.691463, acc.: 52.15%] [G loss: 0.698246]
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690 [D loss: 0.691146, acc.: 55.08%] [G loss: 0.708541]
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691 [D loss: 0.688194, acc.: 55.66%] [G loss: 0.712766]
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692 [D loss: 0.689208, acc.: 56.25%] [G loss: 0.710249]
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693 [D loss: 0.690898, acc.: 55.27%] [G loss: 0.722836]
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694 [D loss: 0.686200, acc.: 58.79%] [G loss: 0.721647]
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695 [D loss: 0.685912, acc.: 58.98%] [G loss: 0.723370]
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696 [D loss: 0.689105, acc.: 54.69%] [G loss: 0.723422]
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697 [D loss: 0.691561, acc.: 54.88%] [G loss: 0.723787]
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698 [D loss: 0.687983, acc.: 56.64%] [G loss: 0.719474]
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699 [D loss: 0.689614, acc.: 57.23%] [G loss: 0.720550]
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700 [D loss: 0.691603, acc.: 54.30%] [G loss: 0.715984]
1/1 [==============================] - 0s 20ms/step
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701 [D loss: 0.686775, acc.: 56.25%] [G loss: 0.711941]
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702 [D loss: 0.685158, acc.: 59.38%] [G loss: 0.708851]
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703 [D loss: 0.686466, acc.: 56.64%] [G loss: 0.708962]
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704 [D loss: 0.683412, acc.: 59.77%] [G loss: 0.704202]
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705 [D loss: 0.682508, acc.: 57.81%] [G loss: 0.694890]
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706 [D loss: 0.685529, acc.: 54.49%] [G loss: 0.692787]
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707 [D loss: 0.685243, acc.: 56.25%] [G loss: 0.687176]
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708 [D loss: 0.692314, acc.: 52.54%] [G loss: 0.684556]
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709 [D loss: 0.692149, acc.: 53.12%] [G loss: 0.698903]
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710 [D loss: 0.694912, acc.: 50.00%] [G loss: 0.702557]
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711 [D loss: 0.690683, acc.: 53.71%] [G loss: 0.707463]
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712 [D loss: 0.693734, acc.: 51.56%] [G loss: 0.718440]
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713 [D loss: 0.691206, acc.: 54.49%] [G loss: 0.723461]
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714 [D loss: 0.691363, acc.: 51.95%] [G loss: 0.745073]
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715 [D loss: 0.694596, acc.: 52.93%] [G loss: 0.744721]
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716 [D loss: 0.695142, acc.: 52.15%] [G loss: 0.739552]
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717 [D loss: 0.693151, acc.: 53.52%] [G loss: 0.728738]
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718 [D loss: 0.692378, acc.: 52.93%] [G loss: 0.729609]
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719 [D loss: 0.693063, acc.: 54.49%] [G loss: 0.724093]
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720 [D loss: 0.686549, acc.: 58.40%] [G loss: 0.727417]
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721 [D loss: 0.680846, acc.: 60.55%] [G loss: 0.724465]
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722 [D loss: 0.682581, acc.: 58.59%] [G loss: 0.735751]
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723 [D loss: 0.686003, acc.: 54.10%] [G loss: 0.723429]
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724 [D loss: 0.689939, acc.: 51.17%] [G loss: 0.717025]
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725 [D loss: 0.692708, acc.: 49.80%] [G loss: 0.699951]
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726 [D loss: 0.695139, acc.: 49.02%] [G loss: 0.694947]
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727 [D loss: 0.694066, acc.: 52.93%] [G loss: 0.708728]
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728 [D loss: 0.691324, acc.: 54.49%] [G loss: 0.722756]
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729 [D loss: 0.681845, acc.: 58.79%] [G loss: 0.736780]
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730 [D loss: 0.682992, acc.: 62.11%] [G loss: 0.747715]
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731 [D loss: 0.688529, acc.: 54.88%] [G loss: 0.756365]
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732 [D loss: 0.692337, acc.: 50.78%] [G loss: 0.739431]
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733 [D loss: 0.702312, acc.: 47.07%] [G loss: 0.723629]
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734 [D loss: 0.696344, acc.: 50.98%] [G loss: 0.721010]
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735 [D loss: 0.689283, acc.: 56.45%] [G loss: 0.730697]
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736 [D loss: 0.689002, acc.: 55.08%] [G loss: 0.739381]
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737 [D loss: 0.689565, acc.: 52.34%] [G loss: 0.730449]
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738 [D loss: 0.685377, acc.: 54.30%] [G loss: 0.725374]
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739 [D loss: 0.685819, acc.: 54.10%] [G loss: 0.708826]
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740 [D loss: 0.694295, acc.: 50.00%] [G loss: 0.704149]
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741 [D loss: 0.686336, acc.: 53.71%] [G loss: 0.707160]
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742 [D loss: 0.685809, acc.: 54.30%] [G loss: 0.706282]
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743 [D loss: 0.689158, acc.: 51.17%] [G loss: 0.707642]
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744 [D loss: 0.688500, acc.: 55.66%] [G loss: 0.716368]
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745 [D loss: 0.686160, acc.: 55.08%] [G loss: 0.711497]
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746 [D loss: 0.692189, acc.: 53.32%] [G loss: 0.706886]
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747 [D loss: 0.690361, acc.: 54.49%] [G loss: 0.707254]
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748 [D loss: 0.694363, acc.: 50.78%] [G loss: 0.700611]
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749 [D loss: 0.692375, acc.: 51.17%] [G loss: 0.709198]
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750 [D loss: 0.690034, acc.: 53.32%] [G loss: 0.709501]
1/1 [==============================] - 0s 20ms/step
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751 [D loss: 0.693842, acc.: 49.41%] [G loss: 0.708500]
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752 [D loss: 0.688949, acc.: 55.08%] [G loss: 0.712009]
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753 [D loss: 0.689290, acc.: 53.32%] [G loss: 0.720170]
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754 [D loss: 0.692845, acc.: 52.93%] [G loss: 0.718273]
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755 [D loss: 0.692365, acc.: 54.30%] [G loss: 0.717142]
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756 [D loss: 0.689204, acc.: 54.30%] [G loss: 0.719510]
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757 [D loss: 0.686013, acc.: 56.45%] [G loss: 0.722650]
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758 [D loss: 0.688545, acc.: 57.42%] [G loss: 0.727245]
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759 [D loss: 0.692315, acc.: 49.41%] [G loss: 0.725936]
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760 [D loss: 0.688548, acc.: 47.85%] [G loss: 0.735319]
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761 [D loss: 0.686343, acc.: 55.47%] [G loss: 0.745543]
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762 [D loss: 0.678497, acc.: 59.38%] [G loss: 0.744316]
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763 [D loss: 0.679548, acc.: 57.81%] [G loss: 0.748762]
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764 [D loss: 0.687689, acc.: 53.12%] [G loss: 0.739545]
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765 [D loss: 0.692737, acc.: 49.02%] [G loss: 0.726715]
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766 [D loss: 0.692287, acc.: 53.91%] [G loss: 0.721621]
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767 [D loss: 0.689357, acc.: 58.01%] [G loss: 0.726793]
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768 [D loss: 0.699683, acc.: 46.68%] [G loss: 0.729868]
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769 [D loss: 0.691978, acc.: 52.54%] [G loss: 0.728999]
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770 [D loss: 0.690569, acc.: 53.32%] [G loss: 0.717218]
8/8 [==============================] - 0s 4ms/step
771 [D loss: 0.687745, acc.: 54.88%] [G loss: 0.719569]
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772 [D loss: 0.685809, acc.: 56.64%] [G loss: 0.716520]
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773 [D loss: 0.683099, acc.: 56.05%] [G loss: 0.701870]
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774 [D loss: 0.687262, acc.: 53.91%] [G loss: 0.701156]
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775 [D loss: 0.688615, acc.: 52.73%] [G loss: 0.697109]
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776 [D loss: 0.690105, acc.: 53.12%] [G loss: 0.691922]
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777 [D loss: 0.691748, acc.: 53.71%] [G loss: 0.686463]
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778 [D loss: 0.692003, acc.: 51.95%] [G loss: 0.683782]
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779 [D loss: 0.688501, acc.: 52.34%] [G loss: 0.700794]
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780 [D loss: 0.687935, acc.: 56.84%] [G loss: 0.709656]
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781 [D loss: 0.682084, acc.: 57.42%] [G loss: 0.724873]
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782 [D loss: 0.688594, acc.: 54.30%] [G loss: 0.730225]
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783 [D loss: 0.685738, acc.: 53.91%] [G loss: 0.732142]
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784 [D loss: 0.688574, acc.: 53.91%] [G loss: 0.744760]
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785 [D loss: 0.690646, acc.: 53.91%] [G loss: 0.744404]
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786 [D loss: 0.691070, acc.: 50.20%] [G loss: 0.738659]
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787 [D loss: 0.692610, acc.: 51.17%] [G loss: 0.738809]
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788 [D loss: 0.698494, acc.: 46.68%] [G loss: 0.729146]
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789 [D loss: 0.687896, acc.: 56.64%] [G loss: 0.731374]
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790 [D loss: 0.685474, acc.: 58.59%] [G loss: 0.737288]
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791 [D loss: 0.671596, acc.: 67.97%] [G loss: 0.746509]
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792 [D loss: 0.679320, acc.: 58.40%] [G loss: 0.740467]
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793 [D loss: 0.682966, acc.: 57.42%] [G loss: 0.704428]
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794 [D loss: 0.695597, acc.: 50.59%] [G loss: 0.696396]
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795 [D loss: 0.694166, acc.: 49.80%] [G loss: 0.670020]
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796 [D loss: 0.699774, acc.: 49.61%] [G loss: 0.671778]
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797 [D loss: 0.696087, acc.: 49.02%] [G loss: 0.690577]
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798 [D loss: 0.689707, acc.: 55.08%] [G loss: 0.705516]
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799 [D loss: 0.688159, acc.: 58.01%] [G loss: 0.733427]
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800 [D loss: 0.681374, acc.: 58.59%] [G loss: 0.761661]
1/1 [==============================] - 0s 22ms/step
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801 [D loss: 0.680481, acc.: 59.18%] [G loss: 0.789748]
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802 [D loss: 0.676379, acc.: 59.38%] [G loss: 0.800367]
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803 [D loss: 0.689288, acc.: 55.08%] [G loss: 0.785235]
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804 [D loss: 0.692075, acc.: 54.30%] [G loss: 0.761170]
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805 [D loss: 0.708824, acc.: 46.09%] [G loss: 0.722625]
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806 [D loss: 0.698192, acc.: 49.80%] [G loss: 0.725352]
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807 [D loss: 0.689322, acc.: 58.59%] [G loss: 0.744376]
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808 [D loss: 0.678730, acc.: 62.89%] [G loss: 0.759143]
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809 [D loss: 0.675813, acc.: 64.26%] [G loss: 0.750393]
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810 [D loss: 0.686103, acc.: 55.47%] [G loss: 0.728293]
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811 [D loss: 0.687656, acc.: 56.45%] [G loss: 0.690954]
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812 [D loss: 0.689462, acc.: 51.95%] [G loss: 0.686045]
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813 [D loss: 0.691442, acc.: 51.56%] [G loss: 0.679905]
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814 [D loss: 0.697229, acc.: 49.80%] [G loss: 0.659043]
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815 [D loss: 0.700444, acc.: 46.68%] [G loss: 0.670827]
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816 [D loss: 0.696141, acc.: 48.44%] [G loss: 0.670602]
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817 [D loss: 0.693759, acc.: 50.39%] [G loss: 0.692867]
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818 [D loss: 0.693004, acc.: 50.98%] [G loss: 0.706521]
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819 [D loss: 0.686138, acc.: 54.30%] [G loss: 0.745104]
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820 [D loss: 0.680012, acc.: 62.70%] [G loss: 0.763697]
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821 [D loss: 0.677019, acc.: 59.77%] [G loss: 0.782775]
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822 [D loss: 0.674260, acc.: 58.01%] [G loss: 0.805767]
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823 [D loss: 0.682457, acc.: 57.62%] [G loss: 0.797087]
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824 [D loss: 0.691672, acc.: 50.78%] [G loss: 0.771941]
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825 [D loss: 0.714130, acc.: 42.38%] [G loss: 0.725986]
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826 [D loss: 0.697761, acc.: 50.98%] [G loss: 0.728626]
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827 [D loss: 0.683814, acc.: 59.38%] [G loss: 0.758776]
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828 [D loss: 0.675288, acc.: 63.48%] [G loss: 0.785176]
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829 [D loss: 0.679111, acc.: 57.03%] [G loss: 0.759656]
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830 [D loss: 0.691409, acc.: 51.37%] [G loss: 0.724905]
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831 [D loss: 0.691061, acc.: 51.95%] [G loss: 0.709572]
8/8 [==============================] - 0s 4ms/step
832 [D loss: 0.685244, acc.: 55.47%] [G loss: 0.700680]
8/8 [==============================] - 0s 4ms/step
833 [D loss: 0.680219, acc.: 57.42%] [G loss: 0.705462]
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834 [D loss: 0.687861, acc.: 53.91%] [G loss: 0.702840]
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835 [D loss: 0.685925, acc.: 52.54%] [G loss: 0.687581]
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836 [D loss: 0.690652, acc.: 53.71%] [G loss: 0.684633]
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837 [D loss: 0.694053, acc.: 51.37%] [G loss: 0.687303]
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838 [D loss: 0.686712, acc.: 56.05%] [G loss: 0.714218]
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839 [D loss: 0.681160, acc.: 56.64%] [G loss: 0.722965]
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840 [D loss: 0.687426, acc.: 52.93%] [G loss: 0.746286]
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841 [D loss: 0.695474, acc.: 52.93%] [G loss: 0.752654]
8/8 [==============================] - 0s 4ms/step
842 [D loss: 0.678914, acc.: 61.72%] [G loss: 0.766419]
8/8 [==============================] - 0s 4ms/step
843 [D loss: 0.674870, acc.: 59.77%] [G loss: 0.813313]
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844 [D loss: 0.673240, acc.: 59.96%] [G loss: 0.825475]
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845 [D loss: 0.687042, acc.: 54.88%] [G loss: 0.782564]
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846 [D loss: 0.711994, acc.: 49.41%] [G loss: 0.723833]
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847 [D loss: 0.711295, acc.: 44.73%] [G loss: 0.721259]
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848 [D loss: 0.682847, acc.: 63.67%] [G loss: 0.752916]
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849 [D loss: 0.667836, acc.: 68.55%] [G loss: 0.799084]
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850 [D loss: 0.662327, acc.: 66.02%] [G loss: 0.809026]
1/1 [==============================] - 0s 20ms/step
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851 [D loss: 0.672630, acc.: 63.48%] [G loss: 0.787832]
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852 [D loss: 0.686294, acc.: 55.08%] [G loss: 0.756840]
8/8 [==============================] - 0s 4ms/step
853 [D loss: 0.688508, acc.: 51.17%] [G loss: 0.725507]
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854 [D loss: 0.689937, acc.: 54.30%] [G loss: 0.707319]
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855 [D loss: 0.697475, acc.: 51.95%] [G loss: 0.707621]
8/8 [==============================] - 0s 4ms/step
856 [D loss: 0.696680, acc.: 51.95%] [G loss: 0.696412]
8/8 [==============================] - 0s 4ms/step
857 [D loss: 0.700441, acc.: 47.46%] [G loss: 0.689470]
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858 [D loss: 0.701587, acc.: 48.24%] [G loss: 0.683205]
8/8 [==============================] - 0s 4ms/step
859 [D loss: 0.690670, acc.: 51.56%] [G loss: 0.695115]
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860 [D loss: 0.695468, acc.: 52.15%] [G loss: 0.722105]
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861 [D loss: 0.694703, acc.: 49.02%] [G loss: 0.752248]
8/8 [==============================] - 0s 4ms/step
862 [D loss: 0.681395, acc.: 56.25%] [G loss: 0.774605]
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863 [D loss: 0.681045, acc.: 60.94%] [G loss: 0.808569]
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864 [D loss: 0.668399, acc.: 58.40%] [G loss: 0.835279]
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865 [D loss: 0.660413, acc.: 64.26%] [G loss: 0.872391]
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866 [D loss: 0.666931, acc.: 61.91%] [G loss: 0.839920]
8/8 [==============================] - 0s 4ms/step
867 [D loss: 0.709236, acc.: 49.61%] [G loss: 0.753940]
8/8 [==============================] - 0s 4ms/step
868 [D loss: 0.724063, acc.: 42.38%] [G loss: 0.704611]
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869 [D loss: 0.707981, acc.: 45.31%] [G loss: 0.724128]
8/8 [==============================] - 0s 4ms/step
870 [D loss: 0.678852, acc.: 62.11%] [G loss: 0.767279]
8/8 [==============================] - 0s 4ms/step
871 [D loss: 0.664106, acc.: 70.51%] [G loss: 0.796029]
8/8 [==============================] - 0s 4ms/step
872 [D loss: 0.672783, acc.: 60.74%] [G loss: 0.790609]
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873 [D loss: 0.686897, acc.: 54.10%] [G loss: 0.748847]
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874 [D loss: 0.684960, acc.: 52.15%] [G loss: 0.744026]
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875 [D loss: 0.670697, acc.: 63.09%] [G loss: 0.729725]
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876 [D loss: 0.671706, acc.: 63.09%] [G loss: 0.740377]
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877 [D loss: 0.677917, acc.: 58.40%] [G loss: 0.730569]
8/8 [==============================] - 0s 4ms/step
878 [D loss: 0.688375, acc.: 52.34%] [G loss: 0.729065]
8/8 [==============================] - 0s 4ms/step
879 [D loss: 0.682507, acc.: 56.45%] [G loss: 0.711266]
8/8 [==============================] - 0s 4ms/step
880 [D loss: 0.687789, acc.: 53.71%] [G loss: 0.685102]
8/8 [==============================] - 0s 4ms/step
881 [D loss: 0.694692, acc.: 49.61%] [G loss: 0.680880]
8/8 [==============================] - 0s 4ms/step
882 [D loss: 0.695017, acc.: 52.93%] [G loss: 0.691720]
8/8 [==============================] - 0s 4ms/step
883 [D loss: 0.697874, acc.: 49.41%] [G loss: 0.691114]
8/8 [==============================] - 0s 4ms/step
884 [D loss: 0.695471, acc.: 51.37%] [G loss: 0.727338]
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885 [D loss: 0.689225, acc.: 55.47%] [G loss: 0.748335]
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886 [D loss: 0.667288, acc.: 61.91%] [G loss: 0.812400]
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887 [D loss: 0.650355, acc.: 63.48%] [G loss: 0.906153]
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888 [D loss: 0.653272, acc.: 62.30%] [G loss: 0.898951]
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889 [D loss: 0.670815, acc.: 58.40%] [G loss: 0.827626]
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890 [D loss: 0.696378, acc.: 55.08%] [G loss: 0.753135]
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891 [D loss: 0.743435, acc.: 37.50%] [G loss: 0.697182]
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892 [D loss: 0.716604, acc.: 40.82%] [G loss: 0.712921]
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893 [D loss: 0.686276, acc.: 58.40%] [G loss: 0.756046]
8/8 [==============================] - 0s 4ms/step
894 [D loss: 0.675597, acc.: 61.72%] [G loss: 0.771466]
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895 [D loss: 0.676123, acc.: 60.74%] [G loss: 0.781758]
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896 [D loss: 0.671995, acc.: 61.91%] [G loss: 0.783212]
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897 [D loss: 0.660792, acc.: 68.36%] [G loss: 0.759950]
8/8 [==============================] - 0s 4ms/step
898 [D loss: 0.674840, acc.: 60.35%] [G loss: 0.745884]
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899 [D loss: 0.678266, acc.: 60.74%] [G loss: 0.724911]
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900 [D loss: 0.680292, acc.: 58.59%] [G loss: 0.717813]
1/1 [==============================] - 0s 21ms/step
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901 [D loss: 0.689471, acc.: 54.30%] [G loss: 0.707900]
8/8 [==============================] - 0s 4ms/step
902 [D loss: 0.697688, acc.: 48.63%] [G loss: 0.683645]
8/8 [==============================] - 0s 4ms/step
903 [D loss: 0.696616, acc.: 49.61%] [G loss: 0.693620]
8/8 [==============================] - 0s 4ms/step
904 [D loss: 0.696351, acc.: 49.61%] [G loss: 0.685565]
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905 [D loss: 0.691572, acc.: 50.98%] [G loss: 0.701184]
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906 [D loss: 0.679660, acc.: 59.57%] [G loss: 0.717692]
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907 [D loss: 0.680923, acc.: 57.23%] [G loss: 0.747802]
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908 [D loss: 0.667262, acc.: 64.84%] [G loss: 0.773203]
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909 [D loss: 0.676289, acc.: 61.13%] [G loss: 0.778500]
8/8 [==============================] - 0s 4ms/step
910 [D loss: 0.685510, acc.: 55.47%] [G loss: 0.772523]
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911 [D loss: 0.685263, acc.: 55.66%] [G loss: 0.801362]
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912 [D loss: 0.693941, acc.: 50.98%] [G loss: 0.760612]
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913 [D loss: 0.707445, acc.: 47.27%] [G loss: 0.740203]
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914 [D loss: 0.698791, acc.: 54.49%] [G loss: 0.717327]
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915 [D loss: 0.700944, acc.: 51.37%] [G loss: 0.718472]
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916 [D loss: 0.693799, acc.: 53.71%] [G loss: 0.724146]
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917 [D loss: 0.678561, acc.: 58.01%] [G loss: 0.746386]
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918 [D loss: 0.675879, acc.: 62.70%] [G loss: 0.746721]
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919 [D loss: 0.673840, acc.: 61.91%] [G loss: 0.755728]
8/8 [==============================] - 0s 4ms/step
920 [D loss: 0.679422, acc.: 57.03%] [G loss: 0.734024]
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921 [D loss: 0.680122, acc.: 58.20%] [G loss: 0.730183]
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922 [D loss: 0.680247, acc.: 59.38%] [G loss: 0.723776]
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923 [D loss: 0.687310, acc.: 52.54%] [G loss: 0.711979]
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924 [D loss: 0.690601, acc.: 50.59%] [G loss: 0.715979]
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925 [D loss: 0.693506, acc.: 52.15%] [G loss: 0.719267]
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926 [D loss: 0.696075, acc.: 50.98%] [G loss: 0.715535]
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927 [D loss: 0.703749, acc.: 46.88%] [G loss: 0.712443]
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928 [D loss: 0.694963, acc.: 50.59%] [G loss: 0.734096]
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929 [D loss: 0.692369, acc.: 54.88%] [G loss: 0.741838]
8/8 [==============================] - 0s 4ms/step
930 [D loss: 0.689252, acc.: 54.30%] [G loss: 0.733259]
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931 [D loss: 0.687756, acc.: 55.47%] [G loss: 0.754819]
8/8 [==============================] - 0s 4ms/step
932 [D loss: 0.681665, acc.: 59.57%] [G loss: 0.757757]
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933 [D loss: 0.685716, acc.: 56.45%] [G loss: 0.748445]
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934 [D loss: 0.681560, acc.: 58.59%] [G loss: 0.750132]
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935 [D loss: 0.682809, acc.: 56.64%] [G loss: 0.739524]
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936 [D loss: 0.684107, acc.: 58.40%] [G loss: 0.736620]
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937 [D loss: 0.682042, acc.: 59.57%] [G loss: 0.740729]
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938 [D loss: 0.682631, acc.: 57.03%] [G loss: 0.736298]
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939 [D loss: 0.685457, acc.: 58.59%] [G loss: 0.729682]
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940 [D loss: 0.687735, acc.: 53.52%] [G loss: 0.720473]
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941 [D loss: 0.688907, acc.: 56.25%] [G loss: 0.718394]
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942 [D loss: 0.692797, acc.: 52.34%] [G loss: 0.720479]
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943 [D loss: 0.689218, acc.: 54.69%] [G loss: 0.715911]
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944 [D loss: 0.686403, acc.: 53.91%] [G loss: 0.724782]
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945 [D loss: 0.687837, acc.: 54.88%] [G loss: 0.724527]
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946 [D loss: 0.690672, acc.: 53.32%] [G loss: 0.727320]
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947 [D loss: 0.685311, acc.: 54.88%] [G loss: 0.733908]
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948 [D loss: 0.677958, acc.: 61.72%] [G loss: 0.730174]
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949 [D loss: 0.682769, acc.: 56.45%] [G loss: 0.728728]
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950 [D loss: 0.686334, acc.: 54.69%] [G loss: 0.716434]
1/1 [==============================] - 0s 20ms/step
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951 [D loss: 0.693761, acc.: 48.24%] [G loss: 0.723956]
8/8 [==============================] - 0s 4ms/step
952 [D loss: 0.687904, acc.: 53.52%] [G loss: 0.724817]
8/8 [==============================] - 0s 4ms/step
953 [D loss: 0.688876, acc.: 51.17%] [G loss: 0.722595]
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954 [D loss: 0.696694, acc.: 46.68%] [G loss: 0.735211]
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955 [D loss: 0.690493, acc.: 53.91%] [G loss: 0.737886]
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956 [D loss: 0.685066, acc.: 55.27%] [G loss: 0.756786]
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957 [D loss: 0.682940, acc.: 58.20%] [G loss: 0.754734]
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958 [D loss: 0.691251, acc.: 57.23%] [G loss: 0.734356]
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959 [D loss: 0.689724, acc.: 54.88%] [G loss: 0.728204]
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960 [D loss: 0.690923, acc.: 55.08%] [G loss: 0.721752]
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961 [D loss: 0.698129, acc.: 51.17%] [G loss: 0.716528]
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962 [D loss: 0.685410, acc.: 53.91%] [G loss: 0.727203]
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963 [D loss: 0.693931, acc.: 51.95%] [G loss: 0.727856]
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964 [D loss: 0.685096, acc.: 56.64%] [G loss: 0.731936]
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965 [D loss: 0.684808, acc.: 58.59%] [G loss: 0.739260]
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966 [D loss: 0.683748, acc.: 58.98%] [G loss: 0.741759]
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967 [D loss: 0.681362, acc.: 60.35%] [G loss: 0.743371]
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968 [D loss: 0.683755, acc.: 59.77%] [G loss: 0.740839]
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969 [D loss: 0.681245, acc.: 58.01%] [G loss: 0.754915]
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970 [D loss: 0.688762, acc.: 52.15%] [G loss: 0.736008]
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971 [D loss: 0.684272, acc.: 56.45%] [G loss: 0.731079]
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972 [D loss: 0.688428, acc.: 54.88%] [G loss: 0.741472]
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973 [D loss: 0.685358, acc.: 53.71%] [G loss: 0.727415]
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974 [D loss: 0.681820, acc.: 58.20%] [G loss: 0.725969]
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975 [D loss: 0.686003, acc.: 54.10%] [G loss: 0.718549]
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976 [D loss: 0.684939, acc.: 53.32%] [G loss: 0.719758]
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977 [D loss: 0.686737, acc.: 51.56%] [G loss: 0.720680]
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978 [D loss: 0.682770, acc.: 55.66%] [G loss: 0.724553]
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979 [D loss: 0.687434, acc.: 56.64%] [G loss: 0.722815]
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980 [D loss: 0.694998, acc.: 51.37%] [G loss: 0.734524]
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981 [D loss: 0.696850, acc.: 48.83%] [G loss: 0.737931]
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982 [D loss: 0.694461, acc.: 51.56%] [G loss: 0.748978]
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983 [D loss: 0.687177, acc.: 58.98%] [G loss: 0.752379]
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984 [D loss: 0.680328, acc.: 59.96%] [G loss: 0.758066]
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985 [D loss: 0.687265, acc.: 55.08%] [G loss: 0.760895]
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986 [D loss: 0.683361, acc.: 56.05%] [G loss: 0.752185]
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987 [D loss: 0.686385, acc.: 58.59%] [G loss: 0.746528]
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988 [D loss: 0.687172, acc.: 56.45%] [G loss: 0.747419]
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989 [D loss: 0.687899, acc.: 53.52%] [G loss: 0.757313]
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990 [D loss: 0.692151, acc.: 51.95%] [G loss: 0.754123]
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991 [D loss: 0.692257, acc.: 52.93%] [G loss: 0.738412]
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992 [D loss: 0.687632, acc.: 54.49%] [G loss: 0.724208]
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993 [D loss: 0.692477, acc.: 51.17%] [G loss: 0.723463]
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994 [D loss: 0.687454, acc.: 53.32%] [G loss: 0.721790]
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995 [D loss: 0.690383, acc.: 52.93%] [G loss: 0.710559]
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996 [D loss: 0.690242, acc.: 50.59%] [G loss: 0.719704]
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997 [D loss: 0.688526, acc.: 51.56%] [G loss: 0.719322]
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998 [D loss: 0.687922, acc.: 52.93%] [G loss: 0.724130]
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999 [D loss: 0.685694, acc.: 53.91%] [G loss: 0.729632]
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1000 [D loss: 0.683813, acc.: 54.88%] [G loss: 0.739490]
1/1 [==============================] - 0s 20ms/step
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1001 [D loss: 0.682338, acc.: 56.05%] [G loss: 0.735725]
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1002 [D loss: 0.683937, acc.: 55.66%] [G loss: 0.735639]
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1003 [D loss: 0.692491, acc.: 51.17%] [G loss: 0.727855]
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1004 [D loss: 0.689402, acc.: 53.32%] [G loss: 0.742081]
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1005 [D loss: 0.687613, acc.: 53.12%] [G loss: 0.738240]
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1006 [D loss: 0.686761, acc.: 54.69%] [G loss: 0.740927]
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1007 [D loss: 0.687492, acc.: 56.64%] [G loss: 0.745341]
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1008 [D loss: 0.689552, acc.: 55.27%] [G loss: 0.742899]
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1009 [D loss: 0.687398, acc.: 53.71%] [G loss: 0.759106]
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1010 [D loss: 0.687807, acc.: 55.66%] [G loss: 0.753220]
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1011 [D loss: 0.688864, acc.: 55.47%] [G loss: 0.737746]
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1012 [D loss: 0.690270, acc.: 54.10%] [G loss: 0.739257]
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1013 [D loss: 0.679676, acc.: 57.03%] [G loss: 0.744793]
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1014 [D loss: 0.689521, acc.: 55.66%] [G loss: 0.737731]
8/8 [==============================] - 0s 4ms/step
1015 [D loss: 0.683607, acc.: 56.05%] [G loss: 0.748492]
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1016 [D loss: 0.692031, acc.: 51.95%] [G loss: 0.745478]
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1017 [D loss: 0.682988, acc.: 56.84%] [G loss: 0.727839]
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1018 [D loss: 0.682108, acc.: 57.62%] [G loss: 0.728042]
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1019 [D loss: 0.689629, acc.: 54.10%] [G loss: 0.708049]
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1020 [D loss: 0.688848, acc.: 51.17%] [G loss: 0.694060]
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1021 [D loss: 0.700159, acc.: 50.59%] [G loss: 0.696733]
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1022 [D loss: 0.691533, acc.: 50.98%] [G loss: 0.699313]
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1023 [D loss: 0.697813, acc.: 49.41%] [G loss: 0.718257]
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1024 [D loss: 0.690040, acc.: 53.32%] [G loss: 0.739983]
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1025 [D loss: 0.691173, acc.: 54.30%] [G loss: 0.745176]
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1026 [D loss: 0.691236, acc.: 53.52%] [G loss: 0.767814]
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1027 [D loss: 0.685766, acc.: 57.03%] [G loss: 0.771865]
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1028 [D loss: 0.681961, acc.: 57.23%] [G loss: 0.772670]
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1029 [D loss: 0.687871, acc.: 54.69%] [G loss: 0.768606]
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1030 [D loss: 0.693643, acc.: 51.95%] [G loss: 0.755749]
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1031 [D loss: 0.684217, acc.: 57.03%] [G loss: 0.755861]
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1032 [D loss: 0.682059, acc.: 58.20%] [G loss: 0.749388]
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1033 [D loss: 0.682275, acc.: 59.77%] [G loss: 0.765733]
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1034 [D loss: 0.678917, acc.: 59.57%] [G loss: 0.758330]
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1035 [D loss: 0.679944, acc.: 57.62%] [G loss: 0.746053]
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1036 [D loss: 0.683784, acc.: 56.64%] [G loss: 0.728890]
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1037 [D loss: 0.691718, acc.: 53.91%] [G loss: 0.724384]
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1038 [D loss: 0.688486, acc.: 51.95%] [G loss: 0.716022]
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1039 [D loss: 0.685143, acc.: 55.27%] [G loss: 0.715010]
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1040 [D loss: 0.685822, acc.: 57.03%] [G loss: 0.724139]
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1041 [D loss: 0.686595, acc.: 55.66%] [G loss: 0.716415]
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1042 [D loss: 0.695669, acc.: 48.63%] [G loss: 0.706487]
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1043 [D loss: 0.690349, acc.: 53.12%] [G loss: 0.714244]
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1044 [D loss: 0.684663, acc.: 54.69%] [G loss: 0.717323]
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1045 [D loss: 0.680626, acc.: 55.66%] [G loss: 0.731064]
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1046 [D loss: 0.675505, acc.: 58.98%] [G loss: 0.747275]
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1047 [D loss: 0.685107, acc.: 53.12%] [G loss: 0.759179]
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1048 [D loss: 0.689411, acc.: 50.78%] [G loss: 0.762836]
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1049 [D loss: 0.685150, acc.: 55.86%] [G loss: 0.774260]
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1050 [D loss: 0.682281, acc.: 56.84%] [G loss: 0.780170]
1/1 [==============================] - 0s 21ms/step
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1051 [D loss: 0.685476, acc.: 57.23%] [G loss: 0.781947]
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1052 [D loss: 0.693951, acc.: 52.93%] [G loss: 0.770336]
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1053 [D loss: 0.699209, acc.: 54.10%] [G loss: 0.755306]
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1054 [D loss: 0.691049, acc.: 54.88%] [G loss: 0.735198]
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1055 [D loss: 0.697319, acc.: 49.80%] [G loss: 0.730677]
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1056 [D loss: 0.691474, acc.: 54.69%] [G loss: 0.755970]
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1057 [D loss: 0.678848, acc.: 59.96%] [G loss: 0.770081]
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1058 [D loss: 0.680663, acc.: 58.98%] [G loss: 0.769980]
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1059 [D loss: 0.677006, acc.: 61.72%] [G loss: 0.750495]
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1060 [D loss: 0.685775, acc.: 54.30%] [G loss: 0.740581]
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1061 [D loss: 0.682260, acc.: 56.05%] [G loss: 0.730066]
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1062 [D loss: 0.681852, acc.: 55.47%] [G loss: 0.714670]
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1063 [D loss: 0.681911, acc.: 56.05%] [G loss: 0.725316]
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1064 [D loss: 0.685282, acc.: 55.47%] [G loss: 0.715257]
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1065 [D loss: 0.692943, acc.: 54.49%] [G loss: 0.719583]
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1066 [D loss: 0.699104, acc.: 50.00%] [G loss: 0.705924]
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1067 [D loss: 0.697063, acc.: 50.00%] [G loss: 0.712840]
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1068 [D loss: 0.695167, acc.: 51.37%] [G loss: 0.717997]
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1069 [D loss: 0.687485, acc.: 54.88%] [G loss: 0.728378]
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1070 [D loss: 0.680303, acc.: 58.59%] [G loss: 0.739588]
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1071 [D loss: 0.678096, acc.: 58.20%] [G loss: 0.759696]
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1072 [D loss: 0.678165, acc.: 60.55%] [G loss: 0.757905]
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1073 [D loss: 0.688572, acc.: 53.52%] [G loss: 0.759656]
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1074 [D loss: 0.689037, acc.: 49.41%] [G loss: 0.758430]
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1075 [D loss: 0.686342, acc.: 57.03%] [G loss: 0.740315]
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1076 [D loss: 0.684986, acc.: 56.84%] [G loss: 0.742444]
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1077 [D loss: 0.695193, acc.: 52.15%] [G loss: 0.729113]
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1078 [D loss: 0.691094, acc.: 55.47%] [G loss: 0.720479]
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1079 [D loss: 0.689786, acc.: 56.05%] [G loss: 0.731112]
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1080 [D loss: 0.688688, acc.: 55.08%] [G loss: 0.724399]
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1081 [D loss: 0.693678, acc.: 52.54%] [G loss: 0.713555]
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1082 [D loss: 0.682974, acc.: 56.45%] [G loss: 0.721486]
8/8 [==============================] - 0s 4ms/step
1083 [D loss: 0.683170, acc.: 52.93%] [G loss: 0.712752]
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1084 [D loss: 0.687454, acc.: 51.76%] [G loss: 0.706399]
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1085 [D loss: 0.681136, acc.: 56.84%] [G loss: 0.719929]
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1086 [D loss: 0.685703, acc.: 54.30%] [G loss: 0.738091]
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1087 [D loss: 0.682841, acc.: 56.05%] [G loss: 0.727697]
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1088 [D loss: 0.684773, acc.: 54.49%] [G loss: 0.761159]
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1089 [D loss: 0.683187, acc.: 57.42%] [G loss: 0.759288]
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1090 [D loss: 0.681511, acc.: 57.81%] [G loss: 0.775138]
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1091 [D loss: 0.684703, acc.: 55.08%] [G loss: 0.766202]
8/8 [==============================] - 0s 4ms/step
1092 [D loss: 0.689652, acc.: 52.34%] [G loss: 0.749994]
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1093 [D loss: 0.692144, acc.: 52.34%] [G loss: 0.736034]
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1094 [D loss: 0.685037, acc.: 55.66%] [G loss: 0.733795]
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1095 [D loss: 0.692192, acc.: 55.27%] [G loss: 0.730219]
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1096 [D loss: 0.685255, acc.: 58.59%] [G loss: 0.746481]
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1097 [D loss: 0.682742, acc.: 55.86%] [G loss: 0.751290]
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1098 [D loss: 0.683990, acc.: 57.03%] [G loss: 0.753606]
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1099 [D loss: 0.672270, acc.: 63.09%] [G loss: 0.761772]
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1100 [D loss: 0.674737, acc.: 60.74%] [G loss: 0.755447]
1/1 [==============================] - 0s 20ms/step
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1101 [D loss: 0.673470, acc.: 62.30%] [G loss: 0.755852]
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1102 [D loss: 0.671622, acc.: 64.26%] [G loss: 0.742660]
8/8 [==============================] - 0s 4ms/step
1103 [D loss: 0.676028, acc.: 61.13%] [G loss: 0.744796]
8/8 [==============================] - 0s 4ms/step
1104 [D loss: 0.683436, acc.: 58.79%] [G loss: 0.726421]
8/8 [==============================] - 0s 4ms/step
1105 [D loss: 0.676730, acc.: 60.55%] [G loss: 0.714652]
8/8 [==============================] - 0s 4ms/step
1106 [D loss: 0.685187, acc.: 54.49%] [G loss: 0.697448]
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1107 [D loss: 0.692700, acc.: 53.32%] [G loss: 0.673856]
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1108 [D loss: 0.704929, acc.: 48.63%] [G loss: 0.673906]
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1109 [D loss: 0.698497, acc.: 47.85%] [G loss: 0.665253]
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1110 [D loss: 0.691031, acc.: 54.49%] [G loss: 0.670768]
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1111 [D loss: 0.691877, acc.: 53.71%] [G loss: 0.694000]
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1112 [D loss: 0.683516, acc.: 55.86%] [G loss: 0.749757]
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1113 [D loss: 0.675184, acc.: 58.01%] [G loss: 0.837000]
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1114 [D loss: 0.663891, acc.: 61.91%] [G loss: 0.900066]
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1115 [D loss: 0.667365, acc.: 61.33%] [G loss: 0.897789]
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1116 [D loss: 0.668500, acc.: 57.23%] [G loss: 0.876988]
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1117 [D loss: 0.685236, acc.: 54.88%] [G loss: 0.818850]
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1118 [D loss: 0.712013, acc.: 48.24%] [G loss: 0.747475]
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1119 [D loss: 0.711169, acc.: 43.16%] [G loss: 0.735368]
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1120 [D loss: 0.697012, acc.: 50.59%] [G loss: 0.775538]
8/8 [==============================] - 0s 4ms/step
1121 [D loss: 0.675471, acc.: 64.26%] [G loss: 0.832896]
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1122 [D loss: 0.664917, acc.: 64.84%] [G loss: 0.854669]
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1123 [D loss: 0.685737, acc.: 54.69%] [G loss: 0.796683]
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1124 [D loss: 0.681443, acc.: 55.47%] [G loss: 0.745071]
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1125 [D loss: 0.679861, acc.: 55.86%] [G loss: 0.730635]
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1126 [D loss: 0.670670, acc.: 58.40%] [G loss: 0.735195]
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1127 [D loss: 0.670693, acc.: 62.30%] [G loss: 0.763748]
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1128 [D loss: 0.668729, acc.: 62.50%] [G loss: 0.763778]
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1129 [D loss: 0.671108, acc.: 63.28%] [G loss: 0.750521]
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1130 [D loss: 0.684940, acc.: 58.98%] [G loss: 0.736655]
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1131 [D loss: 0.675711, acc.: 60.16%] [G loss: 0.720203]
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1132 [D loss: 0.677974, acc.: 57.81%] [G loss: 0.700816]
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1133 [D loss: 0.682150, acc.: 54.10%] [G loss: 0.687367]
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1134 [D loss: 0.681066, acc.: 56.45%] [G loss: 0.680112]
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1135 [D loss: 0.687890, acc.: 52.34%] [G loss: 0.681720]
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1136 [D loss: 0.694100, acc.: 51.56%] [G loss: 0.700238]
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1137 [D loss: 0.703453, acc.: 47.85%] [G loss: 0.752776]
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1138 [D loss: 0.682757, acc.: 59.77%] [G loss: 0.832859]
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1139 [D loss: 0.684029, acc.: 56.45%] [G loss: 0.861318]
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1140 [D loss: 0.685101, acc.: 56.05%] [G loss: 0.878577]
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1141 [D loss: 0.684956, acc.: 55.47%] [G loss: 0.851591]
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1142 [D loss: 0.712674, acc.: 49.41%] [G loss: 0.768170]
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1143 [D loss: 0.706560, acc.: 51.56%] [G loss: 0.747020]
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1144 [D loss: 0.686667, acc.: 57.62%] [G loss: 0.781258]
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1145 [D loss: 0.674719, acc.: 60.35%] [G loss: 0.820764]
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1146 [D loss: 0.652111, acc.: 67.58%] [G loss: 0.845723]
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1147 [D loss: 0.666107, acc.: 63.87%] [G loss: 0.842295]
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1148 [D loss: 0.673485, acc.: 60.35%] [G loss: 0.823411]
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1149 [D loss: 0.675734, acc.: 58.98%] [G loss: 0.784969]
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1150 [D loss: 0.665496, acc.: 63.67%] [G loss: 0.760852]
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1151 [D loss: 0.675450, acc.: 56.25%] [G loss: 0.750818]
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1152 [D loss: 0.666584, acc.: 61.33%] [G loss: 0.751228]
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1153 [D loss: 0.674677, acc.: 58.01%] [G loss: 0.720446]
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1154 [D loss: 0.693847, acc.: 52.73%] [G loss: 0.700876]
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1155 [D loss: 0.703917, acc.: 47.46%] [G loss: 0.696476]
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1156 [D loss: 0.696173, acc.: 51.56%] [G loss: 0.700869]
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1157 [D loss: 0.687306, acc.: 51.95%] [G loss: 0.719857]
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1158 [D loss: 0.690015, acc.: 52.93%] [G loss: 0.762767]
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1159 [D loss: 0.669891, acc.: 58.79%] [G loss: 0.818977]
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1160 [D loss: 0.674199, acc.: 60.16%] [G loss: 0.832622]
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1161 [D loss: 0.668612, acc.: 60.55%] [G loss: 0.855737]
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1162 [D loss: 0.678203, acc.: 55.27%] [G loss: 0.856687]
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1163 [D loss: 0.720621, acc.: 46.68%] [G loss: 0.769940]
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1164 [D loss: 0.714012, acc.: 50.78%] [G loss: 0.734455]
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1165 [D loss: 0.699599, acc.: 57.42%] [G loss: 0.761544]
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1166 [D loss: 0.688662, acc.: 55.86%] [G loss: 0.800581]
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1167 [D loss: 0.663867, acc.: 65.04%] [G loss: 0.843081]
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1168 [D loss: 0.660589, acc.: 67.19%] [G loss: 0.863846]
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1169 [D loss: 0.657148, acc.: 67.19%] [G loss: 0.856015]
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1170 [D loss: 0.650762, acc.: 66.99%] [G loss: 0.836864]
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1171 [D loss: 0.665350, acc.: 60.55%] [G loss: 0.813836]
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1172 [D loss: 0.663551, acc.: 60.16%] [G loss: 0.780475]
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1173 [D loss: 0.683361, acc.: 57.81%] [G loss: 0.768743]
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1174 [D loss: 0.688059, acc.: 55.27%] [G loss: 0.748059]
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1175 [D loss: 0.685016, acc.: 55.66%] [G loss: 0.711286]
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1176 [D loss: 0.671166, acc.: 57.03%] [G loss: 0.671512]
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1177 [D loss: 0.688853, acc.: 52.34%] [G loss: 0.682984]
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1178 [D loss: 0.686889, acc.: 53.52%] [G loss: 0.654833]
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1179 [D loss: 0.685429, acc.: 54.49%] [G loss: 0.662099]
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1180 [D loss: 0.682809, acc.: 56.05%] [G loss: 0.675103]
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1181 [D loss: 0.686046, acc.: 54.49%] [G loss: 0.721496]
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1182 [D loss: 0.674624, acc.: 58.40%] [G loss: 0.803552]
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1183 [D loss: 0.665507, acc.: 60.55%] [G loss: 0.880948]
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1184 [D loss: 0.663952, acc.: 63.09%] [G loss: 0.981420]
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1185 [D loss: 0.679231, acc.: 59.38%] [G loss: 0.998893]
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1186 [D loss: 0.718080, acc.: 51.56%] [G loss: 0.841498]
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1187 [D loss: 0.709603, acc.: 55.27%] [G loss: 0.770381]
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1188 [D loss: 0.704378, acc.: 54.10%] [G loss: 0.750508]
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1189 [D loss: 0.690755, acc.: 56.64%] [G loss: 0.773880]
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1190 [D loss: 0.667567, acc.: 65.43%] [G loss: 0.822808]
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1191 [D loss: 0.662147, acc.: 68.75%] [G loss: 0.854783]
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1192 [D loss: 0.666353, acc.: 65.04%] [G loss: 0.835181]
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1193 [D loss: 0.654382, acc.: 66.02%] [G loss: 0.856665]
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1194 [D loss: 0.659737, acc.: 64.84%] [G loss: 0.839802]
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1195 [D loss: 0.656448, acc.: 63.87%] [G loss: 0.826720]
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1196 [D loss: 0.653382, acc.: 65.82%] [G loss: 0.814594]
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1197 [D loss: 0.650545, acc.: 66.99%] [G loss: 0.803511]
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1198 [D loss: 0.657118, acc.: 60.35%] [G loss: 0.801312]
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1199 [D loss: 0.649721, acc.: 66.60%] [G loss: 0.782030]
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1200 [D loss: 0.662214, acc.: 61.91%] [G loss: 0.766361]
1/1 [==============================] - 0s 21ms/step
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1201 [D loss: 0.666329, acc.: 58.20%] [G loss: 0.733189]
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1202 [D loss: 0.691484, acc.: 51.37%] [G loss: 0.684591]
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1203 [D loss: 0.699395, acc.: 50.39%] [G loss: 0.643309]
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1204 [D loss: 0.694904, acc.: 53.32%] [G loss: 0.631586]
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1205 [D loss: 0.699283, acc.: 51.56%] [G loss: 0.653603]
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1206 [D loss: 0.689097, acc.: 52.93%] [G loss: 0.705865]
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1207 [D loss: 0.667695, acc.: 59.77%] [G loss: 0.807191]
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1208 [D loss: 0.684149, acc.: 57.62%] [G loss: 0.940884]
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1209 [D loss: 0.669486, acc.: 61.13%] [G loss: 1.072321]
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1210 [D loss: 0.685180, acc.: 54.30%] [G loss: 1.115129]
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1211 [D loss: 0.704170, acc.: 48.63%] [G loss: 0.955014]
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1212 [D loss: 0.763599, acc.: 41.21%] [G loss: 0.778194]
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1213 [D loss: 0.751764, acc.: 38.28%] [G loss: 0.721980]
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1214 [D loss: 0.711619, acc.: 50.20%] [G loss: 0.745065]
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1215 [D loss: 0.686885, acc.: 58.79%] [G loss: 0.799711]
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1216 [D loss: 0.660957, acc.: 64.84%] [G loss: 0.854116]
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1217 [D loss: 0.652548, acc.: 69.34%] [G loss: 0.886004]
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1218 [D loss: 0.663369, acc.: 63.87%] [G loss: 0.868259]
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1219 [D loss: 0.648036, acc.: 66.99%] [G loss: 0.834640]
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1220 [D loss: 0.645393, acc.: 66.02%] [G loss: 0.834450]
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1221 [D loss: 0.635312, acc.: 69.34%] [G loss: 0.845604]
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1222 [D loss: 0.640767, acc.: 68.16%] [G loss: 0.817128]
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1223 [D loss: 0.655884, acc.: 63.87%] [G loss: 0.790037]
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1224 [D loss: 0.657420, acc.: 61.91%] [G loss: 0.768022]
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1225 [D loss: 0.665695, acc.: 58.79%] [G loss: 0.755054]
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1226 [D loss: 0.679040, acc.: 57.42%] [G loss: 0.730364]
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1227 [D loss: 0.709756, acc.: 49.41%] [G loss: 0.716105]
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1228 [D loss: 0.697652, acc.: 47.66%] [G loss: 0.703874]
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1229 [D loss: 0.710534, acc.: 47.46%] [G loss: 0.697785]
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1230 [D loss: 0.679877, acc.: 54.10%] [G loss: 0.751016]
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1231 [D loss: 0.684235, acc.: 53.12%] [G loss: 0.799068]
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1232 [D loss: 0.672854, acc.: 57.42%] [G loss: 0.885108]
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1233 [D loss: 0.656068, acc.: 62.50%] [G loss: 0.918730]
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1234 [D loss: 0.654091, acc.: 64.26%] [G loss: 0.938018]
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1235 [D loss: 0.678405, acc.: 58.59%] [G loss: 0.858001]
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1236 [D loss: 0.697535, acc.: 51.37%] [G loss: 0.827251]
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1237 [D loss: 0.708122, acc.: 52.34%] [G loss: 0.769849]
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1238 [D loss: 0.708210, acc.: 50.39%] [G loss: 0.744572]
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1239 [D loss: 0.702089, acc.: 51.56%] [G loss: 0.746411]
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1240 [D loss: 0.681908, acc.: 55.47%] [G loss: 0.763481]
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1241 [D loss: 0.688061, acc.: 56.05%] [G loss: 0.769035]
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1242 [D loss: 0.680349, acc.: 58.98%] [G loss: 0.781695]
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1243 [D loss: 0.675792, acc.: 60.35%] [G loss: 0.775370]
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1244 [D loss: 0.670713, acc.: 60.74%] [G loss: 0.784463]
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1245 [D loss: 0.668248, acc.: 59.38%] [G loss: 0.772829]
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1246 [D loss: 0.677868, acc.: 56.84%] [G loss: 0.764436]
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1247 [D loss: 0.677637, acc.: 58.79%] [G loss: 0.755659]
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1248 [D loss: 0.680647, acc.: 54.30%] [G loss: 0.762504]
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1249 [D loss: 0.676313, acc.: 57.62%] [G loss: 0.731086]
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1250 [D loss: 0.687001, acc.: 55.08%] [G loss: 0.723224]
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1251 [D loss: 0.680659, acc.: 55.27%] [G loss: 0.717623]
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1252 [D loss: 0.692891, acc.: 52.15%] [G loss: 0.711495]
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1253 [D loss: 0.692860, acc.: 52.93%] [G loss: 0.739442]
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1254 [D loss: 0.677958, acc.: 56.64%] [G loss: 0.779955]
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1255 [D loss: 0.683294, acc.: 55.27%] [G loss: 0.800232]
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1256 [D loss: 0.667716, acc.: 59.57%] [G loss: 0.827187]
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1257 [D loss: 0.674367, acc.: 58.20%] [G loss: 0.814068]
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1258 [D loss: 0.682168, acc.: 57.23%] [G loss: 0.852112]
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1259 [D loss: 0.682673, acc.: 55.08%] [G loss: 0.818441]
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1260 [D loss: 0.693080, acc.: 53.91%] [G loss: 0.795842]
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1261 [D loss: 0.704730, acc.: 54.30%] [G loss: 0.763855]
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1262 [D loss: 0.690240, acc.: 53.32%] [G loss: 0.760357]
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1263 [D loss: 0.690141, acc.: 54.49%] [G loss: 0.763699]
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1264 [D loss: 0.679346, acc.: 59.38%] [G loss: 0.783618]
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1265 [D loss: 0.688156, acc.: 53.52%] [G loss: 0.795450]
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1266 [D loss: 0.675767, acc.: 60.94%] [G loss: 0.797706]
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1267 [D loss: 0.679311, acc.: 58.59%] [G loss: 0.781335]
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1268 [D loss: 0.677859, acc.: 60.35%] [G loss: 0.755729]
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1269 [D loss: 0.670562, acc.: 60.94%] [G loss: 0.777642]
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1270 [D loss: 0.686956, acc.: 54.69%] [G loss: 0.761445]
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1271 [D loss: 0.687772, acc.: 56.05%] [G loss: 0.750724]
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1272 [D loss: 0.695175, acc.: 51.95%] [G loss: 0.753158]
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1273 [D loss: 0.684418, acc.: 54.30%] [G loss: 0.745503]
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1274 [D loss: 0.687711, acc.: 53.71%] [G loss: 0.735151]
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1275 [D loss: 0.689641, acc.: 52.73%] [G loss: 0.752060]
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1276 [D loss: 0.677122, acc.: 56.05%] [G loss: 0.750692]
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1277 [D loss: 0.686878, acc.: 54.69%] [G loss: 0.762587]
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1278 [D loss: 0.676869, acc.: 60.55%] [G loss: 0.769996]
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1279 [D loss: 0.679896, acc.: 58.59%] [G loss: 0.775149]
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1280 [D loss: 0.680415, acc.: 59.77%] [G loss: 0.780766]
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1281 [D loss: 0.676732, acc.: 62.11%] [G loss: 0.799273]
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1282 [D loss: 0.681726, acc.: 55.66%] [G loss: 0.801017]
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1283 [D loss: 0.682842, acc.: 54.88%] [G loss: 0.774947]
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1284 [D loss: 0.693355, acc.: 51.56%] [G loss: 0.781664]
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1285 [D loss: 0.685571, acc.: 55.47%] [G loss: 0.766785]
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1286 [D loss: 0.691644, acc.: 54.49%] [G loss: 0.765753]
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1287 [D loss: 0.692822, acc.: 52.34%] [G loss: 0.773540]
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1288 [D loss: 0.681727, acc.: 59.96%] [G loss: 0.775666]
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1289 [D loss: 0.684512, acc.: 56.45%] [G loss: 0.787823]
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1290 [D loss: 0.669628, acc.: 61.72%] [G loss: 0.783788]
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1291 [D loss: 0.676874, acc.: 57.03%] [G loss: 0.785753]
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1292 [D loss: 0.661921, acc.: 61.91%] [G loss: 0.775979]
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1293 [D loss: 0.672722, acc.: 57.42%] [G loss: 0.771285]
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1294 [D loss: 0.676255, acc.: 57.62%] [G loss: 0.755645]
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1295 [D loss: 0.675602, acc.: 58.79%] [G loss: 0.751472]
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1296 [D loss: 0.700622, acc.: 49.41%] [G loss: 0.734763]
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1297 [D loss: 0.687223, acc.: 53.32%] [G loss: 0.710587]
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1298 [D loss: 0.701696, acc.: 48.05%] [G loss: 0.728392]
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1299 [D loss: 0.680611, acc.: 57.03%] [G loss: 0.737850]
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1300 [D loss: 0.687588, acc.: 53.91%] [G loss: 0.741888]
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1301 [D loss: 0.689233, acc.: 55.86%] [G loss: 0.775618]
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1302 [D loss: 0.683787, acc.: 55.27%] [G loss: 0.763564]
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1303 [D loss: 0.675676, acc.: 59.18%] [G loss: 0.790613]
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1304 [D loss: 0.674220, acc.: 62.30%] [G loss: 0.794197]
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1305 [D loss: 0.672616, acc.: 61.52%] [G loss: 0.808419]
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1306 [D loss: 0.673926, acc.: 58.40%] [G loss: 0.814272]
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1307 [D loss: 0.679624, acc.: 58.01%] [G loss: 0.829545]
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1308 [D loss: 0.680374, acc.: 57.81%] [G loss: 0.793159]
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1309 [D loss: 0.692030, acc.: 52.73%] [G loss: 0.781507]
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1310 [D loss: 0.696123, acc.: 51.95%] [G loss: 0.774003]
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1311 [D loss: 0.690533, acc.: 51.95%] [G loss: 0.780490]
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1312 [D loss: 0.672922, acc.: 60.74%] [G loss: 0.790745]
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1313 [D loss: 0.678577, acc.: 56.64%] [G loss: 0.797296]
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1314 [D loss: 0.682561, acc.: 56.84%] [G loss: 0.790035]
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1315 [D loss: 0.672911, acc.: 58.01%] [G loss: 0.779902]
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1316 [D loss: 0.661702, acc.: 62.50%] [G loss: 0.788612]
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1317 [D loss: 0.667492, acc.: 59.96%] [G loss: 0.786465]
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1318 [D loss: 0.673098, acc.: 58.79%] [G loss: 0.762312]
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1319 [D loss: 0.682875, acc.: 55.86%] [G loss: 0.748157]
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1320 [D loss: 0.682213, acc.: 58.20%] [G loss: 0.735284]
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1321 [D loss: 0.683737, acc.: 54.69%] [G loss: 0.716646]
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1322 [D loss: 0.692115, acc.: 52.34%] [G loss: 0.702919]
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1323 [D loss: 0.700584, acc.: 47.85%] [G loss: 0.689286]
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1324 [D loss: 0.681711, acc.: 52.93%] [G loss: 0.707807]
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1325 [D loss: 0.688441, acc.: 52.54%] [G loss: 0.733703]
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1326 [D loss: 0.679520, acc.: 57.03%] [G loss: 0.781468]
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1327 [D loss: 0.671188, acc.: 58.98%] [G loss: 0.833734]
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1328 [D loss: 0.674833, acc.: 59.38%] [G loss: 0.850989]
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1329 [D loss: 0.672128, acc.: 60.94%] [G loss: 0.851831]
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1330 [D loss: 0.665800, acc.: 63.87%] [G loss: 0.835808]
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1331 [D loss: 0.691826, acc.: 56.05%] [G loss: 0.795220]
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1332 [D loss: 0.696627, acc.: 53.32%] [G loss: 0.767367]
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1333 [D loss: 0.684734, acc.: 55.27%] [G loss: 0.776048]
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1334 [D loss: 0.677956, acc.: 57.42%] [G loss: 0.812157]
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1335 [D loss: 0.680588, acc.: 57.42%] [G loss: 0.805153]
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1336 [D loss: 0.677415, acc.: 55.27%] [G loss: 0.798294]
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1337 [D loss: 0.681268, acc.: 57.23%] [G loss: 0.781436]
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1338 [D loss: 0.680711, acc.: 60.35%] [G loss: 0.771788]
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1339 [D loss: 0.682158, acc.: 55.47%] [G loss: 0.786729]
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1340 [D loss: 0.678478, acc.: 58.01%] [G loss: 0.768093]
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1341 [D loss: 0.666513, acc.: 61.52%] [G loss: 0.771801]
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1342 [D loss: 0.672319, acc.: 59.18%] [G loss: 0.767156]
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1343 [D loss: 0.678468, acc.: 54.49%] [G loss: 0.755683]
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1344 [D loss: 0.682013, acc.: 55.47%] [G loss: 0.739226]
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1345 [D loss: 0.688649, acc.: 50.59%] [G loss: 0.721218]
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1346 [D loss: 0.696432, acc.: 51.37%] [G loss: 0.691673]
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1347 [D loss: 0.672477, acc.: 57.81%] [G loss: 0.716798]
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1348 [D loss: 0.683141, acc.: 54.49%] [G loss: 0.739402]
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1349 [D loss: 0.678158, acc.: 54.10%] [G loss: 0.767086]
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1350 [D loss: 0.681508, acc.: 55.47%] [G loss: 0.807869]
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1351 [D loss: 0.676699, acc.: 58.40%] [G loss: 0.799308]
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1352 [D loss: 0.691260, acc.: 51.76%] [G loss: 0.811896]
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1353 [D loss: 0.682545, acc.: 56.25%] [G loss: 0.805679]
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1354 [D loss: 0.694479, acc.: 50.78%] [G loss: 0.770684]
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1355 [D loss: 0.694353, acc.: 54.30%] [G loss: 0.766266]
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1356 [D loss: 0.700219, acc.: 47.07%] [G loss: 0.755497]
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1357 [D loss: 0.694225, acc.: 54.30%] [G loss: 0.769982]
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1358 [D loss: 0.687920, acc.: 54.49%] [G loss: 0.757486]
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1359 [D loss: 0.679277, acc.: 54.88%] [G loss: 0.774535]
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1360 [D loss: 0.678196, acc.: 56.84%] [G loss: 0.753655]
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1361 [D loss: 0.679002, acc.: 57.81%] [G loss: 0.783514]
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1362 [D loss: 0.666986, acc.: 61.72%] [G loss: 0.767919]
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1363 [D loss: 0.672360, acc.: 60.55%] [G loss: 0.769909]
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1364 [D loss: 0.674003, acc.: 58.98%] [G loss: 0.788314]
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1365 [D loss: 0.674727, acc.: 55.86%] [G loss: 0.787516]
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1366 [D loss: 0.680369, acc.: 55.08%] [G loss: 0.767350]
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1367 [D loss: 0.676366, acc.: 57.23%] [G loss: 0.734842]
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1368 [D loss: 0.681365, acc.: 55.86%] [G loss: 0.743863]
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1369 [D loss: 0.678923, acc.: 52.73%] [G loss: 0.717833]
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1370 [D loss: 0.691759, acc.: 52.34%] [G loss: 0.716179]
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1371 [D loss: 0.681118, acc.: 54.10%] [G loss: 0.723511]
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1372 [D loss: 0.675949, acc.: 57.62%] [G loss: 0.713193]
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1373 [D loss: 0.690611, acc.: 50.39%] [G loss: 0.747457]
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1374 [D loss: 0.676540, acc.: 54.88%] [G loss: 0.784585]
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1375 [D loss: 0.669354, acc.: 56.45%] [G loss: 0.799815]
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1376 [D loss: 0.674871, acc.: 57.81%] [G loss: 0.817108]
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1377 [D loss: 0.686833, acc.: 54.10%] [G loss: 0.814791]
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1378 [D loss: 0.680035, acc.: 53.71%] [G loss: 0.798194]
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1379 [D loss: 0.701718, acc.: 50.00%] [G loss: 0.795459]
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1380 [D loss: 0.694684, acc.: 50.98%] [G loss: 0.781822]
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1381 [D loss: 0.695758, acc.: 51.56%] [G loss: 0.764841]
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1382 [D loss: 0.682939, acc.: 56.84%] [G loss: 0.780613]
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1383 [D loss: 0.684786, acc.: 55.47%] [G loss: 0.781326]
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1384 [D loss: 0.670842, acc.: 58.20%] [G loss: 0.787356]
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1385 [D loss: 0.678124, acc.: 58.01%] [G loss: 0.798178]
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1386 [D loss: 0.669427, acc.: 60.94%] [G loss: 0.793401]
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1387 [D loss: 0.680604, acc.: 59.77%] [G loss: 0.770230]
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1388 [D loss: 0.672387, acc.: 61.52%] [G loss: 0.752106]
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1389 [D loss: 0.680593, acc.: 55.27%] [G loss: 0.742832]
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1390 [D loss: 0.690335, acc.: 53.12%] [G loss: 0.740826]
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1391 [D loss: 0.690617, acc.: 53.71%] [G loss: 0.734090]
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1392 [D loss: 0.678742, acc.: 56.25%] [G loss: 0.730907]
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1393 [D loss: 0.697758, acc.: 52.54%] [G loss: 0.722193]
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1394 [D loss: 0.704786, acc.: 48.05%] [G loss: 0.709324]
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1395 [D loss: 0.702087, acc.: 49.22%] [G loss: 0.737668]
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1396 [D loss: 0.696758, acc.: 50.20%] [G loss: 0.741772]
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1397 [D loss: 0.683896, acc.: 57.23%] [G loss: 0.747753]
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1398 [D loss: 0.676445, acc.: 58.59%] [G loss: 0.770016]
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1399 [D loss: 0.670814, acc.: 58.98%] [G loss: 0.781036]
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1400 [D loss: 0.676714, acc.: 56.84%] [G loss: 0.783050]
1/1 [==============================] - 0s 21ms/step
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1401 [D loss: 0.666754, acc.: 60.74%] [G loss: 0.801360]
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1402 [D loss: 0.660005, acc.: 61.72%] [G loss: 0.802400]
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1403 [D loss: 0.672955, acc.: 59.38%] [G loss: 0.810371]
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1404 [D loss: 0.681098, acc.: 56.45%] [G loss: 0.790620]
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1405 [D loss: 0.689662, acc.: 53.71%] [G loss: 0.783688]
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1406 [D loss: 0.691438, acc.: 54.30%] [G loss: 0.767179]
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1407 [D loss: 0.700386, acc.: 53.71%] [G loss: 0.750731]
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1408 [D loss: 0.697036, acc.: 52.34%] [G loss: 0.755554]
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1409 [D loss: 0.693689, acc.: 51.56%] [G loss: 0.767039]
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1410 [D loss: 0.683757, acc.: 55.86%] [G loss: 0.768952]
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1411 [D loss: 0.684479, acc.: 58.01%] [G loss: 0.780033]
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1412 [D loss: 0.680511, acc.: 56.05%] [G loss: 0.796001]
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1413 [D loss: 0.668314, acc.: 62.11%] [G loss: 0.789813]
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1414 [D loss: 0.674353, acc.: 56.25%] [G loss: 0.798774]
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1415 [D loss: 0.678359, acc.: 58.79%] [G loss: 0.791133]
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1416 [D loss: 0.682402, acc.: 55.66%] [G loss: 0.769165]
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1417 [D loss: 0.677541, acc.: 56.05%] [G loss: 0.772925]
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1418 [D loss: 0.689707, acc.: 53.71%] [G loss: 0.735485]
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1419 [D loss: 0.680860, acc.: 54.69%] [G loss: 0.739652]
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1420 [D loss: 0.687198, acc.: 53.32%] [G loss: 0.746925]
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1421 [D loss: 0.686231, acc.: 56.45%] [G loss: 0.755775]
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1422 [D loss: 0.671773, acc.: 58.79%] [G loss: 0.770188]
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1423 [D loss: 0.676037, acc.: 56.45%] [G loss: 0.789724]
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1424 [D loss: 0.681227, acc.: 53.71%] [G loss: 0.802201]
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1425 [D loss: 0.692976, acc.: 52.34%] [G loss: 0.795852]
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1426 [D loss: 0.690766, acc.: 53.71%] [G loss: 0.787147]
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1427 [D loss: 0.687610, acc.: 58.01%] [G loss: 0.784366]
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1428 [D loss: 0.683722, acc.: 54.49%] [G loss: 0.783016]
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1429 [D loss: 0.680300, acc.: 55.66%] [G loss: 0.777561]
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1430 [D loss: 0.680570, acc.: 57.62%] [G loss: 0.776434]
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1431 [D loss: 0.668653, acc.: 63.28%] [G loss: 0.775408]
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1432 [D loss: 0.672081, acc.: 57.62%] [G loss: 0.795057]
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1433 [D loss: 0.670659, acc.: 58.98%] [G loss: 0.797545]
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1434 [D loss: 0.671227, acc.: 60.94%] [G loss: 0.788528]
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1435 [D loss: 0.661375, acc.: 60.94%] [G loss: 0.777601]
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1436 [D loss: 0.680049, acc.: 57.03%] [G loss: 0.755415]
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1437 [D loss: 0.688797, acc.: 54.69%] [G loss: 0.753178]
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1438 [D loss: 0.688054, acc.: 53.12%] [G loss: 0.750838]
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1439 [D loss: 0.690587, acc.: 51.17%] [G loss: 0.757229]
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1440 [D loss: 0.681156, acc.: 57.03%] [G loss: 0.756713]
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1441 [D loss: 0.686822, acc.: 50.59%] [G loss: 0.765633]
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1442 [D loss: 0.688501, acc.: 55.86%] [G loss: 0.756559]
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1443 [D loss: 0.689489, acc.: 50.98%] [G loss: 0.761451]
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1444 [D loss: 0.687950, acc.: 47.27%] [G loss: 0.759100]
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1445 [D loss: 0.674731, acc.: 55.86%] [G loss: 0.795456]
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1446 [D loss: 0.671497, acc.: 58.98%] [G loss: 0.813341]
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1447 [D loss: 0.671239, acc.: 57.42%] [G loss: 0.822743]
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1448 [D loss: 0.678869, acc.: 55.47%] [G loss: 0.816108]
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1449 [D loss: 0.677096, acc.: 55.27%] [G loss: 0.809006]
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1450 [D loss: 0.690407, acc.: 52.15%] [G loss: 0.772435]
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1451 [D loss: 0.694126, acc.: 53.52%] [G loss: 0.790290]
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1452 [D loss: 0.686642, acc.: 53.91%] [G loss: 0.756700]
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1453 [D loss: 0.697410, acc.: 54.49%] [G loss: 0.773789]
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1454 [D loss: 0.692138, acc.: 54.10%] [G loss: 0.760613]
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1455 [D loss: 0.689310, acc.: 52.93%] [G loss: 0.763012]
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1456 [D loss: 0.685345, acc.: 54.69%] [G loss: 0.765663]
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1457 [D loss: 0.688504, acc.: 56.05%] [G loss: 0.766857]
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1458 [D loss: 0.689782, acc.: 55.08%] [G loss: 0.765296]
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1459 [D loss: 0.675750, acc.: 57.42%] [G loss: 0.767753]
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1460 [D loss: 0.677240, acc.: 58.01%] [G loss: 0.762146]
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1461 [D loss: 0.676783, acc.: 56.25%] [G loss: 0.745795]
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1462 [D loss: 0.683566, acc.: 53.71%] [G loss: 0.777543]
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1463 [D loss: 0.689707, acc.: 53.32%] [G loss: 0.754087]
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1464 [D loss: 0.683694, acc.: 56.45%] [G loss: 0.762859]
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1465 [D loss: 0.672970, acc.: 54.88%] [G loss: 0.777333]
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1466 [D loss: 0.694254, acc.: 52.15%] [G loss: 0.763718]
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1467 [D loss: 0.686565, acc.: 52.73%] [G loss: 0.776188]
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1468 [D loss: 0.682940, acc.: 56.05%] [G loss: 0.758491]
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1469 [D loss: 0.686668, acc.: 54.88%] [G loss: 0.780812]
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1470 [D loss: 0.689406, acc.: 50.78%] [G loss: 0.791132]
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1471 [D loss: 0.689159, acc.: 52.73%] [G loss: 0.799473]
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1472 [D loss: 0.679035, acc.: 55.08%] [G loss: 0.799998]
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1473 [D loss: 0.677655, acc.: 57.62%] [G loss: 0.804151]
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1474 [D loss: 0.680882, acc.: 54.10%] [G loss: 0.791393]
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1475 [D loss: 0.674956, acc.: 58.20%] [G loss: 0.791999]
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1476 [D loss: 0.676437, acc.: 55.27%] [G loss: 0.787663]
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1477 [D loss: 0.672699, acc.: 56.64%] [G loss: 0.758449]
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1478 [D loss: 0.684027, acc.: 55.47%] [G loss: 0.761870]
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1479 [D loss: 0.684543, acc.: 54.88%] [G loss: 0.736461]
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1480 [D loss: 0.692631, acc.: 52.54%] [G loss: 0.727449]
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1481 [D loss: 0.694781, acc.: 50.98%] [G loss: 0.728513]
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1482 [D loss: 0.696438, acc.: 55.27%] [G loss: 0.756091]
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1483 [D loss: 0.694149, acc.: 51.17%] [G loss: 0.772417]
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1484 [D loss: 0.676125, acc.: 58.20%] [G loss: 0.803646]
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1485 [D loss: 0.662513, acc.: 59.77%] [G loss: 0.812724]
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1486 [D loss: 0.669742, acc.: 60.74%] [G loss: 0.804687]
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1487 [D loss: 0.674415, acc.: 58.40%] [G loss: 0.818576]
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1488 [D loss: 0.668995, acc.: 60.16%] [G loss: 0.793002]
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1489 [D loss: 0.675866, acc.: 58.20%] [G loss: 0.767567]
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1490 [D loss: 0.680525, acc.: 55.66%] [G loss: 0.780012]
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1491 [D loss: 0.695084, acc.: 52.34%] [G loss: 0.784473]
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1492 [D loss: 0.694494, acc.: 52.93%] [G loss: 0.753163]
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1493 [D loss: 0.699840, acc.: 50.00%] [G loss: 0.754761]
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1494 [D loss: 0.683465, acc.: 55.27%] [G loss: 0.759790]
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1495 [D loss: 0.683496, acc.: 56.25%] [G loss: 0.750351]
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1496 [D loss: 0.690499, acc.: 53.52%] [G loss: 0.741071]
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1497 [D loss: 0.682444, acc.: 55.27%] [G loss: 0.766587]
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1498 [D loss: 0.670944, acc.: 61.33%] [G loss: 0.772022]
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1499 [D loss: 0.670966, acc.: 59.96%] [G loss: 0.766630]
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1500 [D loss: 0.685772, acc.: 56.05%] [G loss: 0.780093]
1/1 [==============================] - 0s 19ms/step
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1501 [D loss: 0.673730, acc.: 59.57%] [G loss: 0.785936]
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1502 [D loss: 0.677842, acc.: 56.45%] [G loss: 0.770764]
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1503 [D loss: 0.667569, acc.: 60.55%] [G loss: 0.788538]
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1504 [D loss: 0.681298, acc.: 55.27%] [G loss: 0.781381]
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1505 [D loss: 0.673975, acc.: 58.01%] [G loss: 0.766349]
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1506 [D loss: 0.681148, acc.: 57.81%] [G loss: 0.763743]
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1507 [D loss: 0.682245, acc.: 54.88%] [G loss: 0.740646]
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1508 [D loss: 0.688444, acc.: 54.69%] [G loss: 0.740369]
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1509 [D loss: 0.681380, acc.: 54.30%] [G loss: 0.719517]
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1510 [D loss: 0.685197, acc.: 54.88%] [G loss: 0.726796]
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1511 [D loss: 0.682963, acc.: 54.88%] [G loss: 0.739159]
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1512 [D loss: 0.688944, acc.: 52.73%] [G loss: 0.747108]
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1513 [D loss: 0.692811, acc.: 50.78%] [G loss: 0.740193]
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1514 [D loss: 0.686269, acc.: 53.12%] [G loss: 0.760440]
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1515 [D loss: 0.692811, acc.: 50.39%] [G loss: 0.778116]
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1516 [D loss: 0.678876, acc.: 54.30%] [G loss: 0.812409]
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1517 [D loss: 0.680803, acc.: 56.64%] [G loss: 0.823508]
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1518 [D loss: 0.668084, acc.: 58.79%] [G loss: 0.830723]
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1519 [D loss: 0.677103, acc.: 57.42%] [G loss: 0.806000]
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1520 [D loss: 0.684703, acc.: 54.10%] [G loss: 0.810181]
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1521 [D loss: 0.662634, acc.: 57.62%] [G loss: 0.781624]
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1522 [D loss: 0.700472, acc.: 49.80%] [G loss: 0.766428]
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1523 [D loss: 0.693810, acc.: 54.30%] [G loss: 0.749041]
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1524 [D loss: 0.690869, acc.: 55.08%] [G loss: 0.750637]
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1525 [D loss: 0.690787, acc.: 53.12%] [G loss: 0.757005]
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1526 [D loss: 0.694551, acc.: 52.15%] [G loss: 0.760208]
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1527 [D loss: 0.689731, acc.: 54.88%] [G loss: 0.761418]
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1528 [D loss: 0.675366, acc.: 58.01%] [G loss: 0.769643]
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1529 [D loss: 0.683311, acc.: 53.52%] [G loss: 0.782936]
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1530 [D loss: 0.678125, acc.: 54.10%] [G loss: 0.777104]
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1531 [D loss: 0.671903, acc.: 59.18%] [G loss: 0.771996]
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1532 [D loss: 0.681093, acc.: 53.91%] [G loss: 0.755295]
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1533 [D loss: 0.682117, acc.: 55.27%] [G loss: 0.725903]
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1534 [D loss: 0.682447, acc.: 55.08%] [G loss: 0.737595]
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1535 [D loss: 0.680375, acc.: 54.88%] [G loss: 0.734921]
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1536 [D loss: 0.686144, acc.: 52.73%] [G loss: 0.726772]
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1537 [D loss: 0.708674, acc.: 47.85%] [G loss: 0.741427]
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1538 [D loss: 0.678218, acc.: 56.64%] [G loss: 0.739403]
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1539 [D loss: 0.689268, acc.: 53.52%] [G loss: 0.764568]
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1540 [D loss: 0.681138, acc.: 55.47%] [G loss: 0.785974]
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1541 [D loss: 0.681303, acc.: 53.91%] [G loss: 0.802030]
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1542 [D loss: 0.680979, acc.: 55.66%] [G loss: 0.792349]
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1543 [D loss: 0.680821, acc.: 55.66%] [G loss: 0.780015]
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1544 [D loss: 0.682058, acc.: 56.25%] [G loss: 0.770750]
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1545 [D loss: 0.686160, acc.: 52.93%] [G loss: 0.764252]
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1546 [D loss: 0.686746, acc.: 53.52%] [G loss: 0.754842]
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1547 [D loss: 0.686052, acc.: 53.91%] [G loss: 0.753721]
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1548 [D loss: 0.690697, acc.: 50.59%] [G loss: 0.748691]
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1549 [D loss: 0.689403, acc.: 56.05%] [G loss: 0.747784]
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1550 [D loss: 0.689469, acc.: 53.52%] [G loss: 0.761600]
1/1 [==============================] - 0s 21ms/step
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1551 [D loss: 0.692870, acc.: 52.73%] [G loss: 0.778324]
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1552 [D loss: 0.679309, acc.: 56.64%] [G loss: 0.786371]
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1553 [D loss: 0.689759, acc.: 51.56%] [G loss: 0.775705]
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1554 [D loss: 0.687115, acc.: 52.54%] [G loss: 0.784567]
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1555 [D loss: 0.679161, acc.: 59.57%] [G loss: 0.784183]
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1556 [D loss: 0.674340, acc.: 60.94%] [G loss: 0.781260]
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1557 [D loss: 0.675638, acc.: 57.03%] [G loss: 0.775085]
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1558 [D loss: 0.689603, acc.: 53.12%] [G loss: 0.754749]
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1559 [D loss: 0.684757, acc.: 57.03%] [G loss: 0.737157]
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1560 [D loss: 0.699562, acc.: 51.37%] [G loss: 0.750713]
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1561 [D loss: 0.688670, acc.: 54.49%] [G loss: 0.720140]
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1562 [D loss: 0.681866, acc.: 53.91%] [G loss: 0.729242]
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1563 [D loss: 0.698304, acc.: 49.41%] [G loss: 0.737331]
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1564 [D loss: 0.684964, acc.: 53.91%] [G loss: 0.750704]
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1565 [D loss: 0.690868, acc.: 49.80%] [G loss: 0.742178]
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1566 [D loss: 0.688797, acc.: 53.32%] [G loss: 0.748886]
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1567 [D loss: 0.678604, acc.: 55.86%] [G loss: 0.759523]
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1568 [D loss: 0.673491, acc.: 57.62%] [G loss: 0.754914]
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1569 [D loss: 0.689750, acc.: 54.10%] [G loss: 0.772135]
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1570 [D loss: 0.681075, acc.: 59.18%] [G loss: 0.780869]
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1571 [D loss: 0.671705, acc.: 58.98%] [G loss: 0.826196]
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1572 [D loss: 0.685657, acc.: 56.25%] [G loss: 0.809796]
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1573 [D loss: 0.690303, acc.: 58.79%] [G loss: 0.784261]
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1574 [D loss: 0.685883, acc.: 57.62%] [G loss: 0.786349]
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1575 [D loss: 0.684592, acc.: 53.12%] [G loss: 0.766515]
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1576 [D loss: 0.693800, acc.: 53.52%] [G loss: 0.762067]
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1577 [D loss: 0.700727, acc.: 53.32%] [G loss: 0.765043]
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1578 [D loss: 0.686389, acc.: 53.71%] [G loss: 0.768297]
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1579 [D loss: 0.685162, acc.: 56.25%] [G loss: 0.777996]
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1580 [D loss: 0.683765, acc.: 56.05%] [G loss: 0.777859]
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1581 [D loss: 0.690234, acc.: 56.64%] [G loss: 0.768886]
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1582 [D loss: 0.680270, acc.: 55.47%] [G loss: 0.789324]
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1583 [D loss: 0.674027, acc.: 59.77%] [G loss: 0.782600]
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1584 [D loss: 0.676824, acc.: 57.81%] [G loss: 0.803920]
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1585 [D loss: 0.667428, acc.: 61.52%] [G loss: 0.789774]
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1586 [D loss: 0.672379, acc.: 58.79%] [G loss: 0.774631]
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1587 [D loss: 0.675383, acc.: 59.18%] [G loss: 0.774051]
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1588 [D loss: 0.694594, acc.: 52.73%] [G loss: 0.755329]
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1589 [D loss: 0.682362, acc.: 58.01%] [G loss: 0.728755]
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1590 [D loss: 0.702596, acc.: 53.91%] [G loss: 0.697793]
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1591 [D loss: 0.698316, acc.: 49.22%] [G loss: 0.732023]
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1592 [D loss: 0.711193, acc.: 47.85%] [G loss: 0.732068]
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1593 [D loss: 0.701941, acc.: 50.00%] [G loss: 0.771669]
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1594 [D loss: 0.675690, acc.: 56.45%] [G loss: 0.793140]
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1595 [D loss: 0.683897, acc.: 56.25%] [G loss: 0.820150]
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1596 [D loss: 0.677296, acc.: 59.57%] [G loss: 0.799854]
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1597 [D loss: 0.682510, acc.: 57.42%] [G loss: 0.781635]
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1598 [D loss: 0.691036, acc.: 51.17%] [G loss: 0.777839]
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1599 [D loss: 0.691824, acc.: 52.34%] [G loss: 0.756675]
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1600 [D loss: 0.692803, acc.: 54.30%] [G loss: 0.754577]
1/1 [==============================] - 0s 21ms/step
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1601 [D loss: 0.694473, acc.: 50.39%] [G loss: 0.753286]
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1602 [D loss: 0.699527, acc.: 49.80%] [G loss: 0.751611]
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1603 [D loss: 0.698857, acc.: 52.15%] [G loss: 0.776074]
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1604 [D loss: 0.692645, acc.: 53.52%] [G loss: 0.773733]
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1605 [D loss: 0.680446, acc.: 58.40%] [G loss: 0.786185]
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1606 [D loss: 0.676490, acc.: 59.57%] [G loss: 0.809082]
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1607 [D loss: 0.690506, acc.: 53.91%] [G loss: 0.774443]
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1608 [D loss: 0.678747, acc.: 56.64%] [G loss: 0.771577]
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1609 [D loss: 0.677106, acc.: 60.16%] [G loss: 0.778621]
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1610 [D loss: 0.676648, acc.: 56.25%] [G loss: 0.762808]
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1611 [D loss: 0.690852, acc.: 55.27%] [G loss: 0.751842]
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1612 [D loss: 0.675454, acc.: 56.84%] [G loss: 0.745958]
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1613 [D loss: 0.681563, acc.: 56.64%] [G loss: 0.751171]
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1614 [D loss: 0.683722, acc.: 56.45%] [G loss: 0.757911]
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1615 [D loss: 0.700638, acc.: 50.98%] [G loss: 0.742644]
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1616 [D loss: 0.701518, acc.: 49.61%] [G loss: 0.743392]
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1617 [D loss: 0.692309, acc.: 52.34%] [G loss: 0.741534]
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1618 [D loss: 0.695819, acc.: 52.54%] [G loss: 0.749323]
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1619 [D loss: 0.687575, acc.: 55.66%] [G loss: 0.739284]
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1620 [D loss: 0.691019, acc.: 51.37%] [G loss: 0.748366]
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1621 [D loss: 0.692023, acc.: 54.10%] [G loss: 0.734795]
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1622 [D loss: 0.680543, acc.: 55.66%] [G loss: 0.752190]
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1623 [D loss: 0.672165, acc.: 57.23%] [G loss: 0.765304]
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1624 [D loss: 0.678737, acc.: 53.91%] [G loss: 0.768340]
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1625 [D loss: 0.678501, acc.: 55.47%] [G loss: 0.749559]
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1626 [D loss: 0.682630, acc.: 57.62%] [G loss: 0.752860]
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1627 [D loss: 0.689017, acc.: 55.08%] [G loss: 0.754753]
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1628 [D loss: 0.684077, acc.: 54.88%] [G loss: 0.768467]
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1629 [D loss: 0.687080, acc.: 55.08%] [G loss: 0.765054]
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1630 [D loss: 0.686362, acc.: 56.25%] [G loss: 0.750152]
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1631 [D loss: 0.688883, acc.: 53.71%] [G loss: 0.750307]
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1632 [D loss: 0.703680, acc.: 50.00%] [G loss: 0.741470]
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1633 [D loss: 0.690342, acc.: 54.10%] [G loss: 0.749336]
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1634 [D loss: 0.688010, acc.: 58.01%] [G loss: 0.752321]
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1635 [D loss: 0.684257, acc.: 53.32%] [G loss: 0.739820]
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1636 [D loss: 0.690164, acc.: 52.54%] [G loss: 0.752723]
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1637 [D loss: 0.683559, acc.: 55.47%] [G loss: 0.751001]
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1638 [D loss: 0.683022, acc.: 52.93%] [G loss: 0.752523]
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1639 [D loss: 0.674650, acc.: 60.16%] [G loss: 0.760778]
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1640 [D loss: 0.666444, acc.: 61.72%] [G loss: 0.772274]
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1641 [D loss: 0.676743, acc.: 57.23%] [G loss: 0.749377]
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1642 [D loss: 0.677862, acc.: 55.08%] [G loss: 0.745943]
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1643 [D loss: 0.682823, acc.: 58.20%] [G loss: 0.748991]
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1644 [D loss: 0.679298, acc.: 57.03%] [G loss: 0.760105]
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1645 [D loss: 0.695331, acc.: 51.56%] [G loss: 0.750586]
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1646 [D loss: 0.695989, acc.: 53.12%] [G loss: 0.731034]
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1647 [D loss: 0.683728, acc.: 56.25%] [G loss: 0.719039]
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1648 [D loss: 0.690420, acc.: 51.37%] [G loss: 0.732987]
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1649 [D loss: 0.683935, acc.: 51.95%] [G loss: 0.747254]
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1650 [D loss: 0.692132, acc.: 52.15%] [G loss: 0.756032]
1/1 [==============================] - 0s 22ms/step
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1651 [D loss: 0.685963, acc.: 54.69%] [G loss: 0.760807]
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1652 [D loss: 0.685740, acc.: 56.45%] [G loss: 0.766416]
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1653 [D loss: 0.688114, acc.: 53.12%] [G loss: 0.765034]
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1654 [D loss: 0.688371, acc.: 54.88%] [G loss: 0.768905]
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1655 [D loss: 0.682936, acc.: 52.93%] [G loss: 0.768204]
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1656 [D loss: 0.675479, acc.: 58.20%] [G loss: 0.771150]
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1657 [D loss: 0.676209, acc.: 57.03%] [G loss: 0.753361]
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1658 [D loss: 0.681508, acc.: 56.84%] [G loss: 0.756142]
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1659 [D loss: 0.688970, acc.: 52.54%] [G loss: 0.759518]
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1660 [D loss: 0.690299, acc.: 54.69%] [G loss: 0.746533]
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1661 [D loss: 0.681894, acc.: 58.20%] [G loss: 0.740581]
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1662 [D loss: 0.686175, acc.: 54.88%] [G loss: 0.738866]
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1663 [D loss: 0.682872, acc.: 51.76%] [G loss: 0.724507]
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1664 [D loss: 0.686759, acc.: 55.86%] [G loss: 0.736405]
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1665 [D loss: 0.681889, acc.: 57.42%] [G loss: 0.739861]
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1666 [D loss: 0.673852, acc.: 58.59%] [G loss: 0.736648]
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1667 [D loss: 0.691566, acc.: 51.56%] [G loss: 0.730225]
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1668 [D loss: 0.680519, acc.: 57.23%] [G loss: 0.765138]
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1669 [D loss: 0.675110, acc.: 57.42%] [G loss: 0.764933]
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1670 [D loss: 0.677323, acc.: 56.84%] [G loss: 0.764756]
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1671 [D loss: 0.689457, acc.: 55.47%] [G loss: 0.759093]
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1672 [D loss: 0.687722, acc.: 53.52%] [G loss: 0.751011]
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1673 [D loss: 0.694947, acc.: 51.37%] [G loss: 0.756028]
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1674 [D loss: 0.692938, acc.: 54.69%] [G loss: 0.749713]
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1675 [D loss: 0.688482, acc.: 53.32%] [G loss: 0.755481]
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1676 [D loss: 0.682204, acc.: 55.27%] [G loss: 0.757496]
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1677 [D loss: 0.682141, acc.: 57.42%] [G loss: 0.755869]
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1678 [D loss: 0.680765, acc.: 56.05%] [G loss: 0.760995]
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1679 [D loss: 0.687272, acc.: 55.66%] [G loss: 0.760898]
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1680 [D loss: 0.686251, acc.: 56.64%] [G loss: 0.756215]
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1681 [D loss: 0.692407, acc.: 50.59%] [G loss: 0.772143]
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1682 [D loss: 0.701048, acc.: 49.61%] [G loss: 0.757630]
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1683 [D loss: 0.691282, acc.: 52.15%] [G loss: 0.753175]
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1684 [D loss: 0.692243, acc.: 51.37%] [G loss: 0.757666]
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1685 [D loss: 0.703019, acc.: 47.85%] [G loss: 0.730336]
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1686 [D loss: 0.694866, acc.: 51.37%] [G loss: 0.734193]
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1687 [D loss: 0.688584, acc.: 54.88%] [G loss: 0.747333]
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1688 [D loss: 0.689504, acc.: 54.10%] [G loss: 0.766191]
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1689 [D loss: 0.683298, acc.: 54.49%] [G loss: 0.787864]
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1690 [D loss: 0.664055, acc.: 61.52%] [G loss: 0.789596]
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1691 [D loss: 0.685316, acc.: 56.05%] [G loss: 0.798357]
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1692 [D loss: 0.676650, acc.: 57.42%] [G loss: 0.799378]
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1693 [D loss: 0.686273, acc.: 53.52%] [G loss: 0.767108]
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1694 [D loss: 0.681242, acc.: 55.27%] [G loss: 0.779588]
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1695 [D loss: 0.669418, acc.: 61.72%] [G loss: 0.756219]
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1696 [D loss: 0.684300, acc.: 56.25%] [G loss: 0.742495]
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1697 [D loss: 0.685818, acc.: 57.62%] [G loss: 0.738706]
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1698 [D loss: 0.696946, acc.: 50.39%] [G loss: 0.731284]
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1699 [D loss: 0.690039, acc.: 56.05%] [G loss: 0.730871]
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1700 [D loss: 0.686848, acc.: 58.20%] [G loss: 0.753973]
1/1 [==============================] - 0s 21ms/step
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1701 [D loss: 0.690238, acc.: 53.32%] [G loss: 0.756485]
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1702 [D loss: 0.687629, acc.: 54.10%] [G loss: 0.742224]
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1703 [D loss: 0.682178, acc.: 57.42%] [G loss: 0.760661]
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1704 [D loss: 0.679646, acc.: 57.23%] [G loss: 0.754634]
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1705 [D loss: 0.673755, acc.: 58.79%] [G loss: 0.773510]
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1706 [D loss: 0.681436, acc.: 50.59%] [G loss: 0.767347]
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1707 [D loss: 0.692792, acc.: 54.88%] [G loss: 0.772369]
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1708 [D loss: 0.692181, acc.: 52.73%] [G loss: 0.760444]
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1709 [D loss: 0.694874, acc.: 52.54%] [G loss: 0.749273]
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1710 [D loss: 0.691160, acc.: 53.91%] [G loss: 0.746428]
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1711 [D loss: 0.693388, acc.: 52.54%] [G loss: 0.755767]
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1712 [D loss: 0.692636, acc.: 51.17%] [G loss: 0.791233]
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1713 [D loss: 0.687172, acc.: 53.71%] [G loss: 0.800002]
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1714 [D loss: 0.684876, acc.: 55.47%] [G loss: 0.798943]
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1715 [D loss: 0.692317, acc.: 54.49%] [G loss: 0.789125]
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1716 [D loss: 0.689797, acc.: 53.91%] [G loss: 0.781560]
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1717 [D loss: 0.676425, acc.: 59.38%] [G loss: 0.782633]
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1718 [D loss: 0.670057, acc.: 59.38%] [G loss: 0.798920]
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1719 [D loss: 0.666409, acc.: 63.87%] [G loss: 0.787655]
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1720 [D loss: 0.661227, acc.: 61.91%] [G loss: 0.762482]
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1721 [D loss: 0.679704, acc.: 57.62%] [G loss: 0.791197]
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1722 [D loss: 0.669327, acc.: 58.01%] [G loss: 0.769713]
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1723 [D loss: 0.676951, acc.: 58.01%] [G loss: 0.771522]
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1724 [D loss: 0.685170, acc.: 56.05%] [G loss: 0.740835]
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1725 [D loss: 0.683071, acc.: 52.54%] [G loss: 0.752452]
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1726 [D loss: 0.690677, acc.: 54.10%] [G loss: 0.733188]
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1727 [D loss: 0.693693, acc.: 52.73%] [G loss: 0.715014]
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1728 [D loss: 0.692617, acc.: 51.56%] [G loss: 0.702854]
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1729 [D loss: 0.705097, acc.: 49.41%] [G loss: 0.705066]
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1730 [D loss: 0.696183, acc.: 50.98%] [G loss: 0.703676]
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1731 [D loss: 0.690665, acc.: 54.49%] [G loss: 0.698040]
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1732 [D loss: 0.688556, acc.: 53.12%] [G loss: 0.713292]
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1733 [D loss: 0.677390, acc.: 60.16%] [G loss: 0.756015]
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1734 [D loss: 0.675983, acc.: 55.08%] [G loss: 0.779276]
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1735 [D loss: 0.680732, acc.: 55.47%] [G loss: 0.800269]
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1736 [D loss: 0.669690, acc.: 58.59%] [G loss: 0.834092]
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1737 [D loss: 0.687587, acc.: 50.98%] [G loss: 0.796589]
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1738 [D loss: 0.688537, acc.: 50.00%] [G loss: 0.813741]
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1739 [D loss: 0.685526, acc.: 53.52%] [G loss: 0.816539]
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1740 [D loss: 0.687118, acc.: 54.10%] [G loss: 0.773308]
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1741 [D loss: 0.695637, acc.: 48.24%] [G loss: 0.761298]
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1742 [D loss: 0.701178, acc.: 47.07%] [G loss: 0.751074]
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1743 [D loss: 0.693673, acc.: 50.98%] [G loss: 0.736751]
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1744 [D loss: 0.701829, acc.: 49.80%] [G loss: 0.735732]
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1745 [D loss: 0.693970, acc.: 54.49%] [G loss: 0.746166]
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1746 [D loss: 0.690548, acc.: 51.37%] [G loss: 0.749195]
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1747 [D loss: 0.691489, acc.: 51.37%] [G loss: 0.751306]
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1748 [D loss: 0.687025, acc.: 52.15%] [G loss: 0.756921]
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1749 [D loss: 0.679401, acc.: 57.42%] [G loss: 0.761181]
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1750 [D loss: 0.688291, acc.: 53.71%] [G loss: 0.752820]
1/1 [==============================] - 0s 20ms/step
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1751 [D loss: 0.684937, acc.: 53.32%] [G loss: 0.751402]
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1752 [D loss: 0.689712, acc.: 51.56%] [G loss: 0.759619]
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1753 [D loss: 0.683868, acc.: 54.10%] [G loss: 0.752638]
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1754 [D loss: 0.681555, acc.: 57.42%] [G loss: 0.727771]
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1755 [D loss: 0.670549, acc.: 57.03%] [G loss: 0.743047]
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1756 [D loss: 0.681682, acc.: 54.69%] [G loss: 0.731755]
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1757 [D loss: 0.689563, acc.: 51.56%] [G loss: 0.728584]
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1758 [D loss: 0.679938, acc.: 54.69%] [G loss: 0.725290]
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1759 [D loss: 0.682887, acc.: 55.08%] [G loss: 0.734704]
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1760 [D loss: 0.687904, acc.: 55.66%] [G loss: 0.728663]
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1761 [D loss: 0.685241, acc.: 55.08%] [G loss: 0.732984]
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1762 [D loss: 0.694975, acc.: 49.80%] [G loss: 0.741789]
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1763 [D loss: 0.695095, acc.: 53.12%] [G loss: 0.745389]
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1764 [D loss: 0.696318, acc.: 51.76%] [G loss: 0.747619]
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1765 [D loss: 0.686345, acc.: 49.41%] [G loss: 0.746470]
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1766 [D loss: 0.690655, acc.: 52.34%] [G loss: 0.744314]
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1767 [D loss: 0.698250, acc.: 50.20%] [G loss: 0.751447]
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1768 [D loss: 0.691725, acc.: 49.22%] [G loss: 0.747279]
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1769 [D loss: 0.685438, acc.: 55.66%] [G loss: 0.759031]
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1770 [D loss: 0.688460, acc.: 52.93%] [G loss: 0.759414]
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1771 [D loss: 0.688746, acc.: 54.49%] [G loss: 0.757106]
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1772 [D loss: 0.680461, acc.: 54.88%] [G loss: 0.755772]
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1773 [D loss: 0.693261, acc.: 52.34%] [G loss: 0.756303]
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1774 [D loss: 0.678100, acc.: 57.23%] [G loss: 0.742914]
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1775 [D loss: 0.686088, acc.: 53.32%] [G loss: 0.745797]
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1776 [D loss: 0.679263, acc.: 57.81%] [G loss: 0.745678]
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1777 [D loss: 0.697160, acc.: 49.02%] [G loss: 0.748931]
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1778 [D loss: 0.692637, acc.: 52.15%] [G loss: 0.745868]
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1779 [D loss: 0.696532, acc.: 48.44%] [G loss: 0.735036]
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1780 [D loss: 0.691003, acc.: 52.73%] [G loss: 0.733283]
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1781 [D loss: 0.690677, acc.: 52.34%] [G loss: 0.729780]
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1782 [D loss: 0.686465, acc.: 55.08%] [G loss: 0.751054]
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1783 [D loss: 0.686376, acc.: 53.12%] [G loss: 0.759029]
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1784 [D loss: 0.681452, acc.: 55.08%] [G loss: 0.757403]
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1785 [D loss: 0.686022, acc.: 52.15%] [G loss: 0.765540]
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1786 [D loss: 0.679463, acc.: 55.27%] [G loss: 0.747905]
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1787 [D loss: 0.679010, acc.: 55.27%] [G loss: 0.734260]
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1788 [D loss: 0.681504, acc.: 55.27%] [G loss: 0.756028]
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1789 [D loss: 0.685433, acc.: 55.08%] [G loss: 0.747130]
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1790 [D loss: 0.695245, acc.: 51.17%] [G loss: 0.734692]
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1791 [D loss: 0.688193, acc.: 52.34%] [G loss: 0.738933]
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1792 [D loss: 0.695674, acc.: 51.95%] [G loss: 0.744807]
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1793 [D loss: 0.695061, acc.: 50.78%] [G loss: 0.746470]
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1794 [D loss: 0.690991, acc.: 53.71%] [G loss: 0.754246]
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1795 [D loss: 0.680502, acc.: 54.49%] [G loss: 0.766248]
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1796 [D loss: 0.687131, acc.: 53.91%] [G loss: 0.759530]
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1797 [D loss: 0.676510, acc.: 57.62%] [G loss: 0.762900]
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1798 [D loss: 0.683869, acc.: 55.66%] [G loss: 0.760880]
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1799 [D loss: 0.690064, acc.: 52.54%] [G loss: 0.748323]
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1800 [D loss: 0.684951, acc.: 53.91%] [G loss: 0.749430]
1/1 [==============================] - 0s 21ms/step
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1801 [D loss: 0.694815, acc.: 52.34%] [G loss: 0.742795]
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1802 [D loss: 0.688509, acc.: 53.52%] [G loss: 0.758235]
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1803 [D loss: 0.685448, acc.: 56.84%] [G loss: 0.768308]
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1804 [D loss: 0.682353, acc.: 53.12%] [G loss: 0.767059]
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1805 [D loss: 0.684265, acc.: 56.25%] [G loss: 0.763160]
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1806 [D loss: 0.682278, acc.: 54.30%] [G loss: 0.762242]
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1807 [D loss: 0.686705, acc.: 53.52%] [G loss: 0.758309]
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1808 [D loss: 0.694760, acc.: 50.98%] [G loss: 0.755810]
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1809 [D loss: 0.683571, acc.: 55.08%] [G loss: 0.743134]
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1810 [D loss: 0.699562, acc.: 49.41%] [G loss: 0.736348]
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1811 [D loss: 0.691026, acc.: 54.30%] [G loss: 0.723835]
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1812 [D loss: 0.691745, acc.: 52.15%] [G loss: 0.758659]
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1813 [D loss: 0.687762, acc.: 53.71%] [G loss: 0.758459]
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1814 [D loss: 0.697624, acc.: 51.76%] [G loss: 0.750517]
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1815 [D loss: 0.676319, acc.: 57.81%] [G loss: 0.739312]
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1816 [D loss: 0.683717, acc.: 53.32%] [G loss: 0.738433]
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1817 [D loss: 0.690086, acc.: 52.34%] [G loss: 0.737192]
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1818 [D loss: 0.689232, acc.: 51.95%] [G loss: 0.735562]
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1819 [D loss: 0.687324, acc.: 53.71%] [G loss: 0.731234]
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1820 [D loss: 0.695907, acc.: 50.59%] [G loss: 0.724637]
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1821 [D loss: 0.686622, acc.: 53.12%] [G loss: 0.736341]
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1822 [D loss: 0.686563, acc.: 55.66%] [G loss: 0.747617]
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1823 [D loss: 0.690353, acc.: 50.20%] [G loss: 0.759095]
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1824 [D loss: 0.698294, acc.: 51.56%] [G loss: 0.783271]
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1825 [D loss: 0.689583, acc.: 53.71%] [G loss: 0.778842]
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1826 [D loss: 0.681720, acc.: 54.49%] [G loss: 0.762445]
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1827 [D loss: 0.690206, acc.: 52.54%] [G loss: 0.754893]
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1828 [D loss: 0.688104, acc.: 54.88%] [G loss: 0.738981]
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1829 [D loss: 0.697742, acc.: 51.76%] [G loss: 0.749199]
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1830 [D loss: 0.699621, acc.: 48.83%] [G loss: 0.751137]
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1831 [D loss: 0.695359, acc.: 51.76%] [G loss: 0.741574]
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1832 [D loss: 0.687331, acc.: 51.95%] [G loss: 0.757509]
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1833 [D loss: 0.693320, acc.: 53.71%] [G loss: 0.755824]
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1834 [D loss: 0.688813, acc.: 54.88%] [G loss: 0.753488]
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1835 [D loss: 0.681657, acc.: 56.45%] [G loss: 0.781504]
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1836 [D loss: 0.682057, acc.: 55.27%] [G loss: 0.763235]
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1837 [D loss: 0.687122, acc.: 54.49%] [G loss: 0.772502]
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1838 [D loss: 0.682709, acc.: 56.45%] [G loss: 0.757675]
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1839 [D loss: 0.690537, acc.: 53.32%] [G loss: 0.748359]
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1840 [D loss: 0.690177, acc.: 52.54%] [G loss: 0.743004]
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1841 [D loss: 0.693615, acc.: 51.95%] [G loss: 0.730058]
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1842 [D loss: 0.678482, acc.: 55.27%] [G loss: 0.732631]
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1843 [D loss: 0.690003, acc.: 53.32%] [G loss: 0.717187]
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1844 [D loss: 0.697154, acc.: 52.73%] [G loss: 0.728434]
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1845 [D loss: 0.690752, acc.: 53.71%] [G loss: 0.720905]
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1846 [D loss: 0.684518, acc.: 53.32%] [G loss: 0.725100]
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1847 [D loss: 0.691576, acc.: 52.15%] [G loss: 0.727732]
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1848 [D loss: 0.688825, acc.: 52.93%] [G loss: 0.738403]
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1849 [D loss: 0.684589, acc.: 57.42%] [G loss: 0.732466]
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1850 [D loss: 0.691709, acc.: 51.95%] [G loss: 0.745170]
1/1 [==============================] - 0s 20ms/step
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1851 [D loss: 0.691598, acc.: 55.27%] [G loss: 0.752328]
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1852 [D loss: 0.684323, acc.: 54.49%] [G loss: 0.775920]
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1853 [D loss: 0.684386, acc.: 54.88%] [G loss: 0.748277]
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1854 [D loss: 0.692504, acc.: 54.49%] [G loss: 0.750186]
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1855 [D loss: 0.691657, acc.: 52.93%] [G loss: 0.753385]
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1856 [D loss: 0.686975, acc.: 54.49%] [G loss: 0.739536]
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1857 [D loss: 0.697497, acc.: 51.17%] [G loss: 0.748215]
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1858 [D loss: 0.688298, acc.: 53.71%] [G loss: 0.765785]
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1859 [D loss: 0.681058, acc.: 54.30%] [G loss: 0.772979]
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1860 [D loss: 0.701274, acc.: 48.24%] [G loss: 0.774084]
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1861 [D loss: 0.680302, acc.: 56.05%] [G loss: 0.750594]
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1862 [D loss: 0.686287, acc.: 54.88%] [G loss: 0.747905]
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1863 [D loss: 0.691246, acc.: 55.27%] [G loss: 0.764275]
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1864 [D loss: 0.682101, acc.: 57.62%] [G loss: 0.762288]
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1865 [D loss: 0.688261, acc.: 52.93%] [G loss: 0.767086]
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1866 [D loss: 0.691432, acc.: 54.49%] [G loss: 0.741440]
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1867 [D loss: 0.686127, acc.: 51.95%] [G loss: 0.735997]
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1868 [D loss: 0.679812, acc.: 55.86%] [G loss: 0.729027]
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1869 [D loss: 0.686755, acc.: 52.93%] [G loss: 0.739272]
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1870 [D loss: 0.689345, acc.: 52.73%] [G loss: 0.739584]
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1871 [D loss: 0.689003, acc.: 54.30%] [G loss: 0.746121]
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1872 [D loss: 0.693215, acc.: 54.88%] [G loss: 0.744744]
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1873 [D loss: 0.678121, acc.: 56.84%] [G loss: 0.730115]
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1874 [D loss: 0.688775, acc.: 53.32%] [G loss: 0.743262]
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1875 [D loss: 0.687405, acc.: 52.54%] [G loss: 0.729850]
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1876 [D loss: 0.694640, acc.: 52.73%] [G loss: 0.727154]
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1877 [D loss: 0.699891, acc.: 52.93%] [G loss: 0.735930]
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1878 [D loss: 0.690376, acc.: 52.54%] [G loss: 0.729076]
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1879 [D loss: 0.695982, acc.: 55.66%] [G loss: 0.738271]
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1880 [D loss: 0.689550, acc.: 51.95%] [G loss: 0.749105]
8/8 [==============================] - 0s 4ms/step
1881 [D loss: 0.691186, acc.: 50.39%] [G loss: 0.745366]
8/8 [==============================] - 0s 4ms/step
1882 [D loss: 0.686067, acc.: 56.25%] [G loss: 0.768350]
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1883 [D loss: 0.688013, acc.: 52.54%] [G loss: 0.772109]
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1884 [D loss: 0.679698, acc.: 56.84%] [G loss: 0.774520]
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1885 [D loss: 0.685540, acc.: 52.93%] [G loss: 0.768115]
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1886 [D loss: 0.686199, acc.: 53.32%] [G loss: 0.755362]
8/8 [==============================] - 0s 4ms/step
1887 [D loss: 0.681501, acc.: 55.86%] [G loss: 0.753651]
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1888 [D loss: 0.678355, acc.: 56.64%] [G loss: 0.754580]
8/8 [==============================] - 0s 4ms/step
1889 [D loss: 0.693482, acc.: 50.20%] [G loss: 0.763027]
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1890 [D loss: 0.691470, acc.: 52.93%] [G loss: 0.761031]
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1891 [D loss: 0.672393, acc.: 62.11%] [G loss: 0.747775]
8/8 [==============================] - 0s 4ms/step
1892 [D loss: 0.695428, acc.: 51.76%] [G loss: 0.734779]
8/8 [==============================] - 0s 4ms/step
1893 [D loss: 0.681749, acc.: 53.32%] [G loss: 0.736024]
8/8 [==============================] - 0s 4ms/step
1894 [D loss: 0.693878, acc.: 54.30%] [G loss: 0.710167]
8/8 [==============================] - 0s 4ms/step
1895 [D loss: 0.692773, acc.: 53.12%] [G loss: 0.720386]
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1896 [D loss: 0.698591, acc.: 49.80%] [G loss: 0.720128]
8/8 [==============================] - 0s 4ms/step
1897 [D loss: 0.686695, acc.: 54.10%] [G loss: 0.724145]
8/8 [==============================] - 0s 4ms/step
1898 [D loss: 0.693992, acc.: 53.12%] [G loss: 0.734718]
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1899 [D loss: 0.694114, acc.: 51.95%] [G loss: 0.728403]
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1900 [D loss: 0.696178, acc.: 51.76%] [G loss: 0.741197]
1/1 [==============================] - 0s 21ms/step
8/8 [==============================] - 0s 4ms/step
1901 [D loss: 0.692277, acc.: 54.88%] [G loss: 0.736151]
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1902 [D loss: 0.685687, acc.: 56.05%] [G loss: 0.734097]
8/8 [==============================] - 0s 4ms/step
1903 [D loss: 0.679481, acc.: 56.84%] [G loss: 0.751931]
8/8 [==============================] - 0s 4ms/step
1904 [D loss: 0.682559, acc.: 57.81%] [G loss: 0.751274]
8/8 [==============================] - 0s 4ms/step
1905 [D loss: 0.680833, acc.: 56.84%] [G loss: 0.754587]
8/8 [==============================] - 0s 4ms/step
1906 [D loss: 0.686470, acc.: 55.47%] [G loss: 0.759557]
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1907 [D loss: 0.685869, acc.: 55.66%] [G loss: 0.762615]
8/8 [==============================] - 0s 4ms/step
1908 [D loss: 0.685926, acc.: 54.49%] [G loss: 0.745827]
8/8 [==============================] - 0s 4ms/step
1909 [D loss: 0.693524, acc.: 49.80%] [G loss: 0.743797]
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1910 [D loss: 0.685457, acc.: 55.08%] [G loss: 0.729608]
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1911 [D loss: 0.684482, acc.: 54.49%] [G loss: 0.729262]
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1912 [D loss: 0.685595, acc.: 54.10%] [G loss: 0.737887]
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1913 [D loss: 0.690964, acc.: 51.37%] [G loss: 0.743540]
8/8 [==============================] - 0s 4ms/step
1914 [D loss: 0.689449, acc.: 53.12%] [G loss: 0.742914]
8/8 [==============================] - 0s 4ms/step
1915 [D loss: 0.700092, acc.: 50.39%] [G loss: 0.743989]
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1916 [D loss: 0.693377, acc.: 52.15%] [G loss: 0.737404]
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1917 [D loss: 0.694746, acc.: 51.56%] [G loss: 0.744813]
8/8 [==============================] - 0s 4ms/step
1918 [D loss: 0.684045, acc.: 54.69%] [G loss: 0.752495]
8/8 [==============================] - 0s 4ms/step
1919 [D loss: 0.677166, acc.: 57.81%] [G loss: 0.749740]
8/8 [==============================] - 0s 4ms/step
1920 [D loss: 0.680821, acc.: 55.66%] [G loss: 0.760068]
8/8 [==============================] - 0s 4ms/step
1921 [D loss: 0.674912, acc.: 59.96%] [G loss: 0.759567]
8/8 [==============================] - 0s 4ms/step
1922 [D loss: 0.684341, acc.: 57.62%] [G loss: 0.752337]
8/8 [==============================] - 0s 4ms/step
1923 [D loss: 0.682669, acc.: 55.47%] [G loss: 0.741124]
8/8 [==============================] - 0s 4ms/step
1924 [D loss: 0.685319, acc.: 52.34%] [G loss: 0.737981]
8/8 [==============================] - 0s 4ms/step
1925 [D loss: 0.703047, acc.: 50.78%] [G loss: 0.719208]
8/8 [==============================] - 0s 4ms/step
1926 [D loss: 0.696673, acc.: 47.27%] [G loss: 0.722107]
8/8 [==============================] - 0s 4ms/step
1927 [D loss: 0.691661, acc.: 50.39%] [G loss: 0.735813]
8/8 [==============================] - 0s 4ms/step
1928 [D loss: 0.697499, acc.: 50.00%] [G loss: 0.714410]
8/8 [==============================] - 0s 4ms/step
1929 [D loss: 0.695273, acc.: 50.20%] [G loss: 0.718020]
8/8 [==============================] - 0s 4ms/step
1930 [D loss: 0.699151, acc.: 49.80%] [G loss: 0.713954]
8/8 [==============================] - 0s 4ms/step
1931 [D loss: 0.697594, acc.: 50.98%] [G loss: 0.737762]
8/8 [==============================] - 0s 4ms/step
1932 [D loss: 0.687835, acc.: 50.98%] [G loss: 0.736194]
8/8 [==============================] - 0s 4ms/step
1933 [D loss: 0.695041, acc.: 49.41%] [G loss: 0.752190]
8/8 [==============================] - 0s 4ms/step
1934 [D loss: 0.678966, acc.: 57.23%] [G loss: 0.743676]
8/8 [==============================] - 0s 4ms/step
1935 [D loss: 0.677590, acc.: 56.64%] [G loss: 0.774258]
8/8 [==============================] - 0s 4ms/step
1936 [D loss: 0.675203, acc.: 57.42%] [G loss: 0.770455]
8/8 [==============================] - 0s 4ms/step
1937 [D loss: 0.683090, acc.: 54.49%] [G loss: 0.768475]
8/8 [==============================] - 0s 4ms/step
1938 [D loss: 0.675763, acc.: 59.96%] [G loss: 0.773069]
8/8 [==============================] - 0s 4ms/step
1939 [D loss: 0.675008, acc.: 58.01%] [G loss: 0.763725]
8/8 [==============================] - 0s 4ms/step
1940 [D loss: 0.684286, acc.: 55.27%] [G loss: 0.740865]
8/8 [==============================] - 0s 4ms/step
1941 [D loss: 0.686024, acc.: 54.69%] [G loss: 0.740424]
8/8 [==============================] - 0s 4ms/step
1942 [D loss: 0.691841, acc.: 50.98%] [G loss: 0.728667]
8/8 [==============================] - 0s 4ms/step
1943 [D loss: 0.687457, acc.: 51.95%] [G loss: 0.724908]
8/8 [==============================] - 0s 4ms/step
1944 [D loss: 0.700152, acc.: 51.37%] [G loss: 0.729142]
8/8 [==============================] - 0s 4ms/step
1945 [D loss: 0.706582, acc.: 49.41%] [G loss: 0.721950]
8/8 [==============================] - 0s 4ms/step
1946 [D loss: 0.697782, acc.: 50.00%] [G loss: 0.729078]
8/8 [==============================] - 0s 4ms/step
1947 [D loss: 0.689365, acc.: 51.76%] [G loss: 0.739615]
8/8 [==============================] - 0s 4ms/step
1948 [D loss: 0.687890, acc.: 56.25%] [G loss: 0.738269]
8/8 [==============================] - 0s 4ms/step
1949 [D loss: 0.678161, acc.: 56.25%] [G loss: 0.736977]
8/8 [==============================] - 0s 4ms/step
1950 [D loss: 0.690199, acc.: 54.10%] [G loss: 0.759706]
1/1 [==============================] - 0s 20ms/step
8/8 [==============================] - 0s 4ms/step
1951 [D loss: 0.679298, acc.: 55.08%] [G loss: 0.737901]
8/8 [==============================] - 0s 4ms/step
1952 [D loss: 0.685754, acc.: 52.54%] [G loss: 0.748520]
8/8 [==============================] - 0s 4ms/step
1953 [D loss: 0.679719, acc.: 58.98%] [G loss: 0.737493]
8/8 [==============================] - 0s 4ms/step
1954 [D loss: 0.676513, acc.: 55.08%] [G loss: 0.745670]
8/8 [==============================] - 0s 4ms/step
1955 [D loss: 0.675634, acc.: 59.38%] [G loss: 0.757908]
8/8 [==============================] - 0s 4ms/step
1956 [D loss: 0.684776, acc.: 55.47%] [G loss: 0.752612]
8/8 [==============================] - 0s 4ms/step
1957 [D loss: 0.704665, acc.: 45.31%] [G loss: 0.758670]
8/8 [==============================] - 0s 4ms/step
1958 [D loss: 0.689484, acc.: 56.05%] [G loss: 0.769328]
8/8 [==============================] - 0s 4ms/step
1959 [D loss: 0.683337, acc.: 57.23%] [G loss: 0.745021]
8/8 [==============================] - 0s 4ms/step
1960 [D loss: 0.690964, acc.: 51.95%] [G loss: 0.747798]
8/8 [==============================] - 0s 4ms/step
1961 [D loss: 0.683159, acc.: 57.03%] [G loss: 0.747019]
8/8 [==============================] - 0s 4ms/step
1962 [D loss: 0.687710, acc.: 56.45%] [G loss: 0.715832]
8/8 [==============================] - 0s 4ms/step
1963 [D loss: 0.694924, acc.: 49.41%] [G loss: 0.725426]
8/8 [==============================] - 0s 4ms/step
1964 [D loss: 0.687074, acc.: 52.93%] [G loss: 0.737816]
8/8 [==============================] - 0s 4ms/step
1965 [D loss: 0.697838, acc.: 50.59%] [G loss: 0.753732]
8/8 [==============================] - 0s 4ms/step
1966 [D loss: 0.685905, acc.: 53.71%] [G loss: 0.745854]
8/8 [==============================] - 0s 4ms/step
1967 [D loss: 0.685308, acc.: 53.32%] [G loss: 0.766801]
8/8 [==============================] - 0s 4ms/step
1968 [D loss: 0.692337, acc.: 54.88%] [G loss: 0.746888]
8/8 [==============================] - 0s 4ms/step
1969 [D loss: 0.683072, acc.: 53.12%] [G loss: 0.763551]
8/8 [==============================] - 0s 4ms/step
1970 [D loss: 0.680435, acc.: 56.84%] [G loss: 0.761927]
8/8 [==============================] - 0s 4ms/step
1971 [D loss: 0.688419, acc.: 55.47%] [G loss: 0.753503]
8/8 [==============================] - 0s 4ms/step
1972 [D loss: 0.693994, acc.: 52.34%] [G loss: 0.740773]
8/8 [==============================] - 0s 4ms/step
1973 [D loss: 0.687871, acc.: 54.10%] [G loss: 0.741343]
8/8 [==============================] - 0s 4ms/step
1974 [D loss: 0.693276, acc.: 52.73%] [G loss: 0.736276]
8/8 [==============================] - 0s 4ms/step
1975 [D loss: 0.692456, acc.: 49.61%] [G loss: 0.739767]
8/8 [==============================] - 0s 4ms/step
1976 [D loss: 0.687416, acc.: 52.93%] [G loss: 0.732858]
8/8 [==============================] - 0s 4ms/step
1977 [D loss: 0.688730, acc.: 51.17%] [G loss: 0.749710]
8/8 [==============================] - 0s 4ms/step
1978 [D loss: 0.692615, acc.: 50.59%] [G loss: 0.748755]
8/8 [==============================] - 0s 4ms/step
1979 [D loss: 0.674819, acc.: 57.03%] [G loss: 0.755942]
8/8 [==============================] - 0s 4ms/step
1980 [D loss: 0.681646, acc.: 54.88%] [G loss: 0.763949]
8/8 [==============================] - 0s 4ms/step
1981 [D loss: 0.673985, acc.: 60.55%] [G loss: 0.745419]
8/8 [==============================] - 0s 4ms/step
1982 [D loss: 0.681771, acc.: 56.05%] [G loss: 0.740750]
8/8 [==============================] - 0s 4ms/step
1983 [D loss: 0.686635, acc.: 56.05%] [G loss: 0.762256]
8/8 [==============================] - 0s 4ms/step
1984 [D loss: 0.692574, acc.: 51.17%] [G loss: 0.752590]
8/8 [==============================] - 0s 4ms/step
1985 [D loss: 0.677478, acc.: 57.42%] [G loss: 0.741965]
8/8 [==============================] - 0s 4ms/step
1986 [D loss: 0.692901, acc.: 52.73%] [G loss: 0.726953]
8/8 [==============================] - 0s 4ms/step
1987 [D loss: 0.697951, acc.: 50.00%] [G loss: 0.717300]
8/8 [==============================] - 0s 4ms/step
1988 [D loss: 0.697589, acc.: 45.90%] [G loss: 0.712467]
8/8 [==============================] - 0s 4ms/step
1989 [D loss: 0.695610, acc.: 50.00%] [G loss: 0.733858]
8/8 [==============================] - 0s 4ms/step
1990 [D loss: 0.689705, acc.: 52.15%] [G loss: 0.736290]
8/8 [==============================] - 0s 4ms/step
1991 [D loss: 0.686030, acc.: 54.10%] [G loss: 0.756537]
8/8 [==============================] - 0s 4ms/step
1992 [D loss: 0.683805, acc.: 54.69%] [G loss: 0.779878]
8/8 [==============================] - 0s 4ms/step
1993 [D loss: 0.677605, acc.: 55.86%] [G loss: 0.788546]
8/8 [==============================] - 0s 4ms/step
1994 [D loss: 0.687377, acc.: 53.91%] [G loss: 0.775388]
8/8 [==============================] - 0s 4ms/step
1995 [D loss: 0.678463, acc.: 56.64%] [G loss: 0.758408]
8/8 [==============================] - 0s 4ms/step
1996 [D loss: 0.684967, acc.: 55.47%] [G loss: 0.757939]
8/8 [==============================] - 0s 4ms/step
1997 [D loss: 0.686037, acc.: 53.91%] [G loss: 0.739258]
8/8 [==============================] - 0s 4ms/step
1998 [D loss: 0.682809, acc.: 55.08%] [G loss: 0.736024]
8/8 [==============================] - 0s 4ms/step
1999 [D loss: 0.698442, acc.: 52.15%] [G loss: 0.731341]
8/8 [==============================] - 0s 4ms/step
2000 [D loss: 0.699983, acc.: 49.61%] [G loss: 0.739874]
1/1 [==============================] - 0s 25ms/step
8/8 [==============================] - 0s 4ms/step
2001 [D loss: 0.706990, acc.: 46.29%] [G loss: 0.753512]
8/8 [==============================] - 0s 4ms/step
2002 [D loss: 0.689429, acc.: 51.17%] [G loss: 0.758571]
8/8 [==============================] - 0s 4ms/step
2003 [D loss: 0.680823, acc.: 53.71%] [G loss: 0.755154]
8/8 [==============================] - 0s 4ms/step
2004 [D loss: 0.688307, acc.: 52.93%] [G loss: 0.779858]
8/8 [==============================] - 0s 4ms/step
2005 [D loss: 0.686737, acc.: 56.05%] [G loss: 0.757499]
8/8 [==============================] - 0s 4ms/step
2006 [D loss: 0.681372, acc.: 54.88%] [G loss: 0.757828]
8/8 [==============================] - 0s 4ms/step
2007 [D loss: 0.682024, acc.: 56.84%] [G loss: 0.746352]
8/8 [==============================] - 0s 4ms/step
2008 [D loss: 0.683478, acc.: 55.66%] [G loss: 0.751572]
8/8 [==============================] - 0s 4ms/step
2009 [D loss: 0.679324, acc.: 58.79%] [G loss: 0.749280]
8/8 [==============================] - 0s 4ms/step
2010 [D loss: 0.679374, acc.: 55.47%] [G loss: 0.755502]
8/8 [==============================] - 0s 4ms/step
2011 [D loss: 0.681640, acc.: 54.30%] [G loss: 0.748585]
8/8 [==============================] - 0s 4ms/step
2012 [D loss: 0.688975, acc.: 54.88%] [G loss: 0.749746]
8/8 [==============================] - 0s 4ms/step
2013 [D loss: 0.689645, acc.: 53.91%] [G loss: 0.755592]
8/8 [==============================] - 0s 4ms/step
2014 [D loss: 0.682034, acc.: 56.05%] [G loss: 0.740943]
8/8 [==============================] - 0s 4ms/step
2015 [D loss: 0.699135, acc.: 48.83%] [G loss: 0.733110]
8/8 [==============================] - 0s 4ms/step
2016 [D loss: 0.701937, acc.: 49.61%] [G loss: 0.731112]
8/8 [==============================] - 0s 4ms/step
2017 [D loss: 0.696651, acc.: 51.17%] [G loss: 0.741240]
8/8 [==============================] - 0s 4ms/step
2018 [D loss: 0.701771, acc.: 48.05%] [G loss: 0.724466]
8/8 [==============================] - 0s 4ms/step
2019 [D loss: 0.693276, acc.: 48.83%] [G loss: 0.732270]
8/8 [==============================] - 0s 4ms/step
2020 [D loss: 0.694508, acc.: 50.78%] [G loss: 0.744953]
8/8 [==============================] - 0s 4ms/step
2021 [D loss: 0.683677, acc.: 54.30%] [G loss: 0.759256]
8/8 [==============================] - 0s 4ms/step
2022 [D loss: 0.685666, acc.: 55.86%] [G loss: 0.773113]
8/8 [==============================] - 0s 4ms/step
2023 [D loss: 0.687927, acc.: 54.10%] [G loss: 0.769420]
8/8 [==============================] - 0s 4ms/step
2024 [D loss: 0.669459, acc.: 58.20%] [G loss: 0.773166]
8/8 [==============================] - 0s 4ms/step
2025 [D loss: 0.675117, acc.: 59.96%] [G loss: 0.765925]
8/8 [==============================] - 0s 4ms/step
2026 [D loss: 0.682740, acc.: 56.64%] [G loss: 0.757431]
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2027 [D loss: 0.684721, acc.: 54.69%] [G loss: 0.736189]
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2028 [D loss: 0.685815, acc.: 53.52%] [G loss: 0.735096]
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2029 [D loss: 0.697270, acc.: 50.00%] [G loss: 0.729625]
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2030 [D loss: 0.696363, acc.: 52.93%] [G loss: 0.734352]
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2031 [D loss: 0.704149, acc.: 47.66%] [G loss: 0.736393]
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2032 [D loss: 0.696656, acc.: 51.56%] [G loss: 0.744745]
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2033 [D loss: 0.695068, acc.: 50.20%] [G loss: 0.763613]
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2034 [D loss: 0.689963, acc.: 53.52%] [G loss: 0.749699]
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2035 [D loss: 0.690012, acc.: 53.12%] [G loss: 0.763485]
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2036 [D loss: 0.683466, acc.: 58.79%] [G loss: 0.750442]
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2037 [D loss: 0.680304, acc.: 56.25%] [G loss: 0.758417]
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2038 [D loss: 0.675821, acc.: 57.42%] [G loss: 0.758312]
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2039 [D loss: 0.677244, acc.: 59.38%] [G loss: 0.750520]
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2040 [D loss: 0.677217, acc.: 55.27%] [G loss: 0.754704]
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2041 [D loss: 0.670692, acc.: 57.81%] [G loss: 0.757867]
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2042 [D loss: 0.676561, acc.: 56.64%] [G loss: 0.761207]
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2043 [D loss: 0.668122, acc.: 60.74%] [G loss: 0.746672]
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2044 [D loss: 0.683049, acc.: 55.66%] [G loss: 0.744436]
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2045 [D loss: 0.678581, acc.: 57.23%] [G loss: 0.723265]
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2046 [D loss: 0.695149, acc.: 52.54%] [G loss: 0.730917]
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2047 [D loss: 0.682813, acc.: 56.45%] [G loss: 0.732997]
8/8 [==============================] - 0s 4ms/step
2048 [D loss: 0.698528, acc.: 52.93%] [G loss: 0.724379]
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2049 [D loss: 0.700357, acc.: 50.59%] [G loss: 0.725702]
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2050 [D loss: 0.700799, acc.: 49.41%] [G loss: 0.719780]
1/1 [==============================] - 0s 20ms/step
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2051 [D loss: 0.699258, acc.: 51.76%] [G loss: 0.729967]
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2052 [D loss: 0.689639, acc.: 54.49%] [G loss: 0.757815]
8/8 [==============================] - 0s 4ms/step
2053 [D loss: 0.687846, acc.: 54.30%] [G loss: 0.760389]
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2054 [D loss: 0.689988, acc.: 55.27%] [G loss: 0.753077]
8/8 [==============================] - 0s 4ms/step
2055 [D loss: 0.688381, acc.: 52.34%] [G loss: 0.763413]
8/8 [==============================] - 0s 4ms/step
2056 [D loss: 0.681592, acc.: 56.45%] [G loss: 0.758754]
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2057 [D loss: 0.692551, acc.: 49.61%] [G loss: 0.778032]
8/8 [==============================] - 0s 4ms/step
2058 [D loss: 0.687019, acc.: 54.10%] [G loss: 0.773283]
8/8 [==============================] - 0s 4ms/step
2059 [D loss: 0.687932, acc.: 52.15%] [G loss: 0.758551]
8/8 [==============================] - 0s 4ms/step
2060 [D loss: 0.686334, acc.: 53.91%] [G loss: 0.770993]
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2061 [D loss: 0.675102, acc.: 59.57%] [G loss: 0.777850]
8/8 [==============================] - 0s 4ms/step
2062 [D loss: 0.700172, acc.: 51.37%] [G loss: 0.757098]
8/8 [==============================] - 0s 4ms/step
2063 [D loss: 0.690116, acc.: 55.66%] [G loss: 0.763927]
8/8 [==============================] - 0s 4ms/step
2064 [D loss: 0.694452, acc.: 53.32%] [G loss: 0.764073]
8/8 [==============================] - 0s 4ms/step
2065 [D loss: 0.689336, acc.: 54.49%] [G loss: 0.771205]
8/8 [==============================] - 0s 4ms/step
2066 [D loss: 0.686142, acc.: 52.93%] [G loss: 0.768147]
8/8 [==============================] - 0s 4ms/step
2067 [D loss: 0.694834, acc.: 52.73%] [G loss: 0.768857]
8/8 [==============================] - 0s 4ms/step
2068 [D loss: 0.688148, acc.: 54.10%] [G loss: 0.755195]
8/8 [==============================] - 0s 4ms/step
2069 [D loss: 0.687864, acc.: 53.71%] [G loss: 0.759247]
8/8 [==============================] - 0s 4ms/step
2070 [D loss: 0.689136, acc.: 52.34%] [G loss: 0.743789]
8/8 [==============================] - 0s 4ms/step
2071 [D loss: 0.689914, acc.: 54.49%] [G loss: 0.749468]
8/8 [==============================] - 0s 4ms/step
2072 [D loss: 0.680661, acc.: 53.91%] [G loss: 0.737314]
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2073 [D loss: 0.686445, acc.: 56.64%] [G loss: 0.753191]
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2074 [D loss: 0.680427, acc.: 56.05%] [G loss: 0.740860]
8/8 [==============================] - 0s 4ms/step
2075 [D loss: 0.692313, acc.: 51.37%] [G loss: 0.746421]
8/8 [==============================] - 0s 4ms/step
2076 [D loss: 0.683897, acc.: 51.17%] [G loss: 0.734302]
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2077 [D loss: 0.691003, acc.: 51.37%] [G loss: 0.734236]
8/8 [==============================] - 0s 4ms/step
2078 [D loss: 0.684359, acc.: 54.49%] [G loss: 0.735330]
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2079 [D loss: 0.690489, acc.: 54.69%] [G loss: 0.759849]
8/8 [==============================] - 0s 4ms/step
2080 [D loss: 0.686446, acc.: 53.32%] [G loss: 0.741857]
8/8 [==============================] - 0s 4ms/step
2081 [D loss: 0.684847, acc.: 53.32%] [G loss: 0.766830]
8/8 [==============================] - 0s 4ms/step
2082 [D loss: 0.691700, acc.: 53.32%] [G loss: 0.757412]
8/8 [==============================] - 0s 4ms/step
2083 [D loss: 0.672991, acc.: 58.79%] [G loss: 0.769977]
8/8 [==============================] - 0s 4ms/step
2084 [D loss: 0.690000, acc.: 52.15%] [G loss: 0.768443]
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2085 [D loss: 0.694462, acc.: 51.76%] [G loss: 0.757270]
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2086 [D loss: 0.680389, acc.: 56.45%] [G loss: 0.758195]
8/8 [==============================] - 0s 4ms/step
2087 [D loss: 0.684021, acc.: 57.42%] [G loss: 0.750926]
8/8 [==============================] - 0s 4ms/step
2088 [D loss: 0.697555, acc.: 52.73%] [G loss: 0.747426]
8/8 [==============================] - 0s 4ms/step
2089 [D loss: 0.695979, acc.: 50.00%] [G loss: 0.758218]
8/8 [==============================] - 0s 4ms/step
2090 [D loss: 0.692173, acc.: 50.39%] [G loss: 0.752770]
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2091 [D loss: 0.696438, acc.: 50.20%] [G loss: 0.744013]
8/8 [==============================] - 0s 4ms/step
2092 [D loss: 0.690775, acc.: 55.08%] [G loss: 0.756310]
8/8 [==============================] - 0s 4ms/step
2093 [D loss: 0.694786, acc.: 50.20%] [G loss: 0.754324]
8/8 [==============================] - 0s 4ms/step
2094 [D loss: 0.695187, acc.: 50.00%] [G loss: 0.750190]
8/8 [==============================] - 0s 4ms/step
2095 [D loss: 0.687048, acc.: 51.76%] [G loss: 0.760516]
8/8 [==============================] - 0s 4ms/step
2096 [D loss: 0.692039, acc.: 52.73%] [G loss: 0.750782]
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2097 [D loss: 0.687067, acc.: 53.91%] [G loss: 0.737909]
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2098 [D loss: 0.686989, acc.: 53.91%] [G loss: 0.739353]
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2099 [D loss: 0.688645, acc.: 52.93%] [G loss: 0.730046]
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2100 [D loss: 0.689774, acc.: 49.02%] [G loss: 0.735239]
1/1 [==============================] - 0s 21ms/step
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2101 [D loss: 0.693249, acc.: 50.20%] [G loss: 0.740249]
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2102 [D loss: 0.692099, acc.: 52.15%] [G loss: 0.735911]
8/8 [==============================] - 0s 4ms/step
2103 [D loss: 0.687774, acc.: 54.88%] [G loss: 0.734525]
8/8 [==============================] - 0s 4ms/step
2104 [D loss: 0.687322, acc.: 53.12%] [G loss: 0.740194]
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2105 [D loss: 0.690175, acc.: 53.32%] [G loss: 0.731377]
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2106 [D loss: 0.690529, acc.: 52.93%] [G loss: 0.731322]
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2107 [D loss: 0.685973, acc.: 52.73%] [G loss: 0.738267]
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2108 [D loss: 0.689005, acc.: 53.52%] [G loss: 0.730938]
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2109 [D loss: 0.685991, acc.: 52.34%] [G loss: 0.743514]
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2110 [D loss: 0.688924, acc.: 53.91%] [G loss: 0.755234]
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2111 [D loss: 0.688010, acc.: 53.52%] [G loss: 0.751278]
8/8 [==============================] - 0s 4ms/step
2112 [D loss: 0.693113, acc.: 52.93%] [G loss: 0.748322]
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2113 [D loss: 0.692899, acc.: 48.83%] [G loss: 0.736392]
8/8 [==============================] - 0s 4ms/step
2114 [D loss: 0.694027, acc.: 50.20%] [G loss: 0.740237]
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2115 [D loss: 0.696637, acc.: 50.59%] [G loss: 0.734156]
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2116 [D loss: 0.691015, acc.: 52.54%] [G loss: 0.738436]
8/8 [==============================] - 0s 4ms/step
2117 [D loss: 0.681543, acc.: 57.42%] [G loss: 0.737924]
8/8 [==============================] - 0s 4ms/step
2118 [D loss: 0.688437, acc.: 53.71%] [G loss: 0.732964]
8/8 [==============================] - 0s 4ms/step
2119 [D loss: 0.693033, acc.: 51.95%] [G loss: 0.739940]
8/8 [==============================] - 0s 4ms/step
2120 [D loss: 0.688051, acc.: 53.12%] [G loss: 0.738443]
8/8 [==============================] - 0s 4ms/step
2121 [D loss: 0.690201, acc.: 50.59%] [G loss: 0.747963]
8/8 [==============================] - 0s 4ms/step
2122 [D loss: 0.683967, acc.: 54.30%] [G loss: 0.762442]
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2123 [D loss: 0.674387, acc.: 54.30%] [G loss: 0.759399]
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2124 [D loss: 0.692723, acc.: 50.00%] [G loss: 0.751166]
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2125 [D loss: 0.685752, acc.: 53.32%] [G loss: 0.736146]
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2126 [D loss: 0.694690, acc.: 52.73%] [G loss: 0.732539]
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2127 [D loss: 0.688423, acc.: 52.34%] [G loss: 0.739888]
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2128 [D loss: 0.688572, acc.: 53.91%] [G loss: 0.719326]
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2129 [D loss: 0.696600, acc.: 48.83%] [G loss: 0.734147]
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2130 [D loss: 0.685055, acc.: 53.71%] [G loss: 0.738136]
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2131 [D loss: 0.692965, acc.: 52.34%] [G loss: 0.742345]
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2132 [D loss: 0.686484, acc.: 51.37%] [G loss: 0.729356]
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2133 [D loss: 0.689702, acc.: 53.52%] [G loss: 0.744273]
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2134 [D loss: 0.695878, acc.: 49.22%] [G loss: 0.740327]
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2135 [D loss: 0.701581, acc.: 48.05%] [G loss: 0.723249]
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2136 [D loss: 0.686964, acc.: 53.32%] [G loss: 0.736823]
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2137 [D loss: 0.691650, acc.: 53.12%] [G loss: 0.742968]
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2138 [D loss: 0.681798, acc.: 52.34%] [G loss: 0.747672]
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2139 [D loss: 0.690581, acc.: 50.39%] [G loss: 0.743077]
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2140 [D loss: 0.682768, acc.: 55.66%] [G loss: 0.751456]
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2141 [D loss: 0.689469, acc.: 53.52%] [G loss: 0.746475]
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2142 [D loss: 0.692064, acc.: 51.37%] [G loss: 0.754034]
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2143 [D loss: 0.695920, acc.: 51.17%] [G loss: 0.752895]
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2144 [D loss: 0.695907, acc.: 52.93%] [G loss: 0.733981]
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2145 [D loss: 0.696779, acc.: 50.98%] [G loss: 0.741217]
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2146 [D loss: 0.689873, acc.: 55.47%] [G loss: 0.741513]
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2147 [D loss: 0.685681, acc.: 54.49%] [G loss: 0.742574]
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2148 [D loss: 0.685864, acc.: 54.88%] [G loss: 0.736512]
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2149 [D loss: 0.684042, acc.: 55.86%] [G loss: 0.739167]
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2150 [D loss: 0.684944, acc.: 52.54%] [G loss: 0.753168]
1/1 [==============================] - 0s 21ms/step
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2151 [D loss: 0.682218, acc.: 55.47%] [G loss: 0.736164]
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2152 [D loss: 0.693858, acc.: 51.17%] [G loss: 0.733634]
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2153 [D loss: 0.699528, acc.: 48.63%] [G loss: 0.721034]
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2154 [D loss: 0.689365, acc.: 49.41%] [G loss: 0.725810]
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2155 [D loss: 0.698491, acc.: 50.20%] [G loss: 0.724405]
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2156 [D loss: 0.695212, acc.: 48.63%] [G loss: 0.733814]
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2157 [D loss: 0.685169, acc.: 53.52%] [G loss: 0.736480]
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2158 [D loss: 0.686012, acc.: 53.71%] [G loss: 0.741501]
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2159 [D loss: 0.689159, acc.: 54.69%] [G loss: 0.759140]
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2160 [D loss: 0.685020, acc.: 55.47%] [G loss: 0.762607]
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2161 [D loss: 0.682580, acc.: 57.42%] [G loss: 0.775480]
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2162 [D loss: 0.681925, acc.: 55.86%] [G loss: 0.761084]
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2163 [D loss: 0.681755, acc.: 54.69%] [G loss: 0.749210]
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2164 [D loss: 0.681924, acc.: 53.12%] [G loss: 0.739176]
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2165 [D loss: 0.687918, acc.: 56.05%] [G loss: 0.728227]
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2166 [D loss: 0.690460, acc.: 52.15%] [G loss: 0.724774]
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2167 [D loss: 0.693465, acc.: 50.98%] [G loss: 0.711206]
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2168 [D loss: 0.696417, acc.: 49.02%] [G loss: 0.723560]
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2169 [D loss: 0.698197, acc.: 51.17%] [G loss: 0.732307]
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2170 [D loss: 0.693534, acc.: 51.95%] [G loss: 0.753981]
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2171 [D loss: 0.705895, acc.: 47.46%] [G loss: 0.743799]
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2172 [D loss: 0.699084, acc.: 47.46%] [G loss: 0.732167]
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2173 [D loss: 0.692738, acc.: 53.91%] [G loss: 0.746185]
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2174 [D loss: 0.699305, acc.: 49.02%] [G loss: 0.730655]
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2175 [D loss: 0.692407, acc.: 50.20%] [G loss: 0.731400]
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2176 [D loss: 0.689363, acc.: 53.32%] [G loss: 0.734936]
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2177 [D loss: 0.684363, acc.: 58.20%] [G loss: 0.739378]
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2178 [D loss: 0.677686, acc.: 59.57%] [G loss: 0.755464]
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2179 [D loss: 0.692832, acc.: 50.98%] [G loss: 0.747537]
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2180 [D loss: 0.683091, acc.: 55.86%] [G loss: 0.748510]
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2181 [D loss: 0.684892, acc.: 53.52%] [G loss: 0.741200]
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2182 [D loss: 0.690834, acc.: 52.93%] [G loss: 0.728179]
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2183 [D loss: 0.685851, acc.: 55.47%] [G loss: 0.722228]
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2184 [D loss: 0.689604, acc.: 51.37%] [G loss: 0.724670]
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2185 [D loss: 0.695601, acc.: 48.83%] [G loss: 0.715430]
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2186 [D loss: 0.691553, acc.: 50.39%] [G loss: 0.708292]
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2187 [D loss: 0.697351, acc.: 50.98%] [G loss: 0.722464]
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2188 [D loss: 0.692002, acc.: 48.24%] [G loss: 0.729794]
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2189 [D loss: 0.695254, acc.: 50.98%] [G loss: 0.737219]
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2190 [D loss: 0.691240, acc.: 50.39%] [G loss: 0.745134]
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2191 [D loss: 0.681347, acc.: 57.23%] [G loss: 0.751286]
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2192 [D loss: 0.682934, acc.: 56.64%] [G loss: 0.761184]
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2193 [D loss: 0.682032, acc.: 57.81%] [G loss: 0.755647]
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2194 [D loss: 0.685410, acc.: 55.47%] [G loss: 0.749983]
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2195 [D loss: 0.679955, acc.: 56.45%] [G loss: 0.750416]
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2196 [D loss: 0.688184, acc.: 52.54%] [G loss: 0.740414]
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2197 [D loss: 0.691642, acc.: 52.54%] [G loss: 0.746116]
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2198 [D loss: 0.692144, acc.: 51.95%] [G loss: 0.731372]
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2199 [D loss: 0.691063, acc.: 51.76%] [G loss: 0.727375]
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2200 [D loss: 0.689975, acc.: 52.34%] [G loss: 0.731627]
1/1 [==============================] - 0s 19ms/step
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2201 [D loss: 0.686613, acc.: 52.34%] [G loss: 0.728742]
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2202 [D loss: 0.698604, acc.: 50.78%] [G loss: 0.739296]
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2203 [D loss: 0.685521, acc.: 54.49%] [G loss: 0.753353]
8/8 [==============================] - 0s 4ms/step
2204 [D loss: 0.687894, acc.: 52.34%] [G loss: 0.750505]
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2205 [D loss: 0.681553, acc.: 54.49%] [G loss: 0.739412]
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2206 [D loss: 0.671654, acc.: 60.94%] [G loss: 0.749719]
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2207 [D loss: 0.686889, acc.: 52.73%] [G loss: 0.739552]
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2208 [D loss: 0.693118, acc.: 50.00%] [G loss: 0.746320]
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2209 [D loss: 0.679579, acc.: 57.23%] [G loss: 0.751161]
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2210 [D loss: 0.692472, acc.: 53.91%] [G loss: 0.743720]
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2211 [D loss: 0.691485, acc.: 49.80%] [G loss: 0.743012]
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2212 [D loss: 0.699005, acc.: 48.83%] [G loss: 0.738730]
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2213 [D loss: 0.687388, acc.: 55.08%] [G loss: 0.735961]
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2214 [D loss: 0.698289, acc.: 48.63%] [G loss: 0.744403]
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2215 [D loss: 0.689330, acc.: 54.10%] [G loss: 0.737584]
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2216 [D loss: 0.687927, acc.: 55.08%] [G loss: 0.738266]
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2217 [D loss: 0.687459, acc.: 50.59%] [G loss: 0.732723]
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2218 [D loss: 0.685331, acc.: 54.49%] [G loss: 0.739799]
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2219 [D loss: 0.686839, acc.: 50.59%] [G loss: 0.736824]
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2220 [D loss: 0.700698, acc.: 48.24%] [G loss: 0.730632]
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2221 [D loss: 0.695411, acc.: 50.78%] [G loss: 0.718797]
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2222 [D loss: 0.687010, acc.: 56.25%] [G loss: 0.735380]
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2223 [D loss: 0.686175, acc.: 52.73%] [G loss: 0.728089]
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2224 [D loss: 0.692422, acc.: 53.91%] [G loss: 0.741762]
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2225 [D loss: 0.684491, acc.: 54.69%] [G loss: 0.727365]
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2226 [D loss: 0.692737, acc.: 51.37%] [G loss: 0.733286]
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2227 [D loss: 0.689161, acc.: 51.56%] [G loss: 0.727183]
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2228 [D loss: 0.685311, acc.: 54.88%] [G loss: 0.718340]
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2229 [D loss: 0.693909, acc.: 52.93%] [G loss: 0.720752]
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2230 [D loss: 0.690007, acc.: 51.56%] [G loss: 0.720472]
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2231 [D loss: 0.683392, acc.: 55.47%] [G loss: 0.728122]
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2232 [D loss: 0.696435, acc.: 50.98%] [G loss: 0.747406]
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2233 [D loss: 0.695191, acc.: 55.27%] [G loss: 0.755438]
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2234 [D loss: 0.690698, acc.: 50.78%] [G loss: 0.767160]
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2235 [D loss: 0.688922, acc.: 52.54%] [G loss: 0.771424]
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2236 [D loss: 0.684083, acc.: 56.05%] [G loss: 0.783367]
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2237 [D loss: 0.687479, acc.: 55.27%] [G loss: 0.753074]
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2238 [D loss: 0.688893, acc.: 55.08%] [G loss: 0.748309]
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2239 [D loss: 0.681746, acc.: 57.62%] [G loss: 0.759502]
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2240 [D loss: 0.686566, acc.: 53.32%] [G loss: 0.750980]
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2241 [D loss: 0.685942, acc.: 53.91%] [G loss: 0.741152]
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2242 [D loss: 0.695392, acc.: 49.80%] [G loss: 0.726596]
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2243 [D loss: 0.699473, acc.: 50.98%] [G loss: 0.732761]
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2244 [D loss: 0.691112, acc.: 53.32%] [G loss: 0.728316]
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2245 [D loss: 0.704894, acc.: 47.27%] [G loss: 0.733859]
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2246 [D loss: 0.694112, acc.: 50.20%] [G loss: 0.745334]
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2247 [D loss: 0.686947, acc.: 55.47%] [G loss: 0.739150]
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2248 [D loss: 0.690852, acc.: 50.39%] [G loss: 0.740826]
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2249 [D loss: 0.689365, acc.: 51.76%] [G loss: 0.746190]
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2250 [D loss: 0.688001, acc.: 52.73%] [G loss: 0.740892]
1/1 [==============================] - 0s 21ms/step
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2251 [D loss: 0.692925, acc.: 51.76%] [G loss: 0.751281]
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2252 [D loss: 0.677149, acc.: 58.40%] [G loss: 0.752388]
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2253 [D loss: 0.685825, acc.: 57.62%] [G loss: 0.742530]
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2254 [D loss: 0.682519, acc.: 55.86%] [G loss: 0.721867]
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2255 [D loss: 0.690709, acc.: 53.52%] [G loss: 0.721403]
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2256 [D loss: 0.693104, acc.: 51.37%] [G loss: 0.714564]
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2257 [D loss: 0.692141, acc.: 52.15%] [G loss: 0.729226]
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2258 [D loss: 0.702643, acc.: 49.22%] [G loss: 0.721712]
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2259 [D loss: 0.687316, acc.: 52.54%] [G loss: 0.739187]
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2260 [D loss: 0.696943, acc.: 49.22%] [G loss: 0.757033]
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2261 [D loss: 0.692867, acc.: 49.61%] [G loss: 0.751550]
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2262 [D loss: 0.691022, acc.: 52.15%] [G loss: 0.744755]
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2263 [D loss: 0.697370, acc.: 50.98%] [G loss: 0.740656]
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2264 [D loss: 0.692005, acc.: 52.73%] [G loss: 0.731446]
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2265 [D loss: 0.693565, acc.: 54.30%] [G loss: 0.739491]
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2266 [D loss: 0.683063, acc.: 53.91%] [G loss: 0.738693]
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2267 [D loss: 0.692188, acc.: 56.05%] [G loss: 0.737333]
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2268 [D loss: 0.684245, acc.: 53.71%] [G loss: 0.755068]
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2269 [D loss: 0.694304, acc.: 51.76%] [G loss: 0.758208]
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2270 [D loss: 0.689050, acc.: 54.10%] [G loss: 0.756201]
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2271 [D loss: 0.684791, acc.: 54.88%] [G loss: 0.746171]
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2272 [D loss: 0.699824, acc.: 49.80%] [G loss: 0.749133]
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2273 [D loss: 0.698082, acc.: 50.00%] [G loss: 0.738965]
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2274 [D loss: 0.688523, acc.: 54.49%] [G loss: 0.742663]
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2275 [D loss: 0.692283, acc.: 51.56%] [G loss: 0.736454]
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2276 [D loss: 0.688265, acc.: 55.47%] [G loss: 0.730567]
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2277 [D loss: 0.694335, acc.: 52.15%] [G loss: 0.729669]
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2278 [D loss: 0.694289, acc.: 50.39%] [G loss: 0.725133]
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2279 [D loss: 0.690896, acc.: 54.69%] [G loss: 0.736360]
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2280 [D loss: 0.688691, acc.: 53.12%] [G loss: 0.730609]
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2281 [D loss: 0.693332, acc.: 53.52%] [G loss: 0.735949]
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2282 [D loss: 0.695640, acc.: 49.22%] [G loss: 0.719253]
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2283 [D loss: 0.686514, acc.: 56.25%] [G loss: 0.732629]
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2284 [D loss: 0.699988, acc.: 49.61%] [G loss: 0.729536]
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2285 [D loss: 0.687579, acc.: 54.88%] [G loss: 0.739562]
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2286 [D loss: 0.691851, acc.: 53.71%] [G loss: 0.732004]
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2287 [D loss: 0.698383, acc.: 51.56%] [G loss: 0.729448]
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2288 [D loss: 0.688119, acc.: 53.32%] [G loss: 0.735760]
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2289 [D loss: 0.695010, acc.: 52.93%] [G loss: 0.731764]
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2290 [D loss: 0.699344, acc.: 49.02%] [G loss: 0.721685]
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2291 [D loss: 0.699618, acc.: 49.61%] [G loss: 0.727756]
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2292 [D loss: 0.683768, acc.: 56.45%] [G loss: 0.729213]
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2293 [D loss: 0.690228, acc.: 52.15%] [G loss: 0.725975]
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2294 [D loss: 0.703539, acc.: 48.83%] [G loss: 0.724463]
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2295 [D loss: 0.695059, acc.: 49.41%] [G loss: 0.740390]
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2296 [D loss: 0.680818, acc.: 55.86%] [G loss: 0.740037]
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2297 [D loss: 0.689502, acc.: 54.69%] [G loss: 0.744202]
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2298 [D loss: 0.674968, acc.: 59.38%] [G loss: 0.745080]
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2299 [D loss: 0.686567, acc.: 52.93%] [G loss: 0.736888]
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2300 [D loss: 0.682017, acc.: 56.05%] [G loss: 0.735846]
1/1 [==============================] - 0s 23ms/step
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2301 [D loss: 0.689538, acc.: 52.15%] [G loss: 0.745220]
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2302 [D loss: 0.684846, acc.: 54.30%] [G loss: 0.730599]
8/8 [==============================] - 0s 4ms/step
2303 [D loss: 0.692297, acc.: 51.95%] [G loss: 0.729275]
8/8 [==============================] - 0s 4ms/step
2304 [D loss: 0.692614, acc.: 52.54%] [G loss: 0.724052]
8/8 [==============================] - 0s 4ms/step
2305 [D loss: 0.695862, acc.: 50.98%] [G loss: 0.728139]
8/8 [==============================] - 0s 4ms/step
2306 [D loss: 0.698145, acc.: 50.59%] [G loss: 0.728565]
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2307 [D loss: 0.689998, acc.: 51.37%] [G loss: 0.724432]
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2308 [D loss: 0.701232, acc.: 49.02%] [G loss: 0.724212]
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2309 [D loss: 0.694249, acc.: 52.73%] [G loss: 0.726171]
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2310 [D loss: 0.696566, acc.: 51.56%] [G loss: 0.728707]
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2311 [D loss: 0.693915, acc.: 51.17%] [G loss: 0.725721]
8/8 [==============================] - 0s 4ms/step
2312 [D loss: 0.688244, acc.: 55.86%] [G loss: 0.723595]
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2313 [D loss: 0.691489, acc.: 50.59%] [G loss: 0.725465]
8/8 [==============================] - 0s 4ms/step
2314 [D loss: 0.693140, acc.: 52.34%] [G loss: 0.735034]
8/8 [==============================] - 0s 4ms/step
2315 [D loss: 0.684583, acc.: 54.49%] [G loss: 0.744675]
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2316 [D loss: 0.689557, acc.: 53.71%] [G loss: 0.739895]
8/8 [==============================] - 0s 4ms/step
2317 [D loss: 0.691323, acc.: 50.20%] [G loss: 0.747483]
8/8 [==============================] - 0s 4ms/step
2318 [D loss: 0.699568, acc.: 50.20%] [G loss: 0.733949]
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2319 [D loss: 0.695067, acc.: 46.48%] [G loss: 0.731859]
8/8 [==============================] - 0s 4ms/step
2320 [D loss: 0.692185, acc.: 52.15%] [G loss: 0.731763]
8/8 [==============================] - 0s 4ms/step
2321 [D loss: 0.689067, acc.: 56.25%] [G loss: 0.736974]
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2322 [D loss: 0.688779, acc.: 54.69%] [G loss: 0.741748]
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2323 [D loss: 0.691071, acc.: 53.71%] [G loss: 0.731503]
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2324 [D loss: 0.700666, acc.: 51.17%] [G loss: 0.728815]
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2325 [D loss: 0.698914, acc.: 48.63%] [G loss: 0.717231]
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2326 [D loss: 0.693921, acc.: 51.17%] [G loss: 0.726232]
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2327 [D loss: 0.695215, acc.: 51.17%] [G loss: 0.717751]
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2328 [D loss: 0.688214, acc.: 52.73%] [G loss: 0.728152]
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2329 [D loss: 0.687661, acc.: 54.30%] [G loss: 0.731031]
8/8 [==============================] - 0s 4ms/step
2330 [D loss: 0.682750, acc.: 55.08%] [G loss: 0.727249]
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2331 [D loss: 0.687246, acc.: 52.93%] [G loss: 0.732953]
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2332 [D loss: 0.690805, acc.: 53.32%] [G loss: 0.736436]
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2333 [D loss: 0.689201, acc.: 53.32%] [G loss: 0.735003]
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2334 [D loss: 0.684753, acc.: 55.66%] [G loss: 0.739961]
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2335 [D loss: 0.696353, acc.: 50.59%] [G loss: 0.747183]
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2336 [D loss: 0.691194, acc.: 51.37%] [G loss: 0.740535]
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2337 [D loss: 0.697425, acc.: 53.71%] [G loss: 0.738451]
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2338 [D loss: 0.684900, acc.: 52.54%] [G loss: 0.738021]
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2339 [D loss: 0.695120, acc.: 50.00%] [G loss: 0.727265]
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2340 [D loss: 0.690749, acc.: 52.34%] [G loss: 0.738903]
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2341 [D loss: 0.690183, acc.: 53.91%] [G loss: 0.726503]
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2342 [D loss: 0.697410, acc.: 47.46%] [G loss: 0.714505]
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2343 [D loss: 0.696165, acc.: 49.22%] [G loss: 0.727479]
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2344 [D loss: 0.687070, acc.: 53.52%] [G loss: 0.732329]
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2345 [D loss: 0.698289, acc.: 47.85%] [G loss: 0.744034]
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2346 [D loss: 0.679126, acc.: 55.08%] [G loss: 0.736608]
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2347 [D loss: 0.683787, acc.: 55.27%] [G loss: 0.736260]
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2348 [D loss: 0.689068, acc.: 53.12%] [G loss: 0.743644]
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2349 [D loss: 0.687736, acc.: 56.45%] [G loss: 0.727878]
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2350 [D loss: 0.693137, acc.: 50.59%] [G loss: 0.733572]
1/1 [==============================] - 0s 30ms/step
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2351 [D loss: 0.702926, acc.: 47.66%] [G loss: 0.736386]
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2352 [D loss: 0.692214, acc.: 50.39%] [G loss: 0.742365]
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2353 [D loss: 0.692409, acc.: 52.34%] [G loss: 0.735547]
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2354 [D loss: 0.694316, acc.: 54.30%] [G loss: 0.735507]
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2355 [D loss: 0.697577, acc.: 50.98%] [G loss: 0.724563]
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2356 [D loss: 0.695532, acc.: 51.37%] [G loss: 0.735145]
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2357 [D loss: 0.699187, acc.: 51.37%] [G loss: 0.731635]
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2358 [D loss: 0.697646, acc.: 47.27%] [G loss: 0.725796]
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2359 [D loss: 0.688195, acc.: 52.73%] [G loss: 0.737413]
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2360 [D loss: 0.691006, acc.: 52.34%] [G loss: 0.738362]
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2361 [D loss: 0.678625, acc.: 58.79%] [G loss: 0.741774]
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2362 [D loss: 0.685201, acc.: 51.17%] [G loss: 0.740214]
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2363 [D loss: 0.683282, acc.: 54.30%] [G loss: 0.734261]
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2364 [D loss: 0.685191, acc.: 51.95%] [G loss: 0.732965]
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2365 [D loss: 0.693549, acc.: 50.78%] [G loss: 0.739693]
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2366 [D loss: 0.685768, acc.: 53.91%] [G loss: 0.729880]
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2367 [D loss: 0.692558, acc.: 51.56%] [G loss: 0.719821]
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2368 [D loss: 0.693818, acc.: 47.66%] [G loss: 0.707110]
8/8 [==============================] - 0s 4ms/step
2369 [D loss: 0.689401, acc.: 51.95%] [G loss: 0.698131]
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2370 [D loss: 0.706250, acc.: 46.09%] [G loss: 0.708073]
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2371 [D loss: 0.694407, acc.: 50.98%] [G loss: 0.718669]
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2372 [D loss: 0.687061, acc.: 53.71%] [G loss: 0.729419]
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2373 [D loss: 0.690652, acc.: 54.10%] [G loss: 0.740559]
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2374 [D loss: 0.679607, acc.: 58.01%] [G loss: 0.753318]
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2375 [D loss: 0.682417, acc.: 57.81%] [G loss: 0.758610]
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2376 [D loss: 0.689725, acc.: 55.08%] [G loss: 0.753214]
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2377 [D loss: 0.677147, acc.: 59.18%] [G loss: 0.757448]
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2378 [D loss: 0.682228, acc.: 56.84%] [G loss: 0.745105]
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2379 [D loss: 0.691632, acc.: 52.93%] [G loss: 0.738822]
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2380 [D loss: 0.691130, acc.: 52.54%] [G loss: 0.740130]
8/8 [==============================] - 0s 4ms/step
2381 [D loss: 0.697579, acc.: 52.93%] [G loss: 0.719850]
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2382 [D loss: 0.689965, acc.: 53.12%] [G loss: 0.720073]
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2383 [D loss: 0.701773, acc.: 49.02%] [G loss: 0.733755]
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2384 [D loss: 0.695811, acc.: 49.80%] [G loss: 0.761410]
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2385 [D loss: 0.695278, acc.: 49.02%] [G loss: 0.758684]
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2386 [D loss: 0.692770, acc.: 54.10%] [G loss: 0.748637]
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2387 [D loss: 0.698055, acc.: 49.41%] [G loss: 0.749246]
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2388 [D loss: 0.679590, acc.: 55.08%] [G loss: 0.743528]
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2389 [D loss: 0.693621, acc.: 52.34%] [G loss: 0.744257]
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2390 [D loss: 0.687361, acc.: 53.91%] [G loss: 0.740265]
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2391 [D loss: 0.691880, acc.: 48.44%] [G loss: 0.718750]
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2392 [D loss: 0.698268, acc.: 49.22%] [G loss: 0.738301]
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2393 [D loss: 0.691518, acc.: 53.12%] [G loss: 0.727446]
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2394 [D loss: 0.690008, acc.: 52.93%] [G loss: 0.735870]
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2395 [D loss: 0.690510, acc.: 53.91%] [G loss: 0.735800]
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2396 [D loss: 0.682884, acc.: 58.59%] [G loss: 0.727038]
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2397 [D loss: 0.704294, acc.: 47.46%] [G loss: 0.729726]
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2398 [D loss: 0.693666, acc.: 48.63%] [G loss: 0.745934]
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2399 [D loss: 0.694374, acc.: 52.34%] [G loss: 0.736827]
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2400 [D loss: 0.689935, acc.: 52.15%] [G loss: 0.744075]
1/1 [==============================] - 0s 36ms/step
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2401 [D loss: 0.690776, acc.: 53.91%] [G loss: 0.757933]
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2402 [D loss: 0.690767, acc.: 53.12%] [G loss: 0.750641]
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2403 [D loss: 0.685958, acc.: 54.30%] [G loss: 0.755983]
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2404 [D loss: 0.691932, acc.: 52.73%] [G loss: 0.755156]
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2405 [D loss: 0.692368, acc.: 54.88%] [G loss: 0.758565]
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2406 [D loss: 0.686463, acc.: 52.73%] [G loss: 0.739357]
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2407 [D loss: 0.686424, acc.: 54.30%] [G loss: 0.732867]
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2408 [D loss: 0.681746, acc.: 58.98%] [G loss: 0.729964]
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2409 [D loss: 0.686364, acc.: 56.84%] [G loss: 0.709720]
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2410 [D loss: 0.690312, acc.: 51.76%] [G loss: 0.717626]
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2411 [D loss: 0.693574, acc.: 53.12%] [G loss: 0.720873]
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2412 [D loss: 0.688862, acc.: 51.37%] [G loss: 0.729898]
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2413 [D loss: 0.690891, acc.: 51.76%] [G loss: 0.724781]
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2414 [D loss: 0.693362, acc.: 53.32%] [G loss: 0.750532]
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2415 [D loss: 0.683008, acc.: 58.20%] [G loss: 0.738971]
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2416 [D loss: 0.680934, acc.: 55.86%] [G loss: 0.749716]
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2417 [D loss: 0.678126, acc.: 57.81%] [G loss: 0.756295]
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2418 [D loss: 0.678487, acc.: 57.81%] [G loss: 0.751822]
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2419 [D loss: 0.693481, acc.: 55.47%] [G loss: 0.757620]
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2420 [D loss: 0.678757, acc.: 57.03%] [G loss: 0.742669]
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2421 [D loss: 0.694737, acc.: 51.17%] [G loss: 0.729792]
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2422 [D loss: 0.702336, acc.: 49.22%] [G loss: 0.722616]
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2423 [D loss: 0.701864, acc.: 48.83%] [G loss: 0.710288]
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2424 [D loss: 0.695613, acc.: 53.52%] [G loss: 0.710771]
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2425 [D loss: 0.701839, acc.: 48.83%] [G loss: 0.727282]
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2426 [D loss: 0.691740, acc.: 54.69%] [G loss: 0.718216]
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2427 [D loss: 0.699444, acc.: 49.22%] [G loss: 0.747201]
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2428 [D loss: 0.691139, acc.: 51.17%] [G loss: 0.737981]
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2429 [D loss: 0.687667, acc.: 53.12%] [G loss: 0.750360]
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2430 [D loss: 0.685872, acc.: 55.47%] [G loss: 0.761981]
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2431 [D loss: 0.690307, acc.: 52.93%] [G loss: 0.754575]
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2432 [D loss: 0.683136, acc.: 56.05%] [G loss: 0.749631]
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2433 [D loss: 0.680888, acc.: 55.47%] [G loss: 0.751696]
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2434 [D loss: 0.681269, acc.: 57.42%] [G loss: 0.737130]
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2435 [D loss: 0.671787, acc.: 59.96%] [G loss: 0.750355]
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2436 [D loss: 0.689676, acc.: 54.10%] [G loss: 0.737410]
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2437 [D loss: 0.692815, acc.: 55.66%] [G loss: 0.738126]
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2438 [D loss: 0.686584, acc.: 56.64%] [G loss: 0.724814]
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2439 [D loss: 0.692959, acc.: 57.03%] [G loss: 0.733733]
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2440 [D loss: 0.708534, acc.: 47.66%] [G loss: 0.734266]
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2441 [D loss: 0.699783, acc.: 51.56%] [G loss: 0.730378]
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2442 [D loss: 0.693177, acc.: 51.56%] [G loss: 0.745193]
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2443 [D loss: 0.693403, acc.: 50.78%] [G loss: 0.721071]
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2444 [D loss: 0.685435, acc.: 55.27%] [G loss: 0.740189]
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2445 [D loss: 0.696465, acc.: 50.98%] [G loss: 0.738198]
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2446 [D loss: 0.679453, acc.: 57.42%] [G loss: 0.732400]
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2447 [D loss: 0.693344, acc.: 53.71%] [G loss: 0.730947]
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2448 [D loss: 0.682041, acc.: 56.64%] [G loss: 0.752794]
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2449 [D loss: 0.688914, acc.: 55.08%] [G loss: 0.751921]
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2450 [D loss: 0.693701, acc.: 52.15%] [G loss: 0.729380]
1/1 [==============================] - 0s 20ms/step
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2451 [D loss: 0.686814, acc.: 56.84%] [G loss: 0.721509]
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2452 [D loss: 0.687478, acc.: 54.49%] [G loss: 0.714473]
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2453 [D loss: 0.694024, acc.: 50.59%] [G loss: 0.736328]
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2454 [D loss: 0.683080, acc.: 55.86%] [G loss: 0.738850]
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2455 [D loss: 0.699732, acc.: 46.29%] [G loss: 0.744310]
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2456 [D loss: 0.684695, acc.: 53.52%] [G loss: 0.744155]
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2457 [D loss: 0.692756, acc.: 52.93%] [G loss: 0.766686]
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2458 [D loss: 0.703008, acc.: 46.29%] [G loss: 0.755910]
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2459 [D loss: 0.685773, acc.: 55.86%] [G loss: 0.768262]
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2460 [D loss: 0.696313, acc.: 51.95%] [G loss: 0.745638]
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2461 [D loss: 0.697957, acc.: 48.44%] [G loss: 0.735869]
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2462 [D loss: 0.692429, acc.: 51.95%] [G loss: 0.742132]
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2463 [D loss: 0.696963, acc.: 51.37%] [G loss: 0.729834]
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2464 [D loss: 0.697010, acc.: 49.41%] [G loss: 0.733074]
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2465 [D loss: 0.701075, acc.: 47.46%] [G loss: 0.727795]
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2466 [D loss: 0.687993, acc.: 55.47%] [G loss: 0.739330]
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2467 [D loss: 0.685842, acc.: 55.66%] [G loss: 0.742763]
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2468 [D loss: 0.686072, acc.: 55.47%] [G loss: 0.721738]
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2469 [D loss: 0.681226, acc.: 55.08%] [G loss: 0.729705]
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2470 [D loss: 0.678184, acc.: 55.86%] [G loss: 0.724135]
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2471 [D loss: 0.677684, acc.: 59.57%] [G loss: 0.725694]
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2472 [D loss: 0.690193, acc.: 53.52%] [G loss: 0.727166]
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2473 [D loss: 0.690642, acc.: 50.78%] [G loss: 0.726272]
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2474 [D loss: 0.694733, acc.: 49.61%] [G loss: 0.723297]
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2475 [D loss: 0.691016, acc.: 52.34%] [G loss: 0.737973]
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2476 [D loss: 0.690802, acc.: 52.34%] [G loss: 0.722185]
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2477 [D loss: 0.695384, acc.: 50.39%] [G loss: 0.735122]
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2478 [D loss: 0.700037, acc.: 48.83%] [G loss: 0.729395]
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2479 [D loss: 0.699617, acc.: 47.07%] [G loss: 0.724429]
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2480 [D loss: 0.699155, acc.: 50.39%] [G loss: 0.737606]
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2481 [D loss: 0.698188, acc.: 48.63%] [G loss: 0.738374]
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2482 [D loss: 0.692087, acc.: 48.83%] [G loss: 0.735418]
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2483 [D loss: 0.691871, acc.: 50.59%] [G loss: 0.740385]
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2484 [D loss: 0.682453, acc.: 55.47%] [G loss: 0.744378]
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2485 [D loss: 0.687831, acc.: 55.86%] [G loss: 0.756269]
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2486 [D loss: 0.681568, acc.: 56.64%] [G loss: 0.746489]
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2487 [D loss: 0.675208, acc.: 59.38%] [G loss: 0.736934]
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2488 [D loss: 0.693772, acc.: 51.37%] [G loss: 0.747528]
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2489 [D loss: 0.693813, acc.: 52.93%] [G loss: 0.755130]
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2490 [D loss: 0.692729, acc.: 52.93%] [G loss: 0.751729]
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2491 [D loss: 0.702889, acc.: 46.88%] [G loss: 0.735318]
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2492 [D loss: 0.700246, acc.: 49.41%] [G loss: 0.728731]
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2493 [D loss: 0.691788, acc.: 51.56%] [G loss: 0.752699]
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2494 [D loss: 0.694268, acc.: 49.22%] [G loss: 0.730814]
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2495 [D loss: 0.694582, acc.: 52.34%] [G loss: 0.737835]
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2496 [D loss: 0.695587, acc.: 46.48%] [G loss: 0.722348]
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2497 [D loss: 0.692443, acc.: 51.17%] [G loss: 0.729603]
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2498 [D loss: 0.682658, acc.: 54.49%] [G loss: 0.737328]
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2499 [D loss: 0.680478, acc.: 55.86%] [G loss: 0.741251]
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2500 [D loss: 0.679135, acc.: 56.84%] [G loss: 0.748946]
1/1 [==============================] - 0s 22ms/step
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2501 [D loss: 0.681291, acc.: 56.25%] [G loss: 0.742309]
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2502 [D loss: 0.695543, acc.: 48.83%] [G loss: 0.739637]
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2503 [D loss: 0.687858, acc.: 52.54%] [G loss: 0.733269]
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2504 [D loss: 0.690790, acc.: 51.56%] [G loss: 0.726160]
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2505 [D loss: 0.694164, acc.: 50.78%] [G loss: 0.717994]
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2506 [D loss: 0.695959, acc.: 49.80%] [G loss: 0.722923]
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2507 [D loss: 0.685900, acc.: 53.12%] [G loss: 0.735445]
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2508 [D loss: 0.698834, acc.: 49.41%] [G loss: 0.733505]
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2509 [D loss: 0.693297, acc.: 49.80%] [G loss: 0.715313]
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2510 [D loss: 0.691479, acc.: 51.17%] [G loss: 0.726703]
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2511 [D loss: 0.691843, acc.: 49.02%] [G loss: 0.735316]
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2512 [D loss: 0.682530, acc.: 53.91%] [G loss: 0.761056]
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2513 [D loss: 0.688700, acc.: 51.56%] [G loss: 0.737013]
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2514 [D loss: 0.689654, acc.: 54.30%] [G loss: 0.749827]
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2515 [D loss: 0.692508, acc.: 52.54%] [G loss: 0.753407]
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2516 [D loss: 0.682941, acc.: 54.49%] [G loss: 0.741823]
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2517 [D loss: 0.694757, acc.: 52.34%] [G loss: 0.737400]
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2518 [D loss: 0.695185, acc.: 52.73%] [G loss: 0.741441]
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2519 [D loss: 0.686402, acc.: 55.66%] [G loss: 0.751658]
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2520 [D loss: 0.687901, acc.: 53.91%] [G loss: 0.728212]
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2521 [D loss: 0.686236, acc.: 54.30%] [G loss: 0.725111]
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2522 [D loss: 0.692882, acc.: 51.56%] [G loss: 0.731710]
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2523 [D loss: 0.695636, acc.: 52.73%] [G loss: 0.721865]
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2524 [D loss: 0.689832, acc.: 53.91%] [G loss: 0.728196]
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2525 [D loss: 0.695302, acc.: 50.39%] [G loss: 0.734736]
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2526 [D loss: 0.702995, acc.: 47.07%] [G loss: 0.749355]
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2527 [D loss: 0.691252, acc.: 51.95%] [G loss: 0.751414]
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2528 [D loss: 0.695948, acc.: 47.46%] [G loss: 0.750116]
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2529 [D loss: 0.690825, acc.: 51.95%] [G loss: 0.736883]
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2530 [D loss: 0.689391, acc.: 54.49%] [G loss: 0.740387]
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2531 [D loss: 0.690334, acc.: 50.98%] [G loss: 0.738643]
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2532 [D loss: 0.691436, acc.: 52.93%] [G loss: 0.733897]
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2533 [D loss: 0.686914, acc.: 55.27%] [G loss: 0.728664]
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2534 [D loss: 0.686058, acc.: 53.52%] [G loss: 0.725449]
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2535 [D loss: 0.687331, acc.: 54.69%] [G loss: 0.729496]
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2536 [D loss: 0.688048, acc.: 53.32%] [G loss: 0.729931]
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2537 [D loss: 0.688001, acc.: 52.93%] [G loss: 0.732105]
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2538 [D loss: 0.688618, acc.: 51.95%] [G loss: 0.726147]
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2539 [D loss: 0.700123, acc.: 52.15%] [G loss: 0.725504]
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2540 [D loss: 0.691456, acc.: 52.15%] [G loss: 0.745445]
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2541 [D loss: 0.691520, acc.: 52.54%] [G loss: 0.745664]
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2542 [D loss: 0.689821, acc.: 53.52%] [G loss: 0.740118]
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2543 [D loss: 0.692770, acc.: 51.76%] [G loss: 0.736361]
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2544 [D loss: 0.691886, acc.: 52.34%] [G loss: 0.737456]
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2545 [D loss: 0.682766, acc.: 57.03%] [G loss: 0.746077]
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2546 [D loss: 0.691300, acc.: 52.15%] [G loss: 0.745662]
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2547 [D loss: 0.701037, acc.: 47.07%] [G loss: 0.719464]
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2548 [D loss: 0.703468, acc.: 49.02%] [G loss: 0.723409]
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2549 [D loss: 0.692838, acc.: 52.34%] [G loss: 0.729570]
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2550 [D loss: 0.689802, acc.: 52.93%] [G loss: 0.739802]
1/1 [==============================] - 0s 21ms/step
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2551 [D loss: 0.695699, acc.: 49.80%] [G loss: 0.739544]
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2552 [D loss: 0.702777, acc.: 49.41%] [G loss: 0.752031]
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2553 [D loss: 0.692450, acc.: 53.52%] [G loss: 0.771010]
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2554 [D loss: 0.696311, acc.: 49.61%] [G loss: 0.764122]
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2555 [D loss: 0.684671, acc.: 57.62%] [G loss: 0.760360]
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2556 [D loss: 0.682318, acc.: 56.25%] [G loss: 0.755457]
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2557 [D loss: 0.692422, acc.: 51.95%] [G loss: 0.744745]
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2558 [D loss: 0.683363, acc.: 57.81%] [G loss: 0.751476]
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2559 [D loss: 0.681313, acc.: 56.64%] [G loss: 0.738062]
8/8 [==============================] - 0s 4ms/step
2560 [D loss: 0.683481, acc.: 55.27%] [G loss: 0.735602]
8/8 [==============================] - 0s 4ms/step
2561 [D loss: 0.686923, acc.: 55.47%] [G loss: 0.742155]
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2562 [D loss: 0.682754, acc.: 58.59%] [G loss: 0.739384]
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2563 [D loss: 0.688363, acc.: 53.91%] [G loss: 0.739501]
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2564 [D loss: 0.691720, acc.: 53.71%] [G loss: 0.735798]
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2565 [D loss: 0.699405, acc.: 49.61%] [G loss: 0.734289]
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2566 [D loss: 0.693444, acc.: 50.20%] [G loss: 0.735548]
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2567 [D loss: 0.699328, acc.: 50.20%] [G loss: 0.729492]
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2568 [D loss: 0.695748, acc.: 52.15%] [G loss: 0.727397]
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2569 [D loss: 0.697080, acc.: 50.00%] [G loss: 0.710121]
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2570 [D loss: 0.700790, acc.: 50.00%] [G loss: 0.718166]
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2571 [D loss: 0.696702, acc.: 50.39%] [G loss: 0.723795]
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2572 [D loss: 0.692229, acc.: 53.32%] [G loss: 0.726443]
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2573 [D loss: 0.687416, acc.: 51.76%] [G loss: 0.734636]
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2574 [D loss: 0.683751, acc.: 54.49%] [G loss: 0.741122]
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2575 [D loss: 0.680763, acc.: 54.49%] [G loss: 0.756697]
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2576 [D loss: 0.678995, acc.: 56.45%] [G loss: 0.746327]
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2577 [D loss: 0.681069, acc.: 56.25%] [G loss: 0.746281]
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2578 [D loss: 0.680912, acc.: 56.25%] [G loss: 0.747515]
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2579 [D loss: 0.691918, acc.: 53.12%] [G loss: 0.742177]
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2580 [D loss: 0.702146, acc.: 48.24%] [G loss: 0.736247]
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2581 [D loss: 0.698087, acc.: 48.83%] [G loss: 0.732614]
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2582 [D loss: 0.702337, acc.: 50.39%] [G loss: 0.726898]
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2583 [D loss: 0.703305, acc.: 48.05%] [G loss: 0.729094]
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2584 [D loss: 0.697470, acc.: 49.61%] [G loss: 0.726507]
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2585 [D loss: 0.701091, acc.: 47.46%] [G loss: 0.730695]
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2586 [D loss: 0.694923, acc.: 50.39%] [G loss: 0.735294]
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2587 [D loss: 0.689202, acc.: 54.88%] [G loss: 0.749221]
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2588 [D loss: 0.679155, acc.: 58.01%] [G loss: 0.747185]
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2589 [D loss: 0.683878, acc.: 56.64%] [G loss: 0.750631]
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2590 [D loss: 0.683649, acc.: 55.08%] [G loss: 0.747907]
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2591 [D loss: 0.674056, acc.: 60.16%] [G loss: 0.744625]
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2592 [D loss: 0.688511, acc.: 54.69%] [G loss: 0.751841]
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2593 [D loss: 0.687282, acc.: 54.49%] [G loss: 0.723568]
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2594 [D loss: 0.685767, acc.: 52.15%] [G loss: 0.719164]
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2595 [D loss: 0.693831, acc.: 51.95%] [G loss: 0.713181]
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2596 [D loss: 0.699259, acc.: 51.76%] [G loss: 0.709350]
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2597 [D loss: 0.686411, acc.: 52.54%] [G loss: 0.706652]
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2598 [D loss: 0.705062, acc.: 50.20%] [G loss: 0.717625]
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2599 [D loss: 0.704962, acc.: 48.05%] [G loss: 0.720152]
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2600 [D loss: 0.700691, acc.: 46.68%] [G loss: 0.725153]
1/1 [==============================] - 0s 22ms/step
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2601 [D loss: 0.697172, acc.: 50.59%] [G loss: 0.740803]
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2602 [D loss: 0.691092, acc.: 52.15%] [G loss: 0.749421]
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2603 [D loss: 0.680735, acc.: 56.84%] [G loss: 0.777080]
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2604 [D loss: 0.682041, acc.: 56.84%] [G loss: 0.759594]
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2605 [D loss: 0.680786, acc.: 57.81%] [G loss: 0.765091]
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2606 [D loss: 0.680583, acc.: 57.62%] [G loss: 0.753027]
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2607 [D loss: 0.678933, acc.: 59.57%] [G loss: 0.760502]
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2608 [D loss: 0.671552, acc.: 59.77%] [G loss: 0.729696]
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2609 [D loss: 0.679123, acc.: 55.66%] [G loss: 0.732146]
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2610 [D loss: 0.686528, acc.: 56.05%] [G loss: 0.729252]
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2611 [D loss: 0.698350, acc.: 48.83%] [G loss: 0.735365]
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2612 [D loss: 0.695762, acc.: 52.54%] [G loss: 0.736541]
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2613 [D loss: 0.697492, acc.: 49.22%] [G loss: 0.719278]
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2614 [D loss: 0.696434, acc.: 49.41%] [G loss: 0.721970]
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2615 [D loss: 0.708531, acc.: 44.14%] [G loss: 0.718780]
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2616 [D loss: 0.693136, acc.: 48.83%] [G loss: 0.732655]
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2617 [D loss: 0.694573, acc.: 48.63%] [G loss: 0.720029]
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2618 [D loss: 0.691619, acc.: 51.17%] [G loss: 0.715322]
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2619 [D loss: 0.692183, acc.: 50.98%] [G loss: 0.721801]
8/8 [==============================] - 0s 4ms/step
2620 [D loss: 0.690927, acc.: 51.17%] [G loss: 0.730099]
8/8 [==============================] - 0s 4ms/step
2621 [D loss: 0.685589, acc.: 52.15%] [G loss: 0.724842]
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2622 [D loss: 0.684964, acc.: 54.10%] [G loss: 0.737475]
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2623 [D loss: 0.679960, acc.: 54.88%] [G loss: 0.727089]
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2624 [D loss: 0.680122, acc.: 57.23%] [G loss: 0.724526]
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2625 [D loss: 0.674968, acc.: 57.23%] [G loss: 0.735290]
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2626 [D loss: 0.677784, acc.: 55.27%] [G loss: 0.728154]
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2627 [D loss: 0.685030, acc.: 55.47%] [G loss: 0.720735]
8/8 [==============================] - 0s 4ms/step
2628 [D loss: 0.684588, acc.: 52.93%] [G loss: 0.710802]
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2629 [D loss: 0.692975, acc.: 53.32%] [G loss: 0.714787]
8/8 [==============================] - 0s 4ms/step
2630 [D loss: 0.695182, acc.: 54.49%] [G loss: 0.711668]
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2631 [D loss: 0.691326, acc.: 53.52%] [G loss: 0.698727]
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2632 [D loss: 0.689945, acc.: 54.30%] [G loss: 0.727556]
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2633 [D loss: 0.689074, acc.: 53.32%] [G loss: 0.725751]
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2634 [D loss: 0.700233, acc.: 51.17%] [G loss: 0.748393]
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2635 [D loss: 0.691010, acc.: 54.49%] [G loss: 0.745529]
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2636 [D loss: 0.677855, acc.: 56.64%] [G loss: 0.774195]
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2637 [D loss: 0.691593, acc.: 50.20%] [G loss: 0.786352]
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2638 [D loss: 0.698029, acc.: 47.66%] [G loss: 0.768422]
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2639 [D loss: 0.692780, acc.: 55.47%] [G loss: 0.744012]
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2640 [D loss: 0.692234, acc.: 52.93%] [G loss: 0.747267]
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2641 [D loss: 0.690243, acc.: 53.71%] [G loss: 0.731805]
8/8 [==============================] - 0s 4ms/step
2642 [D loss: 0.683150, acc.: 55.86%] [G loss: 0.718187]
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2643 [D loss: 0.695870, acc.: 50.98%] [G loss: 0.714396]
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2644 [D loss: 0.701987, acc.: 45.31%] [G loss: 0.710956]
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2645 [D loss: 0.695279, acc.: 49.61%] [G loss: 0.735641]
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2646 [D loss: 0.683758, acc.: 53.12%] [G loss: 0.749823]
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2647 [D loss: 0.674800, acc.: 59.77%] [G loss: 0.781831]
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2648 [D loss: 0.680434, acc.: 55.47%] [G loss: 0.767941]
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2649 [D loss: 0.682262, acc.: 56.25%] [G loss: 0.761131]
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2650 [D loss: 0.688189, acc.: 52.15%] [G loss: 0.738938]
1/1 [==============================] - 0s 22ms/step
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2651 [D loss: 0.689341, acc.: 50.20%] [G loss: 0.733467]
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2652 [D loss: 0.685021, acc.: 55.08%] [G loss: 0.723135]
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2653 [D loss: 0.697415, acc.: 52.54%] [G loss: 0.710893]
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2654 [D loss: 0.699502, acc.: 49.61%] [G loss: 0.689505]
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2655 [D loss: 0.700937, acc.: 47.46%] [G loss: 0.713146]
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2656 [D loss: 0.705461, acc.: 48.63%] [G loss: 0.726758]
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2657 [D loss: 0.697956, acc.: 50.00%] [G loss: 0.738610]
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2658 [D loss: 0.689423, acc.: 52.15%] [G loss: 0.740654]
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2659 [D loss: 0.695213, acc.: 51.95%] [G loss: 0.750201]
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2660 [D loss: 0.684179, acc.: 54.10%] [G loss: 0.766588]
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2661 [D loss: 0.684423, acc.: 55.86%] [G loss: 0.757767]
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2662 [D loss: 0.687587, acc.: 52.54%] [G loss: 0.757292]
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2663 [D loss: 0.676586, acc.: 58.79%] [G loss: 0.754137]
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2664 [D loss: 0.679923, acc.: 56.64%] [G loss: 0.749343]
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2665 [D loss: 0.688436, acc.: 53.32%] [G loss: 0.733141]
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2666 [D loss: 0.692815, acc.: 53.71%] [G loss: 0.723747]
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2667 [D loss: 0.689437, acc.: 48.83%] [G loss: 0.715661]
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2668 [D loss: 0.693796, acc.: 51.95%] [G loss: 0.754683]
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2669 [D loss: 0.697340, acc.: 50.98%] [G loss: 0.743356]
8/8 [==============================] - 0s 4ms/step
2670 [D loss: 0.687281, acc.: 55.08%] [G loss: 0.757020]
8/8 [==============================] - 0s 4ms/step
2671 [D loss: 0.696495, acc.: 51.37%] [G loss: 0.747082]
8/8 [==============================] - 0s 4ms/step
2672 [D loss: 0.688526, acc.: 50.98%] [G loss: 0.737743]
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2673 [D loss: 0.698191, acc.: 52.93%] [G loss: 0.743737]
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2674 [D loss: 0.699137, acc.: 50.00%] [G loss: 0.731739]
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2675 [D loss: 0.694293, acc.: 50.00%] [G loss: 0.737900]
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2676 [D loss: 0.694895, acc.: 52.73%] [G loss: 0.733625]
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2677 [D loss: 0.699084, acc.: 50.39%] [G loss: 0.724284]
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2678 [D loss: 0.699716, acc.: 50.20%] [G loss: 0.728668]
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2679 [D loss: 0.690153, acc.: 51.37%] [G loss: 0.724609]
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2680 [D loss: 0.695031, acc.: 49.02%] [G loss: 0.701929]
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2681 [D loss: 0.687901, acc.: 58.59%] [G loss: 0.723854]
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2682 [D loss: 0.680608, acc.: 54.30%] [G loss: 0.724212]
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2683 [D loss: 0.686884, acc.: 53.52%] [G loss: 0.738695]
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2684 [D loss: 0.689168, acc.: 54.88%] [G loss: 0.741201]
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2685 [D loss: 0.690866, acc.: 57.42%] [G loss: 0.734263]
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2686 [D loss: 0.693468, acc.: 48.24%] [G loss: 0.741593]
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2687 [D loss: 0.685910, acc.: 56.05%] [G loss: 0.747029]
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2688 [D loss: 0.673572, acc.: 61.33%] [G loss: 0.731449]
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2689 [D loss: 0.700104, acc.: 49.61%] [G loss: 0.729737]
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2690 [D loss: 0.695786, acc.: 50.59%] [G loss: 0.739423]
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2691 [D loss: 0.690104, acc.: 53.32%] [G loss: 0.740654]
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2692 [D loss: 0.694810, acc.: 50.78%] [G loss: 0.723619]
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2693 [D loss: 0.690713, acc.: 51.76%] [G loss: 0.732236]
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2694 [D loss: 0.700592, acc.: 48.24%] [G loss: 0.735270]
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2695 [D loss: 0.692090, acc.: 51.17%] [G loss: 0.731990]
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2696 [D loss: 0.685898, acc.: 53.91%] [G loss: 0.737524]
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2697 [D loss: 0.688362, acc.: 51.37%] [G loss: 0.747549]
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2698 [D loss: 0.697797, acc.: 50.59%] [G loss: 0.730758]
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2699 [D loss: 0.696784, acc.: 49.80%] [G loss: 0.740319]
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2700 [D loss: 0.697666, acc.: 52.15%] [G loss: 0.736410]
1/1 [==============================] - 0s 23ms/step
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2701 [D loss: 0.689378, acc.: 52.34%] [G loss: 0.749112]
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2702 [D loss: 0.691335, acc.: 52.93%] [G loss: 0.758059]
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2703 [D loss: 0.692434, acc.: 49.61%] [G loss: 0.755904]
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2704 [D loss: 0.685162, acc.: 54.69%] [G loss: 0.736181]
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2705 [D loss: 0.681112, acc.: 57.23%] [G loss: 0.756676]
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2706 [D loss: 0.680939, acc.: 56.25%] [G loss: 0.744867]
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2707 [D loss: 0.688242, acc.: 55.08%] [G loss: 0.731063]
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2708 [D loss: 0.691051, acc.: 51.37%] [G loss: 0.725811]
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2709 [D loss: 0.701627, acc.: 48.24%] [G loss: 0.716428]
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2710 [D loss: 0.703740, acc.: 45.90%] [G loss: 0.719254]
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2711 [D loss: 0.689749, acc.: 53.32%] [G loss: 0.726115]
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2712 [D loss: 0.698728, acc.: 50.78%] [G loss: 0.718307]
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2713 [D loss: 0.695372, acc.: 51.76%] [G loss: 0.724633]
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2714 [D loss: 0.695356, acc.: 48.24%] [G loss: 0.724349]
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2715 [D loss: 0.688117, acc.: 56.45%] [G loss: 0.735140]
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2716 [D loss: 0.685580, acc.: 56.05%] [G loss: 0.734628]
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2717 [D loss: 0.684778, acc.: 57.23%] [G loss: 0.734775]
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2718 [D loss: 0.694762, acc.: 52.73%] [G loss: 0.745218]
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2719 [D loss: 0.691275, acc.: 51.17%] [G loss: 0.725980]
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2720 [D loss: 0.694347, acc.: 49.41%] [G loss: 0.727887]
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2721 [D loss: 0.693461, acc.: 51.17%] [G loss: 0.729814]
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2722 [D loss: 0.692478, acc.: 50.00%] [G loss: 0.730466]
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2723 [D loss: 0.679228, acc.: 58.01%] [G loss: 0.731641]
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2724 [D loss: 0.691646, acc.: 54.30%] [G loss: 0.746088]
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2725 [D loss: 0.695137, acc.: 50.98%] [G loss: 0.737662]
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2726 [D loss: 0.694508, acc.: 51.56%] [G loss: 0.743655]
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2727 [D loss: 0.691148, acc.: 51.17%] [G loss: 0.742400]
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2728 [D loss: 0.690801, acc.: 53.12%] [G loss: 0.743054]
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2729 [D loss: 0.685242, acc.: 57.42%] [G loss: 0.736154]
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2730 [D loss: 0.680220, acc.: 56.84%] [G loss: 0.738517]
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2731 [D loss: 0.692396, acc.: 50.20%] [G loss: 0.719740]
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2732 [D loss: 0.698431, acc.: 52.15%] [G loss: 0.733990]
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2733 [D loss: 0.691347, acc.: 53.12%] [G loss: 0.730903]
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2734 [D loss: 0.697956, acc.: 48.63%] [G loss: 0.743278]
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2735 [D loss: 0.690600, acc.: 52.73%] [G loss: 0.735362]
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2736 [D loss: 0.691928, acc.: 53.12%] [G loss: 0.733081]
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2737 [D loss: 0.688317, acc.: 54.49%] [G loss: 0.730706]
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2738 [D loss: 0.690110, acc.: 53.32%] [G loss: 0.718331]
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2739 [D loss: 0.689006, acc.: 54.88%] [G loss: 0.720152]
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2740 [D loss: 0.697597, acc.: 51.76%] [G loss: 0.724113]
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2741 [D loss: 0.685921, acc.: 57.03%] [G loss: 0.714837]
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2742 [D loss: 0.687473, acc.: 54.10%] [G loss: 0.719030]
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2743 [D loss: 0.692031, acc.: 51.37%] [G loss: 0.708843]
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2744 [D loss: 0.688287, acc.: 54.88%] [G loss: 0.720087]
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2745 [D loss: 0.698150, acc.: 49.02%] [G loss: 0.704009]
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2746 [D loss: 0.691496, acc.: 53.32%] [G loss: 0.714815]
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2747 [D loss: 0.688808, acc.: 51.56%] [G loss: 0.721771]
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2748 [D loss: 0.690259, acc.: 50.39%] [G loss: 0.739868]
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2749 [D loss: 0.686976, acc.: 53.52%] [G loss: 0.731100]
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2750 [D loss: 0.689233, acc.: 53.91%] [G loss: 0.735383]
1/1 [==============================] - 0s 24ms/step
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2751 [D loss: 0.702359, acc.: 48.24%] [G loss: 0.747185]
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2752 [D loss: 0.695426, acc.: 52.34%] [G loss: 0.756025]
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2753 [D loss: 0.687223, acc.: 55.47%] [G loss: 0.749596]
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2754 [D loss: 0.692125, acc.: 50.20%] [G loss: 0.749077]
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2755 [D loss: 0.693057, acc.: 50.59%] [G loss: 0.752685]
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2756 [D loss: 0.687937, acc.: 51.95%] [G loss: 0.745621]
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2757 [D loss: 0.699164, acc.: 50.78%] [G loss: 0.727517]
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2758 [D loss: 0.699466, acc.: 47.07%] [G loss: 0.711436]
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2759 [D loss: 0.700081, acc.: 49.22%] [G loss: 0.721407]
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2760 [D loss: 0.696806, acc.: 51.76%] [G loss: 0.727889]
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2761 [D loss: 0.693494, acc.: 52.54%] [G loss: 0.733517]
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2762 [D loss: 0.697342, acc.: 51.95%] [G loss: 0.739217]
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2763 [D loss: 0.689131, acc.: 54.69%] [G loss: 0.741323]
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2764 [D loss: 0.684397, acc.: 57.03%] [G loss: 0.744432]
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2765 [D loss: 0.683579, acc.: 58.40%] [G loss: 0.742407]
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2766 [D loss: 0.685195, acc.: 58.20%] [G loss: 0.744670]
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2767 [D loss: 0.678102, acc.: 57.81%] [G loss: 0.748898]
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2768 [D loss: 0.675110, acc.: 59.96%] [G loss: 0.757522]
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2769 [D loss: 0.678822, acc.: 58.98%] [G loss: 0.746855]
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2770 [D loss: 0.679192, acc.: 60.35%] [G loss: 0.734027]
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2771 [D loss: 0.693748, acc.: 52.73%] [G loss: 0.730359]
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2772 [D loss: 0.693972, acc.: 50.98%] [G loss: 0.716332]
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2773 [D loss: 0.699171, acc.: 51.17%] [G loss: 0.706128]
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2774 [D loss: 0.702697, acc.: 49.80%] [G loss: 0.694307]
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2775 [D loss: 0.698294, acc.: 52.54%] [G loss: 0.699820]
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2776 [D loss: 0.699800, acc.: 49.02%] [G loss: 0.693962]
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2777 [D loss: 0.698108, acc.: 49.41%] [G loss: 0.715484]
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2778 [D loss: 0.697377, acc.: 50.59%] [G loss: 0.739257]
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2779 [D loss: 0.695713, acc.: 52.93%] [G loss: 0.742800]
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2780 [D loss: 0.681548, acc.: 56.05%] [G loss: 0.751465]
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2781 [D loss: 0.692057, acc.: 50.98%] [G loss: 0.762224]
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2782 [D loss: 0.690179, acc.: 54.30%] [G loss: 0.766530]
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2783 [D loss: 0.686491, acc.: 55.27%] [G loss: 0.739679]
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2784 [D loss: 0.693196, acc.: 54.10%] [G loss: 0.740931]
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2785 [D loss: 0.698715, acc.: 48.24%] [G loss: 0.725941]
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2786 [D loss: 0.698827, acc.: 50.20%] [G loss: 0.722891]
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2787 [D loss: 0.685919, acc.: 53.52%] [G loss: 0.724298]
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2788 [D loss: 0.703123, acc.: 43.75%] [G loss: 0.724185]
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2789 [D loss: 0.697909, acc.: 49.02%] [G loss: 0.722148]
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2790 [D loss: 0.703946, acc.: 46.88%] [G loss: 0.732231]
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2791 [D loss: 0.694459, acc.: 50.20%] [G loss: 0.744048]
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2792 [D loss: 0.694714, acc.: 52.73%] [G loss: 0.736732]
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2793 [D loss: 0.691230, acc.: 51.56%] [G loss: 0.746378]
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2794 [D loss: 0.690896, acc.: 51.76%] [G loss: 0.751684]
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2795 [D loss: 0.688344, acc.: 53.71%] [G loss: 0.744241]
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2796 [D loss: 0.684823, acc.: 56.05%] [G loss: 0.741919]
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2797 [D loss: 0.685747, acc.: 54.10%] [G loss: 0.750434]
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2798 [D loss: 0.689544, acc.: 51.56%] [G loss: 0.739853]
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2799 [D loss: 0.687066, acc.: 54.10%] [G loss: 0.734052]
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2800 [D loss: 0.693026, acc.: 49.22%] [G loss: 0.725495]
1/1 [==============================] - 0s 22ms/step
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2801 [D loss: 0.687285, acc.: 54.88%] [G loss: 0.729907]
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2802 [D loss: 0.689368, acc.: 51.95%] [G loss: 0.734097]
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2803 [D loss: 0.693387, acc.: 52.34%] [G loss: 0.724590]
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2804 [D loss: 0.697643, acc.: 49.02%] [G loss: 0.721096]
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2805 [D loss: 0.694855, acc.: 50.59%] [G loss: 0.726499]
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2806 [D loss: 0.703235, acc.: 48.83%] [G loss: 0.717928]
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2807 [D loss: 0.694541, acc.: 53.52%] [G loss: 0.719274]
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2808 [D loss: 0.690965, acc.: 52.34%] [G loss: 0.719563]
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2809 [D loss: 0.690984, acc.: 54.10%] [G loss: 0.727054]
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2810 [D loss: 0.686644, acc.: 53.32%] [G loss: 0.734935]
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2811 [D loss: 0.683643, acc.: 56.84%] [G loss: 0.740573]
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2812 [D loss: 0.682299, acc.: 58.59%] [G loss: 0.727018]
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2813 [D loss: 0.691245, acc.: 54.10%] [G loss: 0.736989]
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2814 [D loss: 0.674702, acc.: 59.77%] [G loss: 0.739076]
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2815 [D loss: 0.685023, acc.: 55.66%] [G loss: 0.729392]
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2816 [D loss: 0.687147, acc.: 54.10%] [G loss: 0.736608]
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2817 [D loss: 0.691982, acc.: 53.12%] [G loss: 0.722030]
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2818 [D loss: 0.693754, acc.: 50.98%] [G loss: 0.720900]
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2819 [D loss: 0.698736, acc.: 51.17%] [G loss: 0.715061]
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2820 [D loss: 0.691936, acc.: 50.98%] [G loss: 0.728334]
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2821 [D loss: 0.694864, acc.: 51.17%] [G loss: 0.734266]
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2822 [D loss: 0.689918, acc.: 50.39%] [G loss: 0.733973]
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2823 [D loss: 0.692426, acc.: 55.08%] [G loss: 0.749064]
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2824 [D loss: 0.697984, acc.: 52.54%] [G loss: 0.767749]
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2825 [D loss: 0.691553, acc.: 53.32%] [G loss: 0.751975]
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2826 [D loss: 0.683571, acc.: 56.45%] [G loss: 0.752314]
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2827 [D loss: 0.694388, acc.: 51.95%] [G loss: 0.744693]
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2828 [D loss: 0.684857, acc.: 55.66%] [G loss: 0.743381]
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2829 [D loss: 0.692671, acc.: 53.12%] [G loss: 0.723667]
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2830 [D loss: 0.690664, acc.: 54.10%] [G loss: 0.730257]
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2831 [D loss: 0.693721, acc.: 52.54%] [G loss: 0.713100]
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2832 [D loss: 0.703267, acc.: 48.44%] [G loss: 0.729946]
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2833 [D loss: 0.694969, acc.: 51.17%] [G loss: 0.725013]
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2834 [D loss: 0.697740, acc.: 51.56%] [G loss: 0.726596]
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2835 [D loss: 0.687408, acc.: 56.25%] [G loss: 0.748354]
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2836 [D loss: 0.688470, acc.: 52.54%] [G loss: 0.751348]
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2837 [D loss: 0.687883, acc.: 55.27%] [G loss: 0.756242]
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2838 [D loss: 0.688951, acc.: 55.66%] [G loss: 0.756961]
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2839 [D loss: 0.681446, acc.: 55.27%] [G loss: 0.755127]
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2840 [D loss: 0.683878, acc.: 56.64%] [G loss: 0.761240]
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2841 [D loss: 0.684349, acc.: 57.42%] [G loss: 0.734463]
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2842 [D loss: 0.684578, acc.: 55.86%] [G loss: 0.739997]
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2843 [D loss: 0.683515, acc.: 54.88%] [G loss: 0.745153]
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2844 [D loss: 0.693276, acc.: 50.20%] [G loss: 0.721440]
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2845 [D loss: 0.689659, acc.: 53.52%] [G loss: 0.713992]
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2846 [D loss: 0.692574, acc.: 52.15%] [G loss: 0.731313]
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2847 [D loss: 0.694775, acc.: 53.12%] [G loss: 0.726223]
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2848 [D loss: 0.701702, acc.: 48.63%] [G loss: 0.724015]
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2849 [D loss: 0.705999, acc.: 46.09%] [G loss: 0.717715]
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2850 [D loss: 0.697085, acc.: 51.95%] [G loss: 0.717724]
1/1 [==============================] - 0s 21ms/step
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2851 [D loss: 0.697357, acc.: 50.59%] [G loss: 0.712150]
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2852 [D loss: 0.687312, acc.: 52.73%] [G loss: 0.713724]
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2853 [D loss: 0.687121, acc.: 54.10%] [G loss: 0.712965]
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2854 [D loss: 0.687083, acc.: 54.69%] [G loss: 0.715019]
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2855 [D loss: 0.683344, acc.: 56.84%] [G loss: 0.719438]
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2856 [D loss: 0.682707, acc.: 57.81%] [G loss: 0.737123]
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2857 [D loss: 0.682138, acc.: 56.45%] [G loss: 0.734622]
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2858 [D loss: 0.678790, acc.: 58.20%] [G loss: 0.752279]
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2859 [D loss: 0.680541, acc.: 56.84%] [G loss: 0.751926]
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2860 [D loss: 0.682302, acc.: 56.05%] [G loss: 0.747728]
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2861 [D loss: 0.684591, acc.: 55.86%] [G loss: 0.735707]
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2862 [D loss: 0.691866, acc.: 52.34%] [G loss: 0.703730]
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2863 [D loss: 0.700264, acc.: 50.20%] [G loss: 0.715230]
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2864 [D loss: 0.696338, acc.: 52.54%] [G loss: 0.706456]
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2865 [D loss: 0.706706, acc.: 48.83%] [G loss: 0.702471]
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2866 [D loss: 0.702105, acc.: 47.66%] [G loss: 0.705203]
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2867 [D loss: 0.702602, acc.: 48.44%] [G loss: 0.708971]
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2868 [D loss: 0.691750, acc.: 53.32%] [G loss: 0.727741]
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2869 [D loss: 0.697087, acc.: 50.39%] [G loss: 0.739470]
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2870 [D loss: 0.689269, acc.: 55.27%] [G loss: 0.751110]
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2871 [D loss: 0.677359, acc.: 59.38%] [G loss: 0.774035]
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2872 [D loss: 0.681666, acc.: 58.59%] [G loss: 0.785878]
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2873 [D loss: 0.685519, acc.: 53.32%] [G loss: 0.757306]
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2874 [D loss: 0.677598, acc.: 59.77%] [G loss: 0.761174]
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2875 [D loss: 0.672600, acc.: 60.16%] [G loss: 0.751922]
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2876 [D loss: 0.700328, acc.: 50.78%] [G loss: 0.714833]
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2877 [D loss: 0.700120, acc.: 50.98%] [G loss: 0.702131]
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2878 [D loss: 0.697231, acc.: 50.39%] [G loss: 0.691552]
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2879 [D loss: 0.701650, acc.: 46.29%] [G loss: 0.707270]
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2880 [D loss: 0.701415, acc.: 48.24%] [G loss: 0.704814]
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2881 [D loss: 0.705399, acc.: 44.73%] [G loss: 0.728365]
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2882 [D loss: 0.696605, acc.: 50.20%] [G loss: 0.738497]
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2883 [D loss: 0.693175, acc.: 50.00%] [G loss: 0.740085]
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2884 [D loss: 0.689564, acc.: 54.69%] [G loss: 0.752467]
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2885 [D loss: 0.693940, acc.: 51.56%] [G loss: 0.751700]
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2886 [D loss: 0.689605, acc.: 55.47%] [G loss: 0.751248]
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2887 [D loss: 0.683826, acc.: 55.08%] [G loss: 0.745565]
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2888 [D loss: 0.680135, acc.: 57.81%] [G loss: 0.757073]
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2889 [D loss: 0.682705, acc.: 58.20%] [G loss: 0.749572]
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2890 [D loss: 0.689927, acc.: 53.32%] [G loss: 0.746742]
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2891 [D loss: 0.684146, acc.: 52.34%] [G loss: 0.726820]
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2892 [D loss: 0.690300, acc.: 52.73%] [G loss: 0.718150]
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2893 [D loss: 0.694300, acc.: 52.54%] [G loss: 0.722461]
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2894 [D loss: 0.685572, acc.: 57.23%] [G loss: 0.716345]
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2895 [D loss: 0.697372, acc.: 52.93%] [G loss: 0.707240]
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2896 [D loss: 0.699563, acc.: 50.59%] [G loss: 0.716759]
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2897 [D loss: 0.694118, acc.: 50.00%] [G loss: 0.725675]
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2898 [D loss: 0.699191, acc.: 48.44%] [G loss: 0.740558]
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2899 [D loss: 0.697955, acc.: 49.41%] [G loss: 0.728005]
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2900 [D loss: 0.699069, acc.: 50.20%] [G loss: 0.738868]
1/1 [==============================] - 0s 21ms/step
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2901 [D loss: 0.690488, acc.: 52.93%] [G loss: 0.750718]
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2902 [D loss: 0.684052, acc.: 56.64%] [G loss: 0.752260]
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2903 [D loss: 0.686475, acc.: 55.86%] [G loss: 0.759730]
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2904 [D loss: 0.693302, acc.: 51.37%] [G loss: 0.750442]
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2905 [D loss: 0.682233, acc.: 56.05%] [G loss: 0.744345]
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2906 [D loss: 0.681224, acc.: 57.23%] [G loss: 0.735906]
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2907 [D loss: 0.690663, acc.: 55.27%] [G loss: 0.728828]
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2908 [D loss: 0.696417, acc.: 49.80%] [G loss: 0.719787]
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2909 [D loss: 0.698619, acc.: 48.83%] [G loss: 0.708266]
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2910 [D loss: 0.697445, acc.: 51.95%] [G loss: 0.727040]
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2911 [D loss: 0.695144, acc.: 53.32%] [G loss: 0.722660]
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2912 [D loss: 0.698261, acc.: 51.95%] [G loss: 0.744015]
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2913 [D loss: 0.695358, acc.: 51.76%] [G loss: 0.736192]
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2914 [D loss: 0.699537, acc.: 48.44%] [G loss: 0.736115]
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2915 [D loss: 0.688446, acc.: 54.10%] [G loss: 0.749850]
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2916 [D loss: 0.694862, acc.: 52.34%] [G loss: 0.740129]
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2917 [D loss: 0.685134, acc.: 56.64%] [G loss: 0.746486]
8/8 [==============================] - 0s 4ms/step
2918 [D loss: 0.685418, acc.: 54.69%] [G loss: 0.746658]
8/8 [==============================] - 0s 4ms/step
2919 [D loss: 0.682713, acc.: 55.27%] [G loss: 0.736428]
8/8 [==============================] - 0s 4ms/step
2920 [D loss: 0.676738, acc.: 59.96%] [G loss: 0.735199]
8/8 [==============================] - 0s 4ms/step
2921 [D loss: 0.678930, acc.: 58.40%] [G loss: 0.729142]
8/8 [==============================] - 0s 4ms/step
2922 [D loss: 0.681407, acc.: 54.10%] [G loss: 0.724373]
8/8 [==============================] - 0s 4ms/step
2923 [D loss: 0.685147, acc.: 56.64%] [G loss: 0.730389]
8/8 [==============================] - 0s 4ms/step
2924 [D loss: 0.698258, acc.: 48.63%] [G loss: 0.716335]
8/8 [==============================] - 0s 4ms/step
2925 [D loss: 0.692807, acc.: 51.17%] [G loss: 0.711163]
8/8 [==============================] - 0s 4ms/step
2926 [D loss: 0.697156, acc.: 51.37%] [G loss: 0.705033]
8/8 [==============================] - 0s 4ms/step
2927 [D loss: 0.697851, acc.: 49.22%] [G loss: 0.701310]
8/8 [==============================] - 0s 4ms/step
2928 [D loss: 0.696470, acc.: 52.93%] [G loss: 0.715438]
8/8 [==============================] - 0s 4ms/step
2929 [D loss: 0.694069, acc.: 51.17%] [G loss: 0.713697]
8/8 [==============================] - 0s 4ms/step
2930 [D loss: 0.691494, acc.: 53.71%] [G loss: 0.724506]
8/8 [==============================] - 0s 4ms/step
2931 [D loss: 0.697099, acc.: 49.80%] [G loss: 0.719115]
8/8 [==============================] - 0s 4ms/step
2932 [D loss: 0.698847, acc.: 47.66%] [G loss: 0.712707]
8/8 [==============================] - 0s 4ms/step
2933 [D loss: 0.697615, acc.: 51.17%] [G loss: 0.730098]
8/8 [==============================] - 0s 4ms/step
2934 [D loss: 0.689472, acc.: 53.12%] [G loss: 0.732334]
8/8 [==============================] - 0s 4ms/step
2935 [D loss: 0.687743, acc.: 52.73%] [G loss: 0.735665]
8/8 [==============================] - 0s 4ms/step
2936 [D loss: 0.688133, acc.: 51.76%] [G loss: 0.738907]
8/8 [==============================] - 0s 4ms/step
2937 [D loss: 0.693197, acc.: 50.78%] [G loss: 0.736853]
8/8 [==============================] - 0s 4ms/step
2938 [D loss: 0.694098, acc.: 51.76%] [G loss: 0.744500]
8/8 [==============================] - 0s 4ms/step
2939 [D loss: 0.687342, acc.: 51.95%] [G loss: 0.745354]
8/8 [==============================] - 0s 4ms/step
2940 [D loss: 0.691091, acc.: 52.15%] [G loss: 0.734698]
8/8 [==============================] - 0s 4ms/step
2941 [D loss: 0.695737, acc.: 52.15%] [G loss: 0.730822]
8/8 [==============================] - 0s 4ms/step
2942 [D loss: 0.689209, acc.: 52.15%] [G loss: 0.723174]
8/8 [==============================] - 0s 4ms/step
2943 [D loss: 0.696206, acc.: 50.39%] [G loss: 0.724684]
8/8 [==============================] - 0s 4ms/step
2944 [D loss: 0.688719, acc.: 53.52%] [G loss: 0.718179]
8/8 [==============================] - 0s 4ms/step
2945 [D loss: 0.690978, acc.: 53.71%] [G loss: 0.719284]
8/8 [==============================] - 0s 4ms/step
2946 [D loss: 0.695876, acc.: 48.63%] [G loss: 0.719241]
8/8 [==============================] - 0s 4ms/step
2947 [D loss: 0.693724, acc.: 52.34%] [G loss: 0.718999]
8/8 [==============================] - 0s 4ms/step
2948 [D loss: 0.696482, acc.: 51.17%] [G loss: 0.721775]
8/8 [==============================] - 0s 4ms/step
2949 [D loss: 0.695106, acc.: 50.39%] [G loss: 0.722594]
8/8 [==============================] - 0s 4ms/step
2950 [D loss: 0.696619, acc.: 48.05%] [G loss: 0.722013]
1/1 [==============================] - 0s 23ms/step
8/8 [==============================] - 0s 4ms/step
2951 [D loss: 0.692865, acc.: 50.39%] [G loss: 0.731932]
8/8 [==============================] - 0s 4ms/step
2952 [D loss: 0.693756, acc.: 49.61%] [G loss: 0.730733]
8/8 [==============================] - 0s 4ms/step
2953 [D loss: 0.682626, acc.: 55.86%] [G loss: 0.726194]
8/8 [==============================] - 0s 4ms/step
2954 [D loss: 0.688941, acc.: 52.15%] [G loss: 0.737469]
8/8 [==============================] - 0s 4ms/step
2955 [D loss: 0.681374, acc.: 58.59%] [G loss: 0.726288]
8/8 [==============================] - 0s 4ms/step
2956 [D loss: 0.689870, acc.: 53.32%] [G loss: 0.730175]
8/8 [==============================] - 0s 4ms/step
2957 [D loss: 0.684527, acc.: 57.42%] [G loss: 0.709387]
8/8 [==============================] - 0s 4ms/step
2958 [D loss: 0.684342, acc.: 55.47%] [G loss: 0.724088]
8/8 [==============================] - 0s 4ms/step
2959 [D loss: 0.688533, acc.: 52.54%] [G loss: 0.720766]
8/8 [==============================] - 0s 4ms/step
2960 [D loss: 0.697851, acc.: 52.15%] [G loss: 0.702067]
8/8 [==============================] - 0s 4ms/step
2961 [D loss: 0.686932, acc.: 55.66%] [G loss: 0.714300]
8/8 [==============================] - 0s 4ms/step
2962 [D loss: 0.693533, acc.: 52.15%] [G loss: 0.720133]
8/8 [==============================] - 0s 4ms/step
2963 [D loss: 0.689375, acc.: 52.73%] [G loss: 0.727501]
8/8 [==============================] - 0s 4ms/step
2964 [D loss: 0.683492, acc.: 55.27%] [G loss: 0.758947]
8/8 [==============================] - 0s 4ms/step
2965 [D loss: 0.692483, acc.: 51.17%] [G loss: 0.776533]
8/8 [==============================] - 0s 4ms/step
2966 [D loss: 0.682794, acc.: 55.08%] [G loss: 0.776716]
8/8 [==============================] - 0s 4ms/step
2967 [D loss: 0.681461, acc.: 56.45%] [G loss: 0.772259]
8/8 [==============================] - 0s 4ms/step
2968 [D loss: 0.687100, acc.: 54.30%] [G loss: 0.741284]
8/8 [==============================] - 0s 4ms/step
2969 [D loss: 0.697863, acc.: 49.80%] [G loss: 0.741289]
8/8 [==============================] - 0s 4ms/step
2970 [D loss: 0.689876, acc.: 50.78%] [G loss: 0.734793]
8/8 [==============================] - 0s 4ms/step
2971 [D loss: 0.692812, acc.: 48.24%] [G loss: 0.730084]
8/8 [==============================] - 0s 4ms/step
2972 [D loss: 0.700759, acc.: 46.88%] [G loss: 0.718511]
8/8 [==============================] - 0s 4ms/step
2973 [D loss: 0.696689, acc.: 51.17%] [G loss: 0.722544]
8/8 [==============================] - 0s 4ms/step
2974 [D loss: 0.701507, acc.: 48.24%] [G loss: 0.714484]
8/8 [==============================] - 0s 4ms/step
2975 [D loss: 0.704039, acc.: 50.78%] [G loss: 0.735877]
8/8 [==============================] - 0s 4ms/step
2976 [D loss: 0.692109, acc.: 51.95%] [G loss: 0.750778]
8/8 [==============================] - 0s 4ms/step
2977 [D loss: 0.692797, acc.: 50.98%] [G loss: 0.753149]
8/8 [==============================] - 0s 4ms/step
2978 [D loss: 0.696491, acc.: 49.02%] [G loss: 0.748938]
8/8 [==============================] - 0s 4ms/step
2979 [D loss: 0.692595, acc.: 51.76%] [G loss: 0.738628]
8/8 [==============================] - 0s 4ms/step
2980 [D loss: 0.683201, acc.: 56.84%] [G loss: 0.750433]
8/8 [==============================] - 0s 4ms/step
2981 [D loss: 0.677456, acc.: 58.40%] [G loss: 0.755351]
8/8 [==============================] - 0s 4ms/step
2982 [D loss: 0.681627, acc.: 56.64%] [G loss: 0.731352]
8/8 [==============================] - 0s 4ms/step
2983 [D loss: 0.690940, acc.: 56.45%] [G loss: 0.723709]
8/8 [==============================] - 0s 4ms/step
2984 [D loss: 0.692010, acc.: 51.76%] [G loss: 0.724302]
8/8 [==============================] - 0s 4ms/step
2985 [D loss: 0.703171, acc.: 46.88%] [G loss: 0.719142]
8/8 [==============================] - 0s 4ms/step
2986 [D loss: 0.695921, acc.: 53.32%] [G loss: 0.724863]
8/8 [==============================] - 0s 4ms/step
2987 [D loss: 0.699901, acc.: 47.46%] [G loss: 0.713654]
8/8 [==============================] - 0s 4ms/step
2988 [D loss: 0.695427, acc.: 51.37%] [G loss: 0.719225]
8/8 [==============================] - 0s 4ms/step
2989 [D loss: 0.693420, acc.: 52.54%] [G loss: 0.723339]
8/8 [==============================] - 0s 4ms/step
2990 [D loss: 0.703598, acc.: 48.05%] [G loss: 0.727410]
8/8 [==============================] - 0s 4ms/step
2991 [D loss: 0.695665, acc.: 50.00%] [G loss: 0.727474]
8/8 [==============================] - 0s 4ms/step
2992 [D loss: 0.694122, acc.: 49.61%] [G loss: 0.725727]
8/8 [==============================] - 0s 4ms/step
2993 [D loss: 0.686815, acc.: 53.71%] [G loss: 0.733913]
8/8 [==============================] - 0s 4ms/step
2994 [D loss: 0.686488, acc.: 52.93%] [G loss: 0.740243]
8/8 [==============================] - 0s 4ms/step
2995 [D loss: 0.686328, acc.: 54.49%] [G loss: 0.739657]
8/8 [==============================] - 0s 4ms/step
2996 [D loss: 0.692475, acc.: 52.15%] [G loss: 0.732912]
8/8 [==============================] - 0s 4ms/step
2997 [D loss: 0.689641, acc.: 50.59%] [G loss: 0.735089]
8/8 [==============================] - 0s 4ms/step
2998 [D loss: 0.684307, acc.: 55.86%] [G loss: 0.732162]
8/8 [==============================] - 0s 4ms/step
2999 [D loss: 0.684631, acc.: 55.66%] [G loss: 0.737805]

Plot Loss

plot_losses(cgan.d_losses, cgan.g_losses)

Plot Accuracy

plot_accuracy(cgan.d_accuracy)

Generated Images at Different Epochs (Base Model)

100 Epochs

1000 Epochs

2950 Epochs

Results

The initial high loss of around 17 for the generator and the low loss of approximately 0.4 for the discriminator suggest that the generator's early outputs were highly unrealistic, while the discriminator was initially effective at distinguishing between real and generated images. As training progressed, the generator's loss decreased to around 3.6, indicating an improvement in image quality, while the discriminator's loss increased to about 1, reflecting the growing challenge of distinguishing between real and fake images. Eventually, both losses converged to around 0.7, suggesting a balance where the generator produced sufficiently realistic images that the discriminator could not easily differentiate.

The discriminator's accuracy started high at around 90% but dropped to approximately 82% before fluctuating between 50% and 60%. This fluctuation suggests that the discriminator became less confident as the generator's outputs improved, making it harder to distinguish between real and generated images.

The generated classes are generally distinguishable, but the images lack sharpness, with noticeable black patches appearing in the alphabets.

Increase the Number of Dense Units in the Generator

What changed from the previous model

• Dense units in the first Dense layer of the generator increased from 128 to 1500

Why did we increase the number of dense units for the generator

The first Dense layer of the generator is responsible for taking the input noise vector (latent space representation) and transforming it into a feature representation that can be further processed by subsequent layers to generate realistic images.

By increasing the number of units (neurons) in this layer, we increase the capacity of the generator to learn and capture more complex patterns and features from the input noise vector. This allows the generator to potentially model more intricate relationships and variations in the data distribution it aims to mimic.

class CGAN():
    def __init__(self):
        # Input shape
        self.img_rows = 28
        self.img_cols = 28
        self.channels = 1
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.num_classes = 26
        self.latent_dim = 100

        optimizer = Adam(0.001, 0.5)

        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss=['binary_crossentropy'],
            optimizer=optimizer,
            metrics=['accuracy'])

        # Build the generator
        self.generator = self.build_generator()

        # The generator takes noise and the target label as input
        # and generates the corresponding digit of that label
        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,))
        img = self.generator([noise, label])

        # For the combined model we will only train the generator
        self.discriminator.trainable = False

        # The discriminator takes generated image as input and determines validity
        # and the label of that image
        valid = self.discriminator([img, label])

        # The combined model  (stacked generator and discriminator)
        # Trains generator to fool discriminator
        self.combined = Model([noise, label], valid)
        self.combined.compile(loss=['binary_crossentropy'],
            optimizer=optimizer)

        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []

    def build_generator(self):

        model = Sequential()

        model.add(Dense(512 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 512)))
        
        model.add(Conv2DTranspose(128, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(self.channels, kernel_size=4, strides=(2,2), padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,), dtype='int32')
        label_embedding = Flatten()(Embedding(self.num_classes, self.latent_dim)(label))

        model_input = multiply([noise, label_embedding])
        img = model(model_input)

        return Model([noise, label], img)

    def build_discriminator(self):
        model = Sequential()

        model.add(Conv2D(64, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))

        
        model.add(Flatten())
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        # Image input and label input
        img = Input(shape=self.img_shape)
        label = Input(shape=(1,), dtype='int32')

        # Embedding for label
        label_embedding = Flatten()(Embedding(self.num_classes, np.prod(self.img_shape))(label))
        label_embedding = Dense(np.prod(self.img_shape))(label_embedding)
        label_embedding = Reshape(self.img_shape)(label_embedding)

        # Multiply image and label embeddings
        combined = multiply([img, label_embedding])

        # Validity prediction
        validity = model(combined)

        return Model([img, label], validity)

    def train(self, epochs, batch_size=128, sample_interval=50):


        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values
        y_train = preprocessed_df.iloc[:, 0].values
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)

        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))

        for epoch in range(epochs):

            # ---------------------
            #  Train Discriminator
            # ---------------------

            # Select a random half batch of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs, labels = X_train[idx], y_train[idx]
            # Sample noise as generator input
            noise = np.random.normal(0, 1, (batch_size, 100))

            # Generate a half batch of new images
            gen_imgs = self.generator.predict([noise, labels])

            # Train the discriminator
            d_loss_real = self.discriminator.train_on_batch([imgs, labels], valid)
            d_loss_fake = self.discriminator.train_on_batch([gen_imgs, labels], fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)

            # ---------------------
            #  Train Generator
            # ---------------------

            # Condition on labels (Generate random samples)
            sampled_labels = np.random.randint(1, 27, batch_size).reshape(-1, 1)

            # Train the generator
            g_loss = self.combined.train_on_batch([noise, sampled_labels], valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            
            # Plot the progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100*d_loss[1], g_loss))

            # If at save interval => save generated image samples
            if epoch % sample_interval == 0:
                self.sample_images(epoch)

    def sample_images(self, epoch):
        r, c = 5, 6
        num_samples = 26
        # Generate noise based on the number of samples
        noise = np.random.normal(0, 1, (num_samples, 100))
        sampled_labels = np.arange(1, 27).reshape(-1, 1)

        gen_imgs = self.generator.predict([noise, sampled_labels])

        # Rescale images 0 - 1
        gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0  # Counter for the images
        for i in range(r):
            for j in range(c):
                if cnt < num_samples:  # Ensure we don't go out of bounds
                    axs[i,j].imshow(gen_imgs[cnt,:,:,0], cmap='gray')  # Display image

                    mapped_label = map_labels(sampled_labels[cnt][0])  # Map label to its corresponding class name
                    axs[i,j].set_title("Class: %s" % mapped_label)  # Set title of the subplot
                    axs[i,j].axis('off')  # Turn off axis
                    cnt += 1  # Increment counter
                else:
                    axs[i,j].axis('off')  # Turn off axis if there's no image to display
                    
        # Adjust the spacing between subplots
        plt.subplots_adjust(wspace=0.2, hspace=0.6)
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/cgan/generatorDenser', exist_ok=True)
        fig.savefig("generated_images/cgan/generatorDenser/cgan_{:d}.png".format(epoch))
        plt.close()

cgan = CGAN()
cgan.train(epochs=3000, batch_size=256, sample_interval=50)

Model: "sequential_6"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_27 (Conv2D)          (None, 14, 14, 64)        640       
                                                                 
 leaky_re_lu_24 (LeakyReLU)  (None, 14, 14, 64)        0         
                                                                 
 conv2d_28 (Conv2D)          (None, 7, 7, 128)         73856     
                                                                 
 leaky_re_lu_25 (LeakyReLU)  (None, 7, 7, 128)         0         
                                                                 
 conv2d_29 (Conv2D)          (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_26 (LeakyReLU)  (None, 4, 4, 256)         0         
                                                                 
 flatten_7 (Flatten)         (None, 4096)              0         
                                                                 
 dense_14 (Dense)            (None, 1)                 4097      
                                                                 
=================================================================
Total params: 373,761
Trainable params: 373,761
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_7"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_16 (Dense)            (None, 25088)             2533888   
                                                                 
 reshape_7 (Reshape)         (None, 7, 7, 512)         0         
                                                                 
 conv2d_transpose_3 (Conv2DT  (None, 14, 14, 128)      1048704   
 ranspose)                                                       
                                                                 
 batch_normalization_11 (Bat  (None, 14, 14, 128)      512       
 chNormalization)                                                
                                                                 
 leaky_re_lu_27 (LeakyReLU)  (None, 14, 14, 128)       0         
                                                                 
 conv2d_transpose_4 (Conv2DT  (None, 28, 28, 64)       131136    
 ranspose)                                                       
                                                                 
 batch_normalization_12 (Bat  (None, 28, 28, 64)       256       
 chNormalization)                                                
                                                                 
 leaky_re_lu_28 (LeakyReLU)  (None, 28, 28, 64)        0         
                                                                 
 conv2d_transpose_5 (Conv2DT  (None, 56, 56, 64)       65600     
 ranspose)                                                       
                                                                 
 batch_normalization_13 (Bat  (None, 56, 56, 64)       256       
 chNormalization)                                                
                                                                 
 leaky_re_lu_29 (LeakyReLU)  (None, 56, 56, 64)        0         
                                                                 
 conv2d_30 (Conv2D)          (None, 28, 28, 1)         1025      
                                                                 
 activation_9 (Activation)   (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 3,781,377
Trainable params: 3,780,865
Non-trainable params: 512
_________________________________________________________________
8/8 [==============================] - 0s 4ms/step
0 [D loss: 0.698478, acc.: 13.67%] [G loss: 0.691452]
1/1 [==============================] - 0s 194ms/step
8/8 [==============================] - 0s 4ms/step
1 [D loss: 0.694053, acc.: 50.00%] [G loss: 0.691930]
8/8 [==============================] - 0s 4ms/step
2 [D loss: 0.693414, acc.: 50.00%] [G loss: 0.691966]
8/8 [==============================] - 0s 4ms/step
3 [D loss: 0.692989, acc.: 50.00%] [G loss: 0.690620]
8/8 [==============================] - 0s 4ms/step
4 [D loss: 0.692053, acc.: 90.62%] [G loss: 0.688295]
8/8 [==============================] - 0s 4ms/step
5 [D loss: 0.689384, acc.: 97.07%] [G loss: 0.683669]
8/8 [==============================] - 0s 4ms/step
6 [D loss: 0.680426, acc.: 89.26%] [G loss: 0.662441]
8/8 [==============================] - 0s 4ms/step
7 [D loss: 0.644866, acc.: 89.26%] [G loss: 0.663800]
8/8 [==============================] - 0s 4ms/step
8 [D loss: 0.605076, acc.: 68.55%] [G loss: 0.556148]
8/8 [==============================] - 0s 4ms/step
9 [D loss: 0.604768, acc.: 90.82%] [G loss: 0.423701]
8/8 [==============================] - 0s 4ms/step
10 [D loss: 0.562439, acc.: 92.77%] [G loss: 0.598358]
8/8 [==============================] - 0s 4ms/step
11 [D loss: 0.844183, acc.: 19.73%] [G loss: 0.535077]
8/8 [==============================] - 0s 4ms/step
12 [D loss: 0.735446, acc.: 38.87%] [G loss: 0.674178]
8/8 [==============================] - 0s 4ms/step
13 [D loss: 0.710887, acc.: 46.09%] [G loss: 0.831662]
8/8 [==============================] - 0s 4ms/step
14 [D loss: 0.676082, acc.: 63.87%] [G loss: 1.142140]
8/8 [==============================] - 0s 4ms/step
15 [D loss: 0.651540, acc.: 67.19%] [G loss: 1.356504]
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16 [D loss: 0.599132, acc.: 62.30%] [G loss: 1.510916]
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17 [D loss: 0.606959, acc.: 62.30%] [G loss: 1.397991]
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18 [D loss: 0.577031, acc.: 70.51%] [G loss: 1.157763]
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19 [D loss: 0.803875, acc.: 35.16%] [G loss: 0.968942]
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20 [D loss: 0.866965, acc.: 22.27%] [G loss: 0.609148]
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21 [D loss: 0.695731, acc.: 31.64%] [G loss: 0.664836]
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22 [D loss: 0.618380, acc.: 44.92%] [G loss: 0.676104]
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23 [D loss: 0.577009, acc.: 49.02%] [G loss: 0.680112]
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24 [D loss: 0.525375, acc.: 49.41%] [G loss: 0.685614]
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25 [D loss: 0.457863, acc.: 49.80%] [G loss: 0.694425]
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26 [D loss: 0.421440, acc.: 98.83%] [G loss: 0.705783]
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27 [D loss: 0.403646, acc.: 99.80%] [G loss: 0.722577]
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28 [D loss: 0.367732, acc.: 100.00%] [G loss: 0.754374]
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29 [D loss: 0.337050, acc.: 100.00%] [G loss: 0.820497]
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30 [D loss: 0.310892, acc.: 99.41%] [G loss: 0.974811]
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31 [D loss: 0.239956, acc.: 99.02%] [G loss: 1.397423]
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32 [D loss: 0.194972, acc.: 95.90%] [G loss: 2.118699]
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33 [D loss: 0.137301, acc.: 96.88%] [G loss: 2.747575]
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34 [D loss: 0.147078, acc.: 95.90%] [G loss: 2.834808]
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35 [D loss: 0.083062, acc.: 98.05%] [G loss: 3.177855]
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36 [D loss: 0.065806, acc.: 98.05%] [G loss: 3.429097]
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37 [D loss: 0.051867, acc.: 98.44%] [G loss: 3.660728]
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38 [D loss: 0.061495, acc.: 98.05%] [G loss: 3.666587]
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39 [D loss: 0.079332, acc.: 97.27%] [G loss: 3.420577]
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40 [D loss: 0.047644, acc.: 98.44%] [G loss: 3.687865]
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41 [D loss: 0.034986, acc.: 98.63%] [G loss: 3.968987]
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42 [D loss: 0.040781, acc.: 98.44%] [G loss: 3.932047]
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43 [D loss: 0.030887, acc.: 98.83%] [G loss: 4.082153]
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44 [D loss: 0.036931, acc.: 98.24%] [G loss: 4.036386]
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45 [D loss: 0.021691, acc.: 99.22%] [G loss: 4.279269]
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46 [D loss: 0.043266, acc.: 98.44%] [G loss: 3.996471]
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47 [D loss: 0.022383, acc.: 99.22%] [G loss: 4.258869]
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48 [D loss: 0.018596, acc.: 99.61%] [G loss: 4.462636]
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49 [D loss: 0.014027, acc.: 99.61%] [G loss: 4.689036]
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50 [D loss: 0.012073, acc.: 99.80%] [G loss: 4.818491]
1/1 [==============================] - 0s 22ms/step
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51 [D loss: 0.005841, acc.: 100.00%] [G loss: 5.115966]
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52 [D loss: 0.012592, acc.: 99.61%] [G loss: 5.022364]
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53 [D loss: 0.009912, acc.: 99.80%] [G loss: 5.145314]
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54 [D loss: 0.016521, acc.: 99.61%] [G loss: 4.757427]
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55 [D loss: 0.006413, acc.: 100.00%] [G loss: 5.031612]
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56 [D loss: 0.007109, acc.: 100.00%] [G loss: 5.223897]
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57 [D loss: 0.006940, acc.: 100.00%] [G loss: 5.285788]
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58 [D loss: 0.011730, acc.: 99.41%] [G loss: 5.063430]
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59 [D loss: 0.003959, acc.: 100.00%] [G loss: 5.366467]
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60 [D loss: 0.010450, acc.: 99.61%] [G loss: 5.241531]
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61 [D loss: 0.008302, acc.: 99.80%] [G loss: 5.316312]
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62 [D loss: 0.004856, acc.: 100.00%] [G loss: 5.465380]
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63 [D loss: 0.008086, acc.: 99.61%] [G loss: 5.462789]
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64 [D loss: 0.005039, acc.: 99.80%] [G loss: 5.558300]
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65 [D loss: 0.008221, acc.: 99.80%] [G loss: 5.558368]
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66 [D loss: 0.002004, acc.: 100.00%] [G loss: 5.853273]
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67 [D loss: 0.002181, acc.: 100.00%] [G loss: 6.055140]
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68 [D loss: 0.010398, acc.: 99.61%] [G loss: 5.604028]
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69 [D loss: 0.003524, acc.: 100.00%] [G loss: 5.645784]
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70 [D loss: 0.002039, acc.: 100.00%] [G loss: 5.939649]
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71 [D loss: 0.002004, acc.: 100.00%] [G loss: 6.153804]
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72 [D loss: 0.001704, acc.: 100.00%] [G loss: 6.305362]
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73 [D loss: 0.002168, acc.: 100.00%] [G loss: 6.327810]
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74 [D loss: 0.002093, acc.: 100.00%] [G loss: 6.346178]
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75 [D loss: 0.002276, acc.: 100.00%] [G loss: 6.344781]
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76 [D loss: 0.001007, acc.: 100.00%] [G loss: 6.509235]
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77 [D loss: 0.003173, acc.: 99.80%] [G loss: 6.367979]
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78 [D loss: 0.002701, acc.: 100.00%] [G loss: 6.242855]
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79 [D loss: 0.007108, acc.: 99.61%] [G loss: 5.767608]
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80 [D loss: 0.001580, acc.: 100.00%] [G loss: 6.031815]
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81 [D loss: 0.001238, acc.: 100.00%] [G loss: 6.369635]
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82 [D loss: 0.001391, acc.: 100.00%] [G loss: 6.551770]
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83 [D loss: 0.001267, acc.: 100.00%] [G loss: 6.656988]
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84 [D loss: 0.000783, acc.: 100.00%] [G loss: 6.805722]
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85 [D loss: 0.000939, acc.: 100.00%] [G loss: 6.895258]
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86 [D loss: 0.001183, acc.: 100.00%] [G loss: 6.907555]
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87 [D loss: 0.002977, acc.: 99.80%] [G loss: 6.633602]
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88 [D loss: 0.000963, acc.: 100.00%] [G loss: 6.682880]
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89 [D loss: 0.001241, acc.: 100.00%] [G loss: 6.723545]
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90 [D loss: 5.520508, acc.: 51.76%] [G loss: 24.678041]
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91 [D loss: 18.110106, acc.: 5.27%] [G loss: 2.238812]
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92 [D loss: 4.220191, acc.: 43.95%] [G loss: 3.923971]
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93 [D loss: 1.286028, acc.: 64.06%] [G loss: 2.755311]
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94 [D loss: 1.246938, acc.: 54.69%] [G loss: 1.423492]
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95 [D loss: 0.676964, acc.: 65.04%] [G loss: 1.079998]
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96 [D loss: 0.500001, acc.: 67.77%] [G loss: 0.905371]
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97 [D loss: 0.488179, acc.: 72.66%] [G loss: 0.829696]
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98 [D loss: 0.501811, acc.: 73.44%] [G loss: 0.957841]
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99 [D loss: 0.484459, acc.: 76.56%] [G loss: 1.111509]
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100 [D loss: 0.455931, acc.: 75.78%] [G loss: 1.372735]
1/1 [==============================] - 0s 24ms/step
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101 [D loss: 0.436340, acc.: 76.17%] [G loss: 1.597046]
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102 [D loss: 0.382500, acc.: 76.17%] [G loss: 1.808217]
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103 [D loss: 0.399974, acc.: 75.59%] [G loss: 1.842688]
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104 [D loss: 0.413472, acc.: 78.12%] [G loss: 1.506525]
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105 [D loss: 0.467068, acc.: 74.22%] [G loss: 1.334526]
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106 [D loss: 0.556307, acc.: 68.55%] [G loss: 0.898680]
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107 [D loss: 0.547406, acc.: 72.85%] [G loss: 0.917304]
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108 [D loss: 0.518887, acc.: 75.78%] [G loss: 0.968791]
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109 [D loss: 0.507471, acc.: 78.52%] [G loss: 0.936911]
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110 [D loss: 0.504615, acc.: 81.45%] [G loss: 0.955627]
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111 [D loss: 0.496602, acc.: 80.08%] [G loss: 0.973342]
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112 [D loss: 0.469323, acc.: 82.42%] [G loss: 1.005290]
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113 [D loss: 0.435552, acc.: 83.98%] [G loss: 1.050678]
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114 [D loss: 0.457982, acc.: 81.25%] [G loss: 1.079731]
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115 [D loss: 0.423307, acc.: 82.62%] [G loss: 1.117974]
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116 [D loss: 0.405001, acc.: 85.94%] [G loss: 1.164014]
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117 [D loss: 0.391529, acc.: 85.35%] [G loss: 1.195577]
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118 [D loss: 0.392930, acc.: 83.98%] [G loss: 1.237935]
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119 [D loss: 0.380315, acc.: 85.94%] [G loss: 1.276707]
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120 [D loss: 0.345936, acc.: 88.09%] [G loss: 1.324372]
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121 [D loss: 0.334265, acc.: 88.28%] [G loss: 1.359186]
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122 [D loss: 0.332445, acc.: 88.48%] [G loss: 1.404950]
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123 [D loss: 0.280803, acc.: 93.16%] [G loss: 1.465607]
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124 [D loss: 0.285566, acc.: 90.04%] [G loss: 1.517933]
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125 [D loss: 0.278672, acc.: 91.60%] [G loss: 1.546418]
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126 [D loss: 0.246101, acc.: 93.36%] [G loss: 1.621593]
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127 [D loss: 0.233713, acc.: 93.95%] [G loss: 1.681131]
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128 [D loss: 0.209754, acc.: 94.73%] [G loss: 1.751477]
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129 [D loss: 0.210995, acc.: 94.92%] [G loss: 1.812272]
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130 [D loss: 0.210415, acc.: 93.95%] [G loss: 1.854336]
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131 [D loss: 0.212389, acc.: 92.97%] [G loss: 1.888064]
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132 [D loss: 0.159906, acc.: 97.46%] [G loss: 1.958393]
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133 [D loss: 0.166272, acc.: 95.70%] [G loss: 2.033767]
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134 [D loss: 0.151994, acc.: 96.09%] [G loss: 2.107690]
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135 [D loss: 0.135858, acc.: 97.07%] [G loss: 2.198525]
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136 [D loss: 0.126313, acc.: 97.66%] [G loss: 2.268761]
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137 [D loss: 0.110963, acc.: 97.66%] [G loss: 2.372273]
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138 [D loss: 0.107580, acc.: 97.66%] [G loss: 2.435211]
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139 [D loss: 0.132032, acc.: 95.51%] [G loss: 2.453300]
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140 [D loss: 0.089028, acc.: 98.83%] [G loss: 2.538635]
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141 [D loss: 0.084321, acc.: 97.85%] [G loss: 2.563373]
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142 [D loss: 0.191702, acc.: 94.73%] [G loss: 2.065017]
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143 [D loss: 0.472023, acc.: 79.10%] [G loss: 2.781395]
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144 [D loss: 0.301805, acc.: 88.09%] [G loss: 3.876216]
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145 [D loss: 3.319717, acc.: 43.75%] [G loss: 5.161267]
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146 [D loss: 1.024487, acc.: 59.18%] [G loss: 5.928000]
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147 [D loss: 2.369482, acc.: 37.11%] [G loss: 5.293796]
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148 [D loss: 1.556144, acc.: 34.18%] [G loss: 4.720030]
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149 [D loss: 0.901005, acc.: 66.99%] [G loss: 1.678514]
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150 [D loss: 0.873962, acc.: 53.12%] [G loss: 1.449539]
1/1 [==============================] - 0s 21ms/step
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151 [D loss: 0.687179, acc.: 61.72%] [G loss: 1.544578]
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152 [D loss: 0.833971, acc.: 59.96%] [G loss: 1.218363]
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153 [D loss: 1.042238, acc.: 47.66%] [G loss: 4.596473]
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154 [D loss: 0.753954, acc.: 65.04%] [G loss: 6.054455]
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155 [D loss: 0.610883, acc.: 68.55%] [G loss: 4.793715]
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156 [D loss: 0.445373, acc.: 74.80%] [G loss: 2.967306]
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157 [D loss: 0.732670, acc.: 58.59%] [G loss: 1.679602]
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158 [D loss: 0.392217, acc.: 81.45%] [G loss: 1.361505]
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159 [D loss: 0.445072, acc.: 76.56%] [G loss: 0.943356]
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160 [D loss: 0.435079, acc.: 78.91%] [G loss: 0.707904]
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161 [D loss: 0.425680, acc.: 79.30%] [G loss: 0.782531]
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162 [D loss: 0.528057, acc.: 75.00%] [G loss: 1.037553]
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163 [D loss: 0.485415, acc.: 78.52%] [G loss: 1.253315]
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164 [D loss: 0.495981, acc.: 80.08%] [G loss: 1.364070]
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165 [D loss: 0.554474, acc.: 78.52%] [G loss: 1.403495]
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166 [D loss: 0.545756, acc.: 75.78%] [G loss: 1.657766]
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167 [D loss: 0.566908, acc.: 73.83%] [G loss: 1.193465]
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168 [D loss: 0.618827, acc.: 69.34%] [G loss: 1.225465]
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169 [D loss: 0.553669, acc.: 76.17%] [G loss: 1.291816]
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170 [D loss: 0.693448, acc.: 60.74%] [G loss: 1.035687]
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171 [D loss: 0.561566, acc.: 74.22%] [G loss: 1.100069]
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172 [D loss: 0.556595, acc.: 79.49%] [G loss: 1.051267]
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173 [D loss: 0.535764, acc.: 81.84%] [G loss: 1.068425]
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174 [D loss: 0.487616, acc.: 88.28%] [G loss: 1.130415]
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175 [D loss: 0.463179, acc.: 86.91%] [G loss: 1.193019]
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176 [D loss: 0.489555, acc.: 83.79%] [G loss: 1.241462]
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177 [D loss: 0.392806, acc.: 88.28%] [G loss: 1.299081]
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178 [D loss: 0.447988, acc.: 84.77%] [G loss: 1.503986]
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179 [D loss: 0.419431, acc.: 83.98%] [G loss: 1.652414]
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180 [D loss: 0.354325, acc.: 90.04%] [G loss: 1.689182]
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181 [D loss: 0.356184, acc.: 89.84%] [G loss: 1.708420]
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182 [D loss: 0.356507, acc.: 91.02%] [G loss: 1.634946]
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183 [D loss: 0.348772, acc.: 90.62%] [G loss: 1.769663]
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184 [D loss: 0.331913, acc.: 91.99%] [G loss: 1.867943]
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185 [D loss: 0.294721, acc.: 92.19%] [G loss: 1.840056]
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186 [D loss: 0.392777, acc.: 82.42%] [G loss: 1.844128]
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187 [D loss: 0.451883, acc.: 76.37%] [G loss: 2.038846]
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188 [D loss: 0.507155, acc.: 72.27%] [G loss: 1.906455]
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189 [D loss: 0.566167, acc.: 66.02%] [G loss: 1.809600]
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190 [D loss: 0.520109, acc.: 73.44%] [G loss: 2.044728]
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191 [D loss: 0.452522, acc.: 80.08%] [G loss: 2.007970]
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192 [D loss: 0.546699, acc.: 71.68%] [G loss: 1.789989]
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193 [D loss: 0.475807, acc.: 76.95%] [G loss: 2.159349]
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194 [D loss: 0.457555, acc.: 83.98%] [G loss: 2.172803]
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195 [D loss: 0.497631, acc.: 78.71%] [G loss: 2.275628]
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196 [D loss: 0.564430, acc.: 77.34%] [G loss: 2.245342]
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197 [D loss: 0.534784, acc.: 78.91%] [G loss: 2.780766]
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198 [D loss: 0.516944, acc.: 78.52%] [G loss: 2.769785]
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199 [D loss: 0.450132, acc.: 77.73%] [G loss: 2.693105]
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201 [D loss: 0.421891, acc.: 81.84%] [G loss: 2.356057]
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202 [D loss: 0.355723, acc.: 87.50%] [G loss: 2.528790]
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203 [D loss: 0.385237, acc.: 84.38%] [G loss: 2.335314]
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204 [D loss: 0.433079, acc.: 83.01%] [G loss: 2.251169]
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205 [D loss: 0.520855, acc.: 75.78%] [G loss: 2.018018]
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206 [D loss: 0.573494, acc.: 72.27%] [G loss: 1.639815]
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207 [D loss: 0.534484, acc.: 77.54%] [G loss: 1.522574]
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208 [D loss: 0.597852, acc.: 72.07%] [G loss: 1.316300]
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209 [D loss: 0.571526, acc.: 70.12%] [G loss: 1.293289]
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210 [D loss: 0.633278, acc.: 66.60%] [G loss: 1.266653]
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211 [D loss: 0.667146, acc.: 63.48%] [G loss: 1.455348]
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212 [D loss: 0.757866, acc.: 59.38%] [G loss: 1.295393]
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213 [D loss: 0.660619, acc.: 59.57%] [G loss: 1.807216]
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214 [D loss: 0.557710, acc.: 69.73%] [G loss: 1.967076]
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215 [D loss: 0.601544, acc.: 70.51%] [G loss: 1.984954]
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216 [D loss: 0.493130, acc.: 78.91%] [G loss: 1.952972]
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217 [D loss: 0.427312, acc.: 82.62%] [G loss: 1.941070]
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218 [D loss: 0.479085, acc.: 79.49%] [G loss: 1.864260]
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219 [D loss: 0.515347, acc.: 75.00%] [G loss: 1.477383]
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220 [D loss: 0.518216, acc.: 74.02%] [G loss: 1.288034]
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221 [D loss: 0.647799, acc.: 66.41%] [G loss: 1.358114]
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222 [D loss: 0.592039, acc.: 70.12%] [G loss: 1.294035]
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223 [D loss: 0.558042, acc.: 71.88%] [G loss: 1.321812]
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224 [D loss: 0.577226, acc.: 71.29%] [G loss: 1.405689]
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225 [D loss: 0.483541, acc.: 77.15%] [G loss: 1.461796]
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226 [D loss: 0.539469, acc.: 74.02%] [G loss: 1.366477]
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227 [D loss: 0.494203, acc.: 76.95%] [G loss: 1.359773]
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228 [D loss: 0.520609, acc.: 73.83%] [G loss: 1.337903]
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229 [D loss: 0.488880, acc.: 75.59%] [G loss: 1.315027]
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230 [D loss: 0.561371, acc.: 71.48%] [G loss: 1.314264]
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231 [D loss: 0.542357, acc.: 73.44%] [G loss: 1.472787]
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232 [D loss: 0.519975, acc.: 74.22%] [G loss: 1.395014]
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233 [D loss: 0.499845, acc.: 75.78%] [G loss: 1.377303]
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234 [D loss: 0.517930, acc.: 74.80%] [G loss: 1.404849]
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235 [D loss: 0.527717, acc.: 74.22%] [G loss: 1.431705]
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236 [D loss: 0.615590, acc.: 68.75%] [G loss: 1.546610]
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237 [D loss: 0.616911, acc.: 67.97%] [G loss: 1.400612]
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238 [D loss: 0.643482, acc.: 64.26%] [G loss: 1.248492]
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239 [D loss: 0.703068, acc.: 59.77%] [G loss: 1.100391]
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240 [D loss: 0.767128, acc.: 59.18%] [G loss: 1.137989]
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241 [D loss: 0.841492, acc.: 52.93%] [G loss: 1.119190]
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242 [D loss: 0.814375, acc.: 50.20%] [G loss: 1.178047]
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243 [D loss: 0.804380, acc.: 50.78%] [G loss: 1.089013]
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244 [D loss: 0.730078, acc.: 53.32%] [G loss: 1.104314]
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245 [D loss: 0.747188, acc.: 54.30%] [G loss: 1.048861]
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246 [D loss: 0.743197, acc.: 53.12%] [G loss: 1.017721]
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247 [D loss: 0.769237, acc.: 52.34%] [G loss: 1.022342]
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248 [D loss: 0.712474, acc.: 55.27%] [G loss: 1.015666]
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249 [D loss: 0.745656, acc.: 54.10%] [G loss: 1.028380]
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250 [D loss: 0.659834, acc.: 64.65%] [G loss: 1.031562]
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251 [D loss: 0.683929, acc.: 58.01%] [G loss: 1.032504]
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252 [D loss: 0.638794, acc.: 63.28%] [G loss: 1.017397]
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253 [D loss: 0.663517, acc.: 63.09%] [G loss: 1.038081]
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254 [D loss: 0.674842, acc.: 61.13%] [G loss: 1.014124]
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255 [D loss: 0.648671, acc.: 65.43%] [G loss: 1.020290]
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256 [D loss: 0.636884, acc.: 63.48%] [G loss: 0.989167]
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257 [D loss: 0.654688, acc.: 61.33%] [G loss: 0.974140]
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258 [D loss: 0.653777, acc.: 62.30%] [G loss: 0.934567]
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259 [D loss: 0.671891, acc.: 57.62%] [G loss: 0.886495]
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260 [D loss: 0.702538, acc.: 56.64%] [G loss: 0.879545]
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261 [D loss: 0.702577, acc.: 54.69%] [G loss: 0.877826]
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262 [D loss: 0.681720, acc.: 56.05%] [G loss: 0.845003]
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263 [D loss: 0.684678, acc.: 56.84%] [G loss: 0.855779]
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264 [D loss: 0.662757, acc.: 59.57%] [G loss: 0.818670]
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265 [D loss: 0.693091, acc.: 55.66%] [G loss: 0.783089]
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266 [D loss: 0.708840, acc.: 52.34%] [G loss: 0.795086]
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267 [D loss: 0.725294, acc.: 50.00%] [G loss: 0.792771]
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268 [D loss: 0.700511, acc.: 53.71%] [G loss: 0.832004]
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269 [D loss: 0.685311, acc.: 55.47%] [G loss: 0.818499]
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270 [D loss: 0.714411, acc.: 56.25%] [G loss: 0.831064]
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271 [D loss: 0.685554, acc.: 55.66%] [G loss: 0.854780]
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272 [D loss: 0.724311, acc.: 52.93%] [G loss: 0.830901]
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273 [D loss: 0.754539, acc.: 48.63%] [G loss: 0.835817]
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274 [D loss: 0.720942, acc.: 51.56%] [G loss: 0.819597]
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275 [D loss: 0.725697, acc.: 50.78%] [G loss: 0.835308]
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276 [D loss: 0.732687, acc.: 47.27%] [G loss: 0.845978]
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277 [D loss: 0.705791, acc.: 57.42%] [G loss: 0.891926]
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278 [D loss: 0.696834, acc.: 55.27%] [G loss: 0.847085]
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279 [D loss: 0.707209, acc.: 54.69%] [G loss: 0.913697]
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280 [D loss: 0.707631, acc.: 55.66%] [G loss: 0.827771]
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281 [D loss: 0.719632, acc.: 52.54%] [G loss: 0.832761]
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282 [D loss: 0.712368, acc.: 52.15%] [G loss: 0.775565]
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283 [D loss: 0.701632, acc.: 57.42%] [G loss: 0.805138]
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284 [D loss: 0.709895, acc.: 55.47%] [G loss: 0.819242]
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285 [D loss: 0.716143, acc.: 51.17%] [G loss: 0.800259]
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286 [D loss: 0.741681, acc.: 50.00%] [G loss: 0.845939]
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287 [D loss: 0.718252, acc.: 53.12%] [G loss: 0.799628]
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288 [D loss: 0.736928, acc.: 47.46%] [G loss: 0.814226]
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289 [D loss: 0.725955, acc.: 49.80%] [G loss: 0.800360]
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290 [D loss: 0.727342, acc.: 48.83%] [G loss: 0.790475]
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291 [D loss: 0.718683, acc.: 50.20%] [G loss: 0.778535]
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292 [D loss: 0.733536, acc.: 48.63%] [G loss: 0.744301]
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293 [D loss: 0.712977, acc.: 48.44%] [G loss: 0.768406]
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294 [D loss: 0.729511, acc.: 47.27%] [G loss: 0.761420]
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295 [D loss: 0.715378, acc.: 47.85%] [G loss: 0.770024]
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296 [D loss: 0.717549, acc.: 46.09%] [G loss: 0.754705]
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297 [D loss: 0.712765, acc.: 48.05%] [G loss: 0.753116]
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298 [D loss: 0.720902, acc.: 49.02%] [G loss: 0.739159]
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299 [D loss: 0.711076, acc.: 51.17%] [G loss: 0.752871]
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301 [D loss: 0.726692, acc.: 44.92%] [G loss: 0.726691]
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302 [D loss: 0.730123, acc.: 43.36%] [G loss: 0.730313]
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303 [D loss: 0.720354, acc.: 44.34%] [G loss: 0.725338]
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304 [D loss: 0.718188, acc.: 42.19%] [G loss: 0.734350]
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305 [D loss: 0.726174, acc.: 44.73%] [G loss: 0.747866]
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306 [D loss: 0.720860, acc.: 45.12%] [G loss: 0.748699]
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307 [D loss: 0.715473, acc.: 45.51%] [G loss: 0.735706]
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308 [D loss: 0.716827, acc.: 43.55%] [G loss: 0.725434]
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309 [D loss: 0.715538, acc.: 46.88%] [G loss: 0.723637]
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310 [D loss: 0.720764, acc.: 42.58%] [G loss: 0.728527]
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311 [D loss: 0.706111, acc.: 46.68%] [G loss: 0.717637]
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312 [D loss: 0.717744, acc.: 44.53%] [G loss: 0.712529]
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313 [D loss: 0.716112, acc.: 43.95%] [G loss: 0.723651]
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314 [D loss: 0.709364, acc.: 47.66%] [G loss: 0.722945]
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315 [D loss: 0.715825, acc.: 44.34%] [G loss: 0.703820]
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316 [D loss: 0.710263, acc.: 44.92%] [G loss: 0.702328]
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317 [D loss: 0.716359, acc.: 41.99%] [G loss: 0.708626]
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318 [D loss: 0.716448, acc.: 40.82%] [G loss: 0.707098]
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319 [D loss: 0.713638, acc.: 45.12%] [G loss: 0.706732]
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320 [D loss: 0.719833, acc.: 40.23%] [G loss: 0.701420]
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321 [D loss: 0.710718, acc.: 41.99%] [G loss: 0.698703]
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322 [D loss: 0.713657, acc.: 45.51%] [G loss: 0.711698]
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323 [D loss: 0.715535, acc.: 45.51%] [G loss: 0.712014]
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324 [D loss: 0.719710, acc.: 40.82%] [G loss: 0.701436]
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325 [D loss: 0.709262, acc.: 44.14%] [G loss: 0.700914]
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326 [D loss: 0.705570, acc.: 48.05%] [G loss: 0.708327]
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327 [D loss: 0.700964, acc.: 48.24%] [G loss: 0.706377]
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328 [D loss: 0.706916, acc.: 45.12%] [G loss: 0.698518]
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329 [D loss: 0.714392, acc.: 43.16%] [G loss: 0.701424]
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330 [D loss: 0.712298, acc.: 44.14%] [G loss: 0.707029]
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331 [D loss: 0.708582, acc.: 44.73%] [G loss: 0.706606]
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332 [D loss: 0.709060, acc.: 46.48%] [G loss: 0.706415]
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333 [D loss: 0.712306, acc.: 39.84%] [G loss: 0.706327]
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334 [D loss: 0.706867, acc.: 45.51%] [G loss: 0.700270]
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335 [D loss: 0.702689, acc.: 45.12%] [G loss: 0.712776]
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336 [D loss: 0.701405, acc.: 44.92%] [G loss: 0.698981]
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337 [D loss: 0.709096, acc.: 43.55%] [G loss: 0.710196]
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338 [D loss: 0.703009, acc.: 45.70%] [G loss: 0.702899]
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339 [D loss: 0.706490, acc.: 45.12%] [G loss: 0.704302]
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340 [D loss: 0.705464, acc.: 45.90%] [G loss: 0.701564]
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341 [D loss: 0.707222, acc.: 41.21%] [G loss: 0.709956]
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342 [D loss: 0.710138, acc.: 42.19%] [G loss: 0.708603]
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343 [D loss: 0.703038, acc.: 42.19%] [G loss: 0.703455]
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344 [D loss: 0.700005, acc.: 48.05%] [G loss: 0.704956]
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345 [D loss: 0.699774, acc.: 46.48%] [G loss: 0.703032]
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346 [D loss: 0.703048, acc.: 48.44%] [G loss: 0.697031]
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347 [D loss: 0.702955, acc.: 45.31%] [G loss: 0.693728]
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348 [D loss: 0.704399, acc.: 42.38%] [G loss: 0.690969]
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349 [D loss: 0.699909, acc.: 47.07%] [G loss: 0.697624]
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352 [D loss: 0.706092, acc.: 45.70%] [G loss: 0.700633]
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353 [D loss: 0.704068, acc.: 49.22%] [G loss: 0.706077]
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354 [D loss: 0.698632, acc.: 50.39%] [G loss: 0.690697]
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355 [D loss: 0.701189, acc.: 49.22%] [G loss: 0.699917]
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356 [D loss: 0.700108, acc.: 46.09%] [G loss: 0.701736]
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357 [D loss: 0.699945, acc.: 49.02%] [G loss: 0.699492]
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358 [D loss: 0.702048, acc.: 47.46%] [G loss: 0.701302]
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359 [D loss: 0.699244, acc.: 49.61%] [G loss: 0.697360]
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360 [D loss: 0.703585, acc.: 46.29%] [G loss: 0.699195]
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361 [D loss: 0.703051, acc.: 44.73%] [G loss: 0.696143]
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362 [D loss: 0.700540, acc.: 46.09%] [G loss: 0.694071]
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363 [D loss: 0.703920, acc.: 44.34%] [G loss: 0.696538]
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364 [D loss: 0.706522, acc.: 44.73%] [G loss: 0.694840]
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365 [D loss: 0.699484, acc.: 49.02%] [G loss: 0.693350]
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366 [D loss: 0.707917, acc.: 45.12%] [G loss: 0.688192]
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367 [D loss: 0.701620, acc.: 51.17%] [G loss: 0.693330]
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368 [D loss: 0.704655, acc.: 48.44%] [G loss: 0.689253]
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369 [D loss: 0.704797, acc.: 45.70%] [G loss: 0.695661]
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370 [D loss: 0.701522, acc.: 47.27%] [G loss: 0.689480]
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371 [D loss: 0.706781, acc.: 41.80%] [G loss: 0.697055]
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372 [D loss: 0.703936, acc.: 40.43%] [G loss: 0.700475]
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373 [D loss: 0.703777, acc.: 41.60%] [G loss: 0.698594]
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374 [D loss: 0.699582, acc.: 44.14%] [G loss: 0.698649]
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375 [D loss: 0.701587, acc.: 43.55%] [G loss: 0.699556]
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376 [D loss: 0.707435, acc.: 39.26%] [G loss: 0.694013]
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378 [D loss: 0.699907, acc.: 45.51%] [G loss: 0.697896]
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379 [D loss: 0.704364, acc.: 43.95%] [G loss: 0.704332]
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380 [D loss: 0.704580, acc.: 43.16%] [G loss: 0.703128]
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381 [D loss: 0.704455, acc.: 44.53%] [G loss: 0.701490]
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382 [D loss: 0.700823, acc.: 45.90%] [G loss: 0.699662]
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383 [D loss: 0.702017, acc.: 44.73%] [G loss: 0.691535]
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384 [D loss: 0.699504, acc.: 44.92%] [G loss: 0.696593]
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385 [D loss: 0.700915, acc.: 42.19%] [G loss: 0.693432]
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386 [D loss: 0.700217, acc.: 47.85%] [G loss: 0.704289]
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387 [D loss: 0.700594, acc.: 43.36%] [G loss: 0.697590]
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388 [D loss: 0.702907, acc.: 43.36%] [G loss: 0.696583]
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389 [D loss: 0.702574, acc.: 43.55%] [G loss: 0.695595]
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390 [D loss: 0.698592, acc.: 47.85%] [G loss: 0.697789]
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391 [D loss: 0.699180, acc.: 48.63%] [G loss: 0.705204]
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392 [D loss: 0.700222, acc.: 45.31%] [G loss: 0.704545]
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393 [D loss: 0.699013, acc.: 48.63%] [G loss: 0.708217]
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394 [D loss: 0.702125, acc.: 43.55%] [G loss: 0.701384]
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395 [D loss: 0.695022, acc.: 50.20%] [G loss: 0.709495]
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396 [D loss: 0.696727, acc.: 49.61%] [G loss: 0.711140]
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397 [D loss: 0.697198, acc.: 46.88%] [G loss: 0.706895]
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398 [D loss: 0.702918, acc.: 43.16%] [G loss: 0.701936]
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399 [D loss: 0.700459, acc.: 47.27%] [G loss: 0.706270]
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400 [D loss: 0.698992, acc.: 47.46%] [G loss: 0.704429]
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401 [D loss: 0.700090, acc.: 47.07%] [G loss: 0.705047]
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402 [D loss: 0.695869, acc.: 48.83%] [G loss: 0.701134]
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403 [D loss: 0.699335, acc.: 47.07%] [G loss: 0.703507]
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404 [D loss: 0.701293, acc.: 48.05%] [G loss: 0.705345]
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405 [D loss: 0.698577, acc.: 49.80%] [G loss: 0.701729]
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406 [D loss: 0.695530, acc.: 52.34%] [G loss: 0.699759]
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407 [D loss: 0.700020, acc.: 45.51%] [G loss: 0.700992]
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408 [D loss: 0.700625, acc.: 50.78%] [G loss: 0.693823]
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409 [D loss: 0.697034, acc.: 50.59%] [G loss: 0.692668]
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410 [D loss: 0.696973, acc.: 51.76%] [G loss: 0.706769]
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411 [D loss: 0.697286, acc.: 49.80%] [G loss: 0.702155]
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412 [D loss: 0.698977, acc.: 48.44%] [G loss: 0.707237]
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413 [D loss: 0.698796, acc.: 47.07%] [G loss: 0.706093]
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414 [D loss: 0.701918, acc.: 47.07%] [G loss: 0.707444]
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415 [D loss: 0.695378, acc.: 49.22%] [G loss: 0.702171]
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416 [D loss: 0.697382, acc.: 49.61%] [G loss: 0.700848]
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417 [D loss: 0.697497, acc.: 48.24%] [G loss: 0.699324]
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418 [D loss: 0.696719, acc.: 51.76%] [G loss: 0.702148]
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419 [D loss: 0.701723, acc.: 47.46%] [G loss: 0.694512]
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420 [D loss: 0.697415, acc.: 48.24%] [G loss: 0.700126]
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421 [D loss: 0.697801, acc.: 47.27%] [G loss: 0.701652]
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422 [D loss: 0.700894, acc.: 48.63%] [G loss: 0.693870]
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423 [D loss: 0.697521, acc.: 52.34%] [G loss: 0.698060]
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424 [D loss: 0.698502, acc.: 48.63%] [G loss: 0.697278]
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425 [D loss: 0.700196, acc.: 50.00%] [G loss: 0.701243]
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426 [D loss: 0.699291, acc.: 48.24%] [G loss: 0.706458]
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427 [D loss: 0.699747, acc.: 46.48%] [G loss: 0.708393]
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428 [D loss: 0.697483, acc.: 49.41%] [G loss: 0.705610]
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429 [D loss: 0.697779, acc.: 47.27%] [G loss: 0.713936]
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430 [D loss: 0.702037, acc.: 43.95%] [G loss: 0.703862]
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431 [D loss: 0.697363, acc.: 47.46%] [G loss: 0.697034]
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432 [D loss: 0.702061, acc.: 44.53%] [G loss: 0.698935]
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433 [D loss: 0.696965, acc.: 46.68%] [G loss: 0.694212]
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434 [D loss: 0.700650, acc.: 41.60%] [G loss: 0.698908]
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435 [D loss: 0.696813, acc.: 48.05%] [G loss: 0.695619]
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436 [D loss: 0.700434, acc.: 46.48%] [G loss: 0.697380]
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437 [D loss: 0.698645, acc.: 45.70%] [G loss: 0.693749]
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438 [D loss: 0.699272, acc.: 43.36%] [G loss: 0.697373]
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439 [D loss: 0.695574, acc.: 47.85%] [G loss: 0.697215]
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440 [D loss: 0.701160, acc.: 42.58%] [G loss: 0.695797]
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441 [D loss: 0.702495, acc.: 42.19%] [G loss: 0.699994]
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442 [D loss: 0.697384, acc.: 48.63%] [G loss: 0.700656]
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443 [D loss: 0.696806, acc.: 49.02%] [G loss: 0.701436]
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444 [D loss: 0.698517, acc.: 45.51%] [G loss: 0.705961]
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445 [D loss: 0.695050, acc.: 50.20%] [G loss: 0.707097]
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446 [D loss: 0.695039, acc.: 49.22%] [G loss: 0.703618]
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447 [D loss: 0.694887, acc.: 51.76%] [G loss: 0.706822]
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448 [D loss: 0.691210, acc.: 50.78%] [G loss: 0.706078]
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449 [D loss: 0.695133, acc.: 51.17%] [G loss: 0.700362]
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450 [D loss: 0.694396, acc.: 51.76%] [G loss: 0.704984]
1/1 [==============================] - 0s 20ms/step
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451 [D loss: 0.698685, acc.: 48.24%] [G loss: 0.701869]
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452 [D loss: 0.697790, acc.: 48.44%] [G loss: 0.699434]
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453 [D loss: 0.697506, acc.: 50.59%] [G loss: 0.705138]
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454 [D loss: 0.699398, acc.: 44.92%] [G loss: 0.699092]
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455 [D loss: 0.696610, acc.: 47.46%] [G loss: 0.706536]
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456 [D loss: 0.696520, acc.: 52.34%] [G loss: 0.702947]
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457 [D loss: 0.697174, acc.: 46.48%] [G loss: 0.704274]
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458 [D loss: 0.693973, acc.: 51.17%] [G loss: 0.703286]
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459 [D loss: 0.692113, acc.: 51.95%] [G loss: 0.699345]
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460 [D loss: 0.693964, acc.: 50.59%] [G loss: 0.698301]
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461 [D loss: 0.695376, acc.: 50.39%] [G loss: 0.697386]
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462 [D loss: 0.694344, acc.: 52.15%] [G loss: 0.692932]
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463 [D loss: 0.696387, acc.: 48.05%] [G loss: 0.696868]
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464 [D loss: 0.700107, acc.: 44.14%] [G loss: 0.691414]
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465 [D loss: 0.698253, acc.: 47.66%] [G loss: 0.702337]
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466 [D loss: 0.694411, acc.: 51.37%] [G loss: 0.699566]
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467 [D loss: 0.694694, acc.: 50.59%] [G loss: 0.702401]
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468 [D loss: 0.695766, acc.: 49.41%] [G loss: 0.699686]
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469 [D loss: 0.696284, acc.: 48.44%] [G loss: 0.705763]
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470 [D loss: 0.697377, acc.: 44.92%] [G loss: 0.694417]
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471 [D loss: 0.696998, acc.: 46.29%] [G loss: 0.694233]
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472 [D loss: 0.698974, acc.: 44.34%] [G loss: 0.694683]
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473 [D loss: 0.701307, acc.: 42.77%] [G loss: 0.696819]
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474 [D loss: 0.697991, acc.: 47.07%] [G loss: 0.697631]
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475 [D loss: 0.698165, acc.: 46.48%] [G loss: 0.695545]
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476 [D loss: 0.700140, acc.: 47.46%] [G loss: 0.696886]
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477 [D loss: 0.695985, acc.: 47.66%] [G loss: 0.698723]
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478 [D loss: 0.698889, acc.: 45.90%] [G loss: 0.703025]
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479 [D loss: 0.695932, acc.: 49.02%] [G loss: 0.699430]
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480 [D loss: 0.698683, acc.: 45.51%] [G loss: 0.697620]
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481 [D loss: 0.697773, acc.: 45.70%] [G loss: 0.696587]
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482 [D loss: 0.698400, acc.: 45.31%] [G loss: 0.701941]
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483 [D loss: 0.697582, acc.: 46.48%] [G loss: 0.699529]
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484 [D loss: 0.699499, acc.: 42.58%] [G loss: 0.696397]
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485 [D loss: 0.699958, acc.: 41.21%] [G loss: 0.694242]
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486 [D loss: 0.698542, acc.: 45.31%] [G loss: 0.692535]
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487 [D loss: 0.697597, acc.: 43.75%] [G loss: 0.688943]
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488 [D loss: 0.699810, acc.: 44.34%] [G loss: 0.691214]
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489 [D loss: 0.698913, acc.: 44.73%] [G loss: 0.690604]
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490 [D loss: 0.698774, acc.: 43.55%] [G loss: 0.691392]
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491 [D loss: 0.696724, acc.: 45.90%] [G loss: 0.693441]
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492 [D loss: 0.698382, acc.: 44.14%] [G loss: 0.696850]
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493 [D loss: 0.696073, acc.: 43.55%] [G loss: 0.695591]
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494 [D loss: 0.696218, acc.: 43.75%] [G loss: 0.699582]
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495 [D loss: 0.697095, acc.: 43.55%] [G loss: 0.702551]
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496 [D loss: 0.696730, acc.: 41.80%] [G loss: 0.700804]
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497 [D loss: 0.697396, acc.: 41.99%] [G loss: 0.703363]
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498 [D loss: 0.696520, acc.: 42.19%] [G loss: 0.701937]
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499 [D loss: 0.696165, acc.: 44.92%] [G loss: 0.703223]
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500 [D loss: 0.698237, acc.: 46.48%] [G loss: 0.700543]
1/1 [==============================] - 0s 20ms/step
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501 [D loss: 0.699438, acc.: 41.02%] [G loss: 0.700292]
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502 [D loss: 0.698100, acc.: 42.58%] [G loss: 0.696759]
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503 [D loss: 0.698224, acc.: 41.02%] [G loss: 0.700350]
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504 [D loss: 0.696138, acc.: 44.53%] [G loss: 0.699923]
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505 [D loss: 0.695924, acc.: 44.92%] [G loss: 0.699802]
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506 [D loss: 0.694872, acc.: 48.63%] [G loss: 0.701873]
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507 [D loss: 0.695042, acc.: 50.59%] [G loss: 0.705732]
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508 [D loss: 0.693522, acc.: 50.98%] [G loss: 0.705136]
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509 [D loss: 0.693069, acc.: 51.37%] [G loss: 0.707777]
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510 [D loss: 0.694634, acc.: 48.05%] [G loss: 0.703481]
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511 [D loss: 0.698073, acc.: 44.34%] [G loss: 0.709331]
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512 [D loss: 0.698215, acc.: 40.62%] [G loss: 0.699568]
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513 [D loss: 0.697603, acc.: 47.66%] [G loss: 0.694205]
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514 [D loss: 0.697028, acc.: 41.41%] [G loss: 0.700439]
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515 [D loss: 0.696925, acc.: 44.53%] [G loss: 0.693848]
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516 [D loss: 0.698502, acc.: 44.53%] [G loss: 0.695535]
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517 [D loss: 0.697523, acc.: 45.90%] [G loss: 0.700034]
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518 [D loss: 0.696849, acc.: 45.51%] [G loss: 0.699320]
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519 [D loss: 0.694538, acc.: 52.73%] [G loss: 0.700035]
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520 [D loss: 0.693615, acc.: 51.56%] [G loss: 0.707779]
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521 [D loss: 0.694233, acc.: 49.22%] [G loss: 0.702531]
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522 [D loss: 0.694420, acc.: 48.44%] [G loss: 0.704127]
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523 [D loss: 0.695919, acc.: 50.20%] [G loss: 0.702645]
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524 [D loss: 0.697830, acc.: 42.77%] [G loss: 0.703298]
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525 [D loss: 0.700104, acc.: 43.75%] [G loss: 0.703001]
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526 [D loss: 0.699206, acc.: 40.82%] [G loss: 0.700003]
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527 [D loss: 0.699666, acc.: 41.02%] [G loss: 0.700402]
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528 [D loss: 0.697111, acc.: 46.48%] [G loss: 0.704523]
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529 [D loss: 0.696863, acc.: 44.34%] [G loss: 0.702749]
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530 [D loss: 0.698302, acc.: 41.21%] [G loss: 0.702881]
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531 [D loss: 0.696862, acc.: 46.88%] [G loss: 0.700232]
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532 [D loss: 0.695030, acc.: 49.80%] [G loss: 0.700680]
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533 [D loss: 0.696337, acc.: 46.09%] [G loss: 0.704828]
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534 [D loss: 0.695473, acc.: 48.83%] [G loss: 0.704647]
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535 [D loss: 0.694040, acc.: 49.02%] [G loss: 0.707366]
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536 [D loss: 0.695778, acc.: 47.85%] [G loss: 0.703970]
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537 [D loss: 0.696004, acc.: 48.44%] [G loss: 0.705872]
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538 [D loss: 0.693684, acc.: 50.78%] [G loss: 0.700818]
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539 [D loss: 0.696665, acc.: 47.66%] [G loss: 0.694732]
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540 [D loss: 0.696916, acc.: 46.68%] [G loss: 0.694328]
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541 [D loss: 0.700021, acc.: 40.62%] [G loss: 0.692555]
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542 [D loss: 0.699925, acc.: 40.82%] [G loss: 0.690336]
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543 [D loss: 0.698267, acc.: 40.82%] [G loss: 0.692224]
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544 [D loss: 0.698637, acc.: 41.80%] [G loss: 0.690188]
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545 [D loss: 0.699492, acc.: 43.36%] [G loss: 0.689955]
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546 [D loss: 0.699215, acc.: 40.62%] [G loss: 0.693417]
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547 [D loss: 0.695949, acc.: 45.31%] [G loss: 0.692799]
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548 [D loss: 0.695289, acc.: 49.61%] [G loss: 0.696643]
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549 [D loss: 0.696657, acc.: 47.27%] [G loss: 0.695850]
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550 [D loss: 0.698678, acc.: 41.41%] [G loss: 0.699141]
1/1 [==============================] - 0s 22ms/step
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551 [D loss: 0.696370, acc.: 43.75%] [G loss: 0.693936]
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552 [D loss: 0.696850, acc.: 43.16%] [G loss: 0.697895]
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553 [D loss: 0.697792, acc.: 43.75%] [G loss: 0.692828]
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554 [D loss: 0.699024, acc.: 41.02%] [G loss: 0.696319]
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555 [D loss: 0.698032, acc.: 40.04%] [G loss: 0.696940]
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556 [D loss: 0.699846, acc.: 38.28%] [G loss: 0.694692]
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557 [D loss: 0.697014, acc.: 42.97%] [G loss: 0.697094]
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558 [D loss: 0.696690, acc.: 42.77%] [G loss: 0.697120]
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559 [D loss: 0.695912, acc.: 46.88%] [G loss: 0.694768]
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560 [D loss: 0.695820, acc.: 45.90%] [G loss: 0.697099]
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561 [D loss: 0.694815, acc.: 46.48%] [G loss: 0.695004]
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562 [D loss: 0.695386, acc.: 47.85%] [G loss: 0.695016]
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563 [D loss: 0.696178, acc.: 46.29%] [G loss: 0.696001]
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564 [D loss: 0.696557, acc.: 41.80%] [G loss: 0.695954]
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565 [D loss: 0.694022, acc.: 48.44%] [G loss: 0.694480]
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566 [D loss: 0.697340, acc.: 42.77%] [G loss: 0.697123]
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567 [D loss: 0.697834, acc.: 40.62%] [G loss: 0.695112]
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568 [D loss: 0.696437, acc.: 41.80%] [G loss: 0.696654]
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569 [D loss: 0.696188, acc.: 43.55%] [G loss: 0.698688]
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570 [D loss: 0.696395, acc.: 44.14%] [G loss: 0.697133]
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571 [D loss: 0.695625, acc.: 45.12%] [G loss: 0.697892]
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572 [D loss: 0.693884, acc.: 47.85%] [G loss: 0.699364]
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573 [D loss: 0.695308, acc.: 43.75%] [G loss: 0.698152]
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574 [D loss: 0.697273, acc.: 41.99%] [G loss: 0.695206]
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575 [D loss: 0.695473, acc.: 44.92%] [G loss: 0.694156]
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576 [D loss: 0.694471, acc.: 47.07%] [G loss: 0.690451]
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577 [D loss: 0.694583, acc.: 45.70%] [G loss: 0.692573]
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578 [D loss: 0.694368, acc.: 47.66%] [G loss: 0.691117]
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579 [D loss: 0.695345, acc.: 46.88%] [G loss: 0.689575]
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580 [D loss: 0.694112, acc.: 47.66%] [G loss: 0.694331]
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581 [D loss: 0.694730, acc.: 48.83%] [G loss: 0.692773]
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582 [D loss: 0.693388, acc.: 50.59%] [G loss: 0.694146]
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583 [D loss: 0.695242, acc.: 47.07%] [G loss: 0.691967]
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584 [D loss: 0.694251, acc.: 47.66%] [G loss: 0.695794]
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585 [D loss: 0.695485, acc.: 47.46%] [G loss: 0.698175]
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586 [D loss: 0.695982, acc.: 44.34%] [G loss: 0.697016]
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587 [D loss: 0.697117, acc.: 42.58%] [G loss: 0.699043]
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588 [D loss: 0.695418, acc.: 45.31%] [G loss: 0.697508]
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589 [D loss: 0.696027, acc.: 47.66%] [G loss: 0.695820]
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590 [D loss: 0.696732, acc.: 42.97%] [G loss: 0.696943]
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591 [D loss: 0.696713, acc.: 44.53%] [G loss: 0.697228]
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592 [D loss: 0.695338, acc.: 48.24%] [G loss: 0.700385]
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593 [D loss: 0.696177, acc.: 43.16%] [G loss: 0.700860]
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594 [D loss: 0.694492, acc.: 48.44%] [G loss: 0.698663]
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595 [D loss: 0.694335, acc.: 52.15%] [G loss: 0.696813]
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596 [D loss: 0.695620, acc.: 44.73%] [G loss: 0.699195]
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597 [D loss: 0.694531, acc.: 50.00%] [G loss: 0.697315]
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598 [D loss: 0.693158, acc.: 50.78%] [G loss: 0.699435]
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599 [D loss: 0.695525, acc.: 48.05%] [G loss: 0.696706]
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600 [D loss: 0.694936, acc.: 48.05%] [G loss: 0.701178]
1/1 [==============================] - 0s 21ms/step
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601 [D loss: 0.694547, acc.: 51.76%] [G loss: 0.698834]
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602 [D loss: 0.693767, acc.: 51.76%] [G loss: 0.698598]
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603 [D loss: 0.694231, acc.: 50.59%] [G loss: 0.698296]
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604 [D loss: 0.693279, acc.: 50.98%] [G loss: 0.698906]
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605 [D loss: 0.693543, acc.: 50.59%] [G loss: 0.694756]
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606 [D loss: 0.695257, acc.: 46.68%] [G loss: 0.694078]
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607 [D loss: 0.695877, acc.: 45.90%] [G loss: 0.693939]
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608 [D loss: 0.693605, acc.: 49.41%] [G loss: 0.698047]
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609 [D loss: 0.692162, acc.: 53.91%] [G loss: 0.697832]
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610 [D loss: 0.694545, acc.: 49.80%] [G loss: 0.697399]
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611 [D loss: 0.693886, acc.: 50.98%] [G loss: 0.701536]
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612 [D loss: 0.694707, acc.: 52.54%] [G loss: 0.703915]
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613 [D loss: 0.695085, acc.: 48.44%] [G loss: 0.702560]
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614 [D loss: 0.693478, acc.: 48.83%] [G loss: 0.702538]
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615 [D loss: 0.695578, acc.: 47.85%] [G loss: 0.699607]
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616 [D loss: 0.697437, acc.: 46.48%] [G loss: 0.694630]
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617 [D loss: 0.698814, acc.: 44.53%] [G loss: 0.691353]
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618 [D loss: 0.698189, acc.: 45.70%] [G loss: 0.695527]
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619 [D loss: 0.697787, acc.: 47.46%] [G loss: 0.692945]
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620 [D loss: 0.698809, acc.: 46.09%] [G loss: 0.695489]
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621 [D loss: 0.694414, acc.: 49.61%] [G loss: 0.697531]
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622 [D loss: 0.693962, acc.: 49.80%] [G loss: 0.698779]
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623 [D loss: 0.694264, acc.: 52.54%] [G loss: 0.698774]
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624 [D loss: 0.694058, acc.: 51.17%] [G loss: 0.698194]
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625 [D loss: 0.694349, acc.: 50.39%] [G loss: 0.703324]
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626 [D loss: 0.692122, acc.: 52.73%] [G loss: 0.701789]
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627 [D loss: 0.692714, acc.: 53.91%] [G loss: 0.699943]
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628 [D loss: 0.693138, acc.: 52.15%] [G loss: 0.697726]
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629 [D loss: 0.695159, acc.: 45.90%] [G loss: 0.695608]
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630 [D loss: 0.696023, acc.: 45.51%] [G loss: 0.689824]
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631 [D loss: 0.696628, acc.: 44.53%] [G loss: 0.692955]
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632 [D loss: 0.696739, acc.: 45.70%] [G loss: 0.692650]
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633 [D loss: 0.695305, acc.: 49.22%] [G loss: 0.693595]
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634 [D loss: 0.695759, acc.: 46.29%] [G loss: 0.693533]
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635 [D loss: 0.696413, acc.: 49.02%] [G loss: 0.695435]
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636 [D loss: 0.692798, acc.: 52.34%] [G loss: 0.695065]
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637 [D loss: 0.695420, acc.: 50.00%] [G loss: 0.699300]
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638 [D loss: 0.695513, acc.: 48.44%] [G loss: 0.696192]
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639 [D loss: 0.695074, acc.: 47.27%] [G loss: 0.696903]
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640 [D loss: 0.695529, acc.: 48.83%] [G loss: 0.696680]
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641 [D loss: 0.694934, acc.: 49.80%] [G loss: 0.695933]
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642 [D loss: 0.695612, acc.: 47.66%] [G loss: 0.693076]
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643 [D loss: 0.694665, acc.: 48.63%] [G loss: 0.697511]
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644 [D loss: 0.695101, acc.: 46.29%] [G loss: 0.694314]
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645 [D loss: 0.693224, acc.: 51.76%] [G loss: 0.694926]
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646 [D loss: 0.694589, acc.: 50.20%] [G loss: 0.695675]
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647 [D loss: 0.695038, acc.: 48.24%] [G loss: 0.696164]
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648 [D loss: 0.695553, acc.: 47.46%] [G loss: 0.696567]
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649 [D loss: 0.693774, acc.: 49.41%] [G loss: 0.696083]
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650 [D loss: 0.693896, acc.: 50.98%] [G loss: 0.694569]
1/1 [==============================] - 0s 27ms/step
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651 [D loss: 0.693529, acc.: 52.54%] [G loss: 0.698565]
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652 [D loss: 0.696934, acc.: 46.48%] [G loss: 0.698597]
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653 [D loss: 0.695478, acc.: 47.46%] [G loss: 0.698250]
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654 [D loss: 0.696390, acc.: 46.29%] [G loss: 0.699213]
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655 [D loss: 0.696964, acc.: 46.29%] [G loss: 0.699400]
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656 [D loss: 0.697308, acc.: 44.73%] [G loss: 0.699435]
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657 [D loss: 0.694890, acc.: 49.80%] [G loss: 0.701047]
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658 [D loss: 0.695444, acc.: 49.61%] [G loss: 0.701351]
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659 [D loss: 0.694554, acc.: 50.39%] [G loss: 0.699343]
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660 [D loss: 0.695099, acc.: 49.80%] [G loss: 0.698061]
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661 [D loss: 0.695420, acc.: 48.05%] [G loss: 0.701191]
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662 [D loss: 0.694111, acc.: 52.73%] [G loss: 0.699133]
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663 [D loss: 0.693885, acc.: 50.78%] [G loss: 0.694057]
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664 [D loss: 0.695000, acc.: 47.66%] [G loss: 0.693861]
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665 [D loss: 0.695490, acc.: 47.46%] [G loss: 0.696863]
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666 [D loss: 0.693740, acc.: 51.17%] [G loss: 0.692643]
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667 [D loss: 0.694892, acc.: 48.24%] [G loss: 0.689334]
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668 [D loss: 0.695740, acc.: 47.07%] [G loss: 0.691018]
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669 [D loss: 0.697088, acc.: 44.34%] [G loss: 0.690921]
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670 [D loss: 0.695710, acc.: 47.27%] [G loss: 0.691382]
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671 [D loss: 0.696649, acc.: 48.24%] [G loss: 0.693149]
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672 [D loss: 0.695835, acc.: 47.66%] [G loss: 0.690774]
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673 [D loss: 0.695267, acc.: 49.80%] [G loss: 0.693706]
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674 [D loss: 0.694731, acc.: 49.41%] [G loss: 0.698751]
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675 [D loss: 0.693967, acc.: 50.98%] [G loss: 0.699422]
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676 [D loss: 0.694586, acc.: 44.53%] [G loss: 0.699521]
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677 [D loss: 0.693651, acc.: 50.39%] [G loss: 0.704864]
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678 [D loss: 0.692675, acc.: 53.91%] [G loss: 0.704016]
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679 [D loss: 0.692759, acc.: 53.52%] [G loss: 0.703780]
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680 [D loss: 0.693776, acc.: 51.95%] [G loss: 0.703301]
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681 [D loss: 0.693911, acc.: 55.08%] [G loss: 0.704528]
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682 [D loss: 0.694196, acc.: 52.15%] [G loss: 0.703491]
8/8 [==============================] - 0s 4ms/step
683 [D loss: 0.695293, acc.: 49.80%] [G loss: 0.700379]
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684 [D loss: 0.696964, acc.: 47.85%] [G loss: 0.702494]
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685 [D loss: 0.696142, acc.: 48.24%] [G loss: 0.701748]
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686 [D loss: 0.695655, acc.: 48.63%] [G loss: 0.699530]
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687 [D loss: 0.696924, acc.: 48.63%] [G loss: 0.698742]
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688 [D loss: 0.697266, acc.: 43.55%] [G loss: 0.696596]
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689 [D loss: 0.696126, acc.: 49.61%] [G loss: 0.694623]
8/8 [==============================] - 0s 4ms/step
690 [D loss: 0.695530, acc.: 45.70%] [G loss: 0.692922]
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691 [D loss: 0.695336, acc.: 48.05%] [G loss: 0.693297]
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692 [D loss: 0.695745, acc.: 45.12%] [G loss: 0.695025]
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693 [D loss: 0.694332, acc.: 47.66%] [G loss: 0.694317]
8/8 [==============================] - 0s 4ms/step
694 [D loss: 0.693134, acc.: 49.61%] [G loss: 0.692903]
8/8 [==============================] - 0s 4ms/step
695 [D loss: 0.694326, acc.: 47.07%] [G loss: 0.692870]
8/8 [==============================] - 0s 4ms/step
696 [D loss: 0.694791, acc.: 47.07%] [G loss: 0.691098]
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697 [D loss: 0.695054, acc.: 50.78%] [G loss: 0.692790]
8/8 [==============================] - 0s 4ms/step
698 [D loss: 0.694666, acc.: 49.41%] [G loss: 0.691902]
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699 [D loss: 0.695364, acc.: 46.68%] [G loss: 0.692620]
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700 [D loss: 0.696047, acc.: 44.73%] [G loss: 0.696518]
1/1 [==============================] - 0s 22ms/step
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701 [D loss: 0.695572, acc.: 46.29%] [G loss: 0.693179]
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702 [D loss: 0.696654, acc.: 41.99%] [G loss: 0.692790]
8/8 [==============================] - 0s 4ms/step
703 [D loss: 0.696720, acc.: 42.19%] [G loss: 0.696071]
8/8 [==============================] - 0s 4ms/step
704 [D loss: 0.695986, acc.: 44.14%] [G loss: 0.699309]
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705 [D loss: 0.694592, acc.: 48.44%] [G loss: 0.697532]
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706 [D loss: 0.695433, acc.: 46.88%] [G loss: 0.699809]
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707 [D loss: 0.693243, acc.: 50.39%] [G loss: 0.702298]
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708 [D loss: 0.692505, acc.: 55.08%] [G loss: 0.706070]
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709 [D loss: 0.694611, acc.: 50.98%] [G loss: 0.707618]
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710 [D loss: 0.693864, acc.: 50.39%] [G loss: 0.710976]
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711 [D loss: 0.695578, acc.: 50.00%] [G loss: 0.706663]
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712 [D loss: 0.693416, acc.: 50.00%] [G loss: 0.706257]
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713 [D loss: 0.694069, acc.: 50.98%] [G loss: 0.707760]
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714 [D loss: 0.695199, acc.: 46.88%] [G loss: 0.703547]
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715 [D loss: 0.695268, acc.: 47.85%] [G loss: 0.701008]
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716 [D loss: 0.692772, acc.: 52.34%] [G loss: 0.698481]
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717 [D loss: 0.694287, acc.: 49.22%] [G loss: 0.695848]
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718 [D loss: 0.694490, acc.: 50.00%] [G loss: 0.691734]
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719 [D loss: 0.695544, acc.: 48.24%] [G loss: 0.692690]
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720 [D loss: 0.694391, acc.: 49.41%] [G loss: 0.692185]
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721 [D loss: 0.694632, acc.: 51.56%] [G loss: 0.693823]
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722 [D loss: 0.693873, acc.: 50.98%] [G loss: 0.695397]
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723 [D loss: 0.695316, acc.: 47.07%] [G loss: 0.696357]
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724 [D loss: 0.693522, acc.: 50.78%] [G loss: 0.698298]
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725 [D loss: 0.692677, acc.: 53.52%] [G loss: 0.701161]
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726 [D loss: 0.692591, acc.: 53.52%] [G loss: 0.704219]
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727 [D loss: 0.692998, acc.: 53.71%] [G loss: 0.707683]
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728 [D loss: 0.693677, acc.: 48.44%] [G loss: 0.707800]
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729 [D loss: 0.692949, acc.: 47.46%] [G loss: 0.707308]
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730 [D loss: 0.692508, acc.: 52.73%] [G loss: 0.708512]
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731 [D loss: 0.693757, acc.: 49.61%] [G loss: 0.706750]
8/8 [==============================] - 0s 4ms/step
732 [D loss: 0.693417, acc.: 47.85%] [G loss: 0.707664]
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733 [D loss: 0.693780, acc.: 49.22%] [G loss: 0.704665]
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734 [D loss: 0.693394, acc.: 52.73%] [G loss: 0.704709]
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735 [D loss: 0.694058, acc.: 51.37%] [G loss: 0.700380]
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736 [D loss: 0.695554, acc.: 49.41%] [G loss: 0.700419]
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737 [D loss: 0.695447, acc.: 47.46%] [G loss: 0.695881]
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738 [D loss: 0.697063, acc.: 42.97%] [G loss: 0.693581]
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739 [D loss: 0.694478, acc.: 45.70%] [G loss: 0.694191]
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740 [D loss: 0.694755, acc.: 46.29%] [G loss: 0.698060]
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741 [D loss: 0.693530, acc.: 51.37%] [G loss: 0.698887]
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742 [D loss: 0.693813, acc.: 50.59%] [G loss: 0.696784]
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743 [D loss: 0.693398, acc.: 49.80%] [G loss: 0.697677]
8/8 [==============================] - 0s 4ms/step
744 [D loss: 0.693248, acc.: 47.85%] [G loss: 0.698882]
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745 [D loss: 0.691864, acc.: 53.32%] [G loss: 0.698828]
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746 [D loss: 0.693370, acc.: 49.61%] [G loss: 0.699102]
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747 [D loss: 0.693648, acc.: 49.61%] [G loss: 0.698191]
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748 [D loss: 0.693519, acc.: 50.98%] [G loss: 0.697189]
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749 [D loss: 0.692209, acc.: 52.93%] [G loss: 0.698716]
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750 [D loss: 0.693097, acc.: 51.95%] [G loss: 0.700240]
1/1 [==============================] - 0s 23ms/step
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751 [D loss: 0.694596, acc.: 50.39%] [G loss: 0.695979]
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752 [D loss: 0.693894, acc.: 51.37%] [G loss: 0.695953]
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753 [D loss: 0.694684, acc.: 45.70%] [G loss: 0.696488]
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754 [D loss: 0.694283, acc.: 47.46%] [G loss: 0.695409]
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755 [D loss: 0.694975, acc.: 45.12%] [G loss: 0.695095]
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756 [D loss: 0.692857, acc.: 50.59%] [G loss: 0.694198]
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757 [D loss: 0.695343, acc.: 48.83%] [G loss: 0.693033]
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758 [D loss: 0.694418, acc.: 47.46%] [G loss: 0.691956]
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759 [D loss: 0.696117, acc.: 46.88%] [G loss: 0.693028]
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760 [D loss: 0.694040, acc.: 47.46%] [G loss: 0.697353]
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761 [D loss: 0.693207, acc.: 49.22%] [G loss: 0.696093]
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762 [D loss: 0.693046, acc.: 51.17%] [G loss: 0.701514]
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763 [D loss: 0.694423, acc.: 46.88%] [G loss: 0.699395]
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764 [D loss: 0.693732, acc.: 46.88%] [G loss: 0.699017]
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765 [D loss: 0.693614, acc.: 48.05%] [G loss: 0.702527]
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766 [D loss: 0.694611, acc.: 47.66%] [G loss: 0.700566]
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767 [D loss: 0.692234, acc.: 52.15%] [G loss: 0.700518]
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768 [D loss: 0.693164, acc.: 50.59%] [G loss: 0.696974]
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769 [D loss: 0.692950, acc.: 48.44%] [G loss: 0.698149]
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770 [D loss: 0.693120, acc.: 50.59%] [G loss: 0.698956]
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771 [D loss: 0.692562, acc.: 50.39%] [G loss: 0.699890]
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772 [D loss: 0.692941, acc.: 48.05%] [G loss: 0.699568]
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773 [D loss: 0.695152, acc.: 47.07%] [G loss: 0.697135]
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774 [D loss: 0.694877, acc.: 47.46%] [G loss: 0.697555]
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775 [D loss: 0.694950, acc.: 49.02%] [G loss: 0.695181]
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776 [D loss: 0.693353, acc.: 49.41%] [G loss: 0.696551]
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777 [D loss: 0.693744, acc.: 47.27%] [G loss: 0.697829]
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778 [D loss: 0.693180, acc.: 53.32%] [G loss: 0.697750]
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779 [D loss: 0.692582, acc.: 50.59%] [G loss: 0.694969]
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780 [D loss: 0.694121, acc.: 53.12%] [G loss: 0.696407]
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781 [D loss: 0.693077, acc.: 48.05%] [G loss: 0.694702]
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782 [D loss: 0.693215, acc.: 53.71%] [G loss: 0.693559]
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783 [D loss: 0.691675, acc.: 52.93%] [G loss: 0.695027]
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784 [D loss: 0.693434, acc.: 48.63%] [G loss: 0.690544]
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785 [D loss: 0.694840, acc.: 47.66%] [G loss: 0.690716]
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786 [D loss: 0.695281, acc.: 47.85%] [G loss: 0.689916]
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787 [D loss: 0.695128, acc.: 46.88%] [G loss: 0.688246]
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788 [D loss: 0.695359, acc.: 45.12%] [G loss: 0.691064]
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789 [D loss: 0.694585, acc.: 48.63%] [G loss: 0.693783]
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790 [D loss: 0.694088, acc.: 46.48%] [G loss: 0.693938]
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791 [D loss: 0.693422, acc.: 50.78%] [G loss: 0.697153]
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792 [D loss: 0.692467, acc.: 52.15%] [G loss: 0.699060]
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793 [D loss: 0.692462, acc.: 52.93%] [G loss: 0.698864]
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794 [D loss: 0.693404, acc.: 48.05%] [G loss: 0.697261]
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795 [D loss: 0.693146, acc.: 50.20%] [G loss: 0.699730]
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796 [D loss: 0.692272, acc.: 51.76%] [G loss: 0.697097]
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797 [D loss: 0.694185, acc.: 49.22%] [G loss: 0.700853]
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798 [D loss: 0.694294, acc.: 49.41%] [G loss: 0.698835]
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799 [D loss: 0.693842, acc.: 50.98%] [G loss: 0.697113]
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800 [D loss: 0.692949, acc.: 50.98%] [G loss: 0.695652]
1/1 [==============================] - 0s 24ms/step
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801 [D loss: 0.694880, acc.: 47.66%] [G loss: 0.700070]
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802 [D loss: 0.694100, acc.: 50.20%] [G loss: 0.697941]
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803 [D loss: 0.694275, acc.: 50.39%] [G loss: 0.698387]
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804 [D loss: 0.691152, acc.: 53.12%] [G loss: 0.699232]
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805 [D loss: 0.692297, acc.: 52.93%] [G loss: 0.698485]
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806 [D loss: 0.692651, acc.: 50.78%] [G loss: 0.699011]
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807 [D loss: 0.694244, acc.: 48.44%] [G loss: 0.699473]
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808 [D loss: 0.693479, acc.: 47.46%] [G loss: 0.696949]
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809 [D loss: 0.694957, acc.: 47.46%] [G loss: 0.695476]
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810 [D loss: 0.695670, acc.: 43.36%] [G loss: 0.693951]
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811 [D loss: 0.694337, acc.: 47.85%] [G loss: 0.697316]
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812 [D loss: 0.695629, acc.: 45.90%] [G loss: 0.696307]
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813 [D loss: 0.694685, acc.: 45.12%] [G loss: 0.697443]
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814 [D loss: 0.694047, acc.: 47.85%] [G loss: 0.701725]
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815 [D loss: 0.694278, acc.: 45.70%] [G loss: 0.697361]
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816 [D loss: 0.693352, acc.: 53.52%] [G loss: 0.698615]
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817 [D loss: 0.691324, acc.: 53.71%] [G loss: 0.702830]
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818 [D loss: 0.693223, acc.: 52.73%] [G loss: 0.700918]
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819 [D loss: 0.692407, acc.: 53.52%] [G loss: 0.701803]
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820 [D loss: 0.692171, acc.: 53.71%] [G loss: 0.699990]
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821 [D loss: 0.694294, acc.: 51.17%] [G loss: 0.705100]
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822 [D loss: 0.693290, acc.: 53.91%] [G loss: 0.701285]
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823 [D loss: 0.693982, acc.: 50.78%] [G loss: 0.699855]
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824 [D loss: 0.693032, acc.: 53.52%] [G loss: 0.700140]
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825 [D loss: 0.693334, acc.: 51.95%] [G loss: 0.701227]
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826 [D loss: 0.693026, acc.: 49.61%] [G loss: 0.701064]
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827 [D loss: 0.692994, acc.: 50.39%] [G loss: 0.700154]
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828 [D loss: 0.693421, acc.: 50.20%] [G loss: 0.698389]
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829 [D loss: 0.694052, acc.: 45.90%] [G loss: 0.698213]
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830 [D loss: 0.694421, acc.: 47.66%] [G loss: 0.700089]
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831 [D loss: 0.695631, acc.: 45.31%] [G loss: 0.695770]
8/8 [==============================] - 0s 4ms/step
832 [D loss: 0.694208, acc.: 45.70%] [G loss: 0.696335]
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833 [D loss: 0.694076, acc.: 50.78%] [G loss: 0.696367]
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834 [D loss: 0.694402, acc.: 50.39%] [G loss: 0.697623]
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835 [D loss: 0.692190, acc.: 51.37%] [G loss: 0.697670]
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836 [D loss: 0.694319, acc.: 46.68%] [G loss: 0.699136]
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837 [D loss: 0.692185, acc.: 52.15%] [G loss: 0.698139]
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838 [D loss: 0.690929, acc.: 54.69%] [G loss: 0.700602]
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839 [D loss: 0.692388, acc.: 52.54%] [G loss: 0.698210]
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840 [D loss: 0.692828, acc.: 48.83%] [G loss: 0.698152]
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841 [D loss: 0.692674, acc.: 52.15%] [G loss: 0.696948]
8/8 [==============================] - 0s 4ms/step
842 [D loss: 0.694547, acc.: 47.66%] [G loss: 0.695053]
8/8 [==============================] - 0s 4ms/step
843 [D loss: 0.695037, acc.: 44.34%] [G loss: 0.693108]
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844 [D loss: 0.693218, acc.: 48.05%] [G loss: 0.694597]
8/8 [==============================] - 0s 4ms/step
845 [D loss: 0.693276, acc.: 48.05%] [G loss: 0.695259]
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846 [D loss: 0.693860, acc.: 47.66%] [G loss: 0.694862]
8/8 [==============================] - 0s 4ms/step
847 [D loss: 0.694546, acc.: 46.29%] [G loss: 0.692937]
8/8 [==============================] - 0s 4ms/step
848 [D loss: 0.693036, acc.: 51.76%] [G loss: 0.693687]
8/8 [==============================] - 0s 4ms/step
849 [D loss: 0.693436, acc.: 48.63%] [G loss: 0.695964]
8/8 [==============================] - 0s 4ms/step
850 [D loss: 0.693317, acc.: 49.41%] [G loss: 0.697331]
1/1 [==============================] - 0s 20ms/step
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851 [D loss: 0.693562, acc.: 49.41%] [G loss: 0.697816]
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852 [D loss: 0.693445, acc.: 50.00%] [G loss: 0.699058]
8/8 [==============================] - 0s 4ms/step
853 [D loss: 0.694059, acc.: 47.66%] [G loss: 0.699800]
8/8 [==============================] - 0s 4ms/step
854 [D loss: 0.694237, acc.: 47.85%] [G loss: 0.699720]
8/8 [==============================] - 0s 4ms/step
855 [D loss: 0.693082, acc.: 50.59%] [G loss: 0.702208]
8/8 [==============================] - 0s 4ms/step
856 [D loss: 0.693229, acc.: 49.02%] [G loss: 0.704544]
8/8 [==============================] - 0s 4ms/step
857 [D loss: 0.693179, acc.: 51.95%] [G loss: 0.703965]
8/8 [==============================] - 0s 4ms/step
858 [D loss: 0.691857, acc.: 52.54%] [G loss: 0.703125]
8/8 [==============================] - 0s 4ms/step
859 [D loss: 0.692270, acc.: 50.00%] [G loss: 0.705001]
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860 [D loss: 0.692678, acc.: 50.78%] [G loss: 0.704334]
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861 [D loss: 0.691440, acc.: 55.66%] [G loss: 0.702166]
8/8 [==============================] - 0s 4ms/step
862 [D loss: 0.690497, acc.: 56.05%] [G loss: 0.703773]
8/8 [==============================] - 0s 4ms/step
863 [D loss: 0.690065, acc.: 55.86%] [G loss: 0.703862]
8/8 [==============================] - 0s 4ms/step
864 [D loss: 0.689763, acc.: 57.81%] [G loss: 0.699027]
8/8 [==============================] - 0s 4ms/step
865 [D loss: 0.691526, acc.: 53.52%] [G loss: 0.698354]
8/8 [==============================] - 0s 4ms/step
866 [D loss: 0.692408, acc.: 52.15%] [G loss: 0.695336]
8/8 [==============================] - 0s 4ms/step
867 [D loss: 0.693588, acc.: 50.78%] [G loss: 0.693206]
8/8 [==============================] - 0s 4ms/step
868 [D loss: 0.692906, acc.: 49.22%] [G loss: 0.694609]
8/8 [==============================] - 0s 4ms/step
869 [D loss: 0.693683, acc.: 48.83%] [G loss: 0.693629]
8/8 [==============================] - 0s 4ms/step
870 [D loss: 0.694802, acc.: 45.70%] [G loss: 0.696474]
8/8 [==============================] - 0s 4ms/step
871 [D loss: 0.694071, acc.: 49.41%] [G loss: 0.698864]
8/8 [==============================] - 0s 4ms/step
872 [D loss: 0.694471, acc.: 44.73%] [G loss: 0.702179]
8/8 [==============================] - 0s 4ms/step
873 [D loss: 0.694838, acc.: 46.29%] [G loss: 0.701607]
8/8 [==============================] - 0s 4ms/step
874 [D loss: 0.692466, acc.: 48.05%] [G loss: 0.702243]
8/8 [==============================] - 0s 4ms/step
875 [D loss: 0.693612, acc.: 46.48%] [G loss: 0.701300]
8/8 [==============================] - 0s 4ms/step
876 [D loss: 0.692221, acc.: 49.22%] [G loss: 0.705298]
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877 [D loss: 0.691870, acc.: 49.80%] [G loss: 0.701785]
8/8 [==============================] - 0s 4ms/step
878 [D loss: 0.693269, acc.: 49.61%] [G loss: 0.699445]
8/8 [==============================] - 0s 4ms/step
879 [D loss: 0.692807, acc.: 50.00%] [G loss: 0.697207]
8/8 [==============================] - 0s 4ms/step
880 [D loss: 0.692091, acc.: 48.44%] [G loss: 0.695157]
8/8 [==============================] - 0s 4ms/step
881 [D loss: 0.694135, acc.: 47.27%] [G loss: 0.696249]
8/8 [==============================] - 0s 4ms/step
882 [D loss: 0.693993, acc.: 43.75%] [G loss: 0.695173]
8/8 [==============================] - 0s 4ms/step
883 [D loss: 0.694942, acc.: 46.88%] [G loss: 0.697459]
8/8 [==============================] - 0s 4ms/step
884 [D loss: 0.693973, acc.: 51.37%] [G loss: 0.699526]
8/8 [==============================] - 0s 4ms/step
885 [D loss: 0.693310, acc.: 50.20%] [G loss: 0.700329]
8/8 [==============================] - 0s 4ms/step
886 [D loss: 0.693023, acc.: 50.39%] [G loss: 0.702039]
8/8 [==============================] - 0s 4ms/step
887 [D loss: 0.692650, acc.: 49.80%] [G loss: 0.703449]
8/8 [==============================] - 0s 4ms/step
888 [D loss: 0.692150, acc.: 53.52%] [G loss: 0.704498]
8/8 [==============================] - 0s 4ms/step
889 [D loss: 0.692067, acc.: 50.59%] [G loss: 0.703473]
8/8 [==============================] - 0s 4ms/step
890 [D loss: 0.691919, acc.: 57.03%] [G loss: 0.703131]
8/8 [==============================] - 0s 4ms/step
891 [D loss: 0.692648, acc.: 49.80%] [G loss: 0.702947]
8/8 [==============================] - 0s 4ms/step
892 [D loss: 0.693689, acc.: 49.02%] [G loss: 0.700664]
8/8 [==============================] - 0s 4ms/step
893 [D loss: 0.694366, acc.: 45.70%] [G loss: 0.697655]
8/8 [==============================] - 0s 4ms/step
894 [D loss: 0.695750, acc.: 44.73%] [G loss: 0.695413]
8/8 [==============================] - 0s 4ms/step
895 [D loss: 0.695970, acc.: 41.80%] [G loss: 0.694473]
8/8 [==============================] - 0s 4ms/step
896 [D loss: 0.695743, acc.: 41.41%] [G loss: 0.692373]
8/8 [==============================] - 0s 4ms/step
897 [D loss: 0.695214, acc.: 42.97%] [G loss: 0.695352]
8/8 [==============================] - 0s 4ms/step
898 [D loss: 0.694597, acc.: 45.90%] [G loss: 0.695129]
8/8 [==============================] - 0s 4ms/step
899 [D loss: 0.692012, acc.: 49.80%] [G loss: 0.700214]
8/8 [==============================] - 0s 4ms/step
900 [D loss: 0.692586, acc.: 53.71%] [G loss: 0.699590]
1/1 [==============================] - 0s 27ms/step
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901 [D loss: 0.692142, acc.: 52.73%] [G loss: 0.701997]
8/8 [==============================] - 0s 4ms/step
902 [D loss: 0.691942, acc.: 55.08%] [G loss: 0.698820]
8/8 [==============================] - 0s 4ms/step
903 [D loss: 0.692555, acc.: 51.37%] [G loss: 0.700802]
8/8 [==============================] - 0s 4ms/step
904 [D loss: 0.694360, acc.: 52.54%] [G loss: 0.699374]
8/8 [==============================] - 0s 4ms/step
905 [D loss: 0.691719, acc.: 54.10%] [G loss: 0.694912]
8/8 [==============================] - 0s 4ms/step
906 [D loss: 0.693766, acc.: 51.95%] [G loss: 0.694411]
8/8 [==============================] - 0s 4ms/step
907 [D loss: 0.692991, acc.: 53.91%] [G loss: 0.692910]
8/8 [==============================] - 0s 4ms/step
908 [D loss: 0.693426, acc.: 53.91%] [G loss: 0.692486]
8/8 [==============================] - 0s 4ms/step
909 [D loss: 0.694746, acc.: 47.85%] [G loss: 0.692597]
8/8 [==============================] - 0s 4ms/step
910 [D loss: 0.695189, acc.: 46.68%] [G loss: 0.691656]
8/8 [==============================] - 0s 4ms/step
911 [D loss: 0.694836, acc.: 49.22%] [G loss: 0.695159]
8/8 [==============================] - 0s 4ms/step
912 [D loss: 0.694436, acc.: 47.66%] [G loss: 0.695212]
8/8 [==============================] - 0s 4ms/step
913 [D loss: 0.693548, acc.: 51.37%] [G loss: 0.697704]
8/8 [==============================] - 0s 4ms/step
914 [D loss: 0.694212, acc.: 46.68%] [G loss: 0.701118]
8/8 [==============================] - 0s 4ms/step
915 [D loss: 0.694408, acc.: 46.48%] [G loss: 0.700858]
8/8 [==============================] - 0s 4ms/step
916 [D loss: 0.692035, acc.: 53.71%] [G loss: 0.702690]
8/8 [==============================] - 0s 4ms/step
917 [D loss: 0.694593, acc.: 50.00%] [G loss: 0.700350]
8/8 [==============================] - 0s 4ms/step
918 [D loss: 0.695161, acc.: 46.88%] [G loss: 0.700378]
8/8 [==============================] - 0s 4ms/step
919 [D loss: 0.694563, acc.: 46.88%] [G loss: 0.699736]
8/8 [==============================] - 0s 4ms/step
920 [D loss: 0.693496, acc.: 49.61%] [G loss: 0.696907]
8/8 [==============================] - 0s 4ms/step
921 [D loss: 0.691506, acc.: 54.30%] [G loss: 0.696150]
8/8 [==============================] - 0s 4ms/step
922 [D loss: 0.693323, acc.: 52.54%] [G loss: 0.697382]
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923 [D loss: 0.692950, acc.: 50.39%] [G loss: 0.699612]
8/8 [==============================] - 0s 4ms/step
924 [D loss: 0.691709, acc.: 49.41%] [G loss: 0.700211]
8/8 [==============================] - 0s 4ms/step
925 [D loss: 0.690591, acc.: 50.39%] [G loss: 0.707634]
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926 [D loss: 0.688610, acc.: 56.25%] [G loss: 0.709241]
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927 [D loss: 0.688570, acc.: 57.03%] [G loss: 0.709399]
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928 [D loss: 0.688623, acc.: 55.47%] [G loss: 0.708027]
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929 [D loss: 0.691268, acc.: 52.54%] [G loss: 0.705407]
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930 [D loss: 0.693679, acc.: 49.22%] [G loss: 0.695258]
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931 [D loss: 0.696563, acc.: 49.02%] [G loss: 0.695141]
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932 [D loss: 0.696643, acc.: 46.48%] [G loss: 0.695204]
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933 [D loss: 0.697979, acc.: 42.38%] [G loss: 0.693843]
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934 [D loss: 0.695754, acc.: 48.05%] [G loss: 0.695819]
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935 [D loss: 0.695365, acc.: 46.29%] [G loss: 0.699144]
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936 [D loss: 0.691035, acc.: 57.81%] [G loss: 0.706521]
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937 [D loss: 0.691002, acc.: 55.47%] [G loss: 0.709184]
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938 [D loss: 0.690078, acc.: 57.62%] [G loss: 0.714671]
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939 [D loss: 0.688975, acc.: 57.62%] [G loss: 0.711866]
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940 [D loss: 0.687257, acc.: 62.11%] [G loss: 0.714174]
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941 [D loss: 0.688239, acc.: 60.55%] [G loss: 0.712079]
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942 [D loss: 0.690816, acc.: 54.69%] [G loss: 0.704620]
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943 [D loss: 0.695432, acc.: 48.05%] [G loss: 0.699803]
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944 [D loss: 0.694442, acc.: 47.85%] [G loss: 0.694274]
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945 [D loss: 0.695360, acc.: 46.88%] [G loss: 0.692623]
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946 [D loss: 0.696351, acc.: 43.36%] [G loss: 0.695275]
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947 [D loss: 0.697377, acc.: 40.82%] [G loss: 0.695063]
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948 [D loss: 0.694424, acc.: 45.31%] [G loss: 0.699401]
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949 [D loss: 0.693220, acc.: 46.88%] [G loss: 0.699535]
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950 [D loss: 0.693718, acc.: 49.22%] [G loss: 0.703026]
1/1 [==============================] - 0s 21ms/step
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951 [D loss: 0.692838, acc.: 52.73%] [G loss: 0.706192]
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952 [D loss: 0.691727, acc.: 53.12%] [G loss: 0.707257]
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953 [D loss: 0.689925, acc.: 58.79%] [G loss: 0.707899]
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954 [D loss: 0.689878, acc.: 59.57%] [G loss: 0.709417]
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955 [D loss: 0.691557, acc.: 58.20%] [G loss: 0.706230]
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956 [D loss: 0.694230, acc.: 51.17%] [G loss: 0.701602]
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957 [D loss: 0.693150, acc.: 52.34%] [G loss: 0.692905]
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958 [D loss: 0.695599, acc.: 49.41%] [G loss: 0.695585]
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959 [D loss: 0.694367, acc.: 48.05%] [G loss: 0.690804]
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960 [D loss: 0.696905, acc.: 44.34%] [G loss: 0.694479]
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961 [D loss: 0.692624, acc.: 52.34%] [G loss: 0.696762]
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962 [D loss: 0.694014, acc.: 51.76%] [G loss: 0.699768]
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963 [D loss: 0.691304, acc.: 53.32%] [G loss: 0.698321]
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964 [D loss: 0.691142, acc.: 53.91%] [G loss: 0.702811]
8/8 [==============================] - 0s 4ms/step
965 [D loss: 0.693467, acc.: 51.95%] [G loss: 0.700560]
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966 [D loss: 0.692828, acc.: 54.30%] [G loss: 0.702025]
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967 [D loss: 0.691294, acc.: 52.54%] [G loss: 0.702255]
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968 [D loss: 0.692130, acc.: 52.34%] [G loss: 0.703986]
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969 [D loss: 0.692029, acc.: 51.76%] [G loss: 0.704279]
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970 [D loss: 0.689854, acc.: 52.15%] [G loss: 0.707849]
8/8 [==============================] - 0s 4ms/step
971 [D loss: 0.689870, acc.: 54.88%] [G loss: 0.706109]
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972 [D loss: 0.688266, acc.: 57.62%] [G loss: 0.709297]
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973 [D loss: 0.690709, acc.: 56.84%] [G loss: 0.698794]
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974 [D loss: 0.693288, acc.: 51.37%] [G loss: 0.691228]
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975 [D loss: 0.695979, acc.: 45.70%] [G loss: 0.688923]
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976 [D loss: 0.697131, acc.: 43.16%] [G loss: 0.688892]
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977 [D loss: 0.697580, acc.: 45.90%] [G loss: 0.685358]
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978 [D loss: 0.698694, acc.: 43.75%] [G loss: 0.690000]
8/8 [==============================] - 0s 4ms/step
979 [D loss: 0.696465, acc.: 45.51%] [G loss: 0.692111]
8/8 [==============================] - 0s 4ms/step
980 [D loss: 0.696195, acc.: 48.24%] [G loss: 0.693385]
8/8 [==============================] - 0s 4ms/step
981 [D loss: 0.694093, acc.: 50.00%] [G loss: 0.698941]
8/8 [==============================] - 0s 4ms/step
982 [D loss: 0.692073, acc.: 54.88%] [G loss: 0.700446]
8/8 [==============================] - 0s 4ms/step
983 [D loss: 0.692213, acc.: 52.93%] [G loss: 0.702279]
8/8 [==============================] - 0s 4ms/step
984 [D loss: 0.690872, acc.: 53.52%] [G loss: 0.701566]
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985 [D loss: 0.694210, acc.: 48.83%] [G loss: 0.699319]
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986 [D loss: 0.691939, acc.: 53.32%] [G loss: 0.703264]
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987 [D loss: 0.691328, acc.: 56.25%] [G loss: 0.703848]
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988 [D loss: 0.691370, acc.: 52.54%] [G loss: 0.701209]
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989 [D loss: 0.690805, acc.: 55.27%] [G loss: 0.700120]
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990 [D loss: 0.690572, acc.: 55.27%] [G loss: 0.704046]
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991 [D loss: 0.689964, acc.: 59.18%] [G loss: 0.704515]
8/8 [==============================] - 0s 4ms/step
992 [D loss: 0.689090, acc.: 59.18%] [G loss: 0.704657]
8/8 [==============================] - 0s 4ms/step
993 [D loss: 0.689525, acc.: 56.45%] [G loss: 0.703318]
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994 [D loss: 0.691931, acc.: 50.59%] [G loss: 0.699051]
8/8 [==============================] - 0s 4ms/step
995 [D loss: 0.692640, acc.: 51.95%] [G loss: 0.697648]
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996 [D loss: 0.693904, acc.: 50.39%] [G loss: 0.696601]
8/8 [==============================] - 0s 4ms/step
997 [D loss: 0.691342, acc.: 53.32%] [G loss: 0.697911]
8/8 [==============================] - 0s 4ms/step
998 [D loss: 0.695634, acc.: 47.85%] [G loss: 0.695979]
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999 [D loss: 0.694665, acc.: 47.27%] [G loss: 0.696528]
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1000 [D loss: 0.694095, acc.: 47.27%] [G loss: 0.702013]
1/1 [==============================] - 0s 23ms/step
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1001 [D loss: 0.694173, acc.: 50.59%] [G loss: 0.702949]
8/8 [==============================] - 0s 4ms/step
1002 [D loss: 0.696077, acc.: 46.09%] [G loss: 0.697838]
8/8 [==============================] - 0s 4ms/step
1003 [D loss: 0.694863, acc.: 49.02%] [G loss: 0.697984]
8/8 [==============================] - 0s 4ms/step
1004 [D loss: 0.696302, acc.: 46.68%] [G loss: 0.703110]
8/8 [==============================] - 0s 4ms/step
1005 [D loss: 0.695594, acc.: 49.02%] [G loss: 0.703581]
8/8 [==============================] - 0s 4ms/step
1006 [D loss: 0.693522, acc.: 48.63%] [G loss: 0.704377]
8/8 [==============================] - 0s 4ms/step
1007 [D loss: 0.692827, acc.: 50.39%] [G loss: 0.704460]
8/8 [==============================] - 0s 4ms/step
1008 [D loss: 0.692864, acc.: 51.76%] [G loss: 0.705039]
8/8 [==============================] - 0s 4ms/step
1009 [D loss: 0.692809, acc.: 52.15%] [G loss: 0.707278]
8/8 [==============================] - 0s 4ms/step
1010 [D loss: 0.691807, acc.: 52.15%] [G loss: 0.703434]
8/8 [==============================] - 0s 4ms/step
1011 [D loss: 0.692570, acc.: 50.00%] [G loss: 0.702989]
8/8 [==============================] - 0s 4ms/step
1012 [D loss: 0.693221, acc.: 50.20%] [G loss: 0.701280]
8/8 [==============================] - 0s 4ms/step
1013 [D loss: 0.691367, acc.: 54.49%] [G loss: 0.705808]
8/8 [==============================] - 0s 4ms/step
1014 [D loss: 0.690163, acc.: 56.64%] [G loss: 0.704694]
8/8 [==============================] - 0s 4ms/step
1015 [D loss: 0.687457, acc.: 56.84%] [G loss: 0.701322]
8/8 [==============================] - 0s 4ms/step
1016 [D loss: 0.687682, acc.: 59.57%] [G loss: 0.705194]
8/8 [==============================] - 0s 4ms/step
1017 [D loss: 0.689123, acc.: 55.86%] [G loss: 0.699893]
8/8 [==============================] - 0s 4ms/step
1018 [D loss: 0.691074, acc.: 53.91%] [G loss: 0.701599]
8/8 [==============================] - 0s 4ms/step
1019 [D loss: 0.691435, acc.: 52.15%] [G loss: 0.694876]
8/8 [==============================] - 0s 4ms/step
1020 [D loss: 0.693574, acc.: 52.93%] [G loss: 0.696042]
8/8 [==============================] - 0s 4ms/step
1021 [D loss: 0.694213, acc.: 50.00%] [G loss: 0.699409]
8/8 [==============================] - 0s 4ms/step
1022 [D loss: 0.694279, acc.: 48.63%] [G loss: 0.700821]
8/8 [==============================] - 0s 4ms/step
1023 [D loss: 0.691000, acc.: 52.54%] [G loss: 0.703474]
8/8 [==============================] - 0s 4ms/step
1024 [D loss: 0.690881, acc.: 50.20%] [G loss: 0.706547]
8/8 [==============================] - 0s 4ms/step
1025 [D loss: 0.690211, acc.: 52.73%] [G loss: 0.711230]
8/8 [==============================] - 0s 4ms/step
1026 [D loss: 0.690468, acc.: 54.30%] [G loss: 0.713053]
8/8 [==============================] - 0s 4ms/step
1027 [D loss: 0.689688, acc.: 56.05%] [G loss: 0.716335]
8/8 [==============================] - 0s 4ms/step
1028 [D loss: 0.689790, acc.: 53.12%] [G loss: 0.709611]
8/8 [==============================] - 0s 4ms/step
1029 [D loss: 0.694071, acc.: 47.46%] [G loss: 0.707842]
8/8 [==============================] - 0s 4ms/step
1030 [D loss: 0.698697, acc.: 45.51%] [G loss: 0.704763]
8/8 [==============================] - 0s 4ms/step
1031 [D loss: 0.696279, acc.: 49.22%] [G loss: 0.700419]
8/8 [==============================] - 0s 4ms/step
1032 [D loss: 0.694489, acc.: 47.46%] [G loss: 0.699691]
8/8 [==============================] - 0s 4ms/step
1033 [D loss: 0.691611, acc.: 52.73%] [G loss: 0.706335]
8/8 [==============================] - 0s 4ms/step
1034 [D loss: 0.689129, acc.: 54.69%] [G loss: 0.713092]
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1035 [D loss: 0.689920, acc.: 55.27%] [G loss: 0.714961]
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1036 [D loss: 0.689630, acc.: 55.27%] [G loss: 0.709774]
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1037 [D loss: 0.690322, acc.: 55.08%] [G loss: 0.708677]
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1038 [D loss: 0.691867, acc.: 53.91%] [G loss: 0.704609]
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1039 [D loss: 0.690186, acc.: 53.12%] [G loss: 0.701389]
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1040 [D loss: 0.691328, acc.: 54.69%] [G loss: 0.701114]
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1041 [D loss: 0.693986, acc.: 50.39%] [G loss: 0.696768]
8/8 [==============================] - 0s 4ms/step
1042 [D loss: 0.695346, acc.: 48.83%] [G loss: 0.695214]
8/8 [==============================] - 0s 4ms/step
1043 [D loss: 0.692786, acc.: 51.37%] [G loss: 0.696637]
8/8 [==============================] - 0s 4ms/step
1044 [D loss: 0.694471, acc.: 48.05%] [G loss: 0.697265]
8/8 [==============================] - 0s 4ms/step
1045 [D loss: 0.695065, acc.: 51.56%] [G loss: 0.692092]
8/8 [==============================] - 0s 4ms/step
1046 [D loss: 0.695839, acc.: 48.83%] [G loss: 0.690005]
8/8 [==============================] - 0s 4ms/step
1047 [D loss: 0.694525, acc.: 50.59%] [G loss: 0.689789]
8/8 [==============================] - 0s 4ms/step
1048 [D loss: 0.694033, acc.: 46.88%] [G loss: 0.690907]
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1049 [D loss: 0.696348, acc.: 45.90%] [G loss: 0.691285]
8/8 [==============================] - 0s 4ms/step
1050 [D loss: 0.693668, acc.: 46.48%] [G loss: 0.692819]
1/1 [==============================] - 0s 23ms/step
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1051 [D loss: 0.691803, acc.: 51.56%] [G loss: 0.699523]
8/8 [==============================] - 0s 4ms/step
1052 [D loss: 0.690692, acc.: 50.39%] [G loss: 0.702156]
8/8 [==============================] - 0s 4ms/step
1053 [D loss: 0.687103, acc.: 59.96%] [G loss: 0.707169]
8/8 [==============================] - 0s 4ms/step
1054 [D loss: 0.687183, acc.: 57.42%] [G loss: 0.718586]
8/8 [==============================] - 0s 4ms/step
1055 [D loss: 0.685995, acc.: 57.42%] [G loss: 0.718465]
8/8 [==============================] - 0s 4ms/step
1056 [D loss: 0.686696, acc.: 56.25%] [G loss: 0.716105]
8/8 [==============================] - 0s 4ms/step
1057 [D loss: 0.688074, acc.: 58.59%] [G loss: 0.712058]
8/8 [==============================] - 0s 4ms/step
1058 [D loss: 0.693566, acc.: 48.83%] [G loss: 0.705636]
8/8 [==============================] - 0s 4ms/step
1059 [D loss: 0.696376, acc.: 49.41%] [G loss: 0.697128]
8/8 [==============================] - 0s 4ms/step
1060 [D loss: 0.698071, acc.: 44.92%] [G loss: 0.694625]
8/8 [==============================] - 0s 4ms/step
1061 [D loss: 0.699025, acc.: 41.21%] [G loss: 0.691438]
8/8 [==============================] - 0s 4ms/step
1062 [D loss: 0.699163, acc.: 42.19%] [G loss: 0.690741]
8/8 [==============================] - 0s 4ms/step
1063 [D loss: 0.698892, acc.: 42.77%] [G loss: 0.693936]
8/8 [==============================] - 0s 4ms/step
1064 [D loss: 0.696503, acc.: 44.92%] [G loss: 0.693179]
8/8 [==============================] - 0s 4ms/step
1065 [D loss: 0.693418, acc.: 50.00%] [G loss: 0.702831]
8/8 [==============================] - 0s 4ms/step
1066 [D loss: 0.689238, acc.: 54.88%] [G loss: 0.706897]
8/8 [==============================] - 0s 4ms/step
1067 [D loss: 0.688372, acc.: 58.40%] [G loss: 0.713485]
8/8 [==============================] - 0s 4ms/step
1068 [D loss: 0.688336, acc.: 59.38%] [G loss: 0.712653]
8/8 [==============================] - 0s 4ms/step
1069 [D loss: 0.688531, acc.: 56.64%] [G loss: 0.713148]
8/8 [==============================] - 0s 4ms/step
1070 [D loss: 0.687190, acc.: 60.16%] [G loss: 0.708689]
8/8 [==============================] - 0s 4ms/step
1071 [D loss: 0.686307, acc.: 61.52%] [G loss: 0.708135]
8/8 [==============================] - 0s 4ms/step
1072 [D loss: 0.690840, acc.: 57.23%] [G loss: 0.703742]
8/8 [==============================] - 0s 4ms/step
1073 [D loss: 0.691504, acc.: 51.56%] [G loss: 0.698385]
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1074 [D loss: 0.693348, acc.: 49.80%] [G loss: 0.699092]
8/8 [==============================] - 0s 4ms/step
1075 [D loss: 0.697600, acc.: 45.12%] [G loss: 0.694622]
8/8 [==============================] - 0s 4ms/step
1076 [D loss: 0.698627, acc.: 42.97%] [G loss: 0.693883]
8/8 [==============================] - 0s 4ms/step
1077 [D loss: 0.697988, acc.: 46.68%] [G loss: 0.696767]
8/8 [==============================] - 0s 4ms/step
1078 [D loss: 0.694066, acc.: 47.27%] [G loss: 0.700490]
8/8 [==============================] - 0s 4ms/step
1079 [D loss: 0.694319, acc.: 49.80%] [G loss: 0.708594]
8/8 [==============================] - 0s 4ms/step
1080 [D loss: 0.692508, acc.: 53.12%] [G loss: 0.710152]
8/8 [==============================] - 0s 4ms/step
1081 [D loss: 0.694144, acc.: 48.83%] [G loss: 0.701836]
8/8 [==============================] - 0s 4ms/step
1082 [D loss: 0.691181, acc.: 52.73%] [G loss: 0.708673]
8/8 [==============================] - 0s 4ms/step
1083 [D loss: 0.690687, acc.: 58.40%] [G loss: 0.705155]
8/8 [==============================] - 0s 4ms/step
1084 [D loss: 0.693341, acc.: 51.56%] [G loss: 0.707707]
8/8 [==============================] - 0s 4ms/step
1085 [D loss: 0.692183, acc.: 51.76%] [G loss: 0.706519]
8/8 [==============================] - 0s 4ms/step
1086 [D loss: 0.691933, acc.: 54.69%] [G loss: 0.705608]
8/8 [==============================] - 0s 4ms/step
1087 [D loss: 0.691778, acc.: 54.49%] [G loss: 0.704152]
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1088 [D loss: 0.691507, acc.: 51.56%] [G loss: 0.703731]
8/8 [==============================] - 0s 4ms/step
1089 [D loss: 0.690952, acc.: 54.10%] [G loss: 0.702217]
8/8 [==============================] - 0s 4ms/step
1090 [D loss: 0.692828, acc.: 51.17%] [G loss: 0.699478]
8/8 [==============================] - 0s 4ms/step
1091 [D loss: 0.695192, acc.: 47.66%] [G loss: 0.699233]
8/8 [==============================] - 0s 4ms/step
1092 [D loss: 0.693117, acc.: 47.66%] [G loss: 0.698228]
8/8 [==============================] - 0s 4ms/step
1093 [D loss: 0.694448, acc.: 48.44%] [G loss: 0.698315]
8/8 [==============================] - 0s 4ms/step
1094 [D loss: 0.695835, acc.: 45.70%] [G loss: 0.696818]
8/8 [==============================] - 0s 4ms/step
1095 [D loss: 0.692865, acc.: 49.61%] [G loss: 0.699352]
8/8 [==============================] - 0s 4ms/step
1096 [D loss: 0.691267, acc.: 56.25%] [G loss: 0.700499]
8/8 [==============================] - 0s 4ms/step
1097 [D loss: 0.692735, acc.: 49.80%] [G loss: 0.704974]
8/8 [==============================] - 0s 4ms/step
1098 [D loss: 0.691655, acc.: 52.73%] [G loss: 0.709953]
8/8 [==============================] - 0s 4ms/step
1099 [D loss: 0.689875, acc.: 55.27%] [G loss: 0.708359]
8/8 [==============================] - 0s 4ms/step
1100 [D loss: 0.688983, acc.: 58.01%] [G loss: 0.708089]
1/1 [==============================] - 0s 25ms/step
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1101 [D loss: 0.690344, acc.: 56.64%] [G loss: 0.709671]
8/8 [==============================] - 0s 4ms/step
1102 [D loss: 0.694217, acc.: 49.22%] [G loss: 0.704979]
8/8 [==============================] - 0s 4ms/step
1103 [D loss: 0.693256, acc.: 50.00%] [G loss: 0.703463]
8/8 [==============================] - 0s 4ms/step
1104 [D loss: 0.691802, acc.: 53.71%] [G loss: 0.704332]
8/8 [==============================] - 0s 4ms/step
1105 [D loss: 0.691271, acc.: 55.27%] [G loss: 0.704540]
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1106 [D loss: 0.693097, acc.: 51.17%] [G loss: 0.704089]
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1107 [D loss: 0.691386, acc.: 50.98%] [G loss: 0.702570]
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1108 [D loss: 0.692949, acc.: 52.15%] [G loss: 0.698988]
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1109 [D loss: 0.691501, acc.: 54.10%] [G loss: 0.702841]
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1110 [D loss: 0.691487, acc.: 54.49%] [G loss: 0.699075]
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1111 [D loss: 0.692471, acc.: 53.12%] [G loss: 0.708672]
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1112 [D loss: 0.690572, acc.: 55.27%] [G loss: 0.703583]
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1113 [D loss: 0.688895, acc.: 55.66%] [G loss: 0.699979]
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1114 [D loss: 0.690592, acc.: 53.52%] [G loss: 0.700536]
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1115 [D loss: 0.692629, acc.: 54.30%] [G loss: 0.698884]
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1116 [D loss: 0.695153, acc.: 48.24%] [G loss: 0.691647]
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1117 [D loss: 0.696413, acc.: 49.02%] [G loss: 0.690085]
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1118 [D loss: 0.695532, acc.: 46.68%] [G loss: 0.694164]
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1119 [D loss: 0.693914, acc.: 50.78%] [G loss: 0.695575]
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1120 [D loss: 0.693153, acc.: 51.37%] [G loss: 0.706642]
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1121 [D loss: 0.691439, acc.: 54.69%] [G loss: 0.704808]
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1122 [D loss: 0.690882, acc.: 53.52%] [G loss: 0.707520]
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1123 [D loss: 0.690686, acc.: 50.98%] [G loss: 0.710581]
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1124 [D loss: 0.688143, acc.: 54.88%] [G loss: 0.711472]
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1125 [D loss: 0.687851, acc.: 59.18%] [G loss: 0.709050]
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1126 [D loss: 0.689046, acc.: 56.25%] [G loss: 0.712135]
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1127 [D loss: 0.690229, acc.: 51.76%] [G loss: 0.707470]
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1128 [D loss: 0.690190, acc.: 52.93%] [G loss: 0.707463]
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1129 [D loss: 0.692518, acc.: 54.30%] [G loss: 0.699693]
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1130 [D loss: 0.693449, acc.: 51.17%] [G loss: 0.697738]
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1131 [D loss: 0.697814, acc.: 45.70%] [G loss: 0.699402]
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1132 [D loss: 0.698979, acc.: 44.34%] [G loss: 0.706676]
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1133 [D loss: 0.693789, acc.: 50.59%] [G loss: 0.715403]
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1134 [D loss: 0.687379, acc.: 54.30%] [G loss: 0.723312]
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1135 [D loss: 0.686944, acc.: 55.66%] [G loss: 0.726688]
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1136 [D loss: 0.688102, acc.: 58.01%] [G loss: 0.726527]
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1137 [D loss: 0.690768, acc.: 52.34%] [G loss: 0.708598]
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1138 [D loss: 0.693898, acc.: 51.17%] [G loss: 0.700698]
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1139 [D loss: 0.694723, acc.: 48.44%] [G loss: 0.692733]
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1140 [D loss: 0.697676, acc.: 41.21%] [G loss: 0.689117]
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1141 [D loss: 0.698445, acc.: 45.12%] [G loss: 0.689381]
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1142 [D loss: 0.695702, acc.: 45.12%] [G loss: 0.688654]
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1143 [D loss: 0.696004, acc.: 41.80%] [G loss: 0.689474]
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1144 [D loss: 0.693215, acc.: 46.48%] [G loss: 0.697932]
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1145 [D loss: 0.691026, acc.: 51.95%] [G loss: 0.701549]
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1146 [D loss: 0.689804, acc.: 51.37%] [G loss: 0.709285]
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1147 [D loss: 0.690326, acc.: 56.25%] [G loss: 0.711767]
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1148 [D loss: 0.690160, acc.: 53.52%] [G loss: 0.710713]
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1149 [D loss: 0.690848, acc.: 53.71%] [G loss: 0.709644]
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1150 [D loss: 0.691293, acc.: 52.15%] [G loss: 0.706989]
1/1 [==============================] - 0s 23ms/step
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1151 [D loss: 0.693330, acc.: 45.90%] [G loss: 0.701985]
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1152 [D loss: 0.693672, acc.: 50.59%] [G loss: 0.698920]
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1153 [D loss: 0.693604, acc.: 48.05%] [G loss: 0.699716]
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1154 [D loss: 0.692498, acc.: 50.20%] [G loss: 0.696905]
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1155 [D loss: 0.692079, acc.: 53.32%] [G loss: 0.697717]
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1156 [D loss: 0.691305, acc.: 53.12%] [G loss: 0.698732]
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1157 [D loss: 0.691707, acc.: 51.76%] [G loss: 0.697818]
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1158 [D loss: 0.691659, acc.: 51.37%] [G loss: 0.699625]
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1159 [D loss: 0.691687, acc.: 51.17%] [G loss: 0.699325]
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1160 [D loss: 0.691803, acc.: 51.37%] [G loss: 0.698938]
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1161 [D loss: 0.690120, acc.: 52.54%] [G loss: 0.703046]
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1162 [D loss: 0.688952, acc.: 56.64%] [G loss: 0.709717]
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1163 [D loss: 0.689874, acc.: 55.27%] [G loss: 0.710520]
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1164 [D loss: 0.690799, acc.: 54.49%] [G loss: 0.708258]
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1165 [D loss: 0.690170, acc.: 54.88%] [G loss: 0.707461]
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1166 [D loss: 0.692684, acc.: 49.41%] [G loss: 0.705416]
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1167 [D loss: 0.692600, acc.: 50.98%] [G loss: 0.706109]
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1168 [D loss: 0.690919, acc.: 52.34%] [G loss: 0.703518]
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1169 [D loss: 0.692344, acc.: 50.98%] [G loss: 0.699124]
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1170 [D loss: 0.691777, acc.: 54.49%] [G loss: 0.699548]
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1171 [D loss: 0.693745, acc.: 49.41%] [G loss: 0.697524]
8/8 [==============================] - 0s 4ms/step
1172 [D loss: 0.693391, acc.: 51.95%] [G loss: 0.701505]
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1173 [D loss: 0.692050, acc.: 50.39%] [G loss: 0.702715]
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1174 [D loss: 0.693071, acc.: 50.39%] [G loss: 0.708876]
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1175 [D loss: 0.690356, acc.: 54.10%] [G loss: 0.705457]
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1176 [D loss: 0.690290, acc.: 57.42%] [G loss: 0.709572]
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1177 [D loss: 0.689466, acc.: 52.34%] [G loss: 0.712072]
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1178 [D loss: 0.691168, acc.: 54.49%] [G loss: 0.708207]
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1179 [D loss: 0.690048, acc.: 55.08%] [G loss: 0.707665]
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1180 [D loss: 0.690752, acc.: 54.10%] [G loss: 0.701965]
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1181 [D loss: 0.690406, acc.: 53.71%] [G loss: 0.700812]
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1182 [D loss: 0.689517, acc.: 55.66%] [G loss: 0.699151]
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1183 [D loss: 0.691017, acc.: 54.69%] [G loss: 0.696401]
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1184 [D loss: 0.693328, acc.: 52.15%] [G loss: 0.693506]
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1185 [D loss: 0.692971, acc.: 53.91%] [G loss: 0.692804]
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1186 [D loss: 0.693238, acc.: 53.32%] [G loss: 0.698032]
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1187 [D loss: 0.690631, acc.: 53.12%] [G loss: 0.706940]
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1188 [D loss: 0.692090, acc.: 53.52%] [G loss: 0.702227]
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1189 [D loss: 0.689562, acc.: 52.93%] [G loss: 0.706729]
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1190 [D loss: 0.695180, acc.: 46.48%] [G loss: 0.710242]
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1191 [D loss: 0.690438, acc.: 53.52%] [G loss: 0.713921]
8/8 [==============================] - 0s 4ms/step
1192 [D loss: 0.690207, acc.: 52.34%] [G loss: 0.715185]
8/8 [==============================] - 0s 4ms/step
1193 [D loss: 0.689426, acc.: 51.56%] [G loss: 0.718657]
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1194 [D loss: 0.690423, acc.: 53.32%] [G loss: 0.716232]
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1195 [D loss: 0.691256, acc.: 51.95%] [G loss: 0.716316]
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1196 [D loss: 0.692730, acc.: 50.98%] [G loss: 0.712681]
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1197 [D loss: 0.692800, acc.: 50.78%] [G loss: 0.705841]
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1198 [D loss: 0.692250, acc.: 47.66%] [G loss: 0.705490]
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1199 [D loss: 0.693293, acc.: 48.24%] [G loss: 0.704470]
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1200 [D loss: 0.694484, acc.: 47.27%] [G loss: 0.706038]
1/1 [==============================] - 0s 22ms/step
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1201 [D loss: 0.693620, acc.: 49.61%] [G loss: 0.704555]
8/8 [==============================] - 0s 4ms/step
1202 [D loss: 0.691998, acc.: 54.69%] [G loss: 0.706426]
8/8 [==============================] - 0s 4ms/step
1203 [D loss: 0.692949, acc.: 49.80%] [G loss: 0.701771]
8/8 [==============================] - 0s 4ms/step
1204 [D loss: 0.692150, acc.: 49.41%] [G loss: 0.702226]
8/8 [==============================] - 0s 4ms/step
1205 [D loss: 0.690109, acc.: 52.34%] [G loss: 0.700361]
8/8 [==============================] - 0s 4ms/step
1206 [D loss: 0.690707, acc.: 53.91%] [G loss: 0.699540]
8/8 [==============================] - 0s 4ms/step
1207 [D loss: 0.691584, acc.: 53.91%] [G loss: 0.696607]
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1208 [D loss: 0.691225, acc.: 53.32%] [G loss: 0.694627]
8/8 [==============================] - 0s 4ms/step
1209 [D loss: 0.692049, acc.: 52.93%] [G loss: 0.698801]
8/8 [==============================] - 0s 4ms/step
1210 [D loss: 0.689170, acc.: 57.23%] [G loss: 0.699568]
8/8 [==============================] - 0s 4ms/step
1211 [D loss: 0.691260, acc.: 51.56%] [G loss: 0.698200]
8/8 [==============================] - 0s 4ms/step
1212 [D loss: 0.690132, acc.: 53.52%] [G loss: 0.704951]
8/8 [==============================] - 0s 4ms/step
1213 [D loss: 0.689806, acc.: 55.47%] [G loss: 0.706882]
8/8 [==============================] - 0s 4ms/step
1214 [D loss: 0.689838, acc.: 51.56%] [G loss: 0.706982]
8/8 [==============================] - 0s 4ms/step
1215 [D loss: 0.691683, acc.: 52.34%] [G loss: 0.706598]
8/8 [==============================] - 0s 4ms/step
1216 [D loss: 0.692092, acc.: 54.30%] [G loss: 0.704882]
8/8 [==============================] - 0s 4ms/step
1217 [D loss: 0.693543, acc.: 49.41%] [G loss: 0.704410]
8/8 [==============================] - 0s 4ms/step
1218 [D loss: 0.690519, acc.: 54.30%] [G loss: 0.700604]
8/8 [==============================] - 0s 4ms/step
1219 [D loss: 0.692520, acc.: 50.78%] [G loss: 0.704777]
8/8 [==============================] - 0s 4ms/step
1220 [D loss: 0.695097, acc.: 47.46%] [G loss: 0.710035]
8/8 [==============================] - 0s 4ms/step
1221 [D loss: 0.693224, acc.: 53.32%] [G loss: 0.713360]
8/8 [==============================] - 0s 4ms/step
1222 [D loss: 0.690247, acc.: 55.66%] [G loss: 0.713291]
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1223 [D loss: 0.689011, acc.: 59.38%] [G loss: 0.711505]
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1224 [D loss: 0.690995, acc.: 54.69%] [G loss: 0.711706]
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1225 [D loss: 0.689627, acc.: 53.12%] [G loss: 0.709832]
8/8 [==============================] - 0s 4ms/step
1226 [D loss: 0.691392, acc.: 55.47%] [G loss: 0.703332]
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1227 [D loss: 0.693335, acc.: 52.34%] [G loss: 0.702838]
8/8 [==============================] - 0s 4ms/step
1228 [D loss: 0.692735, acc.: 53.91%] [G loss: 0.692129]
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1229 [D loss: 0.693966, acc.: 48.44%] [G loss: 0.697676]
8/8 [==============================] - 0s 4ms/step
1230 [D loss: 0.694414, acc.: 51.17%] [G loss: 0.693919]
8/8 [==============================] - 0s 4ms/step
1231 [D loss: 0.693223, acc.: 50.78%] [G loss: 0.698140]
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1232 [D loss: 0.691617, acc.: 50.98%] [G loss: 0.702642]
8/8 [==============================] - 0s 4ms/step
1233 [D loss: 0.690549, acc.: 53.12%] [G loss: 0.706606]
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1234 [D loss: 0.687816, acc.: 57.62%] [G loss: 0.707732]
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1235 [D loss: 0.689866, acc.: 56.45%] [G loss: 0.707667]
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1236 [D loss: 0.688424, acc.: 58.59%] [G loss: 0.709489]
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1237 [D loss: 0.688459, acc.: 55.27%] [G loss: 0.708114]
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1238 [D loss: 0.689234, acc.: 53.32%] [G loss: 0.706678]
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1239 [D loss: 0.691474, acc.: 52.34%] [G loss: 0.708638]
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1240 [D loss: 0.691873, acc.: 52.93%] [G loss: 0.704457]
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1241 [D loss: 0.692984, acc.: 50.78%] [G loss: 0.706388]
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1242 [D loss: 0.690979, acc.: 53.71%] [G loss: 0.701588]
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1243 [D loss: 0.691280, acc.: 53.32%] [G loss: 0.701014]
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1244 [D loss: 0.693100, acc.: 49.02%] [G loss: 0.699024]
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1245 [D loss: 0.691719, acc.: 49.22%] [G loss: 0.702407]
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1246 [D loss: 0.692982, acc.: 49.41%] [G loss: 0.706766]
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1247 [D loss: 0.688658, acc.: 54.30%] [G loss: 0.709402]
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1248 [D loss: 0.687621, acc.: 54.88%] [G loss: 0.711554]
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1249 [D loss: 0.689666, acc.: 55.47%] [G loss: 0.709001]
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1250 [D loss: 0.689663, acc.: 54.49%] [G loss: 0.715692]
1/1 [==============================] - 0s 21ms/step
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1251 [D loss: 0.689386, acc.: 57.42%] [G loss: 0.714957]
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1252 [D loss: 0.690627, acc.: 51.95%] [G loss: 0.717155]
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1253 [D loss: 0.692924, acc.: 50.00%] [G loss: 0.711905]
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1254 [D loss: 0.691362, acc.: 50.20%] [G loss: 0.709772]
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1255 [D loss: 0.690634, acc.: 52.34%] [G loss: 0.707057]
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1256 [D loss: 0.694064, acc.: 49.41%] [G loss: 0.706224]
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1257 [D loss: 0.694524, acc.: 47.66%] [G loss: 0.702761]
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1258 [D loss: 0.694164, acc.: 49.02%] [G loss: 0.707710]
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1259 [D loss: 0.692091, acc.: 52.54%] [G loss: 0.702452]
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1260 [D loss: 0.692406, acc.: 52.34%] [G loss: 0.702461]
8/8 [==============================] - 0s 4ms/step
1261 [D loss: 0.692704, acc.: 50.20%] [G loss: 0.708868]
8/8 [==============================] - 0s 4ms/step
1262 [D loss: 0.690792, acc.: 52.34%] [G loss: 0.704750]
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1263 [D loss: 0.691069, acc.: 51.95%] [G loss: 0.702899]
8/8 [==============================] - 0s 4ms/step
1264 [D loss: 0.691302, acc.: 54.88%] [G loss: 0.700523]
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1265 [D loss: 0.691778, acc.: 53.71%] [G loss: 0.702167]
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1266 [D loss: 0.690954, acc.: 54.10%] [G loss: 0.696820]
8/8 [==============================] - 0s 4ms/step
1267 [D loss: 0.691635, acc.: 51.17%] [G loss: 0.695428]
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1268 [D loss: 0.689648, acc.: 54.10%] [G loss: 0.695745]
8/8 [==============================] - 0s 4ms/step
1269 [D loss: 0.691205, acc.: 53.52%] [G loss: 0.695376]
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1270 [D loss: 0.691840, acc.: 50.78%] [G loss: 0.697371]
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1271 [D loss: 0.692200, acc.: 54.10%] [G loss: 0.696686]
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1272 [D loss: 0.693323, acc.: 51.17%] [G loss: 0.697338]
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1273 [D loss: 0.689103, acc.: 53.71%] [G loss: 0.698729]
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1274 [D loss: 0.690468, acc.: 55.47%] [G loss: 0.700693]
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1275 [D loss: 0.695212, acc.: 47.66%] [G loss: 0.699935]
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1276 [D loss: 0.691792, acc.: 53.91%] [G loss: 0.698240]
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1277 [D loss: 0.694605, acc.: 48.63%] [G loss: 0.702507]
8/8 [==============================] - 0s 4ms/step
1278 [D loss: 0.692507, acc.: 49.80%] [G loss: 0.700852]
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1279 [D loss: 0.692791, acc.: 50.39%] [G loss: 0.702397]
8/8 [==============================] - 0s 4ms/step
1280 [D loss: 0.692362, acc.: 49.61%] [G loss: 0.705815]
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1281 [D loss: 0.692193, acc.: 49.41%] [G loss: 0.703292]
8/8 [==============================] - 0s 4ms/step
1282 [D loss: 0.689439, acc.: 51.17%] [G loss: 0.711123]
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1283 [D loss: 0.689545, acc.: 55.27%] [G loss: 0.714837]
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1284 [D loss: 0.690070, acc.: 49.02%] [G loss: 0.715219]
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1285 [D loss: 0.691988, acc.: 50.78%] [G loss: 0.711514]
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1286 [D loss: 0.691538, acc.: 51.37%] [G loss: 0.708065]
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1287 [D loss: 0.692766, acc.: 52.15%] [G loss: 0.699437]
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1288 [D loss: 0.694993, acc.: 45.90%] [G loss: 0.695537]
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1289 [D loss: 0.697911, acc.: 46.09%] [G loss: 0.699874]
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1290 [D loss: 0.694186, acc.: 49.61%] [G loss: 0.699117]
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1291 [D loss: 0.694106, acc.: 50.20%] [G loss: 0.704700]
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1292 [D loss: 0.692896, acc.: 49.80%] [G loss: 0.708538]
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1293 [D loss: 0.690680, acc.: 51.17%] [G loss: 0.710361]
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1294 [D loss: 0.691696, acc.: 53.91%] [G loss: 0.718293]
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1295 [D loss: 0.690567, acc.: 57.23%] [G loss: 0.714315]
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1296 [D loss: 0.688817, acc.: 56.05%] [G loss: 0.715750]
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1297 [D loss: 0.689060, acc.: 59.77%] [G loss: 0.712491]
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1298 [D loss: 0.687127, acc.: 57.03%] [G loss: 0.710107]
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1299 [D loss: 0.690222, acc.: 53.12%] [G loss: 0.711061]
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1300 [D loss: 0.690344, acc.: 53.12%] [G loss: 0.706904]
1/1 [==============================] - 0s 21ms/step
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1301 [D loss: 0.691406, acc.: 50.78%] [G loss: 0.709576]
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1302 [D loss: 0.693413, acc.: 50.39%] [G loss: 0.706417]
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1303 [D loss: 0.689709, acc.: 55.66%] [G loss: 0.705671]
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1304 [D loss: 0.690359, acc.: 55.27%] [G loss: 0.716570]
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1305 [D loss: 0.691672, acc.: 53.32%] [G loss: 0.711823]
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1306 [D loss: 0.692320, acc.: 52.93%] [G loss: 0.711968]
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1307 [D loss: 0.696491, acc.: 45.51%] [G loss: 0.700969]
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1308 [D loss: 0.695595, acc.: 47.66%] [G loss: 0.695947]
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1309 [D loss: 0.697353, acc.: 43.95%] [G loss: 0.693274]
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1310 [D loss: 0.696480, acc.: 47.85%] [G loss: 0.693995]
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1311 [D loss: 0.696719, acc.: 44.34%] [G loss: 0.695703]
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1312 [D loss: 0.693672, acc.: 47.85%] [G loss: 0.698622]
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1313 [D loss: 0.691257, acc.: 50.78%] [G loss: 0.699316]
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1314 [D loss: 0.688435, acc.: 55.27%] [G loss: 0.703249]
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1315 [D loss: 0.685941, acc.: 57.62%] [G loss: 0.709604]
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1316 [D loss: 0.687080, acc.: 58.01%] [G loss: 0.717194]
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1317 [D loss: 0.685423, acc.: 60.35%] [G loss: 0.716291]
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1318 [D loss: 0.687753, acc.: 54.88%] [G loss: 0.716003]
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1319 [D loss: 0.690723, acc.: 52.54%] [G loss: 0.707528]
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1320 [D loss: 0.695580, acc.: 47.27%] [G loss: 0.701472]
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1321 [D loss: 0.694699, acc.: 48.24%] [G loss: 0.690915]
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1322 [D loss: 0.697426, acc.: 44.34%] [G loss: 0.686978]
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1323 [D loss: 0.703034, acc.: 41.21%] [G loss: 0.687499]
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1324 [D loss: 0.697158, acc.: 44.92%] [G loss: 0.694663]
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1325 [D loss: 0.692981, acc.: 49.80%] [G loss: 0.703755]
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1326 [D loss: 0.687943, acc.: 58.40%] [G loss: 0.714941]
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1327 [D loss: 0.686751, acc.: 58.79%] [G loss: 0.721073]
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1328 [D loss: 0.684414, acc.: 56.45%] [G loss: 0.721182]
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1329 [D loss: 0.685284, acc.: 56.64%] [G loss: 0.728872]
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1330 [D loss: 0.688077, acc.: 55.27%] [G loss: 0.715758]
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1331 [D loss: 0.686641, acc.: 59.77%] [G loss: 0.703761]
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1332 [D loss: 0.693437, acc.: 51.17%] [G loss: 0.695465]
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1333 [D loss: 0.697663, acc.: 46.48%] [G loss: 0.685846]
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1334 [D loss: 0.698750, acc.: 50.00%] [G loss: 0.680759]
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1335 [D loss: 0.696273, acc.: 47.66%] [G loss: 0.687372]
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1336 [D loss: 0.696158, acc.: 45.90%] [G loss: 0.700077]
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1337 [D loss: 0.691799, acc.: 51.56%] [G loss: 0.700014]
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1338 [D loss: 0.689532, acc.: 53.71%] [G loss: 0.712099]
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1339 [D loss: 0.687686, acc.: 58.20%] [G loss: 0.714988]
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1340 [D loss: 0.686346, acc.: 57.23%] [G loss: 0.714724]
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1341 [D loss: 0.688535, acc.: 60.35%] [G loss: 0.716992]
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1342 [D loss: 0.684827, acc.: 60.94%] [G loss: 0.717237]
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1343 [D loss: 0.688172, acc.: 55.66%] [G loss: 0.709722]
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1344 [D loss: 0.689357, acc.: 55.27%] [G loss: 0.714677]
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1345 [D loss: 0.695169, acc.: 50.59%] [G loss: 0.705265]
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1346 [D loss: 0.694872, acc.: 45.90%] [G loss: 0.701731]
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1347 [D loss: 0.695325, acc.: 45.12%] [G loss: 0.698508]
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1348 [D loss: 0.693304, acc.: 46.09%] [G loss: 0.698530]
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1349 [D loss: 0.696883, acc.: 45.31%] [G loss: 0.698508]
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1350 [D loss: 0.695433, acc.: 45.51%] [G loss: 0.694773]
1/1 [==============================] - 0s 23ms/step
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1351 [D loss: 0.695183, acc.: 48.44%] [G loss: 0.693014]
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1352 [D loss: 0.694245, acc.: 46.29%] [G loss: 0.696003]
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1353 [D loss: 0.690551, acc.: 52.15%] [G loss: 0.703517]
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1354 [D loss: 0.687758, acc.: 57.42%] [G loss: 0.700087]
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1355 [D loss: 0.689260, acc.: 52.93%] [G loss: 0.705878]
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1356 [D loss: 0.689156, acc.: 53.91%] [G loss: 0.706622]
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1357 [D loss: 0.691480, acc.: 52.34%] [G loss: 0.706071]
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1358 [D loss: 0.691271, acc.: 51.37%] [G loss: 0.703626]
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1359 [D loss: 0.692984, acc.: 51.56%] [G loss: 0.705110]
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1360 [D loss: 0.692112, acc.: 50.59%] [G loss: 0.699862]
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1361 [D loss: 0.689231, acc.: 57.23%] [G loss: 0.706399]
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1362 [D loss: 0.693731, acc.: 51.76%] [G loss: 0.704169]
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1363 [D loss: 0.689789, acc.: 53.52%] [G loss: 0.705664]
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1364 [D loss: 0.688008, acc.: 56.84%] [G loss: 0.703322]
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1365 [D loss: 0.694136, acc.: 50.78%] [G loss: 0.704258]
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1366 [D loss: 0.688825, acc.: 56.84%] [G loss: 0.703322]
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1367 [D loss: 0.692896, acc.: 53.12%] [G loss: 0.710165]
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1368 [D loss: 0.693208, acc.: 52.54%] [G loss: 0.708059]
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1369 [D loss: 0.692756, acc.: 50.59%] [G loss: 0.708806]
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1370 [D loss: 0.692521, acc.: 50.20%] [G loss: 0.705384]
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1371 [D loss: 0.693571, acc.: 49.61%] [G loss: 0.707882]
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1372 [D loss: 0.694821, acc.: 51.56%] [G loss: 0.702342]
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1373 [D loss: 0.693559, acc.: 53.12%] [G loss: 0.710148]
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1374 [D loss: 0.692629, acc.: 53.52%] [G loss: 0.704884]
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1375 [D loss: 0.690961, acc.: 53.91%] [G loss: 0.707747]
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1376 [D loss: 0.689678, acc.: 54.88%] [G loss: 0.718433]
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1377 [D loss: 0.689306, acc.: 57.23%] [G loss: 0.718135]
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1378 [D loss: 0.686719, acc.: 59.57%] [G loss: 0.714898]
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1379 [D loss: 0.687252, acc.: 60.16%] [G loss: 0.716338]
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1380 [D loss: 0.688443, acc.: 59.57%] [G loss: 0.714031]
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1381 [D loss: 0.688279, acc.: 54.49%] [G loss: 0.704494]
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1382 [D loss: 0.690274, acc.: 52.15%] [G loss: 0.696201]
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1383 [D loss: 0.693426, acc.: 49.80%] [G loss: 0.691445]
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1384 [D loss: 0.694316, acc.: 48.05%] [G loss: 0.695984]
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1385 [D loss: 0.696688, acc.: 47.85%] [G loss: 0.696302]
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1386 [D loss: 0.694888, acc.: 49.61%] [G loss: 0.699497]
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1387 [D loss: 0.694598, acc.: 47.46%] [G loss: 0.708630]
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1388 [D loss: 0.690309, acc.: 51.76%] [G loss: 0.713646]
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1389 [D loss: 0.689249, acc.: 53.71%] [G loss: 0.715006]
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1390 [D loss: 0.692390, acc.: 52.54%] [G loss: 0.716562]
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1391 [D loss: 0.689106, acc.: 57.03%] [G loss: 0.709254]
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1392 [D loss: 0.688312, acc.: 56.45%] [G loss: 0.709692]
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1393 [D loss: 0.685431, acc.: 61.33%] [G loss: 0.704709]
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1394 [D loss: 0.687855, acc.: 59.57%] [G loss: 0.696221]
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1395 [D loss: 0.690760, acc.: 52.15%] [G loss: 0.690776]
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1396 [D loss: 0.694985, acc.: 51.56%] [G loss: 0.698388]
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1397 [D loss: 0.691976, acc.: 51.76%] [G loss: 0.706837]
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1398 [D loss: 0.690160, acc.: 56.64%] [G loss: 0.714315]
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1399 [D loss: 0.691632, acc.: 52.73%] [G loss: 0.728073]
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1400 [D loss: 0.690792, acc.: 51.95%] [G loss: 0.733219]
1/1 [==============================] - 0s 23ms/step
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1401 [D loss: 0.688264, acc.: 51.56%] [G loss: 0.737028]
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1402 [D loss: 0.693101, acc.: 50.00%] [G loss: 0.732056]
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1403 [D loss: 0.691107, acc.: 53.71%] [G loss: 0.716256]
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1404 [D loss: 0.692655, acc.: 52.54%] [G loss: 0.706297]
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1405 [D loss: 0.694470, acc.: 51.76%] [G loss: 0.699985]
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1406 [D loss: 0.694372, acc.: 49.80%] [G loss: 0.693955]
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1407 [D loss: 0.688066, acc.: 54.10%] [G loss: 0.699823]
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1408 [D loss: 0.691420, acc.: 54.10%] [G loss: 0.703035]
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1409 [D loss: 0.687723, acc.: 55.47%] [G loss: 0.712198]
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1410 [D loss: 0.683695, acc.: 61.33%] [G loss: 0.714736]
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1411 [D loss: 0.688569, acc.: 55.86%] [G loss: 0.713067]
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1412 [D loss: 0.688403, acc.: 56.45%] [G loss: 0.710310]
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1413 [D loss: 0.691862, acc.: 51.17%] [G loss: 0.705821]
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1414 [D loss: 0.694151, acc.: 49.80%] [G loss: 0.705696]
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1415 [D loss: 0.691208, acc.: 51.37%] [G loss: 0.706067]
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1416 [D loss: 0.689384, acc.: 53.32%] [G loss: 0.711929]
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1417 [D loss: 0.682856, acc.: 57.23%] [G loss: 0.723624]
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1418 [D loss: 0.684852, acc.: 56.05%] [G loss: 0.713458]
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1419 [D loss: 0.691210, acc.: 53.12%] [G loss: 0.699556]
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1420 [D loss: 0.699277, acc.: 45.51%] [G loss: 0.693530]
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1421 [D loss: 0.699244, acc.: 47.46%] [G loss: 0.688320]
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1422 [D loss: 0.696232, acc.: 47.46%] [G loss: 0.694500]
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1423 [D loss: 0.696314, acc.: 47.85%] [G loss: 0.700459]
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1424 [D loss: 0.693134, acc.: 49.22%] [G loss: 0.708067]
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1425 [D loss: 0.692778, acc.: 49.41%] [G loss: 0.711031]
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1426 [D loss: 0.689612, acc.: 57.03%] [G loss: 0.716379]
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1427 [D loss: 0.688010, acc.: 56.05%] [G loss: 0.716598]
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1428 [D loss: 0.688092, acc.: 55.27%] [G loss: 0.719306]
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1429 [D loss: 0.686663, acc.: 57.42%] [G loss: 0.716674]
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1430 [D loss: 0.689438, acc.: 54.88%] [G loss: 0.715181]
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1431 [D loss: 0.691888, acc.: 54.88%] [G loss: 0.717814]
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1432 [D loss: 0.692739, acc.: 54.49%] [G loss: 0.714827]
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1433 [D loss: 0.696687, acc.: 48.83%] [G loss: 0.713119]
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1434 [D loss: 0.692251, acc.: 51.95%] [G loss: 0.716854]
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1435 [D loss: 0.690374, acc.: 53.32%] [G loss: 0.715058]
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1436 [D loss: 0.687040, acc.: 57.42%] [G loss: 0.716813]
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1437 [D loss: 0.685320, acc.: 61.91%] [G loss: 0.709192]
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1438 [D loss: 0.688365, acc.: 53.71%] [G loss: 0.706830]
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1439 [D loss: 0.685580, acc.: 57.42%] [G loss: 0.700889]
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1440 [D loss: 0.692448, acc.: 53.32%] [G loss: 0.693256]
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1441 [D loss: 0.691128, acc.: 52.93%] [G loss: 0.696228]
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1442 [D loss: 0.692301, acc.: 52.34%] [G loss: 0.697413]
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1443 [D loss: 0.693410, acc.: 50.20%] [G loss: 0.700305]
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1444 [D loss: 0.689657, acc.: 54.88%] [G loss: 0.714287]
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1445 [D loss: 0.688560, acc.: 55.08%] [G loss: 0.723180]
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1446 [D loss: 0.687776, acc.: 53.52%] [G loss: 0.710475]
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1447 [D loss: 0.689189, acc.: 50.98%] [G loss: 0.719286]
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1448 [D loss: 0.688520, acc.: 51.56%] [G loss: 0.710351]
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1449 [D loss: 0.691731, acc.: 50.78%] [G loss: 0.704318]
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1450 [D loss: 0.692021, acc.: 51.56%] [G loss: 0.694864]
1/1 [==============================] - 0s 24ms/step
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1451 [D loss: 0.691957, acc.: 48.63%] [G loss: 0.695920]
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1452 [D loss: 0.691420, acc.: 49.80%] [G loss: 0.701545]
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1453 [D loss: 0.689714, acc.: 54.88%] [G loss: 0.705003]
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1454 [D loss: 0.692836, acc.: 50.00%] [G loss: 0.712370]
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1455 [D loss: 0.688510, acc.: 55.27%] [G loss: 0.735550]
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1456 [D loss: 0.683753, acc.: 56.25%] [G loss: 0.744378]
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1457 [D loss: 0.683678, acc.: 62.50%] [G loss: 0.745954]
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1458 [D loss: 0.688740, acc.: 54.49%] [G loss: 0.730375]
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1459 [D loss: 0.688754, acc.: 55.66%] [G loss: 0.714920]
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1460 [D loss: 0.689255, acc.: 58.98%] [G loss: 0.711157]
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1461 [D loss: 0.691491, acc.: 54.10%] [G loss: 0.703863]
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1462 [D loss: 0.692072, acc.: 51.56%] [G loss: 0.685098]
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1463 [D loss: 0.701962, acc.: 47.46%] [G loss: 0.683482]
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1464 [D loss: 0.700145, acc.: 48.63%] [G loss: 0.691646]
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1465 [D loss: 0.693717, acc.: 49.80%] [G loss: 0.706673]
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1466 [D loss: 0.691673, acc.: 51.76%] [G loss: 0.710937]
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1467 [D loss: 0.691277, acc.: 52.34%] [G loss: 0.718624]
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1468 [D loss: 0.687480, acc.: 56.64%] [G loss: 0.727880]
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1469 [D loss: 0.689310, acc.: 56.05%] [G loss: 0.721984]
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1470 [D loss: 0.691848, acc.: 56.84%] [G loss: 0.719712]
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1471 [D loss: 0.684350, acc.: 64.65%] [G loss: 0.720727]
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1472 [D loss: 0.681188, acc.: 66.21%] [G loss: 0.721489]
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1473 [D loss: 0.682295, acc.: 62.70%] [G loss: 0.710900]
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1474 [D loss: 0.685867, acc.: 55.66%] [G loss: 0.698811]
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1475 [D loss: 0.693283, acc.: 49.61%] [G loss: 0.697837]
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1476 [D loss: 0.693073, acc.: 51.17%] [G loss: 0.699514]
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1477 [D loss: 0.691864, acc.: 52.15%] [G loss: 0.707919]
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1478 [D loss: 0.692010, acc.: 51.56%] [G loss: 0.718286]
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1479 [D loss: 0.688511, acc.: 52.93%] [G loss: 0.725001]
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1480 [D loss: 0.690207, acc.: 51.37%] [G loss: 0.729768]
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1481 [D loss: 0.692642, acc.: 49.61%] [G loss: 0.733354]
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1482 [D loss: 0.695851, acc.: 48.05%] [G loss: 0.720429]
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1483 [D loss: 0.691858, acc.: 57.42%] [G loss: 0.717408]
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1484 [D loss: 0.689646, acc.: 59.18%] [G loss: 0.717004]
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1485 [D loss: 0.684475, acc.: 64.65%] [G loss: 0.715277]
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1486 [D loss: 0.684308, acc.: 58.40%] [G loss: 0.706798]
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1487 [D loss: 0.690172, acc.: 51.95%] [G loss: 0.701701]
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1488 [D loss: 0.688539, acc.: 54.49%] [G loss: 0.700345]
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1489 [D loss: 0.685705, acc.: 55.47%] [G loss: 0.701795]
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1490 [D loss: 0.684609, acc.: 58.20%] [G loss: 0.707742]
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1491 [D loss: 0.685434, acc.: 57.23%] [G loss: 0.702821]
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1492 [D loss: 0.687467, acc.: 55.66%] [G loss: 0.706030]
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1493 [D loss: 0.688068, acc.: 52.93%] [G loss: 0.704952]
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1494 [D loss: 0.689690, acc.: 50.39%] [G loss: 0.704771]
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1495 [D loss: 0.693829, acc.: 50.59%] [G loss: 0.702008]
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1496 [D loss: 0.691201, acc.: 51.95%] [G loss: 0.707275]
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1497 [D loss: 0.687819, acc.: 57.81%] [G loss: 0.707575]
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1498 [D loss: 0.693377, acc.: 52.93%] [G loss: 0.711102]
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1499 [D loss: 0.687684, acc.: 57.03%] [G loss: 0.720316]
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1500 [D loss: 0.687994, acc.: 56.64%] [G loss: 0.723984]
1/1 [==============================] - 0s 22ms/step
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1501 [D loss: 0.687671, acc.: 60.16%] [G loss: 0.728624]
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1502 [D loss: 0.682192, acc.: 61.33%] [G loss: 0.733924]
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1503 [D loss: 0.685013, acc.: 56.84%] [G loss: 0.734181]
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1504 [D loss: 0.685707, acc.: 59.57%] [G loss: 0.733136]
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1505 [D loss: 0.688602, acc.: 55.66%] [G loss: 0.725522]
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1506 [D loss: 0.692131, acc.: 53.12%] [G loss: 0.713587]
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1507 [D loss: 0.691708, acc.: 53.12%] [G loss: 0.702505]
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1508 [D loss: 0.692936, acc.: 48.44%] [G loss: 0.696149]
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1509 [D loss: 0.692975, acc.: 51.56%] [G loss: 0.699420]
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1510 [D loss: 0.698265, acc.: 47.85%] [G loss: 0.694350]
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1511 [D loss: 0.691328, acc.: 52.15%] [G loss: 0.707333]
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1512 [D loss: 0.694185, acc.: 52.93%] [G loss: 0.720826]
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1513 [D loss: 0.687029, acc.: 53.91%] [G loss: 0.728787]
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1514 [D loss: 0.690341, acc.: 56.64%] [G loss: 0.727710]
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1515 [D loss: 0.689727, acc.: 54.49%] [G loss: 0.713269]
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1516 [D loss: 0.695180, acc.: 48.63%] [G loss: 0.705614]
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1517 [D loss: 0.688450, acc.: 53.12%] [G loss: 0.710029]
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1518 [D loss: 0.694112, acc.: 46.88%] [G loss: 0.704281]
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1519 [D loss: 0.693648, acc.: 50.59%] [G loss: 0.705147]
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1520 [D loss: 0.693379, acc.: 49.22%] [G loss: 0.712683]
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1521 [D loss: 0.686722, acc.: 54.49%] [G loss: 0.735152]
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1522 [D loss: 0.684580, acc.: 57.23%] [G loss: 0.745196]
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1523 [D loss: 0.684252, acc.: 56.25%] [G loss: 0.739829]
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1524 [D loss: 0.690747, acc.: 54.10%] [G loss: 0.736812]
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1525 [D loss: 0.694783, acc.: 51.56%] [G loss: 0.721738]
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1526 [D loss: 0.697740, acc.: 51.76%] [G loss: 0.706402]
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1527 [D loss: 0.695221, acc.: 51.95%] [G loss: 0.708896]
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1528 [D loss: 0.692309, acc.: 55.47%] [G loss: 0.699542]
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1529 [D loss: 0.698072, acc.: 49.61%] [G loss: 0.706413]
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1530 [D loss: 0.693853, acc.: 52.54%] [G loss: 0.711825]
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1531 [D loss: 0.688051, acc.: 53.52%] [G loss: 0.737919]
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1532 [D loss: 0.681895, acc.: 61.72%] [G loss: 0.738136]
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1533 [D loss: 0.685207, acc.: 57.42%] [G loss: 0.728377]
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1534 [D loss: 0.686247, acc.: 57.81%] [G loss: 0.719664]
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1535 [D loss: 0.690078, acc.: 55.08%] [G loss: 0.707900]
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1536 [D loss: 0.687220, acc.: 55.27%] [G loss: 0.699270]
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1537 [D loss: 0.693354, acc.: 55.27%] [G loss: 0.684816]
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1538 [D loss: 0.694809, acc.: 50.98%] [G loss: 0.683457]
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1539 [D loss: 0.694245, acc.: 50.00%] [G loss: 0.686737]
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1540 [D loss: 0.691282, acc.: 53.32%] [G loss: 0.691549]
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1541 [D loss: 0.695235, acc.: 50.59%] [G loss: 0.706291]
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1542 [D loss: 0.685265, acc.: 56.45%] [G loss: 0.711282]
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1543 [D loss: 0.686330, acc.: 55.27%] [G loss: 0.715095]
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1544 [D loss: 0.687223, acc.: 57.62%] [G loss: 0.716217]
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1545 [D loss: 0.689560, acc.: 54.30%] [G loss: 0.713458]
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1546 [D loss: 0.689783, acc.: 53.32%] [G loss: 0.717671]
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1547 [D loss: 0.687331, acc.: 53.32%] [G loss: 0.716286]
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1548 [D loss: 0.688196, acc.: 51.76%] [G loss: 0.716979]
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1549 [D loss: 0.692119, acc.: 51.37%] [G loss: 0.716680]
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1550 [D loss: 0.687381, acc.: 51.76%] [G loss: 0.717563]
1/1 [==============================] - 0s 25ms/step
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1551 [D loss: 0.688204, acc.: 55.86%] [G loss: 0.725191]
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1552 [D loss: 0.682814, acc.: 57.62%] [G loss: 0.738406]
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1553 [D loss: 0.685470, acc.: 56.84%] [G loss: 0.742089]
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1554 [D loss: 0.686654, acc.: 56.64%] [G loss: 0.734784]
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1555 [D loss: 0.687866, acc.: 59.18%] [G loss: 0.735341]
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1556 [D loss: 0.683803, acc.: 59.57%] [G loss: 0.743707]
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1557 [D loss: 0.684095, acc.: 59.96%] [G loss: 0.736211]
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1558 [D loss: 0.689711, acc.: 56.45%] [G loss: 0.729923]
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1559 [D loss: 0.691625, acc.: 53.32%] [G loss: 0.715481]
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1560 [D loss: 0.696082, acc.: 52.54%] [G loss: 0.704199]
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1561 [D loss: 0.696540, acc.: 50.98%] [G loss: 0.698119]
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1562 [D loss: 0.697271, acc.: 48.83%] [G loss: 0.706749]
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1563 [D loss: 0.694095, acc.: 51.17%] [G loss: 0.718097]
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1564 [D loss: 0.689395, acc.: 54.88%] [G loss: 0.729144]
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1565 [D loss: 0.688987, acc.: 53.71%] [G loss: 0.722864]
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1566 [D loss: 0.683987, acc.: 58.59%] [G loss: 0.710274]
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1567 [D loss: 0.688782, acc.: 55.27%] [G loss: 0.707218]
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1568 [D loss: 0.688883, acc.: 56.45%] [G loss: 0.699006]
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1569 [D loss: 0.692646, acc.: 50.98%] [G loss: 0.705885]
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1570 [D loss: 0.689656, acc.: 53.91%] [G loss: 0.707882]
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1571 [D loss: 0.686227, acc.: 57.23%] [G loss: 0.710563]
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1572 [D loss: 0.685906, acc.: 56.64%] [G loss: 0.716553]
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1573 [D loss: 0.685465, acc.: 54.69%] [G loss: 0.717315]
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1574 [D loss: 0.685180, acc.: 55.08%] [G loss: 0.711469]
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1575 [D loss: 0.688570, acc.: 53.91%] [G loss: 0.699742]
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1576 [D loss: 0.690205, acc.: 50.00%] [G loss: 0.701647]
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1577 [D loss: 0.692932, acc.: 50.59%] [G loss: 0.695343]
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1578 [D loss: 0.697843, acc.: 48.83%] [G loss: 0.704873]
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1579 [D loss: 0.694439, acc.: 50.39%] [G loss: 0.706777]
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1580 [D loss: 0.689043, acc.: 53.91%] [G loss: 0.724041]
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1581 [D loss: 0.692969, acc.: 51.56%] [G loss: 0.717189]
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1582 [D loss: 0.690435, acc.: 53.71%] [G loss: 0.721591]
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1583 [D loss: 0.686566, acc.: 57.42%] [G loss: 0.719118]
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1584 [D loss: 0.690462, acc.: 53.12%] [G loss: 0.721352]
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1585 [D loss: 0.683866, acc.: 57.23%] [G loss: 0.716790]
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1586 [D loss: 0.684973, acc.: 56.25%] [G loss: 0.715616]
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1587 [D loss: 0.690953, acc.: 50.39%] [G loss: 0.711456]
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1588 [D loss: 0.685975, acc.: 54.30%] [G loss: 0.710010]
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1589 [D loss: 0.689854, acc.: 53.91%] [G loss: 0.708840]
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1590 [D loss: 0.689583, acc.: 51.17%] [G loss: 0.721008]
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1591 [D loss: 0.690751, acc.: 55.08%] [G loss: 0.730536]
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1592 [D loss: 0.689756, acc.: 56.25%] [G loss: 0.733175]
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1593 [D loss: 0.692749, acc.: 54.10%] [G loss: 0.740157]
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1594 [D loss: 0.696910, acc.: 49.80%] [G loss: 0.725035]
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1595 [D loss: 0.689456, acc.: 51.95%] [G loss: 0.721897]
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1596 [D loss: 0.686924, acc.: 58.79%] [G loss: 0.716061]
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1597 [D loss: 0.684404, acc.: 59.57%] [G loss: 0.712123]
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1598 [D loss: 0.691188, acc.: 48.24%] [G loss: 0.698056]
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1599 [D loss: 0.685868, acc.: 55.47%] [G loss: 0.705680]
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1600 [D loss: 0.681235, acc.: 59.77%] [G loss: 0.704539]
1/1 [==============================] - 0s 25ms/step
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1601 [D loss: 0.685660, acc.: 53.91%] [G loss: 0.716436]
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1602 [D loss: 0.691856, acc.: 55.86%] [G loss: 0.719370]
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1603 [D loss: 0.692035, acc.: 50.59%] [G loss: 0.711355]
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1604 [D loss: 0.690289, acc.: 53.91%] [G loss: 0.708150]
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1605 [D loss: 0.693096, acc.: 51.76%] [G loss: 0.708270]
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1606 [D loss: 0.690328, acc.: 51.76%] [G loss: 0.706399]
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1607 [D loss: 0.695260, acc.: 48.24%] [G loss: 0.702581]
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1608 [D loss: 0.687719, acc.: 55.66%] [G loss: 0.712091]
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1609 [D loss: 0.688649, acc.: 53.71%] [G loss: 0.714646]
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1610 [D loss: 0.686616, acc.: 57.42%] [G loss: 0.732106]
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1611 [D loss: 0.683401, acc.: 58.01%] [G loss: 0.730561]
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1612 [D loss: 0.683592, acc.: 58.20%] [G loss: 0.736165]
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1613 [D loss: 0.688814, acc.: 57.42%] [G loss: 0.724934]
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1614 [D loss: 0.686709, acc.: 60.74%] [G loss: 0.711523]
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1615 [D loss: 0.690397, acc.: 55.27%] [G loss: 0.716127]
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1616 [D loss: 0.695778, acc.: 51.17%] [G loss: 0.709805]
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1617 [D loss: 0.690802, acc.: 53.32%] [G loss: 0.702213]
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1618 [D loss: 0.696147, acc.: 51.37%] [G loss: 0.708552]
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1619 [D loss: 0.693959, acc.: 53.12%] [G loss: 0.733802]
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1620 [D loss: 0.692720, acc.: 48.44%] [G loss: 0.742456]
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1621 [D loss: 0.685183, acc.: 57.62%] [G loss: 0.757454]
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1622 [D loss: 0.689501, acc.: 53.71%] [G loss: 0.761142]
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1623 [D loss: 0.690160, acc.: 53.12%] [G loss: 0.745470]
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1624 [D loss: 0.691675, acc.: 57.42%] [G loss: 0.731549]
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1625 [D loss: 0.681167, acc.: 64.06%] [G loss: 0.729818]
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1626 [D loss: 0.679308, acc.: 62.50%] [G loss: 0.717891]
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1627 [D loss: 0.688644, acc.: 53.52%] [G loss: 0.701564]
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1628 [D loss: 0.696352, acc.: 47.07%] [G loss: 0.686972]
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1629 [D loss: 0.693880, acc.: 47.66%] [G loss: 0.702149]
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1630 [D loss: 0.686339, acc.: 56.45%] [G loss: 0.719134]
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1631 [D loss: 0.683209, acc.: 58.59%] [G loss: 0.723748]
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1632 [D loss: 0.693364, acc.: 50.39%] [G loss: 0.711507]
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1633 [D loss: 0.690260, acc.: 52.15%] [G loss: 0.706408]
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1634 [D loss: 0.695279, acc.: 48.63%] [G loss: 0.708581]
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1635 [D loss: 0.695345, acc.: 48.83%] [G loss: 0.706950]
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1636 [D loss: 0.690254, acc.: 53.71%] [G loss: 0.704530]
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1637 [D loss: 0.692918, acc.: 51.37%] [G loss: 0.707542]
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1638 [D loss: 0.690911, acc.: 53.52%] [G loss: 0.707550]
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1639 [D loss: 0.688011, acc.: 57.81%] [G loss: 0.709123]
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1640 [D loss: 0.687195, acc.: 55.27%] [G loss: 0.726867]
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1641 [D loss: 0.684254, acc.: 57.81%] [G loss: 0.725587]
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1642 [D loss: 0.687503, acc.: 56.45%] [G loss: 0.723772]
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1643 [D loss: 0.685879, acc.: 57.81%] [G loss: 0.727289]
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1644 [D loss: 0.687499, acc.: 57.81%] [G loss: 0.714013]
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1645 [D loss: 0.693141, acc.: 53.12%] [G loss: 0.715117]
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1646 [D loss: 0.688392, acc.: 54.30%] [G loss: 0.700387]
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1647 [D loss: 0.693981, acc.: 53.71%] [G loss: 0.687791]
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1648 [D loss: 0.699832, acc.: 47.07%] [G loss: 0.702107]
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1649 [D loss: 0.695977, acc.: 50.78%] [G loss: 0.701402]
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1650 [D loss: 0.693434, acc.: 49.02%] [G loss: 0.721091]
1/1 [==============================] - 0s 23ms/step
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1651 [D loss: 0.688807, acc.: 54.88%] [G loss: 0.722381]
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1652 [D loss: 0.686708, acc.: 57.81%] [G loss: 0.729213]
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1653 [D loss: 0.686302, acc.: 57.23%] [G loss: 0.727449]
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1654 [D loss: 0.694270, acc.: 52.93%] [G loss: 0.721538]
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1655 [D loss: 0.688855, acc.: 53.91%] [G loss: 0.711413]
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1656 [D loss: 0.694227, acc.: 47.07%] [G loss: 0.701785]
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1657 [D loss: 0.690994, acc.: 47.46%] [G loss: 0.697875]
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1658 [D loss: 0.690480, acc.: 53.52%] [G loss: 0.701289]
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1659 [D loss: 0.694000, acc.: 50.59%] [G loss: 0.708372]
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1660 [D loss: 0.689980, acc.: 54.10%] [G loss: 0.711705]
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1661 [D loss: 0.689180, acc.: 53.71%] [G loss: 0.713248]
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1662 [D loss: 0.689541, acc.: 54.88%] [G loss: 0.711317]
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1663 [D loss: 0.689791, acc.: 55.86%] [G loss: 0.713821]
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1664 [D loss: 0.688370, acc.: 55.47%] [G loss: 0.708350]
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1665 [D loss: 0.692931, acc.: 50.78%] [G loss: 0.713956]
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1666 [D loss: 0.691780, acc.: 50.78%] [G loss: 0.708917]
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1667 [D loss: 0.690193, acc.: 51.95%] [G loss: 0.706623]
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1668 [D loss: 0.692215, acc.: 52.34%] [G loss: 0.708125]
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1669 [D loss: 0.691533, acc.: 54.88%] [G loss: 0.708344]
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1670 [D loss: 0.694867, acc.: 53.52%] [G loss: 0.716978]
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1671 [D loss: 0.690060, acc.: 52.54%] [G loss: 0.714366]
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1672 [D loss: 0.687380, acc.: 55.47%] [G loss: 0.716870]
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1673 [D loss: 0.694544, acc.: 52.73%] [G loss: 0.720978]
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1674 [D loss: 0.694268, acc.: 49.02%] [G loss: 0.724973]
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1675 [D loss: 0.694007, acc.: 51.56%] [G loss: 0.714696]
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1676 [D loss: 0.691136, acc.: 53.71%] [G loss: 0.714023]
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1677 [D loss: 0.685251, acc.: 59.18%] [G loss: 0.714855]
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1678 [D loss: 0.686112, acc.: 57.03%] [G loss: 0.703982]
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1679 [D loss: 0.690816, acc.: 50.59%] [G loss: 0.715073]
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1680 [D loss: 0.690190, acc.: 50.78%] [G loss: 0.707700]
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1681 [D loss: 0.687258, acc.: 57.23%] [G loss: 0.706333]
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1682 [D loss: 0.695446, acc.: 46.29%] [G loss: 0.706723]
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1683 [D loss: 0.692283, acc.: 50.20%] [G loss: 0.709370]
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1684 [D loss: 0.696269, acc.: 50.20%] [G loss: 0.706153]
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1685 [D loss: 0.688987, acc.: 52.15%] [G loss: 0.716531]
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1686 [D loss: 0.693172, acc.: 50.20%] [G loss: 0.718892]
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1687 [D loss: 0.684802, acc.: 59.57%] [G loss: 0.720009]
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1688 [D loss: 0.688694, acc.: 56.64%] [G loss: 0.722642]
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1689 [D loss: 0.686431, acc.: 56.64%] [G loss: 0.715214]
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1690 [D loss: 0.686475, acc.: 54.10%] [G loss: 0.713914]
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1691 [D loss: 0.690167, acc.: 51.95%] [G loss: 0.706420]
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1692 [D loss: 0.691004, acc.: 49.22%] [G loss: 0.713932]
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1693 [D loss: 0.688778, acc.: 52.34%] [G loss: 0.708732]
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1694 [D loss: 0.687264, acc.: 56.45%] [G loss: 0.712230]
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1695 [D loss: 0.689131, acc.: 53.52%] [G loss: 0.711566]
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1696 [D loss: 0.692249, acc.: 49.41%] [G loss: 0.716825]
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1697 [D loss: 0.694480, acc.: 50.00%] [G loss: 0.712740]
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1698 [D loss: 0.690809, acc.: 51.95%] [G loss: 0.712684]
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1699 [D loss: 0.691458, acc.: 51.95%] [G loss: 0.711057]
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1700 [D loss: 0.693337, acc.: 48.83%] [G loss: 0.714018]
1/1 [==============================] - 0s 24ms/step
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1701 [D loss: 0.692442, acc.: 52.15%] [G loss: 0.718681]
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1702 [D loss: 0.691617, acc.: 52.15%] [G loss: 0.715871]
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1703 [D loss: 0.684712, acc.: 57.62%] [G loss: 0.714841]
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1704 [D loss: 0.683330, acc.: 55.47%] [G loss: 0.714367]
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1705 [D loss: 0.684029, acc.: 53.71%] [G loss: 0.711538]
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1706 [D loss: 0.688589, acc.: 53.32%] [G loss: 0.712821]
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1707 [D loss: 0.686525, acc.: 54.88%] [G loss: 0.708033]
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1708 [D loss: 0.689818, acc.: 51.95%] [G loss: 0.717536]
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1709 [D loss: 0.686817, acc.: 51.76%] [G loss: 0.716265]
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1710 [D loss: 0.695733, acc.: 48.44%] [G loss: 0.718230]
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1711 [D loss: 0.688670, acc.: 58.20%] [G loss: 0.720172]
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1712 [D loss: 0.688004, acc.: 55.27%] [G loss: 0.721825]
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1713 [D loss: 0.689827, acc.: 54.10%] [G loss: 0.723257]
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1714 [D loss: 0.690341, acc.: 53.52%] [G loss: 0.721953]
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1715 [D loss: 0.690058, acc.: 54.49%] [G loss: 0.718063]
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1716 [D loss: 0.689115, acc.: 56.45%] [G loss: 0.717471]
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1717 [D loss: 0.691612, acc.: 51.56%] [G loss: 0.720465]
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1718 [D loss: 0.692550, acc.: 49.80%] [G loss: 0.707585]
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1719 [D loss: 0.687753, acc.: 54.49%] [G loss: 0.710394]
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1720 [D loss: 0.691751, acc.: 48.63%] [G loss: 0.714092]
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1721 [D loss: 0.687495, acc.: 49.61%] [G loss: 0.725140]
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1722 [D loss: 0.685882, acc.: 51.17%] [G loss: 0.728199]
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1723 [D loss: 0.683542, acc.: 57.23%] [G loss: 0.729742]
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1724 [D loss: 0.688402, acc.: 54.49%] [G loss: 0.740553]
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1725 [D loss: 0.684997, acc.: 56.64%] [G loss: 0.743224]
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1726 [D loss: 0.681949, acc.: 58.59%] [G loss: 0.733206]
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1727 [D loss: 0.687903, acc.: 54.49%] [G loss: 0.728309]
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1728 [D loss: 0.685501, acc.: 57.62%] [G loss: 0.716522]
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1729 [D loss: 0.694188, acc.: 51.95%] [G loss: 0.705466]
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1730 [D loss: 0.696570, acc.: 48.24%] [G loss: 0.699383]
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1731 [D loss: 0.697725, acc.: 48.05%] [G loss: 0.708549]
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1732 [D loss: 0.692936, acc.: 51.37%] [G loss: 0.726935]
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1733 [D loss: 0.690678, acc.: 53.52%] [G loss: 0.740130]
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1734 [D loss: 0.684772, acc.: 58.20%] [G loss: 0.740411]
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1735 [D loss: 0.689123, acc.: 54.49%] [G loss: 0.732103]
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1736 [D loss: 0.688619, acc.: 56.05%] [G loss: 0.726626]
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1737 [D loss: 0.685098, acc.: 56.45%] [G loss: 0.710940]
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1738 [D loss: 0.691463, acc.: 50.59%] [G loss: 0.718110]
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1739 [D loss: 0.690620, acc.: 52.93%] [G loss: 0.722535]
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1740 [D loss: 0.685620, acc.: 53.32%] [G loss: 0.720756]
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1741 [D loss: 0.683849, acc.: 53.71%] [G loss: 0.739993]
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1742 [D loss: 0.687970, acc.: 51.76%] [G loss: 0.722635]
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1743 [D loss: 0.685881, acc.: 52.73%] [G loss: 0.718752]
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1744 [D loss: 0.688423, acc.: 54.10%] [G loss: 0.714394]
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1745 [D loss: 0.691884, acc.: 50.39%] [G loss: 0.707603]
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1746 [D loss: 0.697188, acc.: 46.68%] [G loss: 0.709247]
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1747 [D loss: 0.691781, acc.: 53.12%] [G loss: 0.711664]
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1748 [D loss: 0.696911, acc.: 50.59%] [G loss: 0.719256]
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1749 [D loss: 0.694733, acc.: 51.95%] [G loss: 0.725268]
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1750 [D loss: 0.692764, acc.: 49.80%] [G loss: 0.729974]
1/1 [==============================] - 0s 23ms/step
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1751 [D loss: 0.685400, acc.: 53.52%] [G loss: 0.730175]
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1752 [D loss: 0.685208, acc.: 54.49%] [G loss: 0.731030]
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1753 [D loss: 0.688324, acc.: 51.95%] [G loss: 0.751422]
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1754 [D loss: 0.679863, acc.: 59.18%] [G loss: 0.755049]
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1755 [D loss: 0.682756, acc.: 54.69%] [G loss: 0.762010]
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1756 [D loss: 0.683214, acc.: 56.64%] [G loss: 0.757572]
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1757 [D loss: 0.680344, acc.: 58.01%] [G loss: 0.753390]
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1758 [D loss: 0.689116, acc.: 53.91%] [G loss: 0.739971]
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1759 [D loss: 0.689544, acc.: 55.66%] [G loss: 0.725294]
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1760 [D loss: 0.695572, acc.: 52.15%] [G loss: 0.706055]
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1761 [D loss: 0.690227, acc.: 53.71%] [G loss: 0.707384]
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1762 [D loss: 0.688659, acc.: 54.69%] [G loss: 0.726941]
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1763 [D loss: 0.680264, acc.: 56.64%] [G loss: 0.727584]
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1764 [D loss: 0.682772, acc.: 56.25%] [G loss: 0.734380]
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1765 [D loss: 0.683236, acc.: 56.45%] [G loss: 0.739729]
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1766 [D loss: 0.682892, acc.: 55.47%] [G loss: 0.737590]
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1767 [D loss: 0.689258, acc.: 49.61%] [G loss: 0.712853]
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1768 [D loss: 0.681672, acc.: 56.25%] [G loss: 0.712534]
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1769 [D loss: 0.685879, acc.: 50.20%] [G loss: 0.701057]
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1770 [D loss: 0.691095, acc.: 47.46%] [G loss: 0.697773]
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1771 [D loss: 0.696349, acc.: 48.05%] [G loss: 0.699562]
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1772 [D loss: 0.697169, acc.: 46.48%] [G loss: 0.720515]
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1773 [D loss: 0.682034, acc.: 54.69%] [G loss: 0.714047]
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1774 [D loss: 0.687707, acc.: 53.71%] [G loss: 0.724075]
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1775 [D loss: 0.687932, acc.: 53.71%] [G loss: 0.732081]
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1776 [D loss: 0.689959, acc.: 51.37%] [G loss: 0.727073]
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1777 [D loss: 0.688260, acc.: 55.27%] [G loss: 0.734666]
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1778 [D loss: 0.686335, acc.: 55.27%] [G loss: 0.737585]
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1779 [D loss: 0.685907, acc.: 58.79%] [G loss: 0.737119]
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1780 [D loss: 0.687834, acc.: 54.10%] [G loss: 0.739007]
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1781 [D loss: 0.686152, acc.: 55.47%] [G loss: 0.748157]
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1782 [D loss: 0.690555, acc.: 52.93%] [G loss: 0.743893]
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1783 [D loss: 0.692789, acc.: 50.98%] [G loss: 0.746974]
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1784 [D loss: 0.691370, acc.: 51.76%] [G loss: 0.742754]
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1785 [D loss: 0.694358, acc.: 49.02%] [G loss: 0.745948]
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1786 [D loss: 0.699163, acc.: 49.80%] [G loss: 0.741874]
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1787 [D loss: 0.690256, acc.: 56.45%] [G loss: 0.741300]
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1788 [D loss: 0.685394, acc.: 58.59%] [G loss: 0.730236]
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1789 [D loss: 0.685826, acc.: 55.86%] [G loss: 0.725577]
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1790 [D loss: 0.696379, acc.: 49.41%] [G loss: 0.706717]
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1791 [D loss: 0.693309, acc.: 51.37%] [G loss: 0.710839]
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1792 [D loss: 0.689729, acc.: 52.34%] [G loss: 0.718266]
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1793 [D loss: 0.683061, acc.: 54.88%] [G loss: 0.735864]
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1794 [D loss: 0.677554, acc.: 58.59%] [G loss: 0.748039]
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1795 [D loss: 0.688371, acc.: 53.32%] [G loss: 0.733630]
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1796 [D loss: 0.688808, acc.: 52.54%] [G loss: 0.724655]
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1797 [D loss: 0.684836, acc.: 58.01%] [G loss: 0.716628]
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1798 [D loss: 0.688528, acc.: 51.76%] [G loss: 0.700606]
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1799 [D loss: 0.697808, acc.: 51.95%] [G loss: 0.695751]
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1800 [D loss: 0.694833, acc.: 51.17%] [G loss: 0.718247]
1/1 [==============================] - 0s 23ms/step
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1801 [D loss: 0.685687, acc.: 55.27%] [G loss: 0.746485]
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1802 [D loss: 0.682216, acc.: 55.08%] [G loss: 0.741654]
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1803 [D loss: 0.690360, acc.: 53.71%] [G loss: 0.743868]
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1804 [D loss: 0.687369, acc.: 56.05%] [G loss: 0.739578]
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1805 [D loss: 0.689381, acc.: 51.76%] [G loss: 0.733068]
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1806 [D loss: 0.689848, acc.: 51.76%] [G loss: 0.723727]
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1807 [D loss: 0.686716, acc.: 52.54%] [G loss: 0.713339]
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1808 [D loss: 0.691183, acc.: 47.85%] [G loss: 0.723333]
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1809 [D loss: 0.704571, acc.: 44.73%] [G loss: 0.721047]
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1810 [D loss: 0.691561, acc.: 52.34%] [G loss: 0.752793]
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1811 [D loss: 0.685159, acc.: 54.49%] [G loss: 0.759694]
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1812 [D loss: 0.680918, acc.: 57.03%] [G loss: 0.755430]
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1813 [D loss: 0.690083, acc.: 54.49%] [G loss: 0.753477]
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1814 [D loss: 0.691771, acc.: 51.56%] [G loss: 0.741471]
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1815 [D loss: 0.702237, acc.: 49.61%] [G loss: 0.732442]
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1816 [D loss: 0.687423, acc.: 56.84%] [G loss: 0.724964]
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1817 [D loss: 0.688643, acc.: 52.93%] [G loss: 0.719769]
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1818 [D loss: 0.687678, acc.: 53.91%] [G loss: 0.718959]
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1819 [D loss: 0.687347, acc.: 54.69%] [G loss: 0.714378]
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1820 [D loss: 0.688787, acc.: 55.86%] [G loss: 0.738293]
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1821 [D loss: 0.682417, acc.: 57.23%] [G loss: 0.744280]
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1822 [D loss: 0.683716, acc.: 58.59%] [G loss: 0.769082]
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1823 [D loss: 0.683337, acc.: 55.27%] [G loss: 0.758880]
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1824 [D loss: 0.684818, acc.: 58.79%] [G loss: 0.769783]
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1825 [D loss: 0.688696, acc.: 58.20%] [G loss: 0.744212]
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1826 [D loss: 0.687849, acc.: 58.40%] [G loss: 0.727892]
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1827 [D loss: 0.687755, acc.: 54.49%] [G loss: 0.714477]
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1828 [D loss: 0.686828, acc.: 53.71%] [G loss: 0.691406]
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1829 [D loss: 0.690283, acc.: 52.73%] [G loss: 0.687186]
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1830 [D loss: 0.693680, acc.: 52.34%] [G loss: 0.690702]
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1831 [D loss: 0.689654, acc.: 53.32%] [G loss: 0.719517]
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1832 [D loss: 0.689762, acc.: 52.73%] [G loss: 0.742174]
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1833 [D loss: 0.684167, acc.: 56.45%] [G loss: 0.763082]
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1834 [D loss: 0.687826, acc.: 53.32%] [G loss: 0.770133]
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1835 [D loss: 0.692381, acc.: 51.95%] [G loss: 0.769199]
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1836 [D loss: 0.692298, acc.: 51.76%] [G loss: 0.756402]
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1837 [D loss: 0.697617, acc.: 47.85%] [G loss: 0.742785]
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1838 [D loss: 0.699503, acc.: 51.17%] [G loss: 0.729062]
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1839 [D loss: 0.689748, acc.: 54.10%] [G loss: 0.724614]
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1840 [D loss: 0.686703, acc.: 53.52%] [G loss: 0.711703]
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1841 [D loss: 0.695850, acc.: 48.63%] [G loss: 0.721154]
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1842 [D loss: 0.684967, acc.: 55.47%] [G loss: 0.730649]
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1843 [D loss: 0.685695, acc.: 54.69%] [G loss: 0.731997]
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1844 [D loss: 0.678876, acc.: 57.23%] [G loss: 0.764898]
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1845 [D loss: 0.677909, acc.: 58.79%] [G loss: 0.751662]
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1846 [D loss: 0.682684, acc.: 57.42%] [G loss: 0.742075]
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1847 [D loss: 0.682005, acc.: 59.77%] [G loss: 0.732970]
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1848 [D loss: 0.688441, acc.: 58.20%] [G loss: 0.713215]
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1849 [D loss: 0.685632, acc.: 53.32%] [G loss: 0.692611]
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1850 [D loss: 0.703349, acc.: 47.66%] [G loss: 0.683326]
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1851 [D loss: 0.699337, acc.: 46.29%] [G loss: 0.684341]
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1852 [D loss: 0.692613, acc.: 51.17%] [G loss: 0.706194]
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1853 [D loss: 0.687396, acc.: 54.30%] [G loss: 0.715790]
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1854 [D loss: 0.685391, acc.: 55.86%] [G loss: 0.759587]
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1855 [D loss: 0.683578, acc.: 57.23%] [G loss: 0.747056]
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1856 [D loss: 0.685274, acc.: 57.03%] [G loss: 0.739827]
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1857 [D loss: 0.687312, acc.: 57.03%] [G loss: 0.729282]
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1858 [D loss: 0.684144, acc.: 59.57%] [G loss: 0.733284]
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1859 [D loss: 0.685504, acc.: 55.27%] [G loss: 0.722104]
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1860 [D loss: 0.685804, acc.: 54.69%] [G loss: 0.712720]
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1861 [D loss: 0.697393, acc.: 49.80%] [G loss: 0.713398]
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1862 [D loss: 0.688689, acc.: 54.69%] [G loss: 0.719910]
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1863 [D loss: 0.686116, acc.: 52.54%] [G loss: 0.730819]
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1864 [D loss: 0.683472, acc.: 53.52%] [G loss: 0.747227]
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1865 [D loss: 0.685789, acc.: 54.49%] [G loss: 0.741153]
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1866 [D loss: 0.683585, acc.: 52.93%] [G loss: 0.750212]
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1867 [D loss: 0.685351, acc.: 53.91%] [G loss: 0.756045]
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1868 [D loss: 0.682261, acc.: 55.66%] [G loss: 0.742048]
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1869 [D loss: 0.690504, acc.: 50.20%] [G loss: 0.748986]
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1870 [D loss: 0.695780, acc.: 49.02%] [G loss: 0.739692]
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1871 [D loss: 0.700181, acc.: 49.41%] [G loss: 0.728177]
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1872 [D loss: 0.690489, acc.: 52.54%] [G loss: 0.737141]
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1873 [D loss: 0.681582, acc.: 53.52%] [G loss: 0.754879]
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1874 [D loss: 0.688512, acc.: 53.71%] [G loss: 0.749489]
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1875 [D loss: 0.693768, acc.: 52.15%] [G loss: 0.742684]
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1876 [D loss: 0.686967, acc.: 55.27%] [G loss: 0.729230]
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1877 [D loss: 0.681781, acc.: 59.77%] [G loss: 0.710518]
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1878 [D loss: 0.681780, acc.: 58.59%] [G loss: 0.710623]
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1879 [D loss: 0.689440, acc.: 54.49%] [G loss: 0.684549]
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1880 [D loss: 0.686851, acc.: 53.91%] [G loss: 0.704785]
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1881 [D loss: 0.685713, acc.: 55.08%] [G loss: 0.722322]
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1882 [D loss: 0.691519, acc.: 52.54%] [G loss: 0.720664]
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1883 [D loss: 0.691104, acc.: 50.98%] [G loss: 0.747153]
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1884 [D loss: 0.678625, acc.: 57.62%] [G loss: 0.742391]
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1885 [D loss: 0.689021, acc.: 50.39%] [G loss: 0.736859]
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1886 [D loss: 0.684449, acc.: 51.56%] [G loss: 0.733240]
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1887 [D loss: 0.686891, acc.: 53.12%] [G loss: 0.728152]
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1888 [D loss: 0.690843, acc.: 49.22%] [G loss: 0.708156]
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1889 [D loss: 0.689582, acc.: 49.02%] [G loss: 0.703503]
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1890 [D loss: 0.696000, acc.: 51.56%] [G loss: 0.717744]
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1891 [D loss: 0.700829, acc.: 46.29%] [G loss: 0.723168]
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1892 [D loss: 0.691391, acc.: 50.98%] [G loss: 0.729021]
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1893 [D loss: 0.691838, acc.: 49.80%] [G loss: 0.738346]
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1894 [D loss: 0.683439, acc.: 55.66%] [G loss: 0.748742]
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1895 [D loss: 0.685811, acc.: 53.12%] [G loss: 0.750944]
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1896 [D loss: 0.678783, acc.: 56.84%] [G loss: 0.756172]
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1897 [D loss: 0.674891, acc.: 59.18%] [G loss: 0.751182]
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1898 [D loss: 0.681426, acc.: 57.81%] [G loss: 0.749664]
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1899 [D loss: 0.678226, acc.: 57.81%] [G loss: 0.740721]
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1900 [D loss: 0.690351, acc.: 54.30%] [G loss: 0.733838]
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1901 [D loss: 0.686893, acc.: 56.05%] [G loss: 0.733499]
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1902 [D loss: 0.687129, acc.: 53.32%] [G loss: 0.735646]
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1903 [D loss: 0.692495, acc.: 52.93%] [G loss: 0.717542]
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1904 [D loss: 0.697896, acc.: 49.41%] [G loss: 0.718121]
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1905 [D loss: 0.694859, acc.: 49.41%] [G loss: 0.707720]
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1906 [D loss: 0.700179, acc.: 47.07%] [G loss: 0.702945]
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1907 [D loss: 0.694831, acc.: 50.20%] [G loss: 0.712938]
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1908 [D loss: 0.684781, acc.: 56.64%] [G loss: 0.734302]
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1909 [D loss: 0.681134, acc.: 56.64%] [G loss: 0.743804]
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1910 [D loss: 0.676545, acc.: 55.86%] [G loss: 0.747129]
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1911 [D loss: 0.684288, acc.: 53.91%] [G loss: 0.734686]
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1912 [D loss: 0.689389, acc.: 52.93%] [G loss: 0.716404]
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1913 [D loss: 0.688093, acc.: 53.91%] [G loss: 0.702951]
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1914 [D loss: 0.692941, acc.: 50.20%] [G loss: 0.699514]
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1915 [D loss: 0.692391, acc.: 48.83%] [G loss: 0.707616]
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1916 [D loss: 0.689822, acc.: 51.95%] [G loss: 0.728875]
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1917 [D loss: 0.688103, acc.: 51.56%] [G loss: 0.746871]
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1918 [D loss: 0.680712, acc.: 55.08%] [G loss: 0.755198]
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1919 [D loss: 0.684906, acc.: 53.71%] [G loss: 0.758820]
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1920 [D loss: 0.690536, acc.: 49.02%] [G loss: 0.755563]
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1921 [D loss: 0.690541, acc.: 54.49%] [G loss: 0.746255]
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1922 [D loss: 0.690611, acc.: 54.69%] [G loss: 0.736383]
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1923 [D loss: 0.680469, acc.: 56.25%] [G loss: 0.714459]
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1924 [D loss: 0.687827, acc.: 53.91%] [G loss: 0.698992]
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1925 [D loss: 0.687906, acc.: 53.52%] [G loss: 0.696934]
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1926 [D loss: 0.700597, acc.: 51.56%] [G loss: 0.709046]
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1927 [D loss: 0.694537, acc.: 50.78%] [G loss: 0.724955]
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1928 [D loss: 0.690532, acc.: 50.20%] [G loss: 0.753333]
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1929 [D loss: 0.680143, acc.: 55.47%] [G loss: 0.810000]
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1930 [D loss: 0.682609, acc.: 57.23%] [G loss: 0.798467]
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1931 [D loss: 0.688380, acc.: 55.27%] [G loss: 0.778410]
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1932 [D loss: 0.688956, acc.: 52.54%] [G loss: 0.768678]
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1933 [D loss: 0.691642, acc.: 52.93%] [G loss: 0.740964]
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1934 [D loss: 0.688317, acc.: 53.12%] [G loss: 0.735032]
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1935 [D loss: 0.682291, acc.: 57.23%] [G loss: 0.720351]
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1936 [D loss: 0.692295, acc.: 50.39%] [G loss: 0.704620]
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1937 [D loss: 0.691750, acc.: 50.00%] [G loss: 0.700575]
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1938 [D loss: 0.696884, acc.: 53.71%] [G loss: 0.714622]
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1939 [D loss: 0.678770, acc.: 56.25%] [G loss: 0.731646]
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1940 [D loss: 0.690869, acc.: 53.12%] [G loss: 0.741198]
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1941 [D loss: 0.694492, acc.: 50.78%] [G loss: 0.739865]
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1942 [D loss: 0.691788, acc.: 50.39%] [G loss: 0.724685]
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1943 [D loss: 0.691489, acc.: 53.71%] [G loss: 0.724056]
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1944 [D loss: 0.689692, acc.: 52.93%] [G loss: 0.726639]
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1945 [D loss: 0.683501, acc.: 54.30%] [G loss: 0.715389]
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1946 [D loss: 0.687562, acc.: 52.54%] [G loss: 0.713339]
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1947 [D loss: 0.689020, acc.: 48.63%] [G loss: 0.709165]
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1948 [D loss: 0.691882, acc.: 54.69%] [G loss: 0.714131]
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1949 [D loss: 0.686428, acc.: 55.08%] [G loss: 0.712736]
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1950 [D loss: 0.690911, acc.: 56.05%] [G loss: 0.725337]
1/1 [==============================] - 0s 23ms/step
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1951 [D loss: 0.685698, acc.: 55.08%] [G loss: 0.736198]
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1952 [D loss: 0.689949, acc.: 52.34%] [G loss: 0.747603]
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1953 [D loss: 0.685400, acc.: 53.91%] [G loss: 0.751372]
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1954 [D loss: 0.688769, acc.: 55.86%] [G loss: 0.751695]
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1955 [D loss: 0.692541, acc.: 49.80%] [G loss: 0.752497]
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1956 [D loss: 0.694054, acc.: 51.37%] [G loss: 0.740902]
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1957 [D loss: 0.690008, acc.: 53.12%] [G loss: 0.735032]
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1958 [D loss: 0.683445, acc.: 58.01%] [G loss: 0.726443]
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1959 [D loss: 0.686604, acc.: 56.64%] [G loss: 0.719442]
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1960 [D loss: 0.687632, acc.: 53.91%] [G loss: 0.711760]
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1961 [D loss: 0.684095, acc.: 53.71%] [G loss: 0.717072]
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1962 [D loss: 0.687216, acc.: 57.62%] [G loss: 0.744074]
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1963 [D loss: 0.678204, acc.: 55.86%] [G loss: 0.750704]
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1964 [D loss: 0.686771, acc.: 52.93%] [G loss: 0.746214]
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1965 [D loss: 0.683879, acc.: 55.47%] [G loss: 0.747875]
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1966 [D loss: 0.688972, acc.: 53.12%] [G loss: 0.740766]
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1967 [D loss: 0.686770, acc.: 55.08%] [G loss: 0.723586]
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1968 [D loss: 0.689189, acc.: 51.76%] [G loss: 0.724500]
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1969 [D loss: 0.686014, acc.: 53.91%] [G loss: 0.721025]
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1970 [D loss: 0.688059, acc.: 51.76%] [G loss: 0.716753]
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1971 [D loss: 0.695522, acc.: 49.80%] [G loss: 0.720183]
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1972 [D loss: 0.690334, acc.: 54.88%] [G loss: 0.725563]
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1973 [D loss: 0.690402, acc.: 54.30%] [G loss: 0.725877]
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1974 [D loss: 0.692598, acc.: 53.12%] [G loss: 0.745744]
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1975 [D loss: 0.680930, acc.: 55.86%] [G loss: 0.751207]
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1976 [D loss: 0.684846, acc.: 53.52%] [G loss: 0.749334]
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1977 [D loss: 0.687178, acc.: 54.30%] [G loss: 0.742649]
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1978 [D loss: 0.677004, acc.: 57.42%] [G loss: 0.741381]
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1979 [D loss: 0.690704, acc.: 53.52%] [G loss: 0.722696]
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1980 [D loss: 0.681974, acc.: 53.71%] [G loss: 0.729341]
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1981 [D loss: 0.684027, acc.: 54.69%] [G loss: 0.735509]
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1982 [D loss: 0.678428, acc.: 57.23%] [G loss: 0.726778]
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1983 [D loss: 0.685542, acc.: 52.34%] [G loss: 0.738631]
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1984 [D loss: 0.688579, acc.: 53.91%] [G loss: 0.733184]
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1985 [D loss: 0.683220, acc.: 56.64%] [G loss: 0.733751]
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1986 [D loss: 0.692687, acc.: 52.54%] [G loss: 0.743088]
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1987 [D loss: 0.689153, acc.: 53.12%] [G loss: 0.738929]
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1988 [D loss: 0.680737, acc.: 56.45%] [G loss: 0.737592]
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1989 [D loss: 0.683191, acc.: 55.86%] [G loss: 0.737485]
8/8 [==============================] - 0s 4ms/step
1990 [D loss: 0.687923, acc.: 52.73%] [G loss: 0.728694]
8/8 [==============================] - 0s 4ms/step
1991 [D loss: 0.698388, acc.: 47.66%] [G loss: 0.727220]
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1992 [D loss: 0.688332, acc.: 53.71%] [G loss: 0.741748]
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1993 [D loss: 0.686230, acc.: 54.88%] [G loss: 0.727852]
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1994 [D loss: 0.684750, acc.: 54.69%] [G loss: 0.734491]
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1995 [D loss: 0.690367, acc.: 53.32%] [G loss: 0.740430]
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1996 [D loss: 0.692019, acc.: 52.15%] [G loss: 0.733566]
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1997 [D loss: 0.688299, acc.: 53.52%] [G loss: 0.736240]
8/8 [==============================] - 0s 4ms/step
1998 [D loss: 0.695728, acc.: 53.52%] [G loss: 0.728505]
8/8 [==============================] - 0s 4ms/step
1999 [D loss: 0.687598, acc.: 55.27%] [G loss: 0.734136]
8/8 [==============================] - 0s 4ms/step
2000 [D loss: 0.685486, acc.: 57.42%] [G loss: 0.728614]
1/1 [==============================] - 0s 24ms/step
8/8 [==============================] - 0s 4ms/step
2001 [D loss: 0.688459, acc.: 54.10%] [G loss: 0.737528]
8/8 [==============================] - 0s 4ms/step
2002 [D loss: 0.688391, acc.: 54.30%] [G loss: 0.750762]
8/8 [==============================] - 0s 4ms/step
2003 [D loss: 0.674397, acc.: 58.01%] [G loss: 0.761882]
8/8 [==============================] - 0s 4ms/step
2004 [D loss: 0.685642, acc.: 56.64%] [G loss: 0.753828]
8/8 [==============================] - 0s 4ms/step
2005 [D loss: 0.681262, acc.: 56.45%] [G loss: 0.735315]
8/8 [==============================] - 0s 4ms/step
2006 [D loss: 0.676393, acc.: 58.59%] [G loss: 0.725380]
8/8 [==============================] - 0s 4ms/step
2007 [D loss: 0.684606, acc.: 51.17%] [G loss: 0.728607]
8/8 [==============================] - 0s 4ms/step
2008 [D loss: 0.690369, acc.: 51.95%] [G loss: 0.715021]
8/8 [==============================] - 0s 4ms/step
2009 [D loss: 0.695217, acc.: 50.59%] [G loss: 0.736738]
8/8 [==============================] - 0s 4ms/step
2010 [D loss: 0.686125, acc.: 52.73%] [G loss: 0.748156]
8/8 [==============================] - 0s 4ms/step
2011 [D loss: 0.682857, acc.: 54.10%] [G loss: 0.759522]
8/8 [==============================] - 0s 4ms/step
2012 [D loss: 0.683399, acc.: 56.45%] [G loss: 0.753155]
8/8 [==============================] - 0s 4ms/step
2013 [D loss: 0.687451, acc.: 54.10%] [G loss: 0.731379]
8/8 [==============================] - 0s 4ms/step
2014 [D loss: 0.689074, acc.: 53.71%] [G loss: 0.727940]
8/8 [==============================] - 0s 4ms/step
2015 [D loss: 0.691974, acc.: 55.47%] [G loss: 0.736710]
8/8 [==============================] - 0s 4ms/step
2016 [D loss: 0.682985, acc.: 54.10%] [G loss: 0.744813]
8/8 [==============================] - 0s 4ms/step
2017 [D loss: 0.693131, acc.: 53.91%] [G loss: 0.735770]
8/8 [==============================] - 0s 4ms/step
2018 [D loss: 0.685746, acc.: 52.93%] [G loss: 0.742941]
8/8 [==============================] - 0s 4ms/step
2019 [D loss: 0.684026, acc.: 56.64%] [G loss: 0.754805]
8/8 [==============================] - 0s 4ms/step
2020 [D loss: 0.690199, acc.: 50.78%] [G loss: 0.769531]
8/8 [==============================] - 0s 4ms/step
2021 [D loss: 0.683822, acc.: 56.84%] [G loss: 0.760902]
8/8 [==============================] - 0s 4ms/step
2022 [D loss: 0.684427, acc.: 55.08%] [G loss: 0.741535]
8/8 [==============================] - 0s 4ms/step
2023 [D loss: 0.681463, acc.: 56.45%] [G loss: 0.738891]
8/8 [==============================] - 0s 4ms/step
2024 [D loss: 0.689752, acc.: 54.10%] [G loss: 0.721299]
8/8 [==============================] - 0s 4ms/step
2025 [D loss: 0.694346, acc.: 48.44%] [G loss: 0.703381]
8/8 [==============================] - 0s 4ms/step
2026 [D loss: 0.695814, acc.: 51.95%] [G loss: 0.724546]
8/8 [==============================] - 0s 4ms/step
2027 [D loss: 0.691643, acc.: 52.54%] [G loss: 0.747422]
8/8 [==============================] - 0s 4ms/step
2028 [D loss: 0.690464, acc.: 53.71%] [G loss: 0.765373]
8/8 [==============================] - 0s 4ms/step
2029 [D loss: 0.685049, acc.: 55.27%] [G loss: 0.789752]
8/8 [==============================] - 0s 4ms/step
2030 [D loss: 0.685902, acc.: 53.71%] [G loss: 0.775831]
8/8 [==============================] - 0s 4ms/step
2031 [D loss: 0.691431, acc.: 50.98%] [G loss: 0.763983]
8/8 [==============================] - 0s 4ms/step
2032 [D loss: 0.692853, acc.: 52.54%] [G loss: 0.750075]
8/8 [==============================] - 0s 5ms/step
2033 [D loss: 0.691850, acc.: 52.15%] [G loss: 0.728351]
8/8 [==============================] - 0s 4ms/step
2034 [D loss: 0.699942, acc.: 46.09%] [G loss: 0.728055]
8/8 [==============================] - 0s 4ms/step
2035 [D loss: 0.695589, acc.: 52.15%] [G loss: 0.725148]
8/8 [==============================] - 0s 4ms/step
2036 [D loss: 0.691576, acc.: 54.88%] [G loss: 0.753665]
8/8 [==============================] - 0s 4ms/step
2037 [D loss: 0.686599, acc.: 58.01%] [G loss: 0.745913]
8/8 [==============================] - 0s 4ms/step
2038 [D loss: 0.679966, acc.: 58.59%] [G loss: 0.746290]
8/8 [==============================] - 0s 4ms/step
2039 [D loss: 0.679810, acc.: 58.40%] [G loss: 0.744676]
8/8 [==============================] - 0s 4ms/step
2040 [D loss: 0.683212, acc.: 56.25%] [G loss: 0.747343]
8/8 [==============================] - 0s 4ms/step
2041 [D loss: 0.681450, acc.: 56.45%] [G loss: 0.740177]
8/8 [==============================] - 0s 4ms/step
2042 [D loss: 0.688596, acc.: 52.34%] [G loss: 0.737380]
8/8 [==============================] - 0s 4ms/step
2043 [D loss: 0.702924, acc.: 47.46%] [G loss: 0.719169]
8/8 [==============================] - 0s 4ms/step
2044 [D loss: 0.702316, acc.: 45.51%] [G loss: 0.712153]
8/8 [==============================] - 0s 4ms/step
2045 [D loss: 0.693929, acc.: 50.78%] [G loss: 0.702711]
8/8 [==============================] - 0s 4ms/step
2046 [D loss: 0.697968, acc.: 49.80%] [G loss: 0.724593]
8/8 [==============================] - 0s 4ms/step
2047 [D loss: 0.687629, acc.: 54.30%] [G loss: 0.734649]
8/8 [==============================] - 0s 4ms/step
2048 [D loss: 0.693650, acc.: 49.41%] [G loss: 0.739466]
8/8 [==============================] - 0s 4ms/step
2049 [D loss: 0.689865, acc.: 50.59%] [G loss: 0.732312]
8/8 [==============================] - 0s 4ms/step
2050 [D loss: 0.685709, acc.: 54.30%] [G loss: 0.727769]
1/1 [==============================] - 0s 21ms/step
8/8 [==============================] - 0s 4ms/step
2051 [D loss: 0.683510, acc.: 54.30%] [G loss: 0.714684]
8/8 [==============================] - 0s 4ms/step
2052 [D loss: 0.683007, acc.: 54.69%] [G loss: 0.739183]
8/8 [==============================] - 0s 4ms/step
2053 [D loss: 0.689153, acc.: 54.49%] [G loss: 0.745062]
8/8 [==============================] - 0s 4ms/step
2054 [D loss: 0.675935, acc.: 61.13%] [G loss: 0.759621]
8/8 [==============================] - 0s 4ms/step
2055 [D loss: 0.670077, acc.: 58.98%] [G loss: 0.777471]
8/8 [==============================] - 0s 4ms/step
2056 [D loss: 0.682238, acc.: 57.23%] [G loss: 0.764237]
8/8 [==============================] - 0s 5ms/step
2057 [D loss: 0.672427, acc.: 58.40%] [G loss: 0.772590]
8/8 [==============================] - 0s 4ms/step
2058 [D loss: 0.680401, acc.: 56.05%] [G loss: 0.755896]
8/8 [==============================] - 0s 4ms/step
2059 [D loss: 0.681973, acc.: 52.93%] [G loss: 0.729425]
8/8 [==============================] - 0s 4ms/step
2060 [D loss: 0.694387, acc.: 49.61%] [G loss: 0.702775]
8/8 [==============================] - 0s 4ms/step
2061 [D loss: 0.702750, acc.: 44.73%] [G loss: 0.689737]
8/8 [==============================] - 0s 4ms/step
2062 [D loss: 0.702791, acc.: 47.46%] [G loss: 0.693771]
8/8 [==============================] - 0s 4ms/step
2063 [D loss: 0.700238, acc.: 49.41%] [G loss: 0.700774]
8/8 [==============================] - 0s 4ms/step
2064 [D loss: 0.713459, acc.: 44.14%] [G loss: 0.720030]
8/8 [==============================] - 0s 4ms/step
2065 [D loss: 0.696253, acc.: 51.17%] [G loss: 0.730646]
8/8 [==============================] - 0s 4ms/step
2066 [D loss: 0.685900, acc.: 53.52%] [G loss: 0.760246]
8/8 [==============================] - 0s 4ms/step
2067 [D loss: 0.684196, acc.: 56.84%] [G loss: 0.756869]
8/8 [==============================] - 0s 4ms/step
2068 [D loss: 0.681310, acc.: 56.84%] [G loss: 0.744107]
8/8 [==============================] - 0s 4ms/step
2069 [D loss: 0.678293, acc.: 58.59%] [G loss: 0.737266]
8/8 [==============================] - 0s 4ms/step
2070 [D loss: 0.682111, acc.: 53.91%] [G loss: 0.737142]
8/8 [==============================] - 0s 4ms/step
2071 [D loss: 0.679469, acc.: 57.23%] [G loss: 0.721618]
8/8 [==============================] - 0s 4ms/step
2072 [D loss: 0.681023, acc.: 55.27%] [G loss: 0.718578]
8/8 [==============================] - 0s 4ms/step
2073 [D loss: 0.684337, acc.: 52.15%] [G loss: 0.703567]
8/8 [==============================] - 0s 4ms/step
2074 [D loss: 0.692109, acc.: 50.98%] [G loss: 0.709986]
8/8 [==============================] - 0s 4ms/step
2075 [D loss: 0.687199, acc.: 56.05%] [G loss: 0.732346]
8/8 [==============================] - 0s 4ms/step
2076 [D loss: 0.704589, acc.: 49.22%] [G loss: 0.726131]
8/8 [==============================] - 0s 4ms/step
2077 [D loss: 0.699912, acc.: 45.12%] [G loss: 0.730743]
8/8 [==============================] - 0s 4ms/step
2078 [D loss: 0.694429, acc.: 51.56%] [G loss: 0.722178]
8/8 [==============================] - 0s 4ms/step
2079 [D loss: 0.689986, acc.: 51.95%] [G loss: 0.724672]
8/8 [==============================] - 0s 4ms/step
2080 [D loss: 0.697759, acc.: 51.37%] [G loss: 0.730865]
8/8 [==============================] - 0s 4ms/step
2081 [D loss: 0.690380, acc.: 50.98%] [G loss: 0.725756]
8/8 [==============================] - 0s 4ms/step
2082 [D loss: 0.686164, acc.: 54.69%] [G loss: 0.727048]
8/8 [==============================] - 0s 4ms/step
2083 [D loss: 0.679441, acc.: 57.23%] [G loss: 0.741207]
8/8 [==============================] - 0s 4ms/step
2084 [D loss: 0.683186, acc.: 57.81%] [G loss: 0.738173]
8/8 [==============================] - 0s 4ms/step
2085 [D loss: 0.687786, acc.: 51.95%] [G loss: 0.745099]
8/8 [==============================] - 0s 4ms/step
2086 [D loss: 0.688349, acc.: 53.91%] [G loss: 0.752921]
8/8 [==============================] - 0s 4ms/step
2087 [D loss: 0.689926, acc.: 53.12%] [G loss: 0.743726]
8/8 [==============================] - 0s 4ms/step
2088 [D loss: 0.691918, acc.: 53.91%] [G loss: 0.745196]
8/8 [==============================] - 0s 4ms/step
2089 [D loss: 0.686315, acc.: 56.45%] [G loss: 0.736181]
8/8 [==============================] - 0s 4ms/step
2090 [D loss: 0.692679, acc.: 50.98%] [G loss: 0.730372]
8/8 [==============================] - 0s 4ms/step
2091 [D loss: 0.696903, acc.: 50.00%] [G loss: 0.729123]
8/8 [==============================] - 0s 4ms/step
2092 [D loss: 0.688927, acc.: 56.45%] [G loss: 0.740322]
8/8 [==============================] - 0s 4ms/step
2093 [D loss: 0.686209, acc.: 53.32%] [G loss: 0.735073]
8/8 [==============================] - 0s 4ms/step
2094 [D loss: 0.681946, acc.: 57.03%] [G loss: 0.734156]
8/8 [==============================] - 0s 4ms/step
2095 [D loss: 0.691390, acc.: 53.12%] [G loss: 0.734992]
8/8 [==============================] - 0s 4ms/step
2096 [D loss: 0.684530, acc.: 55.86%] [G loss: 0.746407]
8/8 [==============================] - 0s 4ms/step
2097 [D loss: 0.684938, acc.: 53.52%] [G loss: 0.750589]
8/8 [==============================] - 0s 4ms/step
2098 [D loss: 0.683477, acc.: 56.45%] [G loss: 0.740152]
8/8 [==============================] - 0s 4ms/step
2099 [D loss: 0.683020, acc.: 57.23%] [G loss: 0.731769]
8/8 [==============================] - 0s 4ms/step
2100 [D loss: 0.691014, acc.: 53.71%] [G loss: 0.734164]
1/1 [==============================] - 0s 22ms/step
8/8 [==============================] - 0s 4ms/step
2101 [D loss: 0.687920, acc.: 54.30%] [G loss: 0.712619]
8/8 [==============================] - 0s 4ms/step
2102 [D loss: 0.692826, acc.: 51.95%] [G loss: 0.713941]
8/8 [==============================] - 0s 4ms/step
2103 [D loss: 0.691644, acc.: 51.95%] [G loss: 0.708587]
8/8 [==============================] - 0s 4ms/step
2104 [D loss: 0.694564, acc.: 50.78%] [G loss: 0.713270]
8/8 [==============================] - 0s 4ms/step
2105 [D loss: 0.686206, acc.: 54.88%] [G loss: 0.736146]
8/8 [==============================] - 0s 4ms/step
2106 [D loss: 0.691769, acc.: 50.98%] [G loss: 0.750154]
8/8 [==============================] - 0s 4ms/step
2107 [D loss: 0.685865, acc.: 51.95%] [G loss: 0.776207]
8/8 [==============================] - 0s 4ms/step
2108 [D loss: 0.683344, acc.: 54.69%] [G loss: 0.752280]
8/8 [==============================] - 0s 4ms/step
2109 [D loss: 0.686714, acc.: 55.27%] [G loss: 0.768732]
8/8 [==============================] - 0s 4ms/step
2110 [D loss: 0.681584, acc.: 56.05%] [G loss: 0.740389]
8/8 [==============================] - 0s 5ms/step
2111 [D loss: 0.685079, acc.: 54.69%] [G loss: 0.741223]
8/8 [==============================] - 0s 4ms/step
2112 [D loss: 0.683154, acc.: 54.49%] [G loss: 0.720672]
8/8 [==============================] - 0s 4ms/step
2113 [D loss: 0.684244, acc.: 51.56%] [G loss: 0.725900]
8/8 [==============================] - 0s 4ms/step
2114 [D loss: 0.678459, acc.: 55.47%] [G loss: 0.732833]
8/8 [==============================] - 0s 4ms/step
2115 [D loss: 0.686228, acc.: 52.73%] [G loss: 0.735813]
8/8 [==============================] - 0s 4ms/step
2116 [D loss: 0.687942, acc.: 53.12%] [G loss: 0.750045]
8/8 [==============================] - 0s 4ms/step
2117 [D loss: 0.689699, acc.: 53.91%] [G loss: 0.740750]
8/8 [==============================] - 0s 4ms/step
2118 [D loss: 0.683501, acc.: 53.91%] [G loss: 0.751528]
8/8 [==============================] - 0s 5ms/step
2119 [D loss: 0.688467, acc.: 54.88%] [G loss: 0.744427]
8/8 [==============================] - 0s 4ms/step
2120 [D loss: 0.685812, acc.: 55.66%] [G loss: 0.732235]
8/8 [==============================] - 0s 4ms/step
2121 [D loss: 0.689750, acc.: 52.73%] [G loss: 0.732424]
8/8 [==============================] - 0s 4ms/step
2122 [D loss: 0.686518, acc.: 56.45%] [G loss: 0.740231]
8/8 [==============================] - 0s 4ms/step
2123 [D loss: 0.686312, acc.: 58.40%] [G loss: 0.737555]
8/8 [==============================] - 0s 4ms/step
2124 [D loss: 0.683836, acc.: 54.30%] [G loss: 0.749693]
8/8 [==============================] - 0s 4ms/step
2125 [D loss: 0.682822, acc.: 53.91%] [G loss: 0.744206]
8/8 [==============================] - 0s 4ms/step
2126 [D loss: 0.680468, acc.: 54.30%] [G loss: 0.750289]
8/8 [==============================] - 0s 4ms/step
2127 [D loss: 0.684606, acc.: 55.66%] [G loss: 0.744644]
8/8 [==============================] - 0s 4ms/step
2128 [D loss: 0.682978, acc.: 56.05%] [G loss: 0.737796]
8/8 [==============================] - 0s 4ms/step
2129 [D loss: 0.684946, acc.: 56.45%] [G loss: 0.741159]
8/8 [==============================] - 0s 4ms/step
2130 [D loss: 0.696974, acc.: 48.24%] [G loss: 0.732349]
8/8 [==============================] - 0s 4ms/step
2131 [D loss: 0.686709, acc.: 52.93%] [G loss: 0.738107]
8/8 [==============================] - 0s 4ms/step
2132 [D loss: 0.686301, acc.: 55.27%] [G loss: 0.735303]
8/8 [==============================] - 0s 4ms/step
2133 [D loss: 0.682129, acc.: 54.30%] [G loss: 0.766486]
8/8 [==============================] - 0s 4ms/step
2134 [D loss: 0.684522, acc.: 51.95%] [G loss: 0.758032]
8/8 [==============================] - 0s 4ms/step
2135 [D loss: 0.687833, acc.: 51.95%] [G loss: 0.740110]
8/8 [==============================] - 0s 4ms/step
2136 [D loss: 0.684079, acc.: 56.05%] [G loss: 0.729150]
8/8 [==============================] - 0s 4ms/step
2137 [D loss: 0.674799, acc.: 60.74%] [G loss: 0.729781]
8/8 [==============================] - 0s 4ms/step
2138 [D loss: 0.683629, acc.: 55.47%] [G loss: 0.727099]
8/8 [==============================] - 0s 4ms/step
2139 [D loss: 0.686290, acc.: 53.12%] [G loss: 0.714968]
8/8 [==============================] - 0s 4ms/step
2140 [D loss: 0.689978, acc.: 47.66%] [G loss: 0.733667]
8/8 [==============================] - 0s 4ms/step
2141 [D loss: 0.684418, acc.: 53.71%] [G loss: 0.746266]
8/8 [==============================] - 0s 4ms/step
2142 [D loss: 0.682714, acc.: 56.84%] [G loss: 0.750000]
8/8 [==============================] - 0s 4ms/step
2143 [D loss: 0.687802, acc.: 53.91%] [G loss: 0.744844]
8/8 [==============================] - 0s 4ms/step
2144 [D loss: 0.689601, acc.: 49.80%] [G loss: 0.746158]
8/8 [==============================] - 0s 4ms/step
2145 [D loss: 0.688634, acc.: 51.56%] [G loss: 0.753978]
8/8 [==============================] - 0s 4ms/step
2146 [D loss: 0.689379, acc.: 54.69%] [G loss: 0.742116]
8/8 [==============================] - 0s 4ms/step
2147 [D loss: 0.680655, acc.: 54.30%] [G loss: 0.756144]
8/8 [==============================] - 0s 5ms/step
2148 [D loss: 0.690440, acc.: 53.32%] [G loss: 0.743077]
8/8 [==============================] - 0s 4ms/step
2149 [D loss: 0.686306, acc.: 54.10%] [G loss: 0.744231]
8/8 [==============================] - 0s 4ms/step
2150 [D loss: 0.686513, acc.: 55.66%] [G loss: 0.749559]
1/1 [==============================] - 0s 24ms/step
8/8 [==============================] - 0s 4ms/step
2151 [D loss: 0.683353, acc.: 57.03%] [G loss: 0.752089]
8/8 [==============================] - 0s 4ms/step
2152 [D loss: 0.678557, acc.: 54.69%] [G loss: 0.764263]
8/8 [==============================] - 0s 4ms/step
2153 [D loss: 0.694338, acc.: 56.45%] [G loss: 0.735543]
8/8 [==============================] - 0s 4ms/step
2154 [D loss: 0.686395, acc.: 52.93%] [G loss: 0.732864]
8/8 [==============================] - 0s 4ms/step
2155 [D loss: 0.687658, acc.: 52.34%] [G loss: 0.729069]
8/8 [==============================] - 0s 4ms/step
2156 [D loss: 0.696866, acc.: 49.80%] [G loss: 0.716827]
8/8 [==============================] - 0s 4ms/step
2157 [D loss: 0.700986, acc.: 47.85%] [G loss: 0.728832]
8/8 [==============================] - 0s 4ms/step
2158 [D loss: 0.695902, acc.: 47.85%] [G loss: 0.719129]
8/8 [==============================] - 0s 4ms/step
2159 [D loss: 0.691711, acc.: 49.80%] [G loss: 0.728272]
8/8 [==============================] - 0s 4ms/step
2160 [D loss: 0.687591, acc.: 52.54%] [G loss: 0.739194]
8/8 [==============================] - 0s 4ms/step
2161 [D loss: 0.679920, acc.: 55.66%] [G loss: 0.737691]
8/8 [==============================] - 0s 4ms/step
2162 [D loss: 0.688239, acc.: 52.34%] [G loss: 0.750204]
8/8 [==============================] - 0s 4ms/step
2163 [D loss: 0.676619, acc.: 57.03%] [G loss: 0.746406]
8/8 [==============================] - 0s 4ms/step
2164 [D loss: 0.685269, acc.: 51.17%] [G loss: 0.755066]
8/8 [==============================] - 0s 4ms/step
2165 [D loss: 0.676103, acc.: 59.96%] [G loss: 0.744642]
8/8 [==============================] - 0s 4ms/step
2166 [D loss: 0.679113, acc.: 53.71%] [G loss: 0.748510]
8/8 [==============================] - 0s 4ms/step
2167 [D loss: 0.681785, acc.: 56.64%] [G loss: 0.738354]
8/8 [==============================] - 0s 4ms/step
2168 [D loss: 0.691427, acc.: 51.56%] [G loss: 0.745430]
8/8 [==============================] - 0s 4ms/step
2169 [D loss: 0.691276, acc.: 51.76%] [G loss: 0.731456]
8/8 [==============================] - 0s 4ms/step
2170 [D loss: 0.699717, acc.: 47.07%] [G loss: 0.721750]
8/8 [==============================] - 0s 4ms/step
2171 [D loss: 0.691434, acc.: 52.93%] [G loss: 0.733981]
8/8 [==============================] - 0s 4ms/step
2172 [D loss: 0.687758, acc.: 52.34%] [G loss: 0.722271]
8/8 [==============================] - 0s 4ms/step
2173 [D loss: 0.689308, acc.: 55.47%] [G loss: 0.733942]
8/8 [==============================] - 0s 4ms/step
2174 [D loss: 0.688627, acc.: 54.30%] [G loss: 0.737936]
8/8 [==============================] - 0s 4ms/step
2175 [D loss: 0.700191, acc.: 51.37%] [G loss: 0.756158]
8/8 [==============================] - 0s 4ms/step
2176 [D loss: 0.685501, acc.: 56.84%] [G loss: 0.762102]
8/8 [==============================] - 0s 4ms/step
2177 [D loss: 0.683710, acc.: 55.27%] [G loss: 0.747156]
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2178 [D loss: 0.686405, acc.: 54.10%] [G loss: 0.745930]
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2179 [D loss: 0.682077, acc.: 54.69%] [G loss: 0.739304]
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2180 [D loss: 0.686018, acc.: 52.54%] [G loss: 0.763358]
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2181 [D loss: 0.677457, acc.: 57.23%] [G loss: 0.738522]
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2182 [D loss: 0.669122, acc.: 58.98%] [G loss: 0.754742]
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2183 [D loss: 0.676463, acc.: 57.42%] [G loss: 0.738000]
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2184 [D loss: 0.683240, acc.: 53.52%] [G loss: 0.740501]
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2185 [D loss: 0.683967, acc.: 55.47%] [G loss: 0.744258]
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2186 [D loss: 0.678690, acc.: 57.42%] [G loss: 0.742227]
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2187 [D loss: 0.687046, acc.: 54.10%] [G loss: 0.735125]
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2188 [D loss: 0.684598, acc.: 57.81%] [G loss: 0.719896]
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2189 [D loss: 0.689408, acc.: 54.30%] [G loss: 0.732342]
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2190 [D loss: 0.693252, acc.: 50.39%] [G loss: 0.721470]
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2191 [D loss: 0.696161, acc.: 50.78%] [G loss: 0.724698]
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2192 [D loss: 0.689373, acc.: 51.37%] [G loss: 0.743183]
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2193 [D loss: 0.690619, acc.: 51.37%] [G loss: 0.756115]
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2194 [D loss: 0.675498, acc.: 58.59%] [G loss: 0.748289]
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2195 [D loss: 0.688857, acc.: 50.39%] [G loss: 0.756043]
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2196 [D loss: 0.676949, acc.: 57.03%] [G loss: 0.768683]
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2197 [D loss: 0.676970, acc.: 59.96%] [G loss: 0.748801]
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2198 [D loss: 0.692407, acc.: 52.54%] [G loss: 0.758792]
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2199 [D loss: 0.697123, acc.: 50.98%] [G loss: 0.738464]
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2200 [D loss: 0.703057, acc.: 49.80%] [G loss: 0.730194]
1/1 [==============================] - 0s 25ms/step
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2201 [D loss: 0.690791, acc.: 51.95%] [G loss: 0.732626]
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2202 [D loss: 0.697750, acc.: 50.39%] [G loss: 0.745111]
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2203 [D loss: 0.696983, acc.: 51.37%] [G loss: 0.741919]
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2204 [D loss: 0.687802, acc.: 53.91%] [G loss: 0.756156]
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2205 [D loss: 0.685459, acc.: 55.86%] [G loss: 0.762294]
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2206 [D loss: 0.685908, acc.: 55.66%] [G loss: 0.761264]
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2207 [D loss: 0.686226, acc.: 57.03%] [G loss: 0.745753]
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2208 [D loss: 0.680637, acc.: 56.25%] [G loss: 0.739360]
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2209 [D loss: 0.683657, acc.: 56.25%] [G loss: 0.738843]
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2210 [D loss: 0.685659, acc.: 53.71%] [G loss: 0.735212]
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2211 [D loss: 0.685211, acc.: 55.27%] [G loss: 0.726937]
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2212 [D loss: 0.688018, acc.: 50.59%] [G loss: 0.741694]
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2213 [D loss: 0.686014, acc.: 53.71%] [G loss: 0.756990]
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2214 [D loss: 0.688223, acc.: 51.37%] [G loss: 0.755281]
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2215 [D loss: 0.689020, acc.: 51.37%] [G loss: 0.759070]
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2216 [D loss: 0.687716, acc.: 53.12%] [G loss: 0.747687]
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2217 [D loss: 0.682025, acc.: 54.88%] [G loss: 0.745163]
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2218 [D loss: 0.681944, acc.: 56.25%] [G loss: 0.744916]
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2219 [D loss: 0.685200, acc.: 54.10%] [G loss: 0.733428]
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2220 [D loss: 0.687825, acc.: 51.95%] [G loss: 0.739489]
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2221 [D loss: 0.688470, acc.: 51.76%] [G loss: 0.737267]
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2222 [D loss: 0.685519, acc.: 54.30%] [G loss: 0.757516]
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2223 [D loss: 0.689142, acc.: 53.32%] [G loss: 0.776503]
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2224 [D loss: 0.695003, acc.: 51.95%] [G loss: 0.777696]
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2225 [D loss: 0.681434, acc.: 56.25%] [G loss: 0.764909]
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2226 [D loss: 0.688547, acc.: 55.66%] [G loss: 0.764697]
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2227 [D loss: 0.692226, acc.: 50.98%] [G loss: 0.761241]
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2228 [D loss: 0.681199, acc.: 58.79%] [G loss: 0.750996]
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2229 [D loss: 0.685130, acc.: 55.47%] [G loss: 0.722186]
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2230 [D loss: 0.687640, acc.: 56.05%] [G loss: 0.735586]
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2231 [D loss: 0.679181, acc.: 57.62%] [G loss: 0.732451]
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2232 [D loss: 0.688064, acc.: 55.08%] [G loss: 0.758158]
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2233 [D loss: 0.679395, acc.: 57.03%] [G loss: 0.762090]
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2234 [D loss: 0.678147, acc.: 59.18%] [G loss: 0.759668]
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2235 [D loss: 0.685738, acc.: 55.86%] [G loss: 0.762767]
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2236 [D loss: 0.687136, acc.: 52.93%] [G loss: 0.739154]
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2237 [D loss: 0.692028, acc.: 54.49%] [G loss: 0.727710]
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2238 [D loss: 0.690044, acc.: 52.93%] [G loss: 0.718101]
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2239 [D loss: 0.684374, acc.: 56.05%] [G loss: 0.712755]
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2240 [D loss: 0.699458, acc.: 50.20%] [G loss: 0.710876]
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2241 [D loss: 0.692946, acc.: 54.10%] [G loss: 0.726299]
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2242 [D loss: 0.690167, acc.: 55.27%] [G loss: 0.758200]
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2243 [D loss: 0.688881, acc.: 51.95%] [G loss: 0.769765]
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2244 [D loss: 0.675717, acc.: 59.18%] [G loss: 0.784294]
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2245 [D loss: 0.685009, acc.: 55.47%] [G loss: 0.754924]
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2246 [D loss: 0.691235, acc.: 54.49%] [G loss: 0.750884]
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2247 [D loss: 0.700358, acc.: 48.24%] [G loss: 0.732974]
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2248 [D loss: 0.692314, acc.: 52.34%] [G loss: 0.717386]
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2249 [D loss: 0.700942, acc.: 50.78%] [G loss: 0.714821]
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2250 [D loss: 0.694956, acc.: 48.63%] [G loss: 0.721269]
1/1 [==============================] - 0s 23ms/step
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2251 [D loss: 0.689394, acc.: 55.66%] [G loss: 0.736389]
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2252 [D loss: 0.677301, acc.: 55.86%] [G loss: 0.779148]
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2253 [D loss: 0.674914, acc.: 57.62%] [G loss: 0.778586]
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2254 [D loss: 0.683549, acc.: 57.23%] [G loss: 0.785277]
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2255 [D loss: 0.680934, acc.: 59.18%] [G loss: 0.764917]
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2256 [D loss: 0.686970, acc.: 54.69%] [G loss: 0.753579]
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2257 [D loss: 0.687321, acc.: 53.32%] [G loss: 0.740889]
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2258 [D loss: 0.696669, acc.: 52.54%] [G loss: 0.734120]
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2259 [D loss: 0.690678, acc.: 50.98%] [G loss: 0.729866]
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2260 [D loss: 0.689473, acc.: 56.45%] [G loss: 0.725813]
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2261 [D loss: 0.699964, acc.: 50.20%] [G loss: 0.747839]
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2262 [D loss: 0.685353, acc.: 56.05%] [G loss: 0.761474]
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2263 [D loss: 0.693280, acc.: 50.20%] [G loss: 0.764347]
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2264 [D loss: 0.695434, acc.: 54.69%] [G loss: 0.758321]
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2265 [D loss: 0.684000, acc.: 56.45%] [G loss: 0.745325]
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2266 [D loss: 0.697018, acc.: 54.10%] [G loss: 0.741588]
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2267 [D loss: 0.683814, acc.: 57.23%] [G loss: 0.742719]
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2268 [D loss: 0.691665, acc.: 55.66%] [G loss: 0.741646]
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2269 [D loss: 0.674458, acc.: 57.81%] [G loss: 0.718298]
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2270 [D loss: 0.684940, acc.: 56.25%] [G loss: 0.715552]
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2271 [D loss: 0.689898, acc.: 54.69%] [G loss: 0.725733]
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2272 [D loss: 0.701198, acc.: 51.37%] [G loss: 0.725987]
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2273 [D loss: 0.688559, acc.: 54.69%] [G loss: 0.735620]
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2274 [D loss: 0.693832, acc.: 51.56%] [G loss: 0.748424]
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2275 [D loss: 0.683654, acc.: 57.03%] [G loss: 0.791456]
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2276 [D loss: 0.678839, acc.: 57.03%] [G loss: 0.804486]
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2277 [D loss: 0.686360, acc.: 54.30%] [G loss: 0.801584]
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2278 [D loss: 0.686226, acc.: 55.66%] [G loss: 0.775842]
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2279 [D loss: 0.685297, acc.: 52.34%] [G loss: 0.752236]
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2280 [D loss: 0.690658, acc.: 52.15%] [G loss: 0.751529]
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2281 [D loss: 0.688952, acc.: 51.76%] [G loss: 0.736226]
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2282 [D loss: 0.694765, acc.: 50.78%] [G loss: 0.720473]
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2283 [D loss: 0.700659, acc.: 50.59%] [G loss: 0.710768]
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2284 [D loss: 0.692740, acc.: 52.54%] [G loss: 0.706658]
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2285 [D loss: 0.687994, acc.: 52.34%] [G loss: 0.729492]
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2286 [D loss: 0.688333, acc.: 53.52%] [G loss: 0.748922]
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2287 [D loss: 0.690507, acc.: 53.12%] [G loss: 0.765262]
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2288 [D loss: 0.680381, acc.: 56.25%] [G loss: 0.766504]
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2289 [D loss: 0.681997, acc.: 60.35%] [G loss: 0.750972]
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2290 [D loss: 0.681103, acc.: 54.69%] [G loss: 0.734440]
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2291 [D loss: 0.685275, acc.: 52.93%] [G loss: 0.731083]
8/8 [==============================] - 0s 4ms/step
2292 [D loss: 0.701883, acc.: 49.41%] [G loss: 0.728499]
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2293 [D loss: 0.692593, acc.: 50.98%] [G loss: 0.737712]
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2294 [D loss: 0.704174, acc.: 47.66%] [G loss: 0.733753]
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2295 [D loss: 0.698866, acc.: 51.76%] [G loss: 0.748893]
8/8 [==============================] - 0s 4ms/step
2296 [D loss: 0.704809, acc.: 49.22%] [G loss: 0.754961]
8/8 [==============================] - 0s 4ms/step
2297 [D loss: 0.687326, acc.: 52.34%] [G loss: 0.757833]
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2298 [D loss: 0.688756, acc.: 54.10%] [G loss: 0.763206]
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2299 [D loss: 0.685065, acc.: 56.05%] [G loss: 0.766796]
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2300 [D loss: 0.682019, acc.: 56.45%] [G loss: 0.759470]
1/1 [==============================] - 0s 24ms/step
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2301 [D loss: 0.674662, acc.: 58.01%] [G loss: 0.761898]
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2302 [D loss: 0.675523, acc.: 59.57%] [G loss: 0.746087]
8/8 [==============================] - 0s 4ms/step
2303 [D loss: 0.672409, acc.: 57.62%] [G loss: 0.757558]
8/8 [==============================] - 0s 4ms/step
2304 [D loss: 0.685449, acc.: 55.27%] [G loss: 0.746616]
8/8 [==============================] - 0s 4ms/step
2305 [D loss: 0.674692, acc.: 58.79%] [G loss: 0.743577]
8/8 [==============================] - 0s 4ms/step
2306 [D loss: 0.684510, acc.: 54.10%] [G loss: 0.734573]
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2307 [D loss: 0.688607, acc.: 52.54%] [G loss: 0.730204]
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2308 [D loss: 0.698529, acc.: 50.39%] [G loss: 0.732817]
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2309 [D loss: 0.691316, acc.: 51.56%] [G loss: 0.748845]
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2310 [D loss: 0.686479, acc.: 51.76%] [G loss: 0.739680]
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2311 [D loss: 0.695579, acc.: 51.76%] [G loss: 0.738872]
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2312 [D loss: 0.696613, acc.: 50.78%] [G loss: 0.733605]
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2313 [D loss: 0.689794, acc.: 50.78%] [G loss: 0.748450]
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2314 [D loss: 0.676780, acc.: 57.42%] [G loss: 0.740605]
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2315 [D loss: 0.679798, acc.: 55.47%] [G loss: 0.729166]
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2316 [D loss: 0.686765, acc.: 57.42%] [G loss: 0.726401]
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2317 [D loss: 0.687611, acc.: 53.71%] [G loss: 0.730009]
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2318 [D loss: 0.693790, acc.: 50.98%] [G loss: 0.741001]
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2319 [D loss: 0.681892, acc.: 55.27%] [G loss: 0.766931]
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2320 [D loss: 0.690272, acc.: 52.93%] [G loss: 0.767396]
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2321 [D loss: 0.690449, acc.: 54.69%] [G loss: 0.770495]
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2322 [D loss: 0.700275, acc.: 53.12%] [G loss: 0.760072]
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2323 [D loss: 0.687957, acc.: 54.69%] [G loss: 0.730213]
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2324 [D loss: 0.693768, acc.: 51.37%] [G loss: 0.730192]
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2325 [D loss: 0.686058, acc.: 51.17%] [G loss: 0.715978]
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2326 [D loss: 0.701661, acc.: 49.41%] [G loss: 0.723840]
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2327 [D loss: 0.684594, acc.: 55.86%] [G loss: 0.711110]
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2328 [D loss: 0.689226, acc.: 54.69%] [G loss: 0.719665]
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2329 [D loss: 0.689845, acc.: 53.71%] [G loss: 0.752773]
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2330 [D loss: 0.696352, acc.: 53.32%] [G loss: 0.754568]
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2331 [D loss: 0.680297, acc.: 56.84%] [G loss: 0.761704]
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2332 [D loss: 0.687900, acc.: 54.30%] [G loss: 0.765341]
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2333 [D loss: 0.686530, acc.: 52.54%] [G loss: 0.757485]
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2334 [D loss: 0.688531, acc.: 53.12%] [G loss: 0.734346]
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2335 [D loss: 0.686652, acc.: 54.69%] [G loss: 0.727290]
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2336 [D loss: 0.694732, acc.: 50.59%] [G loss: 0.717593]
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2337 [D loss: 0.684911, acc.: 54.69%] [G loss: 0.718117]
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2338 [D loss: 0.696718, acc.: 49.80%] [G loss: 0.710170]
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2339 [D loss: 0.694516, acc.: 49.61%] [G loss: 0.733097]
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2340 [D loss: 0.693398, acc.: 52.54%] [G loss: 0.740074]
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2341 [D loss: 0.677435, acc.: 57.42%] [G loss: 0.745591]
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2342 [D loss: 0.681768, acc.: 55.66%] [G loss: 0.780709]
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2343 [D loss: 0.684219, acc.: 55.27%] [G loss: 0.771399]
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2344 [D loss: 0.678864, acc.: 58.01%] [G loss: 0.764612]
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2345 [D loss: 0.690186, acc.: 53.52%] [G loss: 0.753695]
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2346 [D loss: 0.693216, acc.: 52.93%] [G loss: 0.736326]
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2347 [D loss: 0.688947, acc.: 52.34%] [G loss: 0.724012]
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2348 [D loss: 0.694086, acc.: 53.12%] [G loss: 0.721539]
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2349 [D loss: 0.698514, acc.: 49.61%] [G loss: 0.709969]
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2350 [D loss: 0.697228, acc.: 50.20%] [G loss: 0.723579]
1/1 [==============================] - 0s 23ms/step
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2351 [D loss: 0.686491, acc.: 54.88%] [G loss: 0.742048]
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2352 [D loss: 0.684505, acc.: 58.98%] [G loss: 0.756818]
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2353 [D loss: 0.680312, acc.: 56.64%] [G loss: 0.760090]
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2354 [D loss: 0.685850, acc.: 54.49%] [G loss: 0.765196]
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2355 [D loss: 0.685522, acc.: 54.69%] [G loss: 0.770324]
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2356 [D loss: 0.689970, acc.: 52.93%] [G loss: 0.749498]
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2357 [D loss: 0.686445, acc.: 53.12%] [G loss: 0.738889]
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2358 [D loss: 0.687922, acc.: 52.54%] [G loss: 0.730674]
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2359 [D loss: 0.679081, acc.: 59.18%] [G loss: 0.740676]
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2360 [D loss: 0.690946, acc.: 53.32%] [G loss: 0.723600]
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2361 [D loss: 0.685123, acc.: 52.73%] [G loss: 0.762682]
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2362 [D loss: 0.680885, acc.: 55.27%] [G loss: 0.766879]
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2363 [D loss: 0.676809, acc.: 54.10%] [G loss: 0.772618]
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2364 [D loss: 0.679757, acc.: 58.98%] [G loss: 0.776983]
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2365 [D loss: 0.679390, acc.: 53.91%] [G loss: 0.753678]
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2366 [D loss: 0.669803, acc.: 58.79%] [G loss: 0.755268]
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2367 [D loss: 0.685493, acc.: 51.95%] [G loss: 0.744129]
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2368 [D loss: 0.677131, acc.: 53.32%] [G loss: 0.727241]
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2369 [D loss: 0.692790, acc.: 50.59%] [G loss: 0.709942]
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2370 [D loss: 0.702464, acc.: 48.83%] [G loss: 0.724539]
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2371 [D loss: 0.689050, acc.: 51.56%] [G loss: 0.748748]
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2372 [D loss: 0.690452, acc.: 54.30%] [G loss: 0.755556]
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2373 [D loss: 0.694118, acc.: 53.91%] [G loss: 0.775869]
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2374 [D loss: 0.684839, acc.: 51.37%] [G loss: 0.773409]
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2375 [D loss: 0.692423, acc.: 50.00%] [G loss: 0.760958]
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2376 [D loss: 0.684851, acc.: 57.62%] [G loss: 0.750537]
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2377 [D loss: 0.672758, acc.: 59.18%] [G loss: 0.740882]
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2378 [D loss: 0.686240, acc.: 55.86%] [G loss: 0.732875]
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2379 [D loss: 0.685086, acc.: 54.10%] [G loss: 0.702095]
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2380 [D loss: 0.679223, acc.: 57.81%] [G loss: 0.729754]
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2381 [D loss: 0.676385, acc.: 57.81%] [G loss: 0.723025]
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2382 [D loss: 0.698034, acc.: 48.63%] [G loss: 0.722660]
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2383 [D loss: 0.696729, acc.: 53.91%] [G loss: 0.725128]
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2384 [D loss: 0.698845, acc.: 50.78%] [G loss: 0.734745]
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2385 [D loss: 0.695969, acc.: 50.98%] [G loss: 0.733253]
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2386 [D loss: 0.684208, acc.: 57.42%] [G loss: 0.746501]
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2387 [D loss: 0.685674, acc.: 54.69%] [G loss: 0.733730]
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2388 [D loss: 0.689964, acc.: 54.69%] [G loss: 0.741831]
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2389 [D loss: 0.698078, acc.: 49.41%] [G loss: 0.741676]
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2390 [D loss: 0.686610, acc.: 53.12%] [G loss: 0.744408]
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2391 [D loss: 0.682376, acc.: 54.10%] [G loss: 0.746776]
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2392 [D loss: 0.674663, acc.: 58.98%] [G loss: 0.767366]
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2393 [D loss: 0.682261, acc.: 52.93%] [G loss: 0.745865]
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2394 [D loss: 0.680511, acc.: 53.52%] [G loss: 0.753452]
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2395 [D loss: 0.681983, acc.: 55.27%] [G loss: 0.760418]
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2396 [D loss: 0.692334, acc.: 49.02%] [G loss: 0.761330]
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2397 [D loss: 0.691694, acc.: 50.78%] [G loss: 0.738941]
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2398 [D loss: 0.684310, acc.: 53.32%] [G loss: 0.728858]
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2399 [D loss: 0.686824, acc.: 51.76%] [G loss: 0.734415]
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2400 [D loss: 0.678036, acc.: 53.52%] [G loss: 0.739327]
1/1 [==============================] - 0s 24ms/step
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2401 [D loss: 0.695872, acc.: 50.78%] [G loss: 0.724254]
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2402 [D loss: 0.699263, acc.: 49.41%] [G loss: 0.726543]
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2403 [D loss: 0.696910, acc.: 50.98%] [G loss: 0.741315]
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2404 [D loss: 0.698274, acc.: 50.78%] [G loss: 0.727846]
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2405 [D loss: 0.702304, acc.: 47.27%] [G loss: 0.751933]
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2406 [D loss: 0.694391, acc.: 51.17%] [G loss: 0.747191]
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2407 [D loss: 0.691753, acc.: 55.08%] [G loss: 0.762798]
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2408 [D loss: 0.692932, acc.: 50.78%] [G loss: 0.753929]
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2409 [D loss: 0.682079, acc.: 56.25%] [G loss: 0.764277]
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2410 [D loss: 0.674872, acc.: 60.74%] [G loss: 0.756761]
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2411 [D loss: 0.673213, acc.: 60.55%] [G loss: 0.770841]
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2412 [D loss: 0.671858, acc.: 57.62%] [G loss: 0.755387]
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2413 [D loss: 0.686487, acc.: 54.30%] [G loss: 0.750579]
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2414 [D loss: 0.695508, acc.: 54.30%] [G loss: 0.735320]
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2415 [D loss: 0.694511, acc.: 52.54%] [G loss: 0.750957]
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2416 [D loss: 0.693764, acc.: 50.00%] [G loss: 0.747330]
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2417 [D loss: 0.691397, acc.: 52.73%] [G loss: 0.751629]
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2418 [D loss: 0.697863, acc.: 51.56%] [G loss: 0.776672]
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2419 [D loss: 0.697134, acc.: 48.63%] [G loss: 0.767917]
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2420 [D loss: 0.686575, acc.: 55.27%] [G loss: 0.765694]
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2421 [D loss: 0.677209, acc.: 58.79%] [G loss: 0.752323]
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2422 [D loss: 0.676198, acc.: 55.08%] [G loss: 0.721868]
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2423 [D loss: 0.695446, acc.: 51.76%] [G loss: 0.729702]
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2424 [D loss: 0.692454, acc.: 52.34%] [G loss: 0.720744]
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2425 [D loss: 0.676716, acc.: 58.79%] [G loss: 0.749185]
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2426 [D loss: 0.683694, acc.: 54.10%] [G loss: 0.765747]
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2427 [D loss: 0.697045, acc.: 50.00%] [G loss: 0.759694]
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2428 [D loss: 0.684307, acc.: 55.66%] [G loss: 0.752558]
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2429 [D loss: 0.695930, acc.: 49.41%] [G loss: 0.740018]
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2430 [D loss: 0.693479, acc.: 51.17%] [G loss: 0.750728]
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2431 [D loss: 0.688831, acc.: 51.76%] [G loss: 0.737418]
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2432 [D loss: 0.684816, acc.: 52.73%] [G loss: 0.733944]
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2433 [D loss: 0.683018, acc.: 55.08%] [G loss: 0.733787]
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2434 [D loss: 0.688077, acc.: 50.59%] [G loss: 0.739958]
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2435 [D loss: 0.686402, acc.: 53.91%] [G loss: 0.755143]
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2436 [D loss: 0.678066, acc.: 58.20%] [G loss: 0.776231]
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2437 [D loss: 0.679894, acc.: 55.08%] [G loss: 0.772354]
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2438 [D loss: 0.680064, acc.: 55.66%] [G loss: 0.796863]
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2439 [D loss: 0.674714, acc.: 63.87%] [G loss: 0.800767]
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2440 [D loss: 0.679832, acc.: 54.88%] [G loss: 0.766773]
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2441 [D loss: 0.674439, acc.: 54.30%] [G loss: 0.747827]
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2442 [D loss: 0.675985, acc.: 56.25%] [G loss: 0.716470]
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2443 [D loss: 0.699922, acc.: 46.68%] [G loss: 0.701752]
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2444 [D loss: 0.706154, acc.: 50.00%] [G loss: 0.697158]
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2445 [D loss: 0.700157, acc.: 49.41%] [G loss: 0.690892]
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2446 [D loss: 0.709625, acc.: 48.63%] [G loss: 0.734405]
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2447 [D loss: 0.694216, acc.: 50.59%] [G loss: 0.754881]
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2448 [D loss: 0.702130, acc.: 50.00%] [G loss: 0.763833]
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2449 [D loss: 0.693389, acc.: 50.59%] [G loss: 0.762625]
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2450 [D loss: 0.690112, acc.: 55.08%] [G loss: 0.754122]
1/1 [==============================] - 0s 25ms/step
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2451 [D loss: 0.689204, acc.: 56.25%] [G loss: 0.747569]
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2452 [D loss: 0.687309, acc.: 51.56%] [G loss: 0.741416]
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2453 [D loss: 0.685471, acc.: 54.49%] [G loss: 0.754704]
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2454 [D loss: 0.677844, acc.: 58.59%] [G loss: 0.750283]
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2455 [D loss: 0.684182, acc.: 56.84%] [G loss: 0.738512]
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2456 [D loss: 0.679630, acc.: 56.64%] [G loss: 0.746536]
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2457 [D loss: 0.685586, acc.: 52.54%] [G loss: 0.748993]
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2458 [D loss: 0.681799, acc.: 54.30%] [G loss: 0.766225]
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2459 [D loss: 0.680194, acc.: 52.73%] [G loss: 0.768930]
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2460 [D loss: 0.695709, acc.: 49.22%] [G loss: 0.753385]
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2461 [D loss: 0.691971, acc.: 52.54%] [G loss: 0.762421]
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2462 [D loss: 0.688425, acc.: 54.69%] [G loss: 0.746338]
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2463 [D loss: 0.690646, acc.: 50.98%] [G loss: 0.734068]
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2464 [D loss: 0.686981, acc.: 51.37%] [G loss: 0.733278]
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2465 [D loss: 0.679881, acc.: 55.86%] [G loss: 0.726445]
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2466 [D loss: 0.674432, acc.: 57.03%] [G loss: 0.748352]
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2467 [D loss: 0.684669, acc.: 57.42%] [G loss: 0.733992]
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2468 [D loss: 0.674646, acc.: 58.40%] [G loss: 0.767892]
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2469 [D loss: 0.685727, acc.: 56.45%] [G loss: 0.779321]
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2470 [D loss: 0.687757, acc.: 55.66%] [G loss: 0.759916]
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2471 [D loss: 0.690247, acc.: 53.71%] [G loss: 0.743174]
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2472 [D loss: 0.696213, acc.: 49.41%] [G loss: 0.724330]
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2473 [D loss: 0.687309, acc.: 52.73%] [G loss: 0.724616]
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2474 [D loss: 0.708529, acc.: 49.41%] [G loss: 0.711015]
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2475 [D loss: 0.707578, acc.: 46.68%] [G loss: 0.708161]
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2476 [D loss: 0.694588, acc.: 49.02%] [G loss: 0.735863]
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2477 [D loss: 0.694957, acc.: 52.93%] [G loss: 0.758330]
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2478 [D loss: 0.687348, acc.: 54.88%] [G loss: 0.770762]
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2479 [D loss: 0.682739, acc.: 56.84%] [G loss: 0.768423]
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2480 [D loss: 0.683309, acc.: 58.40%] [G loss: 0.770688]
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2481 [D loss: 0.678842, acc.: 58.59%] [G loss: 0.770578]
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2482 [D loss: 0.681840, acc.: 55.66%] [G loss: 0.755938]
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2483 [D loss: 0.678936, acc.: 58.59%] [G loss: 0.748092]
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2484 [D loss: 0.677538, acc.: 57.03%] [G loss: 0.723810]
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2485 [D loss: 0.682047, acc.: 55.47%] [G loss: 0.711368]
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2486 [D loss: 0.699897, acc.: 49.41%] [G loss: 0.712237]
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2487 [D loss: 0.690095, acc.: 51.76%] [G loss: 0.713105]
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2488 [D loss: 0.693089, acc.: 50.78%] [G loss: 0.737111]
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2489 [D loss: 0.693776, acc.: 51.56%] [G loss: 0.768210]
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2490 [D loss: 0.696286, acc.: 50.00%] [G loss: 0.771443]
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2491 [D loss: 0.702580, acc.: 50.00%] [G loss: 0.771903]
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2492 [D loss: 0.706368, acc.: 49.22%] [G loss: 0.748841]
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2493 [D loss: 0.692932, acc.: 51.37%] [G loss: 0.748551]
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2494 [D loss: 0.684596, acc.: 55.86%] [G loss: 0.742328]
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2495 [D loss: 0.686481, acc.: 53.52%] [G loss: 0.736253]
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2496 [D loss: 0.698016, acc.: 48.83%] [G loss: 0.727748]
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2497 [D loss: 0.686364, acc.: 55.47%] [G loss: 0.739641]
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2498 [D loss: 0.676744, acc.: 58.40%] [G loss: 0.747641]
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2499 [D loss: 0.685997, acc.: 54.30%] [G loss: 0.765984]
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2500 [D loss: 0.674235, acc.: 58.01%] [G loss: 0.762732]
1/1 [==============================] - 0s 24ms/step
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2501 [D loss: 0.691581, acc.: 52.15%] [G loss: 0.756935]
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2502 [D loss: 0.690095, acc.: 52.34%] [G loss: 0.750866]
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2503 [D loss: 0.688202, acc.: 53.12%] [G loss: 0.746340]
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2504 [D loss: 0.694069, acc.: 53.52%] [G loss: 0.730981]
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2505 [D loss: 0.692616, acc.: 50.98%] [G loss: 0.720282]
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2506 [D loss: 0.689657, acc.: 49.80%] [G loss: 0.717455]
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2507 [D loss: 0.697462, acc.: 52.34%] [G loss: 0.719329]
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2508 [D loss: 0.692006, acc.: 48.83%] [G loss: 0.734316]
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2509 [D loss: 0.695667, acc.: 51.17%] [G loss: 0.742264]
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2510 [D loss: 0.692530, acc.: 52.73%] [G loss: 0.753253]
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2511 [D loss: 0.686485, acc.: 53.52%] [G loss: 0.754414]
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2512 [D loss: 0.689525, acc.: 55.08%] [G loss: 0.759861]
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2513 [D loss: 0.691434, acc.: 53.71%] [G loss: 0.735186]
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2514 [D loss: 0.694251, acc.: 53.91%] [G loss: 0.732031]
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2515 [D loss: 0.685785, acc.: 56.64%] [G loss: 0.738819]
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2516 [D loss: 0.681691, acc.: 58.59%] [G loss: 0.740454]
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2517 [D loss: 0.686376, acc.: 55.08%] [G loss: 0.731537]
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2518 [D loss: 0.691004, acc.: 53.32%] [G loss: 0.721229]
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2519 [D loss: 0.688900, acc.: 52.73%] [G loss: 0.718225]
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2520 [D loss: 0.686623, acc.: 54.49%] [G loss: 0.732157]
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2521 [D loss: 0.693743, acc.: 51.76%] [G loss: 0.749073]
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2522 [D loss: 0.689585, acc.: 54.30%] [G loss: 0.743763]
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2523 [D loss: 0.685875, acc.: 51.95%] [G loss: 0.738737]
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2524 [D loss: 0.691800, acc.: 53.12%] [G loss: 0.747419]
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2525 [D loss: 0.693168, acc.: 47.66%] [G loss: 0.743871]
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2526 [D loss: 0.700648, acc.: 49.02%] [G loss: 0.747072]
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2527 [D loss: 0.686268, acc.: 55.08%] [G loss: 0.740712]
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2528 [D loss: 0.684861, acc.: 56.45%] [G loss: 0.735242]
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2529 [D loss: 0.692733, acc.: 49.22%] [G loss: 0.730218]
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2530 [D loss: 0.690887, acc.: 52.34%] [G loss: 0.745052]
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2531 [D loss: 0.682079, acc.: 54.10%] [G loss: 0.734249]
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2532 [D loss: 0.695355, acc.: 51.17%] [G loss: 0.765343]
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2533 [D loss: 0.684236, acc.: 54.69%] [G loss: 0.773399]
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2534 [D loss: 0.685489, acc.: 53.52%] [G loss: 0.771837]
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2535 [D loss: 0.694871, acc.: 48.83%] [G loss: 0.751810]
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2536 [D loss: 0.695460, acc.: 53.32%] [G loss: 0.760113]
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2537 [D loss: 0.684844, acc.: 55.08%] [G loss: 0.750174]
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2538 [D loss: 0.691024, acc.: 51.95%] [G loss: 0.729924]
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2539 [D loss: 0.690763, acc.: 50.59%] [G loss: 0.735633]
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2540 [D loss: 0.684192, acc.: 54.30%] [G loss: 0.736942]
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2541 [D loss: 0.688031, acc.: 53.52%] [G loss: 0.736024]
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2542 [D loss: 0.690865, acc.: 50.59%] [G loss: 0.737926]
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2543 [D loss: 0.688482, acc.: 52.54%] [G loss: 0.738928]
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2544 [D loss: 0.683422, acc.: 53.52%] [G loss: 0.745597]
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2545 [D loss: 0.683881, acc.: 55.08%] [G loss: 0.756528]
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2546 [D loss: 0.695676, acc.: 50.00%] [G loss: 0.735427]
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2547 [D loss: 0.690455, acc.: 53.91%] [G loss: 0.732089]
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2548 [D loss: 0.690362, acc.: 50.98%] [G loss: 0.734550]
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2549 [D loss: 0.694685, acc.: 52.93%] [G loss: 0.748556]
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2550 [D loss: 0.691419, acc.: 54.10%] [G loss: 0.741110]
1/1 [==============================] - 0s 23ms/step
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2551 [D loss: 0.691843, acc.: 51.37%] [G loss: 0.737815]
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2552 [D loss: 0.687195, acc.: 56.05%] [G loss: 0.729180]
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2553 [D loss: 0.689934, acc.: 50.00%] [G loss: 0.732220]
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2554 [D loss: 0.685210, acc.: 54.10%] [G loss: 0.732118]
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2555 [D loss: 0.688491, acc.: 52.34%] [G loss: 0.737948]
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2556 [D loss: 0.688951, acc.: 54.30%] [G loss: 0.741287]
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2557 [D loss: 0.683777, acc.: 53.12%] [G loss: 0.731363]
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2558 [D loss: 0.686507, acc.: 53.91%] [G loss: 0.733255]
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2559 [D loss: 0.686673, acc.: 51.56%] [G loss: 0.742062]
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2560 [D loss: 0.685580, acc.: 55.08%] [G loss: 0.739294]
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2561 [D loss: 0.700174, acc.: 50.78%] [G loss: 0.727767]
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2562 [D loss: 0.688772, acc.: 51.56%] [G loss: 0.730086]
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2563 [D loss: 0.692278, acc.: 51.76%] [G loss: 0.723085]
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2564 [D loss: 0.698084, acc.: 49.41%] [G loss: 0.721841]
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2565 [D loss: 0.702888, acc.: 49.22%] [G loss: 0.712242]
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2566 [D loss: 0.693324, acc.: 49.80%] [G loss: 0.714164]
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2567 [D loss: 0.683724, acc.: 53.71%] [G loss: 0.736946]
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2568 [D loss: 0.694470, acc.: 50.98%] [G loss: 0.736927]
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2569 [D loss: 0.687496, acc.: 55.66%] [G loss: 0.736181]
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2570 [D loss: 0.677490, acc.: 55.66%] [G loss: 0.740083]
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2571 [D loss: 0.677177, acc.: 56.64%] [G loss: 0.741670]
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2572 [D loss: 0.690017, acc.: 52.15%] [G loss: 0.724525]
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2573 [D loss: 0.695493, acc.: 51.17%] [G loss: 0.715307]
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2574 [D loss: 0.693364, acc.: 51.95%] [G loss: 0.735337]
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2575 [D loss: 0.685749, acc.: 53.32%] [G loss: 0.734879]
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2576 [D loss: 0.699535, acc.: 49.61%] [G loss: 0.735855]
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2577 [D loss: 0.695498, acc.: 51.37%] [G loss: 0.729712]
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2578 [D loss: 0.686445, acc.: 54.30%] [G loss: 0.755255]
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2579 [D loss: 0.687157, acc.: 52.73%] [G loss: 0.762436]
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2580 [D loss: 0.691035, acc.: 53.32%] [G loss: 0.756253]
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2581 [D loss: 0.679643, acc.: 57.62%] [G loss: 0.744585]
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2582 [D loss: 0.693274, acc.: 50.98%] [G loss: 0.738161]
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2583 [D loss: 0.680470, acc.: 55.27%] [G loss: 0.737007]
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2584 [D loss: 0.679360, acc.: 52.93%] [G loss: 0.732400]
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2585 [D loss: 0.691798, acc.: 50.00%] [G loss: 0.716479]
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2586 [D loss: 0.697202, acc.: 49.61%] [G loss: 0.720536]
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2587 [D loss: 0.691087, acc.: 52.34%] [G loss: 0.728595]
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2588 [D loss: 0.689885, acc.: 51.76%] [G loss: 0.746800]
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2589 [D loss: 0.688607, acc.: 52.54%] [G loss: 0.760194]
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2590 [D loss: 0.685015, acc.: 54.10%] [G loss: 0.774229]
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2591 [D loss: 0.685676, acc.: 53.52%] [G loss: 0.744041]
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2592 [D loss: 0.692890, acc.: 48.24%] [G loss: 0.741006]
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2593 [D loss: 0.679686, acc.: 57.62%] [G loss: 0.738098]
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2594 [D loss: 0.680523, acc.: 53.71%] [G loss: 0.727691]
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2595 [D loss: 0.678347, acc.: 56.64%] [G loss: 0.714296]
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2596 [D loss: 0.695578, acc.: 48.63%] [G loss: 0.708107]
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2597 [D loss: 0.692227, acc.: 51.37%] [G loss: 0.708360]
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2598 [D loss: 0.687116, acc.: 53.71%] [G loss: 0.724501]
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2599 [D loss: 0.680634, acc.: 55.27%] [G loss: 0.728657]
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2600 [D loss: 0.695851, acc.: 50.59%] [G loss: 0.737635]
1/1 [==============================] - 0s 25ms/step
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2601 [D loss: 0.686268, acc.: 53.71%] [G loss: 0.740926]
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2602 [D loss: 0.695631, acc.: 53.12%] [G loss: 0.739550]
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2603 [D loss: 0.690696, acc.: 52.34%] [G loss: 0.737154]
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2604 [D loss: 0.691791, acc.: 52.93%] [G loss: 0.732002]
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2605 [D loss: 0.689336, acc.: 51.56%] [G loss: 0.733760]
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2606 [D loss: 0.696824, acc.: 50.39%] [G loss: 0.748551]
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2607 [D loss: 0.689141, acc.: 53.52%] [G loss: 0.738684]
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2608 [D loss: 0.691209, acc.: 51.37%] [G loss: 0.724866]
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2609 [D loss: 0.686527, acc.: 53.52%] [G loss: 0.754826]
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2610 [D loss: 0.697385, acc.: 50.98%] [G loss: 0.744910]
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2611 [D loss: 0.685790, acc.: 52.93%] [G loss: 0.753585]
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2612 [D loss: 0.698045, acc.: 48.44%] [G loss: 0.748072]
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2613 [D loss: 0.690859, acc.: 51.17%] [G loss: 0.757550]
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2614 [D loss: 0.694814, acc.: 51.76%] [G loss: 0.746073]
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2615 [D loss: 0.687709, acc.: 54.49%] [G loss: 0.747442]
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2616 [D loss: 0.696711, acc.: 53.32%] [G loss: 0.733985]
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2617 [D loss: 0.691293, acc.: 51.56%] [G loss: 0.725668]
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2618 [D loss: 0.683994, acc.: 56.05%] [G loss: 0.731297]
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2619 [D loss: 0.688876, acc.: 51.56%] [G loss: 0.732065]
8/8 [==============================] - 0s 4ms/step
2620 [D loss: 0.679909, acc.: 55.86%] [G loss: 0.729179]
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2621 [D loss: 0.679495, acc.: 58.20%] [G loss: 0.741972]
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2622 [D loss: 0.678445, acc.: 56.64%] [G loss: 0.737194]
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2623 [D loss: 0.682153, acc.: 54.49%] [G loss: 0.749769]
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2624 [D loss: 0.685180, acc.: 52.34%] [G loss: 0.733587]
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2625 [D loss: 0.690860, acc.: 51.95%] [G loss: 0.734715]
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2626 [D loss: 0.701031, acc.: 49.22%] [G loss: 0.711508]
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2627 [D loss: 0.694836, acc.: 51.17%] [G loss: 0.705275]
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2628 [D loss: 0.697861, acc.: 50.59%] [G loss: 0.710935]
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2629 [D loss: 0.697524, acc.: 49.80%] [G loss: 0.721703]
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2630 [D loss: 0.693351, acc.: 48.63%] [G loss: 0.726380]
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2631 [D loss: 0.691437, acc.: 52.54%] [G loss: 0.734405]
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2632 [D loss: 0.694310, acc.: 48.83%] [G loss: 0.749402]
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2633 [D loss: 0.694858, acc.: 50.98%] [G loss: 0.752358]
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2634 [D loss: 0.700131, acc.: 50.00%] [G loss: 0.747698]
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2635 [D loss: 0.681118, acc.: 56.25%] [G loss: 0.750657]
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2636 [D loss: 0.688188, acc.: 53.91%] [G loss: 0.739931]
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2637 [D loss: 0.684619, acc.: 56.05%] [G loss: 0.754104]
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2638 [D loss: 0.692599, acc.: 53.91%] [G loss: 0.738021]
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2639 [D loss: 0.686396, acc.: 53.52%] [G loss: 0.751416]
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2640 [D loss: 0.692890, acc.: 53.12%] [G loss: 0.740818]
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2641 [D loss: 0.692779, acc.: 49.22%] [G loss: 0.732111]
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2642 [D loss: 0.692583, acc.: 52.34%] [G loss: 0.734430]
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2643 [D loss: 0.695749, acc.: 53.91%] [G loss: 0.744782]
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2644 [D loss: 0.687487, acc.: 52.15%] [G loss: 0.773430]
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2645 [D loss: 0.697798, acc.: 45.90%] [G loss: 0.747626]
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2646 [D loss: 0.697947, acc.: 45.31%] [G loss: 0.737342]
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2647 [D loss: 0.697955, acc.: 50.20%] [G loss: 0.733242]
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2648 [D loss: 0.690895, acc.: 52.54%] [G loss: 0.730921]
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2649 [D loss: 0.689146, acc.: 53.91%] [G loss: 0.726539]
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2650 [D loss: 0.691524, acc.: 49.80%] [G loss: 0.719408]
1/1 [==============================] - 0s 26ms/step
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2651 [D loss: 0.702600, acc.: 46.29%] [G loss: 0.714342]
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2652 [D loss: 0.686610, acc.: 53.12%] [G loss: 0.722644]
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2653 [D loss: 0.685334, acc.: 55.08%] [G loss: 0.743944]
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2654 [D loss: 0.686888, acc.: 52.93%] [G loss: 0.751292]
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2655 [D loss: 0.687929, acc.: 53.32%] [G loss: 0.741970]
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2656 [D loss: 0.684585, acc.: 55.27%] [G loss: 0.756655]
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2657 [D loss: 0.693353, acc.: 50.59%] [G loss: 0.744863]
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2658 [D loss: 0.687573, acc.: 51.37%] [G loss: 0.723013]
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2659 [D loss: 0.698050, acc.: 48.63%] [G loss: 0.730634]
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2660 [D loss: 0.694908, acc.: 50.00%] [G loss: 0.724493]
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2661 [D loss: 0.700637, acc.: 47.27%] [G loss: 0.727058]
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2662 [D loss: 0.692552, acc.: 48.44%] [G loss: 0.733107]
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2663 [D loss: 0.690858, acc.: 51.37%] [G loss: 0.729172]
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2664 [D loss: 0.694593, acc.: 50.78%] [G loss: 0.737882]
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2665 [D loss: 0.689203, acc.: 50.59%] [G loss: 0.730717]
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2666 [D loss: 0.680890, acc.: 55.86%] [G loss: 0.738717]
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2667 [D loss: 0.685212, acc.: 53.91%] [G loss: 0.736669]
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2668 [D loss: 0.686646, acc.: 56.45%] [G loss: 0.736419]
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2669 [D loss: 0.681449, acc.: 55.27%] [G loss: 0.738473]
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2670 [D loss: 0.684584, acc.: 56.05%] [G loss: 0.729316]
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2671 [D loss: 0.693819, acc.: 50.59%] [G loss: 0.736590]
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2672 [D loss: 0.687064, acc.: 52.54%] [G loss: 0.733071]
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2673 [D loss: 0.687775, acc.: 54.69%] [G loss: 0.716028]
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2674 [D loss: 0.698224, acc.: 48.63%] [G loss: 0.722321]
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2675 [D loss: 0.684554, acc.: 55.27%] [G loss: 0.733098]
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2676 [D loss: 0.692807, acc.: 50.98%] [G loss: 0.728102]
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2677 [D loss: 0.691676, acc.: 52.54%] [G loss: 0.721467]
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2678 [D loss: 0.697471, acc.: 49.41%] [G loss: 0.726852]
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2679 [D loss: 0.679062, acc.: 59.57%] [G loss: 0.731195]
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2680 [D loss: 0.683330, acc.: 55.86%] [G loss: 0.738796]
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2681 [D loss: 0.688842, acc.: 53.12%] [G loss: 0.743890]
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2682 [D loss: 0.690788, acc.: 54.49%] [G loss: 0.734487]
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2683 [D loss: 0.698362, acc.: 49.22%] [G loss: 0.730752]
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2684 [D loss: 0.689303, acc.: 51.37%] [G loss: 0.727352]
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2685 [D loss: 0.688326, acc.: 54.49%] [G loss: 0.712651]
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2686 [D loss: 0.695720, acc.: 48.44%] [G loss: 0.713474]
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2687 [D loss: 0.695395, acc.: 50.59%] [G loss: 0.707053]
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2688 [D loss: 0.688620, acc.: 52.15%] [G loss: 0.703567]
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2689 [D loss: 0.692902, acc.: 49.22%] [G loss: 0.724504]
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2690 [D loss: 0.692802, acc.: 52.34%] [G loss: 0.732237]
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2691 [D loss: 0.685902, acc.: 53.71%] [G loss: 0.730557]
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2692 [D loss: 0.697658, acc.: 52.73%] [G loss: 0.753365]
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2693 [D loss: 0.682612, acc.: 56.64%] [G loss: 0.753031]
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2694 [D loss: 0.676653, acc.: 57.81%] [G loss: 0.754741]
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2695 [D loss: 0.687161, acc.: 55.08%] [G loss: 0.751600]
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2696 [D loss: 0.688601, acc.: 54.69%] [G loss: 0.739027]
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2697 [D loss: 0.689417, acc.: 51.76%] [G loss: 0.730930]
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2698 [D loss: 0.694098, acc.: 53.32%] [G loss: 0.718642]
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2699 [D loss: 0.698029, acc.: 52.93%] [G loss: 0.720208]
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2700 [D loss: 0.693724, acc.: 51.76%] [G loss: 0.711652]
1/1 [==============================] - 0s 25ms/step
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2701 [D loss: 0.696024, acc.: 52.15%] [G loss: 0.720343]
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2702 [D loss: 0.695697, acc.: 49.22%] [G loss: 0.738021]
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2703 [D loss: 0.694093, acc.: 53.12%] [G loss: 0.756244]
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2704 [D loss: 0.700064, acc.: 50.20%] [G loss: 0.751848]
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2705 [D loss: 0.695046, acc.: 53.12%] [G loss: 0.763830]
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2706 [D loss: 0.693953, acc.: 54.30%] [G loss: 0.755667]
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2707 [D loss: 0.686309, acc.: 55.27%] [G loss: 0.743663]
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2708 [D loss: 0.683891, acc.: 54.88%] [G loss: 0.742981]
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2709 [D loss: 0.688771, acc.: 54.49%] [G loss: 0.727982]
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2710 [D loss: 0.686216, acc.: 53.91%] [G loss: 0.706687]
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2711 [D loss: 0.692066, acc.: 50.98%] [G loss: 0.711452]
8/8 [==============================] - 0s 4ms/step
2712 [D loss: 0.692716, acc.: 50.20%] [G loss: 0.711784]
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2713 [D loss: 0.692713, acc.: 51.76%] [G loss: 0.740677]
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2714 [D loss: 0.690540, acc.: 52.73%] [G loss: 0.755121]
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2715 [D loss: 0.688979, acc.: 54.30%] [G loss: 0.770473]
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2716 [D loss: 0.692528, acc.: 53.52%] [G loss: 0.762434]
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2717 [D loss: 0.695183, acc.: 50.00%] [G loss: 0.757690]
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2718 [D loss: 0.700370, acc.: 46.48%] [G loss: 0.737378]
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2719 [D loss: 0.699077, acc.: 49.80%] [G loss: 0.738462]
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2720 [D loss: 0.692661, acc.: 50.59%] [G loss: 0.727488]
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2721 [D loss: 0.685527, acc.: 53.52%] [G loss: 0.727208]
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2722 [D loss: 0.690859, acc.: 50.39%] [G loss: 0.709583]
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2723 [D loss: 0.687804, acc.: 51.37%] [G loss: 0.711577]
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2724 [D loss: 0.694177, acc.: 54.10%] [G loss: 0.725954]
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2725 [D loss: 0.684564, acc.: 53.52%] [G loss: 0.741958]
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2726 [D loss: 0.680639, acc.: 58.01%] [G loss: 0.757023]
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2727 [D loss: 0.679881, acc.: 56.45%] [G loss: 0.771374]
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2728 [D loss: 0.689345, acc.: 54.49%] [G loss: 0.762456]
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2729 [D loss: 0.691509, acc.: 49.22%] [G loss: 0.746037]
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2730 [D loss: 0.693266, acc.: 51.76%] [G loss: 0.746248]
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2731 [D loss: 0.696752, acc.: 49.22%] [G loss: 0.731649]
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2732 [D loss: 0.692500, acc.: 47.66%] [G loss: 0.727894]
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2733 [D loss: 0.698631, acc.: 49.61%] [G loss: 0.721371]
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2734 [D loss: 0.699917, acc.: 46.68%] [G loss: 0.732624]
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2735 [D loss: 0.698298, acc.: 51.76%] [G loss: 0.734083]
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2736 [D loss: 0.691404, acc.: 53.91%] [G loss: 0.745315]
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2737 [D loss: 0.688306, acc.: 55.66%] [G loss: 0.756169]
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2738 [D loss: 0.682146, acc.: 59.18%] [G loss: 0.744740]
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2739 [D loss: 0.689736, acc.: 55.86%] [G loss: 0.742608]
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2740 [D loss: 0.685997, acc.: 54.49%] [G loss: 0.733334]
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2741 [D loss: 0.682664, acc.: 54.88%] [G loss: 0.736340]
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2742 [D loss: 0.687934, acc.: 54.49%] [G loss: 0.726406]
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2743 [D loss: 0.687825, acc.: 54.30%] [G loss: 0.710326]
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2744 [D loss: 0.695723, acc.: 51.76%] [G loss: 0.716135]
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2745 [D loss: 0.698225, acc.: 50.78%] [G loss: 0.716289]
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2746 [D loss: 0.695337, acc.: 47.07%] [G loss: 0.726896]
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2747 [D loss: 0.684848, acc.: 58.01%] [G loss: 0.717592]
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2748 [D loss: 0.686553, acc.: 54.30%] [G loss: 0.728962]
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2749 [D loss: 0.695349, acc.: 49.41%] [G loss: 0.739266]
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2750 [D loss: 0.692328, acc.: 53.12%] [G loss: 0.743311]
1/1 [==============================] - 0s 27ms/step
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2751 [D loss: 0.685391, acc.: 51.56%] [G loss: 0.743677]
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2752 [D loss: 0.700337, acc.: 48.05%] [G loss: 0.747636]
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2753 [D loss: 0.691867, acc.: 54.49%] [G loss: 0.720214]
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2754 [D loss: 0.688889, acc.: 52.34%] [G loss: 0.729739]
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2755 [D loss: 0.683740, acc.: 53.71%] [G loss: 0.740866]
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2756 [D loss: 0.683337, acc.: 51.56%] [G loss: 0.739011]
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2757 [D loss: 0.686291, acc.: 54.69%] [G loss: 0.751442]
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2758 [D loss: 0.688327, acc.: 52.73%] [G loss: 0.737292]
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2759 [D loss: 0.695849, acc.: 48.05%] [G loss: 0.721750]
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2760 [D loss: 0.697958, acc.: 52.15%] [G loss: 0.722869]
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2761 [D loss: 0.685438, acc.: 58.01%] [G loss: 0.740411]
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2762 [D loss: 0.687915, acc.: 54.49%] [G loss: 0.747357]
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2763 [D loss: 0.695313, acc.: 52.54%] [G loss: 0.756644]
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2764 [D loss: 0.694492, acc.: 49.41%] [G loss: 0.757363]
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2765 [D loss: 0.685570, acc.: 55.08%] [G loss: 0.765906]
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2766 [D loss: 0.686843, acc.: 55.86%] [G loss: 0.771418]
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2767 [D loss: 0.682410, acc.: 55.47%] [G loss: 0.762253]
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2768 [D loss: 0.681980, acc.: 55.86%] [G loss: 0.751542]
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2769 [D loss: 0.679476, acc.: 57.81%] [G loss: 0.729482]
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2770 [D loss: 0.686359, acc.: 54.88%] [G loss: 0.716746]
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2771 [D loss: 0.690646, acc.: 55.47%] [G loss: 0.708841]
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2772 [D loss: 0.697119, acc.: 50.00%] [G loss: 0.718871]
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2773 [D loss: 0.694166, acc.: 48.83%] [G loss: 0.724820]
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2774 [D loss: 0.694121, acc.: 50.39%] [G loss: 0.727036]
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2775 [D loss: 0.687722, acc.: 52.15%] [G loss: 0.743378]
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2776 [D loss: 0.694473, acc.: 52.15%] [G loss: 0.756396]
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2777 [D loss: 0.693114, acc.: 50.20%] [G loss: 0.734181]
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2778 [D loss: 0.687917, acc.: 54.49%] [G loss: 0.738020]
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2779 [D loss: 0.692928, acc.: 49.22%] [G loss: 0.728167]
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2780 [D loss: 0.685628, acc.: 55.27%] [G loss: 0.729900]
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2781 [D loss: 0.695399, acc.: 50.78%] [G loss: 0.726308]
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2782 [D loss: 0.684961, acc.: 55.86%] [G loss: 0.722764]
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2783 [D loss: 0.690240, acc.: 52.93%] [G loss: 0.726043]
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2784 [D loss: 0.698176, acc.: 49.22%] [G loss: 0.721053]
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2785 [D loss: 0.701311, acc.: 50.20%] [G loss: 0.725152]
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2786 [D loss: 0.687964, acc.: 52.73%] [G loss: 0.733708]
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2787 [D loss: 0.688448, acc.: 53.12%] [G loss: 0.753656]
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2788 [D loss: 0.690489, acc.: 53.12%] [G loss: 0.738230]
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2789 [D loss: 0.694729, acc.: 50.59%] [G loss: 0.740284]
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2790 [D loss: 0.690634, acc.: 52.93%] [G loss: 0.737950]
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2791 [D loss: 0.690912, acc.: 51.56%] [G loss: 0.732591]
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2792 [D loss: 0.691113, acc.: 51.17%] [G loss: 0.734670]
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2793 [D loss: 0.694036, acc.: 49.80%] [G loss: 0.714883]
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2794 [D loss: 0.691581, acc.: 51.37%] [G loss: 0.724354]
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2795 [D loss: 0.694561, acc.: 51.17%] [G loss: 0.733593]
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2796 [D loss: 0.693886, acc.: 49.61%] [G loss: 0.735993]
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2797 [D loss: 0.686654, acc.: 54.88%] [G loss: 0.746428]
8/8 [==============================] - 0s 4ms/step
2798 [D loss: 0.691362, acc.: 52.93%] [G loss: 0.743769]
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2799 [D loss: 0.688534, acc.: 52.73%] [G loss: 0.734256]
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2800 [D loss: 0.696791, acc.: 51.17%] [G loss: 0.735653]
1/1 [==============================] - 0s 28ms/step
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2801 [D loss: 0.700537, acc.: 46.09%] [G loss: 0.732408]
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2802 [D loss: 0.703766, acc.: 49.41%] [G loss: 0.727233]
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2803 [D loss: 0.696469, acc.: 51.56%] [G loss: 0.714228]
8/8 [==============================] - 0s 4ms/step
2804 [D loss: 0.703533, acc.: 46.48%] [G loss: 0.720908]
8/8 [==============================] - 0s 4ms/step
2805 [D loss: 0.692989, acc.: 50.98%] [G loss: 0.732092]
8/8 [==============================] - 0s 4ms/step
2806 [D loss: 0.690400, acc.: 51.17%] [G loss: 0.748497]
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2807 [D loss: 0.675539, acc.: 60.94%] [G loss: 0.777602]
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2808 [D loss: 0.674025, acc.: 60.74%] [G loss: 0.768698]
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2809 [D loss: 0.671874, acc.: 59.38%] [G loss: 0.775430]
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2810 [D loss: 0.680283, acc.: 58.98%] [G loss: 0.758156]
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2811 [D loss: 0.671345, acc.: 59.96%] [G loss: 0.746095]
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2812 [D loss: 0.694454, acc.: 52.15%] [G loss: 0.722139]
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2813 [D loss: 0.694624, acc.: 51.17%] [G loss: 0.718241]
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2814 [D loss: 0.706400, acc.: 44.92%] [G loss: 0.714486]
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2815 [D loss: 0.693619, acc.: 49.61%] [G loss: 0.709208]
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2816 [D loss: 0.698806, acc.: 48.05%] [G loss: 0.736875]
8/8 [==============================] - 0s 4ms/step
2817 [D loss: 0.695347, acc.: 50.20%] [G loss: 0.752183]
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2818 [D loss: 0.688712, acc.: 53.32%] [G loss: 0.740670]
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2819 [D loss: 0.690373, acc.: 55.66%] [G loss: 0.751360]
8/8 [==============================] - 0s 4ms/step
2820 [D loss: 0.682022, acc.: 58.59%] [G loss: 0.739978]
8/8 [==============================] - 0s 4ms/step
2821 [D loss: 0.692160, acc.: 54.69%] [G loss: 0.742285]
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2822 [D loss: 0.691694, acc.: 54.49%] [G loss: 0.723513]
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2823 [D loss: 0.689671, acc.: 50.20%] [G loss: 0.724210]
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2824 [D loss: 0.690788, acc.: 55.66%] [G loss: 0.716849]
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2825 [D loss: 0.689458, acc.: 52.73%] [G loss: 0.722668]
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2826 [D loss: 0.689505, acc.: 55.47%] [G loss: 0.723077]
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2827 [D loss: 0.697459, acc.: 49.02%] [G loss: 0.723927]
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2828 [D loss: 0.693916, acc.: 53.12%] [G loss: 0.736124]
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2829 [D loss: 0.695248, acc.: 49.80%] [G loss: 0.738028]
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2830 [D loss: 0.695300, acc.: 48.63%] [G loss: 0.729318]
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2831 [D loss: 0.697024, acc.: 48.05%] [G loss: 0.723810]
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2832 [D loss: 0.689788, acc.: 53.52%] [G loss: 0.722381]
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2833 [D loss: 0.683512, acc.: 54.88%] [G loss: 0.733644]
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2834 [D loss: 0.695339, acc.: 47.27%] [G loss: 0.735608]
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2835 [D loss: 0.693354, acc.: 52.73%] [G loss: 0.724308]
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2836 [D loss: 0.702329, acc.: 48.83%] [G loss: 0.740370]
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2837 [D loss: 0.684454, acc.: 56.45%] [G loss: 0.742560]
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2838 [D loss: 0.690209, acc.: 49.22%] [G loss: 0.761397]
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2839 [D loss: 0.685541, acc.: 52.93%] [G loss: 0.752121]
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2840 [D loss: 0.691334, acc.: 53.71%] [G loss: 0.765750]
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2841 [D loss: 0.685810, acc.: 53.12%] [G loss: 0.765379]
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2842 [D loss: 0.680970, acc.: 57.03%] [G loss: 0.755011]
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2843 [D loss: 0.682212, acc.: 55.08%] [G loss: 0.761965]
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2844 [D loss: 0.680415, acc.: 59.18%] [G loss: 0.753152]
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2845 [D loss: 0.695284, acc.: 52.15%] [G loss: 0.739487]
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2846 [D loss: 0.680416, acc.: 57.81%] [G loss: 0.736144]
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2847 [D loss: 0.697260, acc.: 48.83%] [G loss: 0.729769]
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2848 [D loss: 0.697693, acc.: 50.98%] [G loss: 0.730368]
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2849 [D loss: 0.700735, acc.: 47.27%] [G loss: 0.712804]
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2850 [D loss: 0.697960, acc.: 49.41%] [G loss: 0.730571]
1/1 [==============================] - 0s 23ms/step
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2851 [D loss: 0.693961, acc.: 49.61%] [G loss: 0.724582]
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2852 [D loss: 0.695525, acc.: 47.07%] [G loss: 0.734053]
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2853 [D loss: 0.685860, acc.: 55.27%] [G loss: 0.734664]
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2854 [D loss: 0.689355, acc.: 50.39%] [G loss: 0.734711]
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2855 [D loss: 0.685295, acc.: 54.69%] [G loss: 0.731219]
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2856 [D loss: 0.688272, acc.: 50.59%] [G loss: 0.728891]
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2857 [D loss: 0.686243, acc.: 53.71%] [G loss: 0.734856]
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2858 [D loss: 0.696935, acc.: 50.59%] [G loss: 0.727126]
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2859 [D loss: 0.685831, acc.: 52.15%] [G loss: 0.736257]
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2860 [D loss: 0.685216, acc.: 54.30%] [G loss: 0.731049]
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2861 [D loss: 0.692745, acc.: 53.71%] [G loss: 0.733393]
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2862 [D loss: 0.687894, acc.: 53.32%] [G loss: 0.735026]
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2863 [D loss: 0.684991, acc.: 52.34%] [G loss: 0.728814]
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2864 [D loss: 0.691362, acc.: 51.95%] [G loss: 0.725882]
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2865 [D loss: 0.692984, acc.: 51.37%] [G loss: 0.716901]
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2866 [D loss: 0.691262, acc.: 51.95%] [G loss: 0.737467]
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2867 [D loss: 0.692237, acc.: 53.91%] [G loss: 0.734715]
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2868 [D loss: 0.695953, acc.: 50.20%] [G loss: 0.737676]
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2869 [D loss: 0.681834, acc.: 55.66%] [G loss: 0.745147]
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2870 [D loss: 0.691892, acc.: 53.91%] [G loss: 0.739137]
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2871 [D loss: 0.684682, acc.: 53.12%] [G loss: 0.728317]
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2872 [D loss: 0.693606, acc.: 51.76%] [G loss: 0.734264]
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2873 [D loss: 0.687895, acc.: 51.95%] [G loss: 0.742555]
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2874 [D loss: 0.696840, acc.: 50.39%] [G loss: 0.737710]
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2875 [D loss: 0.689599, acc.: 52.93%] [G loss: 0.734573]
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2876 [D loss: 0.693246, acc.: 48.83%] [G loss: 0.749901]
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2877 [D loss: 0.685125, acc.: 52.54%] [G loss: 0.753863]
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2878 [D loss: 0.694150, acc.: 51.95%] [G loss: 0.741036]
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2879 [D loss: 0.687131, acc.: 55.08%] [G loss: 0.753594]
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2880 [D loss: 0.688580, acc.: 53.71%] [G loss: 0.744688]
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2881 [D loss: 0.694998, acc.: 50.59%] [G loss: 0.736037]
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2882 [D loss: 0.683073, acc.: 55.66%] [G loss: 0.736292]
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2883 [D loss: 0.689224, acc.: 51.17%] [G loss: 0.717312]
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2884 [D loss: 0.689903, acc.: 55.27%] [G loss: 0.722058]
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2885 [D loss: 0.695215, acc.: 51.56%] [G loss: 0.704984]
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2886 [D loss: 0.691108, acc.: 52.15%] [G loss: 0.712854]
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2887 [D loss: 0.693650, acc.: 55.86%] [G loss: 0.724921]
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2888 [D loss: 0.694340, acc.: 54.30%] [G loss: 0.732641]
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2889 [D loss: 0.690378, acc.: 52.93%] [G loss: 0.741420]
8/8 [==============================] - 0s 4ms/step
2890 [D loss: 0.692296, acc.: 52.93%] [G loss: 0.740477]
8/8 [==============================] - 0s 4ms/step
2891 [D loss: 0.683263, acc.: 57.03%] [G loss: 0.740564]
8/8 [==============================] - 0s 4ms/step
2892 [D loss: 0.694457, acc.: 52.93%] [G loss: 0.729491]
8/8 [==============================] - 0s 4ms/step
2893 [D loss: 0.702096, acc.: 50.00%] [G loss: 0.725930]
8/8 [==============================] - 0s 4ms/step
2894 [D loss: 0.684071, acc.: 55.27%] [G loss: 0.716384]
8/8 [==============================] - 0s 4ms/step
2895 [D loss: 0.702504, acc.: 49.80%] [G loss: 0.703115]
8/8 [==============================] - 0s 4ms/step
2896 [D loss: 0.696536, acc.: 50.00%] [G loss: 0.700510]
8/8 [==============================] - 0s 4ms/step
2897 [D loss: 0.691580, acc.: 50.98%] [G loss: 0.711255]
8/8 [==============================] - 0s 4ms/step
2898 [D loss: 0.690284, acc.: 52.15%] [G loss: 0.724772]
8/8 [==============================] - 0s 4ms/step
2899 [D loss: 0.684424, acc.: 53.71%] [G loss: 0.735824]
8/8 [==============================] - 0s 4ms/step
2900 [D loss: 0.688740, acc.: 52.15%] [G loss: 0.738412]
1/1 [==============================] - 0s 25ms/step
8/8 [==============================] - 0s 4ms/step
2901 [D loss: 0.685989, acc.: 52.54%] [G loss: 0.750755]
8/8 [==============================] - 0s 4ms/step
2902 [D loss: 0.687003, acc.: 56.45%] [G loss: 0.747686]
8/8 [==============================] - 0s 4ms/step
2903 [D loss: 0.691718, acc.: 50.20%] [G loss: 0.739436]
8/8 [==============================] - 0s 4ms/step
2904 [D loss: 0.686730, acc.: 53.12%] [G loss: 0.744914]
8/8 [==============================] - 0s 4ms/step
2905 [D loss: 0.692779, acc.: 53.12%] [G loss: 0.754966]
8/8 [==============================] - 0s 4ms/step
2906 [D loss: 0.690811, acc.: 55.08%] [G loss: 0.738153]
8/8 [==============================] - 0s 4ms/step
2907 [D loss: 0.687586, acc.: 52.73%] [G loss: 0.726413]
8/8 [==============================] - 0s 4ms/step
2908 [D loss: 0.696462, acc.: 49.02%] [G loss: 0.725891]
8/8 [==============================] - 0s 4ms/step
2909 [D loss: 0.695177, acc.: 50.98%] [G loss: 0.720150]
8/8 [==============================] - 0s 4ms/step
2910 [D loss: 0.691902, acc.: 52.54%] [G loss: 0.731813]
8/8 [==============================] - 0s 4ms/step
2911 [D loss: 0.700257, acc.: 51.95%] [G loss: 0.734214]
8/8 [==============================] - 0s 4ms/step
2912 [D loss: 0.690977, acc.: 52.15%] [G loss: 0.719733]
8/8 [==============================] - 0s 4ms/step
2913 [D loss: 0.688306, acc.: 52.93%] [G loss: 0.741871]
8/8 [==============================] - 0s 4ms/step
2914 [D loss: 0.685342, acc.: 56.45%] [G loss: 0.742975]
8/8 [==============================] - 0s 4ms/step
2915 [D loss: 0.690580, acc.: 51.37%] [G loss: 0.748142]
8/8 [==============================] - 0s 4ms/step
2916 [D loss: 0.684191, acc.: 54.10%] [G loss: 0.755020]
8/8 [==============================] - 0s 4ms/step
2917 [D loss: 0.685375, acc.: 57.23%] [G loss: 0.744565]
8/8 [==============================] - 0s 4ms/step
2918 [D loss: 0.683602, acc.: 57.23%] [G loss: 0.741663]
8/8 [==============================] - 0s 4ms/step
2919 [D loss: 0.689012, acc.: 53.52%] [G loss: 0.742445]
8/8 [==============================] - 0s 4ms/step
2920 [D loss: 0.676596, acc.: 57.62%] [G loss: 0.728377]
8/8 [==============================] - 0s 4ms/step
2921 [D loss: 0.691701, acc.: 52.73%] [G loss: 0.718184]
8/8 [==============================] - 0s 4ms/step
2922 [D loss: 0.700507, acc.: 48.63%] [G loss: 0.713987]
8/8 [==============================] - 0s 4ms/step
2923 [D loss: 0.700962, acc.: 48.83%] [G loss: 0.712641]
8/8 [==============================] - 0s 4ms/step
2924 [D loss: 0.694392, acc.: 53.12%] [G loss: 0.727200]
8/8 [==============================] - 0s 4ms/step
2925 [D loss: 0.687769, acc.: 53.52%] [G loss: 0.719544]
8/8 [==============================] - 0s 4ms/step
2926 [D loss: 0.693772, acc.: 51.17%] [G loss: 0.727793]
8/8 [==============================] - 0s 4ms/step
2927 [D loss: 0.692424, acc.: 49.22%] [G loss: 0.742489]
8/8 [==============================] - 0s 4ms/step
2928 [D loss: 0.688507, acc.: 53.52%] [G loss: 0.748043]
8/8 [==============================] - 0s 4ms/step
2929 [D loss: 0.689286, acc.: 50.98%] [G loss: 0.742875]
8/8 [==============================] - 0s 4ms/step
2930 [D loss: 0.692755, acc.: 51.17%] [G loss: 0.745166]
8/8 [==============================] - 0s 4ms/step
2931 [D loss: 0.686503, acc.: 54.10%] [G loss: 0.729343]
8/8 [==============================] - 0s 4ms/step
2932 [D loss: 0.689734, acc.: 53.52%] [G loss: 0.736058]
8/8 [==============================] - 0s 4ms/step
2933 [D loss: 0.690404, acc.: 55.08%] [G loss: 0.727520]
8/8 [==============================] - 0s 5ms/step
2934 [D loss: 0.682475, acc.: 56.05%] [G loss: 0.729203]
8/8 [==============================] - 0s 4ms/step
2935 [D loss: 0.694076, acc.: 55.27%] [G loss: 0.734150]
8/8 [==============================] - 0s 4ms/step
2936 [D loss: 0.693000, acc.: 51.95%] [G loss: 0.727011]
8/8 [==============================] - 0s 4ms/step
2937 [D loss: 0.699449, acc.: 50.39%] [G loss: 0.736100]
8/8 [==============================] - 0s 4ms/step
2938 [D loss: 0.692701, acc.: 53.71%] [G loss: 0.721284]
8/8 [==============================] - 0s 4ms/step
2939 [D loss: 0.687160, acc.: 56.84%] [G loss: 0.740142]
8/8 [==============================] - 0s 4ms/step
2940 [D loss: 0.696790, acc.: 51.37%] [G loss: 0.729366]
8/8 [==============================] - 0s 5ms/step
2941 [D loss: 0.684458, acc.: 56.64%] [G loss: 0.740228]
8/8 [==============================] - 0s 4ms/step
2942 [D loss: 0.692330, acc.: 51.56%] [G loss: 0.733588]
8/8 [==============================] - 0s 4ms/step
2943 [D loss: 0.682330, acc.: 53.91%] [G loss: 0.739370]
8/8 [==============================] - 0s 4ms/step
2944 [D loss: 0.681199, acc.: 57.42%] [G loss: 0.742669]
8/8 [==============================] - 0s 4ms/step
2945 [D loss: 0.685087, acc.: 58.01%] [G loss: 0.751347]
8/8 [==============================] - 0s 4ms/step
2946 [D loss: 0.688116, acc.: 51.95%] [G loss: 0.758923]
8/8 [==============================] - 0s 4ms/step
2947 [D loss: 0.697520, acc.: 52.34%] [G loss: 0.739743]
8/8 [==============================] - 0s 4ms/step
2948 [D loss: 0.694339, acc.: 52.34%] [G loss: 0.749616]
8/8 [==============================] - 0s 4ms/step
2949 [D loss: 0.704300, acc.: 46.68%] [G loss: 0.733587]
8/8 [==============================] - 0s 4ms/step
2950 [D loss: 0.693478, acc.: 53.32%] [G loss: 0.738069]
1/1 [==============================] - 0s 22ms/step
8/8 [==============================] - 0s 4ms/step
2951 [D loss: 0.698210, acc.: 47.46%] [G loss: 0.723414]
8/8 [==============================] - 0s 4ms/step
2952 [D loss: 0.700590, acc.: 47.66%] [G loss: 0.722905]
8/8 [==============================] - 0s 4ms/step
2953 [D loss: 0.696658, acc.: 50.20%] [G loss: 0.725654]
8/8 [==============================] - 0s 5ms/step
2954 [D loss: 0.687200, acc.: 53.52%] [G loss: 0.727011]
8/8 [==============================] - 0s 4ms/step
2955 [D loss: 0.692103, acc.: 51.37%] [G loss: 0.730482]
8/8 [==============================] - 0s 4ms/step
2956 [D loss: 0.685829, acc.: 54.88%] [G loss: 0.741624]
8/8 [==============================] - 0s 4ms/step
2957 [D loss: 0.689162, acc.: 53.32%] [G loss: 0.747621]
8/8 [==============================] - 0s 4ms/step
2958 [D loss: 0.680549, acc.: 59.18%] [G loss: 0.749683]
8/8 [==============================] - 0s 4ms/step
2959 [D loss: 0.687260, acc.: 51.76%] [G loss: 0.749840]
8/8 [==============================] - 0s 4ms/step
2960 [D loss: 0.680468, acc.: 55.86%] [G loss: 0.746080]
8/8 [==============================] - 0s 4ms/step
2961 [D loss: 0.675062, acc.: 58.59%] [G loss: 0.741598]
8/8 [==============================] - 0s 4ms/step
2962 [D loss: 0.684965, acc.: 54.10%] [G loss: 0.731584]
8/8 [==============================] - 0s 5ms/step
2963 [D loss: 0.693526, acc.: 50.98%] [G loss: 0.720964]
8/8 [==============================] - 0s 4ms/step
2964 [D loss: 0.702724, acc.: 49.02%] [G loss: 0.719853]
8/8 [==============================] - 0s 4ms/step
2965 [D loss: 0.701419, acc.: 46.88%] [G loss: 0.698149]
8/8 [==============================] - 0s 4ms/step
2966 [D loss: 0.697250, acc.: 48.44%] [G loss: 0.710022]
8/8 [==============================] - 0s 4ms/step
2967 [D loss: 0.702582, acc.: 51.17%] [G loss: 0.730684]
8/8 [==============================] - 0s 4ms/step
2968 [D loss: 0.681096, acc.: 56.25%] [G loss: 0.762631]
8/8 [==============================] - 0s 4ms/step
2969 [D loss: 0.681892, acc.: 56.64%] [G loss: 0.775089]
8/8 [==============================] - 0s 5ms/step
2970 [D loss: 0.683263, acc.: 54.49%] [G loss: 0.778032]
8/8 [==============================] - 0s 4ms/step
2971 [D loss: 0.682422, acc.: 56.25%] [G loss: 0.759677]
8/8 [==============================] - 0s 4ms/step
2972 [D loss: 0.689456, acc.: 53.52%] [G loss: 0.752958]
8/8 [==============================] - 0s 4ms/step
2973 [D loss: 0.685283, acc.: 58.40%] [G loss: 0.720034]
8/8 [==============================] - 0s 4ms/step
2974 [D loss: 0.689910, acc.: 52.93%] [G loss: 0.717201]
8/8 [==============================] - 0s 4ms/step
2975 [D loss: 0.691447, acc.: 54.49%] [G loss: 0.699173]
8/8 [==============================] - 0s 4ms/step
2976 [D loss: 0.691965, acc.: 52.34%] [G loss: 0.691580]
8/8 [==============================] - 0s 4ms/step
2977 [D loss: 0.698748, acc.: 50.20%] [G loss: 0.704538]
8/8 [==============================] - 0s 5ms/step
2978 [D loss: 0.697383, acc.: 52.54%] [G loss: 0.714745]
8/8 [==============================] - 0s 4ms/step
2979 [D loss: 0.689426, acc.: 49.61%] [G loss: 0.745603]
8/8 [==============================] - 0s 4ms/step
2980 [D loss: 0.686123, acc.: 54.10%] [G loss: 0.779524]
8/8 [==============================] - 0s 4ms/step
2981 [D loss: 0.691289, acc.: 49.02%] [G loss: 0.777029]
8/8 [==============================] - 0s 4ms/step
2982 [D loss: 0.685070, acc.: 54.69%] [G loss: 0.775155]
8/8 [==============================] - 0s 4ms/step
2983 [D loss: 0.696678, acc.: 49.02%] [G loss: 0.772953]
8/8 [==============================] - 0s 4ms/step
2984 [D loss: 0.681922, acc.: 56.05%] [G loss: 0.764003]
8/8 [==============================] - 0s 4ms/step
2985 [D loss: 0.682625, acc.: 58.79%] [G loss: 0.753729]
8/8 [==============================] - 0s 5ms/step
2986 [D loss: 0.677921, acc.: 57.23%] [G loss: 0.734224]
8/8 [==============================] - 0s 4ms/step
2987 [D loss: 0.682383, acc.: 56.64%] [G loss: 0.724662]
8/8 [==============================] - 0s 4ms/step
2988 [D loss: 0.689113, acc.: 53.12%] [G loss: 0.712390]
8/8 [==============================] - 0s 4ms/step
2989 [D loss: 0.701899, acc.: 49.41%] [G loss: 0.705580]
8/8 [==============================] - 0s 4ms/step
2990 [D loss: 0.701497, acc.: 52.73%] [G loss: 0.697079]
8/8 [==============================] - 0s 4ms/step
2991 [D loss: 0.693652, acc.: 51.56%] [G loss: 0.713997]
8/8 [==============================] - 0s 4ms/step
2992 [D loss: 0.696310, acc.: 51.17%] [G loss: 0.726935]
8/8 [==============================] - 0s 4ms/step
2993 [D loss: 0.694445, acc.: 52.15%] [G loss: 0.731953]
8/8 [==============================] - 0s 4ms/step
2994 [D loss: 0.692710, acc.: 50.78%] [G loss: 0.760671]
8/8 [==============================] - 0s 4ms/step
2995 [D loss: 0.697296, acc.: 45.90%] [G loss: 0.756173]
8/8 [==============================] - 0s 4ms/step
2996 [D loss: 0.696711, acc.: 49.80%] [G loss: 0.762230]
8/8 [==============================] - 0s 4ms/step
2997 [D loss: 0.693907, acc.: 53.32%] [G loss: 0.753222]
8/8 [==============================] - 0s 4ms/step
2998 [D loss: 0.693857, acc.: 52.54%] [G loss: 0.746391]
8/8 [==============================] - 0s 4ms/step
2999 [D loss: 0.696197, acc.: 50.20%] [G loss: 0.740447]

Plot Loss

plot_losses(cgan.d_losses, cgan.g_losses)

Plot Accuracy

plot_accuracy(cgan.d_accuracy)

Generated Images at Different Epochs (More Dense Unit in Generator)

100 Epochs

1000 Epochs

2950 Epochs

Results

The generator's initial high loss of around 14 and the discriminator's low loss of about 0.3 indicate that the generator's early images were unrealistic, while the discriminator was effective at telling real from fake. As training continued, the generator's loss dropped to 5.8, showing improved image quality, while the discriminator's loss rose to 2.1, reflecting increased difficulty in distinguishing images. Both losses eventually converged at 0.7, suggesting a balance where the generator produced realistic images.

The discriminator's accuracy, initially high at 90%, fell to about 80% and then fluctuated between 50% and 60%. This fluctuation indicates that as the generator improved, the discriminator struggled to differentiate between real and generated images.s.

While more classes are now distinguishable in the generated images, the sharpness still needs improvement. The enhanced recognizability indicates progress in the generator's ability to produce diverse and identifiable characters. However, the images continue to lack detail and clarity.

Remove Batch Normalization Layer from the Generator

What changed from the previous model

• Batch normalization layer from the generator is removed
• Number of epochs increased from 3000 to 10000

Why did we remove batch normalization layer from the generator

Batch normalization (BN) layers are typically used to stabilize and speed up the training of neural networks by normalizing activations and reducing internal covariate shift. In the context of GANs, the training dynamics can be quite sensitive, and batch normalization might interfere with the adversarial training process.

Why did we increase the number of epochs

From the previous models, we observed that 3000 epochs were insufficient for the generator to fully learn the underlying patterns in the data. By increasing the number of epochs to 10000, we aim to provide the model with more training time to refine its outputs and improve image quality. This extended training period allows the generator to better capture the complexities of the dataset, leading to more realistic and detailed images.

class CGAN():
    def __init__(self):
        # Input shape
        self.img_rows = 28
        self.img_cols = 28
        self.channels = 1
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.num_classes = 26
        self.latent_dim = 100

        optimizer = Adam(0.001, 0.5)

        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss=['binary_crossentropy'],
            optimizer=optimizer,
            metrics=['accuracy'])

        # Build the generator
        self.generator = self.build_generator()

        # The generator takes noise and the target label as input
        # and generates the corresponding digit of that label
        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,))
        img = self.generator([noise, label])

        # For the combined model we will only train the generator
        self.discriminator.trainable = False

        # The discriminator takes generated image as input and determines validity
        # and the label of that image
        valid = self.discriminator([img, label])

        # The combined model  (stacked generator and discriminator)
        # Trains generator to fool discriminator
        self.combined = Model([noise, label], valid)
        self.combined.compile(loss=['binary_crossentropy'],
            optimizer=optimizer)

        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []

    def build_generator(self):

        model = Sequential()

        model.add(Dense(512 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 512)))
        
        model.add(Conv2DTranspose(128, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(self.channels, kernel_size=4, strides=(2,2), padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,), dtype='int32')
        label_embedding = Flatten()(Embedding(self.num_classes, self.latent_dim)(label))

        model_input = multiply([noise, label_embedding])
        img = model(model_input)

        return Model([noise, label], img)

    def build_discriminator(self):
        model = Sequential()

        model.add(Conv2D(64, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))

        
        model.add(Flatten())
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        # Image input and label input
        img = Input(shape=self.img_shape)
        label = Input(shape=(1,), dtype='int32')

        # Embedding for label
        label_embedding = Flatten()(Embedding(self.num_classes, np.prod(self.img_shape))(label))
        label_embedding = Dense(np.prod(self.img_shape))(label_embedding)
        label_embedding = Reshape(self.img_shape)(label_embedding)

        # Multiply image and label embeddings
        combined = multiply([img, label_embedding])

        # Validity prediction
        validity = model(combined)

        return Model([img, label], validity)

    def train(self, epochs, batch_size=128, sample_interval=50):


        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values
        y_train = preprocessed_df.iloc[:, 0].values
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)

        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))

        for epoch in range(epochs):

            # ---------------------
            #  Train Discriminator
            # ---------------------

            # Select a random half batch of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs, labels = X_train[idx], y_train[idx]
            # Sample noise as generator input
            noise = np.random.normal(0, 1, (batch_size, 100))

            # Generate a half batch of new images
            gen_imgs = self.generator.predict([noise, labels])

            # Train the discriminator
            d_loss_real = self.discriminator.train_on_batch([imgs, labels], valid)
            d_loss_fake = self.discriminator.train_on_batch([gen_imgs, labels], fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)

            # ---------------------
            #  Train Generator
            # ---------------------

            # Condition on labels (Generate random samples)
            sampled_labels = np.random.randint(1, 27, batch_size).reshape(-1, 1)

            # Train the generator
            g_loss = self.combined.train_on_batch([noise, sampled_labels], valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            
            # Plot the progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100*d_loss[1], g_loss))

            # If at save interval => save generated image samples
            if epoch % sample_interval == 0:
                self.sample_images(epoch)

    def sample_images(self, epoch):
        r, c = 5, 6
        num_samples = 26
        # Generate noise based on the number of samples
        noise = np.random.normal(0, 1, (num_samples, 100))
        sampled_labels = np.arange(1, 27).reshape(-1, 1)

        gen_imgs = self.generator.predict([noise, sampled_labels])

        # Rescale images 0 - 1
        gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0  # Counter for the images
        for i in range(r):
            for j in range(c):
                if cnt < num_samples:  # Ensure we don't go out of bounds
                    axs[i,j].imshow(gen_imgs[cnt,:,:,0], cmap='gray')  # Display image

                    mapped_label = map_labels(sampled_labels[cnt][0])  # Map label to its corresponding class name
                    axs[i,j].set_title("Class: %s" % mapped_label)  # Set title of the subplot
                    axs[i,j].axis('off')  # Turn off axis
                    cnt += 1  # Increment counter
                else:
                    axs[i,j].axis('off')  # Turn off axis if there's no image to display
                    
        # Adjust the spacing between subplots
        plt.subplots_adjust(wspace=0.2, hspace=0.6)
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/cgan/rmvBatch', exist_ok=True)
        fig.savefig("generated_images/cgan/rmvBatch/cgan_{:d}.png".format(epoch))
        plt.close()

cgan = CGAN()
cgan.train(epochs=10000, batch_size=256, sample_interval=50)

Model: "sequential_8"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_31 (Conv2D)          (None, 14, 14, 64)        640       
                                                                 
 leaky_re_lu_30 (LeakyReLU)  (None, 14, 14, 64)        0         
                                                                 
 conv2d_32 (Conv2D)          (None, 7, 7, 128)         73856     
                                                                 
 leaky_re_lu_31 (LeakyReLU)  (None, 7, 7, 128)         0         
                                                                 
 conv2d_33 (Conv2D)          (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_32 (LeakyReLU)  (None, 4, 4, 256)         0         
                                                                 
 flatten_10 (Flatten)        (None, 4096)              0         
                                                                 
 dense_17 (Dense)            (None, 1)                 4097      
                                                                 
=================================================================
Total params: 373,761
Trainable params: 373,761
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_9"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_19 (Dense)            (None, 25088)             2533888   
                                                                 
 reshape_9 (Reshape)         (None, 7, 7, 512)         0         
                                                                 
 conv2d_transpose_6 (Conv2DT  (None, 14, 14, 128)      1048704   
 ranspose)                                                       
                                                                 
 leaky_re_lu_33 (LeakyReLU)  (None, 14, 14, 128)       0         
                                                                 
 conv2d_transpose_7 (Conv2DT  (None, 28, 28, 64)       131136    
 ranspose)                                                       
                                                                 
 leaky_re_lu_34 (LeakyReLU)  (None, 28, 28, 64)        0         
                                                                 
 conv2d_transpose_8 (Conv2DT  (None, 56, 56, 64)       65600     
 ranspose)                                                       
                                                                 
 leaky_re_lu_35 (LeakyReLU)  (None, 56, 56, 64)        0         
                                                                 
 conv2d_34 (Conv2D)          (None, 28, 28, 1)         1025      
                                                                 
 activation_10 (Activation)  (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 3,780,353
Trainable params: 3,780,353
Non-trainable params: 0
_________________________________________________________________
8/8 [==============================] - 0s 4ms/step
0 [D loss: 0.699945, acc.: 36.72%] [G loss: 0.690394]
1/1 [==============================] - 0s 86ms/step
8/8 [==============================] - 0s 6ms/step
1 [D loss: 0.694050, acc.: 50.00%] [G loss: 0.691746]
8/8 [==============================] - 0s 5ms/step
2 [D loss: 0.693335, acc.: 50.00%] [G loss: 0.693247]
8/8 [==============================] - 0s 4ms/step
3 [D loss: 0.692629, acc.: 53.91%] [G loss: 0.696233]
8/8 [==============================] - 0s 4ms/step
4 [D loss: 0.691186, acc.: 96.09%] [G loss: 0.706290]
8/8 [==============================] - 0s 4ms/step
5 [D loss: 0.686002, acc.: 95.51%] [G loss: 0.745194]
8/8 [==============================] - 0s 4ms/step
6 [D loss: 0.669564, acc.: 81.64%] [G loss: 0.857646]
8/8 [==============================] - 0s 4ms/step
7 [D loss: 0.600251, acc.: 94.92%] [G loss: 1.427188]
8/8 [==============================] - 0s 4ms/step
8 [D loss: 0.510131, acc.: 79.10%] [G loss: 2.216589]
8/8 [==============================] - 0s 4ms/step
9 [D loss: 0.465085, acc.: 93.75%] [G loss: 2.209073]
8/8 [==============================] - 0s 4ms/step
10 [D loss: 0.643331, acc.: 48.44%] [G loss: 0.633387]
8/8 [==============================] - 0s 4ms/step
11 [D loss: 0.514403, acc.: 49.22%] [G loss: 0.672340]
8/8 [==============================] - 0s 4ms/step
12 [D loss: 0.390423, acc.: 50.00%] [G loss: 0.730960]
8/8 [==============================] - 0s 4ms/step
13 [D loss: 0.334562, acc.: 98.83%] [G loss: 0.817645]
8/8 [==============================] - 0s 4ms/step
14 [D loss: 0.293058, acc.: 98.24%] [G loss: 0.992932]
8/8 [==============================] - 0s 4ms/step
15 [D loss: 0.224784, acc.: 98.63%] [G loss: 1.382296]
8/8 [==============================] - 0s 4ms/step
16 [D loss: 0.165557, acc.: 97.27%] [G loss: 2.050662]
8/8 [==============================] - 0s 4ms/step
17 [D loss: 0.120216, acc.: 97.46%] [G loss: 2.823170]
8/8 [==============================] - 0s 4ms/step
18 [D loss: 0.101898, acc.: 98.63%] [G loss: 4.085758]
8/8 [==============================] - 0s 4ms/step
19 [D loss: 0.758756, acc.: 71.29%] [G loss: 5.326498]
8/8 [==============================] - 0s 4ms/step
20 [D loss: 2.067460, acc.: 39.84%] [G loss: 4.108539]
8/8 [==============================] - 0s 4ms/step
21 [D loss: 5.090448, acc.: 20.90%] [G loss: 1.052309]
8/8 [==============================] - 0s 4ms/step
22 [D loss: 1.468328, acc.: 34.38%] [G loss: 2.877860]
8/8 [==============================] - 0s 4ms/step
23 [D loss: 0.919346, acc.: 50.00%] [G loss: 2.011038]
8/8 [==============================] - 0s 4ms/step
24 [D loss: 0.761055, acc.: 50.00%] [G loss: 1.193741]
8/8 [==============================] - 0s 4ms/step
25 [D loss: 0.706806, acc.: 50.00%] [G loss: 1.043726]
8/8 [==============================] - 0s 4ms/step
26 [D loss: 0.679897, acc.: 48.05%] [G loss: 1.018021]
8/8 [==============================] - 0s 4ms/step
27 [D loss: 0.678489, acc.: 50.00%] [G loss: 0.965316]
8/8 [==============================] - 0s 4ms/step
28 [D loss: 0.665990, acc.: 51.95%] [G loss: 0.979421]
8/8 [==============================] - 0s 4ms/step
29 [D loss: 0.663758, acc.: 55.66%] [G loss: 0.984298]
8/8 [==============================] - 0s 4ms/step
30 [D loss: 0.650541, acc.: 57.62%] [G loss: 1.012757]
8/8 [==============================] - 0s 4ms/step
31 [D loss: 0.649181, acc.: 61.13%] [G loss: 1.046751]
8/8 [==============================] - 0s 4ms/step
32 [D loss: 0.674159, acc.: 58.20%] [G loss: 1.002337]
8/8 [==============================] - 0s 4ms/step
33 [D loss: 0.669548, acc.: 60.16%] [G loss: 0.977932]
8/8 [==============================] - 0s 4ms/step
34 [D loss: 0.661391, acc.: 61.72%] [G loss: 1.063897]
8/8 [==============================] - 0s 4ms/step
35 [D loss: 0.632360, acc.: 63.48%] [G loss: 1.207190]
8/8 [==============================] - 0s 4ms/step
36 [D loss: 0.612487, acc.: 61.91%] [G loss: 1.383318]
8/8 [==============================] - 0s 4ms/step
37 [D loss: 0.593644, acc.: 63.28%] [G loss: 1.517559]
8/8 [==============================] - 0s 4ms/step
38 [D loss: 0.579273, acc.: 65.62%] [G loss: 1.576733]
8/8 [==============================] - 0s 4ms/step
39 [D loss: 0.613440, acc.: 66.02%] [G loss: 1.373904]
8/8 [==============================] - 0s 4ms/step
40 [D loss: 0.753895, acc.: 38.28%] [G loss: 0.751187]
8/8 [==============================] - 0s 4ms/step
41 [D loss: 0.808087, acc.: 29.69%] [G loss: 0.530164]
8/8 [==============================] - 0s 4ms/step
42 [D loss: 0.756854, acc.: 40.23%] [G loss: 0.538179]
8/8 [==============================] - 0s 4ms/step
43 [D loss: 0.718824, acc.: 48.63%] [G loss: 0.555359]
8/8 [==============================] - 0s 4ms/step
44 [D loss: 0.703739, acc.: 48.83%] [G loss: 0.571688]
8/8 [==============================] - 0s 4ms/step
45 [D loss: 0.689125, acc.: 48.83%] [G loss: 0.587929]
8/8 [==============================] - 0s 4ms/step
46 [D loss: 0.677623, acc.: 49.61%] [G loss: 0.604080]
8/8 [==============================] - 0s 4ms/step
47 [D loss: 0.668457, acc.: 49.61%] [G loss: 0.619807]
8/8 [==============================] - 0s 4ms/step
48 [D loss: 0.655118, acc.: 50.00%] [G loss: 0.636669]
8/8 [==============================] - 0s 4ms/step
49 [D loss: 0.641044, acc.: 50.00%] [G loss: 0.655349]
8/8 [==============================] - 0s 4ms/step
50 [D loss: 0.626534, acc.: 49.80%] [G loss: 0.676470]
1/1 [==============================] - 0s 35ms/step
8/8 [==============================] - 0s 4ms/step
51 [D loss: 0.615275, acc.: 49.80%] [G loss: 0.699167]
8/8 [==============================] - 0s 4ms/step
52 [D loss: 0.599002, acc.: 98.05%] [G loss: 0.724174]
8/8 [==============================] - 0s 4ms/step
53 [D loss: 0.577645, acc.: 97.07%] [G loss: 0.754118]
8/8 [==============================] - 0s 4ms/step
54 [D loss: 0.554628, acc.: 95.70%] [G loss: 0.790759]
8/8 [==============================] - 0s 4ms/step
55 [D loss: 0.522617, acc.: 93.75%] [G loss: 0.835780]
8/8 [==============================] - 0s 4ms/step
56 [D loss: 0.487209, acc.: 93.75%] [G loss: 0.892338]
8/8 [==============================] - 0s 4ms/step
57 [D loss: 0.455428, acc.: 93.75%] [G loss: 0.960392]
8/8 [==============================] - 0s 4ms/step
58 [D loss: 0.427907, acc.: 92.38%] [G loss: 1.038961]
8/8 [==============================] - 0s 4ms/step
59 [D loss: 0.396116, acc.: 89.84%] [G loss: 1.127434]
8/8 [==============================] - 0s 4ms/step
60 [D loss: 0.363952, acc.: 91.02%] [G loss: 1.226951]
8/8 [==============================] - 0s 4ms/step
61 [D loss: 0.334536, acc.: 92.19%] [G loss: 1.335421]
8/8 [==============================] - 0s 4ms/step
62 [D loss: 0.293698, acc.: 93.16%] [G loss: 1.459186]
8/8 [==============================] - 0s 4ms/step
63 [D loss: 0.258187, acc.: 94.34%] [G loss: 1.599767]
8/8 [==============================] - 0s 4ms/step
64 [D loss: 0.246974, acc.: 92.38%] [G loss: 1.722502]
8/8 [==============================] - 0s 4ms/step
65 [D loss: 0.226217, acc.: 94.53%] [G loss: 1.835781]
8/8 [==============================] - 0s 4ms/step
66 [D loss: 0.215947, acc.: 94.53%] [G loss: 1.933831]
8/8 [==============================] - 0s 4ms/step
67 [D loss: 0.174886, acc.: 95.70%] [G loss: 2.057906]
8/8 [==============================] - 0s 4ms/step
68 [D loss: 0.144143, acc.: 97.66%] [G loss: 2.206095]
8/8 [==============================] - 0s 4ms/step
69 [D loss: 0.139520, acc.: 97.27%] [G loss: 2.330756]
8/8 [==============================] - 0s 4ms/step
70 [D loss: 0.163024, acc.: 95.51%] [G loss: 2.379894]
8/8 [==============================] - 0s 4ms/step
71 [D loss: 0.122598, acc.: 97.27%] [G loss: 2.472836]
8/8 [==============================] - 0s 4ms/step
72 [D loss: 0.113589, acc.: 97.66%] [G loss: 2.572931]
8/8 [==============================] - 0s 4ms/step
73 [D loss: 0.102352, acc.: 98.24%] [G loss: 2.673927]
8/8 [==============================] - 0s 4ms/step
74 [D loss: 0.144076, acc.: 96.29%] [G loss: 2.677650]
8/8 [==============================] - 0s 4ms/step
75 [D loss: 0.107597, acc.: 97.07%] [G loss: 2.728694]
8/8 [==============================] - 0s 4ms/step
76 [D loss: 0.121359, acc.: 96.88%] [G loss: 2.756835]
8/8 [==============================] - 0s 4ms/step
77 [D loss: 0.138897, acc.: 96.09%] [G loss: 2.738452]
8/8 [==============================] - 0s 4ms/step
78 [D loss: 0.113730, acc.: 97.27%] [G loss: 2.759505]
8/8 [==============================] - 0s 4ms/step
79 [D loss: 0.079549, acc.: 98.44%] [G loss: 2.857935]
8/8 [==============================] - 0s 4ms/step
80 [D loss: 0.120517, acc.: 96.48%] [G loss: 2.866198]
8/8 [==============================] - 0s 4ms/step
81 [D loss: 0.094304, acc.: 97.66%] [G loss: 2.909028]
8/8 [==============================] - 0s 4ms/step
82 [D loss: 0.103186, acc.: 97.07%] [G loss: 2.929585]
8/8 [==============================] - 0s 4ms/step
83 [D loss: 0.084575, acc.: 98.05%] [G loss: 2.987824]
8/8 [==============================] - 0s 4ms/step
84 [D loss: 0.126616, acc.: 96.68%] [G loss: 2.948774]
8/8 [==============================] - 0s 4ms/step
85 [D loss: 0.062877, acc.: 98.83%] [G loss: 3.039052]
8/8 [==============================] - 0s 4ms/step
86 [D loss: 0.089263, acc.: 97.27%] [G loss: 3.067550]
8/8 [==============================] - 0s 4ms/step
87 [D loss: 0.108800, acc.: 97.07%] [G loss: 3.048702]
8/8 [==============================] - 0s 4ms/step
88 [D loss: 0.091038, acc.: 97.66%] [G loss: 3.068160]
8/8 [==============================] - 0s 4ms/step
89 [D loss: 0.096281, acc.: 97.27%] [G loss: 3.066828]
8/8 [==============================] - 0s 4ms/step
90 [D loss: 0.062407, acc.: 98.63%] [G loss: 3.139684]
8/8 [==============================] - 0s 4ms/step
91 [D loss: 0.087507, acc.: 97.85%] [G loss: 3.159045]
8/8 [==============================] - 0s 4ms/step
92 [D loss: 0.063479, acc.: 98.24%] [G loss: 3.210921]
8/8 [==============================] - 0s 4ms/step
93 [D loss: 0.072877, acc.: 98.24%] [G loss: 3.238024]
8/8 [==============================] - 0s 4ms/step
94 [D loss: 0.074823, acc.: 98.05%] [G loss: 3.260723]
8/8 [==============================] - 0s 4ms/step
95 [D loss: 0.070568, acc.: 98.44%] [G loss: 3.306585]
8/8 [==============================] - 0s 4ms/step
96 [D loss: 0.090803, acc.: 97.46%] [G loss: 3.273011]
8/8 [==============================] - 0s 4ms/step
97 [D loss: 0.063687, acc.: 98.05%] [G loss: 3.288911]
8/8 [==============================] - 0s 4ms/step
98 [D loss: 0.075167, acc.: 97.66%] [G loss: 3.295883]
8/8 [==============================] - 0s 4ms/step
99 [D loss: 0.109760, acc.: 96.88%] [G loss: 3.211456]
8/8 [==============================] - 0s 4ms/step
100 [D loss: 0.083158, acc.: 97.46%] [G loss: 3.188120]
1/1 [==============================] - 0s 25ms/step
8/8 [==============================] - 0s 4ms/step
101 [D loss: 0.068219, acc.: 97.85%] [G loss: 3.229490]
8/8 [==============================] - 0s 4ms/step
102 [D loss: 0.100054, acc.: 96.88%] [G loss: 3.175109]
8/8 [==============================] - 0s 4ms/step
103 [D loss: 0.048157, acc.: 98.83%] [G loss: 3.272923]
8/8 [==============================] - 0s 4ms/step
104 [D loss: 0.081152, acc.: 96.88%] [G loss: 3.254287]
8/8 [==============================] - 0s 4ms/step
105 [D loss: 0.054896, acc.: 98.44%] [G loss: 3.304402]
8/8 [==============================] - 0s 4ms/step
106 [D loss: 0.070552, acc.: 97.85%] [G loss: 3.319075]
8/8 [==============================] - 0s 4ms/step
107 [D loss: 0.082915, acc.: 97.46%] [G loss: 3.294709]
8/8 [==============================] - 0s 4ms/step
108 [D loss: 0.051659, acc.: 98.44%] [G loss: 3.350924]
8/8 [==============================] - 0s 4ms/step
109 [D loss: 0.069069, acc.: 97.85%] [G loss: 3.350448]
8/8 [==============================] - 0s 4ms/step
110 [D loss: 0.049126, acc.: 98.63%] [G loss: 3.402580]
8/8 [==============================] - 0s 4ms/step
111 [D loss: 0.059441, acc.: 98.44%] [G loss: 3.432691]
8/8 [==============================] - 0s 4ms/step
112 [D loss: 0.042365, acc.: 99.02%] [G loss: 3.515707]
8/8 [==============================] - 0s 4ms/step
113 [D loss: 0.031761, acc.: 99.41%] [G loss: 3.610621]
8/8 [==============================] - 0s 4ms/step
114 [D loss: 0.032485, acc.: 99.22%] [G loss: 3.695323]
8/8 [==============================] - 0s 4ms/step
115 [D loss: 0.071038, acc.: 97.66%] [G loss: 3.595424]
8/8 [==============================] - 0s 4ms/step
116 [D loss: 0.057390, acc.: 98.05%] [G loss: 3.529214]
8/8 [==============================] - 0s 4ms/step
117 [D loss: 0.061643, acc.: 98.05%] [G loss: 3.494670]
8/8 [==============================] - 0s 4ms/step
118 [D loss: 0.029438, acc.: 99.41%] [G loss: 3.656125]
8/8 [==============================] - 0s 4ms/step
119 [D loss: 0.041574, acc.: 98.44%] [G loss: 3.701111]
8/8 [==============================] - 0s 4ms/step
120 [D loss: 0.029972, acc.: 99.41%] [G loss: 3.789969]
8/8 [==============================] - 0s 4ms/step
121 [D loss: 0.049401, acc.: 98.44%] [G loss: 3.774091]
8/8 [==============================] - 0s 4ms/step
122 [D loss: 0.030023, acc.: 99.41%] [G loss: 3.838390]
8/8 [==============================] - 0s 4ms/step
123 [D loss: 0.033141, acc.: 99.02%] [G loss: 3.869745]
8/8 [==============================] - 0s 4ms/step
124 [D loss: 0.056981, acc.: 98.24%] [G loss: 3.787256]
8/8 [==============================] - 0s 4ms/step
125 [D loss: 0.012278, acc.: 100.00%] [G loss: 3.939355]
8/8 [==============================] - 0s 4ms/step
126 [D loss: 0.028552, acc.: 99.41%] [G loss: 3.992923]
8/8 [==============================] - 0s 4ms/step
127 [D loss: 0.035400, acc.: 99.22%] [G loss: 3.992647]
8/8 [==============================] - 0s 4ms/step
128 [D loss: 0.028482, acc.: 99.41%] [G loss: 4.029968]
8/8 [==============================] - 0s 4ms/step
129 [D loss: 0.035156, acc.: 99.02%] [G loss: 4.042265]
8/8 [==============================] - 0s 4ms/step
130 [D loss: 0.021471, acc.: 99.41%] [G loss: 4.097275]
8/8 [==============================] - 0s 4ms/step
131 [D loss: 0.027124, acc.: 99.22%] [G loss: 4.115693]
8/8 [==============================] - 0s 4ms/step
132 [D loss: 0.014741, acc.: 99.61%] [G loss: 4.197666]
8/8 [==============================] - 0s 4ms/step
133 [D loss: 0.017601, acc.: 99.41%] [G loss: 4.246454]
8/8 [==============================] - 0s 4ms/step
134 [D loss: 0.026790, acc.: 99.22%] [G loss: 4.264427]
8/8 [==============================] - 0s 4ms/step
135 [D loss: 0.025521, acc.: 99.22%] [G loss: 4.271331]
8/8 [==============================] - 0s 4ms/step
136 [D loss: 0.018355, acc.: 99.41%] [G loss: 4.305910]
8/8 [==============================] - 0s 4ms/step
137 [D loss: 0.023247, acc.: 99.41%] [G loss: 4.335345]
8/8 [==============================] - 0s 4ms/step
138 [D loss: 0.045195, acc.: 98.44%] [G loss: 4.110826]
8/8 [==============================] - 0s 4ms/step
139 [D loss: 0.023632, acc.: 99.41%] [G loss: 4.206520]
8/8 [==============================] - 0s 4ms/step
140 [D loss: 0.029250, acc.: 99.41%] [G loss: 4.260324]
8/8 [==============================] - 0s 4ms/step
141 [D loss: 0.009518, acc.: 100.00%] [G loss: 4.396863]
8/8 [==============================] - 0s 4ms/step
142 [D loss: 0.015010, acc.: 99.61%] [G loss: 4.442820]
8/8 [==============================] - 0s 4ms/step
143 [D loss: 0.020574, acc.: 99.41%] [G loss: 4.456266]
8/8 [==============================] - 0s 4ms/step
144 [D loss: 0.032094, acc.: 99.02%] [G loss: 4.329288]
8/8 [==============================] - 0s 4ms/step
145 [D loss: 0.018566, acc.: 99.61%] [G loss: 4.397223]
8/8 [==============================] - 0s 4ms/step
146 [D loss: 0.012140, acc.: 99.80%] [G loss: 4.485353]
8/8 [==============================] - 0s 4ms/step
147 [D loss: 0.013088, acc.: 99.61%] [G loss: 4.548219]
8/8 [==============================] - 0s 4ms/step
148 [D loss: 0.017272, acc.: 99.41%] [G loss: 4.574086]
8/8 [==============================] - 0s 4ms/step
149 [D loss: 0.024917, acc.: 99.22%] [G loss: 4.505642]
8/8 [==============================] - 0s 4ms/step
150 [D loss: 0.005538, acc.: 100.00%] [G loss: 4.632266]
1/1 [==============================] - 0s 23ms/step
8/8 [==============================] - 0s 4ms/step
151 [D loss: 0.021822, acc.: 99.22%] [G loss: 4.618164]
8/8 [==============================] - 0s 4ms/step
152 [D loss: 0.011596, acc.: 99.61%] [G loss: 4.664080]
8/8 [==============================] - 0s 4ms/step
153 [D loss: 0.016790, acc.: 99.22%] [G loss: 4.661876]
8/8 [==============================] - 0s 4ms/step
154 [D loss: 0.011412, acc.: 100.00%] [G loss: 4.662127]
8/8 [==============================] - 0s 4ms/step
155 [D loss: 0.009596, acc.: 99.61%] [G loss: 4.711688]
8/8 [==============================] - 0s 4ms/step
156 [D loss: 0.011153, acc.: 99.80%] [G loss: 4.736183]
8/8 [==============================] - 0s 4ms/step
157 [D loss: 0.010168, acc.: 99.61%] [G loss: 4.783623]
8/8 [==============================] - 0s 4ms/step
158 [D loss: 0.008485, acc.: 99.80%] [G loss: 4.832392]
8/8 [==============================] - 0s 4ms/step
159 [D loss: 0.005605, acc.: 100.00%] [G loss: 4.900718]
8/8 [==============================] - 0s 4ms/step
160 [D loss: 0.019213, acc.: 99.61%] [G loss: 4.892053]
8/8 [==============================] - 0s 4ms/step
161 [D loss: 0.006786, acc.: 99.80%] [G loss: 4.938093]
8/8 [==============================] - 0s 4ms/step
162 [D loss: 0.008919, acc.: 99.80%] [G loss: 4.968928]
8/8 [==============================] - 0s 4ms/step
163 [D loss: 0.005244, acc.: 100.00%] [G loss: 5.023521]
8/8 [==============================] - 0s 4ms/step
164 [D loss: 0.009886, acc.: 99.80%] [G loss: 5.023648]
8/8 [==============================] - 0s 4ms/step
165 [D loss: 0.005258, acc.: 100.00%] [G loss: 5.073984]
8/8 [==============================] - 0s 4ms/step
166 [D loss: 0.009880, acc.: 99.80%] [G loss: 5.082787]
8/8 [==============================] - 0s 4ms/step
167 [D loss: 0.004779, acc.: 100.00%] [G loss: 5.130447]
8/8 [==============================] - 0s 4ms/step
168 [D loss: 0.016624, acc.: 99.61%] [G loss: 5.077349]
8/8 [==============================] - 0s 4ms/step
169 [D loss: 0.005451, acc.: 99.80%] [G loss: 5.145830]
8/8 [==============================] - 0s 4ms/step
170 [D loss: 0.003374, acc.: 100.00%] [G loss: 5.224092]
8/8 [==============================] - 0s 4ms/step
171 [D loss: 0.012264, acc.: 99.61%] [G loss: 5.175414]
8/8 [==============================] - 0s 4ms/step
172 [D loss: 0.028934, acc.: 99.41%] [G loss: 4.967057]
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173 [D loss: 0.007985, acc.: 99.61%] [G loss: 5.074146]
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174 [D loss: 0.004273, acc.: 100.00%] [G loss: 5.202724]
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175 [D loss: 0.006093, acc.: 99.80%] [G loss: 5.234032]
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176 [D loss: 0.003363, acc.: 100.00%] [G loss: 5.295587]
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177 [D loss: 0.011493, acc.: 99.61%] [G loss: 5.231290]
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178 [D loss: 0.002833, acc.: 100.00%] [G loss: 5.327752]
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179 [D loss: 0.013961, acc.: 99.41%] [G loss: 5.255333]
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180 [D loss: 0.003519, acc.: 100.00%] [G loss: 5.333635]
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181 [D loss: 0.003574, acc.: 100.00%] [G loss: 5.394101]
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182 [D loss: 0.002813, acc.: 100.00%] [G loss: 5.453846]
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183 [D loss: 0.005612, acc.: 99.80%] [G loss: 5.444089]
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184 [D loss: 0.003865, acc.: 100.00%] [G loss: 5.480702]
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185 [D loss: 0.009259, acc.: 99.80%] [G loss: 5.449959]
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186 [D loss: 0.010010, acc.: 99.61%] [G loss: 5.408784]
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187 [D loss: 0.002909, acc.: 100.00%] [G loss: 5.491188]
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188 [D loss: 0.005682, acc.: 99.61%] [G loss: 5.488271]
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189 [D loss: 0.002402, acc.: 100.00%] [G loss: 5.545658]
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190 [D loss: 0.009907, acc.: 99.61%] [G loss: 5.506350]
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191 [D loss: 0.002390, acc.: 100.00%] [G loss: 5.580499]
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192 [D loss: 0.003292, acc.: 100.00%] [G loss: 5.608670]
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193 [D loss: 0.002646, acc.: 100.00%] [G loss: 5.648847]
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194 [D loss: 0.003601, acc.: 100.00%] [G loss: 5.670044]
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195 [D loss: 0.001940, acc.: 100.00%] [G loss: 5.727765]
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196 [D loss: 0.011275, acc.: 99.61%] [G loss: 5.656177]
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197 [D loss: 0.004203, acc.: 100.00%] [G loss: 5.680895]
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198 [D loss: 0.004520, acc.: 99.80%] [G loss: 5.703372]
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199 [D loss: 0.010792, acc.: 99.61%] [G loss: 5.596744]
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1/1 [==============================] - 0s 22ms/step
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201 [D loss: 0.003796, acc.: 100.00%] [G loss: 5.714411]
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203 [D loss: 0.002195, acc.: 100.00%] [G loss: 5.813238]
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204 [D loss: 0.001729, acc.: 100.00%] [G loss: 5.866764]
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205 [D loss: 0.002131, acc.: 100.00%] [G loss: 5.901654]
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206 [D loss: 0.002511, acc.: 100.00%] [G loss: 5.923374]
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207 [D loss: 0.002917, acc.: 100.00%] [G loss: 5.933066]
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208 [D loss: 0.007348, acc.: 99.80%] [G loss: 5.904918]
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209 [D loss: 0.003185, acc.: 100.00%] [G loss: 5.929832]
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210 [D loss: 0.002456, acc.: 100.00%] [G loss: 5.962925]
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211 [D loss: 0.001844, acc.: 100.00%] [G loss: 5.998027]
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212 [D loss: 0.003023, acc.: 99.80%] [G loss: 5.999128]
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213 [D loss: 0.001281, acc.: 100.00%] [G loss: 6.047000]
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214 [D loss: 0.002807, acc.: 100.00%] [G loss: 6.060017]
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215 [D loss: 0.016116, acc.: 99.61%] [G loss: 5.938647]
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216 [D loss: 0.007130, acc.: 99.80%] [G loss: 5.925209]
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217 [D loss: 0.001532, acc.: 100.00%] [G loss: 6.046000]
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218 [D loss: 0.001660, acc.: 100.00%] [G loss: 6.099531]
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219 [D loss: 0.005359, acc.: 99.80%] [G loss: 6.034268]
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220 [D loss: 0.001580, acc.: 100.00%] [G loss: 6.082599]
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221 [D loss: 0.009490, acc.: 99.61%] [G loss: 5.855836]
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222 [D loss: 0.001832, acc.: 100.00%] [G loss: 6.037804]
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223 [D loss: 0.004306, acc.: 100.00%] [G loss: 6.005954]
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224 [D loss: 0.004148, acc.: 99.80%] [G loss: 5.963941]
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225 [D loss: 0.004741, acc.: 99.80%] [G loss: 5.867774]
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226 [D loss: 0.003341, acc.: 99.80%] [G loss: 5.964692]
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227 [D loss: 0.001280, acc.: 100.00%] [G loss: 6.111133]
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228 [D loss: 0.002872, acc.: 99.80%] [G loss: 6.115811]
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229 [D loss: 0.001263, acc.: 100.00%] [G loss: 6.160643]
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230 [D loss: 0.001240, acc.: 100.00%] [G loss: 6.205366]
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231 [D loss: 0.003708, acc.: 99.80%] [G loss: 6.191920]
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232 [D loss: 0.001296, acc.: 100.00%] [G loss: 6.229453]
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233 [D loss: 0.002013, acc.: 100.00%] [G loss: 6.238223]
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234 [D loss: 0.001138, acc.: 100.00%] [G loss: 6.275677]
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235 [D loss: 0.001139, acc.: 100.00%] [G loss: 6.314731]
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236 [D loss: 0.000895, acc.: 100.00%] [G loss: 6.363868]
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237 [D loss: 0.000908, acc.: 100.00%] [G loss: 6.411184]
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238 [D loss: 0.000872, acc.: 100.00%] [G loss: 6.454814]
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239 [D loss: 0.008477, acc.: 99.61%] [G loss: 6.217574]
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240 [D loss: 0.001111, acc.: 100.00%] [G loss: 6.382487]
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241 [D loss: 0.000933, acc.: 100.00%] [G loss: 6.449363]
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242 [D loss: 0.002711, acc.: 99.80%] [G loss: 6.417880]
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243 [D loss: 0.000974, acc.: 100.00%] [G loss: 6.460943]
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244 [D loss: 0.001246, acc.: 100.00%] [G loss: 6.487059]
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245 [D loss: 0.000777, acc.: 100.00%] [G loss: 6.526793]
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246 [D loss: 0.000744, acc.: 100.00%] [G loss: 6.568623]
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247 [D loss: 0.000694, acc.: 100.00%] [G loss: 6.611835]
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248 [D loss: 0.001932, acc.: 100.00%] [G loss: 6.590963]
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249 [D loss: 0.003306, acc.: 99.80%] [G loss: 6.509777]
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251 [D loss: 0.000786, acc.: 100.00%] [G loss: 6.576392]
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253 [D loss: 0.000648, acc.: 100.00%] [G loss: 6.680015]
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254 [D loss: 0.000698, acc.: 100.00%] [G loss: 6.716817]
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257 [D loss: 0.000595, acc.: 100.00%] [G loss: 6.784338]
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258 [D loss: 0.001200, acc.: 100.00%] [G loss: 6.787699]
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259 [D loss: 0.000797, acc.: 100.00%] [G loss: 6.801893]
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260 [D loss: 0.000643, acc.: 100.00%] [G loss: 6.827165]
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261 [D loss: 0.000674, acc.: 100.00%] [G loss: 6.851641]
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262 [D loss: 0.000553, acc.: 100.00%] [G loss: 6.882504]
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263 [D loss: 0.001077, acc.: 100.00%] [G loss: 6.878248]
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264 [D loss: 0.001941, acc.: 100.00%] [G loss: 6.820272]
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265 [D loss: 0.000537, acc.: 100.00%] [G loss: 6.896883]
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266 [D loss: 0.001591, acc.: 100.00%] [G loss: 6.868144]
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267 [D loss: 0.000523, acc.: 100.00%] [G loss: 6.906584]
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268 [D loss: 0.001023, acc.: 100.00%] [G loss: 6.909379]
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269 [D loss: 0.000497, acc.: 100.00%] [G loss: 6.940967]
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270 [D loss: 0.000659, acc.: 100.00%] [G loss: 6.962834]
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271 [D loss: 0.000605, acc.: 100.00%] [G loss: 6.984572]
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272 [D loss: 0.000469, acc.: 100.00%] [G loss: 7.013912]
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273 [D loss: 0.000876, acc.: 100.00%] [G loss: 7.014969]
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274 [D loss: 0.000587, acc.: 100.00%] [G loss: 7.042204]
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275 [D loss: 0.009951, acc.: 99.80%] [G loss: 6.588177]
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276 [D loss: 0.002015, acc.: 100.00%] [G loss: 6.814444]
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277 [D loss: 0.001440, acc.: 100.00%] [G loss: 6.886340]
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278 [D loss: 0.000715, acc.: 100.00%] [G loss: 6.962970]
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279 [D loss: 0.000739, acc.: 100.00%] [G loss: 6.992759]
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280 [D loss: 0.000548, acc.: 100.00%] [G loss: 7.022276]
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281 [D loss: 0.000562, acc.: 100.00%] [G loss: 7.046343]
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282 [D loss: 0.000501, acc.: 100.00%] [G loss: 7.073689]
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283 [D loss: 0.002899, acc.: 99.80%] [G loss: 6.971854]
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284 [D loss: 0.000501, acc.: 100.00%] [G loss: 7.029747]
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285 [D loss: 0.000439, acc.: 100.00%] [G loss: 7.073841]
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286 [D loss: 0.000534, acc.: 100.00%] [G loss: 7.099767]
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287 [D loss: 0.000425, acc.: 100.00%] [G loss: 7.129079]
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288 [D loss: 0.000403, acc.: 100.00%] [G loss: 7.159118]
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289 [D loss: 0.000420, acc.: 100.00%] [G loss: 7.186702]
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290 [D loss: 0.000639, acc.: 100.00%] [G loss: 7.200877]
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291 [D loss: 0.000926, acc.: 100.00%] [G loss: 7.184220]
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292 [D loss: 0.003164, acc.: 99.80%] [G loss: 6.910556]
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293 [D loss: 0.000665, acc.: 100.00%] [G loss: 7.111351]
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294 [D loss: 0.000404, acc.: 100.00%] [G loss: 7.183720]
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295 [D loss: 0.000382, acc.: 100.00%] [G loss: 7.220705]
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296 [D loss: 0.000666, acc.: 100.00%] [G loss: 7.224011]
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297 [D loss: 0.000419, acc.: 100.00%] [G loss: 7.242802]
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298 [D loss: 0.000419, acc.: 100.00%] [G loss: 7.264287]
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301 [D loss: 0.000405, acc.: 100.00%] [G loss: 7.266088]
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302 [D loss: 0.000398, acc.: 100.00%] [G loss: 7.294142]
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303 [D loss: 0.006017, acc.: 99.80%] [G loss: 6.737983]
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304 [D loss: 0.000583, acc.: 100.00%] [G loss: 7.099529]
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305 [D loss: 0.000396, acc.: 100.00%] [G loss: 7.247538]
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306 [D loss: 0.000459, acc.: 100.00%] [G loss: 7.283563]
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307 [D loss: 0.000386, acc.: 100.00%] [G loss: 7.310865]
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308 [D loss: 0.001856, acc.: 99.80%] [G loss: 7.190846]
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309 [D loss: 0.000386, acc.: 100.00%] [G loss: 7.239584]
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310 [D loss: 0.000351, acc.: 100.00%] [G loss: 7.299057]
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311 [D loss: 0.001811, acc.: 99.80%] [G loss: 7.242061]
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312 [D loss: 0.000369, acc.: 100.00%] [G loss: 7.291742]
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313 [D loss: 0.000349, acc.: 100.00%] [G loss: 7.327665]
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314 [D loss: 0.000325, acc.: 100.00%] [G loss: 7.358789]
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315 [D loss: 0.000318, acc.: 100.00%] [G loss: 7.386910]
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316 [D loss: 0.000365, acc.: 100.00%] [G loss: 7.410222]
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317 [D loss: 0.000357, acc.: 100.00%] [G loss: 7.430432]
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318 [D loss: 0.000337, acc.: 100.00%] [G loss: 7.450970]
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319 [D loss: 0.000331, acc.: 100.00%] [G loss: 7.471398]
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320 [D loss: 0.000288, acc.: 100.00%] [G loss: 7.494704]
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321 [D loss: 0.000913, acc.: 100.00%] [G loss: 7.460594]
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322 [D loss: 0.000299, acc.: 100.00%] [G loss: 7.471805]
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323 [D loss: 0.000289, acc.: 100.00%] [G loss: 7.495992]
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324 [D loss: 0.000347, acc.: 100.00%] [G loss: 7.514065]
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325 [D loss: 0.000276, acc.: 100.00%] [G loss: 7.536086]
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326 [D loss: 0.000317, acc.: 100.00%] [G loss: 7.555938]
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327 [D loss: 0.000477, acc.: 100.00%] [G loss: 7.559678]
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328 [D loss: 0.000287, acc.: 100.00%] [G loss: 7.576630]
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329 [D loss: 0.000262, acc.: 100.00%] [G loss: 7.598145]
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330 [D loss: 0.000959, acc.: 100.00%] [G loss: 7.563973]
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331 [D loss: 0.000532, acc.: 100.00%] [G loss: 7.568239]
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332 [D loss: 0.000311, acc.: 100.00%] [G loss: 7.594288]
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333 [D loss: 0.000250, acc.: 100.00%] [G loss: 7.618706]
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334 [D loss: 0.004624, acc.: 99.80%] [G loss: 7.074013]
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335 [D loss: 0.000404, acc.: 100.00%] [G loss: 7.459785]
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336 [D loss: 0.000276, acc.: 100.00%] [G loss: 7.567578]
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337 [D loss: 0.000275, acc.: 100.00%] [G loss: 7.602401]
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338 [D loss: 0.000556, acc.: 100.00%] [G loss: 7.599141]
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339 [D loss: 0.000449, acc.: 100.00%] [G loss: 7.597227]
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340 [D loss: 0.000430, acc.: 100.00%] [G loss: 7.596078]
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341 [D loss: 0.000326, acc.: 100.00%] [G loss: 7.613439]
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342 [D loss: 0.000386, acc.: 100.00%] [G loss: 7.623041]
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343 [D loss: 0.001105, acc.: 100.00%] [G loss: 7.539719]
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344 [D loss: 0.002111, acc.: 99.80%] [G loss: 7.125700]
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345 [D loss: 0.002120, acc.: 100.00%] [G loss: 7.040378]
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346 [D loss: 0.000403, acc.: 100.00%] [G loss: 7.450627]
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347 [D loss: 0.000431, acc.: 100.00%] [G loss: 7.382703]
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348 [D loss: 3.360719, acc.: 58.59%] [G loss: 20.945211]
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349 [D loss: 12.836993, acc.: 32.81%] [G loss: 19.115761]
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350 [D loss: 9.511470, acc.: 28.52%] [G loss: 4.342344]
1/1 [==============================] - 0s 33ms/step
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351 [D loss: 2.065933, acc.: 50.00%] [G loss: 3.983003]
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352 [D loss: 0.580725, acc.: 49.41%] [G loss: 3.870939]
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353 [D loss: 0.413525, acc.: 88.09%] [G loss: 4.364143]
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354 [D loss: 0.751339, acc.: 53.91%] [G loss: 1.393632]
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355 [D loss: 0.838173, acc.: 44.53%] [G loss: 0.504700]
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356 [D loss: 0.752516, acc.: 45.12%] [G loss: 0.591786]
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357 [D loss: 0.700809, acc.: 48.83%] [G loss: 0.671433]
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358 [D loss: 0.676235, acc.: 44.73%] [G loss: 0.695880]
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359 [D loss: 0.655594, acc.: 43.36%] [G loss: 0.724544]
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360 [D loss: 0.635617, acc.: 78.32%] [G loss: 0.755882]
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361 [D loss: 0.622548, acc.: 81.84%] [G loss: 0.784440]
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362 [D loss: 0.592870, acc.: 81.45%] [G loss: 0.807834]
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363 [D loss: 0.581836, acc.: 80.66%] [G loss: 0.829903]
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364 [D loss: 0.562347, acc.: 82.42%] [G loss: 0.926793]
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365 [D loss: 0.511638, acc.: 82.03%] [G loss: 0.997475]
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366 [D loss: 0.491861, acc.: 86.52%] [G loss: 0.991292]
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367 [D loss: 0.475987, acc.: 85.16%] [G loss: 1.033025]
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368 [D loss: 0.439130, acc.: 85.74%] [G loss: 1.115015]
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369 [D loss: 0.452186, acc.: 79.10%] [G loss: 1.339795]
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370 [D loss: 0.365987, acc.: 88.67%] [G loss: 1.648614]
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371 [D loss: 0.321434, acc.: 89.84%] [G loss: 1.853403]
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372 [D loss: 0.270533, acc.: 92.19%] [G loss: 2.042455]
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373 [D loss: 0.221786, acc.: 93.55%] [G loss: 2.115989]
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374 [D loss: 0.198752, acc.: 93.36%] [G loss: 2.045895]
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375 [D loss: 0.160443, acc.: 95.90%] [G loss: 2.214826]
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376 [D loss: 0.148208, acc.: 96.09%] [G loss: 2.426265]
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377 [D loss: 0.123550, acc.: 96.88%] [G loss: 2.768693]
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378 [D loss: 0.417196, acc.: 80.47%] [G loss: 3.868781]
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379 [D loss: 1.519645, acc.: 55.47%] [G loss: 7.829711]
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380 [D loss: 4.959661, acc.: 4.69%] [G loss: 1.761285]
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381 [D loss: 1.130495, acc.: 38.87%] [G loss: 3.116590]
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382 [D loss: 0.639278, acc.: 60.55%] [G loss: 2.038987]
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383 [D loss: 0.669149, acc.: 58.59%] [G loss: 1.464421]
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384 [D loss: 0.697344, acc.: 50.78%] [G loss: 1.189178]
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385 [D loss: 0.665307, acc.: 58.20%] [G loss: 1.192241]
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386 [D loss: 0.670923, acc.: 59.77%] [G loss: 1.271233]
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387 [D loss: 0.614189, acc.: 63.28%] [G loss: 1.325336]
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388 [D loss: 0.681706, acc.: 59.18%] [G loss: 0.936329]
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389 [D loss: 0.698855, acc.: 50.39%] [G loss: 0.739527]
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390 [D loss: 0.675946, acc.: 55.86%] [G loss: 0.730792]
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391 [D loss: 0.632129, acc.: 65.04%] [G loss: 0.756533]
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392 [D loss: 0.602011, acc.: 74.02%] [G loss: 0.786722]
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393 [D loss: 0.589058, acc.: 74.80%] [G loss: 0.826536]
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394 [D loss: 0.542868, acc.: 79.30%] [G loss: 0.868467]
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395 [D loss: 0.557657, acc.: 80.08%] [G loss: 0.918378]
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396 [D loss: 0.523802, acc.: 83.59%] [G loss: 0.940565]
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397 [D loss: 0.477943, acc.: 87.50%] [G loss: 1.013881]
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398 [D loss: 0.482478, acc.: 85.74%] [G loss: 1.053840]
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399 [D loss: 0.468680, acc.: 86.72%] [G loss: 1.144286]
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400 [D loss: 0.438301, acc.: 86.72%] [G loss: 1.166108]
1/1 [==============================] - 0s 24ms/step
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401 [D loss: 0.419874, acc.: 86.52%] [G loss: 1.207935]
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402 [D loss: 0.431130, acc.: 85.16%] [G loss: 1.205042]
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403 [D loss: 0.391067, acc.: 88.28%] [G loss: 1.251640]
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404 [D loss: 0.387043, acc.: 88.28%] [G loss: 1.263149]
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405 [D loss: 0.394088, acc.: 88.28%] [G loss: 1.305933]
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406 [D loss: 0.352829, acc.: 91.60%] [G loss: 1.361504]
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407 [D loss: 0.346534, acc.: 90.43%] [G loss: 1.425342]
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408 [D loss: 0.290712, acc.: 91.99%] [G loss: 1.537271]
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409 [D loss: 0.297899, acc.: 91.02%] [G loss: 1.655460]
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410 [D loss: 0.307047, acc.: 91.02%] [G loss: 1.705049]
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411 [D loss: 0.276734, acc.: 91.41%] [G loss: 1.752151]
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412 [D loss: 0.248966, acc.: 92.77%] [G loss: 1.832212]
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413 [D loss: 0.238794, acc.: 93.16%] [G loss: 1.865643]
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414 [D loss: 0.205528, acc.: 95.31%] [G loss: 1.990229]
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415 [D loss: 0.193874, acc.: 95.12%] [G loss: 2.038136]
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416 [D loss: 0.194398, acc.: 95.70%] [G loss: 2.068712]
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417 [D loss: 0.185502, acc.: 95.12%] [G loss: 2.094707]
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418 [D loss: 0.153427, acc.: 97.46%] [G loss: 2.175838]
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419 [D loss: 0.187798, acc.: 95.12%] [G loss: 2.281047]
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420 [D loss: 0.241029, acc.: 91.99%] [G loss: 2.238295]
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421 [D loss: 0.214929, acc.: 93.36%] [G loss: 2.136876]
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422 [D loss: 0.288961, acc.: 87.30%] [G loss: 2.186164]
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423 [D loss: 0.291178, acc.: 87.89%] [G loss: 2.774390]
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424 [D loss: 0.249074, acc.: 91.41%] [G loss: 3.039091]
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425 [D loss: 0.547080, acc.: 80.66%] [G loss: 3.126516]
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426 [D loss: 0.814384, acc.: 68.95%] [G loss: 3.915556]
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427 [D loss: 0.620935, acc.: 72.85%] [G loss: 3.719452]
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428 [D loss: 0.829986, acc.: 58.01%] [G loss: 3.521646]
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429 [D loss: 0.927730, acc.: 52.73%] [G loss: 2.992450]
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430 [D loss: 0.623307, acc.: 66.99%] [G loss: 2.686594]
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431 [D loss: 0.590911, acc.: 69.73%] [G loss: 1.988041]
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432 [D loss: 0.551592, acc.: 72.85%] [G loss: 1.550842]
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433 [D loss: 0.555716, acc.: 73.05%] [G loss: 1.702067]
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434 [D loss: 0.441990, acc.: 81.84%] [G loss: 2.014553]
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435 [D loss: 0.415082, acc.: 83.79%] [G loss: 1.873863]
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436 [D loss: 0.355130, acc.: 87.70%] [G loss: 1.902963]
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437 [D loss: 0.281119, acc.: 92.77%] [G loss: 2.005052]
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438 [D loss: 0.287415, acc.: 92.38%] [G loss: 1.963834]
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439 [D loss: 0.272572, acc.: 93.75%] [G loss: 1.874971]
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440 [D loss: 0.272374, acc.: 93.36%] [G loss: 1.773346]
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441 [D loss: 0.286637, acc.: 93.75%] [G loss: 1.838194]
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442 [D loss: 0.250245, acc.: 92.97%] [G loss: 1.961728]
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443 [D loss: 0.266024, acc.: 90.82%] [G loss: 2.189203]
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444 [D loss: 0.247916, acc.: 91.99%] [G loss: 2.055641]
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445 [D loss: 0.281625, acc.: 91.60%] [G loss: 2.295138]
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446 [D loss: 0.236337, acc.: 94.53%] [G loss: 2.043126]
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447 [D loss: 0.345118, acc.: 87.50%] [G loss: 1.894065]
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448 [D loss: 0.667941, acc.: 64.45%] [G loss: 2.484274]
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449 [D loss: 0.334550, acc.: 86.91%] [G loss: 2.292503]
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450 [D loss: 0.677768, acc.: 64.84%] [G loss: 1.946197]
1/1 [==============================] - 0s 26ms/step
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451 [D loss: 0.732835, acc.: 58.79%] [G loss: 3.281750]
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452 [D loss: 0.526513, acc.: 80.27%] [G loss: 2.365258]
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453 [D loss: 0.449617, acc.: 83.01%] [G loss: 2.093226]
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454 [D loss: 0.417342, acc.: 83.79%] [G loss: 1.601248]
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455 [D loss: 0.434481, acc.: 78.12%] [G loss: 1.871627]
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456 [D loss: 0.413544, acc.: 84.38%] [G loss: 2.150262]
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457 [D loss: 0.447290, acc.: 80.66%] [G loss: 2.180368]
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458 [D loss: 0.426184, acc.: 82.62%] [G loss: 2.398721]
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459 [D loss: 0.408197, acc.: 84.96%] [G loss: 2.282715]
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460 [D loss: 0.367638, acc.: 86.33%] [G loss: 1.979842]
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461 [D loss: 0.357020, acc.: 86.91%] [G loss: 2.051642]
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462 [D loss: 0.406294, acc.: 84.38%] [G loss: 2.033915]
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463 [D loss: 0.444702, acc.: 80.66%] [G loss: 2.686184]
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464 [D loss: 0.324751, acc.: 86.52%] [G loss: 2.572681]
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465 [D loss: 0.411269, acc.: 84.57%] [G loss: 2.369923]
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466 [D loss: 0.367875, acc.: 85.94%] [G loss: 1.961474]
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467 [D loss: 0.401856, acc.: 81.64%] [G loss: 1.889411]
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468 [D loss: 0.406224, acc.: 82.03%] [G loss: 2.089892]
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469 [D loss: 0.443402, acc.: 81.05%] [G loss: 2.080624]
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470 [D loss: 0.375500, acc.: 84.38%] [G loss: 2.228325]
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471 [D loss: 0.432103, acc.: 80.86%] [G loss: 2.518422]
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472 [D loss: 0.449452, acc.: 80.08%] [G loss: 2.675562]
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473 [D loss: 0.379808, acc.: 81.45%] [G loss: 2.402563]
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474 [D loss: 0.304535, acc.: 90.23%] [G loss: 2.162760]
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475 [D loss: 0.367948, acc.: 84.57%] [G loss: 1.974156]
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476 [D loss: 0.403470, acc.: 83.40%] [G loss: 2.077420]
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477 [D loss: 0.365525, acc.: 84.77%] [G loss: 2.395696]
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478 [D loss: 0.364023, acc.: 86.52%] [G loss: 2.687546]
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479 [D loss: 0.328533, acc.: 86.52%] [G loss: 2.852625]
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480 [D loss: 0.444581, acc.: 83.40%] [G loss: 2.640244]
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481 [D loss: 0.560355, acc.: 76.37%] [G loss: 2.220821]
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482 [D loss: 0.644338, acc.: 66.21%] [G loss: 2.460573]
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483 [D loss: 0.510952, acc.: 75.39%] [G loss: 2.539262]
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484 [D loss: 0.579848, acc.: 74.02%] [G loss: 2.039177]
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485 [D loss: 0.495456, acc.: 76.56%] [G loss: 2.136342]
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486 [D loss: 0.463106, acc.: 79.30%] [G loss: 2.296431]
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487 [D loss: 0.479903, acc.: 77.54%] [G loss: 2.168450]
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488 [D loss: 0.441262, acc.: 81.84%] [G loss: 1.897991]
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489 [D loss: 0.408991, acc.: 82.42%] [G loss: 1.752750]
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490 [D loss: 0.499363, acc.: 75.39%] [G loss: 1.630745]
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491 [D loss: 0.419181, acc.: 81.64%] [G loss: 2.241057]
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492 [D loss: 0.483838, acc.: 78.12%] [G loss: 1.918487]
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493 [D loss: 0.473540, acc.: 77.15%] [G loss: 1.861685]
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494 [D loss: 0.520278, acc.: 76.17%] [G loss: 1.715376]
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495 [D loss: 0.581228, acc.: 70.90%] [G loss: 2.045230]
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496 [D loss: 0.514160, acc.: 77.15%] [G loss: 2.179662]
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497 [D loss: 0.546508, acc.: 75.20%] [G loss: 1.827954]
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498 [D loss: 0.634448, acc.: 69.73%] [G loss: 1.617274]
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499 [D loss: 0.648272, acc.: 66.80%] [G loss: 1.868090]
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500 [D loss: 0.575377, acc.: 72.85%] [G loss: 2.117837]
1/1 [==============================] - 0s 28ms/step
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501 [D loss: 0.589683, acc.: 71.48%] [G loss: 1.563710]
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502 [D loss: 0.588418, acc.: 69.92%] [G loss: 1.366688]
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503 [D loss: 0.676964, acc.: 65.62%] [G loss: 1.727556]
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504 [D loss: 0.625969, acc.: 66.80%] [G loss: 2.071343]
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505 [D loss: 0.621243, acc.: 70.70%] [G loss: 1.490109]
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506 [D loss: 0.590176, acc.: 70.51%] [G loss: 1.186290]
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507 [D loss: 0.708744, acc.: 62.89%] [G loss: 1.449518]
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508 [D loss: 0.592886, acc.: 69.92%] [G loss: 1.767521]
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509 [D loss: 0.609602, acc.: 70.12%] [G loss: 1.402316]
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510 [D loss: 0.628379, acc.: 63.28%] [G loss: 1.211555]
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511 [D loss: 0.613482, acc.: 66.80%] [G loss: 1.252814]
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512 [D loss: 0.655804, acc.: 66.02%] [G loss: 1.464723]
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513 [D loss: 0.592106, acc.: 71.09%] [G loss: 1.313738]
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514 [D loss: 0.609502, acc.: 68.36%] [G loss: 1.130028]
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515 [D loss: 0.716908, acc.: 59.18%] [G loss: 1.225405]
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516 [D loss: 0.655726, acc.: 64.45%] [G loss: 1.228504]
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517 [D loss: 0.658204, acc.: 65.43%] [G loss: 1.230226]
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518 [D loss: 0.633230, acc.: 66.80%] [G loss: 1.169178]
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519 [D loss: 0.758976, acc.: 53.32%] [G loss: 1.189121]
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520 [D loss: 0.645867, acc.: 64.45%] [G loss: 1.150042]
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521 [D loss: 0.623519, acc.: 67.38%] [G loss: 1.148745]
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522 [D loss: 0.696716, acc.: 59.18%] [G loss: 1.101254]
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523 [D loss: 0.685399, acc.: 59.18%] [G loss: 1.164900]
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524 [D loss: 0.673074, acc.: 63.28%] [G loss: 1.098577]
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525 [D loss: 0.679125, acc.: 62.30%] [G loss: 1.078652]
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526 [D loss: 0.687798, acc.: 58.98%] [G loss: 1.054543]
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527 [D loss: 0.691890, acc.: 58.79%] [G loss: 1.091180]
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528 [D loss: 0.683946, acc.: 61.13%] [G loss: 1.079379]
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529 [D loss: 0.641077, acc.: 63.48%] [G loss: 1.045961]
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530 [D loss: 0.675021, acc.: 61.91%] [G loss: 1.040898]
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531 [D loss: 0.712736, acc.: 58.98%] [G loss: 0.967738]
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532 [D loss: 0.694193, acc.: 60.94%] [G loss: 1.005624]
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533 [D loss: 0.677146, acc.: 58.79%] [G loss: 0.959772]
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534 [D loss: 0.712918, acc.: 56.05%] [G loss: 1.056139]
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535 [D loss: 0.693593, acc.: 62.30%] [G loss: 0.959679]
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536 [D loss: 0.708066, acc.: 55.47%] [G loss: 0.913068]
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537 [D loss: 0.694909, acc.: 57.62%] [G loss: 0.983726]
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538 [D loss: 0.678908, acc.: 56.05%] [G loss: 0.977016]
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539 [D loss: 0.676676, acc.: 62.89%] [G loss: 0.946593]
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540 [D loss: 0.689073, acc.: 59.57%] [G loss: 0.888323]
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541 [D loss: 0.739251, acc.: 50.78%] [G loss: 0.876305]
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542 [D loss: 0.734885, acc.: 50.78%] [G loss: 0.893857]
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543 [D loss: 0.685064, acc.: 58.20%] [G loss: 0.901374]
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544 [D loss: 0.699738, acc.: 55.66%] [G loss: 0.907404]
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545 [D loss: 0.698274, acc.: 56.05%] [G loss: 0.866415]
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546 [D loss: 0.701251, acc.: 59.18%] [G loss: 0.909434]
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547 [D loss: 0.709528, acc.: 52.54%] [G loss: 0.901958]
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548 [D loss: 0.702255, acc.: 55.66%] [G loss: 0.838533]
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549 [D loss: 0.721371, acc.: 49.41%] [G loss: 0.850739]
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550 [D loss: 0.718373, acc.: 53.12%] [G loss: 0.855640]
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551 [D loss: 0.732285, acc.: 47.07%] [G loss: 0.808851]
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552 [D loss: 0.733626, acc.: 46.88%] [G loss: 0.825737]
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553 [D loss: 0.705623, acc.: 53.12%] [G loss: 0.809740]
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554 [D loss: 0.738851, acc.: 47.66%] [G loss: 0.792859]
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555 [D loss: 0.712023, acc.: 53.32%] [G loss: 0.838131]
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556 [D loss: 0.714340, acc.: 50.98%] [G loss: 0.824968]
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557 [D loss: 0.725681, acc.: 52.15%] [G loss: 0.804888]
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558 [D loss: 0.738244, acc.: 47.85%] [G loss: 0.804306]
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559 [D loss: 0.695045, acc.: 52.93%] [G loss: 0.814471]
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560 [D loss: 0.723512, acc.: 49.80%] [G loss: 0.795953]
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561 [D loss: 0.730965, acc.: 48.83%] [G loss: 0.815831]
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562 [D loss: 0.739223, acc.: 47.66%] [G loss: 0.766204]
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563 [D loss: 0.722135, acc.: 50.00%] [G loss: 0.783699]
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564 [D loss: 0.728423, acc.: 46.88%] [G loss: 0.781413]
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565 [D loss: 0.702997, acc.: 52.34%] [G loss: 0.809613]
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566 [D loss: 0.721296, acc.: 49.80%] [G loss: 0.796946]
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567 [D loss: 0.741946, acc.: 44.53%] [G loss: 0.770342]
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568 [D loss: 0.724017, acc.: 44.92%] [G loss: 0.775453]
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569 [D loss: 0.703865, acc.: 52.15%] [G loss: 0.785205]
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570 [D loss: 0.713694, acc.: 47.46%] [G loss: 0.799481]
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571 [D loss: 0.724128, acc.: 46.68%] [G loss: 0.766042]
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572 [D loss: 0.715054, acc.: 52.73%] [G loss: 0.757932]
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573 [D loss: 0.721553, acc.: 44.53%] [G loss: 0.786097]
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574 [D loss: 0.729845, acc.: 48.83%] [G loss: 0.784744]
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575 [D loss: 0.720184, acc.: 46.68%] [G loss: 0.757255]
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576 [D loss: 0.722147, acc.: 46.29%] [G loss: 0.763969]
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577 [D loss: 0.717591, acc.: 46.48%] [G loss: 0.762069]
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578 [D loss: 0.707993, acc.: 49.61%] [G loss: 0.771337]
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579 [D loss: 0.717709, acc.: 50.00%] [G loss: 0.765537]
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580 [D loss: 0.705745, acc.: 51.76%] [G loss: 0.731729]
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581 [D loss: 0.726960, acc.: 47.46%] [G loss: 0.750260]
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582 [D loss: 0.704700, acc.: 50.00%] [G loss: 0.759178]
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583 [D loss: 0.711938, acc.: 47.27%] [G loss: 0.750806]
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584 [D loss: 0.705295, acc.: 51.17%] [G loss: 0.773220]
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585 [D loss: 0.708409, acc.: 48.83%] [G loss: 0.740976]
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586 [D loss: 0.715196, acc.: 48.05%] [G loss: 0.769489]
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587 [D loss: 0.704803, acc.: 50.20%] [G loss: 0.749222]
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588 [D loss: 0.694762, acc.: 54.10%] [G loss: 0.762861]
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589 [D loss: 0.698306, acc.: 53.91%] [G loss: 0.757932]
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590 [D loss: 0.700784, acc.: 51.56%] [G loss: 0.762750]
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591 [D loss: 0.718140, acc.: 47.85%] [G loss: 0.775716]
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592 [D loss: 0.698063, acc.: 53.71%] [G loss: 0.756935]
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593 [D loss: 0.697116, acc.: 53.91%] [G loss: 0.747027]
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594 [D loss: 0.701436, acc.: 50.59%] [G loss: 0.742687]
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595 [D loss: 0.699934, acc.: 52.15%] [G loss: 0.746767]
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596 [D loss: 0.698173, acc.: 50.39%] [G loss: 0.741894]
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597 [D loss: 0.690880, acc.: 55.08%] [G loss: 0.744163]
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598 [D loss: 0.698510, acc.: 51.76%] [G loss: 0.751092]
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599 [D loss: 0.704158, acc.: 50.39%] [G loss: 0.756722]
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600 [D loss: 0.691997, acc.: 54.88%] [G loss: 0.743182]
1/1 [==============================] - 0s 30ms/step
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601 [D loss: 0.699381, acc.: 51.56%] [G loss: 0.754026]
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602 [D loss: 0.696654, acc.: 52.15%] [G loss: 0.740345]
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603 [D loss: 0.693482, acc.: 51.56%] [G loss: 0.753592]
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604 [D loss: 0.704284, acc.: 50.00%] [G loss: 0.754480]
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605 [D loss: 0.702270, acc.: 48.83%] [G loss: 0.742701]
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606 [D loss: 0.697809, acc.: 52.34%] [G loss: 0.753846]
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607 [D loss: 0.691878, acc.: 51.56%] [G loss: 0.751985]
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608 [D loss: 0.689120, acc.: 54.10%] [G loss: 0.756307]
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609 [D loss: 0.702780, acc.: 50.98%] [G loss: 0.747597]
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610 [D loss: 0.705404, acc.: 51.37%] [G loss: 0.759442]
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611 [D loss: 0.697887, acc.: 52.93%] [G loss: 0.749506]
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612 [D loss: 0.693380, acc.: 53.52%] [G loss: 0.740279]
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613 [D loss: 0.702829, acc.: 47.85%] [G loss: 0.739199]
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614 [D loss: 0.701916, acc.: 48.83%] [G loss: 0.736844]
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615 [D loss: 0.697369, acc.: 51.76%] [G loss: 0.740823]
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616 [D loss: 0.705871, acc.: 48.24%] [G loss: 0.736905]
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617 [D loss: 0.697218, acc.: 53.12%] [G loss: 0.733134]
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618 [D loss: 0.692561, acc.: 49.41%] [G loss: 0.728396]
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619 [D loss: 0.690749, acc.: 53.91%] [G loss: 0.730309]
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620 [D loss: 0.694227, acc.: 50.78%] [G loss: 0.738712]
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621 [D loss: 0.688653, acc.: 52.73%] [G loss: 0.737585]
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622 [D loss: 0.691442, acc.: 53.71%] [G loss: 0.759250]
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623 [D loss: 0.694446, acc.: 52.73%] [G loss: 0.738529]
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624 [D loss: 0.698249, acc.: 51.76%] [G loss: 0.745589]
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625 [D loss: 0.699847, acc.: 50.39%] [G loss: 0.734143]
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626 [D loss: 0.705809, acc.: 47.66%] [G loss: 0.724686]
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627 [D loss: 0.701951, acc.: 47.85%] [G loss: 0.732180]
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628 [D loss: 0.703074, acc.: 48.63%] [G loss: 0.738297]
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629 [D loss: 0.703486, acc.: 49.61%] [G loss: 0.749918]
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630 [D loss: 0.700672, acc.: 49.22%] [G loss: 0.753618]
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631 [D loss: 0.694288, acc.: 52.15%] [G loss: 0.735631]
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632 [D loss: 0.696215, acc.: 50.98%] [G loss: 0.742750]
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633 [D loss: 0.699928, acc.: 47.66%] [G loss: 0.725903]
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634 [D loss: 0.697093, acc.: 46.68%] [G loss: 0.739270]
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635 [D loss: 0.699716, acc.: 49.02%] [G loss: 0.744724]
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636 [D loss: 0.695702, acc.: 50.98%] [G loss: 0.743146]
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637 [D loss: 0.697989, acc.: 49.41%] [G loss: 0.742195]
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638 [D loss: 0.695302, acc.: 51.56%] [G loss: 0.734647]
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639 [D loss: 0.690280, acc.: 53.12%] [G loss: 0.730905]
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640 [D loss: 0.700958, acc.: 48.24%] [G loss: 0.722797]
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641 [D loss: 0.689024, acc.: 52.15%] [G loss: 0.735167]
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642 [D loss: 0.703287, acc.: 49.02%] [G loss: 0.726506]
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643 [D loss: 0.692472, acc.: 51.37%] [G loss: 0.732738]
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644 [D loss: 0.697073, acc.: 46.88%] [G loss: 0.740846]
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645 [D loss: 0.692801, acc.: 48.05%] [G loss: 0.731611]
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646 [D loss: 0.697538, acc.: 49.80%] [G loss: 0.726855]
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647 [D loss: 0.697296, acc.: 46.48%] [G loss: 0.729326]
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648 [D loss: 0.692185, acc.: 50.20%] [G loss: 0.736219]
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649 [D loss: 0.695756, acc.: 47.46%] [G loss: 0.720846]
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650 [D loss: 0.695166, acc.: 49.41%] [G loss: 0.725275]
1/1 [==============================] - 0s 28ms/step
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651 [D loss: 0.703024, acc.: 46.09%] [G loss: 0.731362]
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652 [D loss: 0.699771, acc.: 42.77%] [G loss: 0.720092]
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653 [D loss: 0.699112, acc.: 46.68%] [G loss: 0.716960]
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654 [D loss: 0.699376, acc.: 47.85%] [G loss: 0.714134]
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655 [D loss: 0.701773, acc.: 48.63%] [G loss: 0.728964]
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656 [D loss: 0.691982, acc.: 50.78%] [G loss: 0.729714]
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657 [D loss: 0.695120, acc.: 50.00%] [G loss: 0.720459]
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658 [D loss: 0.698836, acc.: 50.20%] [G loss: 0.732699]
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659 [D loss: 0.687828, acc.: 54.30%] [G loss: 0.725866]
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660 [D loss: 0.696651, acc.: 51.37%] [G loss: 0.723201]
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661 [D loss: 0.698564, acc.: 48.05%] [G loss: 0.713543]
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662 [D loss: 0.698136, acc.: 48.05%] [G loss: 0.714076]
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663 [D loss: 0.699310, acc.: 49.80%] [G loss: 0.735022]
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664 [D loss: 0.708222, acc.: 44.92%] [G loss: 0.723879]
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665 [D loss: 0.703366, acc.: 46.48%] [G loss: 0.724438]
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666 [D loss: 0.694209, acc.: 50.59%] [G loss: 0.717940]
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667 [D loss: 0.703142, acc.: 48.05%] [G loss: 0.720269]
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668 [D loss: 0.700189, acc.: 48.63%] [G loss: 0.716155]
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669 [D loss: 0.699280, acc.: 49.02%] [G loss: 0.735138]
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670 [D loss: 0.694325, acc.: 49.22%] [G loss: 0.743032]
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671 [D loss: 0.701231, acc.: 46.48%] [G loss: 0.737900]
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672 [D loss: 0.692745, acc.: 52.34%] [G loss: 0.724088]
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673 [D loss: 0.696942, acc.: 50.00%] [G loss: 0.733356]
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674 [D loss: 0.696537, acc.: 50.39%] [G loss: 0.722170]
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675 [D loss: 0.692561, acc.: 49.22%] [G loss: 0.745763]
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676 [D loss: 0.688015, acc.: 52.34%] [G loss: 0.740825]
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677 [D loss: 0.688097, acc.: 55.08%] [G loss: 0.752477]
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678 [D loss: 0.689292, acc.: 54.49%] [G loss: 0.733832]
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679 [D loss: 0.689643, acc.: 54.88%] [G loss: 0.735531]
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680 [D loss: 0.690396, acc.: 53.32%] [G loss: 0.739360]
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681 [D loss: 0.684196, acc.: 53.52%] [G loss: 0.740254]
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682 [D loss: 0.689704, acc.: 53.52%] [G loss: 0.735036]
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683 [D loss: 0.687444, acc.: 51.37%] [G loss: 0.743935]
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684 [D loss: 0.687423, acc.: 52.15%] [G loss: 0.734562]
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685 [D loss: 0.689376, acc.: 52.15%] [G loss: 0.727503]
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686 [D loss: 0.693306, acc.: 53.12%] [G loss: 0.723269]
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687 [D loss: 0.691985, acc.: 52.73%] [G loss: 0.718975]
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688 [D loss: 0.697308, acc.: 48.24%] [G loss: 0.730653]
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689 [D loss: 0.691972, acc.: 53.52%] [G loss: 0.725346]
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690 [D loss: 0.693932, acc.: 53.32%] [G loss: 0.739929]
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691 [D loss: 0.688292, acc.: 54.10%] [G loss: 0.740214]
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692 [D loss: 0.684908, acc.: 54.49%] [G loss: 0.741599]
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693 [D loss: 0.690940, acc.: 51.95%] [G loss: 0.751857]
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694 [D loss: 0.693255, acc.: 54.30%] [G loss: 0.734528]
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695 [D loss: 0.691066, acc.: 54.10%] [G loss: 0.725848]
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696 [D loss: 0.689255, acc.: 56.05%] [G loss: 0.729549]
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697 [D loss: 0.691119, acc.: 50.78%] [G loss: 0.714285]
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698 [D loss: 0.690365, acc.: 53.32%] [G loss: 0.742191]
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699 [D loss: 0.687845, acc.: 55.47%] [G loss: 0.740644]
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700 [D loss: 0.691419, acc.: 52.15%] [G loss: 0.728828]
1/1 [==============================] - 0s 23ms/step
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701 [D loss: 0.686671, acc.: 56.45%] [G loss: 0.729532]
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702 [D loss: 0.689722, acc.: 51.56%] [G loss: 0.719031]
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703 [D loss: 0.693143, acc.: 48.24%] [G loss: 0.715986]
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704 [D loss: 0.691105, acc.: 50.00%] [G loss: 0.715991]
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705 [D loss: 0.700094, acc.: 48.05%] [G loss: 0.725782]
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706 [D loss: 0.688236, acc.: 51.76%] [G loss: 0.719679]
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707 [D loss: 0.695064, acc.: 50.98%] [G loss: 0.723224]
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708 [D loss: 0.692782, acc.: 51.56%] [G loss: 0.716793]
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709 [D loss: 0.695688, acc.: 48.44%] [G loss: 0.729587]
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710 [D loss: 0.695500, acc.: 47.07%] [G loss: 0.726069]
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711 [D loss: 0.691631, acc.: 50.78%] [G loss: 0.712656]
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712 [D loss: 0.698018, acc.: 48.05%] [G loss: 0.724062]
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713 [D loss: 0.691686, acc.: 51.56%] [G loss: 0.734338]
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714 [D loss: 0.695531, acc.: 50.00%] [G loss: 0.711926]
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715 [D loss: 0.695600, acc.: 50.59%] [G loss: 0.721618]
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716 [D loss: 0.693138, acc.: 51.76%] [G loss: 0.718096]
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717 [D loss: 0.697874, acc.: 50.20%] [G loss: 0.712494]
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718 [D loss: 0.695970, acc.: 52.34%] [G loss: 0.713990]
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719 [D loss: 0.701007, acc.: 50.20%] [G loss: 0.714627]
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720 [D loss: 0.702833, acc.: 45.51%] [G loss: 0.719252]
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721 [D loss: 0.699511, acc.: 50.00%] [G loss: 0.724555]
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722 [D loss: 0.690866, acc.: 52.34%] [G loss: 0.721881]
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723 [D loss: 0.699879, acc.: 46.48%] [G loss: 0.720472]
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724 [D loss: 0.696975, acc.: 50.78%] [G loss: 0.721685]
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725 [D loss: 0.694812, acc.: 47.85%] [G loss: 0.714328]
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726 [D loss: 0.698711, acc.: 47.46%] [G loss: 0.720295]
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727 [D loss: 0.693407, acc.: 50.20%] [G loss: 0.718451]
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728 [D loss: 0.689557, acc.: 51.76%] [G loss: 0.731198]
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729 [D loss: 0.695832, acc.: 47.66%] [G loss: 0.722090]
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730 [D loss: 0.696738, acc.: 45.31%] [G loss: 0.732208]
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731 [D loss: 0.690530, acc.: 50.39%] [G loss: 0.731341]
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732 [D loss: 0.690603, acc.: 52.73%] [G loss: 0.727910]
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733 [D loss: 0.692982, acc.: 51.17%] [G loss: 0.705032]
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734 [D loss: 0.694485, acc.: 50.59%] [G loss: 0.732954]
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735 [D loss: 0.691635, acc.: 50.78%] [G loss: 0.737414]
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736 [D loss: 0.693769, acc.: 50.78%] [G loss: 0.727148]
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737 [D loss: 0.693928, acc.: 50.39%] [G loss: 0.720975]
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738 [D loss: 0.686825, acc.: 53.91%] [G loss: 0.722815]
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739 [D loss: 0.696073, acc.: 50.78%] [G loss: 0.714119]
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740 [D loss: 0.705219, acc.: 45.90%] [G loss: 0.714075]
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741 [D loss: 0.691505, acc.: 51.17%] [G loss: 0.717291]
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742 [D loss: 0.697027, acc.: 47.07%] [G loss: 0.728993]
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743 [D loss: 0.687161, acc.: 53.71%] [G loss: 0.722490]
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744 [D loss: 0.689628, acc.: 52.15%] [G loss: 0.709103]
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745 [D loss: 0.696758, acc.: 48.24%] [G loss: 0.708969]
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746 [D loss: 0.694516, acc.: 49.80%] [G loss: 0.704925]
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747 [D loss: 0.698087, acc.: 47.27%] [G loss: 0.708594]
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748 [D loss: 0.698556, acc.: 47.07%] [G loss: 0.716038]
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749 [D loss: 0.696121, acc.: 47.27%] [G loss: 0.720190]
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750 [D loss: 0.695068, acc.: 50.59%] [G loss: 0.721257]
1/1 [==============================] - 0s 30ms/step
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751 [D loss: 0.689277, acc.: 51.37%] [G loss: 0.726745]
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752 [D loss: 0.695251, acc.: 50.59%] [G loss: 0.718003]
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753 [D loss: 0.692309, acc.: 50.78%] [G loss: 0.718977]
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754 [D loss: 0.695323, acc.: 47.46%] [G loss: 0.711595]
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755 [D loss: 0.693718, acc.: 46.88%] [G loss: 0.721743]
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756 [D loss: 0.689245, acc.: 51.37%] [G loss: 0.725428]
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757 [D loss: 0.691303, acc.: 51.17%] [G loss: 0.719881]
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758 [D loss: 0.690722, acc.: 51.95%] [G loss: 0.724299]
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759 [D loss: 0.693043, acc.: 51.76%] [G loss: 0.717581]
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760 [D loss: 0.698097, acc.: 48.05%] [G loss: 0.710667]
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761 [D loss: 0.699275, acc.: 46.68%] [G loss: 0.709557]
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762 [D loss: 0.696269, acc.: 48.83%] [G loss: 0.711725]
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763 [D loss: 0.697152, acc.: 46.48%] [G loss: 0.716454]
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764 [D loss: 0.688588, acc.: 53.32%] [G loss: 0.711090]
8/8 [==============================] - 0s 4ms/step
765 [D loss: 0.694863, acc.: 49.41%] [G loss: 0.707355]
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766 [D loss: 0.690129, acc.: 52.34%] [G loss: 0.718963]
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767 [D loss: 0.694757, acc.: 48.63%] [G loss: 0.721781]
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768 [D loss: 0.693103, acc.: 47.85%] [G loss: 0.722480]
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769 [D loss: 0.696492, acc.: 46.88%] [G loss: 0.712316]
8/8 [==============================] - 0s 4ms/step
770 [D loss: 0.692372, acc.: 51.17%] [G loss: 0.704545]
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771 [D loss: 0.692550, acc.: 49.80%] [G loss: 0.701297]
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772 [D loss: 0.694163, acc.: 47.85%] [G loss: 0.702761]
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773 [D loss: 0.694900, acc.: 50.59%] [G loss: 0.702909]
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774 [D loss: 0.694500, acc.: 47.27%] [G loss: 0.713881]
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775 [D loss: 0.688562, acc.: 52.54%] [G loss: 0.714762]
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776 [D loss: 0.692815, acc.: 50.00%] [G loss: 0.716735]
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777 [D loss: 0.688290, acc.: 51.95%] [G loss: 0.713710]
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778 [D loss: 0.689846, acc.: 52.73%] [G loss: 0.713291]
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779 [D loss: 0.696747, acc.: 46.68%] [G loss: 0.708059]
8/8 [==============================] - 0s 4ms/step
780 [D loss: 0.695590, acc.: 47.27%] [G loss: 0.711913]
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781 [D loss: 0.695412, acc.: 46.68%] [G loss: 0.715459]
8/8 [==============================] - 0s 4ms/step
782 [D loss: 0.699642, acc.: 49.61%] [G loss: 0.716175]
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783 [D loss: 0.697271, acc.: 49.22%] [G loss: 0.710699]
8/8 [==============================] - 0s 4ms/step
784 [D loss: 0.693355, acc.: 50.98%] [G loss: 0.715699]
8/8 [==============================] - 0s 4ms/step
785 [D loss: 0.697548, acc.: 46.48%] [G loss: 0.710127]
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786 [D loss: 0.694644, acc.: 49.80%] [G loss: 0.714083]
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787 [D loss: 0.695022, acc.: 50.00%] [G loss: 0.711430]
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788 [D loss: 0.687474, acc.: 53.32%] [G loss: 0.716014]
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789 [D loss: 0.685419, acc.: 55.47%] [G loss: 0.715377]
8/8 [==============================] - 0s 4ms/step
790 [D loss: 0.696642, acc.: 49.80%] [G loss: 0.715836]
8/8 [==============================] - 0s 4ms/step
791 [D loss: 0.694186, acc.: 49.22%] [G loss: 0.717885]
8/8 [==============================] - 0s 4ms/step
792 [D loss: 0.693715, acc.: 52.15%] [G loss: 0.705405]
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793 [D loss: 0.696117, acc.: 51.76%] [G loss: 0.716112]
8/8 [==============================] - 0s 4ms/step
794 [D loss: 0.694327, acc.: 49.61%] [G loss: 0.712025]
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795 [D loss: 0.691991, acc.: 52.34%] [G loss: 0.706757]
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796 [D loss: 0.692359, acc.: 49.61%] [G loss: 0.713966]
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797 [D loss: 0.690293, acc.: 49.41%] [G loss: 0.712035]
8/8 [==============================] - 0s 4ms/step
798 [D loss: 0.688932, acc.: 52.54%] [G loss: 0.717181]
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799 [D loss: 0.693392, acc.: 48.24%] [G loss: 0.714482]
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800 [D loss: 0.692331, acc.: 50.20%] [G loss: 0.715817]
1/1 [==============================] - 0s 24ms/step
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801 [D loss: 0.693514, acc.: 51.17%] [G loss: 0.712496]
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802 [D loss: 0.695410, acc.: 50.98%] [G loss: 0.709561]
8/8 [==============================] - 0s 4ms/step
803 [D loss: 0.696619, acc.: 47.27%] [G loss: 0.712119]
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804 [D loss: 0.692465, acc.: 50.00%] [G loss: 0.713738]
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805 [D loss: 0.700146, acc.: 43.95%] [G loss: 0.713078]
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806 [D loss: 0.697177, acc.: 45.70%] [G loss: 0.709599]
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807 [D loss: 0.697448, acc.: 48.83%] [G loss: 0.709210]
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808 [D loss: 0.697663, acc.: 47.46%] [G loss: 0.709130]
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809 [D loss: 0.700596, acc.: 47.46%] [G loss: 0.701827]
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810 [D loss: 0.697671, acc.: 45.90%] [G loss: 0.702333]
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811 [D loss: 0.689849, acc.: 49.02%] [G loss: 0.703775]
8/8 [==============================] - 0s 4ms/step
812 [D loss: 0.692757, acc.: 49.41%] [G loss: 0.711323]
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813 [D loss: 0.693994, acc.: 47.07%] [G loss: 0.711260]
8/8 [==============================] - 0s 4ms/step
814 [D loss: 0.689650, acc.: 49.22%] [G loss: 0.714769]
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815 [D loss: 0.691722, acc.: 50.59%] [G loss: 0.705848]
8/8 [==============================] - 0s 4ms/step
816 [D loss: 0.692579, acc.: 47.07%] [G loss: 0.709094]
8/8 [==============================] - 0s 4ms/step
817 [D loss: 0.692279, acc.: 50.78%] [G loss: 0.712851]
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818 [D loss: 0.688534, acc.: 53.91%] [G loss: 0.711244]
8/8 [==============================] - 0s 4ms/step
819 [D loss: 0.688427, acc.: 52.73%] [G loss: 0.715620]
8/8 [==============================] - 0s 4ms/step
820 [D loss: 0.684974, acc.: 56.84%] [G loss: 0.715644]
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821 [D loss: 0.696703, acc.: 48.63%] [G loss: 0.715861]
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822 [D loss: 0.690011, acc.: 52.54%] [G loss: 0.717253]
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823 [D loss: 0.687621, acc.: 54.69%] [G loss: 0.714182]
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824 [D loss: 0.690025, acc.: 50.39%] [G loss: 0.712048]
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825 [D loss: 0.689654, acc.: 54.88%] [G loss: 0.715938]
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826 [D loss: 0.686521, acc.: 52.54%] [G loss: 0.716230]
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827 [D loss: 0.692262, acc.: 50.00%] [G loss: 0.722647]
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828 [D loss: 0.690983, acc.: 52.54%] [G loss: 0.724796]
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829 [D loss: 0.694155, acc.: 51.56%] [G loss: 0.714614]
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830 [D loss: 0.688197, acc.: 54.88%] [G loss: 0.713486]
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831 [D loss: 0.694426, acc.: 48.63%] [G loss: 0.715826]
8/8 [==============================] - 0s 4ms/step
832 [D loss: 0.691626, acc.: 51.76%] [G loss: 0.705596]
8/8 [==============================] - 0s 4ms/step
833 [D loss: 0.697660, acc.: 49.02%] [G loss: 0.695990]
8/8 [==============================] - 0s 4ms/step
834 [D loss: 0.695906, acc.: 48.63%] [G loss: 0.704536]
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835 [D loss: 0.695505, acc.: 48.44%] [G loss: 0.706454]
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836 [D loss: 0.697293, acc.: 49.80%] [G loss: 0.711076]
8/8 [==============================] - 0s 4ms/step
837 [D loss: 0.690521, acc.: 52.34%] [G loss: 0.713881]
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838 [D loss: 0.696107, acc.: 50.78%] [G loss: 0.711725]
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839 [D loss: 0.689475, acc.: 53.71%] [G loss: 0.721968]
8/8 [==============================] - 0s 4ms/step
840 [D loss: 0.685483, acc.: 57.62%] [G loss: 0.716268]
8/8 [==============================] - 0s 4ms/step
841 [D loss: 0.688797, acc.: 52.34%] [G loss: 0.706406]
8/8 [==============================] - 0s 4ms/step
842 [D loss: 0.692853, acc.: 50.98%] [G loss: 0.705213]
8/8 [==============================] - 0s 4ms/step
843 [D loss: 0.690730, acc.: 50.59%] [G loss: 0.732287]
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844 [D loss: 0.689726, acc.: 52.93%] [G loss: 0.729263]
8/8 [==============================] - 0s 4ms/step
845 [D loss: 0.692956, acc.: 55.86%] [G loss: 0.718298]
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846 [D loss: 0.691207, acc.: 53.52%] [G loss: 0.714421]
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847 [D loss: 0.682951, acc.: 60.16%] [G loss: 0.717438]
8/8 [==============================] - 0s 4ms/step
848 [D loss: 0.687946, acc.: 54.49%] [G loss: 0.712333]
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849 [D loss: 0.691428, acc.: 53.12%] [G loss: 0.703871]
8/8 [==============================] - 0s 4ms/step
850 [D loss: 0.691261, acc.: 52.73%] [G loss: 0.725281]
1/1 [==============================] - 0s 25ms/step
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851 [D loss: 0.685375, acc.: 54.49%] [G loss: 0.745820]
8/8 [==============================] - 0s 4ms/step
852 [D loss: 0.692215, acc.: 52.93%] [G loss: 0.724909]
8/8 [==============================] - 0s 4ms/step
853 [D loss: 0.694561, acc.: 52.93%] [G loss: 0.717009]
8/8 [==============================] - 0s 4ms/step
854 [D loss: 0.689087, acc.: 56.05%] [G loss: 0.710736]
8/8 [==============================] - 0s 4ms/step
855 [D loss: 0.692582, acc.: 50.59%] [G loss: 0.706456]
8/8 [==============================] - 0s 4ms/step
856 [D loss: 0.699382, acc.: 45.31%] [G loss: 0.699898]
8/8 [==============================] - 0s 4ms/step
857 [D loss: 0.686647, acc.: 54.30%] [G loss: 0.745210]
8/8 [==============================] - 0s 4ms/step
858 [D loss: 0.683732, acc.: 56.84%] [G loss: 0.763325]
8/8 [==============================] - 0s 4ms/step
859 [D loss: 0.689060, acc.: 54.30%] [G loss: 0.740241]
8/8 [==============================] - 0s 4ms/step
860 [D loss: 0.685246, acc.: 57.81%] [G loss: 0.731291]
8/8 [==============================] - 0s 4ms/step
861 [D loss: 0.683178, acc.: 61.72%] [G loss: 0.746397]
8/8 [==============================] - 0s 4ms/step
862 [D loss: 0.682691, acc.: 56.05%] [G loss: 0.713786]
8/8 [==============================] - 0s 4ms/step
863 [D loss: 0.701811, acc.: 46.88%] [G loss: 0.687823]
8/8 [==============================] - 0s 4ms/step
864 [D loss: 0.696856, acc.: 50.59%] [G loss: 0.735994]
8/8 [==============================] - 0s 4ms/step
865 [D loss: 0.677831, acc.: 59.38%] [G loss: 0.770493]
8/8 [==============================] - 0s 4ms/step
866 [D loss: 0.692101, acc.: 48.63%] [G loss: 0.732996]
8/8 [==============================] - 0s 4ms/step
867 [D loss: 0.697071, acc.: 50.39%] [G loss: 0.715776]
8/8 [==============================] - 0s 4ms/step
868 [D loss: 0.683303, acc.: 60.74%] [G loss: 0.747892]
8/8 [==============================] - 0s 4ms/step
869 [D loss: 0.673441, acc.: 66.99%] [G loss: 0.753761]
8/8 [==============================] - 0s 4ms/step
870 [D loss: 0.687467, acc.: 53.52%] [G loss: 0.703206]
8/8 [==============================] - 0s 4ms/step
871 [D loss: 0.707895, acc.: 42.58%] [G loss: 0.689951]
8/8 [==============================] - 0s 4ms/step
872 [D loss: 0.696509, acc.: 47.07%] [G loss: 0.747696]
8/8 [==============================] - 0s 4ms/step
873 [D loss: 0.678940, acc.: 57.62%] [G loss: 0.774023]
8/8 [==============================] - 0s 4ms/step
874 [D loss: 0.684362, acc.: 57.23%] [G loss: 0.724656]
8/8 [==============================] - 0s 4ms/step
875 [D loss: 0.687961, acc.: 56.25%] [G loss: 0.733195]
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876 [D loss: 0.681926, acc.: 62.11%] [G loss: 0.740190]
8/8 [==============================] - 0s 4ms/step
877 [D loss: 0.688644, acc.: 53.52%] [G loss: 0.721291]
8/8 [==============================] - 0s 4ms/step
878 [D loss: 0.711099, acc.: 46.29%] [G loss: 0.685010]
8/8 [==============================] - 0s 4ms/step
879 [D loss: 0.700940, acc.: 48.05%] [G loss: 0.737305]
8/8 [==============================] - 0s 4ms/step
880 [D loss: 0.682063, acc.: 56.25%] [G loss: 0.767287]
8/8 [==============================] - 0s 4ms/step
881 [D loss: 0.689632, acc.: 53.71%] [G loss: 0.737866]
8/8 [==============================] - 0s 4ms/step
882 [D loss: 0.688355, acc.: 56.25%] [G loss: 0.739503]
8/8 [==============================] - 0s 4ms/step
883 [D loss: 0.678581, acc.: 61.91%] [G loss: 0.741848]
8/8 [==============================] - 0s 4ms/step
884 [D loss: 0.680649, acc.: 63.09%] [G loss: 0.730886]
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885 [D loss: 0.692597, acc.: 48.63%] [G loss: 0.698595]
8/8 [==============================] - 0s 4ms/step
886 [D loss: 0.690147, acc.: 50.59%] [G loss: 0.716983]
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887 [D loss: 0.680965, acc.: 58.59%] [G loss: 0.732740]
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888 [D loss: 0.683868, acc.: 59.18%] [G loss: 0.717250]
8/8 [==============================] - 0s 4ms/step
889 [D loss: 0.686400, acc.: 54.10%] [G loss: 0.713492]
8/8 [==============================] - 0s 4ms/step
890 [D loss: 0.686308, acc.: 57.81%] [G loss: 0.718005]
8/8 [==============================] - 0s 4ms/step
891 [D loss: 0.686124, acc.: 54.10%] [G loss: 0.713732]
8/8 [==============================] - 0s 4ms/step
892 [D loss: 0.686132, acc.: 55.66%] [G loss: 0.704218]
8/8 [==============================] - 0s 4ms/step
893 [D loss: 0.695264, acc.: 51.17%] [G loss: 0.708434]
8/8 [==============================] - 0s 4ms/step
894 [D loss: 0.700035, acc.: 47.07%] [G loss: 0.711149]
8/8 [==============================] - 0s 4ms/step
895 [D loss: 0.698835, acc.: 46.09%] [G loss: 0.709664]
8/8 [==============================] - 0s 4ms/step
896 [D loss: 0.698551, acc.: 48.44%] [G loss: 0.706564]
8/8 [==============================] - 0s 4ms/step
897 [D loss: 0.699241, acc.: 49.80%] [G loss: 0.705501]
8/8 [==============================] - 0s 4ms/step
898 [D loss: 0.691092, acc.: 53.91%] [G loss: 0.712368]
8/8 [==============================] - 0s 4ms/step
899 [D loss: 0.699019, acc.: 48.05%] [G loss: 0.716256]
8/8 [==============================] - 0s 4ms/step
900 [D loss: 0.691993, acc.: 51.76%] [G loss: 0.716344]
1/1 [==============================] - 0s 26ms/step
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901 [D loss: 0.690267, acc.: 51.17%] [G loss: 0.717035]
8/8 [==============================] - 0s 4ms/step
902 [D loss: 0.696058, acc.: 50.20%] [G loss: 0.721589]
8/8 [==============================] - 0s 4ms/step
903 [D loss: 0.702364, acc.: 45.70%] [G loss: 0.720511]
8/8 [==============================] - 0s 4ms/step
904 [D loss: 0.691718, acc.: 53.12%] [G loss: 0.723276]
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905 [D loss: 0.692780, acc.: 47.66%] [G loss: 0.721701]
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906 [D loss: 0.697367, acc.: 48.24%] [G loss: 0.717893]
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907 [D loss: 0.692492, acc.: 51.17%] [G loss: 0.707738]
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908 [D loss: 0.692317, acc.: 52.15%] [G loss: 0.708780]
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909 [D loss: 0.690896, acc.: 52.15%] [G loss: 0.725398]
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910 [D loss: 0.693902, acc.: 50.59%] [G loss: 0.720307]
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911 [D loss: 0.692490, acc.: 52.34%] [G loss: 0.726925]
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912 [D loss: 0.688086, acc.: 54.10%] [G loss: 0.725024]
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913 [D loss: 0.693550, acc.: 51.76%] [G loss: 0.732849]
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914 [D loss: 0.690102, acc.: 51.95%] [G loss: 0.719111]
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915 [D loss: 0.691180, acc.: 52.54%] [G loss: 0.715487]
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916 [D loss: 0.687702, acc.: 53.91%] [G loss: 0.719803]
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917 [D loss: 0.688550, acc.: 53.91%] [G loss: 0.725856]
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918 [D loss: 0.693146, acc.: 49.80%] [G loss: 0.725369]
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919 [D loss: 0.694408, acc.: 49.02%] [G loss: 0.720235]
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920 [D loss: 0.689682, acc.: 54.10%] [G loss: 0.714411]
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921 [D loss: 0.690454, acc.: 50.98%] [G loss: 0.721128]
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922 [D loss: 0.694428, acc.: 48.44%] [G loss: 0.714613]
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923 [D loss: 0.689811, acc.: 50.20%] [G loss: 0.716955]
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924 [D loss: 0.692402, acc.: 50.59%] [G loss: 0.717399]
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925 [D loss: 0.689256, acc.: 51.56%] [G loss: 0.722158]
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926 [D loss: 0.690080, acc.: 52.73%] [G loss: 0.723585]
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927 [D loss: 0.689206, acc.: 51.95%] [G loss: 0.717353]
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928 [D loss: 0.694896, acc.: 48.83%] [G loss: 0.727301]
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929 [D loss: 0.691604, acc.: 53.71%] [G loss: 0.723494]
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930 [D loss: 0.687460, acc.: 54.69%] [G loss: 0.720897]
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931 [D loss: 0.694080, acc.: 50.20%] [G loss: 0.715492]
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932 [D loss: 0.689604, acc.: 54.69%] [G loss: 0.718525]
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933 [D loss: 0.686429, acc.: 56.05%] [G loss: 0.732740]
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934 [D loss: 0.685893, acc.: 56.64%] [G loss: 0.732059]
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935 [D loss: 0.686239, acc.: 56.25%] [G loss: 0.738071]
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936 [D loss: 0.691149, acc.: 55.08%] [G loss: 0.734351]
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937 [D loss: 0.684510, acc.: 59.96%] [G loss: 0.729533]
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938 [D loss: 0.686010, acc.: 55.47%] [G loss: 0.720377]
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939 [D loss: 0.690040, acc.: 53.12%] [G loss: 0.712958]
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940 [D loss: 0.693427, acc.: 54.49%] [G loss: 0.711375]
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941 [D loss: 0.689967, acc.: 51.56%] [G loss: 0.728109]
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942 [D loss: 0.689929, acc.: 54.69%] [G loss: 0.739951]
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943 [D loss: 0.692067, acc.: 52.34%] [G loss: 0.722398]
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944 [D loss: 0.695439, acc.: 52.93%] [G loss: 0.723521]
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945 [D loss: 0.689659, acc.: 54.88%] [G loss: 0.715246]
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946 [D loss: 0.692204, acc.: 50.98%] [G loss: 0.714547]
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947 [D loss: 0.693806, acc.: 48.83%] [G loss: 0.703997]
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948 [D loss: 0.688953, acc.: 53.32%] [G loss: 0.704593]
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949 [D loss: 0.689277, acc.: 52.34%] [G loss: 0.718087]
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950 [D loss: 0.685760, acc.: 55.27%] [G loss: 0.732579]
1/1 [==============================] - 0s 26ms/step
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951 [D loss: 0.693488, acc.: 48.83%] [G loss: 0.724068]
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952 [D loss: 0.689870, acc.: 50.39%] [G loss: 0.723126]
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953 [D loss: 0.685868, acc.: 54.49%] [G loss: 0.722878]
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954 [D loss: 0.687771, acc.: 57.03%] [G loss: 0.712598]
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955 [D loss: 0.690901, acc.: 52.73%] [G loss: 0.709621]
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956 [D loss: 0.691153, acc.: 51.95%] [G loss: 0.707321]
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957 [D loss: 0.693016, acc.: 48.44%] [G loss: 0.720020]
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958 [D loss: 0.683006, acc.: 56.45%] [G loss: 0.732442]
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959 [D loss: 0.689807, acc.: 53.71%] [G loss: 0.731915]
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960 [D loss: 0.689017, acc.: 53.71%] [G loss: 0.727239]
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961 [D loss: 0.693494, acc.: 52.93%] [G loss: 0.717485]
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962 [D loss: 0.687083, acc.: 54.10%] [G loss: 0.722593]
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963 [D loss: 0.687759, acc.: 54.69%] [G loss: 0.719425]
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964 [D loss: 0.691568, acc.: 50.59%] [G loss: 0.700009]
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965 [D loss: 0.693978, acc.: 51.17%] [G loss: 0.719628]
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966 [D loss: 0.688729, acc.: 53.91%] [G loss: 0.739828]
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967 [D loss: 0.683244, acc.: 59.18%] [G loss: 0.759882]
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968 [D loss: 0.691693, acc.: 53.71%] [G loss: 0.734369]
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969 [D loss: 0.689455, acc.: 54.69%] [G loss: 0.734383]
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970 [D loss: 0.683705, acc.: 56.45%] [G loss: 0.737827]
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971 [D loss: 0.682851, acc.: 58.98%] [G loss: 0.726037]
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972 [D loss: 0.693988, acc.: 49.80%] [G loss: 0.706130]
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973 [D loss: 0.702465, acc.: 46.48%] [G loss: 0.698473]
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974 [D loss: 0.691316, acc.: 50.20%] [G loss: 0.730663]
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975 [D loss: 0.682713, acc.: 56.45%] [G loss: 0.748949]
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976 [D loss: 0.692293, acc.: 52.54%] [G loss: 0.730047]
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977 [D loss: 0.696823, acc.: 47.27%] [G loss: 0.720704]
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978 [D loss: 0.690430, acc.: 54.30%] [G loss: 0.719473]
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979 [D loss: 0.684397, acc.: 57.42%] [G loss: 0.728201]
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980 [D loss: 0.685827, acc.: 52.54%] [G loss: 0.706884]
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981 [D loss: 0.696237, acc.: 49.41%] [G loss: 0.695183]
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982 [D loss: 0.699521, acc.: 47.27%] [G loss: 0.700934]
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983 [D loss: 0.685608, acc.: 57.81%] [G loss: 0.724945]
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984 [D loss: 0.685118, acc.: 56.64%] [G loss: 0.741145]
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985 [D loss: 0.688195, acc.: 55.47%] [G loss: 0.728933]
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986 [D loss: 0.691394, acc.: 56.25%] [G loss: 0.736416]
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987 [D loss: 0.685836, acc.: 57.03%] [G loss: 0.734364]
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988 [D loss: 0.688507, acc.: 55.66%] [G loss: 0.732109]
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989 [D loss: 0.692852, acc.: 53.32%] [G loss: 0.712003]
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990 [D loss: 0.694192, acc.: 51.95%] [G loss: 0.708611]
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991 [D loss: 0.689916, acc.: 53.71%] [G loss: 0.723778]
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992 [D loss: 0.690937, acc.: 48.63%] [G loss: 0.740610]
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993 [D loss: 0.692970, acc.: 51.95%] [G loss: 0.733416]
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994 [D loss: 0.689423, acc.: 52.73%] [G loss: 0.728760]
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995 [D loss: 0.687754, acc.: 57.42%] [G loss: 0.734043]
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996 [D loss: 0.680662, acc.: 60.55%] [G loss: 0.730031]
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997 [D loss: 0.686633, acc.: 55.86%] [G loss: 0.722436]
8/8 [==============================] - 0s 4ms/step
998 [D loss: 0.694644, acc.: 51.56%] [G loss: 0.712825]
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999 [D loss: 0.690170, acc.: 53.32%] [G loss: 0.718941]
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1000 [D loss: 0.687648, acc.: 54.10%] [G loss: 0.730997]
1/1 [==============================] - 0s 23ms/step
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1001 [D loss: 0.692868, acc.: 52.34%] [G loss: 0.724331]
8/8 [==============================] - 0s 4ms/step
1002 [D loss: 0.697191, acc.: 51.95%] [G loss: 0.714235]
8/8 [==============================] - 0s 4ms/step
1003 [D loss: 0.696481, acc.: 49.41%] [G loss: 0.712112]
8/8 [==============================] - 0s 4ms/step
1004 [D loss: 0.692651, acc.: 52.34%] [G loss: 0.713477]
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1005 [D loss: 0.688408, acc.: 54.88%] [G loss: 0.709589]
8/8 [==============================] - 0s 4ms/step
1006 [D loss: 0.693532, acc.: 53.71%] [G loss: 0.710600]
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1007 [D loss: 0.687043, acc.: 53.91%] [G loss: 0.722648]
8/8 [==============================] - 0s 4ms/step
1008 [D loss: 0.685173, acc.: 56.84%] [G loss: 0.737576]
8/8 [==============================] - 0s 4ms/step
1009 [D loss: 0.686267, acc.: 55.27%] [G loss: 0.739474]
8/8 [==============================] - 0s 4ms/step
1010 [D loss: 0.686878, acc.: 55.08%] [G loss: 0.733785]
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1011 [D loss: 0.684399, acc.: 59.57%] [G loss: 0.730152]
8/8 [==============================] - 0s 4ms/step
1012 [D loss: 0.685268, acc.: 54.10%] [G loss: 0.724015]
8/8 [==============================] - 0s 4ms/step
1013 [D loss: 0.693061, acc.: 50.20%] [G loss: 0.706763]
8/8 [==============================] - 0s 4ms/step
1014 [D loss: 0.699101, acc.: 46.88%] [G loss: 0.711267]
8/8 [==============================] - 0s 4ms/step
1015 [D loss: 0.692959, acc.: 49.80%] [G loss: 0.711649]
8/8 [==============================] - 0s 4ms/step
1016 [D loss: 0.692198, acc.: 48.63%] [G loss: 0.719512]
8/8 [==============================] - 0s 4ms/step
1017 [D loss: 0.689279, acc.: 52.34%] [G loss: 0.720121]
8/8 [==============================] - 0s 4ms/step
1018 [D loss: 0.686379, acc.: 57.03%] [G loss: 0.723032]
8/8 [==============================] - 0s 4ms/step
1019 [D loss: 0.687166, acc.: 56.45%] [G loss: 0.720782]
8/8 [==============================] - 0s 4ms/step
1020 [D loss: 0.685306, acc.: 54.88%] [G loss: 0.719701]
8/8 [==============================] - 0s 4ms/step
1021 [D loss: 0.683140, acc.: 58.40%] [G loss: 0.720289]
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1022 [D loss: 0.692384, acc.: 50.59%] [G loss: 0.708015]
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1023 [D loss: 0.694334, acc.: 51.56%] [G loss: 0.704829]
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1024 [D loss: 0.691715, acc.: 53.71%] [G loss: 0.726503]
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1025 [D loss: 0.686603, acc.: 56.05%] [G loss: 0.730399]
8/8 [==============================] - 0s 4ms/step
1026 [D loss: 0.688044, acc.: 54.69%] [G loss: 0.719521]
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1027 [D loss: 0.693688, acc.: 52.34%] [G loss: 0.717108]
8/8 [==============================] - 0s 4ms/step
1028 [D loss: 0.689277, acc.: 54.69%] [G loss: 0.730910]
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1029 [D loss: 0.685500, acc.: 55.47%] [G loss: 0.725227]
8/8 [==============================] - 0s 4ms/step
1030 [D loss: 0.690530, acc.: 50.59%] [G loss: 0.710970]
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1031 [D loss: 0.691248, acc.: 52.34%] [G loss: 0.723973]
8/8 [==============================] - 0s 4ms/step
1032 [D loss: 0.690906, acc.: 49.22%] [G loss: 0.724993]
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1033 [D loss: 0.691340, acc.: 53.71%] [G loss: 0.726837]
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1034 [D loss: 0.694733, acc.: 51.17%] [G loss: 0.715806]
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1035 [D loss: 0.694404, acc.: 52.15%] [G loss: 0.716417]
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1036 [D loss: 0.689379, acc.: 53.91%] [G loss: 0.722077]
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1037 [D loss: 0.687418, acc.: 53.52%] [G loss: 0.714263]
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1038 [D loss: 0.691208, acc.: 52.34%] [G loss: 0.710628]
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1039 [D loss: 0.687742, acc.: 55.47%] [G loss: 0.725994]
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1040 [D loss: 0.683299, acc.: 59.77%] [G loss: 0.728642]
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1041 [D loss: 0.684367, acc.: 58.20%] [G loss: 0.726814]
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1042 [D loss: 0.684620, acc.: 57.23%] [G loss: 0.730695]
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1043 [D loss: 0.689807, acc.: 52.15%] [G loss: 0.718607]
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1044 [D loss: 0.684807, acc.: 59.96%] [G loss: 0.716386]
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1045 [D loss: 0.693262, acc.: 53.52%] [G loss: 0.704373]
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1046 [D loss: 0.694499, acc.: 52.54%] [G loss: 0.693391]
8/8 [==============================] - 0s 4ms/step
1047 [D loss: 0.697388, acc.: 50.39%] [G loss: 0.707384]
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1048 [D loss: 0.691527, acc.: 50.00%] [G loss: 0.735952]
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1049 [D loss: 0.687566, acc.: 52.93%] [G loss: 0.748483]
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1050 [D loss: 0.688821, acc.: 50.78%] [G loss: 0.745371]
1/1 [==============================] - 0s 21ms/step
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1051 [D loss: 0.681408, acc.: 60.94%] [G loss: 0.733644]
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1052 [D loss: 0.686388, acc.: 60.55%] [G loss: 0.737619]
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1053 [D loss: 0.682773, acc.: 59.38%] [G loss: 0.723557]
8/8 [==============================] - 0s 4ms/step
1054 [D loss: 0.692965, acc.: 50.20%] [G loss: 0.704760]
8/8 [==============================] - 0s 4ms/step
1055 [D loss: 0.699945, acc.: 46.68%] [G loss: 0.700758]
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1056 [D loss: 0.702625, acc.: 45.51%] [G loss: 0.711791]
8/8 [==============================] - 0s 4ms/step
1057 [D loss: 0.687531, acc.: 51.56%] [G loss: 0.736127]
8/8 [==============================] - 0s 4ms/step
1058 [D loss: 0.684958, acc.: 56.45%] [G loss: 0.742489]
8/8 [==============================] - 0s 4ms/step
1059 [D loss: 0.690867, acc.: 54.69%] [G loss: 0.727352]
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1060 [D loss: 0.689682, acc.: 56.84%] [G loss: 0.732447]
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1061 [D loss: 0.679761, acc.: 64.06%] [G loss: 0.743390]
8/8 [==============================] - 0s 4ms/step
1062 [D loss: 0.671882, acc.: 65.43%] [G loss: 0.738886]
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1063 [D loss: 0.683723, acc.: 53.52%] [G loss: 0.714042]
8/8 [==============================] - 0s 4ms/step
1064 [D loss: 0.698867, acc.: 46.68%] [G loss: 0.699444]
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1065 [D loss: 0.693613, acc.: 49.61%] [G loss: 0.732940]
8/8 [==============================] - 0s 4ms/step
1066 [D loss: 0.678089, acc.: 55.47%] [G loss: 0.759714]
8/8 [==============================] - 0s 4ms/step
1067 [D loss: 0.684646, acc.: 56.45%] [G loss: 0.741230]
8/8 [==============================] - 0s 4ms/step
1068 [D loss: 0.704477, acc.: 45.31%] [G loss: 0.711325]
8/8 [==============================] - 0s 4ms/step
1069 [D loss: 0.691267, acc.: 57.42%] [G loss: 0.723844]
8/8 [==============================] - 0s 4ms/step
1070 [D loss: 0.684606, acc.: 60.16%] [G loss: 0.737888]
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1071 [D loss: 0.675096, acc.: 63.09%] [G loss: 0.738764]
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1072 [D loss: 0.684509, acc.: 56.64%] [G loss: 0.719975]
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1073 [D loss: 0.690692, acc.: 51.17%] [G loss: 0.718494]
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1074 [D loss: 0.689282, acc.: 53.52%] [G loss: 0.747207]
8/8 [==============================] - 0s 4ms/step
1075 [D loss: 0.682699, acc.: 54.30%] [G loss: 0.751891]
8/8 [==============================] - 0s 4ms/step
1076 [D loss: 0.690908, acc.: 53.32%] [G loss: 0.732210]
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1077 [D loss: 0.694792, acc.: 48.63%] [G loss: 0.710200]
8/8 [==============================] - 0s 4ms/step
1078 [D loss: 0.693150, acc.: 52.54%] [G loss: 0.716039]
8/8 [==============================] - 0s 4ms/step
1079 [D loss: 0.689245, acc.: 54.30%] [G loss: 0.717969]
8/8 [==============================] - 0s 4ms/step
1080 [D loss: 0.695740, acc.: 48.05%] [G loss: 0.710944]
8/8 [==============================] - 0s 4ms/step
1081 [D loss: 0.696610, acc.: 48.63%] [G loss: 0.715396]
8/8 [==============================] - 0s 4ms/step
1082 [D loss: 0.689997, acc.: 52.73%] [G loss: 0.738217]
8/8 [==============================] - 0s 4ms/step
1083 [D loss: 0.676142, acc.: 61.33%] [G loss: 0.765522]
8/8 [==============================] - 0s 4ms/step
1084 [D loss: 0.675487, acc.: 63.48%] [G loss: 0.756169]
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1085 [D loss: 0.684510, acc.: 53.12%] [G loss: 0.729152]
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1086 [D loss: 0.685423, acc.: 57.62%] [G loss: 0.728310]
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1087 [D loss: 0.694014, acc.: 50.98%] [G loss: 0.721037]
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1088 [D loss: 0.689204, acc.: 51.95%] [G loss: 0.714141]
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1089 [D loss: 0.690001, acc.: 52.73%] [G loss: 0.707812]
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1090 [D loss: 0.698388, acc.: 50.78%] [G loss: 0.696412]
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1091 [D loss: 0.690272, acc.: 50.78%] [G loss: 0.740432]
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1092 [D loss: 0.681279, acc.: 58.40%] [G loss: 0.753301]
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1093 [D loss: 0.682194, acc.: 57.03%] [G loss: 0.744305]
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1094 [D loss: 0.684988, acc.: 53.12%] [G loss: 0.739147]
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1095 [D loss: 0.685723, acc.: 56.64%] [G loss: 0.736823]
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1096 [D loss: 0.684350, acc.: 57.62%] [G loss: 0.730258]
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1097 [D loss: 0.690340, acc.: 51.37%] [G loss: 0.716187]
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1098 [D loss: 0.697473, acc.: 48.44%] [G loss: 0.703008]
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1099 [D loss: 0.693480, acc.: 51.56%] [G loss: 0.717912]
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1100 [D loss: 0.690641, acc.: 52.54%] [G loss: 0.725000]
1/1 [==============================] - 0s 27ms/step
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1101 [D loss: 0.684664, acc.: 56.25%] [G loss: 0.741378]
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1102 [D loss: 0.688170, acc.: 53.91%] [G loss: 0.743885]
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1103 [D loss: 0.687693, acc.: 58.79%] [G loss: 0.733669]
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1104 [D loss: 0.688451, acc.: 57.03%] [G loss: 0.737954]
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1105 [D loss: 0.680071, acc.: 60.16%] [G loss: 0.739061]
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1106 [D loss: 0.680036, acc.: 59.96%] [G loss: 0.727883]
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1107 [D loss: 0.689625, acc.: 53.52%] [G loss: 0.720481]
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1108 [D loss: 0.686255, acc.: 54.30%] [G loss: 0.711642]
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1109 [D loss: 0.693148, acc.: 49.22%] [G loss: 0.718626]
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1110 [D loss: 0.688596, acc.: 52.34%] [G loss: 0.733640]
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1111 [D loss: 0.690753, acc.: 51.95%] [G loss: 0.726086]
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1112 [D loss: 0.689168, acc.: 53.12%] [G loss: 0.719382]
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1113 [D loss: 0.692730, acc.: 53.32%] [G loss: 0.727047]
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1114 [D loss: 0.684092, acc.: 57.81%] [G loss: 0.728294]
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1115 [D loss: 0.678017, acc.: 60.55%] [G loss: 0.734481]
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1116 [D loss: 0.685551, acc.: 54.88%] [G loss: 0.731270]
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1117 [D loss: 0.688717, acc.: 53.71%] [G loss: 0.722580]
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1118 [D loss: 0.692813, acc.: 52.15%] [G loss: 0.720606]
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1119 [D loss: 0.686772, acc.: 54.10%] [G loss: 0.720630]
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1120 [D loss: 0.696843, acc.: 49.41%] [G loss: 0.719089]
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1121 [D loss: 0.697805, acc.: 50.20%] [G loss: 0.712855]
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1122 [D loss: 0.695254, acc.: 49.80%] [G loss: 0.715586]
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1123 [D loss: 0.687629, acc.: 57.03%] [G loss: 0.718542]
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1124 [D loss: 0.686839, acc.: 57.42%] [G loss: 0.723127]
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1125 [D loss: 0.684462, acc.: 54.49%] [G loss: 0.719619]
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1126 [D loss: 0.682114, acc.: 56.05%] [G loss: 0.727083]
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1127 [D loss: 0.690769, acc.: 54.10%] [G loss: 0.736328]
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1128 [D loss: 0.685294, acc.: 57.42%] [G loss: 0.736364]
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1129 [D loss: 0.684296, acc.: 56.45%] [G loss: 0.733623]
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1130 [D loss: 0.694741, acc.: 52.93%] [G loss: 0.726339]
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1131 [D loss: 0.691892, acc.: 53.91%] [G loss: 0.723607]
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1132 [D loss: 0.686711, acc.: 53.91%] [G loss: 0.736296]
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1133 [D loss: 0.682685, acc.: 59.96%] [G loss: 0.736931]
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1134 [D loss: 0.683317, acc.: 57.42%] [G loss: 0.734615]
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1135 [D loss: 0.686434, acc.: 55.47%] [G loss: 0.736245]
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1136 [D loss: 0.681107, acc.: 58.40%] [G loss: 0.742446]
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1137 [D loss: 0.683113, acc.: 56.84%] [G loss: 0.746697]
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1138 [D loss: 0.685669, acc.: 56.05%] [G loss: 0.743911]
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1139 [D loss: 0.692938, acc.: 53.12%] [G loss: 0.726313]
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1140 [D loss: 0.699138, acc.: 48.24%] [G loss: 0.716546]
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1141 [D loss: 0.695699, acc.: 49.22%] [G loss: 0.717651]
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1142 [D loss: 0.695688, acc.: 51.37%] [G loss: 0.713896]
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1143 [D loss: 0.686631, acc.: 52.93%] [G loss: 0.711681]
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1144 [D loss: 0.690297, acc.: 54.88%] [G loss: 0.712980]
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1145 [D loss: 0.684190, acc.: 55.66%] [G loss: 0.721567]
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1146 [D loss: 0.681093, acc.: 60.94%] [G loss: 0.748630]
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1147 [D loss: 0.673373, acc.: 63.28%] [G loss: 0.759059]
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1148 [D loss: 0.676738, acc.: 65.23%] [G loss: 0.753064]
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1149 [D loss: 0.687792, acc.: 54.69%] [G loss: 0.732201]
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1150 [D loss: 0.691592, acc.: 53.91%] [G loss: 0.716332]
1/1 [==============================] - 0s 26ms/step
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1151 [D loss: 0.692301, acc.: 51.76%] [G loss: 0.715833]
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1152 [D loss: 0.689873, acc.: 55.86%] [G loss: 0.715292]
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1153 [D loss: 0.699205, acc.: 50.00%] [G loss: 0.692205]
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1154 [D loss: 0.701252, acc.: 47.85%] [G loss: 0.695816]
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1155 [D loss: 0.696396, acc.: 49.02%] [G loss: 0.715013]
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1156 [D loss: 0.682269, acc.: 55.66%] [G loss: 0.759390]
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1157 [D loss: 0.679820, acc.: 61.33%] [G loss: 0.765113]
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1158 [D loss: 0.685536, acc.: 57.42%] [G loss: 0.745243]
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1159 [D loss: 0.692157, acc.: 54.49%] [G loss: 0.730832]
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1160 [D loss: 0.683574, acc.: 57.81%] [G loss: 0.740689]
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1161 [D loss: 0.682243, acc.: 59.18%] [G loss: 0.731475]
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1162 [D loss: 0.686418, acc.: 55.27%] [G loss: 0.728634]
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1163 [D loss: 0.695190, acc.: 50.00%] [G loss: 0.708076]
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1164 [D loss: 0.697528, acc.: 49.41%] [G loss: 0.729979]
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1165 [D loss: 0.683621, acc.: 56.05%] [G loss: 0.765370]
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1166 [D loss: 0.677247, acc.: 60.55%] [G loss: 0.762662]
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1167 [D loss: 0.687704, acc.: 56.45%] [G loss: 0.739152]
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1168 [D loss: 0.691626, acc.: 52.93%] [G loss: 0.730113]
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1169 [D loss: 0.684934, acc.: 56.45%] [G loss: 0.724111]
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1170 [D loss: 0.686514, acc.: 55.86%] [G loss: 0.717605]
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1171 [D loss: 0.696927, acc.: 50.39%] [G loss: 0.696351]
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1172 [D loss: 0.712462, acc.: 45.31%] [G loss: 0.688994]
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1173 [D loss: 0.701275, acc.: 47.66%] [G loss: 0.724203]
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1174 [D loss: 0.683994, acc.: 57.81%] [G loss: 0.770691]
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1175 [D loss: 0.683880, acc.: 58.01%] [G loss: 0.755921]
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1176 [D loss: 0.683525, acc.: 60.16%] [G loss: 0.743993]
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1177 [D loss: 0.687499, acc.: 54.30%] [G loss: 0.744761]
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1178 [D loss: 0.677366, acc.: 65.43%] [G loss: 0.753432]
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1179 [D loss: 0.664922, acc.: 68.36%] [G loss: 0.749326]
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1180 [D loss: 0.680386, acc.: 56.05%] [G loss: 0.718651]
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1181 [D loss: 0.699080, acc.: 47.85%] [G loss: 0.695372]
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1182 [D loss: 0.701849, acc.: 49.41%] [G loss: 0.702771]
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1183 [D loss: 0.689217, acc.: 51.37%] [G loss: 0.748776]
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1184 [D loss: 0.681614, acc.: 55.47%] [G loss: 0.774083]
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1185 [D loss: 0.685763, acc.: 55.86%] [G loss: 0.750040]
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1186 [D loss: 0.695122, acc.: 50.00%] [G loss: 0.733200]
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1187 [D loss: 0.687997, acc.: 57.42%] [G loss: 0.742832]
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1188 [D loss: 0.673540, acc.: 64.45%] [G loss: 0.756642]
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1189 [D loss: 0.672846, acc.: 62.89%] [G loss: 0.754502]
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1190 [D loss: 0.678650, acc.: 58.20%] [G loss: 0.717761]
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1191 [D loss: 0.694715, acc.: 51.37%] [G loss: 0.705081]
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1192 [D loss: 0.685436, acc.: 57.62%] [G loss: 0.744333]
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1193 [D loss: 0.675456, acc.: 59.38%] [G loss: 0.817751]
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1194 [D loss: 0.677188, acc.: 58.20%] [G loss: 0.788337]
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1195 [D loss: 0.704522, acc.: 51.37%] [G loss: 0.723657]
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1196 [D loss: 0.695617, acc.: 53.32%] [G loss: 0.720653]
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1197 [D loss: 0.690358, acc.: 53.91%] [G loss: 0.749831]
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1198 [D loss: 0.680292, acc.: 59.96%] [G loss: 0.760636]
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1199 [D loss: 0.676991, acc.: 58.98%] [G loss: 0.752591]
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1200 [D loss: 0.690660, acc.: 53.12%] [G loss: 0.738047]
1/1 [==============================] - 0s 26ms/step
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1201 [D loss: 0.690173, acc.: 53.52%] [G loss: 0.760396]
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1202 [D loss: 0.671264, acc.: 59.96%] [G loss: 0.816336]
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1203 [D loss: 0.687458, acc.: 54.30%] [G loss: 0.770922]
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1204 [D loss: 0.697045, acc.: 50.39%] [G loss: 0.727742]
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1205 [D loss: 0.694354, acc.: 51.56%] [G loss: 0.731095]
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1206 [D loss: 0.694080, acc.: 50.39%] [G loss: 0.722021]
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1207 [D loss: 0.699649, acc.: 48.44%] [G loss: 0.709091]
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1208 [D loss: 0.699303, acc.: 47.27%] [G loss: 0.704887]
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1209 [D loss: 0.699827, acc.: 44.73%] [G loss: 0.713996]
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1210 [D loss: 0.678353, acc.: 57.42%] [G loss: 0.748400]
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1211 [D loss: 0.672131, acc.: 60.55%] [G loss: 0.778477]
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1212 [D loss: 0.680162, acc.: 60.55%] [G loss: 0.759448]
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1213 [D loss: 0.679185, acc.: 60.16%] [G loss: 0.749676]
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1214 [D loss: 0.683231, acc.: 57.03%] [G loss: 0.751901]
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1215 [D loss: 0.675819, acc.: 61.52%] [G loss: 0.752490]
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1216 [D loss: 0.680505, acc.: 58.59%] [G loss: 0.752092]
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1217 [D loss: 0.683076, acc.: 54.49%] [G loss: 0.727366]
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1218 [D loss: 0.696344, acc.: 50.98%] [G loss: 0.697279]
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1219 [D loss: 0.698492, acc.: 49.61%] [G loss: 0.721021]
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1220 [D loss: 0.698187, acc.: 50.78%] [G loss: 0.752532]
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1221 [D loss: 0.692834, acc.: 51.17%] [G loss: 0.773175]
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1222 [D loss: 0.686479, acc.: 55.27%] [G loss: 0.758069]
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1223 [D loss: 0.689046, acc.: 55.66%] [G loss: 0.743259]
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1224 [D loss: 0.681432, acc.: 61.52%] [G loss: 0.761560]
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1225 [D loss: 0.671123, acc.: 64.65%] [G loss: 0.771561]
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1226 [D loss: 0.667530, acc.: 64.84%] [G loss: 0.763338]
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1227 [D loss: 0.673836, acc.: 60.16%] [G loss: 0.744050]
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1228 [D loss: 0.693930, acc.: 52.54%] [G loss: 0.715126]
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1229 [D loss: 0.696575, acc.: 50.59%] [G loss: 0.726413]
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1230 [D loss: 0.689157, acc.: 51.76%] [G loss: 0.764812]
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1231 [D loss: 0.682848, acc.: 57.81%] [G loss: 0.751137]
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1232 [D loss: 0.689647, acc.: 50.78%] [G loss: 0.731011]
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1233 [D loss: 0.690712, acc.: 53.32%] [G loss: 0.721194]
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1234 [D loss: 0.687844, acc.: 56.64%] [G loss: 0.727844]
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1235 [D loss: 0.685068, acc.: 56.05%] [G loss: 0.726202]
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1236 [D loss: 0.686601, acc.: 53.91%] [G loss: 0.721132]
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1237 [D loss: 0.692904, acc.: 52.93%] [G loss: 0.717083]
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1238 [D loss: 0.682315, acc.: 57.03%] [G loss: 0.732007]
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1239 [D loss: 0.684287, acc.: 56.25%] [G loss: 0.748923]
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1240 [D loss: 0.686675, acc.: 54.10%] [G loss: 0.746745]
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1241 [D loss: 0.701417, acc.: 46.88%] [G loss: 0.720622]
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1242 [D loss: 0.695301, acc.: 50.00%] [G loss: 0.729724]
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1243 [D loss: 0.695696, acc.: 50.20%] [G loss: 0.728093]
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1244 [D loss: 0.685026, acc.: 56.05%] [G loss: 0.722691]
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1245 [D loss: 0.690303, acc.: 51.95%] [G loss: 0.720863]
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1246 [D loss: 0.687807, acc.: 54.49%] [G loss: 0.730984]
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1247 [D loss: 0.691231, acc.: 50.98%] [G loss: 0.733906]
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1248 [D loss: 0.680913, acc.: 56.84%] [G loss: 0.752012]
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1249 [D loss: 0.685146, acc.: 55.47%] [G loss: 0.765376]
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1250 [D loss: 0.692921, acc.: 51.95%] [G loss: 0.734578]
1/1 [==============================] - 0s 22ms/step
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1251 [D loss: 0.697942, acc.: 50.00%] [G loss: 0.720273]
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1252 [D loss: 0.685639, acc.: 55.66%] [G loss: 0.729648]
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1253 [D loss: 0.685234, acc.: 53.71%] [G loss: 0.716921]
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1254 [D loss: 0.690760, acc.: 53.91%] [G loss: 0.714424]
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1255 [D loss: 0.694428, acc.: 48.63%] [G loss: 0.724599]
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1256 [D loss: 0.694520, acc.: 49.61%] [G loss: 0.732790]
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1257 [D loss: 0.687008, acc.: 55.47%] [G loss: 0.745998]
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1258 [D loss: 0.684443, acc.: 59.18%] [G loss: 0.755443]
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1259 [D loss: 0.675910, acc.: 62.30%] [G loss: 0.758189]
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1260 [D loss: 0.679233, acc.: 56.84%] [G loss: 0.753414]
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1261 [D loss: 0.689717, acc.: 54.10%] [G loss: 0.739072]
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1262 [D loss: 0.686775, acc.: 54.10%] [G loss: 0.724656]
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1263 [D loss: 0.692170, acc.: 53.32%] [G loss: 0.723970]
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1264 [D loss: 0.693752, acc.: 50.39%] [G loss: 0.706031]
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1265 [D loss: 0.702663, acc.: 45.31%] [G loss: 0.691781]
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1266 [D loss: 0.697816, acc.: 47.27%] [G loss: 0.703651]
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1267 [D loss: 0.695752, acc.: 47.27%] [G loss: 0.732084]
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1268 [D loss: 0.679353, acc.: 58.98%] [G loss: 0.753361]
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1269 [D loss: 0.683582, acc.: 55.66%] [G loss: 0.757087]
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1270 [D loss: 0.684250, acc.: 58.20%] [G loss: 0.745398]
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1271 [D loss: 0.683365, acc.: 57.62%] [G loss: 0.740711]
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1272 [D loss: 0.680874, acc.: 61.52%] [G loss: 0.735052]
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1273 [D loss: 0.684418, acc.: 56.84%] [G loss: 0.736398]
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1274 [D loss: 0.688600, acc.: 54.69%] [G loss: 0.709531]
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1275 [D loss: 0.702276, acc.: 45.70%] [G loss: 0.695527]
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1276 [D loss: 0.700627, acc.: 43.75%] [G loss: 0.704587]
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1277 [D loss: 0.695912, acc.: 46.48%] [G loss: 0.714740]
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1278 [D loss: 0.689698, acc.: 52.15%] [G loss: 0.747527]
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1279 [D loss: 0.691924, acc.: 52.34%] [G loss: 0.737819]
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1280 [D loss: 0.689602, acc.: 54.30%] [G loss: 0.737452]
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1281 [D loss: 0.687669, acc.: 55.27%] [G loss: 0.731106]
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1282 [D loss: 0.680377, acc.: 58.20%] [G loss: 0.738367]
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1283 [D loss: 0.679120, acc.: 59.77%] [G loss: 0.726582]
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1284 [D loss: 0.680360, acc.: 58.59%] [G loss: 0.714677]
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1285 [D loss: 0.688526, acc.: 53.12%] [G loss: 0.707258]
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1286 [D loss: 0.697783, acc.: 50.39%] [G loss: 0.702337]
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1287 [D loss: 0.688714, acc.: 53.52%] [G loss: 0.720863]
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1288 [D loss: 0.686767, acc.: 55.27%] [G loss: 0.726725]
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1289 [D loss: 0.685290, acc.: 56.05%] [G loss: 0.727457]
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1290 [D loss: 0.690955, acc.: 52.73%] [G loss: 0.726256]
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1291 [D loss: 0.684086, acc.: 55.47%] [G loss: 0.731265]
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1292 [D loss: 0.682550, acc.: 58.79%] [G loss: 0.731688]
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1293 [D loss: 0.684504, acc.: 55.08%] [G loss: 0.722394]
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1294 [D loss: 0.684760, acc.: 54.88%] [G loss: 0.727157]
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1295 [D loss: 0.694488, acc.: 49.61%] [G loss: 0.717559]
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1296 [D loss: 0.690832, acc.: 49.02%] [G loss: 0.709449]
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1297 [D loss: 0.692112, acc.: 49.80%] [G loss: 0.729237]
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1298 [D loss: 0.688881, acc.: 54.49%] [G loss: 0.736112]
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1299 [D loss: 0.695365, acc.: 48.24%] [G loss: 0.736675]
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1300 [D loss: 0.690369, acc.: 55.86%] [G loss: 0.724719]
1/1 [==============================] - 0s 31ms/step
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1301 [D loss: 0.689757, acc.: 55.86%] [G loss: 0.725130]
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1302 [D loss: 0.691240, acc.: 54.30%] [G loss: 0.719279]
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1303 [D loss: 0.688921, acc.: 53.12%] [G loss: 0.722866]
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1304 [D loss: 0.687648, acc.: 51.76%] [G loss: 0.713754]
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1305 [D loss: 0.689380, acc.: 51.56%] [G loss: 0.712884]
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1306 [D loss: 0.687354, acc.: 53.71%] [G loss: 0.716656]
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1307 [D loss: 0.680489, acc.: 55.66%] [G loss: 0.733273]
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1308 [D loss: 0.685582, acc.: 54.49%] [G loss: 0.735970]
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1309 [D loss: 0.687500, acc.: 53.91%] [G loss: 0.741532]
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1310 [D loss: 0.695394, acc.: 50.00%] [G loss: 0.728936]
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1311 [D loss: 0.694879, acc.: 50.98%] [G loss: 0.725214]
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1312 [D loss: 0.690852, acc.: 53.12%] [G loss: 0.724530]
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1313 [D loss: 0.683304, acc.: 55.66%] [G loss: 0.725551]
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1314 [D loss: 0.689894, acc.: 51.95%] [G loss: 0.725115]
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1315 [D loss: 0.691139, acc.: 50.98%] [G loss: 0.715972]
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1316 [D loss: 0.696395, acc.: 49.02%] [G loss: 0.731816]
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1317 [D loss: 0.689617, acc.: 54.49%] [G loss: 0.743701]
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1318 [D loss: 0.683675, acc.: 55.66%] [G loss: 0.775215]
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1319 [D loss: 0.688866, acc.: 56.05%] [G loss: 0.751648]
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1320 [D loss: 0.696563, acc.: 51.95%] [G loss: 0.729220]
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1321 [D loss: 0.695121, acc.: 50.39%] [G loss: 0.725365]
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1322 [D loss: 0.692768, acc.: 52.54%] [G loss: 0.720117]
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1323 [D loss: 0.686535, acc.: 56.64%] [G loss: 0.719663]
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1324 [D loss: 0.686766, acc.: 56.05%] [G loss: 0.712104]
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1325 [D loss: 0.693011, acc.: 54.30%] [G loss: 0.709623]
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1326 [D loss: 0.691148, acc.: 51.56%] [G loss: 0.715394]
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1327 [D loss: 0.689390, acc.: 54.69%] [G loss: 0.741897]
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1328 [D loss: 0.673970, acc.: 61.91%] [G loss: 0.752357]
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1329 [D loss: 0.675937, acc.: 61.33%] [G loss: 0.766344]
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1330 [D loss: 0.682263, acc.: 56.84%] [G loss: 0.752656]
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1331 [D loss: 0.692256, acc.: 53.91%] [G loss: 0.730061]
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1332 [D loss: 0.680604, acc.: 59.77%] [G loss: 0.729206]
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1333 [D loss: 0.680297, acc.: 56.84%] [G loss: 0.719554]
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1334 [D loss: 0.688307, acc.: 54.49%] [G loss: 0.697628]
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1335 [D loss: 0.704315, acc.: 47.46%] [G loss: 0.682045]
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1336 [D loss: 0.706045, acc.: 45.31%] [G loss: 0.688028]
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1337 [D loss: 0.693989, acc.: 51.17%] [G loss: 0.747693]
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1338 [D loss: 0.679141, acc.: 62.50%] [G loss: 0.774913]
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1339 [D loss: 0.680858, acc.: 58.98%] [G loss: 0.781244]
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1340 [D loss: 0.684848, acc.: 57.81%] [G loss: 0.745115]
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1341 [D loss: 0.691145, acc.: 53.12%] [G loss: 0.727646]
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1342 [D loss: 0.689103, acc.: 55.66%] [G loss: 0.733796]
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1343 [D loss: 0.683210, acc.: 58.01%] [G loss: 0.717668]
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1344 [D loss: 0.687092, acc.: 53.91%] [G loss: 0.711676]
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1345 [D loss: 0.699632, acc.: 48.24%] [G loss: 0.687253]
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1346 [D loss: 0.695863, acc.: 49.80%] [G loss: 0.698750]
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1347 [D loss: 0.691531, acc.: 53.91%] [G loss: 0.743273]
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1348 [D loss: 0.683434, acc.: 57.23%] [G loss: 0.786753]
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1349 [D loss: 0.687047, acc.: 55.86%] [G loss: 0.767528]
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1350 [D loss: 0.700401, acc.: 48.63%] [G loss: 0.728943]
1/1 [==============================] - 0s 23ms/step
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1351 [D loss: 0.692080, acc.: 55.08%] [G loss: 0.728464]
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1352 [D loss: 0.678114, acc.: 60.35%] [G loss: 0.744844]
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1353 [D loss: 0.673290, acc.: 61.91%] [G loss: 0.749142]
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1354 [D loss: 0.680548, acc.: 56.64%] [G loss: 0.723601]
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1355 [D loss: 0.696942, acc.: 50.59%] [G loss: 0.688976]
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1356 [D loss: 0.698623, acc.: 47.46%] [G loss: 0.703046]
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1357 [D loss: 0.691797, acc.: 53.91%] [G loss: 0.763608]
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1358 [D loss: 0.666738, acc.: 64.84%] [G loss: 0.805651]
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1359 [D loss: 0.684075, acc.: 55.86%] [G loss: 0.756799]
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1360 [D loss: 0.692965, acc.: 52.93%] [G loss: 0.733344]
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1361 [D loss: 0.685477, acc.: 58.59%] [G loss: 0.734155]
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1362 [D loss: 0.679866, acc.: 58.01%] [G loss: 0.743327]
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1363 [D loss: 0.678220, acc.: 59.18%] [G loss: 0.738840]
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1364 [D loss: 0.685305, acc.: 55.47%] [G loss: 0.716720]
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1365 [D loss: 0.699512, acc.: 48.63%] [G loss: 0.694226]
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1366 [D loss: 0.701976, acc.: 46.09%] [G loss: 0.707043]
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1367 [D loss: 0.686562, acc.: 54.30%] [G loss: 0.757822]
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1368 [D loss: 0.681125, acc.: 57.81%] [G loss: 0.754339]
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1369 [D loss: 0.684487, acc.: 56.45%] [G loss: 0.744570]
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1370 [D loss: 0.688223, acc.: 54.49%] [G loss: 0.739037]
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1371 [D loss: 0.688102, acc.: 54.69%] [G loss: 0.737897]
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1372 [D loss: 0.676446, acc.: 59.77%] [G loss: 0.735473]
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1373 [D loss: 0.678704, acc.: 58.98%] [G loss: 0.731880]
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1374 [D loss: 0.691814, acc.: 52.93%] [G loss: 0.711238]
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1375 [D loss: 0.700198, acc.: 46.68%] [G loss: 0.697445]
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1376 [D loss: 0.700647, acc.: 48.24%] [G loss: 0.705467]
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1377 [D loss: 0.688244, acc.: 54.88%] [G loss: 0.748916]
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1378 [D loss: 0.683500, acc.: 57.03%] [G loss: 0.785790]
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1379 [D loss: 0.690487, acc.: 53.91%] [G loss: 0.756601]
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1380 [D loss: 0.694402, acc.: 52.73%] [G loss: 0.738440]
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1381 [D loss: 0.683609, acc.: 60.94%] [G loss: 0.741620]
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1382 [D loss: 0.677208, acc.: 59.38%] [G loss: 0.738988]
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1383 [D loss: 0.679598, acc.: 58.40%] [G loss: 0.747325]
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1384 [D loss: 0.684233, acc.: 56.84%] [G loss: 0.728164]
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1385 [D loss: 0.688587, acc.: 57.62%] [G loss: 0.720322]
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1386 [D loss: 0.692365, acc.: 50.98%] [G loss: 0.721289]
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1387 [D loss: 0.683057, acc.: 56.84%] [G loss: 0.749605]
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1388 [D loss: 0.687634, acc.: 52.34%] [G loss: 0.745975]
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1389 [D loss: 0.689837, acc.: 55.27%] [G loss: 0.737008]
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1390 [D loss: 0.688008, acc.: 52.54%] [G loss: 0.732534]
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1391 [D loss: 0.687834, acc.: 55.66%] [G loss: 0.727980]
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1392 [D loss: 0.681519, acc.: 56.84%] [G loss: 0.722914]
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1393 [D loss: 0.678519, acc.: 55.86%] [G loss: 0.726958]
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1394 [D loss: 0.686446, acc.: 54.10%] [G loss: 0.722701]
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1395 [D loss: 0.691206, acc.: 52.34%] [G loss: 0.708480]
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1396 [D loss: 0.691923, acc.: 53.52%] [G loss: 0.728423]
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1397 [D loss: 0.678450, acc.: 59.38%] [G loss: 0.756621]
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1398 [D loss: 0.684780, acc.: 53.12%] [G loss: 0.762630]
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1399 [D loss: 0.693121, acc.: 52.15%] [G loss: 0.748062]
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1400 [D loss: 0.690120, acc.: 54.88%] [G loss: 0.728669]
1/1 [==============================] - 0s 23ms/step
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1401 [D loss: 0.694208, acc.: 52.34%] [G loss: 0.726070]
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1402 [D loss: 0.683856, acc.: 57.81%] [G loss: 0.723785]
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1403 [D loss: 0.687469, acc.: 54.88%] [G loss: 0.725871]
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1404 [D loss: 0.686810, acc.: 53.12%] [G loss: 0.716921]
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1405 [D loss: 0.688235, acc.: 54.69%] [G loss: 0.727188]
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1406 [D loss: 0.687651, acc.: 54.88%] [G loss: 0.739005]
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1407 [D loss: 0.681828, acc.: 54.49%] [G loss: 0.771972]
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1408 [D loss: 0.683057, acc.: 55.66%] [G loss: 0.747257]
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1409 [D loss: 0.692032, acc.: 52.54%] [G loss: 0.734958]
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1410 [D loss: 0.684691, acc.: 56.64%] [G loss: 0.732954]
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1411 [D loss: 0.690936, acc.: 53.32%] [G loss: 0.733432]
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1412 [D loss: 0.687961, acc.: 54.30%] [G loss: 0.707587]
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1413 [D loss: 0.694636, acc.: 50.20%] [G loss: 0.714150]
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1414 [D loss: 0.695437, acc.: 51.95%] [G loss: 0.709073]
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1415 [D loss: 0.695122, acc.: 46.48%] [G loss: 0.694981]
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1416 [D loss: 0.697139, acc.: 49.41%] [G loss: 0.736325]
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1417 [D loss: 0.677412, acc.: 59.57%] [G loss: 0.757490]
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1418 [D loss: 0.680488, acc.: 57.42%] [G loss: 0.758117]
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1419 [D loss: 0.685108, acc.: 57.42%] [G loss: 0.750251]
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1420 [D loss: 0.680748, acc.: 60.94%] [G loss: 0.740868]
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1421 [D loss: 0.681035, acc.: 59.38%] [G loss: 0.740019]
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1422 [D loss: 0.676238, acc.: 61.91%] [G loss: 0.737844]
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1423 [D loss: 0.680786, acc.: 59.38%] [G loss: 0.729986]
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1424 [D loss: 0.691328, acc.: 51.37%] [G loss: 0.709124]
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1425 [D loss: 0.697565, acc.: 49.02%] [G loss: 0.705189]
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1426 [D loss: 0.689433, acc.: 54.49%] [G loss: 0.724760]
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1427 [D loss: 0.690614, acc.: 53.52%] [G loss: 0.742095]
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1428 [D loss: 0.689999, acc.: 51.37%] [G loss: 0.734079]
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1429 [D loss: 0.695495, acc.: 51.37%] [G loss: 0.735080]
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1430 [D loss: 0.697764, acc.: 50.00%] [G loss: 0.745631]
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1431 [D loss: 0.687637, acc.: 54.10%] [G loss: 0.744618]
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1432 [D loss: 0.680851, acc.: 58.20%] [G loss: 0.742158]
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1433 [D loss: 0.683767, acc.: 57.23%] [G loss: 0.741759]
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1434 [D loss: 0.682591, acc.: 55.08%] [G loss: 0.734550]
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1435 [D loss: 0.691615, acc.: 52.93%] [G loss: 0.740636]
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1436 [D loss: 0.690632, acc.: 53.12%] [G loss: 0.741222]
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1437 [D loss: 0.688525, acc.: 52.54%] [G loss: 0.744732]
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1438 [D loss: 0.686707, acc.: 55.08%] [G loss: 0.736962]
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1439 [D loss: 0.699087, acc.: 50.00%] [G loss: 0.730157]
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1440 [D loss: 0.695586, acc.: 49.02%] [G loss: 0.720329]
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1441 [D loss: 0.696587, acc.: 48.63%] [G loss: 0.721290]
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1442 [D loss: 0.697672, acc.: 48.63%] [G loss: 0.713630]
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1443 [D loss: 0.696078, acc.: 49.02%] [G loss: 0.725687]
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1444 [D loss: 0.691223, acc.: 50.78%] [G loss: 0.728753]
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1445 [D loss: 0.688063, acc.: 53.91%] [G loss: 0.732822]
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1446 [D loss: 0.678075, acc.: 59.18%] [G loss: 0.740641]
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1447 [D loss: 0.676915, acc.: 58.79%] [G loss: 0.753113]
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1448 [D loss: 0.666640, acc.: 65.23%] [G loss: 0.757491]
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1449 [D loss: 0.673790, acc.: 59.96%] [G loss: 0.752449]
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1450 [D loss: 0.683224, acc.: 54.49%] [G loss: 0.747909]
1/1 [==============================] - 0s 27ms/step
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1451 [D loss: 0.686172, acc.: 57.03%] [G loss: 0.734702]
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1452 [D loss: 0.686217, acc.: 52.93%] [G loss: 0.713081]
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1453 [D loss: 0.688914, acc.: 52.73%] [G loss: 0.713670]
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1454 [D loss: 0.694636, acc.: 50.20%] [G loss: 0.704774]
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1455 [D loss: 0.697208, acc.: 50.39%] [G loss: 0.707491]
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1456 [D loss: 0.696018, acc.: 49.02%] [G loss: 0.719843]
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1457 [D loss: 0.688633, acc.: 52.54%] [G loss: 0.735025]
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1458 [D loss: 0.678333, acc.: 57.03%] [G loss: 0.771603]
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1459 [D loss: 0.676268, acc.: 58.20%] [G loss: 0.781483]
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1460 [D loss: 0.680844, acc.: 58.20%] [G loss: 0.763473]
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1461 [D loss: 0.688804, acc.: 56.05%] [G loss: 0.743785]
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1462 [D loss: 0.679104, acc.: 58.59%] [G loss: 0.742509]
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1463 [D loss: 0.677854, acc.: 58.59%] [G loss: 0.727053]
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1464 [D loss: 0.683469, acc.: 58.40%] [G loss: 0.710435]
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1465 [D loss: 0.693009, acc.: 52.54%] [G loss: 0.701171]
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1466 [D loss: 0.702528, acc.: 47.46%] [G loss: 0.703750]
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1467 [D loss: 0.701650, acc.: 47.07%] [G loss: 0.729468]
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1468 [D loss: 0.695959, acc.: 49.41%] [G loss: 0.762766]
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1469 [D loss: 0.683839, acc.: 55.86%] [G loss: 0.765667]
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1470 [D loss: 0.684491, acc.: 54.49%] [G loss: 0.762939]
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1471 [D loss: 0.695150, acc.: 49.41%] [G loss: 0.748372]
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1472 [D loss: 0.693411, acc.: 52.34%] [G loss: 0.742810]
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1473 [D loss: 0.678942, acc.: 58.98%] [G loss: 0.749845]
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1474 [D loss: 0.671795, acc.: 62.50%] [G loss: 0.746730]
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1475 [D loss: 0.675456, acc.: 60.35%] [G loss: 0.733280]
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1476 [D loss: 0.678603, acc.: 57.03%] [G loss: 0.713828]
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1477 [D loss: 0.695421, acc.: 49.80%] [G loss: 0.697805]
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1478 [D loss: 0.696939, acc.: 50.00%] [G loss: 0.713525]
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1479 [D loss: 0.682401, acc.: 55.08%] [G loss: 0.789711]
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1480 [D loss: 0.675850, acc.: 55.47%] [G loss: 0.791030]
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1481 [D loss: 0.702655, acc.: 48.24%] [G loss: 0.732645]
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1482 [D loss: 0.700833, acc.: 47.85%] [G loss: 0.715520]
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1483 [D loss: 0.692635, acc.: 53.71%] [G loss: 0.730082]
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1484 [D loss: 0.679181, acc.: 58.79%] [G loss: 0.745695]
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1485 [D loss: 0.679002, acc.: 57.23%] [G loss: 0.737506]
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1486 [D loss: 0.687974, acc.: 51.95%] [G loss: 0.725028]
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1487 [D loss: 0.694008, acc.: 49.61%] [G loss: 0.700447]
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1488 [D loss: 0.684851, acc.: 55.66%] [G loss: 0.747594]
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1489 [D loss: 0.686589, acc.: 55.86%] [G loss: 0.786520]
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1490 [D loss: 0.665110, acc.: 64.06%] [G loss: 0.827271]
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1491 [D loss: 0.684234, acc.: 54.69%] [G loss: 0.787507]
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1492 [D loss: 0.692285, acc.: 52.93%] [G loss: 0.729467]
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1493 [D loss: 0.693583, acc.: 52.34%] [G loss: 0.728122]
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1494 [D loss: 0.692070, acc.: 54.10%] [G loss: 0.732644]
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1495 [D loss: 0.689390, acc.: 54.10%] [G loss: 0.708206]
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1496 [D loss: 0.690371, acc.: 51.56%] [G loss: 0.707436]
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1497 [D loss: 0.700325, acc.: 47.07%] [G loss: 0.695915]
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1498 [D loss: 0.696104, acc.: 49.41%] [G loss: 0.696609]
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1499 [D loss: 0.695092, acc.: 52.73%] [G loss: 0.741235]
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1500 [D loss: 0.677947, acc.: 60.35%] [G loss: 0.792059]
1/1 [==============================] - 0s 24ms/step
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1501 [D loss: 0.670138, acc.: 60.55%] [G loss: 0.784028]
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1502 [D loss: 0.692767, acc.: 54.49%] [G loss: 0.752528]
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1503 [D loss: 0.690727, acc.: 56.84%] [G loss: 0.744074]
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1504 [D loss: 0.682562, acc.: 58.01%] [G loss: 0.746442]
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1505 [D loss: 0.681121, acc.: 59.38%] [G loss: 0.739928]
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1506 [D loss: 0.675923, acc.: 58.79%] [G loss: 0.728350]
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1507 [D loss: 0.692410, acc.: 52.73%] [G loss: 0.716492]
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1508 [D loss: 0.697842, acc.: 47.27%] [G loss: 0.711562]
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1509 [D loss: 0.694596, acc.: 51.56%] [G loss: 0.727869]
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1510 [D loss: 0.688905, acc.: 52.93%] [G loss: 0.742435]
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1511 [D loss: 0.681566, acc.: 54.69%] [G loss: 0.761503]
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1512 [D loss: 0.685322, acc.: 57.23%] [G loss: 0.749233]
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1513 [D loss: 0.687487, acc.: 51.95%] [G loss: 0.742149]
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1514 [D loss: 0.678044, acc.: 58.20%] [G loss: 0.733101]
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1515 [D loss: 0.687558, acc.: 52.34%] [G loss: 0.738049]
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1516 [D loss: 0.677755, acc.: 59.18%] [G loss: 0.731212]
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1517 [D loss: 0.678644, acc.: 56.25%] [G loss: 0.725499]
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1518 [D loss: 0.692276, acc.: 50.98%] [G loss: 0.718147]
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1519 [D loss: 0.691660, acc.: 52.73%] [G loss: 0.723778]
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1520 [D loss: 0.699406, acc.: 48.44%] [G loss: 0.726089]
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1521 [D loss: 0.686932, acc.: 53.71%] [G loss: 0.760872]
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1522 [D loss: 0.679274, acc.: 59.77%] [G loss: 0.775661]
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1523 [D loss: 0.685569, acc.: 55.66%] [G loss: 0.769972]
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1524 [D loss: 0.692948, acc.: 52.54%] [G loss: 0.748924]
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1525 [D loss: 0.685761, acc.: 57.42%] [G loss: 0.734911]
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1526 [D loss: 0.689416, acc.: 53.52%] [G loss: 0.725444]
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1527 [D loss: 0.686755, acc.: 54.30%] [G loss: 0.722105]
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1528 [D loss: 0.688776, acc.: 52.93%] [G loss: 0.721195]
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1529 [D loss: 0.696027, acc.: 51.37%] [G loss: 0.705514]
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1530 [D loss: 0.697353, acc.: 49.61%] [G loss: 0.720613]
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1531 [D loss: 0.689028, acc.: 50.59%] [G loss: 0.743570]
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1532 [D loss: 0.678978, acc.: 57.62%] [G loss: 0.769323]
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1533 [D loss: 0.685064, acc.: 54.10%] [G loss: 0.768725]
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1534 [D loss: 0.692771, acc.: 51.95%] [G loss: 0.747674]
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1535 [D loss: 0.696679, acc.: 53.12%] [G loss: 0.738576]
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1536 [D loss: 0.689188, acc.: 56.45%] [G loss: 0.713797]
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1537 [D loss: 0.684753, acc.: 57.03%] [G loss: 0.730054]
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1538 [D loss: 0.686870, acc.: 54.49%] [G loss: 0.725919]
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1539 [D loss: 0.690856, acc.: 52.73%] [G loss: 0.724404]
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1540 [D loss: 0.692911, acc.: 50.98%] [G loss: 0.711237]
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1541 [D loss: 0.692139, acc.: 53.52%] [G loss: 0.727811]
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1542 [D loss: 0.683179, acc.: 55.08%] [G loss: 0.758489]
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1543 [D loss: 0.677670, acc.: 57.42%] [G loss: 0.765298]
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1544 [D loss: 0.680169, acc.: 55.27%] [G loss: 0.754086]
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1545 [D loss: 0.693951, acc.: 51.95%] [G loss: 0.749650]
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1546 [D loss: 0.694209, acc.: 49.02%] [G loss: 0.736748]
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1547 [D loss: 0.682085, acc.: 58.01%] [G loss: 0.724999]
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1548 [D loss: 0.689969, acc.: 52.73%] [G loss: 0.726252]
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1549 [D loss: 0.685973, acc.: 52.15%] [G loss: 0.721189]
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1550 [D loss: 0.694902, acc.: 47.85%] [G loss: 0.710288]
1/1 [==============================] - 0s 25ms/step
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1551 [D loss: 0.692247, acc.: 53.12%] [G loss: 0.703549]
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1552 [D loss: 0.686128, acc.: 53.91%] [G loss: 0.712620]
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1553 [D loss: 0.697317, acc.: 50.00%] [G loss: 0.721067]
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1554 [D loss: 0.686812, acc.: 51.76%] [G loss: 0.761089]
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1555 [D loss: 0.677891, acc.: 61.72%] [G loss: 0.763506]
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1556 [D loss: 0.688917, acc.: 55.86%] [G loss: 0.756324]
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1557 [D loss: 0.685897, acc.: 55.47%] [G loss: 0.754396]
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1558 [D loss: 0.684416, acc.: 58.59%] [G loss: 0.738212]
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1559 [D loss: 0.679233, acc.: 58.20%] [G loss: 0.737064]
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1560 [D loss: 0.684412, acc.: 56.45%] [G loss: 0.738529]
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1561 [D loss: 0.682974, acc.: 55.47%] [G loss: 0.728122]
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1562 [D loss: 0.689731, acc.: 53.32%] [G loss: 0.704381]
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1563 [D loss: 0.698544, acc.: 49.80%] [G loss: 0.703376]
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1564 [D loss: 0.702136, acc.: 45.31%] [G loss: 0.729135]
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1565 [D loss: 0.693216, acc.: 52.54%] [G loss: 0.770706]
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1566 [D loss: 0.687460, acc.: 55.27%] [G loss: 0.775975]
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1567 [D loss: 0.695047, acc.: 51.56%] [G loss: 0.755389]
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1568 [D loss: 0.687072, acc.: 56.64%] [G loss: 0.745612]
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1569 [D loss: 0.689633, acc.: 54.10%] [G loss: 0.745735]
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1570 [D loss: 0.676686, acc.: 58.98%] [G loss: 0.753343]
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1571 [D loss: 0.670631, acc.: 61.72%] [G loss: 0.747374]
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1572 [D loss: 0.685695, acc.: 55.27%] [G loss: 0.715150]
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1573 [D loss: 0.691575, acc.: 51.17%] [G loss: 0.698359]
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1574 [D loss: 0.700846, acc.: 52.15%] [G loss: 0.698950]
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1575 [D loss: 0.696990, acc.: 50.39%] [G loss: 0.711530]
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1576 [D loss: 0.689309, acc.: 55.27%] [G loss: 0.740968]
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1577 [D loss: 0.679740, acc.: 57.62%] [G loss: 0.781695]
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1578 [D loss: 0.676473, acc.: 61.52%] [G loss: 0.766585]
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1579 [D loss: 0.685325, acc.: 54.88%] [G loss: 0.752838]
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1580 [D loss: 0.695793, acc.: 53.52%] [G loss: 0.743572]
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1581 [D loss: 0.690469, acc.: 53.52%] [G loss: 0.730617]
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1582 [D loss: 0.679194, acc.: 59.18%] [G loss: 0.737310]
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1583 [D loss: 0.673751, acc.: 62.30%] [G loss: 0.742815]
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1584 [D loss: 0.683572, acc.: 56.05%] [G loss: 0.716401]
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1585 [D loss: 0.699127, acc.: 49.02%] [G loss: 0.704630]
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1586 [D loss: 0.698222, acc.: 49.61%] [G loss: 0.693442]
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1587 [D loss: 0.702171, acc.: 50.39%] [G loss: 0.719871]
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1588 [D loss: 0.685759, acc.: 56.05%] [G loss: 0.760476]
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1589 [D loss: 0.676026, acc.: 59.18%] [G loss: 0.769967]
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1590 [D loss: 0.678966, acc.: 58.79%] [G loss: 0.765881]
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1591 [D loss: 0.693631, acc.: 50.98%] [G loss: 0.747776]
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1592 [D loss: 0.695237, acc.: 51.95%] [G loss: 0.736809]
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1593 [D loss: 0.689212, acc.: 52.93%] [G loss: 0.733966]
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1594 [D loss: 0.691094, acc.: 53.12%] [G loss: 0.725182]
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1595 [D loss: 0.689504, acc.: 54.10%] [G loss: 0.712750]
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1596 [D loss: 0.690989, acc.: 52.34%] [G loss: 0.707081]
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1597 [D loss: 0.693959, acc.: 50.98%] [G loss: 0.707160]
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1598 [D loss: 0.698700, acc.: 54.10%] [G loss: 0.736382]
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1599 [D loss: 0.680447, acc.: 56.84%] [G loss: 0.752684]
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1600 [D loss: 0.681120, acc.: 56.25%] [G loss: 0.791018]
1/1 [==============================] - 0s 22ms/step
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1601 [D loss: 0.677353, acc.: 57.42%] [G loss: 0.785965]
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1602 [D loss: 0.681968, acc.: 57.81%] [G loss: 0.780642]
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1603 [D loss: 0.687621, acc.: 56.84%] [G loss: 0.748038]
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1604 [D loss: 0.694401, acc.: 52.73%] [G loss: 0.739588]
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1605 [D loss: 0.683465, acc.: 56.05%] [G loss: 0.745416]
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1606 [D loss: 0.675250, acc.: 60.74%] [G loss: 0.743316]
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1607 [D loss: 0.671766, acc.: 61.13%] [G loss: 0.738495]
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1608 [D loss: 0.688158, acc.: 52.34%] [G loss: 0.705079]
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1609 [D loss: 0.690977, acc.: 51.76%] [G loss: 0.689457]
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1610 [D loss: 0.705034, acc.: 45.51%] [G loss: 0.686657]
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1611 [D loss: 0.696327, acc.: 50.78%] [G loss: 0.750224]
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1612 [D loss: 0.669836, acc.: 59.38%] [G loss: 0.815093]
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1613 [D loss: 0.680055, acc.: 56.64%] [G loss: 0.771115]
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1614 [D loss: 0.695147, acc.: 53.91%] [G loss: 0.740158]
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1615 [D loss: 0.682929, acc.: 59.38%] [G loss: 0.739780]
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1616 [D loss: 0.682673, acc.: 56.05%] [G loss: 0.748456]
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1617 [D loss: 0.672944, acc.: 61.52%] [G loss: 0.738897]
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1618 [D loss: 0.679407, acc.: 54.69%] [G loss: 0.712844]
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1619 [D loss: 0.705450, acc.: 49.02%] [G loss: 0.687114]
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1620 [D loss: 0.710505, acc.: 46.09%] [G loss: 0.691806]
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1621 [D loss: 0.696230, acc.: 50.98%] [G loss: 0.753243]
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1622 [D loss: 0.675359, acc.: 59.96%] [G loss: 0.798763]
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1623 [D loss: 0.680564, acc.: 53.71%] [G loss: 0.807312]
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1624 [D loss: 0.697170, acc.: 52.73%] [G loss: 0.766270]
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1625 [D loss: 0.692024, acc.: 55.08%] [G loss: 0.740086]
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1626 [D loss: 0.691995, acc.: 56.84%] [G loss: 0.739496]
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1627 [D loss: 0.681948, acc.: 59.18%] [G loss: 0.746074]
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1628 [D loss: 0.679103, acc.: 57.03%] [G loss: 0.733895]
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1629 [D loss: 0.690682, acc.: 51.56%] [G loss: 0.713230]
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1630 [D loss: 0.702608, acc.: 48.83%] [G loss: 0.701206]
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1631 [D loss: 0.699650, acc.: 48.83%] [G loss: 0.700878]
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1632 [D loss: 0.699809, acc.: 48.44%] [G loss: 0.744940]
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1633 [D loss: 0.681605, acc.: 56.64%] [G loss: 0.770698]
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1634 [D loss: 0.675424, acc.: 58.01%] [G loss: 0.804397]
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1635 [D loss: 0.685374, acc.: 53.52%] [G loss: 0.771001]
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1636 [D loss: 0.689487, acc.: 55.66%] [G loss: 0.745093]
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1637 [D loss: 0.679103, acc.: 59.96%] [G loss: 0.757297]
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1638 [D loss: 0.665169, acc.: 63.28%] [G loss: 0.748540]
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1639 [D loss: 0.670420, acc.: 61.33%] [G loss: 0.741358]
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1640 [D loss: 0.688404, acc.: 53.71%] [G loss: 0.716835]
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1641 [D loss: 0.700321, acc.: 49.02%] [G loss: 0.696547]
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1642 [D loss: 0.710185, acc.: 45.31%] [G loss: 0.694412]
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1643 [D loss: 0.698679, acc.: 50.59%] [G loss: 0.741867]
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1644 [D loss: 0.682862, acc.: 54.69%] [G loss: 0.777676]
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1645 [D loss: 0.688669, acc.: 54.30%] [G loss: 0.784565]
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1646 [D loss: 0.681874, acc.: 56.64%] [G loss: 0.766397]
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1647 [D loss: 0.690020, acc.: 53.71%] [G loss: 0.751592]
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1648 [D loss: 0.684558, acc.: 57.81%] [G loss: 0.749781]
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1649 [D loss: 0.667180, acc.: 66.41%] [G loss: 0.763264]
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1650 [D loss: 0.678681, acc.: 59.57%] [G loss: 0.737784]
1/1 [==============================] - 0s 23ms/step
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1651 [D loss: 0.689957, acc.: 53.32%] [G loss: 0.711237]
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1652 [D loss: 0.708074, acc.: 46.68%] [G loss: 0.688816]
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1653 [D loss: 0.706398, acc.: 49.80%] [G loss: 0.704168]
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1654 [D loss: 0.690597, acc.: 53.32%] [G loss: 0.737267]
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1655 [D loss: 0.682850, acc.: 57.62%] [G loss: 0.765954]
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1656 [D loss: 0.685321, acc.: 53.71%] [G loss: 0.751503]
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1657 [D loss: 0.689634, acc.: 53.12%] [G loss: 0.759936]
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1658 [D loss: 0.687246, acc.: 55.66%] [G loss: 0.750986]
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1659 [D loss: 0.686829, acc.: 55.66%] [G loss: 0.748191]
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1660 [D loss: 0.675532, acc.: 60.74%] [G loss: 0.748998]
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1661 [D loss: 0.686402, acc.: 54.88%] [G loss: 0.732241]
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1662 [D loss: 0.694918, acc.: 48.83%] [G loss: 0.710260]
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1663 [D loss: 0.704841, acc.: 49.22%] [G loss: 0.707259]
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1664 [D loss: 0.693509, acc.: 51.76%] [G loss: 0.721265]
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1665 [D loss: 0.695618, acc.: 52.54%] [G loss: 0.727936]
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1666 [D loss: 0.688781, acc.: 54.49%] [G loss: 0.753450]
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1667 [D loss: 0.693174, acc.: 54.10%] [G loss: 0.760965]
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1668 [D loss: 0.692429, acc.: 54.30%] [G loss: 0.748387]
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1669 [D loss: 0.687485, acc.: 55.08%] [G loss: 0.750374]
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1670 [D loss: 0.673912, acc.: 60.74%] [G loss: 0.753828]
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1671 [D loss: 0.675115, acc.: 57.81%] [G loss: 0.744750]
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1672 [D loss: 0.678826, acc.: 59.18%] [G loss: 0.732662]
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1673 [D loss: 0.686886, acc.: 54.69%] [G loss: 0.736411]
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1674 [D loss: 0.693355, acc.: 49.61%] [G loss: 0.707801]
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1675 [D loss: 0.692920, acc.: 52.73%] [G loss: 0.723154]
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1676 [D loss: 0.689583, acc.: 51.37%] [G loss: 0.738779]
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1677 [D loss: 0.692085, acc.: 53.52%] [G loss: 0.742525]
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1678 [D loss: 0.696161, acc.: 51.76%] [G loss: 0.745645]
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1679 [D loss: 0.691150, acc.: 54.10%] [G loss: 0.728243]
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1680 [D loss: 0.694085, acc.: 52.73%] [G loss: 0.737104]
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1681 [D loss: 0.682093, acc.: 57.81%] [G loss: 0.742751]
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1682 [D loss: 0.678438, acc.: 58.40%] [G loss: 0.749125]
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1683 [D loss: 0.683879, acc.: 56.05%] [G loss: 0.740746]
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1684 [D loss: 0.683598, acc.: 54.49%] [G loss: 0.728882]
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1685 [D loss: 0.694213, acc.: 50.00%] [G loss: 0.725585]
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1686 [D loss: 0.698590, acc.: 48.63%] [G loss: 0.726956]
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1687 [D loss: 0.698466, acc.: 47.07%] [G loss: 0.746135]
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1688 [D loss: 0.693601, acc.: 51.95%] [G loss: 0.734671]
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1689 [D loss: 0.692308, acc.: 51.17%] [G loss: 0.743528]
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1690 [D loss: 0.694072, acc.: 50.98%] [G loss: 0.737849]
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1691 [D loss: 0.686744, acc.: 53.91%] [G loss: 0.740417]
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1692 [D loss: 0.690835, acc.: 52.73%] [G loss: 0.742306]
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1693 [D loss: 0.690420, acc.: 54.49%] [G loss: 0.744547]
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1694 [D loss: 0.685967, acc.: 54.49%] [G loss: 0.738133]
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1695 [D loss: 0.684460, acc.: 54.69%] [G loss: 0.739666]
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1696 [D loss: 0.688971, acc.: 54.10%] [G loss: 0.738975]
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1697 [D loss: 0.686505, acc.: 54.10%] [G loss: 0.727384]
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1698 [D loss: 0.686117, acc.: 54.69%] [G loss: 0.746098]
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1699 [D loss: 0.683912, acc.: 54.69%] [G loss: 0.753932]
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1700 [D loss: 0.689101, acc.: 53.52%] [G loss: 0.738212]
1/1 [==============================] - 0s 24ms/step
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1701 [D loss: 0.691210, acc.: 52.15%] [G loss: 0.745455]
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1702 [D loss: 0.694464, acc.: 51.95%] [G loss: 0.734008]
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1703 [D loss: 0.700969, acc.: 47.27%] [G loss: 0.743031]
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1704 [D loss: 0.687938, acc.: 53.91%] [G loss: 0.739511]
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1705 [D loss: 0.688267, acc.: 49.80%] [G loss: 0.737018]
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1706 [D loss: 0.680839, acc.: 57.23%] [G loss: 0.744820]
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1707 [D loss: 0.677875, acc.: 58.01%] [G loss: 0.750686]
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1708 [D loss: 0.674406, acc.: 60.74%] [G loss: 0.760216]
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1709 [D loss: 0.673873, acc.: 59.38%] [G loss: 0.739840]
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1710 [D loss: 0.692267, acc.: 53.32%] [G loss: 0.734829]
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1711 [D loss: 0.689109, acc.: 50.59%] [G loss: 0.732594]
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1712 [D loss: 0.696867, acc.: 48.05%] [G loss: 0.719457]
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1713 [D loss: 0.702719, acc.: 46.68%] [G loss: 0.714929]
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1714 [D loss: 0.703270, acc.: 47.27%] [G loss: 0.722228]
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1715 [D loss: 0.700052, acc.: 48.05%] [G loss: 0.728814]
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1716 [D loss: 0.694942, acc.: 48.05%] [G loss: 0.726996]
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1717 [D loss: 0.687104, acc.: 53.12%] [G loss: 0.738868]
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1718 [D loss: 0.687217, acc.: 52.73%] [G loss: 0.746482]
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1719 [D loss: 0.688040, acc.: 56.25%] [G loss: 0.742066]
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1720 [D loss: 0.684676, acc.: 59.18%] [G loss: 0.755846]
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1721 [D loss: 0.684939, acc.: 53.52%] [G loss: 0.750725]
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1722 [D loss: 0.686849, acc.: 54.49%] [G loss: 0.742512]
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1723 [D loss: 0.684606, acc.: 58.20%] [G loss: 0.737049]
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1724 [D loss: 0.692377, acc.: 50.78%] [G loss: 0.730761]
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1725 [D loss: 0.693143, acc.: 51.37%] [G loss: 0.742060]
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1726 [D loss: 0.689131, acc.: 51.37%] [G loss: 0.737452]
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1727 [D loss: 0.693983, acc.: 53.12%] [G loss: 0.729364]
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1728 [D loss: 0.698554, acc.: 50.59%] [G loss: 0.728695]
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1729 [D loss: 0.694593, acc.: 52.34%] [G loss: 0.735279]
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1730 [D loss: 0.686162, acc.: 54.30%] [G loss: 0.741346]
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1731 [D loss: 0.680310, acc.: 58.59%] [G loss: 0.741863]
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1732 [D loss: 0.677696, acc.: 58.79%] [G loss: 0.768403]
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1733 [D loss: 0.681433, acc.: 58.98%] [G loss: 0.750492]
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1734 [D loss: 0.677788, acc.: 57.62%] [G loss: 0.739092]
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1735 [D loss: 0.665349, acc.: 61.72%] [G loss: 0.725206]
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1736 [D loss: 0.689222, acc.: 55.27%] [G loss: 0.724495]
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1737 [D loss: 0.689732, acc.: 55.27%] [G loss: 0.712605]
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1738 [D loss: 0.707592, acc.: 44.73%] [G loss: 0.716947]
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1739 [D loss: 0.703809, acc.: 47.66%] [G loss: 0.726898]
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1740 [D loss: 0.693904, acc.: 51.95%] [G loss: 0.743407]
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1741 [D loss: 0.687360, acc.: 55.66%] [G loss: 0.741657]
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1742 [D loss: 0.687779, acc.: 51.95%] [G loss: 0.749610]
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1743 [D loss: 0.693712, acc.: 51.37%] [G loss: 0.742539]
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1744 [D loss: 0.689041, acc.: 54.30%] [G loss: 0.739129]
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1745 [D loss: 0.684450, acc.: 53.71%] [G loss: 0.737299]
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1746 [D loss: 0.677019, acc.: 59.38%] [G loss: 0.734537]
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1747 [D loss: 0.685100, acc.: 54.30%] [G loss: 0.727955]
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1748 [D loss: 0.684757, acc.: 52.34%] [G loss: 0.718204]
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1749 [D loss: 0.691501, acc.: 51.37%] [G loss: 0.712956]
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1750 [D loss: 0.692287, acc.: 51.56%] [G loss: 0.734674]
1/1 [==============================] - 0s 27ms/step
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1751 [D loss: 0.684735, acc.: 55.08%] [G loss: 0.740323]
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1752 [D loss: 0.693703, acc.: 52.54%] [G loss: 0.763145]
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1753 [D loss: 0.688361, acc.: 51.56%] [G loss: 0.760503]
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1754 [D loss: 0.682315, acc.: 54.49%] [G loss: 0.760220]
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1755 [D loss: 0.689508, acc.: 54.49%] [G loss: 0.743457]
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1756 [D loss: 0.682204, acc.: 57.03%] [G loss: 0.745095]
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1757 [D loss: 0.683566, acc.: 58.59%] [G loss: 0.750159]
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1758 [D loss: 0.679772, acc.: 57.42%] [G loss: 0.736178]
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1759 [D loss: 0.674491, acc.: 60.35%] [G loss: 0.721132]
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1760 [D loss: 0.680213, acc.: 55.66%] [G loss: 0.719196]
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1761 [D loss: 0.700841, acc.: 48.24%] [G loss: 0.712993]
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1762 [D loss: 0.690855, acc.: 53.12%] [G loss: 0.705295]
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1763 [D loss: 0.695644, acc.: 52.54%] [G loss: 0.751068]
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1764 [D loss: 0.692219, acc.: 51.76%] [G loss: 0.762500]
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1765 [D loss: 0.693762, acc.: 49.80%] [G loss: 0.763311]
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1766 [D loss: 0.700544, acc.: 49.02%] [G loss: 0.750844]
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1767 [D loss: 0.694617, acc.: 49.80%] [G loss: 0.736260]
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1768 [D loss: 0.691774, acc.: 49.02%] [G loss: 0.734923]
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1769 [D loss: 0.682579, acc.: 53.52%] [G loss: 0.745724]
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1770 [D loss: 0.664584, acc.: 66.80%] [G loss: 0.738594]
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1771 [D loss: 0.671252, acc.: 59.77%] [G loss: 0.727932]
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1772 [D loss: 0.682608, acc.: 56.84%] [G loss: 0.717455]
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1773 [D loss: 0.690589, acc.: 53.71%] [G loss: 0.732677]
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1774 [D loss: 0.689369, acc.: 51.56%] [G loss: 0.756141]
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1775 [D loss: 0.683047, acc.: 54.49%] [G loss: 0.779663]
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1776 [D loss: 0.688895, acc.: 56.05%] [G loss: 0.781391]
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1777 [D loss: 0.701387, acc.: 48.83%] [G loss: 0.758132]
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1778 [D loss: 0.698955, acc.: 46.68%] [G loss: 0.729157]
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1779 [D loss: 0.696338, acc.: 50.20%] [G loss: 0.725594]
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1780 [D loss: 0.688589, acc.: 55.66%] [G loss: 0.751002]
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1781 [D loss: 0.674392, acc.: 59.18%] [G loss: 0.754522]
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1782 [D loss: 0.677104, acc.: 55.47%] [G loss: 0.751222]
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1783 [D loss: 0.681299, acc.: 56.25%] [G loss: 0.736300]
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1784 [D loss: 0.677756, acc.: 56.84%] [G loss: 0.733968]
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1785 [D loss: 0.699497, acc.: 47.07%] [G loss: 0.732045]
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1786 [D loss: 0.699659, acc.: 50.78%] [G loss: 0.742708]
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1787 [D loss: 0.704480, acc.: 47.07%] [G loss: 0.729526]
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1788 [D loss: 0.705321, acc.: 47.46%] [G loss: 0.727607]
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1789 [D loss: 0.695766, acc.: 50.59%] [G loss: 0.714560]
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1790 [D loss: 0.691164, acc.: 52.93%] [G loss: 0.725199]
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1791 [D loss: 0.692011, acc.: 53.91%] [G loss: 0.728567]
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1792 [D loss: 0.687363, acc.: 55.86%] [G loss: 0.738958]
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1793 [D loss: 0.691740, acc.: 52.34%] [G loss: 0.740092]
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1794 [D loss: 0.679184, acc.: 59.18%] [G loss: 0.751182]
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1795 [D loss: 0.675722, acc.: 60.55%] [G loss: 0.757576]
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1796 [D loss: 0.671700, acc.: 59.96%] [G loss: 0.762652]
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1797 [D loss: 0.677022, acc.: 56.84%] [G loss: 0.752411]
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1798 [D loss: 0.681197, acc.: 57.03%] [G loss: 0.751998]
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1799 [D loss: 0.683837, acc.: 55.27%] [G loss: 0.730646]
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1800 [D loss: 0.693303, acc.: 51.17%] [G loss: 0.732078]
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1801 [D loss: 0.692232, acc.: 51.95%] [G loss: 0.741067]
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1802 [D loss: 0.695592, acc.: 51.56%] [G loss: 0.717915]
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1803 [D loss: 0.705241, acc.: 49.02%] [G loss: 0.737513]
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1804 [D loss: 0.701001, acc.: 50.20%] [G loss: 0.763412]
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1805 [D loss: 0.692980, acc.: 52.54%] [G loss: 0.787723]
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1806 [D loss: 0.687434, acc.: 54.69%] [G loss: 0.770277]
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1807 [D loss: 0.698048, acc.: 51.56%] [G loss: 0.752330]
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1808 [D loss: 0.682337, acc.: 58.98%] [G loss: 0.751124]
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1809 [D loss: 0.685360, acc.: 53.91%] [G loss: 0.748443]
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1810 [D loss: 0.686297, acc.: 53.32%] [G loss: 0.742906]
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1811 [D loss: 0.683573, acc.: 54.69%] [G loss: 0.727454]
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1812 [D loss: 0.695463, acc.: 50.98%] [G loss: 0.725218]
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1813 [D loss: 0.696976, acc.: 50.98%] [G loss: 0.730055]
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1814 [D loss: 0.686364, acc.: 54.88%] [G loss: 0.758509]
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1815 [D loss: 0.690408, acc.: 53.32%] [G loss: 0.783810]
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1816 [D loss: 0.677887, acc.: 59.96%] [G loss: 0.779792]
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1817 [D loss: 0.687632, acc.: 52.73%] [G loss: 0.760413]
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1818 [D loss: 0.695883, acc.: 50.98%] [G loss: 0.735902]
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1819 [D loss: 0.687502, acc.: 55.86%] [G loss: 0.745542]
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1820 [D loss: 0.685024, acc.: 54.30%] [G loss: 0.745890]
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1821 [D loss: 0.675752, acc.: 60.74%] [G loss: 0.746985]
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1822 [D loss: 0.678669, acc.: 55.86%] [G loss: 0.735530]
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1823 [D loss: 0.682736, acc.: 56.45%] [G loss: 0.723871]
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1824 [D loss: 0.694129, acc.: 50.59%] [G loss: 0.733173]
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1825 [D loss: 0.686002, acc.: 55.08%] [G loss: 0.760308]
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1826 [D loss: 0.672743, acc.: 57.81%] [G loss: 0.785715]
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1827 [D loss: 0.696972, acc.: 47.27%] [G loss: 0.778359]
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1828 [D loss: 0.694932, acc.: 50.59%] [G loss: 0.748108]
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1829 [D loss: 0.697643, acc.: 50.20%] [G loss: 0.738164]
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1830 [D loss: 0.701311, acc.: 47.85%] [G loss: 0.741526]
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1831 [D loss: 0.682789, acc.: 58.20%] [G loss: 0.749126]
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1832 [D loss: 0.671675, acc.: 62.50%] [G loss: 0.748906]
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1833 [D loss: 0.671818, acc.: 58.98%] [G loss: 0.750810]
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1834 [D loss: 0.677223, acc.: 57.42%] [G loss: 0.734942]
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1835 [D loss: 0.685523, acc.: 55.27%] [G loss: 0.725332]
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1836 [D loss: 0.704187, acc.: 46.48%] [G loss: 0.719392]
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1837 [D loss: 0.700505, acc.: 49.41%] [G loss: 0.733754]
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1838 [D loss: 0.686970, acc.: 52.93%] [G loss: 0.739485]
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1839 [D loss: 0.694127, acc.: 49.61%] [G loss: 0.744956]
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1840 [D loss: 0.699374, acc.: 48.44%] [G loss: 0.738481]
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1841 [D loss: 0.698717, acc.: 51.37%] [G loss: 0.736962]
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1842 [D loss: 0.682348, acc.: 56.64%] [G loss: 0.747575]
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1843 [D loss: 0.689566, acc.: 51.76%] [G loss: 0.740754]
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1844 [D loss: 0.683592, acc.: 55.08%] [G loss: 0.737536]
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1845 [D loss: 0.690516, acc.: 53.91%] [G loss: 0.746395]
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1846 [D loss: 0.686566, acc.: 53.12%] [G loss: 0.761358]
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1847 [D loss: 0.676962, acc.: 57.81%] [G loss: 0.756689]
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1848 [D loss: 0.669483, acc.: 60.74%] [G loss: 0.763879]
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1849 [D loss: 0.679145, acc.: 57.42%] [G loss: 0.760552]
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1850 [D loss: 0.684060, acc.: 55.27%] [G loss: 0.752583]
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1851 [D loss: 0.685492, acc.: 58.59%] [G loss: 0.742465]
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1852 [D loss: 0.683134, acc.: 57.23%] [G loss: 0.724117]
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1853 [D loss: 0.686335, acc.: 53.91%] [G loss: 0.725862]
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1854 [D loss: 0.691477, acc.: 53.71%] [G loss: 0.719763]
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1855 [D loss: 0.691335, acc.: 52.34%] [G loss: 0.704669]
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1856 [D loss: 0.690722, acc.: 56.05%] [G loss: 0.731648]
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1857 [D loss: 0.690597, acc.: 55.47%] [G loss: 0.743650]
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1858 [D loss: 0.689887, acc.: 52.34%] [G loss: 0.773901]
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1859 [D loss: 0.692477, acc.: 53.32%] [G loss: 0.768023]
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1860 [D loss: 0.687694, acc.: 55.47%] [G loss: 0.740452]
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1861 [D loss: 0.689123, acc.: 53.32%] [G loss: 0.742906]
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1862 [D loss: 0.691887, acc.: 50.78%] [G loss: 0.728243]
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1863 [D loss: 0.684354, acc.: 55.47%] [G loss: 0.727384]
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1864 [D loss: 0.687400, acc.: 52.54%] [G loss: 0.710149]
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1865 [D loss: 0.687516, acc.: 52.15%] [G loss: 0.693965]
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1866 [D loss: 0.698513, acc.: 45.70%] [G loss: 0.694903]
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1867 [D loss: 0.704407, acc.: 44.92%] [G loss: 0.718556]
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1868 [D loss: 0.687335, acc.: 54.30%] [G loss: 0.774826]
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1869 [D loss: 0.678652, acc.: 57.03%] [G loss: 0.799534]
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1870 [D loss: 0.672377, acc.: 61.52%] [G loss: 0.793110]
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1871 [D loss: 0.681774, acc.: 58.01%] [G loss: 0.764997]
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1872 [D loss: 0.674911, acc.: 62.70%] [G loss: 0.780426]
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1873 [D loss: 0.668761, acc.: 65.62%] [G loss: 0.773822]
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1874 [D loss: 0.679129, acc.: 56.64%] [G loss: 0.752654]
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1875 [D loss: 0.686285, acc.: 55.08%] [G loss: 0.728378]
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1876 [D loss: 0.703542, acc.: 48.44%] [G loss: 0.702228]
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1877 [D loss: 0.705123, acc.: 48.83%] [G loss: 0.709163]
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1878 [D loss: 0.704778, acc.: 49.02%] [G loss: 0.727632]
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1879 [D loss: 0.689192, acc.: 53.52%] [G loss: 0.780405]
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1880 [D loss: 0.684592, acc.: 57.62%] [G loss: 0.782881]
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1881 [D loss: 0.686414, acc.: 56.84%] [G loss: 0.758283]
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1882 [D loss: 0.688264, acc.: 55.27%] [G loss: 0.757198]
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1883 [D loss: 0.679433, acc.: 60.35%] [G loss: 0.757829]
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1884 [D loss: 0.673739, acc.: 65.23%] [G loss: 0.750232]
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1885 [D loss: 0.676203, acc.: 59.77%] [G loss: 0.758213]
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1886 [D loss: 0.680583, acc.: 58.01%] [G loss: 0.730972]
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1887 [D loss: 0.684277, acc.: 55.47%] [G loss: 0.717172]
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1888 [D loss: 0.702963, acc.: 48.44%] [G loss: 0.717263]
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1889 [D loss: 0.702065, acc.: 47.27%] [G loss: 0.729272]
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1890 [D loss: 0.693942, acc.: 50.78%] [G loss: 0.751521]
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1891 [D loss: 0.683919, acc.: 53.71%] [G loss: 0.783940]
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1892 [D loss: 0.687663, acc.: 50.98%] [G loss: 0.773895]
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1893 [D loss: 0.699020, acc.: 49.41%] [G loss: 0.753157]
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1894 [D loss: 0.699773, acc.: 48.63%] [G loss: 0.744503]
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1895 [D loss: 0.686328, acc.: 56.45%] [G loss: 0.746013]
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1896 [D loss: 0.690443, acc.: 52.93%] [G loss: 0.737782]
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1897 [D loss: 0.688605, acc.: 55.08%] [G loss: 0.734989]
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1898 [D loss: 0.689773, acc.: 53.52%] [G loss: 0.717945]
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1899 [D loss: 0.693343, acc.: 51.76%] [G loss: 0.714912]
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1900 [D loss: 0.700359, acc.: 48.05%] [G loss: 0.718279]
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1901 [D loss: 0.689006, acc.: 53.71%] [G loss: 0.749116]
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1902 [D loss: 0.687604, acc.: 52.93%] [G loss: 0.762459]
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1903 [D loss: 0.682895, acc.: 56.64%] [G loss: 0.776130]
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1904 [D loss: 0.691723, acc.: 50.39%] [G loss: 0.745490]
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1905 [D loss: 0.682349, acc.: 57.42%] [G loss: 0.747984]
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1906 [D loss: 0.690422, acc.: 55.08%] [G loss: 0.738205]
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1907 [D loss: 0.689469, acc.: 52.34%] [G loss: 0.729752]
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1908 [D loss: 0.682556, acc.: 57.81%] [G loss: 0.729994]
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1909 [D loss: 0.676374, acc.: 58.20%] [G loss: 0.730207]
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1910 [D loss: 0.691162, acc.: 51.17%] [G loss: 0.730471]
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1911 [D loss: 0.687889, acc.: 53.52%] [G loss: 0.718983]
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1912 [D loss: 0.689323, acc.: 52.54%] [G loss: 0.730323]
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1913 [D loss: 0.694514, acc.: 50.20%] [G loss: 0.749912]
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1914 [D loss: 0.685438, acc.: 51.95%] [G loss: 0.767603]
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1915 [D loss: 0.686957, acc.: 56.45%] [G loss: 0.759097]
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1916 [D loss: 0.687037, acc.: 54.69%] [G loss: 0.767820]
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1917 [D loss: 0.684929, acc.: 56.25%] [G loss: 0.748045]
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1918 [D loss: 0.701663, acc.: 50.78%] [G loss: 0.744005]
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1919 [D loss: 0.685727, acc.: 53.52%] [G loss: 0.733707]
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1920 [D loss: 0.689795, acc.: 53.91%] [G loss: 0.733684]
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1921 [D loss: 0.686879, acc.: 52.93%] [G loss: 0.732461]
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1922 [D loss: 0.693527, acc.: 52.54%] [G loss: 0.724156]
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1923 [D loss: 0.686379, acc.: 52.54%] [G loss: 0.727576]
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1924 [D loss: 0.677971, acc.: 56.45%] [G loss: 0.736179]
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1925 [D loss: 0.697682, acc.: 49.80%] [G loss: 0.752023]
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1926 [D loss: 0.686124, acc.: 54.30%] [G loss: 0.770508]
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1927 [D loss: 0.688921, acc.: 54.69%] [G loss: 0.773926]
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1928 [D loss: 0.693123, acc.: 52.15%] [G loss: 0.762124]
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1929 [D loss: 0.694648, acc.: 50.98%] [G loss: 0.738098]
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1930 [D loss: 0.694556, acc.: 53.12%] [G loss: 0.730614]
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1931 [D loss: 0.689289, acc.: 53.32%] [G loss: 0.731044]
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1932 [D loss: 0.682785, acc.: 56.45%] [G loss: 0.720811]
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1933 [D loss: 0.687899, acc.: 56.25%] [G loss: 0.725953]
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1934 [D loss: 0.687119, acc.: 55.08%] [G loss: 0.716295]
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1935 [D loss: 0.690769, acc.: 52.93%] [G loss: 0.715671]
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1936 [D loss: 0.687306, acc.: 55.08%] [G loss: 0.721669]
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1937 [D loss: 0.690712, acc.: 52.73%] [G loss: 0.718541]
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1938 [D loss: 0.688074, acc.: 52.73%] [G loss: 0.743900]
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1939 [D loss: 0.685396, acc.: 55.47%] [G loss: 0.746615]
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1940 [D loss: 0.687851, acc.: 52.73%] [G loss: 0.738714]
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1941 [D loss: 0.690955, acc.: 51.95%] [G loss: 0.746186]
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1942 [D loss: 0.689715, acc.: 55.08%] [G loss: 0.745463]
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1943 [D loss: 0.687324, acc.: 55.47%] [G loss: 0.737195]
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1944 [D loss: 0.682837, acc.: 54.30%] [G loss: 0.745298]
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1945 [D loss: 0.684679, acc.: 56.64%] [G loss: 0.732286]
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1946 [D loss: 0.694100, acc.: 51.95%] [G loss: 0.724710]
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1947 [D loss: 0.704524, acc.: 48.05%] [G loss: 0.713147]
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1948 [D loss: 0.697498, acc.: 51.17%] [G loss: 0.728378]
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1949 [D loss: 0.688048, acc.: 54.30%] [G loss: 0.751777]
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1950 [D loss: 0.693716, acc.: 54.10%] [G loss: 0.752108]
1/1 [==============================] - 0s 25ms/step
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1951 [D loss: 0.695660, acc.: 51.56%] [G loss: 0.753052]
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1952 [D loss: 0.682335, acc.: 57.62%] [G loss: 0.771430]
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1953 [D loss: 0.682071, acc.: 59.38%] [G loss: 0.757895]
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1954 [D loss: 0.680066, acc.: 59.77%] [G loss: 0.749890]
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1955 [D loss: 0.684772, acc.: 57.03%] [G loss: 0.749647]
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1956 [D loss: 0.686940, acc.: 55.86%] [G loss: 0.726882]
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1957 [D loss: 0.687206, acc.: 53.12%] [G loss: 0.723245]
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1958 [D loss: 0.690474, acc.: 50.98%] [G loss: 0.724430]
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1959 [D loss: 0.698655, acc.: 52.73%] [G loss: 0.712697]
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1960 [D loss: 0.700852, acc.: 50.20%] [G loss: 0.722303]
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1961 [D loss: 0.703522, acc.: 48.44%] [G loss: 0.736880]
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1962 [D loss: 0.693840, acc.: 51.95%] [G loss: 0.747264]
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1963 [D loss: 0.691909, acc.: 52.54%] [G loss: 0.749562]
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1964 [D loss: 0.692344, acc.: 50.98%] [G loss: 0.749540]
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1965 [D loss: 0.691096, acc.: 50.78%] [G loss: 0.734183]
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1966 [D loss: 0.682461, acc.: 57.42%] [G loss: 0.729535]
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1967 [D loss: 0.685517, acc.: 53.71%] [G loss: 0.731492]
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1968 [D loss: 0.683270, acc.: 57.23%] [G loss: 0.745947]
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1969 [D loss: 0.679814, acc.: 54.88%] [G loss: 0.738684]
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1970 [D loss: 0.677634, acc.: 55.47%] [G loss: 0.732100]
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1971 [D loss: 0.691896, acc.: 52.73%] [G loss: 0.717224]
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1972 [D loss: 0.697220, acc.: 53.71%] [G loss: 0.731297]
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1973 [D loss: 0.697060, acc.: 51.17%] [G loss: 0.735655]
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1974 [D loss: 0.693836, acc.: 52.73%] [G loss: 0.727925]
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1975 [D loss: 0.696284, acc.: 51.76%] [G loss: 0.742821]
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1976 [D loss: 0.700284, acc.: 51.17%] [G loss: 0.749241]
8/8 [==============================] - 0s 4ms/step
1977 [D loss: 0.696519, acc.: 50.00%] [G loss: 0.738917]
8/8 [==============================] - 0s 4ms/step
1978 [D loss: 0.691556, acc.: 47.66%] [G loss: 0.730463]
8/8 [==============================] - 0s 4ms/step
1979 [D loss: 0.684534, acc.: 56.64%] [G loss: 0.738555]
8/8 [==============================] - 0s 4ms/step
1980 [D loss: 0.681014, acc.: 56.64%] [G loss: 0.734464]
8/8 [==============================] - 0s 4ms/step
1981 [D loss: 0.688638, acc.: 50.59%] [G loss: 0.732114]
8/8 [==============================] - 0s 4ms/step
1982 [D loss: 0.692766, acc.: 49.80%] [G loss: 0.729991]
8/8 [==============================] - 0s 4ms/step
1983 [D loss: 0.694369, acc.: 51.37%] [G loss: 0.719048]
8/8 [==============================] - 0s 4ms/step
1984 [D loss: 0.687544, acc.: 54.88%] [G loss: 0.749262]
8/8 [==============================] - 0s 4ms/step
1985 [D loss: 0.686192, acc.: 53.32%] [G loss: 0.766699]
8/8 [==============================] - 0s 4ms/step
1986 [D loss: 0.687059, acc.: 51.95%] [G loss: 0.758741]
8/8 [==============================] - 0s 4ms/step
1987 [D loss: 0.691598, acc.: 51.37%] [G loss: 0.746735]
8/8 [==============================] - 0s 4ms/step
1988 [D loss: 0.692306, acc.: 54.10%] [G loss: 0.746424]
8/8 [==============================] - 0s 4ms/step
1989 [D loss: 0.687944, acc.: 54.30%] [G loss: 0.752093]
8/8 [==============================] - 0s 4ms/step
1990 [D loss: 0.684214, acc.: 57.23%] [G loss: 0.736843]
8/8 [==============================] - 0s 4ms/step
1991 [D loss: 0.684918, acc.: 54.69%] [G loss: 0.739715]
8/8 [==============================] - 0s 4ms/step
1992 [D loss: 0.685288, acc.: 53.12%] [G loss: 0.738836]
8/8 [==============================] - 0s 4ms/step
1993 [D loss: 0.687875, acc.: 53.71%] [G loss: 0.743682]
8/8 [==============================] - 0s 5ms/step
1994 [D loss: 0.692013, acc.: 51.95%] [G loss: 0.722428]
8/8 [==============================] - 0s 4ms/step
1995 [D loss: 0.699489, acc.: 46.48%] [G loss: 0.711429]
8/8 [==============================] - 0s 4ms/step
1996 [D loss: 0.700620, acc.: 49.61%] [G loss: 0.732776]
8/8 [==============================] - 0s 4ms/step
1997 [D loss: 0.694436, acc.: 49.22%] [G loss: 0.745557]
8/8 [==============================] - 0s 4ms/step
1998 [D loss: 0.690028, acc.: 51.17%] [G loss: 0.765108]
8/8 [==============================] - 0s 4ms/step
1999 [D loss: 0.695012, acc.: 50.39%] [G loss: 0.748731]
8/8 [==============================] - 0s 4ms/step
2000 [D loss: 0.695074, acc.: 49.61%] [G loss: 0.739040]
1/1 [==============================] - 0s 28ms/step
8/8 [==============================] - 0s 4ms/step
2001 [D loss: 0.689450, acc.: 52.93%] [G loss: 0.726774]
8/8 [==============================] - 0s 4ms/step
2002 [D loss: 0.690679, acc.: 52.34%] [G loss: 0.726534]
8/8 [==============================] - 0s 4ms/step
2003 [D loss: 0.689910, acc.: 53.71%] [G loss: 0.724379]
8/8 [==============================] - 0s 4ms/step
2004 [D loss: 0.679341, acc.: 59.18%] [G loss: 0.723650]
8/8 [==============================] - 0s 4ms/step
2005 [D loss: 0.683803, acc.: 54.49%] [G loss: 0.715773]
8/8 [==============================] - 0s 4ms/step
2006 [D loss: 0.687472, acc.: 52.54%] [G loss: 0.723155]
8/8 [==============================] - 0s 4ms/step
2007 [D loss: 0.684015, acc.: 55.86%] [G loss: 0.712159]
8/8 [==============================] - 0s 4ms/step
2008 [D loss: 0.686283, acc.: 53.91%] [G loss: 0.724153]
8/8 [==============================] - 0s 4ms/step
2009 [D loss: 0.681231, acc.: 54.49%] [G loss: 0.750819]
8/8 [==============================] - 0s 4ms/step
2010 [D loss: 0.692758, acc.: 50.59%] [G loss: 0.743126]
8/8 [==============================] - 0s 4ms/step
2011 [D loss: 0.684419, acc.: 54.10%] [G loss: 0.759932]
8/8 [==============================] - 0s 4ms/step
2012 [D loss: 0.685483, acc.: 55.66%] [G loss: 0.756257]
8/8 [==============================] - 0s 4ms/step
2013 [D loss: 0.692930, acc.: 50.00%] [G loss: 0.758565]
8/8 [==============================] - 0s 4ms/step
2014 [D loss: 0.694744, acc.: 52.15%] [G loss: 0.748438]
8/8 [==============================] - 0s 4ms/step
2015 [D loss: 0.697011, acc.: 51.56%] [G loss: 0.739889]
8/8 [==============================] - 0s 4ms/step
2016 [D loss: 0.698035, acc.: 52.73%] [G loss: 0.727510]
8/8 [==============================] - 0s 4ms/step
2017 [D loss: 0.682901, acc.: 55.08%] [G loss: 0.726989]
8/8 [==============================] - 0s 4ms/step
2018 [D loss: 0.693481, acc.: 52.73%] [G loss: 0.720407]
8/8 [==============================] - 0s 4ms/step
2019 [D loss: 0.693803, acc.: 52.93%] [G loss: 0.721896]
8/8 [==============================] - 0s 4ms/step
2020 [D loss: 0.688671, acc.: 53.91%] [G loss: 0.737978]
8/8 [==============================] - 0s 4ms/step
2021 [D loss: 0.687958, acc.: 52.54%] [G loss: 0.747999]
8/8 [==============================] - 0s 4ms/step
2022 [D loss: 0.691478, acc.: 53.71%] [G loss: 0.762140]
8/8 [==============================] - 0s 4ms/step
2023 [D loss: 0.687720, acc.: 52.93%] [G loss: 0.766888]
8/8 [==============================] - 0s 4ms/step
2024 [D loss: 0.680036, acc.: 57.42%] [G loss: 0.782785]
8/8 [==============================] - 0s 4ms/step
2025 [D loss: 0.689770, acc.: 54.10%] [G loss: 0.780391]
8/8 [==============================] - 0s 4ms/step
2026 [D loss: 0.690141, acc.: 53.91%] [G loss: 0.759163]
8/8 [==============================] - 0s 4ms/step
2027 [D loss: 0.690429, acc.: 54.30%] [G loss: 0.741334]
8/8 [==============================] - 0s 4ms/step
2028 [D loss: 0.688126, acc.: 58.01%] [G loss: 0.739654]
8/8 [==============================] - 0s 4ms/step
2029 [D loss: 0.681301, acc.: 57.81%] [G loss: 0.722743]
8/8 [==============================] - 0s 4ms/step
2030 [D loss: 0.678175, acc.: 58.01%] [G loss: 0.723690]
8/8 [==============================] - 0s 4ms/step
2031 [D loss: 0.691359, acc.: 53.52%] [G loss: 0.699343]
8/8 [==============================] - 0s 4ms/step
2032 [D loss: 0.687619, acc.: 54.69%] [G loss: 0.693723]
8/8 [==============================] - 0s 4ms/step
2033 [D loss: 0.705940, acc.: 48.05%] [G loss: 0.689474]
8/8 [==============================] - 0s 4ms/step
2034 [D loss: 0.702593, acc.: 49.80%] [G loss: 0.714715]
8/8 [==============================] - 0s 4ms/step
2035 [D loss: 0.697829, acc.: 53.12%] [G loss: 0.755125]
8/8 [==============================] - 0s 4ms/step
2036 [D loss: 0.685717, acc.: 54.30%] [G loss: 0.790739]
8/8 [==============================] - 0s 4ms/step
2037 [D loss: 0.682611, acc.: 55.66%] [G loss: 0.771020]
8/8 [==============================] - 0s 4ms/step
2038 [D loss: 0.684863, acc.: 53.52%] [G loss: 0.755916]
8/8 [==============================] - 0s 4ms/step
2039 [D loss: 0.690361, acc.: 52.93%] [G loss: 0.746493]
8/8 [==============================] - 0s 4ms/step
2040 [D loss: 0.683945, acc.: 55.08%] [G loss: 0.744093]
8/8 [==============================] - 0s 4ms/step
2041 [D loss: 0.681100, acc.: 60.74%] [G loss: 0.741782]
8/8 [==============================] - 0s 4ms/step
2042 [D loss: 0.680671, acc.: 57.62%] [G loss: 0.732700]
8/8 [==============================] - 0s 4ms/step
2043 [D loss: 0.681265, acc.: 56.25%] [G loss: 0.739958]
8/8 [==============================] - 0s 4ms/step
2044 [D loss: 0.686643, acc.: 54.49%] [G loss: 0.702424]
8/8 [==============================] - 0s 4ms/step
2045 [D loss: 0.689536, acc.: 51.37%] [G loss: 0.694362]
8/8 [==============================] - 0s 4ms/step
2046 [D loss: 0.698251, acc.: 51.56%] [G loss: 0.701131]
8/8 [==============================] - 0s 4ms/step
2047 [D loss: 0.697502, acc.: 52.73%] [G loss: 0.726159]
8/8 [==============================] - 0s 5ms/step
2048 [D loss: 0.690190, acc.: 54.88%] [G loss: 0.755833]
8/8 [==============================] - 0s 4ms/step
2049 [D loss: 0.687893, acc.: 55.66%] [G loss: 0.761494]
8/8 [==============================] - 0s 4ms/step
2050 [D loss: 0.686169, acc.: 56.84%] [G loss: 0.748429]
1/1 [==============================] - 0s 26ms/step
8/8 [==============================] - 0s 4ms/step
2051 [D loss: 0.697059, acc.: 51.95%] [G loss: 0.740068]
8/8 [==============================] - 0s 6ms/step
2052 [D loss: 0.693943, acc.: 52.73%] [G loss: 0.725688]
8/8 [==============================] - 0s 4ms/step
2053 [D loss: 0.685159, acc.: 55.86%] [G loss: 0.734831]
8/8 [==============================] - 0s 4ms/step
2054 [D loss: 0.687035, acc.: 54.30%] [G loss: 0.735278]
8/8 [==============================] - 0s 4ms/step
2055 [D loss: 0.684575, acc.: 56.05%] [G loss: 0.720798]
8/8 [==============================] - 0s 4ms/step
2056 [D loss: 0.677545, acc.: 57.03%] [G loss: 0.720458]
8/8 [==============================] - 0s 4ms/step
2057 [D loss: 0.681304, acc.: 55.86%] [G loss: 0.712886]
8/8 [==============================] - 0s 4ms/step
2058 [D loss: 0.693411, acc.: 53.91%] [G loss: 0.705362]
8/8 [==============================] - 0s 4ms/step
2059 [D loss: 0.693312, acc.: 51.37%] [G loss: 0.707657]
8/8 [==============================] - 0s 4ms/step
2060 [D loss: 0.687921, acc.: 54.88%] [G loss: 0.739251]
8/8 [==============================] - 0s 4ms/step
2061 [D loss: 0.681025, acc.: 56.45%] [G loss: 0.767468]
8/8 [==============================] - 0s 4ms/step
2062 [D loss: 0.685921, acc.: 52.73%] [G loss: 0.774354]
8/8 [==============================] - 0s 4ms/step
2063 [D loss: 0.686146, acc.: 56.05%] [G loss: 0.754337]
8/8 [==============================] - 0s 4ms/step
2064 [D loss: 0.698126, acc.: 52.93%] [G loss: 0.733969]
8/8 [==============================] - 0s 4ms/step
2065 [D loss: 0.691237, acc.: 53.32%] [G loss: 0.735696]
8/8 [==============================] - 0s 4ms/step
2066 [D loss: 0.687217, acc.: 56.25%] [G loss: 0.732853]
8/8 [==============================] - 0s 4ms/step
2067 [D loss: 0.690195, acc.: 53.91%] [G loss: 0.744911]
8/8 [==============================] - 0s 4ms/step
2068 [D loss: 0.684452, acc.: 55.27%] [G loss: 0.731868]
8/8 [==============================] - 0s 4ms/step
2069 [D loss: 0.685110, acc.: 54.30%] [G loss: 0.714600]
8/8 [==============================] - 0s 4ms/step
2070 [D loss: 0.681214, acc.: 53.71%] [G loss: 0.718967]
8/8 [==============================] - 0s 4ms/step
2071 [D loss: 0.690739, acc.: 52.54%] [G loss: 0.720519]
8/8 [==============================] - 0s 4ms/step
2072 [D loss: 0.687651, acc.: 50.59%] [G loss: 0.746365]
8/8 [==============================] - 0s 4ms/step
2073 [D loss: 0.681071, acc.: 58.20%] [G loss: 0.776055]
8/8 [==============================] - 0s 4ms/step
2074 [D loss: 0.686911, acc.: 52.34%] [G loss: 0.752857]
8/8 [==============================] - 0s 4ms/step
2075 [D loss: 0.693665, acc.: 51.76%] [G loss: 0.754281]
8/8 [==============================] - 0s 4ms/step
2076 [D loss: 0.690184, acc.: 53.12%] [G loss: 0.741031]
8/8 [==============================] - 0s 5ms/step
2077 [D loss: 0.689220, acc.: 55.86%] [G loss: 0.738664]
8/8 [==============================] - 0s 4ms/step
2078 [D loss: 0.689807, acc.: 50.00%] [G loss: 0.720652]
8/8 [==============================] - 0s 4ms/step
2079 [D loss: 0.683568, acc.: 54.69%] [G loss: 0.729072]
8/8 [==============================] - 0s 4ms/step
2080 [D loss: 0.693475, acc.: 52.54%] [G loss: 0.725703]
8/8 [==============================] - 0s 4ms/step
2081 [D loss: 0.686922, acc.: 52.54%] [G loss: 0.742478]
8/8 [==============================] - 0s 4ms/step
2082 [D loss: 0.689961, acc.: 53.12%] [G loss: 0.740443]
8/8 [==============================] - 0s 4ms/step
2083 [D loss: 0.696226, acc.: 52.15%] [G loss: 0.745793]
8/8 [==============================] - 0s 4ms/step
2084 [D loss: 0.682868, acc.: 58.59%] [G loss: 0.750842]
8/8 [==============================] - 0s 4ms/step
2085 [D loss: 0.684025, acc.: 57.03%] [G loss: 0.746490]
8/8 [==============================] - 0s 4ms/step
2086 [D loss: 0.682613, acc.: 54.49%] [G loss: 0.727249]
8/8 [==============================] - 0s 4ms/step
2087 [D loss: 0.688853, acc.: 53.52%] [G loss: 0.731943]
8/8 [==============================] - 0s 4ms/step
2088 [D loss: 0.692261, acc.: 52.34%] [G loss: 0.727012]
8/8 [==============================] - 0s 4ms/step
2089 [D loss: 0.685546, acc.: 56.84%] [G loss: 0.718719]
8/8 [==============================] - 0s 4ms/step
2090 [D loss: 0.694494, acc.: 50.98%] [G loss: 0.714812]
8/8 [==============================] - 0s 4ms/step
2091 [D loss: 0.688293, acc.: 53.91%] [G loss: 0.720766]
8/8 [==============================] - 0s 4ms/step
2092 [D loss: 0.697322, acc.: 51.95%] [G loss: 0.724915]
8/8 [==============================] - 0s 4ms/step
2093 [D loss: 0.699170, acc.: 48.24%] [G loss: 0.732247]
8/8 [==============================] - 0s 4ms/step
2094 [D loss: 0.697397, acc.: 52.93%] [G loss: 0.733939]
8/8 [==============================] - 0s 4ms/step
2095 [D loss: 0.687539, acc.: 55.08%] [G loss: 0.740090]
8/8 [==============================] - 0s 4ms/step
2096 [D loss: 0.696801, acc.: 53.32%] [G loss: 0.740813]
8/8 [==============================] - 0s 4ms/step
2097 [D loss: 0.685866, acc.: 54.88%] [G loss: 0.747977]
8/8 [==============================] - 0s 4ms/step
2098 [D loss: 0.691436, acc.: 53.12%] [G loss: 0.747655]
8/8 [==============================] - 0s 4ms/step
2099 [D loss: 0.687010, acc.: 53.71%] [G loss: 0.733103]
8/8 [==============================] - 0s 4ms/step
2100 [D loss: 0.694126, acc.: 50.59%] [G loss: 0.741009]
1/1 [==============================] - 0s 25ms/step
8/8 [==============================] - 0s 4ms/step
2101 [D loss: 0.685183, acc.: 54.69%] [G loss: 0.724563]
8/8 [==============================] - 0s 4ms/step
2102 [D loss: 0.685552, acc.: 54.69%] [G loss: 0.726595]
8/8 [==============================] - 0s 4ms/step
2103 [D loss: 0.687894, acc.: 52.73%] [G loss: 0.725082]
8/8 [==============================] - 0s 4ms/step
2104 [D loss: 0.688815, acc.: 51.37%] [G loss: 0.719058]
8/8 [==============================] - 0s 4ms/step
2105 [D loss: 0.689480, acc.: 53.91%] [G loss: 0.725221]
8/8 [==============================] - 0s 4ms/step
2106 [D loss: 0.687446, acc.: 55.86%] [G loss: 0.739866]
8/8 [==============================] - 0s 4ms/step
2107 [D loss: 0.694573, acc.: 52.73%] [G loss: 0.750588]
8/8 [==============================] - 0s 4ms/step
2108 [D loss: 0.685292, acc.: 56.84%] [G loss: 0.754330]
8/8 [==============================] - 0s 4ms/step
2109 [D loss: 0.683866, acc.: 55.27%] [G loss: 0.750162]
8/8 [==============================] - 0s 4ms/step
2110 [D loss: 0.696975, acc.: 50.39%] [G loss: 0.744461]
8/8 [==============================] - 0s 4ms/step
2111 [D loss: 0.681929, acc.: 57.42%] [G loss: 0.736445]
8/8 [==============================] - 0s 4ms/step
2112 [D loss: 0.705866, acc.: 47.07%] [G loss: 0.746638]
8/8 [==============================] - 0s 4ms/step
2113 [D loss: 0.693753, acc.: 50.39%] [G loss: 0.722679]
8/8 [==============================] - 0s 4ms/step
2114 [D loss: 0.696402, acc.: 50.20%] [G loss: 0.733270]
8/8 [==============================] - 0s 4ms/step
2115 [D loss: 0.686214, acc.: 53.52%] [G loss: 0.721951]
8/8 [==============================] - 0s 4ms/step
2116 [D loss: 0.693975, acc.: 53.52%] [G loss: 0.713031]
8/8 [==============================] - 0s 4ms/step
2117 [D loss: 0.693565, acc.: 50.00%] [G loss: 0.718452]
8/8 [==============================] - 0s 4ms/step
2118 [D loss: 0.686882, acc.: 51.37%] [G loss: 0.726181]
8/8 [==============================] - 0s 4ms/step
2119 [D loss: 0.688995, acc.: 51.95%] [G loss: 0.721091]
8/8 [==============================] - 0s 4ms/step
2120 [D loss: 0.692481, acc.: 49.41%] [G loss: 0.725039]
8/8 [==============================] - 0s 4ms/step
2121 [D loss: 0.686448, acc.: 56.05%] [G loss: 0.735335]
8/8 [==============================] - 0s 4ms/step
2122 [D loss: 0.693037, acc.: 51.95%] [G loss: 0.735188]
8/8 [==============================] - 0s 4ms/step
2123 [D loss: 0.691262, acc.: 54.10%] [G loss: 0.753197]
8/8 [==============================] - 0s 4ms/step
2124 [D loss: 0.692221, acc.: 51.95%] [G loss: 0.760878]
8/8 [==============================] - 0s 4ms/step
2125 [D loss: 0.689697, acc.: 56.64%] [G loss: 0.766410]
8/8 [==============================] - 0s 4ms/step
2126 [D loss: 0.689794, acc.: 52.34%] [G loss: 0.753273]
8/8 [==============================] - 0s 4ms/step
2127 [D loss: 0.686490, acc.: 57.23%] [G loss: 0.735720]
8/8 [==============================] - 0s 4ms/step
2128 [D loss: 0.690021, acc.: 53.91%] [G loss: 0.742095]
8/8 [==============================] - 0s 4ms/step
2129 [D loss: 0.685605, acc.: 57.03%] [G loss: 0.741799]
8/8 [==============================] - 0s 5ms/step
2130 [D loss: 0.683083, acc.: 56.25%] [G loss: 0.723066]
8/8 [==============================] - 0s 4ms/step
2131 [D loss: 0.686602, acc.: 56.25%] [G loss: 0.715653]
8/8 [==============================] - 0s 4ms/step
2132 [D loss: 0.687118, acc.: 55.27%] [G loss: 0.714523]
8/8 [==============================] - 0s 4ms/step
2133 [D loss: 0.703361, acc.: 47.07%] [G loss: 0.684696]
8/8 [==============================] - 0s 4ms/step
2134 [D loss: 0.697997, acc.: 51.76%] [G loss: 0.703297]
8/8 [==============================] - 0s 4ms/step
2135 [D loss: 0.707388, acc.: 49.41%] [G loss: 0.718532]
8/8 [==============================] - 0s 4ms/step
2136 [D loss: 0.689047, acc.: 50.20%] [G loss: 0.734221]
8/8 [==============================] - 0s 4ms/step
2137 [D loss: 0.701394, acc.: 49.80%] [G loss: 0.721971]
8/8 [==============================] - 0s 4ms/step
2138 [D loss: 0.684272, acc.: 55.66%] [G loss: 0.754067]
8/8 [==============================] - 0s 4ms/step
2139 [D loss: 0.680442, acc.: 54.88%] [G loss: 0.761529]
8/8 [==============================] - 0s 4ms/step
2140 [D loss: 0.678022, acc.: 59.96%] [G loss: 0.761727]
8/8 [==============================] - 0s 4ms/step
2141 [D loss: 0.677004, acc.: 60.16%] [G loss: 0.763797]
8/8 [==============================] - 0s 4ms/step
2142 [D loss: 0.679561, acc.: 60.35%] [G loss: 0.739656]
8/8 [==============================] - 0s 4ms/step
2143 [D loss: 0.681031, acc.: 55.47%] [G loss: 0.721200]
8/8 [==============================] - 0s 4ms/step
2144 [D loss: 0.692775, acc.: 53.32%] [G loss: 0.708762]
8/8 [==============================] - 0s 4ms/step
2145 [D loss: 0.697786, acc.: 52.73%] [G loss: 0.687155]
8/8 [==============================] - 0s 4ms/step
2146 [D loss: 0.710269, acc.: 43.95%] [G loss: 0.693538]
8/8 [==============================] - 0s 4ms/step
2147 [D loss: 0.703036, acc.: 44.92%] [G loss: 0.716903]
8/8 [==============================] - 0s 4ms/step
2148 [D loss: 0.694834, acc.: 50.20%] [G loss: 0.748869]
8/8 [==============================] - 0s 4ms/step
2149 [D loss: 0.681914, acc.: 55.47%] [G loss: 0.776670]
8/8 [==============================] - 0s 4ms/step
2150 [D loss: 0.689166, acc.: 54.49%] [G loss: 0.777139]
1/1 [==============================] - 0s 31ms/step
8/8 [==============================] - 0s 4ms/step
2151 [D loss: 0.689762, acc.: 54.10%] [G loss: 0.760389]
8/8 [==============================] - 0s 4ms/step
2152 [D loss: 0.697131, acc.: 53.91%] [G loss: 0.746820]
8/8 [==============================] - 0s 4ms/step
2153 [D loss: 0.682619, acc.: 54.88%] [G loss: 0.742247]
8/8 [==============================] - 0s 4ms/step
2154 [D loss: 0.679962, acc.: 57.62%] [G loss: 0.736215]
8/8 [==============================] - 0s 4ms/step
2155 [D loss: 0.682668, acc.: 56.05%] [G loss: 0.737262]
8/8 [==============================] - 0s 4ms/step
2156 [D loss: 0.674323, acc.: 56.64%] [G loss: 0.729467]
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2157 [D loss: 0.687676, acc.: 52.54%] [G loss: 0.716542]
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2158 [D loss: 0.689162, acc.: 51.95%] [G loss: 0.698129]
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2159 [D loss: 0.695506, acc.: 49.61%] [G loss: 0.710521]
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2160 [D loss: 0.694498, acc.: 51.56%] [G loss: 0.713876]
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2161 [D loss: 0.691734, acc.: 48.05%] [G loss: 0.755289]
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2162 [D loss: 0.690571, acc.: 54.30%] [G loss: 0.773351]
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2163 [D loss: 0.693120, acc.: 52.54%] [G loss: 0.774548]
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2164 [D loss: 0.692913, acc.: 53.12%] [G loss: 0.746886]
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2165 [D loss: 0.693339, acc.: 54.49%] [G loss: 0.755599]
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2166 [D loss: 0.685945, acc.: 57.42%] [G loss: 0.753351]
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2167 [D loss: 0.676641, acc.: 60.74%] [G loss: 0.739041]
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2168 [D loss: 0.682201, acc.: 56.25%] [G loss: 0.725064]
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2169 [D loss: 0.684965, acc.: 55.47%] [G loss: 0.720677]
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2170 [D loss: 0.691434, acc.: 54.30%] [G loss: 0.702631]
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2171 [D loss: 0.691511, acc.: 51.37%] [G loss: 0.706986]
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2172 [D loss: 0.691654, acc.: 53.52%] [G loss: 0.735758]
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2173 [D loss: 0.687313, acc.: 54.49%] [G loss: 0.745293]
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2174 [D loss: 0.691760, acc.: 56.25%] [G loss: 0.771884]
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2175 [D loss: 0.684174, acc.: 54.10%] [G loss: 0.778654]
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2176 [D loss: 0.680353, acc.: 59.77%] [G loss: 0.759558]
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2177 [D loss: 0.688388, acc.: 55.86%] [G loss: 0.750968]
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2178 [D loss: 0.689426, acc.: 57.62%] [G loss: 0.745104]
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2179 [D loss: 0.682241, acc.: 55.08%] [G loss: 0.736184]
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2180 [D loss: 0.682043, acc.: 58.20%] [G loss: 0.735682]
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2181 [D loss: 0.680649, acc.: 57.62%] [G loss: 0.729361]
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2182 [D loss: 0.691522, acc.: 55.47%] [G loss: 0.716084]
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2183 [D loss: 0.688990, acc.: 56.25%] [G loss: 0.695639]
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2184 [D loss: 0.688559, acc.: 53.32%] [G loss: 0.709606]
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2185 [D loss: 0.697054, acc.: 51.76%] [G loss: 0.727310]
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2186 [D loss: 0.698759, acc.: 50.59%] [G loss: 0.756029]
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2187 [D loss: 0.688404, acc.: 53.71%] [G loss: 0.772598]
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2188 [D loss: 0.691256, acc.: 52.93%] [G loss: 0.754523]
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2189 [D loss: 0.707702, acc.: 47.27%] [G loss: 0.737972]
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2190 [D loss: 0.692209, acc.: 50.00%] [G loss: 0.733067]
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2191 [D loss: 0.682339, acc.: 56.84%] [G loss: 0.742150]
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2192 [D loss: 0.675101, acc.: 56.84%] [G loss: 0.746925]
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2193 [D loss: 0.676059, acc.: 59.18%] [G loss: 0.733344]
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2194 [D loss: 0.679401, acc.: 56.84%] [G loss: 0.728222]
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2195 [D loss: 0.687953, acc.: 53.52%] [G loss: 0.726091]
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2196 [D loss: 0.688401, acc.: 54.49%] [G loss: 0.714133]
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2197 [D loss: 0.688153, acc.: 53.32%] [G loss: 0.728974]
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2198 [D loss: 0.693196, acc.: 51.56%] [G loss: 0.719798]
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2199 [D loss: 0.701828, acc.: 49.02%] [G loss: 0.726419]
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2200 [D loss: 0.699016, acc.: 52.54%] [G loss: 0.733026]
1/1 [==============================] - 0s 26ms/step
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2201 [D loss: 0.684741, acc.: 56.64%] [G loss: 0.743273]
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2202 [D loss: 0.681405, acc.: 56.05%] [G loss: 0.758058]
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2203 [D loss: 0.683562, acc.: 57.03%] [G loss: 0.753387]
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2204 [D loss: 0.682925, acc.: 56.84%] [G loss: 0.751227]
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2205 [D loss: 0.679367, acc.: 58.01%] [G loss: 0.756913]
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2206 [D loss: 0.683625, acc.: 54.88%] [G loss: 0.750267]
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2207 [D loss: 0.682561, acc.: 55.08%] [G loss: 0.736274]
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2208 [D loss: 0.691276, acc.: 52.34%] [G loss: 0.750960]
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2209 [D loss: 0.696809, acc.: 51.76%] [G loss: 0.738549]
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2210 [D loss: 0.699558, acc.: 50.20%] [G loss: 0.737946]
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2211 [D loss: 0.690609, acc.: 53.12%] [G loss: 0.757003]
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2212 [D loss: 0.698181, acc.: 48.44%] [G loss: 0.769237]
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2213 [D loss: 0.691200, acc.: 51.76%] [G loss: 0.770878]
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2214 [D loss: 0.690171, acc.: 54.69%] [G loss: 0.773336]
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2215 [D loss: 0.693520, acc.: 51.76%] [G loss: 0.763375]
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2216 [D loss: 0.686077, acc.: 55.27%] [G loss: 0.757485]
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2217 [D loss: 0.679558, acc.: 57.62%] [G loss: 0.754440]
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2218 [D loss: 0.677411, acc.: 59.38%] [G loss: 0.756955]
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2219 [D loss: 0.681535, acc.: 55.47%] [G loss: 0.745138]
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2220 [D loss: 0.677268, acc.: 58.40%] [G loss: 0.738329]
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2221 [D loss: 0.690102, acc.: 52.93%] [G loss: 0.727707]
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2222 [D loss: 0.697912, acc.: 50.39%] [G loss: 0.711818]
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2223 [D loss: 0.696208, acc.: 52.34%] [G loss: 0.749614]
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2224 [D loss: 0.682967, acc.: 53.91%] [G loss: 0.757905]
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2225 [D loss: 0.691605, acc.: 50.59%] [G loss: 0.752518]
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2226 [D loss: 0.704661, acc.: 47.66%] [G loss: 0.738044]
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2227 [D loss: 0.699468, acc.: 49.80%] [G loss: 0.730922]
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2228 [D loss: 0.688230, acc.: 56.25%] [G loss: 0.736443]
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2229 [D loss: 0.686976, acc.: 54.69%] [G loss: 0.731791]
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2230 [D loss: 0.678079, acc.: 58.98%] [G loss: 0.725228]
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2231 [D loss: 0.683305, acc.: 58.20%] [G loss: 0.706074]
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2232 [D loss: 0.682726, acc.: 57.81%] [G loss: 0.717307]
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2233 [D loss: 0.691136, acc.: 55.47%] [G loss: 0.732343]
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2234 [D loss: 0.687329, acc.: 55.27%] [G loss: 0.741701]
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2235 [D loss: 0.681160, acc.: 54.69%] [G loss: 0.744294]
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2236 [D loss: 0.688064, acc.: 53.12%] [G loss: 0.738961]
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2237 [D loss: 0.690885, acc.: 52.15%] [G loss: 0.735297]
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2238 [D loss: 0.691325, acc.: 53.12%] [G loss: 0.746972]
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2239 [D loss: 0.694465, acc.: 50.00%] [G loss: 0.744935]
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2240 [D loss: 0.689124, acc.: 52.54%] [G loss: 0.726088]
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2241 [D loss: 0.694844, acc.: 52.93%] [G loss: 0.740780]
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2242 [D loss: 0.692798, acc.: 50.39%] [G loss: 0.734536]
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2243 [D loss: 0.681154, acc.: 57.81%] [G loss: 0.731282]
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2244 [D loss: 0.690359, acc.: 52.54%] [G loss: 0.734380]
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2245 [D loss: 0.682653, acc.: 58.40%] [G loss: 0.741224]
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2246 [D loss: 0.691692, acc.: 51.17%] [G loss: 0.771907]
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2247 [D loss: 0.690010, acc.: 53.71%] [G loss: 0.775045]
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2248 [D loss: 0.685144, acc.: 58.59%] [G loss: 0.755546]
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2249 [D loss: 0.684177, acc.: 59.18%] [G loss: 0.763081]
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2250 [D loss: 0.685729, acc.: 53.32%] [G loss: 0.746030]
1/1 [==============================] - 0s 25ms/step
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2251 [D loss: 0.678888, acc.: 58.98%] [G loss: 0.752137]
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2252 [D loss: 0.677456, acc.: 58.79%] [G loss: 0.742815]
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2253 [D loss: 0.690613, acc.: 51.76%] [G loss: 0.737059]
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2254 [D loss: 0.682978, acc.: 56.64%] [G loss: 0.713698]
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2255 [D loss: 0.692212, acc.: 54.10%] [G loss: 0.725817]
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2256 [D loss: 0.692858, acc.: 49.61%] [G loss: 0.726133]
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2257 [D loss: 0.683857, acc.: 58.40%] [G loss: 0.719017]
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2258 [D loss: 0.689834, acc.: 51.76%] [G loss: 0.719232]
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2259 [D loss: 0.695513, acc.: 51.76%] [G loss: 0.721910]
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2260 [D loss: 0.699440, acc.: 49.80%] [G loss: 0.724810]
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2261 [D loss: 0.689760, acc.: 54.30%] [G loss: 0.717690]
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2262 [D loss: 0.686412, acc.: 56.25%] [G loss: 0.708675]
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2263 [D loss: 0.683432, acc.: 56.64%] [G loss: 0.726785]
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2264 [D loss: 0.698308, acc.: 50.98%] [G loss: 0.730994]
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2265 [D loss: 0.688704, acc.: 54.69%] [G loss: 0.732592]
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2266 [D loss: 0.684628, acc.: 55.47%] [G loss: 0.749538]
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2267 [D loss: 0.683461, acc.: 55.66%] [G loss: 0.738701]
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2268 [D loss: 0.686721, acc.: 55.47%] [G loss: 0.725757]
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2269 [D loss: 0.689705, acc.: 51.95%] [G loss: 0.740784]
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2270 [D loss: 0.686441, acc.: 55.08%] [G loss: 0.744507]
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2271 [D loss: 0.693360, acc.: 52.54%] [G loss: 0.731199]
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2272 [D loss: 0.688451, acc.: 51.95%] [G loss: 0.726689]
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2273 [D loss: 0.687652, acc.: 53.32%] [G loss: 0.736223]
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2274 [D loss: 0.698225, acc.: 50.78%] [G loss: 0.731463]
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2275 [D loss: 0.690730, acc.: 52.15%] [G loss: 0.752104]
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2276 [D loss: 0.689025, acc.: 54.10%] [G loss: 0.745974]
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2277 [D loss: 0.685587, acc.: 56.45%] [G loss: 0.735301]
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2278 [D loss: 0.693054, acc.: 49.02%] [G loss: 0.747959]
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2279 [D loss: 0.694770, acc.: 51.37%] [G loss: 0.748220]
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2280 [D loss: 0.687464, acc.: 52.73%] [G loss: 0.741272]
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2281 [D loss: 0.686550, acc.: 54.10%] [G loss: 0.746525]
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2282 [D loss: 0.683375, acc.: 56.25%] [G loss: 0.737010]
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2283 [D loss: 0.688754, acc.: 53.91%] [G loss: 0.746631]
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2284 [D loss: 0.692792, acc.: 53.12%] [G loss: 0.713305]
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2285 [D loss: 0.686963, acc.: 52.34%] [G loss: 0.725669]
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2286 [D loss: 0.695111, acc.: 52.34%] [G loss: 0.721812]
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2287 [D loss: 0.692602, acc.: 53.32%] [G loss: 0.732097]
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2288 [D loss: 0.690729, acc.: 53.91%] [G loss: 0.742256]
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2289 [D loss: 0.690012, acc.: 51.37%] [G loss: 0.758142]
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2290 [D loss: 0.688598, acc.: 55.08%] [G loss: 0.758924]
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2291 [D loss: 0.690386, acc.: 55.08%] [G loss: 0.748228]
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2292 [D loss: 0.692175, acc.: 50.78%] [G loss: 0.732554]
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2293 [D loss: 0.699547, acc.: 50.20%] [G loss: 0.734609]
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2294 [D loss: 0.682230, acc.: 53.91%] [G loss: 0.731603]
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2295 [D loss: 0.684326, acc.: 51.76%] [G loss: 0.733183]
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2296 [D loss: 0.684046, acc.: 54.49%] [G loss: 0.729487]
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2297 [D loss: 0.689494, acc.: 53.52%] [G loss: 0.721337]
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2298 [D loss: 0.690301, acc.: 55.08%] [G loss: 0.732675]
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2299 [D loss: 0.698365, acc.: 47.27%] [G loss: 0.723468]
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2300 [D loss: 0.688696, acc.: 53.32%] [G loss: 0.733407]
1/1 [==============================] - 0s 27ms/step
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2301 [D loss: 0.693178, acc.: 54.30%] [G loss: 0.763539]
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2302 [D loss: 0.679988, acc.: 57.03%] [G loss: 0.782732]
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2303 [D loss: 0.693120, acc.: 53.52%] [G loss: 0.765621]
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2304 [D loss: 0.687986, acc.: 54.10%] [G loss: 0.764567]
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2305 [D loss: 0.687870, acc.: 55.47%] [G loss: 0.758232]
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2306 [D loss: 0.690313, acc.: 53.91%] [G loss: 0.742724]
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2307 [D loss: 0.691043, acc.: 53.12%] [G loss: 0.732034]
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2308 [D loss: 0.701625, acc.: 50.78%] [G loss: 0.728109]
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2309 [D loss: 0.687232, acc.: 54.49%] [G loss: 0.720356]
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2310 [D loss: 0.695199, acc.: 51.76%] [G loss: 0.701129]
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2311 [D loss: 0.699968, acc.: 48.44%] [G loss: 0.698088]
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2312 [D loss: 0.702823, acc.: 49.80%] [G loss: 0.703871]
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2313 [D loss: 0.694537, acc.: 52.34%] [G loss: 0.745642]
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2314 [D loss: 0.689710, acc.: 53.32%] [G loss: 0.760096]
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2315 [D loss: 0.688501, acc.: 53.71%] [G loss: 0.774574]
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2316 [D loss: 0.682388, acc.: 57.03%] [G loss: 0.769247]
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2317 [D loss: 0.690778, acc.: 54.49%] [G loss: 0.752392]
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2318 [D loss: 0.692942, acc.: 52.93%] [G loss: 0.740878]
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2319 [D loss: 0.690642, acc.: 53.12%] [G loss: 0.736900]
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2320 [D loss: 0.695587, acc.: 47.27%] [G loss: 0.729427]
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2321 [D loss: 0.689984, acc.: 54.88%] [G loss: 0.718502]
8/8 [==============================] - 0s 4ms/step
2322 [D loss: 0.695588, acc.: 50.20%] [G loss: 0.710100]
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2323 [D loss: 0.695075, acc.: 47.66%] [G loss: 0.691796]
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2324 [D loss: 0.693984, acc.: 48.44%] [G loss: 0.700679]
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2325 [D loss: 0.694367, acc.: 50.20%] [G loss: 0.709596]
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2326 [D loss: 0.693823, acc.: 51.17%] [G loss: 0.719482]
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2327 [D loss: 0.691968, acc.: 51.17%] [G loss: 0.755956]
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2328 [D loss: 0.687592, acc.: 54.30%] [G loss: 0.751540]
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2329 [D loss: 0.685943, acc.: 55.66%] [G loss: 0.769147]
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2330 [D loss: 0.679779, acc.: 61.33%] [G loss: 0.753715]
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2331 [D loss: 0.689252, acc.: 54.30%] [G loss: 0.745694]
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2332 [D loss: 0.687276, acc.: 53.52%] [G loss: 0.743550]
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2333 [D loss: 0.681951, acc.: 59.18%] [G loss: 0.743990]
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2334 [D loss: 0.673927, acc.: 59.96%] [G loss: 0.744726]
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2335 [D loss: 0.677957, acc.: 58.98%] [G loss: 0.743681]
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2336 [D loss: 0.684805, acc.: 52.93%] [G loss: 0.720445]
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2337 [D loss: 0.691150, acc.: 51.56%] [G loss: 0.721917]
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2338 [D loss: 0.698582, acc.: 48.05%] [G loss: 0.717554]
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2339 [D loss: 0.692061, acc.: 50.98%] [G loss: 0.735197]
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2340 [D loss: 0.692704, acc.: 51.17%] [G loss: 0.751410]
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2341 [D loss: 0.684364, acc.: 56.64%] [G loss: 0.766429]
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2342 [D loss: 0.689382, acc.: 51.37%] [G loss: 0.749848]
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2343 [D loss: 0.695391, acc.: 51.17%] [G loss: 0.730491]
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2344 [D loss: 0.691217, acc.: 51.95%] [G loss: 0.734968]
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2345 [D loss: 0.687653, acc.: 54.88%] [G loss: 0.734092]
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2346 [D loss: 0.679222, acc.: 60.74%] [G loss: 0.730234]
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2347 [D loss: 0.687337, acc.: 52.34%] [G loss: 0.737115]
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2348 [D loss: 0.680783, acc.: 55.86%] [G loss: 0.718045]
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2349 [D loss: 0.689179, acc.: 53.91%] [G loss: 0.722971]
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2350 [D loss: 0.685524, acc.: 56.05%] [G loss: 0.707427]
1/1 [==============================] - 0s 24ms/step
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2351 [D loss: 0.693160, acc.: 53.32%] [G loss: 0.719354]
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2352 [D loss: 0.691522, acc.: 51.37%] [G loss: 0.736480]
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2353 [D loss: 0.684567, acc.: 52.34%] [G loss: 0.764116]
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2354 [D loss: 0.684347, acc.: 50.98%] [G loss: 0.745731]
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2355 [D loss: 0.693866, acc.: 52.93%] [G loss: 0.750275]
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2356 [D loss: 0.698589, acc.: 47.27%] [G loss: 0.729520]
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2357 [D loss: 0.695264, acc.: 49.80%] [G loss: 0.727940]
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2358 [D loss: 0.686807, acc.: 56.05%] [G loss: 0.730099]
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2359 [D loss: 0.690397, acc.: 50.98%] [G loss: 0.728960]
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2360 [D loss: 0.693008, acc.: 49.61%] [G loss: 0.711837]
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2361 [D loss: 0.686366, acc.: 54.88%] [G loss: 0.710004]
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2362 [D loss: 0.689136, acc.: 53.71%] [G loss: 0.713507]
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2363 [D loss: 0.689427, acc.: 52.73%] [G loss: 0.723611]
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2364 [D loss: 0.689864, acc.: 52.93%] [G loss: 0.756926]
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2365 [D loss: 0.685600, acc.: 50.59%] [G loss: 0.769675]
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2366 [D loss: 0.676398, acc.: 55.08%] [G loss: 0.780831]
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2367 [D loss: 0.681797, acc.: 54.88%] [G loss: 0.769604]
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2368 [D loss: 0.699881, acc.: 50.59%] [G loss: 0.743704]
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2369 [D loss: 0.702056, acc.: 48.83%] [G loss: 0.739074]
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2370 [D loss: 0.707542, acc.: 46.68%] [G loss: 0.723312]
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2371 [D loss: 0.697629, acc.: 50.20%] [G loss: 0.721838]
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2372 [D loss: 0.686014, acc.: 56.45%] [G loss: 0.730514]
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2373 [D loss: 0.690227, acc.: 53.52%] [G loss: 0.723234]
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2374 [D loss: 0.688408, acc.: 52.15%] [G loss: 0.707916]
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2375 [D loss: 0.688776, acc.: 54.10%] [G loss: 0.702583]
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2376 [D loss: 0.696459, acc.: 50.20%] [G loss: 0.730120]
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2377 [D loss: 0.683376, acc.: 56.84%] [G loss: 0.750019]
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2378 [D loss: 0.692009, acc.: 48.63%] [G loss: 0.760342]
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2379 [D loss: 0.674881, acc.: 58.20%] [G loss: 0.768207]
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2380 [D loss: 0.683514, acc.: 55.47%] [G loss: 0.756085]
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2381 [D loss: 0.689035, acc.: 53.32%] [G loss: 0.729812]
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2382 [D loss: 0.688869, acc.: 54.30%] [G loss: 0.730372]
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2383 [D loss: 0.694275, acc.: 50.98%] [G loss: 0.729229]
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2384 [D loss: 0.692861, acc.: 53.12%] [G loss: 0.710041]
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2385 [D loss: 0.694832, acc.: 49.02%] [G loss: 0.713784]
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2386 [D loss: 0.701075, acc.: 48.83%] [G loss: 0.702385]
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2387 [D loss: 0.694098, acc.: 49.22%] [G loss: 0.705207]
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2388 [D loss: 0.694336, acc.: 49.61%] [G loss: 0.707948]
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2389 [D loss: 0.697178, acc.: 50.59%] [G loss: 0.732895]
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2390 [D loss: 0.685927, acc.: 52.15%] [G loss: 0.741955]
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2391 [D loss: 0.688101, acc.: 54.69%] [G loss: 0.767499]
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2392 [D loss: 0.691520, acc.: 54.49%] [G loss: 0.755575]
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2393 [D loss: 0.696364, acc.: 51.17%] [G loss: 0.749092]
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2394 [D loss: 0.693227, acc.: 52.34%] [G loss: 0.748700]
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2395 [D loss: 0.690602, acc.: 53.32%] [G loss: 0.735241]
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2396 [D loss: 0.689044, acc.: 50.59%] [G loss: 0.744359]
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2397 [D loss: 0.684218, acc.: 55.66%] [G loss: 0.731853]
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2398 [D loss: 0.693246, acc.: 53.32%] [G loss: 0.728535]
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2399 [D loss: 0.692263, acc.: 50.98%] [G loss: 0.724858]
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2400 [D loss: 0.687676, acc.: 53.32%] [G loss: 0.710281]
1/1 [==============================] - 0s 25ms/step
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2401 [D loss: 0.698550, acc.: 49.80%] [G loss: 0.710104]
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2402 [D loss: 0.688687, acc.: 54.10%] [G loss: 0.724502]
8/8 [==============================] - 0s 4ms/step
2403 [D loss: 0.693113, acc.: 53.32%] [G loss: 0.735489]
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2404 [D loss: 0.688918, acc.: 53.91%] [G loss: 0.742181]
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2405 [D loss: 0.691155, acc.: 51.56%] [G loss: 0.740993]
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2406 [D loss: 0.686928, acc.: 54.69%] [G loss: 0.745039]
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2407 [D loss: 0.688180, acc.: 55.86%] [G loss: 0.747784]
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2408 [D loss: 0.686310, acc.: 56.84%] [G loss: 0.745241]
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2409 [D loss: 0.681335, acc.: 55.86%] [G loss: 0.724740]
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2410 [D loss: 0.685221, acc.: 50.20%] [G loss: 0.733508]
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2411 [D loss: 0.681397, acc.: 55.47%] [G loss: 0.723346]
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2412 [D loss: 0.689791, acc.: 53.71%] [G loss: 0.714409]
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2413 [D loss: 0.690324, acc.: 50.59%] [G loss: 0.708924]
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2414 [D loss: 0.697262, acc.: 49.61%] [G loss: 0.692987]
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2415 [D loss: 0.702725, acc.: 50.78%] [G loss: 0.698840]
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2416 [D loss: 0.690454, acc.: 50.20%] [G loss: 0.714027]
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2417 [D loss: 0.689062, acc.: 54.49%] [G loss: 0.730225]
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2418 [D loss: 0.686513, acc.: 57.42%] [G loss: 0.745849]
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2419 [D loss: 0.694234, acc.: 53.32%] [G loss: 0.758205]
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2420 [D loss: 0.687074, acc.: 51.95%] [G loss: 0.770144]
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2421 [D loss: 0.692699, acc.: 51.76%] [G loss: 0.740046]
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2422 [D loss: 0.685528, acc.: 54.49%] [G loss: 0.731378]
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2423 [D loss: 0.689444, acc.: 53.32%] [G loss: 0.729776]
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2424 [D loss: 0.681056, acc.: 59.57%] [G loss: 0.733021]
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2425 [D loss: 0.682035, acc.: 58.98%] [G loss: 0.735623]
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2426 [D loss: 0.673876, acc.: 58.40%] [G loss: 0.720751]
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2427 [D loss: 0.682640, acc.: 55.86%] [G loss: 0.699246]
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2428 [D loss: 0.696838, acc.: 52.15%] [G loss: 0.707408]
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2429 [D loss: 0.696338, acc.: 51.17%] [G loss: 0.709548]
8/8 [==============================] - 0s 4ms/step
2430 [D loss: 0.694442, acc.: 53.91%] [G loss: 0.751770]
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2431 [D loss: 0.677472, acc.: 58.79%] [G loss: 0.801745]
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2432 [D loss: 0.679640, acc.: 56.25%] [G loss: 0.796493]
8/8 [==============================] - 0s 4ms/step
2433 [D loss: 0.699995, acc.: 51.17%] [G loss: 0.762335]
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2434 [D loss: 0.698929, acc.: 50.59%] [G loss: 0.738736]
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2435 [D loss: 0.699467, acc.: 49.80%] [G loss: 0.740197]
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2436 [D loss: 0.688530, acc.: 53.91%] [G loss: 0.739881]
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2437 [D loss: 0.685864, acc.: 56.84%] [G loss: 0.731533]
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2438 [D loss: 0.684530, acc.: 56.64%] [G loss: 0.734379]
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2439 [D loss: 0.688019, acc.: 51.95%] [G loss: 0.718176]
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2440 [D loss: 0.696960, acc.: 49.41%] [G loss: 0.707776]
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2441 [D loss: 0.691395, acc.: 53.12%] [G loss: 0.716196]
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2442 [D loss: 0.679622, acc.: 56.25%] [G loss: 0.725183]
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2443 [D loss: 0.687961, acc.: 56.45%] [G loss: 0.767759]
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2444 [D loss: 0.682594, acc.: 57.62%] [G loss: 0.779625]
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2445 [D loss: 0.679213, acc.: 59.38%] [G loss: 0.782205]
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2446 [D loss: 0.694129, acc.: 53.71%] [G loss: 0.757497]
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2447 [D loss: 0.695725, acc.: 51.17%] [G loss: 0.741217]
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2448 [D loss: 0.702437, acc.: 49.61%] [G loss: 0.728955]
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2449 [D loss: 0.687765, acc.: 53.12%] [G loss: 0.739900]
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2450 [D loss: 0.675836, acc.: 59.38%] [G loss: 0.732899]
1/1 [==============================] - 0s 22ms/step
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2451 [D loss: 0.683572, acc.: 53.52%] [G loss: 0.715151]
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2452 [D loss: 0.682057, acc.: 54.49%] [G loss: 0.699707]
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2453 [D loss: 0.697043, acc.: 49.80%] [G loss: 0.693756]
8/8 [==============================] - 0s 4ms/step
2454 [D loss: 0.707784, acc.: 47.07%] [G loss: 0.694126]
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2455 [D loss: 0.684071, acc.: 58.01%] [G loss: 0.746892]
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2456 [D loss: 0.677240, acc.: 60.35%] [G loss: 0.761172]
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2457 [D loss: 0.686933, acc.: 53.52%] [G loss: 0.760229]
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2458 [D loss: 0.691574, acc.: 53.52%] [G loss: 0.753938]
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2459 [D loss: 0.695880, acc.: 51.95%] [G loss: 0.740170]
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2460 [D loss: 0.699014, acc.: 50.39%] [G loss: 0.725194]
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2461 [D loss: 0.689074, acc.: 52.15%] [G loss: 0.722962]
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2462 [D loss: 0.686653, acc.: 54.69%] [G loss: 0.719958]
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2463 [D loss: 0.687687, acc.: 53.32%] [G loss: 0.722282]
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2464 [D loss: 0.693415, acc.: 49.61%] [G loss: 0.704274]
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2465 [D loss: 0.688946, acc.: 53.32%] [G loss: 0.716774]
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2466 [D loss: 0.693911, acc.: 50.00%] [G loss: 0.731458]
8/8 [==============================] - 0s 4ms/step
2467 [D loss: 0.696587, acc.: 52.34%] [G loss: 0.763215]
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2468 [D loss: 0.692451, acc.: 50.59%] [G loss: 0.778342]
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2469 [D loss: 0.690069, acc.: 53.71%] [G loss: 0.758696]
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2470 [D loss: 0.689713, acc.: 55.27%] [G loss: 0.758115]
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2471 [D loss: 0.690738, acc.: 52.93%] [G loss: 0.744084]
8/8 [==============================] - 0s 4ms/step
2472 [D loss: 0.688410, acc.: 55.86%] [G loss: 0.736298]
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2473 [D loss: 0.689022, acc.: 56.25%] [G loss: 0.752772]
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2474 [D loss: 0.683626, acc.: 58.01%] [G loss: 0.739687]
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2475 [D loss: 0.687821, acc.: 54.88%] [G loss: 0.735016]
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2476 [D loss: 0.686547, acc.: 54.88%] [G loss: 0.724287]
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2477 [D loss: 0.683899, acc.: 57.03%] [G loss: 0.723422]
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2478 [D loss: 0.691879, acc.: 54.10%] [G loss: 0.725886]
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2479 [D loss: 0.693702, acc.: 51.17%] [G loss: 0.723036]
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2480 [D loss: 0.693635, acc.: 54.10%] [G loss: 0.719713]
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2481 [D loss: 0.699288, acc.: 46.68%] [G loss: 0.737260]
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2482 [D loss: 0.689954, acc.: 52.34%] [G loss: 0.751222]
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2483 [D loss: 0.683772, acc.: 56.84%] [G loss: 0.755978]
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2484 [D loss: 0.691970, acc.: 52.34%] [G loss: 0.754323]
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2485 [D loss: 0.684010, acc.: 55.66%] [G loss: 0.745886]
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2486 [D loss: 0.688559, acc.: 55.47%] [G loss: 0.733696]
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2487 [D loss: 0.683915, acc.: 58.59%] [G loss: 0.733182]
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2488 [D loss: 0.671694, acc.: 58.98%] [G loss: 0.711040]
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2489 [D loss: 0.690505, acc.: 51.37%] [G loss: 0.709234]
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2490 [D loss: 0.690561, acc.: 52.15%] [G loss: 0.713897]
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2491 [D loss: 0.699204, acc.: 50.39%] [G loss: 0.723631]
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2492 [D loss: 0.695521, acc.: 49.41%] [G loss: 0.729234]
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2493 [D loss: 0.688206, acc.: 52.93%] [G loss: 0.745593]
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2494 [D loss: 0.675749, acc.: 58.59%] [G loss: 0.772769]
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2495 [D loss: 0.675156, acc.: 62.11%] [G loss: 0.779781]
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2496 [D loss: 0.694208, acc.: 53.52%] [G loss: 0.766347]
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2497 [D loss: 0.684720, acc.: 57.23%] [G loss: 0.748255]
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2498 [D loss: 0.677054, acc.: 59.96%] [G loss: 0.749521]
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2499 [D loss: 0.678553, acc.: 59.18%] [G loss: 0.737971]
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2500 [D loss: 0.677112, acc.: 57.81%] [G loss: 0.726255]
1/1 [==============================] - 0s 25ms/step
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2501 [D loss: 0.691411, acc.: 50.78%] [G loss: 0.720693]
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2502 [D loss: 0.699270, acc.: 48.24%] [G loss: 0.694484]
8/8 [==============================] - 0s 4ms/step
2503 [D loss: 0.697179, acc.: 48.83%] [G loss: 0.698640]
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2504 [D loss: 0.708207, acc.: 48.83%] [G loss: 0.729050]
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2505 [D loss: 0.694622, acc.: 51.17%] [G loss: 0.754279]
8/8 [==============================] - 0s 4ms/step
2506 [D loss: 0.689908, acc.: 52.73%] [G loss: 0.783145]
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2507 [D loss: 0.685592, acc.: 56.05%] [G loss: 0.771192]
8/8 [==============================] - 0s 4ms/step
2508 [D loss: 0.695214, acc.: 51.17%] [G loss: 0.758224]
8/8 [==============================] - 0s 4ms/step
2509 [D loss: 0.686612, acc.: 57.62%] [G loss: 0.745358]
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2510 [D loss: 0.677904, acc.: 59.57%] [G loss: 0.748981]
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2511 [D loss: 0.680190, acc.: 56.64%] [G loss: 0.734568]
8/8 [==============================] - 0s 4ms/step
2512 [D loss: 0.681159, acc.: 55.27%] [G loss: 0.722427]
8/8 [==============================] - 0s 4ms/step
2513 [D loss: 0.698066, acc.: 47.27%] [G loss: 0.707367]
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2514 [D loss: 0.702167, acc.: 48.83%] [G loss: 0.715120]
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2515 [D loss: 0.689027, acc.: 49.02%] [G loss: 0.728134]
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2516 [D loss: 0.693418, acc.: 53.32%] [G loss: 0.745066]
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2517 [D loss: 0.686537, acc.: 55.08%] [G loss: 0.774933]
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2518 [D loss: 0.683881, acc.: 57.42%] [G loss: 0.777632]
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2519 [D loss: 0.683989, acc.: 58.40%] [G loss: 0.772183]
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2520 [D loss: 0.686996, acc.: 55.86%] [G loss: 0.751321]
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2521 [D loss: 0.682890, acc.: 56.05%] [G loss: 0.740342]
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2522 [D loss: 0.688534, acc.: 54.49%] [G loss: 0.748053]
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2523 [D loss: 0.678420, acc.: 58.01%] [G loss: 0.729438]
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2524 [D loss: 0.682924, acc.: 57.42%] [G loss: 0.726200]
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2525 [D loss: 0.685388, acc.: 54.69%] [G loss: 0.729083]
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2526 [D loss: 0.699387, acc.: 49.22%] [G loss: 0.715350]
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2527 [D loss: 0.694762, acc.: 51.95%] [G loss: 0.725580]
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2528 [D loss: 0.697475, acc.: 49.61%] [G loss: 0.744592]
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2529 [D loss: 0.694064, acc.: 52.15%] [G loss: 0.749530]
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2530 [D loss: 0.691052, acc.: 52.93%] [G loss: 0.763806]
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2531 [D loss: 0.693209, acc.: 52.34%] [G loss: 0.764878]
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2532 [D loss: 0.689231, acc.: 54.88%] [G loss: 0.742019]
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2533 [D loss: 0.688388, acc.: 55.47%] [G loss: 0.756240]
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2534 [D loss: 0.688222, acc.: 54.49%] [G loss: 0.737662]
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2535 [D loss: 0.679851, acc.: 57.03%] [G loss: 0.737676]
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2536 [D loss: 0.684294, acc.: 54.88%] [G loss: 0.723235]
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2537 [D loss: 0.690078, acc.: 51.17%] [G loss: 0.714371]
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2538 [D loss: 0.690666, acc.: 50.98%] [G loss: 0.719361]
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2539 [D loss: 0.696444, acc.: 49.02%] [G loss: 0.738419]
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2540 [D loss: 0.687548, acc.: 50.20%] [G loss: 0.732162]
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2541 [D loss: 0.690123, acc.: 50.78%] [G loss: 0.747788]
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2542 [D loss: 0.688077, acc.: 53.91%] [G loss: 0.746000]
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2543 [D loss: 0.690461, acc.: 51.76%] [G loss: 0.743256]
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2544 [D loss: 0.695577, acc.: 50.59%] [G loss: 0.739130]
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2545 [D loss: 0.694825, acc.: 50.98%] [G loss: 0.738252]
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2546 [D loss: 0.691339, acc.: 52.73%] [G loss: 0.731758]
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2547 [D loss: 0.684970, acc.: 53.91%] [G loss: 0.731183]
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2548 [D loss: 0.691787, acc.: 50.59%] [G loss: 0.729491]
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2549 [D loss: 0.686718, acc.: 52.15%] [G loss: 0.722444]
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2550 [D loss: 0.687382, acc.: 53.52%] [G loss: 0.732305]
1/1 [==============================] - 0s 32ms/step
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2551 [D loss: 0.687906, acc.: 52.93%] [G loss: 0.736814]
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2552 [D loss: 0.688805, acc.: 50.98%] [G loss: 0.754956]
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2553 [D loss: 0.695858, acc.: 47.27%] [G loss: 0.761477]
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2554 [D loss: 0.693713, acc.: 52.54%] [G loss: 0.757179]
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2555 [D loss: 0.689758, acc.: 54.30%] [G loss: 0.751383]
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2556 [D loss: 0.689923, acc.: 51.76%] [G loss: 0.734856]
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2557 [D loss: 0.692755, acc.: 53.52%] [G loss: 0.744222]
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2558 [D loss: 0.693411, acc.: 52.15%] [G loss: 0.730682]
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2559 [D loss: 0.691610, acc.: 52.34%] [G loss: 0.721932]
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2560 [D loss: 0.691640, acc.: 51.56%] [G loss: 0.728099]
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2561 [D loss: 0.694444, acc.: 51.76%] [G loss: 0.714972]
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2562 [D loss: 0.685239, acc.: 54.49%] [G loss: 0.733011]
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2563 [D loss: 0.697980, acc.: 49.41%] [G loss: 0.732951]
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2564 [D loss: 0.685149, acc.: 53.91%] [G loss: 0.743481]
8/8 [==============================] - 0s 4ms/step
2565 [D loss: 0.687754, acc.: 54.10%] [G loss: 0.739336]
8/8 [==============================] - 0s 4ms/step
2566 [D loss: 0.684460, acc.: 58.40%] [G loss: 0.741550]
8/8 [==============================] - 0s 4ms/step
2567 [D loss: 0.700200, acc.: 49.80%] [G loss: 0.745222]
8/8 [==============================] - 0s 4ms/step
2568 [D loss: 0.688998, acc.: 55.27%] [G loss: 0.752702]
8/8 [==============================] - 0s 4ms/step
2569 [D loss: 0.683998, acc.: 55.08%] [G loss: 0.746599]
8/8 [==============================] - 0s 4ms/step
2570 [D loss: 0.697687, acc.: 50.78%] [G loss: 0.750806]
8/8 [==============================] - 0s 4ms/step
2571 [D loss: 0.689191, acc.: 54.30%] [G loss: 0.751035]
8/8 [==============================] - 0s 4ms/step
2572 [D loss: 0.691843, acc.: 50.98%] [G loss: 0.727533]
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2573 [D loss: 0.692988, acc.: 49.61%] [G loss: 0.755219]
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2574 [D loss: 0.689718, acc.: 57.62%] [G loss: 0.742682]
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2575 [D loss: 0.688379, acc.: 56.05%] [G loss: 0.764104]
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2576 [D loss: 0.683745, acc.: 54.30%] [G loss: 0.752464]
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2577 [D loss: 0.680326, acc.: 57.03%] [G loss: 0.757557]
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2578 [D loss: 0.687759, acc.: 56.64%] [G loss: 0.757759]
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2579 [D loss: 0.695930, acc.: 51.95%] [G loss: 0.742868]
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2580 [D loss: 0.680901, acc.: 57.03%] [G loss: 0.742576]
8/8 [==============================] - 0s 4ms/step
2581 [D loss: 0.703483, acc.: 49.61%] [G loss: 0.735738]
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2582 [D loss: 0.691020, acc.: 54.10%] [G loss: 0.731740]
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2583 [D loss: 0.691407, acc.: 52.93%] [G loss: 0.741198]
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2584 [D loss: 0.691298, acc.: 51.95%] [G loss: 0.741099]
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2585 [D loss: 0.688096, acc.: 57.42%] [G loss: 0.743898]
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2586 [D loss: 0.684526, acc.: 55.86%] [G loss: 0.752058]
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2587 [D loss: 0.678098, acc.: 54.49%] [G loss: 0.757540]
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2588 [D loss: 0.682359, acc.: 55.66%] [G loss: 0.762548]
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2589 [D loss: 0.680848, acc.: 55.86%] [G loss: 0.742334]
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2590 [D loss: 0.684471, acc.: 55.47%] [G loss: 0.748671]
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2591 [D loss: 0.696551, acc.: 52.34%] [G loss: 0.722641]
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2592 [D loss: 0.692638, acc.: 52.93%] [G loss: 0.719267]
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2593 [D loss: 0.694886, acc.: 51.76%] [G loss: 0.737833]
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2594 [D loss: 0.699843, acc.: 48.44%] [G loss: 0.736486]
8/8 [==============================] - 0s 4ms/step
2595 [D loss: 0.692820, acc.: 53.32%] [G loss: 0.730686]
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2596 [D loss: 0.695409, acc.: 54.88%] [G loss: 0.763747]
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2597 [D loss: 0.681831, acc.: 57.81%] [G loss: 0.751922]
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2598 [D loss: 0.674363, acc.: 60.94%] [G loss: 0.744797]
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2599 [D loss: 0.686855, acc.: 53.91%] [G loss: 0.742126]
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2600 [D loss: 0.690230, acc.: 53.12%] [G loss: 0.734514]
1/1 [==============================] - 0s 29ms/step
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2601 [D loss: 0.682282, acc.: 54.49%] [G loss: 0.736684]
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2602 [D loss: 0.693247, acc.: 51.17%] [G loss: 0.740507]
8/8 [==============================] - 0s 4ms/step
2603 [D loss: 0.698911, acc.: 48.24%] [G loss: 0.737741]
8/8 [==============================] - 0s 4ms/step
2604 [D loss: 0.693903, acc.: 52.54%] [G loss: 0.735002]
8/8 [==============================] - 0s 4ms/step
2605 [D loss: 0.691439, acc.: 51.56%] [G loss: 0.746861]
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2606 [D loss: 0.691469, acc.: 53.91%] [G loss: 0.755232]
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2607 [D loss: 0.693363, acc.: 51.95%] [G loss: 0.731786]
8/8 [==============================] - 0s 4ms/step
2608 [D loss: 0.694047, acc.: 50.39%] [G loss: 0.740484]
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2609 [D loss: 0.698788, acc.: 51.76%] [G loss: 0.745578]
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2610 [D loss: 0.687989, acc.: 52.54%] [G loss: 0.731257]
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2611 [D loss: 0.696637, acc.: 48.83%] [G loss: 0.727415]
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2612 [D loss: 0.689732, acc.: 52.15%] [G loss: 0.726303]
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2613 [D loss: 0.690185, acc.: 53.91%] [G loss: 0.733857]
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2614 [D loss: 0.697211, acc.: 50.00%] [G loss: 0.757915]
8/8 [==============================] - 0s 4ms/step
2615 [D loss: 0.679912, acc.: 58.01%] [G loss: 0.763250]
8/8 [==============================] - 0s 4ms/step
2616 [D loss: 0.682878, acc.: 53.12%] [G loss: 0.790491]
8/8 [==============================] - 0s 4ms/step
2617 [D loss: 0.673159, acc.: 59.57%] [G loss: 0.799179]
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2618 [D loss: 0.683596, acc.: 55.86%] [G loss: 0.783131]
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2619 [D loss: 0.686289, acc.: 56.05%] [G loss: 0.746957]
8/8 [==============================] - 0s 4ms/step
2620 [D loss: 0.689856, acc.: 52.15%] [G loss: 0.739483]
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2621 [D loss: 0.689209, acc.: 56.45%] [G loss: 0.743483]
8/8 [==============================] - 0s 4ms/step
2622 [D loss: 0.682633, acc.: 53.52%] [G loss: 0.734115]
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2623 [D loss: 0.692510, acc.: 56.05%] [G loss: 0.733660]
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2624 [D loss: 0.688748, acc.: 53.12%] [G loss: 0.744715]
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2625 [D loss: 0.676475, acc.: 58.01%] [G loss: 0.733986]
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2626 [D loss: 0.690575, acc.: 52.54%] [G loss: 0.740904]
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2627 [D loss: 0.684578, acc.: 54.88%] [G loss: 0.741462]
8/8 [==============================] - 0s 4ms/step
2628 [D loss: 0.672106, acc.: 58.98%] [G loss: 0.748124]
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2629 [D loss: 0.698398, acc.: 49.22%] [G loss: 0.759201]
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2630 [D loss: 0.679547, acc.: 57.62%] [G loss: 0.758452]
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2631 [D loss: 0.693342, acc.: 52.34%] [G loss: 0.749289]
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2632 [D loss: 0.691603, acc.: 52.15%] [G loss: 0.736300]
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2633 [D loss: 0.688848, acc.: 53.32%] [G loss: 0.735465]
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2634 [D loss: 0.704797, acc.: 47.46%] [G loss: 0.735870]
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2635 [D loss: 0.692200, acc.: 51.76%] [G loss: 0.736049]
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2636 [D loss: 0.684775, acc.: 54.88%] [G loss: 0.739485]
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2637 [D loss: 0.683594, acc.: 56.05%] [G loss: 0.726133]
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2638 [D loss: 0.684975, acc.: 57.62%] [G loss: 0.732191]
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2639 [D loss: 0.679282, acc.: 58.01%] [G loss: 0.733586]
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2640 [D loss: 0.701550, acc.: 51.95%] [G loss: 0.735013]
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2641 [D loss: 0.685041, acc.: 56.25%] [G loss: 0.735680]
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2642 [D loss: 0.690322, acc.: 54.10%] [G loss: 0.753345]
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2643 [D loss: 0.693142, acc.: 54.30%] [G loss: 0.763856]
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2644 [D loss: 0.692972, acc.: 51.17%] [G loss: 0.774053]
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2645 [D loss: 0.688934, acc.: 54.49%] [G loss: 0.753435]
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2646 [D loss: 0.693031, acc.: 54.88%] [G loss: 0.753263]
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2647 [D loss: 0.694281, acc.: 51.56%] [G loss: 0.736186]
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2648 [D loss: 0.691711, acc.: 53.52%] [G loss: 0.739510]
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2649 [D loss: 0.696491, acc.: 49.80%] [G loss: 0.725071]
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2650 [D loss: 0.685339, acc.: 54.30%] [G loss: 0.733095]
1/1 [==============================] - 0s 30ms/step
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2651 [D loss: 0.693554, acc.: 50.59%] [G loss: 0.732905]
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2652 [D loss: 0.697586, acc.: 50.20%] [G loss: 0.722785]
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2653 [D loss: 0.690201, acc.: 52.34%] [G loss: 0.732263]
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2654 [D loss: 0.690023, acc.: 53.91%] [G loss: 0.742313]
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2655 [D loss: 0.689439, acc.: 55.86%] [G loss: 0.786998]
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2656 [D loss: 0.682009, acc.: 57.81%] [G loss: 0.787707]
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2657 [D loss: 0.687330, acc.: 53.91%] [G loss: 0.776394]
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2658 [D loss: 0.688514, acc.: 52.93%] [G loss: 0.783062]
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2659 [D loss: 0.685190, acc.: 55.86%] [G loss: 0.751185]
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2660 [D loss: 0.679665, acc.: 56.84%] [G loss: 0.746563]
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2661 [D loss: 0.681246, acc.: 58.20%] [G loss: 0.739727]
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2662 [D loss: 0.670821, acc.: 59.57%] [G loss: 0.722455]
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2663 [D loss: 0.691002, acc.: 54.88%] [G loss: 0.692694]
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2664 [D loss: 0.706381, acc.: 47.85%] [G loss: 0.700663]
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2665 [D loss: 0.704812, acc.: 50.39%] [G loss: 0.709817]
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2666 [D loss: 0.700467, acc.: 51.37%] [G loss: 0.737280]
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2667 [D loss: 0.683588, acc.: 56.64%] [G loss: 0.809488]
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2668 [D loss: 0.692514, acc.: 54.30%] [G loss: 0.810787]
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2669 [D loss: 0.698929, acc.: 51.56%] [G loss: 0.780483]
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2670 [D loss: 0.691624, acc.: 55.86%] [G loss: 0.754043]
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2671 [D loss: 0.673756, acc.: 62.70%] [G loss: 0.768312]
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2672 [D loss: 0.660979, acc.: 67.38%] [G loss: 0.796151]
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2673 [D loss: 0.661039, acc.: 65.82%] [G loss: 0.778870]
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2674 [D loss: 0.690552, acc.: 52.15%] [G loss: 0.720132]
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2675 [D loss: 0.699508, acc.: 51.37%] [G loss: 0.674917]
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2676 [D loss: 0.716129, acc.: 46.09%] [G loss: 0.684397]
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2677 [D loss: 0.710540, acc.: 49.61%] [G loss: 0.745699]
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2678 [D loss: 0.687162, acc.: 56.45%] [G loss: 0.808366]
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2679 [D loss: 0.679557, acc.: 60.16%] [G loss: 0.829032]
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2680 [D loss: 0.701064, acc.: 49.02%] [G loss: 0.776104]
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2681 [D loss: 0.706682, acc.: 49.80%] [G loss: 0.743264]
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2682 [D loss: 0.693367, acc.: 57.23%] [G loss: 0.749263]
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2683 [D loss: 0.683366, acc.: 57.62%] [G loss: 0.759906]
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2684 [D loss: 0.679304, acc.: 61.13%] [G loss: 0.749192]
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2685 [D loss: 0.675835, acc.: 60.35%] [G loss: 0.733155]
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2686 [D loss: 0.698744, acc.: 50.20%] [G loss: 0.696595]
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2687 [D loss: 0.694565, acc.: 50.39%] [G loss: 0.698015]
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2688 [D loss: 0.690413, acc.: 49.61%] [G loss: 0.748288]
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2689 [D loss: 0.679454, acc.: 57.42%] [G loss: 0.795778]
8/8 [==============================] - 0s 4ms/step
2690 [D loss: 0.680990, acc.: 56.45%] [G loss: 0.777303]
8/8 [==============================] - 0s 4ms/step
2691 [D loss: 0.687802, acc.: 54.30%] [G loss: 0.761272]
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2692 [D loss: 0.698573, acc.: 51.95%] [G loss: 0.743951]
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2693 [D loss: 0.691856, acc.: 53.91%] [G loss: 0.747821]
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2694 [D loss: 0.683056, acc.: 56.45%] [G loss: 0.748203]
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2695 [D loss: 0.677746, acc.: 59.38%] [G loss: 0.740643]
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2696 [D loss: 0.691797, acc.: 51.56%] [G loss: 0.723879]
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2697 [D loss: 0.693501, acc.: 52.54%] [G loss: 0.709072]
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2698 [D loss: 0.696958, acc.: 51.95%] [G loss: 0.712562]
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2699 [D loss: 0.692901, acc.: 51.56%] [G loss: 0.737648]
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2700 [D loss: 0.685025, acc.: 54.88%] [G loss: 0.750089]
1/1 [==============================] - 0s 29ms/step
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2701 [D loss: 0.698528, acc.: 50.20%] [G loss: 0.758019]
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2702 [D loss: 0.683144, acc.: 55.86%] [G loss: 0.757749]
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2703 [D loss: 0.692294, acc.: 51.56%] [G loss: 0.743258]
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2704 [D loss: 0.704266, acc.: 45.90%] [G loss: 0.731768]
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2705 [D loss: 0.693053, acc.: 48.44%] [G loss: 0.728718]
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2706 [D loss: 0.685062, acc.: 53.71%] [G loss: 0.734274]
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2707 [D loss: 0.683008, acc.: 55.08%] [G loss: 0.736922]
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2708 [D loss: 0.690991, acc.: 52.73%] [G loss: 0.728117]
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2709 [D loss: 0.690722, acc.: 51.76%] [G loss: 0.736902]
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2710 [D loss: 0.688503, acc.: 54.10%] [G loss: 0.741677]
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2711 [D loss: 0.686743, acc.: 55.08%] [G loss: 0.754119]
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2712 [D loss: 0.686159, acc.: 56.45%] [G loss: 0.763431]
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2713 [D loss: 0.692800, acc.: 53.52%] [G loss: 0.750232]
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2714 [D loss: 0.681789, acc.: 57.42%] [G loss: 0.747031]
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2715 [D loss: 0.682716, acc.: 56.45%] [G loss: 0.746033]
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2716 [D loss: 0.693015, acc.: 54.10%] [G loss: 0.745763]
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2717 [D loss: 0.687803, acc.: 52.54%] [G loss: 0.753708]
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2718 [D loss: 0.685686, acc.: 53.12%] [G loss: 0.747041]
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2719 [D loss: 0.684049, acc.: 57.03%] [G loss: 0.749591]
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2720 [D loss: 0.686333, acc.: 55.47%] [G loss: 0.750129]
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2721 [D loss: 0.686006, acc.: 51.95%] [G loss: 0.739208]
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2722 [D loss: 0.690115, acc.: 53.71%] [G loss: 0.744831]
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2723 [D loss: 0.692344, acc.: 54.10%] [G loss: 0.742360]
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2724 [D loss: 0.692140, acc.: 52.73%] [G loss: 0.751669]
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2725 [D loss: 0.695253, acc.: 53.71%] [G loss: 0.753960]
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2726 [D loss: 0.696852, acc.: 50.39%] [G loss: 0.757983]
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2727 [D loss: 0.686746, acc.: 54.69%] [G loss: 0.764885]
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2728 [D loss: 0.687345, acc.: 57.03%] [G loss: 0.760514]
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2729 [D loss: 0.682485, acc.: 57.23%] [G loss: 0.750274]
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2730 [D loss: 0.678422, acc.: 57.62%] [G loss: 0.744826]
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2731 [D loss: 0.678480, acc.: 57.62%] [G loss: 0.734811]
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2732 [D loss: 0.684984, acc.: 54.30%] [G loss: 0.715185]
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2733 [D loss: 0.686629, acc.: 53.52%] [G loss: 0.706940]
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2734 [D loss: 0.701464, acc.: 49.22%] [G loss: 0.709319]
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2735 [D loss: 0.697562, acc.: 50.00%] [G loss: 0.723870]
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2736 [D loss: 0.691668, acc.: 52.93%] [G loss: 0.742193]
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2737 [D loss: 0.684416, acc.: 58.01%] [G loss: 0.763590]
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2738 [D loss: 0.682663, acc.: 54.69%] [G loss: 0.773661]
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2739 [D loss: 0.685965, acc.: 55.08%] [G loss: 0.769206]
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2740 [D loss: 0.686104, acc.: 52.34%] [G loss: 0.770923]
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2741 [D loss: 0.682220, acc.: 55.66%] [G loss: 0.762944]
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2742 [D loss: 0.677361, acc.: 58.59%] [G loss: 0.766480]
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2743 [D loss: 0.674956, acc.: 57.81%] [G loss: 0.761116]
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2744 [D loss: 0.690521, acc.: 52.34%] [G loss: 0.739439]
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2745 [D loss: 0.700056, acc.: 48.63%] [G loss: 0.719887]
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2746 [D loss: 0.703978, acc.: 48.83%] [G loss: 0.714337]
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2747 [D loss: 0.713710, acc.: 45.31%] [G loss: 0.736574]
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2748 [D loss: 0.696322, acc.: 50.39%] [G loss: 0.752195]
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2749 [D loss: 0.692578, acc.: 53.52%] [G loss: 0.763666]
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2750 [D loss: 0.678368, acc.: 58.40%] [G loss: 0.756369]
1/1 [==============================] - 0s 26ms/step
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2751 [D loss: 0.680673, acc.: 58.01%] [G loss: 0.761343]
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2752 [D loss: 0.677223, acc.: 58.79%] [G loss: 0.755562]
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2753 [D loss: 0.680941, acc.: 56.05%] [G loss: 0.751151]
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2754 [D loss: 0.686447, acc.: 54.88%] [G loss: 0.739996]
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2755 [D loss: 0.684492, acc.: 53.71%] [G loss: 0.722361]
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2756 [D loss: 0.692076, acc.: 54.10%] [G loss: 0.716808]
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2757 [D loss: 0.687621, acc.: 54.30%] [G loss: 0.698774]
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2758 [D loss: 0.704255, acc.: 50.20%] [G loss: 0.717826]
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2759 [D loss: 0.709440, acc.: 44.34%] [G loss: 0.716490]
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2760 [D loss: 0.701243, acc.: 47.66%] [G loss: 0.730552]
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2761 [D loss: 0.696095, acc.: 49.61%] [G loss: 0.748447]
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2762 [D loss: 0.694259, acc.: 51.56%] [G loss: 0.747170]
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2763 [D loss: 0.687184, acc.: 52.34%] [G loss: 0.759487]
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2764 [D loss: 0.697038, acc.: 50.20%] [G loss: 0.758197]
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2765 [D loss: 0.680580, acc.: 56.05%] [G loss: 0.769583]
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2766 [D loss: 0.694061, acc.: 50.98%] [G loss: 0.763221]
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2767 [D loss: 0.682072, acc.: 54.30%] [G loss: 0.757510]
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2768 [D loss: 0.693804, acc.: 52.93%] [G loss: 0.760689]
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2769 [D loss: 0.688860, acc.: 53.91%] [G loss: 0.732963]
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2770 [D loss: 0.692282, acc.: 50.39%] [G loss: 0.731841]
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2771 [D loss: 0.694889, acc.: 50.98%] [G loss: 0.727534]
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2772 [D loss: 0.695234, acc.: 51.76%] [G loss: 0.736640]
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2773 [D loss: 0.704753, acc.: 47.07%] [G loss: 0.738383]
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2774 [D loss: 0.684668, acc.: 56.05%] [G loss: 0.753668]
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2775 [D loss: 0.689246, acc.: 51.76%] [G loss: 0.770985]
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2776 [D loss: 0.696252, acc.: 49.02%] [G loss: 0.750792]
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2777 [D loss: 0.695083, acc.: 52.73%] [G loss: 0.747428]
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2778 [D loss: 0.683731, acc.: 55.86%] [G loss: 0.740406]
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2779 [D loss: 0.695313, acc.: 48.05%] [G loss: 0.732067]
8/8 [==============================] - 0s 4ms/step
2780 [D loss: 0.692487, acc.: 50.59%] [G loss: 0.714721]
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2781 [D loss: 0.694366, acc.: 54.88%] [G loss: 0.700883]
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2782 [D loss: 0.700033, acc.: 50.39%] [G loss: 0.709033]
8/8 [==============================] - 0s 4ms/step
2783 [D loss: 0.697346, acc.: 50.20%] [G loss: 0.724165]
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2784 [D loss: 0.699007, acc.: 47.85%] [G loss: 0.715321]
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2785 [D loss: 0.687922, acc.: 55.66%] [G loss: 0.748051]
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2786 [D loss: 0.684661, acc.: 56.45%] [G loss: 0.765247]
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2787 [D loss: 0.687336, acc.: 53.71%] [G loss: 0.759779]
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2788 [D loss: 0.686316, acc.: 53.71%] [G loss: 0.757861]
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2789 [D loss: 0.688607, acc.: 54.10%] [G loss: 0.748390]
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2790 [D loss: 0.682709, acc.: 56.64%] [G loss: 0.742289]
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2791 [D loss: 0.686167, acc.: 54.69%] [G loss: 0.737009]
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2792 [D loss: 0.683333, acc.: 57.03%] [G loss: 0.727351]
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2793 [D loss: 0.680843, acc.: 58.98%] [G loss: 0.724192]
8/8 [==============================] - 0s 4ms/step
2794 [D loss: 0.692511, acc.: 50.20%] [G loss: 0.721160]
8/8 [==============================] - 0s 4ms/step
2795 [D loss: 0.692243, acc.: 50.39%] [G loss: 0.707919]
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2796 [D loss: 0.699285, acc.: 47.46%] [G loss: 0.720350]
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2797 [D loss: 0.690802, acc.: 52.93%] [G loss: 0.750130]
8/8 [==============================] - 0s 4ms/step
2798 [D loss: 0.687165, acc.: 57.42%] [G loss: 0.759312]
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2799 [D loss: 0.686528, acc.: 54.69%] [G loss: 0.758957]
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2800 [D loss: 0.696661, acc.: 50.39%] [G loss: 0.754540]
1/1 [==============================] - 0s 25ms/step
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2801 [D loss: 0.686958, acc.: 55.27%] [G loss: 0.751005]
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2802 [D loss: 0.689379, acc.: 54.69%] [G loss: 0.754649]
8/8 [==============================] - 0s 4ms/step
2803 [D loss: 0.691439, acc.: 50.00%] [G loss: 0.739829]
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2804 [D loss: 0.691831, acc.: 53.12%] [G loss: 0.732567]
8/8 [==============================] - 0s 4ms/step
2805 [D loss: 0.695304, acc.: 50.39%] [G loss: 0.728711]
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2806 [D loss: 0.704287, acc.: 49.41%] [G loss: 0.731652]
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2807 [D loss: 0.699717, acc.: 49.41%] [G loss: 0.719614]
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2808 [D loss: 0.689092, acc.: 55.27%] [G loss: 0.742754]
8/8 [==============================] - 0s 4ms/step
2809 [D loss: 0.692557, acc.: 53.52%] [G loss: 0.763530]
8/8 [==============================] - 0s 4ms/step
2810 [D loss: 0.675959, acc.: 59.77%] [G loss: 0.776112]
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2811 [D loss: 0.677276, acc.: 58.40%] [G loss: 0.760498]
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2812 [D loss: 0.690353, acc.: 51.37%] [G loss: 0.751797]
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2813 [D loss: 0.688337, acc.: 55.66%] [G loss: 0.744740]
8/8 [==============================] - 0s 4ms/step
2814 [D loss: 0.693028, acc.: 52.54%] [G loss: 0.734382]
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2815 [D loss: 0.698158, acc.: 52.34%] [G loss: 0.732155]
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2816 [D loss: 0.688920, acc.: 54.49%] [G loss: 0.726553]
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2817 [D loss: 0.691694, acc.: 52.15%] [G loss: 0.730843]
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2818 [D loss: 0.694062, acc.: 48.44%] [G loss: 0.734487]
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2819 [D loss: 0.690544, acc.: 53.32%] [G loss: 0.755285]
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2820 [D loss: 0.682312, acc.: 56.84%] [G loss: 0.766874]
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2821 [D loss: 0.691769, acc.: 50.00%] [G loss: 0.773254]
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2822 [D loss: 0.693238, acc.: 53.71%] [G loss: 0.762700]
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2823 [D loss: 0.689186, acc.: 56.05%] [G loss: 0.757544]
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2824 [D loss: 0.692815, acc.: 52.73%] [G loss: 0.762953]
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2825 [D loss: 0.677099, acc.: 59.57%] [G loss: 0.749878]
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2826 [D loss: 0.688299, acc.: 55.47%] [G loss: 0.735856]
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2827 [D loss: 0.679191, acc.: 58.79%] [G loss: 0.742992]
8/8 [==============================] - 0s 4ms/step
2828 [D loss: 0.697072, acc.: 47.27%] [G loss: 0.725784]
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2829 [D loss: 0.700309, acc.: 48.44%] [G loss: 0.720130]
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2830 [D loss: 0.698566, acc.: 47.85%] [G loss: 0.753024]
8/8 [==============================] - 0s 4ms/step
2831 [D loss: 0.704647, acc.: 48.44%] [G loss: 0.753664]
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2832 [D loss: 0.689161, acc.: 51.17%] [G loss: 0.771973]
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2833 [D loss: 0.691887, acc.: 52.54%] [G loss: 0.761371]
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2834 [D loss: 0.693898, acc.: 52.54%] [G loss: 0.746703]
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2835 [D loss: 0.691879, acc.: 51.17%] [G loss: 0.763669]
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2836 [D loss: 0.682159, acc.: 59.77%] [G loss: 0.762053]
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2837 [D loss: 0.679383, acc.: 58.79%] [G loss: 0.758800]
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2838 [D loss: 0.682235, acc.: 57.23%] [G loss: 0.739073]
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2839 [D loss: 0.675330, acc.: 56.84%] [G loss: 0.740185]
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2840 [D loss: 0.686996, acc.: 54.10%] [G loss: 0.722003]
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2841 [D loss: 0.697095, acc.: 55.47%] [G loss: 0.722610]
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2842 [D loss: 0.696835, acc.: 48.63%] [G loss: 0.741385]
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2843 [D loss: 0.684821, acc.: 55.66%] [G loss: 0.761105]
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2844 [D loss: 0.689080, acc.: 55.66%] [G loss: 0.773139]
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2845 [D loss: 0.690686, acc.: 50.98%] [G loss: 0.774539]
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2846 [D loss: 0.702562, acc.: 48.44%] [G loss: 0.765329]
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2847 [D loss: 0.694195, acc.: 52.34%] [G loss: 0.748539]
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2848 [D loss: 0.690272, acc.: 51.56%] [G loss: 0.751432]
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2849 [D loss: 0.685061, acc.: 55.08%] [G loss: 0.756051]
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2850 [D loss: 0.680458, acc.: 57.23%] [G loss: 0.748708]
1/1 [==============================] - 0s 31ms/step
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2851 [D loss: 0.675351, acc.: 60.55%] [G loss: 0.734097]
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2852 [D loss: 0.688086, acc.: 55.27%] [G loss: 0.744721]
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2853 [D loss: 0.675798, acc.: 59.57%] [G loss: 0.746089]
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2854 [D loss: 0.688662, acc.: 56.45%] [G loss: 0.757185]
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2855 [D loss: 0.684279, acc.: 59.18%] [G loss: 0.762129]
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2856 [D loss: 0.684429, acc.: 58.01%] [G loss: 0.754968]
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2857 [D loss: 0.695369, acc.: 51.37%] [G loss: 0.748656]
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2858 [D loss: 0.696161, acc.: 50.00%] [G loss: 0.740801]
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2859 [D loss: 0.699706, acc.: 51.17%] [G loss: 0.743304]
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2860 [D loss: 0.704563, acc.: 46.88%] [G loss: 0.720119]
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2861 [D loss: 0.703202, acc.: 48.83%] [G loss: 0.699068]
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2862 [D loss: 0.695503, acc.: 50.00%] [G loss: 0.722590]
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2863 [D loss: 0.703543, acc.: 47.07%] [G loss: 0.709162]
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2864 [D loss: 0.699223, acc.: 50.00%] [G loss: 0.736661]
8/8 [==============================] - 0s 4ms/step
2865 [D loss: 0.694266, acc.: 53.12%] [G loss: 0.759084]
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2866 [D loss: 0.684071, acc.: 54.88%] [G loss: 0.760162]
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2867 [D loss: 0.684628, acc.: 55.47%] [G loss: 0.766150]
8/8 [==============================] - 0s 4ms/step
2868 [D loss: 0.689112, acc.: 50.59%] [G loss: 0.750520]
8/8 [==============================] - 0s 4ms/step
2869 [D loss: 0.690501, acc.: 52.54%] [G loss: 0.738807]
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2870 [D loss: 0.682418, acc.: 54.49%] [G loss: 0.744074]
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2871 [D loss: 0.687181, acc.: 56.25%] [G loss: 0.733631]
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2872 [D loss: 0.690735, acc.: 50.39%] [G loss: 0.724258]
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2873 [D loss: 0.692735, acc.: 50.98%] [G loss: 0.741322]
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2874 [D loss: 0.687561, acc.: 55.66%] [G loss: 0.743558]
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2875 [D loss: 0.684975, acc.: 55.66%] [G loss: 0.751711]
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2876 [D loss: 0.690368, acc.: 56.25%] [G loss: 0.753156]
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2877 [D loss: 0.687641, acc.: 53.12%] [G loss: 0.740778]
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2878 [D loss: 0.695289, acc.: 52.34%] [G loss: 0.745300]
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2879 [D loss: 0.687788, acc.: 54.10%] [G loss: 0.741770]
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2880 [D loss: 0.683649, acc.: 55.86%] [G loss: 0.729632]
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2881 [D loss: 0.696960, acc.: 53.52%] [G loss: 0.751715]
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2882 [D loss: 0.683971, acc.: 56.05%] [G loss: 0.742038]
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2883 [D loss: 0.694459, acc.: 50.78%] [G loss: 0.735275]
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2884 [D loss: 0.686082, acc.: 56.05%] [G loss: 0.726226]
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2885 [D loss: 0.687627, acc.: 56.05%] [G loss: 0.736148]
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2886 [D loss: 0.701192, acc.: 46.88%] [G loss: 0.742654]
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2887 [D loss: 0.690063, acc.: 53.32%] [G loss: 0.754580]
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2888 [D loss: 0.695942, acc.: 54.88%] [G loss: 0.759229]
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2889 [D loss: 0.703300, acc.: 49.02%] [G loss: 0.766876]
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2890 [D loss: 0.701080, acc.: 47.85%] [G loss: 0.742949]
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2891 [D loss: 0.692835, acc.: 52.15%] [G loss: 0.744060]
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2892 [D loss: 0.682662, acc.: 57.03%] [G loss: 0.744441]
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2893 [D loss: 0.687182, acc.: 52.15%] [G loss: 0.741888]
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2894 [D loss: 0.680486, acc.: 54.88%] [G loss: 0.750191]
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2895 [D loss: 0.688104, acc.: 52.93%] [G loss: 0.730966]
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2896 [D loss: 0.691574, acc.: 50.00%] [G loss: 0.737566]
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2897 [D loss: 0.683634, acc.: 55.86%] [G loss: 0.741232]
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2898 [D loss: 0.682916, acc.: 55.27%] [G loss: 0.759074]
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2899 [D loss: 0.687661, acc.: 51.76%] [G loss: 0.734629]
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2900 [D loss: 0.689166, acc.: 53.32%] [G loss: 0.747362]
1/1 [==============================] - 0s 28ms/step
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2901 [D loss: 0.695124, acc.: 51.56%] [G loss: 0.735508]
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2902 [D loss: 0.699796, acc.: 49.41%] [G loss: 0.721128]
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2903 [D loss: 0.694338, acc.: 52.34%] [G loss: 0.709603]
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2904 [D loss: 0.687503, acc.: 53.12%] [G loss: 0.725417]
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2905 [D loss: 0.701233, acc.: 48.24%] [G loss: 0.706070]
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2906 [D loss: 0.691153, acc.: 51.56%] [G loss: 0.726603]
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2907 [D loss: 0.689150, acc.: 52.54%] [G loss: 0.742491]
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2908 [D loss: 0.695667, acc.: 50.78%] [G loss: 0.734333]
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2909 [D loss: 0.689695, acc.: 52.34%] [G loss: 0.754618]
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2910 [D loss: 0.686162, acc.: 55.86%] [G loss: 0.750279]
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2911 [D loss: 0.689076, acc.: 54.88%] [G loss: 0.751434]
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2912 [D loss: 0.692508, acc.: 52.54%] [G loss: 0.760221]
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2913 [D loss: 0.694323, acc.: 51.56%] [G loss: 0.747110]
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2914 [D loss: 0.687278, acc.: 52.54%] [G loss: 0.757900]
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2915 [D loss: 0.692392, acc.: 54.30%] [G loss: 0.739193]
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2916 [D loss: 0.685456, acc.: 53.71%] [G loss: 0.752288]
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2917 [D loss: 0.698377, acc.: 47.85%] [G loss: 0.740666]
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2918 [D loss: 0.690360, acc.: 51.56%] [G loss: 0.739808]
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2919 [D loss: 0.688486, acc.: 52.93%] [G loss: 0.741305]
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2920 [D loss: 0.693013, acc.: 50.98%] [G loss: 0.746367]
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2921 [D loss: 0.700803, acc.: 49.61%] [G loss: 0.737264]
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2922 [D loss: 0.694914, acc.: 54.69%] [G loss: 0.733827]
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2923 [D loss: 0.697110, acc.: 51.95%] [G loss: 0.733130]
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2924 [D loss: 0.697453, acc.: 49.80%] [G loss: 0.725036]
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2925 [D loss: 0.685191, acc.: 56.64%] [G loss: 0.725785]
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2926 [D loss: 0.695329, acc.: 51.95%] [G loss: 0.720797]
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2927 [D loss: 0.681651, acc.: 56.25%] [G loss: 0.727367]
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2928 [D loss: 0.685052, acc.: 56.84%] [G loss: 0.722447]
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2929 [D loss: 0.688758, acc.: 56.05%] [G loss: 0.719786]
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2930 [D loss: 0.678668, acc.: 60.16%] [G loss: 0.732998]
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2931 [D loss: 0.690041, acc.: 53.12%] [G loss: 0.733182]
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2932 [D loss: 0.691130, acc.: 52.54%] [G loss: 0.740149]
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2933 [D loss: 0.688679, acc.: 55.27%] [G loss: 0.757049]
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2934 [D loss: 0.691284, acc.: 55.47%] [G loss: 0.745109]
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2935 [D loss: 0.690063, acc.: 52.54%] [G loss: 0.749342]
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2936 [D loss: 0.689487, acc.: 56.25%] [G loss: 0.744315]
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2937 [D loss: 0.697620, acc.: 53.12%] [G loss: 0.739810]
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2938 [D loss: 0.690091, acc.: 52.34%] [G loss: 0.736977]
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2939 [D loss: 0.685977, acc.: 54.69%] [G loss: 0.739356]
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2940 [D loss: 0.690508, acc.: 54.49%] [G loss: 0.729486]
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2941 [D loss: 0.692864, acc.: 55.47%] [G loss: 0.722205]
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2942 [D loss: 0.694559, acc.: 50.39%] [G loss: 0.723477]
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2943 [D loss: 0.690992, acc.: 54.30%] [G loss: 0.744857]
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2944 [D loss: 0.687525, acc.: 54.69%] [G loss: 0.741468]
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2945 [D loss: 0.687847, acc.: 53.32%] [G loss: 0.740203]
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2946 [D loss: 0.682030, acc.: 58.59%] [G loss: 0.759251]
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2947 [D loss: 0.687931, acc.: 55.66%] [G loss: 0.764330]
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2948 [D loss: 0.681993, acc.: 56.25%] [G loss: 0.740339]
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2949 [D loss: 0.693510, acc.: 51.95%] [G loss: 0.733203]
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2950 [D loss: 0.699432, acc.: 51.37%] [G loss: 0.724612]
1/1 [==============================] - 0s 24ms/step
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2951 [D loss: 0.699845, acc.: 53.71%] [G loss: 0.718788]
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2952 [D loss: 0.699036, acc.: 51.37%] [G loss: 0.733445]
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2953 [D loss: 0.692510, acc.: 55.86%] [G loss: 0.715798]
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2954 [D loss: 0.682779, acc.: 55.66%] [G loss: 0.716521]
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2955 [D loss: 0.689835, acc.: 49.80%] [G loss: 0.729203]
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2956 [D loss: 0.692402, acc.: 53.32%] [G loss: 0.725419]
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2957 [D loss: 0.693409, acc.: 50.00%] [G loss: 0.731421]
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2958 [D loss: 0.681015, acc.: 57.62%] [G loss: 0.748312]
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2959 [D loss: 0.694998, acc.: 50.78%] [G loss: 0.761216]
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2960 [D loss: 0.693840, acc.: 52.93%] [G loss: 0.766465]
8/8 [==============================] - 0s 4ms/step
2961 [D loss: 0.703001, acc.: 48.44%] [G loss: 0.755509]
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2962 [D loss: 0.702137, acc.: 48.44%] [G loss: 0.740479]
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2963 [D loss: 0.691392, acc.: 54.10%] [G loss: 0.735217]
8/8 [==============================] - 0s 4ms/step
2964 [D loss: 0.685311, acc.: 56.25%] [G loss: 0.734279]
8/8 [==============================] - 0s 4ms/step
2965 [D loss: 0.687269, acc.: 56.05%] [G loss: 0.730539]
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2966 [D loss: 0.699718, acc.: 50.39%] [G loss: 0.720973]
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2967 [D loss: 0.692558, acc.: 50.00%] [G loss: 0.734576]
8/8 [==============================] - 0s 4ms/step
2968 [D loss: 0.686196, acc.: 55.86%] [G loss: 0.722646]
8/8 [==============================] - 0s 4ms/step
2969 [D loss: 0.695013, acc.: 49.61%] [G loss: 0.740903]
8/8 [==============================] - 0s 4ms/step
2970 [D loss: 0.679248, acc.: 61.91%] [G loss: 0.776994]
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2971 [D loss: 0.676178, acc.: 61.33%] [G loss: 0.779153]
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2972 [D loss: 0.695599, acc.: 54.10%] [G loss: 0.771886]
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2973 [D loss: 0.686499, acc.: 53.32%] [G loss: 0.764015]
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2974 [D loss: 0.692365, acc.: 52.54%] [G loss: 0.745584]
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2975 [D loss: 0.690477, acc.: 52.73%] [G loss: 0.735992]
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2976 [D loss: 0.683415, acc.: 54.88%] [G loss: 0.730031]
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2977 [D loss: 0.687872, acc.: 54.88%] [G loss: 0.706348]
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2978 [D loss: 0.683775, acc.: 54.69%] [G loss: 0.704391]
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2979 [D loss: 0.716519, acc.: 46.29%] [G loss: 0.705527]
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2980 [D loss: 0.708705, acc.: 44.73%] [G loss: 0.698040]
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2981 [D loss: 0.705292, acc.: 45.31%] [G loss: 0.706293]
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2982 [D loss: 0.702570, acc.: 44.34%] [G loss: 0.750969]
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2983 [D loss: 0.690299, acc.: 52.34%] [G loss: 0.771124]
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2984 [D loss: 0.691106, acc.: 52.54%] [G loss: 0.768748]
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2985 [D loss: 0.689453, acc.: 51.56%] [G loss: 0.765844]
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2986 [D loss: 0.687888, acc.: 54.30%] [G loss: 0.758223]
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2987 [D loss: 0.688112, acc.: 57.62%] [G loss: 0.752010]
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2988 [D loss: 0.688093, acc.: 54.49%] [G loss: 0.733653]
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2989 [D loss: 0.679476, acc.: 58.40%] [G loss: 0.737131]
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2990 [D loss: 0.683919, acc.: 55.08%] [G loss: 0.726275]
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2991 [D loss: 0.682373, acc.: 55.27%] [G loss: 0.719469]
8/8 [==============================] - 0s 4ms/step
2992 [D loss: 0.693683, acc.: 52.34%] [G loss: 0.702974]
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2993 [D loss: 0.690765, acc.: 53.52%] [G loss: 0.703957]
8/8 [==============================] - 0s 4ms/step
2994 [D loss: 0.702054, acc.: 46.88%] [G loss: 0.724603]
8/8 [==============================] - 0s 4ms/step
2995 [D loss: 0.697483, acc.: 50.20%] [G loss: 0.748569]
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2996 [D loss: 0.689995, acc.: 53.91%] [G loss: 0.789556]
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2997 [D loss: 0.688871, acc.: 54.30%] [G loss: 0.779996]
8/8 [==============================] - 0s 4ms/step
2998 [D loss: 0.698135, acc.: 52.54%] [G loss: 0.768630]
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2999 [D loss: 0.694117, acc.: 53.12%] [G loss: 0.752870]
8/8 [==============================] - 0s 4ms/step
3000 [D loss: 0.684515, acc.: 58.59%] [G loss: 0.764808]
1/1 [==============================] - 0s 26ms/step
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3001 [D loss: 0.670020, acc.: 62.30%] [G loss: 0.764674]
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3002 [D loss: 0.676212, acc.: 61.33%] [G loss: 0.754690]
8/8 [==============================] - 0s 4ms/step
3003 [D loss: 0.685264, acc.: 54.69%] [G loss: 0.726046]
8/8 [==============================] - 0s 4ms/step
3004 [D loss: 0.696297, acc.: 53.52%] [G loss: 0.709494]
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3005 [D loss: 0.703307, acc.: 50.59%] [G loss: 0.712850]
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3006 [D loss: 0.706060, acc.: 47.27%] [G loss: 0.718368]
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3007 [D loss: 0.694145, acc.: 50.39%] [G loss: 0.772285]
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3008 [D loss: 0.700476, acc.: 51.17%] [G loss: 0.778312]
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3009 [D loss: 0.693669, acc.: 50.39%] [G loss: 0.782454]
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3010 [D loss: 0.691085, acc.: 56.25%] [G loss: 0.767300]
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3011 [D loss: 0.695216, acc.: 49.22%] [G loss: 0.745596]
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3012 [D loss: 0.692964, acc.: 52.93%] [G loss: 0.744744]
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3013 [D loss: 0.689550, acc.: 54.30%] [G loss: 0.741678]
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3014 [D loss: 0.679785, acc.: 58.20%] [G loss: 0.750483]
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3015 [D loss: 0.680366, acc.: 58.20%] [G loss: 0.724677]
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3016 [D loss: 0.679828, acc.: 55.27%] [G loss: 0.720767]
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3017 [D loss: 0.684136, acc.: 53.91%] [G loss: 0.711599]
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3018 [D loss: 0.694798, acc.: 54.10%] [G loss: 0.712853]
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3019 [D loss: 0.695457, acc.: 53.32%] [G loss: 0.720275]
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3020 [D loss: 0.694626, acc.: 50.20%] [G loss: 0.745874]
8/8 [==============================] - 0s 4ms/step
3021 [D loss: 0.686978, acc.: 54.69%] [G loss: 0.768839]
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3022 [D loss: 0.688806, acc.: 50.20%] [G loss: 0.767623]
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3023 [D loss: 0.697180, acc.: 52.93%] [G loss: 0.750172]
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3024 [D loss: 0.701121, acc.: 48.83%] [G loss: 0.746323]
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3025 [D loss: 0.690269, acc.: 53.71%] [G loss: 0.733998]
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3026 [D loss: 0.693467, acc.: 52.34%] [G loss: 0.751051]
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3027 [D loss: 0.676758, acc.: 58.20%] [G loss: 0.748772]
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3028 [D loss: 0.680083, acc.: 58.20%] [G loss: 0.764985]
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3029 [D loss: 0.678714, acc.: 58.79%] [G loss: 0.736018]
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3030 [D loss: 0.682254, acc.: 55.08%] [G loss: 0.723119]
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3031 [D loss: 0.695285, acc.: 50.59%] [G loss: 0.722281]
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3032 [D loss: 0.692450, acc.: 51.56%] [G loss: 0.722416]
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3033 [D loss: 0.686638, acc.: 53.52%] [G loss: 0.731651]
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3034 [D loss: 0.695771, acc.: 52.73%] [G loss: 0.756931]
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3035 [D loss: 0.690689, acc.: 53.32%] [G loss: 0.741180]
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3036 [D loss: 0.695287, acc.: 51.76%] [G loss: 0.748850]
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3037 [D loss: 0.693525, acc.: 51.76%] [G loss: 0.739106]
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3038 [D loss: 0.688585, acc.: 54.69%] [G loss: 0.744181]
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3039 [D loss: 0.697416, acc.: 51.56%] [G loss: 0.734144]
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3040 [D loss: 0.686273, acc.: 55.08%] [G loss: 0.725009]
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3041 [D loss: 0.686916, acc.: 52.73%] [G loss: 0.720529]
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3042 [D loss: 0.688937, acc.: 55.86%] [G loss: 0.711217]
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3043 [D loss: 0.687173, acc.: 54.69%] [G loss: 0.725675]
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3044 [D loss: 0.688245, acc.: 54.69%] [G loss: 0.738617]
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3045 [D loss: 0.686670, acc.: 54.49%] [G loss: 0.749232]
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3046 [D loss: 0.688592, acc.: 51.17%] [G loss: 0.717645]
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3047 [D loss: 0.697779, acc.: 48.63%] [G loss: 0.748825]
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3048 [D loss: 0.693136, acc.: 53.32%] [G loss: 0.732364]
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3049 [D loss: 0.693395, acc.: 49.61%] [G loss: 0.717379]
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3050 [D loss: 0.700504, acc.: 50.00%] [G loss: 0.717410]
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3051 [D loss: 0.703717, acc.: 49.41%] [G loss: 0.717371]
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3052 [D loss: 0.697396, acc.: 48.63%] [G loss: 0.726637]
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3053 [D loss: 0.699398, acc.: 47.27%] [G loss: 0.729703]
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3054 [D loss: 0.688874, acc.: 54.49%] [G loss: 0.738959]
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3055 [D loss: 0.678329, acc.: 59.18%] [G loss: 0.737302]
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3056 [D loss: 0.685329, acc.: 54.69%] [G loss: 0.738147]
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3057 [D loss: 0.684751, acc.: 54.10%] [G loss: 0.743394]
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3058 [D loss: 0.681045, acc.: 57.23%] [G loss: 0.739374]
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3059 [D loss: 0.684967, acc.: 55.08%] [G loss: 0.726816]
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3060 [D loss: 0.691384, acc.: 51.37%] [G loss: 0.725155]
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3061 [D loss: 0.700824, acc.: 48.24%] [G loss: 0.721124]
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3062 [D loss: 0.687964, acc.: 50.20%] [G loss: 0.725828]
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3063 [D loss: 0.688100, acc.: 53.32%] [G loss: 0.733289]
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3064 [D loss: 0.687521, acc.: 53.91%] [G loss: 0.737070]
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3065 [D loss: 0.696958, acc.: 49.02%] [G loss: 0.739886]
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3066 [D loss: 0.694682, acc.: 50.78%] [G loss: 0.741215]
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3067 [D loss: 0.691311, acc.: 54.10%] [G loss: 0.740695]
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3068 [D loss: 0.685855, acc.: 54.30%] [G loss: 0.734607]
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3069 [D loss: 0.686687, acc.: 52.15%] [G loss: 0.719403]
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3070 [D loss: 0.692875, acc.: 51.17%] [G loss: 0.726060]
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3071 [D loss: 0.688947, acc.: 50.59%] [G loss: 0.718550]
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3072 [D loss: 0.696526, acc.: 49.22%] [G loss: 0.721783]
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3073 [D loss: 0.694212, acc.: 50.39%] [G loss: 0.734154]
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3074 [D loss: 0.691077, acc.: 47.85%] [G loss: 0.740287]
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3075 [D loss: 0.683169, acc.: 55.08%] [G loss: 0.756730]
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3076 [D loss: 0.683653, acc.: 53.71%] [G loss: 0.755907]
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3077 [D loss: 0.683964, acc.: 56.05%] [G loss: 0.761060]
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3078 [D loss: 0.690988, acc.: 53.91%] [G loss: 0.765295]
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3079 [D loss: 0.694970, acc.: 50.59%] [G loss: 0.751238]
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3080 [D loss: 0.683722, acc.: 54.49%] [G loss: 0.745965]
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3081 [D loss: 0.682627, acc.: 58.01%] [G loss: 0.738520]
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3082 [D loss: 0.699029, acc.: 47.85%] [G loss: 0.732645]
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3083 [D loss: 0.682094, acc.: 57.03%] [G loss: 0.729034]
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3084 [D loss: 0.687428, acc.: 53.71%] [G loss: 0.729152]
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3085 [D loss: 0.689429, acc.: 53.71%] [G loss: 0.729511]
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3086 [D loss: 0.689138, acc.: 52.93%] [G loss: 0.738278]
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3087 [D loss: 0.681178, acc.: 55.27%] [G loss: 0.752606]
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3088 [D loss: 0.678955, acc.: 56.25%] [G loss: 0.753465]
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3089 [D loss: 0.680764, acc.: 56.25%] [G loss: 0.744486]
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3090 [D loss: 0.692423, acc.: 51.76%] [G loss: 0.726453]
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3091 [D loss: 0.695995, acc.: 49.61%] [G loss: 0.724831]
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3092 [D loss: 0.701952, acc.: 50.78%] [G loss: 0.708586]
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3093 [D loss: 0.695903, acc.: 51.17%] [G loss: 0.718629]
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3094 [D loss: 0.705914, acc.: 45.90%] [G loss: 0.712080]
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3095 [D loss: 0.693987, acc.: 52.93%] [G loss: 0.724128]
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3096 [D loss: 0.694968, acc.: 50.39%] [G loss: 0.727991]
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3097 [D loss: 0.683196, acc.: 54.49%] [G loss: 0.737468]
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3098 [D loss: 0.691436, acc.: 53.32%] [G loss: 0.741019]
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3099 [D loss: 0.691438, acc.: 54.30%] [G loss: 0.725674]
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3100 [D loss: 0.692564, acc.: 53.52%] [G loss: 0.716653]
1/1 [==============================] - 0s 26ms/step
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3101 [D loss: 0.697967, acc.: 49.22%] [G loss: 0.723696]
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3102 [D loss: 0.689816, acc.: 50.59%] [G loss: 0.724962]
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3103 [D loss: 0.691446, acc.: 50.59%] [G loss: 0.725224]
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3104 [D loss: 0.690291, acc.: 53.91%] [G loss: 0.732446]
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3105 [D loss: 0.695830, acc.: 49.80%] [G loss: 0.732776]
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3106 [D loss: 0.688286, acc.: 54.10%] [G loss: 0.748813]
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3107 [D loss: 0.688883, acc.: 54.10%] [G loss: 0.757975]
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3108 [D loss: 0.699166, acc.: 52.73%] [G loss: 0.750884]
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3109 [D loss: 0.688610, acc.: 55.66%] [G loss: 0.744951]
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3110 [D loss: 0.688183, acc.: 53.91%] [G loss: 0.742539]
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3111 [D loss: 0.689379, acc.: 55.47%] [G loss: 0.750482]
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3112 [D loss: 0.695732, acc.: 51.37%] [G loss: 0.758317]
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3113 [D loss: 0.682544, acc.: 55.86%] [G loss: 0.740934]
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3114 [D loss: 0.686881, acc.: 53.91%] [G loss: 0.729268]
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3115 [D loss: 0.696642, acc.: 52.34%] [G loss: 0.740554]
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3116 [D loss: 0.703489, acc.: 50.20%] [G loss: 0.735408]
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3117 [D loss: 0.696512, acc.: 51.95%] [G loss: 0.741570]
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3118 [D loss: 0.692103, acc.: 53.52%] [G loss: 0.745106]
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3119 [D loss: 0.697992, acc.: 52.73%] [G loss: 0.745905]
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3120 [D loss: 0.685906, acc.: 54.10%] [G loss: 0.752757]
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3121 [D loss: 0.693193, acc.: 50.98%] [G loss: 0.750529]
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3122 [D loss: 0.689636, acc.: 51.95%] [G loss: 0.754519]
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3123 [D loss: 0.679543, acc.: 59.18%] [G loss: 0.751192]
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3124 [D loss: 0.691713, acc.: 51.56%] [G loss: 0.747248]
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3125 [D loss: 0.683463, acc.: 56.64%] [G loss: 0.740895]
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3126 [D loss: 0.689232, acc.: 52.73%] [G loss: 0.725710]
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3127 [D loss: 0.675102, acc.: 60.74%] [G loss: 0.716917]
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3128 [D loss: 0.697959, acc.: 50.20%] [G loss: 0.701570]
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3129 [D loss: 0.692585, acc.: 53.71%] [G loss: 0.691876]
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3130 [D loss: 0.704374, acc.: 46.29%] [G loss: 0.698153]
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3131 [D loss: 0.697992, acc.: 50.39%] [G loss: 0.728733]
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3132 [D loss: 0.687837, acc.: 52.34%] [G loss: 0.757447]
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3133 [D loss: 0.690737, acc.: 50.00%] [G loss: 0.759660]
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3134 [D loss: 0.687994, acc.: 53.52%] [G loss: 0.757946]
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3135 [D loss: 0.690364, acc.: 52.54%] [G loss: 0.745744]
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3136 [D loss: 0.688408, acc.: 55.66%] [G loss: 0.749498]
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3137 [D loss: 0.684414, acc.: 55.47%] [G loss: 0.759021]
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3138 [D loss: 0.678731, acc.: 58.20%] [G loss: 0.745308]
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3139 [D loss: 0.686570, acc.: 50.20%] [G loss: 0.726218]
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3140 [D loss: 0.702306, acc.: 50.39%] [G loss: 0.706154]
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3141 [D loss: 0.712464, acc.: 47.27%] [G loss: 0.712701]
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3142 [D loss: 0.707909, acc.: 45.31%] [G loss: 0.732913]
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3143 [D loss: 0.687153, acc.: 50.20%] [G loss: 0.790192]
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3144 [D loss: 0.683198, acc.: 54.88%] [G loss: 0.792719]
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3145 [D loss: 0.692952, acc.: 51.56%] [G loss: 0.774276]
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3146 [D loss: 0.703226, acc.: 49.22%] [G loss: 0.756920]
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3147 [D loss: 0.691214, acc.: 55.86%] [G loss: 0.762768]
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3148 [D loss: 0.677715, acc.: 61.33%] [G loss: 0.780170]
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3149 [D loss: 0.678587, acc.: 59.38%] [G loss: 0.760347]
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3150 [D loss: 0.688751, acc.: 53.71%] [G loss: 0.727114]
1/1 [==============================] - 0s 25ms/step
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3151 [D loss: 0.705511, acc.: 45.31%] [G loss: 0.697041]
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3152 [D loss: 0.704664, acc.: 48.05%] [G loss: 0.684375]
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3153 [D loss: 0.712415, acc.: 46.29%] [G loss: 0.703372]
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3154 [D loss: 0.688272, acc.: 55.27%] [G loss: 0.755344]
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3155 [D loss: 0.682921, acc.: 54.69%] [G loss: 0.792014]
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3156 [D loss: 0.677800, acc.: 58.79%] [G loss: 0.818910]
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3157 [D loss: 0.691992, acc.: 50.00%] [G loss: 0.780862]
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3158 [D loss: 0.695388, acc.: 56.05%] [G loss: 0.765599]
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3159 [D loss: 0.690335, acc.: 53.91%] [G loss: 0.752522]
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3160 [D loss: 0.685184, acc.: 54.88%] [G loss: 0.757950]
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3161 [D loss: 0.683902, acc.: 56.84%] [G loss: 0.753005]
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3162 [D loss: 0.680343, acc.: 58.01%] [G loss: 0.744133]
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3163 [D loss: 0.682084, acc.: 54.30%] [G loss: 0.730089]
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3164 [D loss: 0.701042, acc.: 49.22%] [G loss: 0.704119]
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3165 [D loss: 0.698448, acc.: 50.78%] [G loss: 0.705740]
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3166 [D loss: 0.696480, acc.: 49.22%] [G loss: 0.721528]
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3167 [D loss: 0.695874, acc.: 46.48%] [G loss: 0.750803]
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3168 [D loss: 0.688715, acc.: 53.52%] [G loss: 0.768117]
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3169 [D loss: 0.687142, acc.: 52.54%] [G loss: 0.758109]
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3170 [D loss: 0.696365, acc.: 48.24%] [G loss: 0.748929]
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3171 [D loss: 0.694979, acc.: 51.56%] [G loss: 0.756728]
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3172 [D loss: 0.686968, acc.: 54.88%] [G loss: 0.736937]
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3173 [D loss: 0.687620, acc.: 54.10%] [G loss: 0.728903]
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3174 [D loss: 0.690125, acc.: 51.95%] [G loss: 0.718940]
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3175 [D loss: 0.694868, acc.: 50.39%] [G loss: 0.716646]
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3176 [D loss: 0.694033, acc.: 49.02%] [G loss: 0.732569]
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3177 [D loss: 0.688459, acc.: 51.17%] [G loss: 0.758410]
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3178 [D loss: 0.693008, acc.: 53.91%] [G loss: 0.750145]
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3179 [D loss: 0.693955, acc.: 53.91%] [G loss: 0.744255]
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3180 [D loss: 0.689837, acc.: 54.88%] [G loss: 0.747795]
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3181 [D loss: 0.692815, acc.: 52.15%] [G loss: 0.749074]
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3182 [D loss: 0.695390, acc.: 50.39%] [G loss: 0.739574]
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3183 [D loss: 0.681050, acc.: 56.05%] [G loss: 0.750444]
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3184 [D loss: 0.680977, acc.: 57.42%] [G loss: 0.731715]
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3185 [D loss: 0.698712, acc.: 49.80%] [G loss: 0.729883]
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3186 [D loss: 0.686379, acc.: 54.49%] [G loss: 0.718676]
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3187 [D loss: 0.698189, acc.: 49.61%] [G loss: 0.731640]
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3188 [D loss: 0.693389, acc.: 53.32%] [G loss: 0.726058]
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3189 [D loss: 0.695567, acc.: 50.98%] [G loss: 0.751116]
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3190 [D loss: 0.684896, acc.: 55.27%] [G loss: 0.767040]
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3191 [D loss: 0.690761, acc.: 51.17%] [G loss: 0.768836]
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3192 [D loss: 0.685616, acc.: 54.88%] [G loss: 0.761049]
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3193 [D loss: 0.695350, acc.: 50.78%] [G loss: 0.752892]
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3194 [D loss: 0.692552, acc.: 51.76%] [G loss: 0.749860]
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3195 [D loss: 0.684294, acc.: 54.10%] [G loss: 0.749062]
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3196 [D loss: 0.684003, acc.: 55.86%] [G loss: 0.740372]
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3197 [D loss: 0.686602, acc.: 56.64%] [G loss: 0.739853]
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3198 [D loss: 0.695891, acc.: 50.20%] [G loss: 0.724627]
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3199 [D loss: 0.697197, acc.: 52.54%] [G loss: 0.730367]
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3200 [D loss: 0.689488, acc.: 53.71%] [G loss: 0.721654]
1/1 [==============================] - 0s 27ms/step
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3201 [D loss: 0.697477, acc.: 50.39%] [G loss: 0.739700]
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3202 [D loss: 0.691505, acc.: 49.02%] [G loss: 0.729263]
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3203 [D loss: 0.694005, acc.: 50.59%] [G loss: 0.743410]
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3204 [D loss: 0.694123, acc.: 53.71%] [G loss: 0.743603]
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3205 [D loss: 0.695640, acc.: 53.91%] [G loss: 0.736317]
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3206 [D loss: 0.689656, acc.: 52.34%] [G loss: 0.739280]
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3207 [D loss: 0.690964, acc.: 53.71%] [G loss: 0.742068]
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3208 [D loss: 0.692863, acc.: 50.00%] [G loss: 0.723389]
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3209 [D loss: 0.686604, acc.: 56.64%] [G loss: 0.718979]
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3210 [D loss: 0.693013, acc.: 54.49%] [G loss: 0.719287]
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3211 [D loss: 0.691343, acc.: 51.76%] [G loss: 0.712713]
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3212 [D loss: 0.699216, acc.: 50.39%] [G loss: 0.713594]
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3213 [D loss: 0.691356, acc.: 51.37%] [G loss: 0.742149]
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3214 [D loss: 0.692653, acc.: 52.34%] [G loss: 0.754210]
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3215 [D loss: 0.687713, acc.: 54.88%] [G loss: 0.763198]
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3216 [D loss: 0.687958, acc.: 52.73%] [G loss: 0.761784]
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3217 [D loss: 0.689938, acc.: 52.73%] [G loss: 0.756110]
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3218 [D loss: 0.689021, acc.: 53.91%] [G loss: 0.742057]
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3219 [D loss: 0.683351, acc.: 58.20%] [G loss: 0.749890]
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3220 [D loss: 0.681699, acc.: 58.98%] [G loss: 0.739989]
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3221 [D loss: 0.689983, acc.: 54.10%] [G loss: 0.734369]
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3222 [D loss: 0.684278, acc.: 56.05%] [G loss: 0.718014]
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3223 [D loss: 0.687454, acc.: 53.12%] [G loss: 0.727666]
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3224 [D loss: 0.694109, acc.: 49.80%] [G loss: 0.707789]
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3225 [D loss: 0.692477, acc.: 51.56%] [G loss: 0.723144]
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3226 [D loss: 0.689131, acc.: 55.08%] [G loss: 0.732842]
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3227 [D loss: 0.690237, acc.: 53.32%] [G loss: 0.746917]
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3228 [D loss: 0.684483, acc.: 55.47%] [G loss: 0.771575]
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3229 [D loss: 0.688620, acc.: 54.49%] [G loss: 0.752914]
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3230 [D loss: 0.694896, acc.: 50.59%] [G loss: 0.748397]
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3231 [D loss: 0.693576, acc.: 52.34%] [G loss: 0.752247]
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3232 [D loss: 0.685079, acc.: 54.88%] [G loss: 0.757807]
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3233 [D loss: 0.688919, acc.: 50.20%] [G loss: 0.754997]
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3234 [D loss: 0.681383, acc.: 56.45%] [G loss: 0.739503]
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3235 [D loss: 0.695217, acc.: 51.76%] [G loss: 0.722784]
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3236 [D loss: 0.691767, acc.: 51.95%] [G loss: 0.727488]
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3237 [D loss: 0.695660, acc.: 51.37%] [G loss: 0.722011]
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3238 [D loss: 0.691412, acc.: 52.73%] [G loss: 0.717786]
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3239 [D loss: 0.692987, acc.: 50.98%] [G loss: 0.732840]
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3240 [D loss: 0.689818, acc.: 52.73%] [G loss: 0.748999]
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3241 [D loss: 0.689379, acc.: 54.10%] [G loss: 0.752662]
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3242 [D loss: 0.684995, acc.: 55.27%] [G loss: 0.753569]
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3243 [D loss: 0.686185, acc.: 55.66%] [G loss: 0.751378]
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3244 [D loss: 0.689442, acc.: 53.12%] [G loss: 0.744231]
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3245 [D loss: 0.691650, acc.: 50.00%] [G loss: 0.742188]
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3246 [D loss: 0.685146, acc.: 59.18%] [G loss: 0.743158]
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3247 [D loss: 0.693640, acc.: 50.39%] [G loss: 0.733830]
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3248 [D loss: 0.681433, acc.: 56.84%] [G loss: 0.718426]
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3249 [D loss: 0.697456, acc.: 52.93%] [G loss: 0.719975]
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3250 [D loss: 0.690360, acc.: 55.08%] [G loss: 0.718348]
1/1 [==============================] - 0s 24ms/step
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3251 [D loss: 0.694827, acc.: 50.98%] [G loss: 0.716024]
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3252 [D loss: 0.703000, acc.: 46.48%] [G loss: 0.730536]
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3253 [D loss: 0.692335, acc.: 51.76%] [G loss: 0.738116]
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3254 [D loss: 0.687531, acc.: 55.08%] [G loss: 0.739781]
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3255 [D loss: 0.690811, acc.: 52.73%] [G loss: 0.746389]
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3256 [D loss: 0.686625, acc.: 55.66%] [G loss: 0.747177]
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3257 [D loss: 0.685395, acc.: 54.10%] [G loss: 0.735905]
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3258 [D loss: 0.694656, acc.: 51.56%] [G loss: 0.733580]
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3259 [D loss: 0.696896, acc.: 50.39%] [G loss: 0.729580]
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3260 [D loss: 0.689507, acc.: 54.10%] [G loss: 0.726870]
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3261 [D loss: 0.684089, acc.: 56.84%] [G loss: 0.736227]
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3262 [D loss: 0.693222, acc.: 50.98%] [G loss: 0.728145]
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3263 [D loss: 0.690628, acc.: 51.56%] [G loss: 0.733008]
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3264 [D loss: 0.690233, acc.: 51.37%] [G loss: 0.735520]
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3265 [D loss: 0.689978, acc.: 51.56%] [G loss: 0.742948]
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3266 [D loss: 0.684859, acc.: 55.86%] [G loss: 0.737856]
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3267 [D loss: 0.698577, acc.: 48.44%] [G loss: 0.746990]
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3268 [D loss: 0.690571, acc.: 53.71%] [G loss: 0.738447]
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3269 [D loss: 0.685524, acc.: 54.30%] [G loss: 0.743271]
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3270 [D loss: 0.691315, acc.: 51.95%] [G loss: 0.746219]
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3271 [D loss: 0.693272, acc.: 51.76%] [G loss: 0.732144]
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3272 [D loss: 0.692090, acc.: 52.34%] [G loss: 0.728989]
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3273 [D loss: 0.686829, acc.: 54.88%] [G loss: 0.721925]
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3274 [D loss: 0.695531, acc.: 52.34%] [G loss: 0.718662]
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3275 [D loss: 0.686851, acc.: 56.05%] [G loss: 0.716332]
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3276 [D loss: 0.689950, acc.: 51.37%] [G loss: 0.734608]
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3277 [D loss: 0.689265, acc.: 53.71%] [G loss: 0.740677]
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3278 [D loss: 0.689518, acc.: 54.30%] [G loss: 0.742890]
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3279 [D loss: 0.695303, acc.: 50.39%] [G loss: 0.729005]
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3280 [D loss: 0.695425, acc.: 52.93%] [G loss: 0.737667]
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3281 [D loss: 0.688814, acc.: 51.56%] [G loss: 0.736107]
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3282 [D loss: 0.695886, acc.: 49.80%] [G loss: 0.730188]
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3283 [D loss: 0.692592, acc.: 48.83%] [G loss: 0.725238]
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3284 [D loss: 0.696283, acc.: 50.20%] [G loss: 0.726457]
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3285 [D loss: 0.694151, acc.: 52.15%] [G loss: 0.715064]
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3286 [D loss: 0.689267, acc.: 50.98%] [G loss: 0.729884]
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3287 [D loss: 0.697852, acc.: 50.59%] [G loss: 0.743650]
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3288 [D loss: 0.689926, acc.: 52.73%] [G loss: 0.748755]
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3289 [D loss: 0.681672, acc.: 55.86%] [G loss: 0.753786]
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3290 [D loss: 0.682452, acc.: 58.01%] [G loss: 0.741554]
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3291 [D loss: 0.696739, acc.: 50.59%] [G loss: 0.742514]
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3292 [D loss: 0.694647, acc.: 50.98%] [G loss: 0.736811]
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3293 [D loss: 0.688770, acc.: 55.27%] [G loss: 0.731833]
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3294 [D loss: 0.692756, acc.: 52.54%] [G loss: 0.724853]
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3295 [D loss: 0.688084, acc.: 53.32%] [G loss: 0.719197]
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3296 [D loss: 0.684537, acc.: 54.49%] [G loss: 0.721156]
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3297 [D loss: 0.693679, acc.: 52.54%] [G loss: 0.713797]
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3298 [D loss: 0.697196, acc.: 48.44%] [G loss: 0.722842]
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3299 [D loss: 0.693770, acc.: 52.15%] [G loss: 0.723069]
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3300 [D loss: 0.700311, acc.: 49.22%] [G loss: 0.756784]
1/1 [==============================] - 0s 24ms/step
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3301 [D loss: 0.684614, acc.: 53.71%] [G loss: 0.770424]
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3302 [D loss: 0.681566, acc.: 56.05%] [G loss: 0.756088]
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3303 [D loss: 0.691631, acc.: 51.37%] [G loss: 0.762629]
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3304 [D loss: 0.691530, acc.: 50.98%] [G loss: 0.744891]
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3305 [D loss: 0.685610, acc.: 55.08%] [G loss: 0.741045]
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3306 [D loss: 0.684971, acc.: 56.05%] [G loss: 0.738360]
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3307 [D loss: 0.691947, acc.: 51.56%] [G loss: 0.736829]
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3308 [D loss: 0.695788, acc.: 49.41%] [G loss: 0.726605]
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3309 [D loss: 0.693993, acc.: 52.34%] [G loss: 0.702740]
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3310 [D loss: 0.693747, acc.: 50.39%] [G loss: 0.717720]
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3311 [D loss: 0.693963, acc.: 51.56%] [G loss: 0.733713]
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3312 [D loss: 0.688646, acc.: 47.07%] [G loss: 0.757258]
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3313 [D loss: 0.687855, acc.: 56.64%] [G loss: 0.775222]
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3314 [D loss: 0.685439, acc.: 54.49%] [G loss: 0.778066]
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3315 [D loss: 0.691077, acc.: 51.76%] [G loss: 0.757821]
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3316 [D loss: 0.696907, acc.: 50.20%] [G loss: 0.741548]
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3317 [D loss: 0.694784, acc.: 50.78%] [G loss: 0.740979]
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3318 [D loss: 0.694969, acc.: 50.98%] [G loss: 0.728957]
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3319 [D loss: 0.687770, acc.: 54.30%] [G loss: 0.727051]
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3320 [D loss: 0.695116, acc.: 49.61%] [G loss: 0.715288]
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3321 [D loss: 0.692071, acc.: 50.78%] [G loss: 0.700963]
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3322 [D loss: 0.691862, acc.: 51.56%] [G loss: 0.711952]
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3323 [D loss: 0.689716, acc.: 52.73%] [G loss: 0.733838]
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3324 [D loss: 0.684117, acc.: 55.27%] [G loss: 0.754949]
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3325 [D loss: 0.683454, acc.: 58.79%] [G loss: 0.770393]
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3326 [D loss: 0.690228, acc.: 53.52%] [G loss: 0.777971]
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3327 [D loss: 0.689008, acc.: 54.30%] [G loss: 0.770401]
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3328 [D loss: 0.685856, acc.: 54.69%] [G loss: 0.746385]
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3329 [D loss: 0.696275, acc.: 48.63%] [G loss: 0.741752]
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3330 [D loss: 0.685555, acc.: 55.27%] [G loss: 0.737578]
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3331 [D loss: 0.693854, acc.: 52.73%] [G loss: 0.724927]
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3332 [D loss: 0.690025, acc.: 50.59%] [G loss: 0.720335]
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3333 [D loss: 0.690930, acc.: 51.37%] [G loss: 0.709124]
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3334 [D loss: 0.705112, acc.: 45.70%] [G loss: 0.698208]
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3335 [D loss: 0.700898, acc.: 48.63%] [G loss: 0.702337]
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3336 [D loss: 0.698328, acc.: 49.61%] [G loss: 0.718690]
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3337 [D loss: 0.688934, acc.: 55.66%] [G loss: 0.765703]
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3338 [D loss: 0.685914, acc.: 53.71%] [G loss: 0.771107]
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3339 [D loss: 0.683264, acc.: 55.08%] [G loss: 0.772946]
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3340 [D loss: 0.699611, acc.: 48.83%] [G loss: 0.735677]
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3341 [D loss: 0.699009, acc.: 51.76%] [G loss: 0.728871]
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3342 [D loss: 0.694528, acc.: 51.17%] [G loss: 0.729324]
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3343 [D loss: 0.687656, acc.: 50.78%] [G loss: 0.718959]
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3344 [D loss: 0.689327, acc.: 50.59%] [G loss: 0.719899]
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3345 [D loss: 0.691411, acc.: 53.52%] [G loss: 0.715507]
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3346 [D loss: 0.699100, acc.: 49.61%] [G loss: 0.710067]
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3347 [D loss: 0.689423, acc.: 50.59%] [G loss: 0.711237]
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3348 [D loss: 0.690311, acc.: 52.34%] [G loss: 0.727511]
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3349 [D loss: 0.680498, acc.: 58.40%] [G loss: 0.752712]
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3350 [D loss: 0.690564, acc.: 50.78%] [G loss: 0.765959]
1/1 [==============================] - 0s 33ms/step
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3351 [D loss: 0.685779, acc.: 56.05%] [G loss: 0.765845]
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3352 [D loss: 0.695332, acc.: 51.95%] [G loss: 0.772860]
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3353 [D loss: 0.698968, acc.: 51.95%] [G loss: 0.756907]
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3354 [D loss: 0.709350, acc.: 45.12%] [G loss: 0.733602]
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3355 [D loss: 0.703472, acc.: 47.66%] [G loss: 0.730463]
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3356 [D loss: 0.691382, acc.: 53.71%] [G loss: 0.731355]
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3357 [D loss: 0.694845, acc.: 52.15%] [G loss: 0.726261]
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3358 [D loss: 0.693539, acc.: 53.52%] [G loss: 0.735561]
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3359 [D loss: 0.689856, acc.: 54.49%] [G loss: 0.742630]
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3360 [D loss: 0.684837, acc.: 55.08%] [G loss: 0.764307]
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3361 [D loss: 0.682789, acc.: 56.84%] [G loss: 0.758853]
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3362 [D loss: 0.676559, acc.: 59.96%] [G loss: 0.771333]
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3363 [D loss: 0.685687, acc.: 56.05%] [G loss: 0.762632]
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3364 [D loss: 0.696126, acc.: 50.59%] [G loss: 0.752400]
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3365 [D loss: 0.680461, acc.: 54.69%] [G loss: 0.722629]
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3366 [D loss: 0.687100, acc.: 54.10%] [G loss: 0.719716]
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3367 [D loss: 0.688517, acc.: 53.91%] [G loss: 0.720113]
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3368 [D loss: 0.698120, acc.: 48.44%] [G loss: 0.709901]
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3369 [D loss: 0.698579, acc.: 48.83%] [G loss: 0.725176]
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3370 [D loss: 0.699201, acc.: 49.80%] [G loss: 0.726009]
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3371 [D loss: 0.688753, acc.: 53.12%] [G loss: 0.739180]
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3372 [D loss: 0.687002, acc.: 53.91%] [G loss: 0.748664]
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3373 [D loss: 0.690530, acc.: 52.54%] [G loss: 0.758353]
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3374 [D loss: 0.699559, acc.: 49.80%] [G loss: 0.742298]
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3375 [D loss: 0.692977, acc.: 52.54%] [G loss: 0.729593]
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3376 [D loss: 0.686609, acc.: 53.71%] [G loss: 0.740428]
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3377 [D loss: 0.687832, acc.: 55.08%] [G loss: 0.745249]
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3378 [D loss: 0.683231, acc.: 53.32%] [G loss: 0.741779]
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3379 [D loss: 0.685218, acc.: 53.91%] [G loss: 0.730410]
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3380 [D loss: 0.687032, acc.: 53.91%] [G loss: 0.730684]
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3381 [D loss: 0.692742, acc.: 51.17%] [G loss: 0.723132]
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3382 [D loss: 0.690590, acc.: 52.34%] [G loss: 0.737754]
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3383 [D loss: 0.683426, acc.: 55.47%] [G loss: 0.757666]
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3384 [D loss: 0.690113, acc.: 49.80%] [G loss: 0.755079]
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3385 [D loss: 0.691675, acc.: 53.91%] [G loss: 0.743206]
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3386 [D loss: 0.696185, acc.: 52.34%] [G loss: 0.738876]
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3387 [D loss: 0.686132, acc.: 54.88%] [G loss: 0.740326]
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3388 [D loss: 0.687171, acc.: 57.42%] [G loss: 0.740626]
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3389 [D loss: 0.682910, acc.: 55.27%] [G loss: 0.738750]
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3390 [D loss: 0.681739, acc.: 57.42%] [G loss: 0.718043]
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3391 [D loss: 0.698818, acc.: 49.80%] [G loss: 0.701112]
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3392 [D loss: 0.698784, acc.: 47.27%] [G loss: 0.710659]
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3393 [D loss: 0.703501, acc.: 47.27%] [G loss: 0.731023]
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3394 [D loss: 0.700104, acc.: 50.39%] [G loss: 0.749994]
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3395 [D loss: 0.698846, acc.: 48.44%] [G loss: 0.775549]
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3396 [D loss: 0.689687, acc.: 53.71%] [G loss: 0.768976]
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3397 [D loss: 0.689923, acc.: 51.17%] [G loss: 0.756849]
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3398 [D loss: 0.692333, acc.: 49.02%] [G loss: 0.741408]
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3399 [D loss: 0.688946, acc.: 53.12%] [G loss: 0.742704]
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3400 [D loss: 0.692814, acc.: 51.76%] [G loss: 0.743627]
1/1 [==============================] - 0s 27ms/step
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3401 [D loss: 0.678672, acc.: 57.03%] [G loss: 0.742203]
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3402 [D loss: 0.679641, acc.: 57.81%] [G loss: 0.738000]
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3403 [D loss: 0.684088, acc.: 55.47%] [G loss: 0.736498]
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3404 [D loss: 0.688979, acc.: 51.17%] [G loss: 0.714393]
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3405 [D loss: 0.693627, acc.: 52.15%] [G loss: 0.713562]
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3406 [D loss: 0.686729, acc.: 49.61%] [G loss: 0.731240]
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3407 [D loss: 0.687425, acc.: 55.08%] [G loss: 0.736448]
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3408 [D loss: 0.681222, acc.: 56.45%] [G loss: 0.750531]
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3409 [D loss: 0.692943, acc.: 51.37%] [G loss: 0.746839]
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3410 [D loss: 0.691021, acc.: 53.32%] [G loss: 0.747420]
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3411 [D loss: 0.690017, acc.: 52.54%] [G loss: 0.735641]
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3412 [D loss: 0.695871, acc.: 49.02%] [G loss: 0.727640]
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3413 [D loss: 0.689934, acc.: 52.73%] [G loss: 0.735187]
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3414 [D loss: 0.686346, acc.: 56.45%] [G loss: 0.719606]
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3415 [D loss: 0.699642, acc.: 51.56%] [G loss: 0.725265]
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3416 [D loss: 0.695059, acc.: 50.78%] [G loss: 0.734665]
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3417 [D loss: 0.689031, acc.: 52.54%] [G loss: 0.733692]
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3418 [D loss: 0.689856, acc.: 51.76%] [G loss: 0.730330]
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3419 [D loss: 0.684577, acc.: 57.03%] [G loss: 0.739077]
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3420 [D loss: 0.691447, acc.: 52.93%] [G loss: 0.771056]
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3421 [D loss: 0.680140, acc.: 55.08%] [G loss: 0.755856]
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3422 [D loss: 0.688419, acc.: 51.37%] [G loss: 0.771103]
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3423 [D loss: 0.695000, acc.: 50.20%] [G loss: 0.752595]
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3424 [D loss: 0.697181, acc.: 47.85%] [G loss: 0.737530]
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3425 [D loss: 0.692425, acc.: 54.10%] [G loss: 0.730283]
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3426 [D loss: 0.693780, acc.: 50.78%] [G loss: 0.713059]
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3427 [D loss: 0.705831, acc.: 47.07%] [G loss: 0.717269]
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3428 [D loss: 0.699493, acc.: 48.83%] [G loss: 0.704667]
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3429 [D loss: 0.697642, acc.: 51.95%] [G loss: 0.723347]
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3430 [D loss: 0.691924, acc.: 52.73%] [G loss: 0.734832]
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3431 [D loss: 0.680672, acc.: 55.86%] [G loss: 0.747298]
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3432 [D loss: 0.682664, acc.: 54.88%] [G loss: 0.747024]
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3433 [D loss: 0.688145, acc.: 53.91%] [G loss: 0.736133]
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3434 [D loss: 0.683389, acc.: 54.69%] [G loss: 0.743537]
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3435 [D loss: 0.682810, acc.: 56.64%] [G loss: 0.748289]
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3436 [D loss: 0.686613, acc.: 54.10%] [G loss: 0.733378]
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3437 [D loss: 0.694734, acc.: 53.32%] [G loss: 0.728665]
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3438 [D loss: 0.691379, acc.: 53.52%] [G loss: 0.716305]
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3439 [D loss: 0.695010, acc.: 50.00%] [G loss: 0.717368]
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3440 [D loss: 0.695670, acc.: 52.93%] [G loss: 0.730331]
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3441 [D loss: 0.697580, acc.: 49.41%] [G loss: 0.735497]
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3442 [D loss: 0.690794, acc.: 50.20%] [G loss: 0.747341]
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3443 [D loss: 0.699497, acc.: 48.24%] [G loss: 0.759343]
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3444 [D loss: 0.699056, acc.: 47.46%] [G loss: 0.765670]
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3445 [D loss: 0.695989, acc.: 52.54%] [G loss: 0.751637]
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3446 [D loss: 0.698643, acc.: 48.83%] [G loss: 0.754692]
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3447 [D loss: 0.690095, acc.: 50.78%] [G loss: 0.750871]
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3448 [D loss: 0.683072, acc.: 56.45%] [G loss: 0.754965]
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3449 [D loss: 0.683816, acc.: 56.84%] [G loss: 0.750806]
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3450 [D loss: 0.675415, acc.: 62.30%] [G loss: 0.738662]
1/1 [==============================] - 0s 27ms/step
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3451 [D loss: 0.691574, acc.: 51.95%] [G loss: 0.723585]
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3452 [D loss: 0.707429, acc.: 45.90%] [G loss: 0.712315]
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3453 [D loss: 0.696010, acc.: 51.37%] [G loss: 0.709352]
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3454 [D loss: 0.692954, acc.: 50.98%] [G loss: 0.744490]
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3455 [D loss: 0.684464, acc.: 57.81%] [G loss: 0.768333]
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3456 [D loss: 0.693330, acc.: 51.37%] [G loss: 0.775811]
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3457 [D loss: 0.701470, acc.: 51.17%] [G loss: 0.758982]
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3458 [D loss: 0.704257, acc.: 49.22%] [G loss: 0.732461]
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3459 [D loss: 0.700564, acc.: 47.85%] [G loss: 0.736573]
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3460 [D loss: 0.691406, acc.: 54.30%] [G loss: 0.730597]
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3461 [D loss: 0.678951, acc.: 58.01%] [G loss: 0.719985]
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3462 [D loss: 0.678486, acc.: 58.40%] [G loss: 0.715144]
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3463 [D loss: 0.694136, acc.: 53.12%] [G loss: 0.700549]
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3464 [D loss: 0.698649, acc.: 49.61%] [G loss: 0.703018]
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3465 [D loss: 0.696658, acc.: 47.66%] [G loss: 0.695339]
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3466 [D loss: 0.700000, acc.: 49.61%] [G loss: 0.710984]
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3467 [D loss: 0.692509, acc.: 48.63%] [G loss: 0.732215]
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3468 [D loss: 0.694750, acc.: 49.41%] [G loss: 0.754211]
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3469 [D loss: 0.696554, acc.: 50.59%] [G loss: 0.751116]
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3470 [D loss: 0.697063, acc.: 47.66%] [G loss: 0.744372]
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3471 [D loss: 0.701524, acc.: 47.85%] [G loss: 0.744306]
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3472 [D loss: 0.693328, acc.: 49.22%] [G loss: 0.745426]
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3473 [D loss: 0.687222, acc.: 54.69%] [G loss: 0.735137]
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3474 [D loss: 0.684132, acc.: 54.69%] [G loss: 0.741422]
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3475 [D loss: 0.688414, acc.: 51.17%] [G loss: 0.733527]
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3476 [D loss: 0.686855, acc.: 54.49%] [G loss: 0.731532]
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3477 [D loss: 0.683356, acc.: 53.71%] [G loss: 0.729019]
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3478 [D loss: 0.691370, acc.: 52.15%] [G loss: 0.710904]
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3479 [D loss: 0.697117, acc.: 52.15%] [G loss: 0.719034]
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3480 [D loss: 0.693490, acc.: 47.07%] [G loss: 0.725136]
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3481 [D loss: 0.695714, acc.: 49.22%] [G loss: 0.760882]
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3482 [D loss: 0.687938, acc.: 51.76%] [G loss: 0.760702]
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3483 [D loss: 0.690794, acc.: 50.39%] [G loss: 0.756491]
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3484 [D loss: 0.693466, acc.: 52.34%] [G loss: 0.749147]
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3485 [D loss: 0.693726, acc.: 52.34%] [G loss: 0.750201]
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3486 [D loss: 0.687338, acc.: 53.71%] [G loss: 0.756685]
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3487 [D loss: 0.680623, acc.: 57.81%] [G loss: 0.752903]
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3488 [D loss: 0.684168, acc.: 56.45%] [G loss: 0.742546]
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3489 [D loss: 0.682126, acc.: 55.47%] [G loss: 0.723305]
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3490 [D loss: 0.695054, acc.: 48.44%] [G loss: 0.721265]
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3491 [D loss: 0.690336, acc.: 50.59%] [G loss: 0.725929]
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3492 [D loss: 0.687635, acc.: 53.91%] [G loss: 0.740900]
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3493 [D loss: 0.690123, acc.: 55.27%] [G loss: 0.753727]
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3494 [D loss: 0.702835, acc.: 51.17%] [G loss: 0.768957]
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3495 [D loss: 0.700687, acc.: 49.80%] [G loss: 0.745483]
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3496 [D loss: 0.706074, acc.: 49.61%] [G loss: 0.738854]
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3497 [D loss: 0.702586, acc.: 48.44%] [G loss: 0.717942]
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3498 [D loss: 0.697870, acc.: 48.05%] [G loss: 0.724537]
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3499 [D loss: 0.692382, acc.: 49.61%] [G loss: 0.715403]
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3500 [D loss: 0.689566, acc.: 53.12%] [G loss: 0.729441]
1/1 [==============================] - 0s 27ms/step
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3501 [D loss: 0.691033, acc.: 53.91%] [G loss: 0.730754]
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3502 [D loss: 0.685072, acc.: 53.71%] [G loss: 0.733122]
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3503 [D loss: 0.692564, acc.: 53.52%] [G loss: 0.754708]
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3504 [D loss: 0.682551, acc.: 56.84%] [G loss: 0.742094]
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3505 [D loss: 0.678279, acc.: 58.01%] [G loss: 0.772511]
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3506 [D loss: 0.678664, acc.: 57.23%] [G loss: 0.777773]
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3507 [D loss: 0.685159, acc.: 56.64%] [G loss: 0.768918]
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3508 [D loss: 0.683085, acc.: 52.15%] [G loss: 0.735155]
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3509 [D loss: 0.690707, acc.: 51.76%] [G loss: 0.737388]
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3510 [D loss: 0.688068, acc.: 55.86%] [G loss: 0.738127]
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3511 [D loss: 0.705185, acc.: 48.24%] [G loss: 0.715590]
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3512 [D loss: 0.697789, acc.: 54.49%] [G loss: 0.718957]
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3513 [D loss: 0.697726, acc.: 49.61%] [G loss: 0.714705]
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3514 [D loss: 0.690735, acc.: 50.78%] [G loss: 0.725097]
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3515 [D loss: 0.696438, acc.: 50.59%] [G loss: 0.736284]
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3516 [D loss: 0.687471, acc.: 52.54%] [G loss: 0.722194]
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3517 [D loss: 0.688279, acc.: 51.95%] [G loss: 0.728682]
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3518 [D loss: 0.690088, acc.: 49.41%] [G loss: 0.729563]
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3519 [D loss: 0.688963, acc.: 54.30%] [G loss: 0.735110]
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3520 [D loss: 0.685367, acc.: 57.23%] [G loss: 0.723143]
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3521 [D loss: 0.697363, acc.: 50.00%] [G loss: 0.733096]
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3522 [D loss: 0.683729, acc.: 54.69%] [G loss: 0.725933]
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3523 [D loss: 0.691083, acc.: 53.91%] [G loss: 0.729126]
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3524 [D loss: 0.693489, acc.: 50.59%] [G loss: 0.729860]
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3525 [D loss: 0.686295, acc.: 53.12%] [G loss: 0.734630]
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3526 [D loss: 0.696673, acc.: 50.59%] [G loss: 0.738501]
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3527 [D loss: 0.688278, acc.: 55.08%] [G loss: 0.748559]
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3528 [D loss: 0.683299, acc.: 55.08%] [G loss: 0.760151]
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3529 [D loss: 0.688189, acc.: 55.66%] [G loss: 0.772532]
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3530 [D loss: 0.692560, acc.: 53.12%] [G loss: 0.769161]
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3531 [D loss: 0.682441, acc.: 55.27%] [G loss: 0.771235]
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3532 [D loss: 0.683959, acc.: 58.59%] [G loss: 0.766465]
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3533 [D loss: 0.683530, acc.: 54.69%] [G loss: 0.750158]
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3534 [D loss: 0.679058, acc.: 56.25%] [G loss: 0.743198]
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3535 [D loss: 0.670405, acc.: 61.13%] [G loss: 0.743253]
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3536 [D loss: 0.696358, acc.: 48.24%] [G loss: 0.731660]
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3537 [D loss: 0.691413, acc.: 50.98%] [G loss: 0.696452]
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3538 [D loss: 0.697387, acc.: 48.05%] [G loss: 0.697216]
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3539 [D loss: 0.719233, acc.: 43.36%] [G loss: 0.685534]
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3540 [D loss: 0.703241, acc.: 49.02%] [G loss: 0.718470]
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3541 [D loss: 0.701823, acc.: 47.46%] [G loss: 0.751756]
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3542 [D loss: 0.693807, acc.: 50.98%] [G loss: 0.794715]
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3543 [D loss: 0.682425, acc.: 57.42%] [G loss: 0.795686]
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3544 [D loss: 0.685591, acc.: 54.49%] [G loss: 0.759610]
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3545 [D loss: 0.693236, acc.: 54.30%] [G loss: 0.746991]
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3546 [D loss: 0.684625, acc.: 57.03%] [G loss: 0.743688]
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3547 [D loss: 0.686599, acc.: 55.86%] [G loss: 0.740772]
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3548 [D loss: 0.684100, acc.: 55.86%] [G loss: 0.737252]
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3549 [D loss: 0.681038, acc.: 54.49%] [G loss: 0.720575]
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3550 [D loss: 0.687317, acc.: 53.71%] [G loss: 0.710435]
1/1 [==============================] - 0s 25ms/step
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3551 [D loss: 0.692863, acc.: 51.17%] [G loss: 0.702117]
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3552 [D loss: 0.698935, acc.: 50.59%] [G loss: 0.705971]
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3553 [D loss: 0.690829, acc.: 54.88%] [G loss: 0.737475]
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3554 [D loss: 0.690264, acc.: 54.10%] [G loss: 0.756959]
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3555 [D loss: 0.689206, acc.: 52.15%] [G loss: 0.788749]
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3556 [D loss: 0.686136, acc.: 54.69%] [G loss: 0.776106]
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3557 [D loss: 0.706862, acc.: 45.90%] [G loss: 0.755963]
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3558 [D loss: 0.687816, acc.: 51.56%] [G loss: 0.750895]
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3559 [D loss: 0.687171, acc.: 55.08%] [G loss: 0.751439]
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3560 [D loss: 0.683352, acc.: 55.47%] [G loss: 0.748490]
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3561 [D loss: 0.680456, acc.: 57.62%] [G loss: 0.734081]
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3562 [D loss: 0.685663, acc.: 52.15%] [G loss: 0.732202]
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3563 [D loss: 0.690918, acc.: 55.27%] [G loss: 0.713717]
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3564 [D loss: 0.697673, acc.: 51.37%] [G loss: 0.722325]
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3565 [D loss: 0.702164, acc.: 49.61%] [G loss: 0.732118]
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3566 [D loss: 0.693427, acc.: 50.00%] [G loss: 0.742983]
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3567 [D loss: 0.701952, acc.: 49.41%] [G loss: 0.743787]
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3568 [D loss: 0.695402, acc.: 51.56%] [G loss: 0.750700]
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3569 [D loss: 0.703265, acc.: 48.05%] [G loss: 0.750031]
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3570 [D loss: 0.698472, acc.: 46.48%] [G loss: 0.736274]
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3571 [D loss: 0.691935, acc.: 52.15%] [G loss: 0.724051]
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3572 [D loss: 0.687774, acc.: 50.00%] [G loss: 0.730992]
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3573 [D loss: 0.685126, acc.: 55.08%] [G loss: 0.721764]
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3574 [D loss: 0.696874, acc.: 50.39%] [G loss: 0.726412]
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3575 [D loss: 0.691775, acc.: 50.20%] [G loss: 0.733508]
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3576 [D loss: 0.695924, acc.: 46.88%] [G loss: 0.722700]
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3577 [D loss: 0.689485, acc.: 54.49%] [G loss: 0.725799]
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3578 [D loss: 0.692138, acc.: 50.78%] [G loss: 0.740169]
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3579 [D loss: 0.695759, acc.: 51.95%] [G loss: 0.738515]
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3580 [D loss: 0.698131, acc.: 47.07%] [G loss: 0.751186]
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3581 [D loss: 0.703172, acc.: 47.07%] [G loss: 0.736129]
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3582 [D loss: 0.695171, acc.: 48.63%] [G loss: 0.743052]
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3583 [D loss: 0.698987, acc.: 48.83%] [G loss: 0.738613]
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3584 [D loss: 0.684038, acc.: 54.10%] [G loss: 0.741711]
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3585 [D loss: 0.684611, acc.: 56.05%] [G loss: 0.755101]
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3586 [D loss: 0.678918, acc.: 57.23%] [G loss: 0.749253]
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3587 [D loss: 0.672480, acc.: 58.01%] [G loss: 0.746589]
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3588 [D loss: 0.675080, acc.: 58.20%] [G loss: 0.740765]
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3589 [D loss: 0.689758, acc.: 50.98%] [G loss: 0.736874]
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3590 [D loss: 0.693036, acc.: 51.76%] [G loss: 0.737567]
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3591 [D loss: 0.696429, acc.: 48.83%] [G loss: 0.733970]
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3592 [D loss: 0.695959, acc.: 52.93%] [G loss: 0.734176]
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3593 [D loss: 0.708013, acc.: 48.44%] [G loss: 0.739049]
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3594 [D loss: 0.698992, acc.: 50.00%] [G loss: 0.724678]
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3595 [D loss: 0.702867, acc.: 48.44%] [G loss: 0.723550]
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3596 [D loss: 0.688906, acc.: 54.49%] [G loss: 0.733012]
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3597 [D loss: 0.692570, acc.: 53.32%] [G loss: 0.734450]
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3598 [D loss: 0.688993, acc.: 53.91%] [G loss: 0.735086]
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3599 [D loss: 0.689169, acc.: 54.30%] [G loss: 0.729356]
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3600 [D loss: 0.681069, acc.: 56.25%] [G loss: 0.752677]
1/1 [==============================] - 0s 31ms/step
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3601 [D loss: 0.687483, acc.: 52.73%] [G loss: 0.732467]
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3602 [D loss: 0.688371, acc.: 55.27%] [G loss: 0.751013]
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3603 [D loss: 0.695294, acc.: 47.66%] [G loss: 0.745301]
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3604 [D loss: 0.691817, acc.: 51.56%] [G loss: 0.743641]
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3605 [D loss: 0.687923, acc.: 52.93%] [G loss: 0.751884]
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3606 [D loss: 0.696702, acc.: 52.54%] [G loss: 0.741377]
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3607 [D loss: 0.680676, acc.: 53.71%] [G loss: 0.743492]
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3608 [D loss: 0.676672, acc.: 56.25%] [G loss: 0.752116]
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3609 [D loss: 0.677083, acc.: 58.01%] [G loss: 0.754039]
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3610 [D loss: 0.682616, acc.: 55.47%] [G loss: 0.755250]
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3611 [D loss: 0.676927, acc.: 56.84%] [G loss: 0.771509]
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3612 [D loss: 0.680975, acc.: 55.86%] [G loss: 0.760086]
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3613 [D loss: 0.679191, acc.: 56.64%] [G loss: 0.766137]
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3614 [D loss: 0.692932, acc.: 49.02%] [G loss: 0.734978]
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3615 [D loss: 0.708474, acc.: 45.51%] [G loss: 0.723340]
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3616 [D loss: 0.706862, acc.: 45.51%] [G loss: 0.715485]
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3617 [D loss: 0.708627, acc.: 43.95%] [G loss: 0.703000]
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3618 [D loss: 0.701038, acc.: 48.63%] [G loss: 0.715821]
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3619 [D loss: 0.697217, acc.: 47.46%] [G loss: 0.719440]
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3620 [D loss: 0.696155, acc.: 48.83%] [G loss: 0.720795]
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3621 [D loss: 0.681952, acc.: 53.91%] [G loss: 0.748859]
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3622 [D loss: 0.682607, acc.: 55.66%] [G loss: 0.745452]
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3623 [D loss: 0.685549, acc.: 55.08%] [G loss: 0.740639]
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3624 [D loss: 0.683284, acc.: 55.66%] [G loss: 0.744737]
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3625 [D loss: 0.688296, acc.: 52.93%] [G loss: 0.758817]
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3626 [D loss: 0.684832, acc.: 55.27%] [G loss: 0.749211]
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3627 [D loss: 0.688060, acc.: 53.32%] [G loss: 0.731093]
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3628 [D loss: 0.688797, acc.: 52.54%] [G loss: 0.739240]
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3629 [D loss: 0.698103, acc.: 50.59%] [G loss: 0.728922]
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3630 [D loss: 0.695259, acc.: 48.44%] [G loss: 0.732030]
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3631 [D loss: 0.699294, acc.: 49.02%] [G loss: 0.725384]
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3632 [D loss: 0.692611, acc.: 51.76%] [G loss: 0.723552]
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3633 [D loss: 0.698903, acc.: 48.83%] [G loss: 0.736758]
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3634 [D loss: 0.685361, acc.: 53.71%] [G loss: 0.746794]
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3635 [D loss: 0.681524, acc.: 58.01%] [G loss: 0.757618]
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3636 [D loss: 0.691855, acc.: 53.71%] [G loss: 0.762865]
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3637 [D loss: 0.681801, acc.: 55.08%] [G loss: 0.764720]
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3638 [D loss: 0.686037, acc.: 56.45%] [G loss: 0.744364]
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3639 [D loss: 0.680110, acc.: 58.40%] [G loss: 0.761496]
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3640 [D loss: 0.686313, acc.: 53.32%] [G loss: 0.731913]
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3641 [D loss: 0.698977, acc.: 47.07%] [G loss: 0.724994]
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3642 [D loss: 0.689723, acc.: 52.93%] [G loss: 0.722587]
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3643 [D loss: 0.696215, acc.: 51.95%] [G loss: 0.719618]
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3644 [D loss: 0.712770, acc.: 43.16%] [G loss: 0.724295]
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3645 [D loss: 0.697456, acc.: 49.80%] [G loss: 0.741109]
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3646 [D loss: 0.701858, acc.: 49.41%] [G loss: 0.747595]
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3647 [D loss: 0.687902, acc.: 50.78%] [G loss: 0.752043]
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3648 [D loss: 0.693610, acc.: 44.53%] [G loss: 0.747942]
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3649 [D loss: 0.699063, acc.: 47.46%] [G loss: 0.740566]
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3650 [D loss: 0.685644, acc.: 58.20%] [G loss: 0.742702]
1/1 [==============================] - 0s 38ms/step
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3651 [D loss: 0.674862, acc.: 62.11%] [G loss: 0.757661]
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3652 [D loss: 0.675657, acc.: 60.94%] [G loss: 0.739466]
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3653 [D loss: 0.676040, acc.: 59.38%] [G loss: 0.736310]
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3654 [D loss: 0.686035, acc.: 54.69%] [G loss: 0.708978]
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3655 [D loss: 0.699124, acc.: 48.05%] [G loss: 0.699095]
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3656 [D loss: 0.702303, acc.: 48.63%] [G loss: 0.712041]
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3657 [D loss: 0.691875, acc.: 49.80%] [G loss: 0.745652]
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3658 [D loss: 0.690664, acc.: 52.93%] [G loss: 0.789194]
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3659 [D loss: 0.687450, acc.: 52.54%] [G loss: 0.785852]
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3660 [D loss: 0.699576, acc.: 47.07%] [G loss: 0.760808]
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3661 [D loss: 0.691994, acc.: 52.15%] [G loss: 0.748973]
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3662 [D loss: 0.693779, acc.: 53.12%] [G loss: 0.750288]
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3663 [D loss: 0.682046, acc.: 57.62%] [G loss: 0.754831]
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3664 [D loss: 0.680856, acc.: 57.62%] [G loss: 0.756812]
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3665 [D loss: 0.681116, acc.: 55.66%] [G loss: 0.749927]
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3666 [D loss: 0.691885, acc.: 49.22%] [G loss: 0.712737]
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3667 [D loss: 0.707627, acc.: 47.46%] [G loss: 0.695619]
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3668 [D loss: 0.702516, acc.: 47.27%] [G loss: 0.713378]
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3669 [D loss: 0.690470, acc.: 50.00%] [G loss: 0.748654]
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3670 [D loss: 0.693261, acc.: 49.22%] [G loss: 0.767435]
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3671 [D loss: 0.693134, acc.: 48.44%] [G loss: 0.776599]
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3672 [D loss: 0.694488, acc.: 50.00%] [G loss: 0.764157]
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3673 [D loss: 0.694967, acc.: 52.15%] [G loss: 0.753142]
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3674 [D loss: 0.689136, acc.: 53.52%] [G loss: 0.741742]
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3675 [D loss: 0.689797, acc.: 54.10%] [G loss: 0.736826]
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3676 [D loss: 0.691064, acc.: 50.98%] [G loss: 0.734642]
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3677 [D loss: 0.694003, acc.: 52.15%] [G loss: 0.720616]
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3678 [D loss: 0.681945, acc.: 55.66%] [G loss: 0.718431]
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3679 [D loss: 0.688693, acc.: 52.34%] [G loss: 0.720237]
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3680 [D loss: 0.690123, acc.: 53.32%] [G loss: 0.723579]
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3681 [D loss: 0.694683, acc.: 53.32%] [G loss: 0.738029]
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3682 [D loss: 0.690207, acc.: 50.78%] [G loss: 0.735138]
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3683 [D loss: 0.688176, acc.: 52.15%] [G loss: 0.752239]
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3684 [D loss: 0.692372, acc.: 52.15%] [G loss: 0.753768]
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3685 [D loss: 0.700278, acc.: 49.22%] [G loss: 0.751048]
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3686 [D loss: 0.696295, acc.: 50.00%] [G loss: 0.748231]
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3687 [D loss: 0.702531, acc.: 46.48%] [G loss: 0.734072]
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3688 [D loss: 0.703731, acc.: 48.63%] [G loss: 0.742826]
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3689 [D loss: 0.702866, acc.: 47.46%] [G loss: 0.718318]
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3690 [D loss: 0.694361, acc.: 49.41%] [G loss: 0.735512]
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3691 [D loss: 0.680084, acc.: 57.62%] [G loss: 0.745370]
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3692 [D loss: 0.689429, acc.: 54.88%] [G loss: 0.739144]
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3693 [D loss: 0.684068, acc.: 57.03%] [G loss: 0.732301]
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3694 [D loss: 0.686337, acc.: 55.27%] [G loss: 0.742172]
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3695 [D loss: 0.688065, acc.: 54.49%] [G loss: 0.733344]
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3696 [D loss: 0.690601, acc.: 52.54%] [G loss: 0.728210]
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3697 [D loss: 0.688799, acc.: 53.91%] [G loss: 0.729264]
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3698 [D loss: 0.705236, acc.: 46.68%] [G loss: 0.727799]
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3699 [D loss: 0.701539, acc.: 48.44%] [G loss: 0.723352]
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3700 [D loss: 0.695539, acc.: 47.85%] [G loss: 0.733841]
1/1 [==============================] - 0s 26ms/step
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3701 [D loss: 0.696262, acc.: 49.61%] [G loss: 0.732672]
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3702 [D loss: 0.691451, acc.: 53.12%] [G loss: 0.738471]
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3703 [D loss: 0.684166, acc.: 54.69%] [G loss: 0.743507]
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3704 [D loss: 0.691907, acc.: 52.73%] [G loss: 0.746450]
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3705 [D loss: 0.695110, acc.: 54.30%] [G loss: 0.747417]
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3706 [D loss: 0.687935, acc.: 53.12%] [G loss: 0.734690]
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3707 [D loss: 0.696097, acc.: 52.73%] [G loss: 0.727348]
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3708 [D loss: 0.690291, acc.: 55.47%] [G loss: 0.725477]
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3709 [D loss: 0.688557, acc.: 53.32%] [G loss: 0.725298]
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3710 [D loss: 0.690316, acc.: 53.71%] [G loss: 0.748033]
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3711 [D loss: 0.692461, acc.: 50.98%] [G loss: 0.739277]
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3712 [D loss: 0.683206, acc.: 55.47%] [G loss: 0.751739]
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3713 [D loss: 0.699769, acc.: 47.46%] [G loss: 0.734723]
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3714 [D loss: 0.687655, acc.: 52.15%] [G loss: 0.737325]
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3715 [D loss: 0.688983, acc.: 52.73%] [G loss: 0.728607]
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3716 [D loss: 0.693463, acc.: 53.12%] [G loss: 0.734957]
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3717 [D loss: 0.690746, acc.: 51.17%] [G loss: 0.751491]
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3718 [D loss: 0.686135, acc.: 52.54%] [G loss: 0.764614]
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3719 [D loss: 0.678110, acc.: 57.23%] [G loss: 0.782539]
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3720 [D loss: 0.687034, acc.: 55.66%] [G loss: 0.755567]
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3721 [D loss: 0.689652, acc.: 57.42%] [G loss: 0.755377]
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3722 [D loss: 0.689369, acc.: 55.66%] [G loss: 0.753442]
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3723 [D loss: 0.679670, acc.: 55.47%] [G loss: 0.762323]
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3724 [D loss: 0.687515, acc.: 55.08%] [G loss: 0.750073]
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3725 [D loss: 0.687724, acc.: 56.64%] [G loss: 0.744459]
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3726 [D loss: 0.698765, acc.: 49.02%] [G loss: 0.702262]
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3727 [D loss: 0.700910, acc.: 46.88%] [G loss: 0.705443]
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3728 [D loss: 0.715646, acc.: 47.07%] [G loss: 0.708151]
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3729 [D loss: 0.693148, acc.: 52.15%] [G loss: 0.741896]
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3730 [D loss: 0.687115, acc.: 55.47%] [G loss: 0.784265]
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3731 [D loss: 0.681983, acc.: 60.35%] [G loss: 0.782461]
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3732 [D loss: 0.676105, acc.: 57.81%] [G loss: 0.782711]
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3733 [D loss: 0.690240, acc.: 54.30%] [G loss: 0.770500]
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3734 [D loss: 0.676446, acc.: 62.11%] [G loss: 0.769042]
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3735 [D loss: 0.685071, acc.: 55.08%] [G loss: 0.743066]
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3736 [D loss: 0.697898, acc.: 50.98%] [G loss: 0.730685]
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3737 [D loss: 0.708069, acc.: 48.63%] [G loss: 0.689827]
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3738 [D loss: 0.710799, acc.: 44.14%] [G loss: 0.697115]
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3739 [D loss: 0.702664, acc.: 46.48%] [G loss: 0.721099]
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3740 [D loss: 0.699604, acc.: 47.66%] [G loss: 0.749284]
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3741 [D loss: 0.688805, acc.: 52.15%] [G loss: 0.792624]
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3742 [D loss: 0.689958, acc.: 50.39%] [G loss: 0.773985]
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3743 [D loss: 0.690943, acc.: 52.54%] [G loss: 0.767154]
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3744 [D loss: 0.687092, acc.: 54.10%] [G loss: 0.755052]
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3745 [D loss: 0.682463, acc.: 54.88%] [G loss: 0.751196]
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3746 [D loss: 0.684787, acc.: 54.69%] [G loss: 0.752461]
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3747 [D loss: 0.684415, acc.: 56.64%] [G loss: 0.754775]
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3748 [D loss: 0.680659, acc.: 54.69%] [G loss: 0.736367]
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3749 [D loss: 0.704870, acc.: 48.05%] [G loss: 0.700149]
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3750 [D loss: 0.705454, acc.: 51.37%] [G loss: 0.702600]
1/1 [==============================] - 0s 26ms/step
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3751 [D loss: 0.708503, acc.: 47.66%] [G loss: 0.732620]
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3752 [D loss: 0.685061, acc.: 53.71%] [G loss: 0.780375]
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3753 [D loss: 0.693433, acc.: 51.37%] [G loss: 0.777449]
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3754 [D loss: 0.694205, acc.: 53.52%] [G loss: 0.763014]
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3755 [D loss: 0.695772, acc.: 52.34%] [G loss: 0.749708]
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3756 [D loss: 0.699289, acc.: 50.59%] [G loss: 0.732464]
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3757 [D loss: 0.690352, acc.: 53.71%] [G loss: 0.752808]
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3758 [D loss: 0.682265, acc.: 55.47%] [G loss: 0.728965]
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3759 [D loss: 0.690118, acc.: 55.86%] [G loss: 0.718778]
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3760 [D loss: 0.682771, acc.: 54.88%] [G loss: 0.716437]
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3761 [D loss: 0.691045, acc.: 51.76%] [G loss: 0.711667]
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3762 [D loss: 0.690709, acc.: 50.00%] [G loss: 0.713592]
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3763 [D loss: 0.699154, acc.: 51.95%] [G loss: 0.723192]
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3764 [D loss: 0.693111, acc.: 52.54%] [G loss: 0.750536]
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3765 [D loss: 0.684685, acc.: 53.32%] [G loss: 0.779353]
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3766 [D loss: 0.684931, acc.: 58.59%] [G loss: 0.785058]
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3767 [D loss: 0.696835, acc.: 49.41%] [G loss: 0.752647]
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3768 [D loss: 0.701768, acc.: 47.85%] [G loss: 0.737411]
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3769 [D loss: 0.686783, acc.: 54.10%] [G loss: 0.738623]
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3770 [D loss: 0.690932, acc.: 52.34%] [G loss: 0.741653]
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3771 [D loss: 0.683552, acc.: 56.05%] [G loss: 0.745842]
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3772 [D loss: 0.680368, acc.: 56.64%] [G loss: 0.741698]
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3773 [D loss: 0.697461, acc.: 50.59%] [G loss: 0.736571]
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3774 [D loss: 0.691111, acc.: 53.71%] [G loss: 0.726987]
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3775 [D loss: 0.693065, acc.: 50.78%] [G loss: 0.736497]
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3776 [D loss: 0.700888, acc.: 50.20%] [G loss: 0.752727]
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3777 [D loss: 0.687277, acc.: 55.66%] [G loss: 0.763725]
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3778 [D loss: 0.683622, acc.: 54.10%] [G loss: 0.769657]
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3779 [D loss: 0.691125, acc.: 52.73%] [G loss: 0.746921]
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3780 [D loss: 0.697981, acc.: 49.22%] [G loss: 0.742115]
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3781 [D loss: 0.681927, acc.: 55.66%] [G loss: 0.738258]
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3782 [D loss: 0.687852, acc.: 57.03%] [G loss: 0.732745]
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3783 [D loss: 0.687393, acc.: 54.69%] [G loss: 0.733345]
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3784 [D loss: 0.684915, acc.: 55.86%] [G loss: 0.728577]
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3785 [D loss: 0.688288, acc.: 53.52%] [G loss: 0.721519]
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3786 [D loss: 0.698685, acc.: 49.22%] [G loss: 0.717079]
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3787 [D loss: 0.691001, acc.: 54.30%] [G loss: 0.741786]
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3788 [D loss: 0.694783, acc.: 51.95%] [G loss: 0.765855]
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3789 [D loss: 0.690446, acc.: 53.12%] [G loss: 0.752826]
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3790 [D loss: 0.695002, acc.: 50.20%] [G loss: 0.755458]
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3791 [D loss: 0.687050, acc.: 51.17%] [G loss: 0.747176]
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3792 [D loss: 0.693917, acc.: 50.78%] [G loss: 0.737533]
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3793 [D loss: 0.688944, acc.: 53.12%] [G loss: 0.741011]
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3794 [D loss: 0.686395, acc.: 54.88%] [G loss: 0.746785]
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3795 [D loss: 0.691784, acc.: 50.78%] [G loss: 0.724690]
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3796 [D loss: 0.690378, acc.: 51.76%] [G loss: 0.708029]
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3797 [D loss: 0.699172, acc.: 50.20%] [G loss: 0.692831]
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3798 [D loss: 0.710761, acc.: 43.55%] [G loss: 0.703577]
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3799 [D loss: 0.690912, acc.: 49.61%] [G loss: 0.730739]
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3800 [D loss: 0.692489, acc.: 53.52%] [G loss: 0.744495]
1/1 [==============================] - 0s 26ms/step
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3801 [D loss: 0.693955, acc.: 51.95%] [G loss: 0.757137]
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3802 [D loss: 0.686624, acc.: 55.66%] [G loss: 0.768322]
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3803 [D loss: 0.694251, acc.: 51.95%] [G loss: 0.764621]
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3804 [D loss: 0.690549, acc.: 53.91%] [G loss: 0.758922]
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3805 [D loss: 0.692105, acc.: 53.52%] [G loss: 0.749924]
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3806 [D loss: 0.692021, acc.: 53.52%] [G loss: 0.741907]
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3807 [D loss: 0.696394, acc.: 50.39%] [G loss: 0.727570]
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3808 [D loss: 0.688128, acc.: 55.66%] [G loss: 0.721133]
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3809 [D loss: 0.706414, acc.: 44.53%] [G loss: 0.716717]
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3810 [D loss: 0.691767, acc.: 50.78%] [G loss: 0.725556]
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3811 [D loss: 0.695634, acc.: 48.63%] [G loss: 0.736775]
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3812 [D loss: 0.686973, acc.: 55.08%] [G loss: 0.758229]
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3813 [D loss: 0.688042, acc.: 51.17%] [G loss: 0.773841]
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3814 [D loss: 0.682784, acc.: 55.47%] [G loss: 0.753247]
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3815 [D loss: 0.688868, acc.: 50.78%] [G loss: 0.725196]
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3816 [D loss: 0.695743, acc.: 49.22%] [G loss: 0.725657]
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3817 [D loss: 0.699030, acc.: 47.85%] [G loss: 0.722511]
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3818 [D loss: 0.702509, acc.: 47.46%] [G loss: 0.720314]
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3819 [D loss: 0.700978, acc.: 49.22%] [G loss: 0.699719]
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3820 [D loss: 0.699240, acc.: 50.00%] [G loss: 0.698399]
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3821 [D loss: 0.694758, acc.: 51.95%] [G loss: 0.702284]
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3822 [D loss: 0.692354, acc.: 52.15%] [G loss: 0.727981]
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3823 [D loss: 0.692151, acc.: 52.34%] [G loss: 0.728884]
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3824 [D loss: 0.682245, acc.: 56.25%] [G loss: 0.761896]
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3825 [D loss: 0.685374, acc.: 55.86%] [G loss: 0.760327]
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3826 [D loss: 0.686932, acc.: 55.27%] [G loss: 0.750428]
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3827 [D loss: 0.688153, acc.: 52.73%] [G loss: 0.737609]
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3828 [D loss: 0.693948, acc.: 50.20%] [G loss: 0.737448]
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3829 [D loss: 0.698112, acc.: 49.61%] [G loss: 0.725896]
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3830 [D loss: 0.690373, acc.: 53.12%] [G loss: 0.720598]
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3831 [D loss: 0.697054, acc.: 49.22%] [G loss: 0.714726]
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3832 [D loss: 0.699471, acc.: 47.07%] [G loss: 0.714270]
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3833 [D loss: 0.694184, acc.: 51.95%] [G loss: 0.716416]
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3834 [D loss: 0.687841, acc.: 55.08%] [G loss: 0.730837]
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3835 [D loss: 0.695257, acc.: 52.93%] [G loss: 0.750423]
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3836 [D loss: 0.688931, acc.: 53.71%] [G loss: 0.754058]
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3837 [D loss: 0.693896, acc.: 49.22%] [G loss: 0.744082]
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3838 [D loss: 0.696981, acc.: 50.78%] [G loss: 0.730077]
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3839 [D loss: 0.696813, acc.: 51.37%] [G loss: 0.729286]
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3840 [D loss: 0.690271, acc.: 54.49%] [G loss: 0.730311]
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3841 [D loss: 0.691105, acc.: 52.15%] [G loss: 0.726322]
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3842 [D loss: 0.687111, acc.: 55.66%] [G loss: 0.729705]
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3843 [D loss: 0.680367, acc.: 54.30%] [G loss: 0.730893]
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3844 [D loss: 0.684344, acc.: 55.66%] [G loss: 0.723606]
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3845 [D loss: 0.685935, acc.: 53.32%] [G loss: 0.734046]
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3846 [D loss: 0.688097, acc.: 52.73%] [G loss: 0.736495]
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3847 [D loss: 0.696139, acc.: 50.59%] [G loss: 0.749299]
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3848 [D loss: 0.693604, acc.: 51.37%] [G loss: 0.732368]
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3849 [D loss: 0.697345, acc.: 47.46%] [G loss: 0.734221]
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3850 [D loss: 0.703137, acc.: 46.68%] [G loss: 0.740240]
1/1 [==============================] - 0s 42ms/step
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3851 [D loss: 0.692050, acc.: 53.71%] [G loss: 0.740828]
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3852 [D loss: 0.683193, acc.: 56.64%] [G loss: 0.750509]
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3853 [D loss: 0.688418, acc.: 55.08%] [G loss: 0.734355]
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3854 [D loss: 0.688097, acc.: 52.54%] [G loss: 0.748045]
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3855 [D loss: 0.686673, acc.: 53.52%] [G loss: 0.746026]
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3856 [D loss: 0.686637, acc.: 51.95%] [G loss: 0.747829]
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3857 [D loss: 0.694211, acc.: 53.52%] [G loss: 0.750770]
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3858 [D loss: 0.685708, acc.: 55.66%] [G loss: 0.752133]
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3859 [D loss: 0.695112, acc.: 49.61%] [G loss: 0.732855]
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3860 [D loss: 0.693126, acc.: 53.71%] [G loss: 0.737452]
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3861 [D loss: 0.685897, acc.: 55.47%] [G loss: 0.758119]
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3862 [D loss: 0.688692, acc.: 56.64%] [G loss: 0.744913]
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3863 [D loss: 0.688696, acc.: 53.52%] [G loss: 0.734734]
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3864 [D loss: 0.689534, acc.: 51.95%] [G loss: 0.732917]
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3865 [D loss: 0.693391, acc.: 51.17%] [G loss: 0.731914]
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3866 [D loss: 0.688760, acc.: 52.73%] [G loss: 0.723468]
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3867 [D loss: 0.697532, acc.: 50.59%] [G loss: 0.725675]
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3868 [D loss: 0.699043, acc.: 49.22%] [G loss: 0.734580]
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3869 [D loss: 0.693470, acc.: 50.98%] [G loss: 0.744968]
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3870 [D loss: 0.695661, acc.: 50.59%] [G loss: 0.736866]
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3871 [D loss: 0.692236, acc.: 54.49%] [G loss: 0.744184]
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3872 [D loss: 0.691728, acc.: 55.27%] [G loss: 0.734283]
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3873 [D loss: 0.686243, acc.: 51.17%] [G loss: 0.726500]
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3874 [D loss: 0.689200, acc.: 50.20%] [G loss: 0.726161]
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3875 [D loss: 0.684193, acc.: 53.52%] [G loss: 0.728427]
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3876 [D loss: 0.686412, acc.: 52.15%] [G loss: 0.721891]
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3877 [D loss: 0.692021, acc.: 48.63%] [G loss: 0.718511]
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3878 [D loss: 0.687855, acc.: 51.76%] [G loss: 0.705040]
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3879 [D loss: 0.699475, acc.: 52.15%] [G loss: 0.710717]
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3880 [D loss: 0.693847, acc.: 49.61%] [G loss: 0.736657]
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3881 [D loss: 0.695437, acc.: 50.59%] [G loss: 0.752227]
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3882 [D loss: 0.690336, acc.: 50.20%] [G loss: 0.739453]
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3883 [D loss: 0.677363, acc.: 54.10%] [G loss: 0.760908]
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3884 [D loss: 0.682976, acc.: 53.91%] [G loss: 0.767104]
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3885 [D loss: 0.689695, acc.: 53.71%] [G loss: 0.743599]
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3886 [D loss: 0.688897, acc.: 53.52%] [G loss: 0.737362]
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3887 [D loss: 0.690003, acc.: 54.10%] [G loss: 0.730858]
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3888 [D loss: 0.696271, acc.: 51.17%] [G loss: 0.722149]
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3889 [D loss: 0.699590, acc.: 49.22%] [G loss: 0.716694]
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3890 [D loss: 0.694388, acc.: 51.37%] [G loss: 0.720843]
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3891 [D loss: 0.702323, acc.: 49.80%] [G loss: 0.727535]
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3892 [D loss: 0.689107, acc.: 51.56%] [G loss: 0.744660]
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3893 [D loss: 0.690369, acc.: 53.12%] [G loss: 0.750477]
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3894 [D loss: 0.683173, acc.: 55.86%] [G loss: 0.758939]
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3895 [D loss: 0.693238, acc.: 52.34%] [G loss: 0.752046]
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3896 [D loss: 0.697113, acc.: 50.20%] [G loss: 0.747615]
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3897 [D loss: 0.684723, acc.: 57.03%] [G loss: 0.736728]
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3898 [D loss: 0.696049, acc.: 46.68%] [G loss: 0.730193]
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3899 [D loss: 0.685964, acc.: 54.88%] [G loss: 0.723575]
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3900 [D loss: 0.688918, acc.: 54.69%] [G loss: 0.715206]
1/1 [==============================] - 0s 30ms/step
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3901 [D loss: 0.697844, acc.: 49.02%] [G loss: 0.704381]
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3902 [D loss: 0.694524, acc.: 50.78%] [G loss: 0.700404]
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3903 [D loss: 0.692031, acc.: 50.39%] [G loss: 0.719961]
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3904 [D loss: 0.689022, acc.: 52.34%] [G loss: 0.733628]
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3905 [D loss: 0.691098, acc.: 52.34%] [G loss: 0.764557]
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3906 [D loss: 0.686802, acc.: 54.10%] [G loss: 0.758071]
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3907 [D loss: 0.695490, acc.: 50.20%] [G loss: 0.752114]
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3908 [D loss: 0.692993, acc.: 54.10%] [G loss: 0.744036]
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3909 [D loss: 0.691070, acc.: 50.59%] [G loss: 0.744975]
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3910 [D loss: 0.694245, acc.: 47.46%] [G loss: 0.737258]
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3911 [D loss: 0.687176, acc.: 51.56%] [G loss: 0.740099]
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3912 [D loss: 0.686556, acc.: 52.73%] [G loss: 0.733423]
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3913 [D loss: 0.694856, acc.: 49.41%] [G loss: 0.732574]
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3914 [D loss: 0.687101, acc.: 54.49%] [G loss: 0.725541]
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3915 [D loss: 0.689949, acc.: 51.37%] [G loss: 0.727317]
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3916 [D loss: 0.692089, acc.: 52.34%] [G loss: 0.744347]
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3917 [D loss: 0.686522, acc.: 54.49%] [G loss: 0.740880]
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3918 [D loss: 0.700579, acc.: 49.22%] [G loss: 0.730849]
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3919 [D loss: 0.693576, acc.: 49.41%] [G loss: 0.729293]
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3920 [D loss: 0.694241, acc.: 49.80%] [G loss: 0.710817]
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3921 [D loss: 0.697514, acc.: 50.59%] [G loss: 0.718209]
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3922 [D loss: 0.694850, acc.: 50.20%] [G loss: 0.724914]
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3923 [D loss: 0.697752, acc.: 48.24%] [G loss: 0.714043]
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3924 [D loss: 0.691590, acc.: 49.80%] [G loss: 0.722308]
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3925 [D loss: 0.690042, acc.: 52.73%] [G loss: 0.717869]
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3926 [D loss: 0.699623, acc.: 48.05%] [G loss: 0.733364]
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3927 [D loss: 0.690275, acc.: 52.54%] [G loss: 0.737830]
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3928 [D loss: 0.688203, acc.: 55.08%] [G loss: 0.737306]
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3929 [D loss: 0.694206, acc.: 53.52%] [G loss: 0.751446]
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3930 [D loss: 0.695115, acc.: 51.37%] [G loss: 0.748481]
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3931 [D loss: 0.687335, acc.: 54.88%] [G loss: 0.741261]
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3932 [D loss: 0.685024, acc.: 51.76%] [G loss: 0.737034]
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3933 [D loss: 0.696089, acc.: 51.17%] [G loss: 0.740372]
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3934 [D loss: 0.690575, acc.: 54.30%] [G loss: 0.722186]
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3935 [D loss: 0.689671, acc.: 52.34%] [G loss: 0.728379]
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3936 [D loss: 0.695853, acc.: 52.34%] [G loss: 0.721249]
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3937 [D loss: 0.697871, acc.: 49.22%] [G loss: 0.704660]
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3938 [D loss: 0.692179, acc.: 53.52%] [G loss: 0.727822]
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3939 [D loss: 0.693286, acc.: 50.59%] [G loss: 0.715481]
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3940 [D loss: 0.684861, acc.: 55.47%] [G loss: 0.732144]
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3941 [D loss: 0.693275, acc.: 52.34%] [G loss: 0.748761]
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3942 [D loss: 0.689505, acc.: 50.78%] [G loss: 0.746136]
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3943 [D loss: 0.692425, acc.: 51.17%] [G loss: 0.758109]
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3944 [D loss: 0.697437, acc.: 48.05%] [G loss: 0.750125]
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3945 [D loss: 0.688856, acc.: 53.12%] [G loss: 0.746799]
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3946 [D loss: 0.680553, acc.: 56.25%] [G loss: 0.736896]
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3947 [D loss: 0.685392, acc.: 55.66%] [G loss: 0.748364]
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3948 [D loss: 0.687198, acc.: 55.27%] [G loss: 0.740071]
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3949 [D loss: 0.691833, acc.: 50.78%] [G loss: 0.732239]
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3950 [D loss: 0.699221, acc.: 46.09%] [G loss: 0.720172]
1/1 [==============================] - 0s 24ms/step
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3951 [D loss: 0.703507, acc.: 47.27%] [G loss: 0.720373]
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3952 [D loss: 0.692546, acc.: 50.39%] [G loss: 0.734883]
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3953 [D loss: 0.689963, acc.: 51.76%] [G loss: 0.741110]
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3954 [D loss: 0.692708, acc.: 50.78%] [G loss: 0.748534]
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3955 [D loss: 0.692552, acc.: 51.17%] [G loss: 0.747984]
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3956 [D loss: 0.694167, acc.: 50.39%] [G loss: 0.729572]
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3957 [D loss: 0.696970, acc.: 51.95%] [G loss: 0.733007]
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3958 [D loss: 0.693024, acc.: 52.93%] [G loss: 0.730380]
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3959 [D loss: 0.692396, acc.: 51.37%] [G loss: 0.719911]
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3960 [D loss: 0.694660, acc.: 52.73%] [G loss: 0.715596]
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3961 [D loss: 0.691238, acc.: 49.61%] [G loss: 0.723583]
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3962 [D loss: 0.694213, acc.: 50.59%] [G loss: 0.708850]
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3963 [D loss: 0.701610, acc.: 46.09%] [G loss: 0.717626]
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3964 [D loss: 0.694430, acc.: 46.09%] [G loss: 0.722581]
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3965 [D loss: 0.694619, acc.: 48.05%] [G loss: 0.740936]
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3966 [D loss: 0.697306, acc.: 49.61%] [G loss: 0.742195]
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3967 [D loss: 0.686950, acc.: 52.15%] [G loss: 0.748426]
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3968 [D loss: 0.697580, acc.: 47.85%] [G loss: 0.744850]
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3969 [D loss: 0.698096, acc.: 48.24%] [G loss: 0.730666]
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3970 [D loss: 0.694873, acc.: 49.41%] [G loss: 0.737518]
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3971 [D loss: 0.693584, acc.: 51.76%] [G loss: 0.730633]
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3972 [D loss: 0.696992, acc.: 48.05%] [G loss: 0.726401]
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3973 [D loss: 0.691027, acc.: 49.02%] [G loss: 0.718723]
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3974 [D loss: 0.686041, acc.: 56.64%] [G loss: 0.726007]
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3975 [D loss: 0.694630, acc.: 50.78%] [G loss: 0.729593]
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3976 [D loss: 0.694594, acc.: 50.59%] [G loss: 0.723382]
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3977 [D loss: 0.691676, acc.: 54.30%] [G loss: 0.753281]
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3978 [D loss: 0.691684, acc.: 51.37%] [G loss: 0.731751]
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3979 [D loss: 0.692553, acc.: 50.78%] [G loss: 0.737091]
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3980 [D loss: 0.698872, acc.: 49.61%] [G loss: 0.731818]
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3981 [D loss: 0.701451, acc.: 46.68%] [G loss: 0.726151]
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3982 [D loss: 0.699886, acc.: 51.56%] [G loss: 0.721319]
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3983 [D loss: 0.697389, acc.: 50.78%] [G loss: 0.720336]
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3984 [D loss: 0.684429, acc.: 55.08%] [G loss: 0.721107]
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3985 [D loss: 0.682950, acc.: 57.03%] [G loss: 0.716468]
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3986 [D loss: 0.704458, acc.: 47.85%] [G loss: 0.712151]
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3987 [D loss: 0.695710, acc.: 50.78%] [G loss: 0.731051]
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3988 [D loss: 0.688665, acc.: 52.93%] [G loss: 0.730535]
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3989 [D loss: 0.687731, acc.: 57.23%] [G loss: 0.756821]
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3990 [D loss: 0.694769, acc.: 52.93%] [G loss: 0.747631]
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3991 [D loss: 0.697009, acc.: 47.85%] [G loss: 0.738073]
8/8 [==============================] - 0s 4ms/step
3992 [D loss: 0.691852, acc.: 52.73%] [G loss: 0.733559]
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3993 [D loss: 0.688799, acc.: 54.30%] [G loss: 0.750849]
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3994 [D loss: 0.690019, acc.: 49.80%] [G loss: 0.740938]
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3995 [D loss: 0.691737, acc.: 51.56%] [G loss: 0.734478]
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3996 [D loss: 0.677882, acc.: 58.40%] [G loss: 0.735742]
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3997 [D loss: 0.692640, acc.: 52.54%] [G loss: 0.733841]
8/8 [==============================] - 0s 4ms/step
3998 [D loss: 0.690654, acc.: 52.73%] [G loss: 0.733929]
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3999 [D loss: 0.694458, acc.: 52.34%] [G loss: 0.719384]
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4000 [D loss: 0.690345, acc.: 54.88%] [G loss: 0.713602]
1/1 [==============================] - 0s 26ms/step
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4001 [D loss: 0.695090, acc.: 52.15%] [G loss: 0.721971]
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4002 [D loss: 0.698051, acc.: 48.63%] [G loss: 0.710370]
8/8 [==============================] - 0s 4ms/step
4003 [D loss: 0.693195, acc.: 51.37%] [G loss: 0.721436]
8/8 [==============================] - 0s 4ms/step
4004 [D loss: 0.705784, acc.: 47.85%] [G loss: 0.723258]
8/8 [==============================] - 0s 4ms/step
4005 [D loss: 0.690605, acc.: 52.54%] [G loss: 0.723640]
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4006 [D loss: 0.692679, acc.: 52.15%] [G loss: 0.732401]
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4007 [D loss: 0.687635, acc.: 53.32%] [G loss: 0.736665]
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4008 [D loss: 0.692066, acc.: 52.73%] [G loss: 0.742065]
8/8 [==============================] - 0s 4ms/step
4009 [D loss: 0.689753, acc.: 49.80%] [G loss: 0.751074]
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4010 [D loss: 0.698495, acc.: 48.24%] [G loss: 0.739539]
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4011 [D loss: 0.690190, acc.: 52.34%] [G loss: 0.730420]
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4012 [D loss: 0.687484, acc.: 53.12%] [G loss: 0.733304]
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4013 [D loss: 0.683644, acc.: 56.84%] [G loss: 0.729744]
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4014 [D loss: 0.690853, acc.: 54.10%] [G loss: 0.731994]
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4015 [D loss: 0.699158, acc.: 50.78%] [G loss: 0.706723]
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4016 [D loss: 0.696723, acc.: 49.41%] [G loss: 0.714873]
8/8 [==============================] - 0s 4ms/step
4017 [D loss: 0.691226, acc.: 51.37%] [G loss: 0.719266]
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4018 [D loss: 0.694914, acc.: 51.17%] [G loss: 0.738996]
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4019 [D loss: 0.694116, acc.: 49.61%] [G loss: 0.751087]
8/8 [==============================] - 0s 4ms/step
4020 [D loss: 0.690216, acc.: 52.73%] [G loss: 0.751065]
8/8 [==============================] - 0s 4ms/step
4021 [D loss: 0.699090, acc.: 47.07%] [G loss: 0.740161]
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4022 [D loss: 0.698808, acc.: 47.46%] [G loss: 0.735020]
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4023 [D loss: 0.697195, acc.: 49.61%] [G loss: 0.723496]
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4024 [D loss: 0.692973, acc.: 50.00%] [G loss: 0.726818]
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4025 [D loss: 0.684231, acc.: 55.86%] [G loss: 0.720318]
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4026 [D loss: 0.694857, acc.: 50.78%] [G loss: 0.714980]
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4027 [D loss: 0.690740, acc.: 51.17%] [G loss: 0.710540]
8/8 [==============================] - 0s 4ms/step
4028 [D loss: 0.694417, acc.: 48.24%] [G loss: 0.711976]
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4029 [D loss: 0.692727, acc.: 52.34%] [G loss: 0.721917]
8/8 [==============================] - 0s 5ms/step
4030 [D loss: 0.690521, acc.: 52.73%] [G loss: 0.740943]
8/8 [==============================] - 0s 4ms/step
4031 [D loss: 0.694611, acc.: 50.39%] [G loss: 0.734882]
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4032 [D loss: 0.698633, acc.: 47.46%] [G loss: 0.747488]
8/8 [==============================] - 0s 4ms/step
4033 [D loss: 0.698953, acc.: 49.41%] [G loss: 0.737053]
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4034 [D loss: 0.695533, acc.: 50.78%] [G loss: 0.732418]
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4035 [D loss: 0.688454, acc.: 51.95%] [G loss: 0.730119]
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4036 [D loss: 0.689314, acc.: 54.10%] [G loss: 0.718999]
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4037 [D loss: 0.693466, acc.: 51.76%] [G loss: 0.715171]
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4038 [D loss: 0.692674, acc.: 52.54%] [G loss: 0.709571]
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4039 [D loss: 0.692902, acc.: 51.37%] [G loss: 0.728941]
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4040 [D loss: 0.694725, acc.: 50.00%] [G loss: 0.721984]
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4041 [D loss: 0.694277, acc.: 49.02%] [G loss: 0.735267]
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4042 [D loss: 0.690655, acc.: 54.10%] [G loss: 0.732312]
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4043 [D loss: 0.695133, acc.: 47.66%] [G loss: 0.734425]
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4044 [D loss: 0.692470, acc.: 49.80%] [G loss: 0.732625]
8/8 [==============================] - 0s 4ms/step
4045 [D loss: 0.699049, acc.: 51.17%] [G loss: 0.745547]
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4046 [D loss: 0.692601, acc.: 50.39%] [G loss: 0.729024]
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4047 [D loss: 0.689040, acc.: 51.17%] [G loss: 0.741709]
8/8 [==============================] - 0s 4ms/step
4048 [D loss: 0.694503, acc.: 52.15%] [G loss: 0.732916]
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4049 [D loss: 0.691045, acc.: 50.20%] [G loss: 0.722188]
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4050 [D loss: 0.688053, acc.: 50.59%] [G loss: 0.719795]
1/1 [==============================] - 0s 27ms/step
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4051 [D loss: 0.691904, acc.: 50.20%] [G loss: 0.720932]
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4052 [D loss: 0.693211, acc.: 50.39%] [G loss: 0.716028]
8/8 [==============================] - 0s 4ms/step
4053 [D loss: 0.691000, acc.: 50.00%] [G loss: 0.731100]
8/8 [==============================] - 0s 4ms/step
4054 [D loss: 0.697722, acc.: 49.02%] [G loss: 0.733419]
8/8 [==============================] - 0s 4ms/step
4055 [D loss: 0.684186, acc.: 54.10%] [G loss: 0.771093]
8/8 [==============================] - 0s 4ms/step
4056 [D loss: 0.683490, acc.: 52.34%] [G loss: 0.777928]
8/8 [==============================] - 0s 4ms/step
4057 [D loss: 0.687643, acc.: 54.30%] [G loss: 0.771882]
8/8 [==============================] - 0s 4ms/step
4058 [D loss: 0.691972, acc.: 52.93%] [G loss: 0.757432]
8/8 [==============================] - 0s 4ms/step
4059 [D loss: 0.688351, acc.: 54.69%] [G loss: 0.753572]
8/8 [==============================] - 0s 4ms/step
4060 [D loss: 0.679171, acc.: 55.86%] [G loss: 0.751353]
8/8 [==============================] - 0s 4ms/step
4061 [D loss: 0.691521, acc.: 54.10%] [G loss: 0.746594]
8/8 [==============================] - 0s 4ms/step
4062 [D loss: 0.685275, acc.: 55.86%] [G loss: 0.722454]
8/8 [==============================] - 0s 4ms/step
4063 [D loss: 0.693853, acc.: 50.98%] [G loss: 0.708780]
8/8 [==============================] - 0s 4ms/step
4064 [D loss: 0.703571, acc.: 43.95%] [G loss: 0.709124]
8/8 [==============================] - 0s 4ms/step
4065 [D loss: 0.695798, acc.: 50.59%] [G loss: 0.708917]
8/8 [==============================] - 0s 4ms/step
4066 [D loss: 0.693048, acc.: 52.34%] [G loss: 0.721242]
8/8 [==============================] - 0s 4ms/step
4067 [D loss: 0.696480, acc.: 49.41%] [G loss: 0.749678]
8/8 [==============================] - 0s 4ms/step
4068 [D loss: 0.695356, acc.: 50.78%] [G loss: 0.767298]
8/8 [==============================] - 0s 4ms/step
4069 [D loss: 0.692083, acc.: 51.56%] [G loss: 0.751427]
8/8 [==============================] - 0s 4ms/step
4070 [D loss: 0.696699, acc.: 51.76%] [G loss: 0.740743]
8/8 [==============================] - 0s 4ms/step
4071 [D loss: 0.704219, acc.: 46.68%] [G loss: 0.735484]
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4072 [D loss: 0.694668, acc.: 53.52%] [G loss: 0.735508]
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4073 [D loss: 0.689712, acc.: 55.66%] [G loss: 0.746075]
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4074 [D loss: 0.685001, acc.: 55.47%] [G loss: 0.733257]
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4075 [D loss: 0.694714, acc.: 50.59%] [G loss: 0.698599]
8/8 [==============================] - 0s 4ms/step
4076 [D loss: 0.695989, acc.: 47.27%] [G loss: 0.684012]
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4077 [D loss: 0.703054, acc.: 47.07%] [G loss: 0.695279]
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4078 [D loss: 0.700340, acc.: 47.85%] [G loss: 0.724447]
8/8 [==============================] - 0s 4ms/step
4079 [D loss: 0.687535, acc.: 52.73%] [G loss: 0.760973]
8/8 [==============================] - 0s 4ms/step
4080 [D loss: 0.679858, acc.: 56.05%] [G loss: 0.805753]
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4081 [D loss: 0.695312, acc.: 51.95%] [G loss: 0.767276]
8/8 [==============================] - 0s 4ms/step
4082 [D loss: 0.695919, acc.: 50.20%] [G loss: 0.746997]
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4083 [D loss: 0.709445, acc.: 44.73%] [G loss: 0.734949]
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4084 [D loss: 0.690414, acc.: 51.56%] [G loss: 0.744134]
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4085 [D loss: 0.684181, acc.: 56.45%] [G loss: 0.735674]
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4086 [D loss: 0.676858, acc.: 55.47%] [G loss: 0.739668]
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4087 [D loss: 0.681512, acc.: 56.25%] [G loss: 0.730723]
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4088 [D loss: 0.697770, acc.: 50.20%] [G loss: 0.712815]
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4089 [D loss: 0.700824, acc.: 46.88%] [G loss: 0.687478]
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4090 [D loss: 0.702071, acc.: 47.46%] [G loss: 0.690058]
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4091 [D loss: 0.704546, acc.: 47.07%] [G loss: 0.709494]
8/8 [==============================] - 0s 4ms/step
4092 [D loss: 0.685273, acc.: 53.32%] [G loss: 0.747289]
8/8 [==============================] - 0s 4ms/step
4093 [D loss: 0.699372, acc.: 46.09%] [G loss: 0.765004]
8/8 [==============================] - 0s 4ms/step
4094 [D loss: 0.697569, acc.: 49.02%] [G loss: 0.739210]
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4095 [D loss: 0.700827, acc.: 47.07%] [G loss: 0.736310]
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4096 [D loss: 0.691472, acc.: 49.41%] [G loss: 0.736223]
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4097 [D loss: 0.686116, acc.: 52.34%] [G loss: 0.725367]
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4098 [D loss: 0.695127, acc.: 50.78%] [G loss: 0.717267]
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4099 [D loss: 0.698667, acc.: 49.80%] [G loss: 0.706461]
8/8 [==============================] - 0s 4ms/step
4100 [D loss: 0.694565, acc.: 51.76%] [G loss: 0.715936]
1/1 [==============================] - 0s 26ms/step
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4101 [D loss: 0.697900, acc.: 47.85%] [G loss: 0.713509]
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4102 [D loss: 0.694513, acc.: 52.15%] [G loss: 0.727095]
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4103 [D loss: 0.686730, acc.: 52.54%] [G loss: 0.743946]
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4104 [D loss: 0.689542, acc.: 52.54%] [G loss: 0.739982]
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4105 [D loss: 0.687065, acc.: 53.12%] [G loss: 0.738547]
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4106 [D loss: 0.689817, acc.: 51.76%] [G loss: 0.737658]
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4107 [D loss: 0.695223, acc.: 50.78%] [G loss: 0.744818]
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4108 [D loss: 0.685283, acc.: 55.86%] [G loss: 0.751151]
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4109 [D loss: 0.681033, acc.: 54.10%] [G loss: 0.741747]
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4110 [D loss: 0.679455, acc.: 58.01%] [G loss: 0.740748]
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4111 [D loss: 0.683041, acc.: 53.71%] [G loss: 0.740984]
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4112 [D loss: 0.686986, acc.: 50.59%] [G loss: 0.737443]
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4113 [D loss: 0.683945, acc.: 54.88%] [G loss: 0.729042]
8/8 [==============================] - 0s 4ms/step
4114 [D loss: 0.687485, acc.: 53.32%] [G loss: 0.714674]
8/8 [==============================] - 0s 4ms/step
4115 [D loss: 0.693229, acc.: 50.98%] [G loss: 0.728348]
8/8 [==============================] - 0s 4ms/step
4116 [D loss: 0.687073, acc.: 52.34%] [G loss: 0.725951]
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4117 [D loss: 0.689031, acc.: 52.93%] [G loss: 0.728578]
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4118 [D loss: 0.689701, acc.: 50.59%] [G loss: 0.727305]
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4119 [D loss: 0.693585, acc.: 51.37%] [G loss: 0.728356]
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4120 [D loss: 0.695909, acc.: 51.37%] [G loss: 0.723602]
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4121 [D loss: 0.692652, acc.: 53.52%] [G loss: 0.724808]
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4122 [D loss: 0.690358, acc.: 53.91%] [G loss: 0.721145]
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4123 [D loss: 0.691928, acc.: 51.37%] [G loss: 0.721340]
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4124 [D loss: 0.697952, acc.: 49.02%] [G loss: 0.713580]
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4125 [D loss: 0.697254, acc.: 50.00%] [G loss: 0.716000]
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4126 [D loss: 0.699357, acc.: 49.41%] [G loss: 0.732032]
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4127 [D loss: 0.697202, acc.: 50.98%] [G loss: 0.732168]
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4128 [D loss: 0.702017, acc.: 47.27%] [G loss: 0.732734]
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4129 [D loss: 0.693198, acc.: 49.61%] [G loss: 0.737839]
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4130 [D loss: 0.702125, acc.: 48.24%] [G loss: 0.729020]
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4131 [D loss: 0.694509, acc.: 51.37%] [G loss: 0.732925]
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4132 [D loss: 0.697719, acc.: 51.37%] [G loss: 0.731784]
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4133 [D loss: 0.693037, acc.: 49.80%] [G loss: 0.735173]
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4134 [D loss: 0.695637, acc.: 49.80%] [G loss: 0.718381]
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4135 [D loss: 0.692176, acc.: 51.37%] [G loss: 0.720440]
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4136 [D loss: 0.691772, acc.: 52.34%] [G loss: 0.716312]
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4137 [D loss: 0.697572, acc.: 48.05%] [G loss: 0.708991]
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4138 [D loss: 0.695831, acc.: 47.46%] [G loss: 0.721229]
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4139 [D loss: 0.695484, acc.: 47.46%] [G loss: 0.730766]
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4140 [D loss: 0.694342, acc.: 50.78%] [G loss: 0.740710]
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4141 [D loss: 0.690598, acc.: 51.95%] [G loss: 0.737910]
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4142 [D loss: 0.692252, acc.: 50.59%] [G loss: 0.736121]
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4143 [D loss: 0.692620, acc.: 50.00%] [G loss: 0.738236]
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4144 [D loss: 0.683406, acc.: 56.84%] [G loss: 0.741600]
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4145 [D loss: 0.689631, acc.: 54.10%] [G loss: 0.735564]
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4146 [D loss: 0.685362, acc.: 54.88%] [G loss: 0.742109]
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4147 [D loss: 0.691444, acc.: 51.17%] [G loss: 0.736437]
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4148 [D loss: 0.693714, acc.: 50.59%] [G loss: 0.729635]
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4149 [D loss: 0.693859, acc.: 53.52%] [G loss: 0.730829]
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4150 [D loss: 0.685408, acc.: 54.69%] [G loss: 0.732381]
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4151 [D loss: 0.689460, acc.: 54.30%] [G loss: 0.739184]
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4152 [D loss: 0.694465, acc.: 50.78%] [G loss: 0.737841]
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4153 [D loss: 0.686165, acc.: 56.45%] [G loss: 0.739899]
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4154 [D loss: 0.692757, acc.: 52.34%] [G loss: 0.729281]
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4155 [D loss: 0.696294, acc.: 52.34%] [G loss: 0.727810]
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4156 [D loss: 0.692785, acc.: 50.20%] [G loss: 0.730469]
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4157 [D loss: 0.689600, acc.: 53.91%] [G loss: 0.735569]
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4158 [D loss: 0.682691, acc.: 57.42%] [G loss: 0.733306]
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4159 [D loss: 0.688652, acc.: 53.91%] [G loss: 0.732459]
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4160 [D loss: 0.682905, acc.: 54.10%] [G loss: 0.728322]
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4161 [D loss: 0.687850, acc.: 51.56%] [G loss: 0.734750]
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4162 [D loss: 0.695510, acc.: 47.66%] [G loss: 0.724431]
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4163 [D loss: 0.697938, acc.: 50.00%] [G loss: 0.736562]
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4164 [D loss: 0.687084, acc.: 51.56%] [G loss: 0.722241]
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4165 [D loss: 0.687264, acc.: 52.93%] [G loss: 0.722716]
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4166 [D loss: 0.688941, acc.: 53.71%] [G loss: 0.725768]
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4167 [D loss: 0.700087, acc.: 49.22%] [G loss: 0.720702]
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4168 [D loss: 0.690000, acc.: 49.22%] [G loss: 0.729640]
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4169 [D loss: 0.692323, acc.: 52.34%] [G loss: 0.724288]
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4170 [D loss: 0.689324, acc.: 54.10%] [G loss: 0.729546]
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4171 [D loss: 0.685188, acc.: 54.69%] [G loss: 0.739381]
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4172 [D loss: 0.686669, acc.: 55.27%] [G loss: 0.741763]
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4173 [D loss: 0.694020, acc.: 48.83%] [G loss: 0.724221]
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4174 [D loss: 0.690162, acc.: 50.78%] [G loss: 0.725954]
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4175 [D loss: 0.696040, acc.: 47.46%] [G loss: 0.739660]
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4176 [D loss: 0.686036, acc.: 54.30%] [G loss: 0.742494]
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4177 [D loss: 0.694342, acc.: 47.85%] [G loss: 0.730200]
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4178 [D loss: 0.699509, acc.: 49.80%] [G loss: 0.730927]
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4179 [D loss: 0.695971, acc.: 48.44%] [G loss: 0.725240]
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4180 [D loss: 0.688053, acc.: 50.98%] [G loss: 0.724258]
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4181 [D loss: 0.692618, acc.: 51.37%] [G loss: 0.720798]
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4182 [D loss: 0.695748, acc.: 46.88%] [G loss: 0.728863]
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4183 [D loss: 0.699388, acc.: 47.66%] [G loss: 0.727664]
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4184 [D loss: 0.689430, acc.: 51.17%] [G loss: 0.727626]
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4185 [D loss: 0.688300, acc.: 52.93%] [G loss: 0.712969]
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4186 [D loss: 0.690620, acc.: 52.54%] [G loss: 0.727775]
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4187 [D loss: 0.692239, acc.: 51.17%] [G loss: 0.739453]
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4188 [D loss: 0.681089, acc.: 51.76%] [G loss: 0.739502]
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4189 [D loss: 0.686779, acc.: 50.39%] [G loss: 0.731057]
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4190 [D loss: 0.686404, acc.: 52.54%] [G loss: 0.731272]
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4191 [D loss: 0.688864, acc.: 51.37%] [G loss: 0.738591]
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4192 [D loss: 0.695253, acc.: 48.83%] [G loss: 0.717036]
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4193 [D loss: 0.690511, acc.: 51.17%] [G loss: 0.735057]
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4194 [D loss: 0.691643, acc.: 47.66%] [G loss: 0.723604]
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4195 [D loss: 0.691512, acc.: 47.85%] [G loss: 0.714566]
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4196 [D loss: 0.692676, acc.: 48.05%] [G loss: 0.711809]
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4197 [D loss: 0.697557, acc.: 48.83%] [G loss: 0.727229]
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4198 [D loss: 0.689255, acc.: 51.95%] [G loss: 0.727365]
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4199 [D loss: 0.684532, acc.: 53.52%] [G loss: 0.737356]
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4200 [D loss: 0.679791, acc.: 55.86%] [G loss: 0.743750]
1/1 [==============================] - 0s 29ms/step
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4201 [D loss: 0.677503, acc.: 58.40%] [G loss: 0.742171]
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4202 [D loss: 0.682963, acc.: 54.88%] [G loss: 0.744176]
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4203 [D loss: 0.679911, acc.: 55.86%] [G loss: 0.734103]
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4204 [D loss: 0.684891, acc.: 53.91%] [G loss: 0.721736]
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4205 [D loss: 0.696908, acc.: 49.22%] [G loss: 0.709453]
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4206 [D loss: 0.700683, acc.: 47.66%] [G loss: 0.711948]
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4207 [D loss: 0.690961, acc.: 48.63%] [G loss: 0.724438]
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4208 [D loss: 0.697677, acc.: 51.37%] [G loss: 0.740060]
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4209 [D loss: 0.691391, acc.: 52.93%] [G loss: 0.747231]
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4210 [D loss: 0.682565, acc.: 55.86%] [G loss: 0.747409]
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4211 [D loss: 0.686086, acc.: 53.32%] [G loss: 0.748437]
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4212 [D loss: 0.687357, acc.: 52.34%] [G loss: 0.749056]
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4213 [D loss: 0.682429, acc.: 54.30%] [G loss: 0.741838]
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4214 [D loss: 0.679425, acc.: 55.66%] [G loss: 0.737182]
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4215 [D loss: 0.683019, acc.: 54.30%] [G loss: 0.728851]
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4216 [D loss: 0.690679, acc.: 50.78%] [G loss: 0.719742]
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4217 [D loss: 0.689061, acc.: 52.34%] [G loss: 0.717529]
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4218 [D loss: 0.698207, acc.: 47.46%] [G loss: 0.705841]
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4219 [D loss: 0.695870, acc.: 51.17%] [G loss: 0.721069]
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4220 [D loss: 0.695697, acc.: 50.98%] [G loss: 0.729834]
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4221 [D loss: 0.692088, acc.: 49.61%] [G loss: 0.744373]
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4222 [D loss: 0.685613, acc.: 51.37%] [G loss: 0.752948]
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4223 [D loss: 0.689833, acc.: 52.93%] [G loss: 0.747787]
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4224 [D loss: 0.684886, acc.: 54.69%] [G loss: 0.749285]
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4225 [D loss: 0.682555, acc.: 57.03%] [G loss: 0.736445]
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4226 [D loss: 0.682502, acc.: 52.54%] [G loss: 0.739049]
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4227 [D loss: 0.685325, acc.: 57.03%] [G loss: 0.728972]
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4228 [D loss: 0.699655, acc.: 49.80%] [G loss: 0.722218]
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4229 [D loss: 0.697255, acc.: 49.41%] [G loss: 0.710519]
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4230 [D loss: 0.701747, acc.: 46.29%] [G loss: 0.723968]
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4231 [D loss: 0.696960, acc.: 48.83%] [G loss: 0.756001]
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4232 [D loss: 0.691516, acc.: 54.10%] [G loss: 0.762538]
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4233 [D loss: 0.685263, acc.: 55.86%] [G loss: 0.752615]
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4234 [D loss: 0.695500, acc.: 51.37%] [G loss: 0.734457]
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4235 [D loss: 0.699678, acc.: 50.59%] [G loss: 0.738505]
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4236 [D loss: 0.690426, acc.: 54.69%] [G loss: 0.741936]
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4237 [D loss: 0.689069, acc.: 54.88%] [G loss: 0.724649]
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4238 [D loss: 0.693568, acc.: 52.93%] [G loss: 0.704458]
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4239 [D loss: 0.706386, acc.: 47.27%] [G loss: 0.696234]
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4240 [D loss: 0.700792, acc.: 47.07%] [G loss: 0.700968]
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4241 [D loss: 0.693240, acc.: 50.00%] [G loss: 0.712319]
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4242 [D loss: 0.693238, acc.: 53.91%] [G loss: 0.734797]
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4243 [D loss: 0.686677, acc.: 53.52%] [G loss: 0.779575]
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4244 [D loss: 0.673173, acc.: 60.16%] [G loss: 0.779678]
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4245 [D loss: 0.682559, acc.: 56.64%] [G loss: 0.788118]
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4246 [D loss: 0.702431, acc.: 50.98%] [G loss: 0.755152]
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4247 [D loss: 0.700736, acc.: 50.39%] [G loss: 0.723034]
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4248 [D loss: 0.701809, acc.: 47.27%] [G loss: 0.726501]
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4249 [D loss: 0.699519, acc.: 47.07%] [G loss: 0.722670]
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4250 [D loss: 0.703074, acc.: 47.07%] [G loss: 0.722522]
1/1 [==============================] - 0s 39ms/step
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4251 [D loss: 0.699132, acc.: 46.88%] [G loss: 0.706151]
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4252 [D loss: 0.697088, acc.: 47.07%] [G loss: 0.715070]
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4253 [D loss: 0.702324, acc.: 48.63%] [G loss: 0.727555]
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4254 [D loss: 0.688354, acc.: 53.91%] [G loss: 0.760415]
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4255 [D loss: 0.683012, acc.: 55.47%] [G loss: 0.787103]
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4256 [D loss: 0.681697, acc.: 55.86%] [G loss: 0.775081]
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4257 [D loss: 0.692912, acc.: 52.34%] [G loss: 0.742451]
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4258 [D loss: 0.695736, acc.: 49.22%] [G loss: 0.735695]
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4259 [D loss: 0.698130, acc.: 51.37%] [G loss: 0.730816]
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4260 [D loss: 0.697259, acc.: 49.80%] [G loss: 0.714792]
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4261 [D loss: 0.698166, acc.: 50.20%] [G loss: 0.706278]
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4262 [D loss: 0.702247, acc.: 42.58%] [G loss: 0.698312]
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4263 [D loss: 0.702797, acc.: 48.83%] [G loss: 0.691216]
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4264 [D loss: 0.694175, acc.: 49.22%] [G loss: 0.703459]
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4265 [D loss: 0.690654, acc.: 52.73%] [G loss: 0.716863]
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4266 [D loss: 0.688722, acc.: 51.76%] [G loss: 0.741642]
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4267 [D loss: 0.685577, acc.: 55.27%] [G loss: 0.771123]
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4268 [D loss: 0.677324, acc.: 57.03%] [G loss: 0.781597]
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4269 [D loss: 0.688920, acc.: 53.12%] [G loss: 0.765695]
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4270 [D loss: 0.682829, acc.: 55.86%] [G loss: 0.744422]
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4271 [D loss: 0.687136, acc.: 52.93%] [G loss: 0.743690]
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4272 [D loss: 0.688140, acc.: 52.93%] [G loss: 0.733760]
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4273 [D loss: 0.691085, acc.: 50.98%] [G loss: 0.720052]
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4274 [D loss: 0.692826, acc.: 49.61%] [G loss: 0.716880]
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4275 [D loss: 0.700048, acc.: 47.85%] [G loss: 0.709972]
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4276 [D loss: 0.698152, acc.: 47.66%] [G loss: 0.713793]
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4277 [D loss: 0.705444, acc.: 44.73%] [G loss: 0.716963]
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4278 [D loss: 0.700702, acc.: 47.66%] [G loss: 0.740213]
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4279 [D loss: 0.695631, acc.: 52.73%] [G loss: 0.740117]
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4280 [D loss: 0.694897, acc.: 50.20%] [G loss: 0.757168]
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4281 [D loss: 0.689306, acc.: 51.17%] [G loss: 0.750621]
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4282 [D loss: 0.695992, acc.: 50.39%] [G loss: 0.743011]
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4283 [D loss: 0.692333, acc.: 56.05%] [G loss: 0.746366]
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4284 [D loss: 0.695991, acc.: 52.15%] [G loss: 0.742590]
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4285 [D loss: 0.686253, acc.: 54.30%] [G loss: 0.743657]
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4286 [D loss: 0.690186, acc.: 54.30%] [G loss: 0.734213]
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4287 [D loss: 0.688220, acc.: 54.10%] [G loss: 0.721605]
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4288 [D loss: 0.693093, acc.: 50.59%] [G loss: 0.710415]
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4289 [D loss: 0.694134, acc.: 50.78%] [G loss: 0.709655]
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4290 [D loss: 0.697664, acc.: 50.98%] [G loss: 0.733073]
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4291 [D loss: 0.692638, acc.: 51.95%] [G loss: 0.753841]
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4292 [D loss: 0.695244, acc.: 49.02%] [G loss: 0.752650]
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4293 [D loss: 0.686851, acc.: 54.10%] [G loss: 0.753851]
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4294 [D loss: 0.695039, acc.: 49.22%] [G loss: 0.727628]
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4295 [D loss: 0.691736, acc.: 52.34%] [G loss: 0.726488]
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4296 [D loss: 0.695304, acc.: 48.63%] [G loss: 0.727143]
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4297 [D loss: 0.689712, acc.: 52.34%] [G loss: 0.724647]
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4298 [D loss: 0.691040, acc.: 51.37%] [G loss: 0.721207]
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4299 [D loss: 0.693737, acc.: 50.78%] [G loss: 0.714184]
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4300 [D loss: 0.695440, acc.: 51.37%] [G loss: 0.730620]
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4301 [D loss: 0.683850, acc.: 56.05%] [G loss: 0.734855]
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4302 [D loss: 0.683455, acc.: 54.10%] [G loss: 0.740530]
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4303 [D loss: 0.694779, acc.: 51.17%] [G loss: 0.735926]
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4304 [D loss: 0.694950, acc.: 50.39%] [G loss: 0.732608]
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4305 [D loss: 0.692978, acc.: 49.80%] [G loss: 0.733366]
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4306 [D loss: 0.696832, acc.: 50.78%] [G loss: 0.728176]
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4307 [D loss: 0.686536, acc.: 52.73%] [G loss: 0.721706]
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4308 [D loss: 0.685238, acc.: 53.12%] [G loss: 0.726334]
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4309 [D loss: 0.687737, acc.: 51.37%] [G loss: 0.727832]
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4310 [D loss: 0.691475, acc.: 49.22%] [G loss: 0.725906]
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4311 [D loss: 0.689752, acc.: 51.76%] [G loss: 0.719705]
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4312 [D loss: 0.690396, acc.: 54.88%] [G loss: 0.732162]
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4313 [D loss: 0.683721, acc.: 53.12%] [G loss: 0.748997]
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4314 [D loss: 0.681099, acc.: 54.10%] [G loss: 0.754457]
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4315 [D loss: 0.684276, acc.: 55.08%] [G loss: 0.746766]
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4316 [D loss: 0.685734, acc.: 51.56%] [G loss: 0.748560]
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4317 [D loss: 0.685589, acc.: 50.78%] [G loss: 0.730955]
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4318 [D loss: 0.687367, acc.: 55.27%] [G loss: 0.728968]
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4319 [D loss: 0.688102, acc.: 50.20%] [G loss: 0.724459]
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4320 [D loss: 0.696227, acc.: 46.68%] [G loss: 0.723364]
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4321 [D loss: 0.696479, acc.: 49.61%] [G loss: 0.716757]
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4322 [D loss: 0.692686, acc.: 48.63%] [G loss: 0.724963]
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4323 [D loss: 0.689206, acc.: 52.54%] [G loss: 0.724923]
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4324 [D loss: 0.686972, acc.: 53.32%] [G loss: 0.741256]
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4325 [D loss: 0.690336, acc.: 52.54%] [G loss: 0.724567]
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4326 [D loss: 0.693744, acc.: 49.80%] [G loss: 0.729343]
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4327 [D loss: 0.690635, acc.: 48.24%] [G loss: 0.729180]
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4328 [D loss: 0.696113, acc.: 47.66%] [G loss: 0.724374]
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4329 [D loss: 0.695307, acc.: 47.85%] [G loss: 0.721006]
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4330 [D loss: 0.694253, acc.: 53.12%] [G loss: 0.720172]
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4331 [D loss: 0.688078, acc.: 52.34%] [G loss: 0.722029]
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4332 [D loss: 0.687148, acc.: 50.39%] [G loss: 0.723794]
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4333 [D loss: 0.690587, acc.: 51.37%] [G loss: 0.724596]
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4334 [D loss: 0.693794, acc.: 46.88%] [G loss: 0.721680]
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4335 [D loss: 0.691756, acc.: 50.00%] [G loss: 0.726576]
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4336 [D loss: 0.690886, acc.: 52.54%] [G loss: 0.745521]
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4337 [D loss: 0.680117, acc.: 56.64%] [G loss: 0.749897]
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4338 [D loss: 0.683624, acc.: 52.34%] [G loss: 0.757447]
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4339 [D loss: 0.679721, acc.: 58.59%] [G loss: 0.743117]
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4340 [D loss: 0.687438, acc.: 53.12%] [G loss: 0.749186]
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4341 [D loss: 0.689838, acc.: 55.08%] [G loss: 0.737557]
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4342 [D loss: 0.690307, acc.: 53.91%] [G loss: 0.743818]
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4343 [D loss: 0.692564, acc.: 51.17%] [G loss: 0.734708]
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4344 [D loss: 0.690361, acc.: 48.44%] [G loss: 0.727706]
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4345 [D loss: 0.699171, acc.: 45.70%] [G loss: 0.725735]
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4346 [D loss: 0.697919, acc.: 49.41%] [G loss: 0.711272]
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4347 [D loss: 0.691358, acc.: 49.80%] [G loss: 0.723608]
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4348 [D loss: 0.691670, acc.: 50.00%] [G loss: 0.739993]
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4349 [D loss: 0.702208, acc.: 46.48%] [G loss: 0.739336]
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4350 [D loss: 0.698089, acc.: 48.24%] [G loss: 0.735356]
1/1 [==============================] - 0s 27ms/step
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4351 [D loss: 0.683089, acc.: 54.49%] [G loss: 0.742682]
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4352 [D loss: 0.687034, acc.: 52.34%] [G loss: 0.740836]
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4353 [D loss: 0.683550, acc.: 54.30%] [G loss: 0.745752]
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4354 [D loss: 0.686498, acc.: 56.64%] [G loss: 0.737815]
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4355 [D loss: 0.679966, acc.: 55.27%] [G loss: 0.748809]
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4356 [D loss: 0.681809, acc.: 53.71%] [G loss: 0.738523]
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4357 [D loss: 0.691931, acc.: 52.34%] [G loss: 0.728212]
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4358 [D loss: 0.697397, acc.: 50.00%] [G loss: 0.715429]
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4359 [D loss: 0.687957, acc.: 53.91%] [G loss: 0.711177]
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4360 [D loss: 0.695074, acc.: 47.46%] [G loss: 0.723666]
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4361 [D loss: 0.690447, acc.: 50.39%] [G loss: 0.721587]
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4362 [D loss: 0.698208, acc.: 48.44%] [G loss: 0.731949]
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4363 [D loss: 0.693954, acc.: 48.44%] [G loss: 0.726467]
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4364 [D loss: 0.688904, acc.: 50.59%] [G loss: 0.727350]
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4365 [D loss: 0.689173, acc.: 49.02%] [G loss: 0.734341]
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4366 [D loss: 0.692450, acc.: 51.17%] [G loss: 0.744642]
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4367 [D loss: 0.693469, acc.: 48.44%] [G loss: 0.730113]
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4368 [D loss: 0.686504, acc.: 55.27%] [G loss: 0.722869]
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4369 [D loss: 0.685034, acc.: 53.71%] [G loss: 0.729792]
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4370 [D loss: 0.690772, acc.: 50.59%] [G loss: 0.719547]
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4371 [D loss: 0.691414, acc.: 50.78%] [G loss: 0.718305]
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4372 [D loss: 0.694822, acc.: 46.88%] [G loss: 0.734543]
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4373 [D loss: 0.688125, acc.: 49.80%] [G loss: 0.745497]
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4374 [D loss: 0.688982, acc.: 50.78%] [G loss: 0.755153]
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4375 [D loss: 0.685208, acc.: 50.98%] [G loss: 0.758237]
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4376 [D loss: 0.686410, acc.: 54.30%] [G loss: 0.749241]
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4377 [D loss: 0.685654, acc.: 53.12%] [G loss: 0.743984]
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4378 [D loss: 0.682840, acc.: 52.54%] [G loss: 0.741123]
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4379 [D loss: 0.680397, acc.: 54.88%] [G loss: 0.732813]
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4380 [D loss: 0.686238, acc.: 54.49%] [G loss: 0.727234]
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4381 [D loss: 0.690697, acc.: 49.22%] [G loss: 0.716876]
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4382 [D loss: 0.690653, acc.: 53.12%] [G loss: 0.724393]
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4383 [D loss: 0.686648, acc.: 53.32%] [G loss: 0.711952]
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4384 [D loss: 0.693009, acc.: 50.00%] [G loss: 0.728064]
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4385 [D loss: 0.704266, acc.: 47.07%] [G loss: 0.728410]
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4386 [D loss: 0.704011, acc.: 49.22%] [G loss: 0.730705]
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4387 [D loss: 0.692327, acc.: 51.37%] [G loss: 0.733918]
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4388 [D loss: 0.696791, acc.: 48.44%] [G loss: 0.734030]
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4389 [D loss: 0.704406, acc.: 52.15%] [G loss: 0.725095]
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4390 [D loss: 0.699272, acc.: 50.98%] [G loss: 0.725403]
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4391 [D loss: 0.698535, acc.: 49.41%] [G loss: 0.733129]
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4392 [D loss: 0.684549, acc.: 54.69%] [G loss: 0.733300]
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4393 [D loss: 0.694039, acc.: 53.12%] [G loss: 0.728149]
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4394 [D loss: 0.687001, acc.: 51.56%] [G loss: 0.718716]
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4395 [D loss: 0.693746, acc.: 51.17%] [G loss: 0.722952]
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4396 [D loss: 0.701052, acc.: 45.12%] [G loss: 0.732284]
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4397 [D loss: 0.694743, acc.: 51.17%] [G loss: 0.758342]
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4398 [D loss: 0.694218, acc.: 50.00%] [G loss: 0.770298]
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4399 [D loss: 0.687750, acc.: 55.86%] [G loss: 0.760850]
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4400 [D loss: 0.690138, acc.: 48.63%] [G loss: 0.753069]
1/1 [==============================] - 0s 26ms/step
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4401 [D loss: 0.698710, acc.: 52.34%] [G loss: 0.742068]
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4402 [D loss: 0.690471, acc.: 54.30%] [G loss: 0.727849]
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4403 [D loss: 0.699353, acc.: 48.24%] [G loss: 0.721396]
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4404 [D loss: 0.698427, acc.: 50.78%] [G loss: 0.717899]
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4405 [D loss: 0.702981, acc.: 48.44%] [G loss: 0.714702]
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4406 [D loss: 0.692575, acc.: 50.98%] [G loss: 0.715616]
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4407 [D loss: 0.696864, acc.: 52.15%] [G loss: 0.729843]
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4408 [D loss: 0.697264, acc.: 49.80%] [G loss: 0.739560]
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4409 [D loss: 0.688568, acc.: 56.05%] [G loss: 0.742403]
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4410 [D loss: 0.688302, acc.: 54.49%] [G loss: 0.752234]
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4411 [D loss: 0.694094, acc.: 48.63%] [G loss: 0.763667]
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4412 [D loss: 0.698093, acc.: 48.05%] [G loss: 0.740169]
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4413 [D loss: 0.701682, acc.: 45.12%] [G loss: 0.730726]
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4414 [D loss: 0.699885, acc.: 47.85%] [G loss: 0.733440]
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4415 [D loss: 0.690400, acc.: 51.76%] [G loss: 0.731191]
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4416 [D loss: 0.691766, acc.: 50.00%] [G loss: 0.734664]
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4417 [D loss: 0.690605, acc.: 51.37%] [G loss: 0.725150]
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4418 [D loss: 0.690589, acc.: 51.95%] [G loss: 0.718944]
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4419 [D loss: 0.695018, acc.: 48.44%] [G loss: 0.722045]
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4420 [D loss: 0.692182, acc.: 47.46%] [G loss: 0.716001]
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4421 [D loss: 0.692407, acc.: 50.00%] [G loss: 0.715429]
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4422 [D loss: 0.691638, acc.: 52.15%] [G loss: 0.719828]
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4423 [D loss: 0.691090, acc.: 51.95%] [G loss: 0.713663]
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4424 [D loss: 0.695816, acc.: 51.17%] [G loss: 0.717326]
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4425 [D loss: 0.697798, acc.: 49.22%] [G loss: 0.738686]
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4426 [D loss: 0.693956, acc.: 48.83%] [G loss: 0.729236]
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4427 [D loss: 0.695578, acc.: 50.20%] [G loss: 0.723998]
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4428 [D loss: 0.699660, acc.: 46.48%] [G loss: 0.725841]
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4429 [D loss: 0.696988, acc.: 51.17%] [G loss: 0.726557]
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4430 [D loss: 0.693287, acc.: 50.39%] [G loss: 0.729173]
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4431 [D loss: 0.689934, acc.: 51.37%] [G loss: 0.737387]
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4432 [D loss: 0.687137, acc.: 54.69%] [G loss: 0.732339]
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4433 [D loss: 0.685224, acc.: 54.88%] [G loss: 0.738344]
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4434 [D loss: 0.689242, acc.: 55.66%] [G loss: 0.733111]
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4435 [D loss: 0.683821, acc.: 54.49%] [G loss: 0.727687]
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4436 [D loss: 0.694254, acc.: 49.41%] [G loss: 0.738739]
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4437 [D loss: 0.690372, acc.: 50.20%] [G loss: 0.723959]
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4438 [D loss: 0.697874, acc.: 46.48%] [G loss: 0.734328]
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4439 [D loss: 0.693962, acc.: 51.56%] [G loss: 0.724761]
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4440 [D loss: 0.701144, acc.: 46.88%] [G loss: 0.723883]
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4441 [D loss: 0.693743, acc.: 50.78%] [G loss: 0.732339]
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4442 [D loss: 0.697631, acc.: 50.20%] [G loss: 0.741978]
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4443 [D loss: 0.687734, acc.: 50.39%] [G loss: 0.743667]
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4444 [D loss: 0.691968, acc.: 48.83%] [G loss: 0.740619]
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4445 [D loss: 0.692067, acc.: 50.98%] [G loss: 0.742630]
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4446 [D loss: 0.684098, acc.: 55.47%] [G loss: 0.734501]
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4447 [D loss: 0.690844, acc.: 53.12%] [G loss: 0.730131]
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4448 [D loss: 0.691228, acc.: 52.15%] [G loss: 0.734258]
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4449 [D loss: 0.685798, acc.: 53.52%] [G loss: 0.727672]
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4450 [D loss: 0.690758, acc.: 50.78%] [G loss: 0.737430]
1/1 [==============================] - 0s 31ms/step
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4451 [D loss: 0.678087, acc.: 58.40%] [G loss: 0.743152]
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4452 [D loss: 0.680643, acc.: 55.86%] [G loss: 0.752856]
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4453 [D loss: 0.694874, acc.: 51.37%] [G loss: 0.745045]
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4454 [D loss: 0.677000, acc.: 55.47%] [G loss: 0.750007]
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4455 [D loss: 0.701252, acc.: 48.24%] [G loss: 0.732231]
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4456 [D loss: 0.699237, acc.: 50.00%] [G loss: 0.728938]
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4457 [D loss: 0.692559, acc.: 49.61%] [G loss: 0.725820]
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4458 [D loss: 0.703356, acc.: 45.31%] [G loss: 0.726415]
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4459 [D loss: 0.703083, acc.: 46.48%] [G loss: 0.733543]
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4460 [D loss: 0.684439, acc.: 57.81%] [G loss: 0.740626]
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4461 [D loss: 0.693175, acc.: 49.41%] [G loss: 0.730015]
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4462 [D loss: 0.687434, acc.: 56.05%] [G loss: 0.733861]
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4463 [D loss: 0.691353, acc.: 52.15%] [G loss: 0.724071]
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4464 [D loss: 0.690899, acc.: 50.98%] [G loss: 0.740367]
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4465 [D loss: 0.683233, acc.: 55.66%] [G loss: 0.737660]
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4466 [D loss: 0.695553, acc.: 49.22%] [G loss: 0.713953]
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4467 [D loss: 0.693424, acc.: 49.61%] [G loss: 0.715996]
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4468 [D loss: 0.702950, acc.: 44.92%] [G loss: 0.707147]
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4469 [D loss: 0.692051, acc.: 48.44%] [G loss: 0.705654]
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4470 [D loss: 0.710777, acc.: 46.48%] [G loss: 0.725954]
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4471 [D loss: 0.688051, acc.: 50.78%] [G loss: 0.734587]
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4472 [D loss: 0.694337, acc.: 49.02%] [G loss: 0.746645]
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4473 [D loss: 0.686747, acc.: 53.52%] [G loss: 0.748797]
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4474 [D loss: 0.689073, acc.: 50.78%] [G loss: 0.742252]
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4475 [D loss: 0.688118, acc.: 51.76%] [G loss: 0.745277]
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4476 [D loss: 0.676491, acc.: 57.42%] [G loss: 0.752357]
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4477 [D loss: 0.689212, acc.: 53.32%] [G loss: 0.738364]
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4478 [D loss: 0.678752, acc.: 56.45%] [G loss: 0.733380]
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4479 [D loss: 0.685288, acc.: 50.98%] [G loss: 0.725853]
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4480 [D loss: 0.689129, acc.: 51.17%] [G loss: 0.708795]
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4481 [D loss: 0.695166, acc.: 48.05%] [G loss: 0.704935]
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4482 [D loss: 0.686419, acc.: 55.08%] [G loss: 0.718086]
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4483 [D loss: 0.692474, acc.: 54.88%] [G loss: 0.734062]
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4484 [D loss: 0.689647, acc.: 53.71%] [G loss: 0.742248]
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4485 [D loss: 0.693192, acc.: 52.34%] [G loss: 0.747573]
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4486 [D loss: 0.698589, acc.: 45.70%] [G loss: 0.727696]
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4487 [D loss: 0.695973, acc.: 47.07%] [G loss: 0.726368]
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4488 [D loss: 0.689104, acc.: 53.71%] [G loss: 0.727718]
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4489 [D loss: 0.680390, acc.: 54.10%] [G loss: 0.733805]
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4490 [D loss: 0.681215, acc.: 55.86%] [G loss: 0.730679]
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4491 [D loss: 0.688699, acc.: 53.71%] [G loss: 0.710901]
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4492 [D loss: 0.689102, acc.: 53.12%] [G loss: 0.707283]
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4493 [D loss: 0.707603, acc.: 47.27%] [G loss: 0.685315]
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4494 [D loss: 0.702198, acc.: 50.00%] [G loss: 0.694587]
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4495 [D loss: 0.706694, acc.: 46.88%] [G loss: 0.732395]
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4496 [D loss: 0.692495, acc.: 53.12%] [G loss: 0.740779]
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4497 [D loss: 0.697621, acc.: 51.76%] [G loss: 0.749665]
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4498 [D loss: 0.687781, acc.: 55.66%] [G loss: 0.755737]
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4499 [D loss: 0.699854, acc.: 47.46%] [G loss: 0.753223]
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4500 [D loss: 0.699050, acc.: 45.90%] [G loss: 0.735181]
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4501 [D loss: 0.691931, acc.: 52.54%] [G loss: 0.750182]
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4502 [D loss: 0.684392, acc.: 56.45%] [G loss: 0.764712]
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4503 [D loss: 0.688347, acc.: 52.34%] [G loss: 0.752878]
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4504 [D loss: 0.691299, acc.: 51.17%] [G loss: 0.726701]
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4505 [D loss: 0.702390, acc.: 48.44%] [G loss: 0.726858]
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4506 [D loss: 0.696949, acc.: 49.22%] [G loss: 0.727252]
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4507 [D loss: 0.691281, acc.: 49.02%] [G loss: 0.744617]
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4508 [D loss: 0.689622, acc.: 52.15%] [G loss: 0.777753]
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4509 [D loss: 0.692638, acc.: 51.76%] [G loss: 0.766375]
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4510 [D loss: 0.702825, acc.: 47.46%] [G loss: 0.756057]
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4511 [D loss: 0.699043, acc.: 46.29%] [G loss: 0.746924]
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4512 [D loss: 0.688264, acc.: 54.69%] [G loss: 0.748229]
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4513 [D loss: 0.684569, acc.: 56.05%] [G loss: 0.751331]
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4514 [D loss: 0.681913, acc.: 58.01%] [G loss: 0.749382]
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4515 [D loss: 0.695158, acc.: 54.10%] [G loss: 0.720691]
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4516 [D loss: 0.688592, acc.: 55.08%] [G loss: 0.701316]
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4517 [D loss: 0.692304, acc.: 51.56%] [G loss: 0.696932]
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4518 [D loss: 0.695326, acc.: 48.83%] [G loss: 0.700538]
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4519 [D loss: 0.688571, acc.: 54.88%] [G loss: 0.718673]
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4520 [D loss: 0.687338, acc.: 53.52%] [G loss: 0.722073]
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4521 [D loss: 0.696704, acc.: 48.44%] [G loss: 0.718943]
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4522 [D loss: 0.695558, acc.: 49.02%] [G loss: 0.730836]
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4523 [D loss: 0.687445, acc.: 52.34%] [G loss: 0.723103]
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4524 [D loss: 0.687411, acc.: 51.17%] [G loss: 0.728517]
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4525 [D loss: 0.690144, acc.: 52.54%] [G loss: 0.725697]
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4526 [D loss: 0.689892, acc.: 50.39%] [G loss: 0.729665]
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4527 [D loss: 0.685931, acc.: 54.30%] [G loss: 0.730563]
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4528 [D loss: 0.681625, acc.: 54.88%] [G loss: 0.733131]
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4529 [D loss: 0.684747, acc.: 53.32%] [G loss: 0.725524]
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4530 [D loss: 0.691171, acc.: 52.15%] [G loss: 0.722377]
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4531 [D loss: 0.692793, acc.: 49.61%] [G loss: 0.726589]
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4532 [D loss: 0.700615, acc.: 48.83%] [G loss: 0.730355]
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4533 [D loss: 0.698410, acc.: 46.09%] [G loss: 0.720223]
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4534 [D loss: 0.695693, acc.: 51.17%] [G loss: 0.726032]
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4535 [D loss: 0.701541, acc.: 47.66%] [G loss: 0.731823]
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4536 [D loss: 0.690112, acc.: 53.32%] [G loss: 0.745605]
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4537 [D loss: 0.690571, acc.: 52.34%] [G loss: 0.736987]
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4538 [D loss: 0.678690, acc.: 59.38%] [G loss: 0.735324]
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4539 [D loss: 0.688088, acc.: 55.27%] [G loss: 0.751967]
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4540 [D loss: 0.691554, acc.: 53.52%] [G loss: 0.734409]
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4541 [D loss: 0.696833, acc.: 48.24%] [G loss: 0.733076]
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4542 [D loss: 0.681076, acc.: 56.84%] [G loss: 0.729993]
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4543 [D loss: 0.694173, acc.: 50.39%] [G loss: 0.711620]
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4544 [D loss: 0.692037, acc.: 52.15%] [G loss: 0.728636]
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4545 [D loss: 0.702779, acc.: 48.44%] [G loss: 0.713002]
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4546 [D loss: 0.700162, acc.: 45.12%] [G loss: 0.711872]
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4547 [D loss: 0.698736, acc.: 48.83%] [G loss: 0.722789]
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4548 [D loss: 0.700130, acc.: 49.22%] [G loss: 0.718218]
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4549 [D loss: 0.698321, acc.: 46.48%] [G loss: 0.718947]
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4550 [D loss: 0.693063, acc.: 51.17%] [G loss: 0.731219]
1/1 [==============================] - 0s 27ms/step
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4551 [D loss: 0.697281, acc.: 47.85%] [G loss: 0.727498]
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4552 [D loss: 0.695695, acc.: 47.85%] [G loss: 0.726782]
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4553 [D loss: 0.688736, acc.: 50.78%] [G loss: 0.737042]
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4554 [D loss: 0.689450, acc.: 50.59%] [G loss: 0.737009]
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4555 [D loss: 0.693457, acc.: 53.71%] [G loss: 0.726753]
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4556 [D loss: 0.685351, acc.: 53.52%] [G loss: 0.731485]
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4557 [D loss: 0.695747, acc.: 49.80%] [G loss: 0.719398]
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4558 [D loss: 0.695346, acc.: 49.22%] [G loss: 0.723125]
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4559 [D loss: 0.689494, acc.: 53.12%] [G loss: 0.704796]
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4560 [D loss: 0.701867, acc.: 49.41%] [G loss: 0.727939]
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4561 [D loss: 0.694989, acc.: 52.54%] [G loss: 0.736454]
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4562 [D loss: 0.700637, acc.: 46.29%] [G loss: 0.741236]
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4563 [D loss: 0.696586, acc.: 46.48%] [G loss: 0.734951]
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4564 [D loss: 0.694914, acc.: 50.78%] [G loss: 0.732306]
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4565 [D loss: 0.687564, acc.: 51.95%] [G loss: 0.743160]
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4566 [D loss: 0.689061, acc.: 51.56%] [G loss: 0.741014]
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4567 [D loss: 0.685062, acc.: 56.84%] [G loss: 0.729025]
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4568 [D loss: 0.686635, acc.: 52.73%] [G loss: 0.732870]
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4569 [D loss: 0.692459, acc.: 51.17%] [G loss: 0.726114]
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4570 [D loss: 0.696331, acc.: 49.02%] [G loss: 0.719463]
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4571 [D loss: 0.694019, acc.: 51.95%] [G loss: 0.707103]
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4572 [D loss: 0.685431, acc.: 50.98%] [G loss: 0.719395]
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4573 [D loss: 0.688855, acc.: 50.98%] [G loss: 0.727451]
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4574 [D loss: 0.692931, acc.: 50.39%] [G loss: 0.734502]
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4575 [D loss: 0.698466, acc.: 48.63%] [G loss: 0.717434]
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4576 [D loss: 0.687588, acc.: 53.71%] [G loss: 0.744062]
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4577 [D loss: 0.697137, acc.: 50.78%] [G loss: 0.739351]
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4578 [D loss: 0.699814, acc.: 47.85%] [G loss: 0.736109]
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4579 [D loss: 0.688397, acc.: 51.56%] [G loss: 0.739151]
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4580 [D loss: 0.690276, acc.: 52.54%] [G loss: 0.735902]
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4581 [D loss: 0.696678, acc.: 47.66%] [G loss: 0.725237]
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4582 [D loss: 0.695380, acc.: 48.44%] [G loss: 0.718422]
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4583 [D loss: 0.693328, acc.: 51.76%] [G loss: 0.726427]
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4584 [D loss: 0.691801, acc.: 50.98%] [G loss: 0.727499]
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4585 [D loss: 0.695444, acc.: 53.12%] [G loss: 0.729075]
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4586 [D loss: 0.696361, acc.: 46.09%] [G loss: 0.731988]
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4587 [D loss: 0.698226, acc.: 49.22%] [G loss: 0.720787]
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4588 [D loss: 0.695277, acc.: 50.00%] [G loss: 0.718343]
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4589 [D loss: 0.694858, acc.: 47.07%] [G loss: 0.715739]
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4590 [D loss: 0.687241, acc.: 52.93%] [G loss: 0.721096]
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4591 [D loss: 0.691571, acc.: 51.95%] [G loss: 0.722101]
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4592 [D loss: 0.688593, acc.: 50.98%] [G loss: 0.707903]
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4593 [D loss: 0.684465, acc.: 56.64%] [G loss: 0.716389]
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4594 [D loss: 0.683145, acc.: 55.08%] [G loss: 0.717209]
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4595 [D loss: 0.695465, acc.: 49.02%] [G loss: 0.713336]
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4596 [D loss: 0.691425, acc.: 50.20%] [G loss: 0.720940]
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4597 [D loss: 0.697996, acc.: 49.80%] [G loss: 0.721797]
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4598 [D loss: 0.695727, acc.: 48.05%] [G loss: 0.728633]
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4599 [D loss: 0.696345, acc.: 51.37%] [G loss: 0.731687]
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4600 [D loss: 0.696369, acc.: 51.76%] [G loss: 0.722656]
1/1 [==============================] - 0s 27ms/step
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4601 [D loss: 0.700094, acc.: 49.61%] [G loss: 0.723294]
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4602 [D loss: 0.701470, acc.: 47.27%] [G loss: 0.720369]
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4603 [D loss: 0.695941, acc.: 51.76%] [G loss: 0.721206]
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4604 [D loss: 0.693861, acc.: 51.95%] [G loss: 0.719190]
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4605 [D loss: 0.694144, acc.: 50.39%] [G loss: 0.722922]
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4606 [D loss: 0.686005, acc.: 51.37%] [G loss: 0.722495]
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4607 [D loss: 0.691675, acc.: 50.98%] [G loss: 0.726914]
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4608 [D loss: 0.689982, acc.: 53.52%] [G loss: 0.714578]
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4609 [D loss: 0.686270, acc.: 56.45%] [G loss: 0.729387]
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4610 [D loss: 0.684385, acc.: 56.25%] [G loss: 0.734995]
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4611 [D loss: 0.690047, acc.: 53.12%] [G loss: 0.748656]
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4612 [D loss: 0.693335, acc.: 52.93%] [G loss: 0.748595]
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4613 [D loss: 0.688342, acc.: 54.10%] [G loss: 0.739487]
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4614 [D loss: 0.696851, acc.: 49.61%] [G loss: 0.738089]
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4615 [D loss: 0.695969, acc.: 51.17%] [G loss: 0.722632]
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4616 [D loss: 0.698782, acc.: 47.07%] [G loss: 0.714716]
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4617 [D loss: 0.703406, acc.: 42.77%] [G loss: 0.705464]
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4618 [D loss: 0.693089, acc.: 48.83%] [G loss: 0.718599]
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4619 [D loss: 0.697076, acc.: 49.80%] [G loss: 0.719981]
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4620 [D loss: 0.692454, acc.: 48.83%] [G loss: 0.727609]
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4621 [D loss: 0.692415, acc.: 51.56%] [G loss: 0.734631]
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4622 [D loss: 0.693875, acc.: 51.56%] [G loss: 0.735646]
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4623 [D loss: 0.692964, acc.: 50.59%] [G loss: 0.739941]
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4624 [D loss: 0.690166, acc.: 50.98%] [G loss: 0.734860]
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4625 [D loss: 0.703239, acc.: 49.02%] [G loss: 0.721923]
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4626 [D loss: 0.691877, acc.: 50.59%] [G loss: 0.718461]
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4627 [D loss: 0.695011, acc.: 50.39%] [G loss: 0.712601]
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4628 [D loss: 0.696270, acc.: 49.22%] [G loss: 0.715295]
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4629 [D loss: 0.697971, acc.: 45.90%] [G loss: 0.710271]
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4630 [D loss: 0.697554, acc.: 48.83%] [G loss: 0.710826]
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4631 [D loss: 0.694540, acc.: 49.41%] [G loss: 0.710844]
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4632 [D loss: 0.689553, acc.: 55.66%] [G loss: 0.724965]
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4633 [D loss: 0.695428, acc.: 48.83%] [G loss: 0.727614]
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4634 [D loss: 0.691921, acc.: 50.59%] [G loss: 0.727059]
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4635 [D loss: 0.690315, acc.: 51.95%] [G loss: 0.731928]
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4636 [D loss: 0.692468, acc.: 49.22%] [G loss: 0.725623]
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4637 [D loss: 0.696064, acc.: 47.66%] [G loss: 0.730976]
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4638 [D loss: 0.692275, acc.: 50.98%] [G loss: 0.725400]
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4639 [D loss: 0.691956, acc.: 51.17%] [G loss: 0.724764]
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4640 [D loss: 0.687422, acc.: 51.17%] [G loss: 0.713054]
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4641 [D loss: 0.686917, acc.: 56.64%] [G loss: 0.720813]
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4642 [D loss: 0.691175, acc.: 51.37%] [G loss: 0.716969]
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4643 [D loss: 0.694096, acc.: 51.37%] [G loss: 0.724801]
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4644 [D loss: 0.688194, acc.: 54.30%] [G loss: 0.733990]
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4645 [D loss: 0.684313, acc.: 53.71%] [G loss: 0.724487]
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4646 [D loss: 0.681857, acc.: 56.05%] [G loss: 0.733846]
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4647 [D loss: 0.689742, acc.: 52.73%] [G loss: 0.741554]
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4648 [D loss: 0.686612, acc.: 53.91%] [G loss: 0.749965]
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4649 [D loss: 0.681698, acc.: 54.30%] [G loss: 0.738742]
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4650 [D loss: 0.687341, acc.: 53.12%] [G loss: 0.736064]
1/1 [==============================] - 0s 27ms/step
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4651 [D loss: 0.688270, acc.: 50.39%] [G loss: 0.735701]
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4652 [D loss: 0.688584, acc.: 51.56%] [G loss: 0.726166]
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4653 [D loss: 0.686134, acc.: 49.02%] [G loss: 0.733349]
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4654 [D loss: 0.695360, acc.: 50.39%] [G loss: 0.707933]
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4655 [D loss: 0.694921, acc.: 51.95%] [G loss: 0.697907]
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4656 [D loss: 0.696041, acc.: 48.83%] [G loss: 0.711406]
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4657 [D loss: 0.694101, acc.: 48.24%] [G loss: 0.715590]
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4658 [D loss: 0.697868, acc.: 43.75%] [G loss: 0.708993]
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4659 [D loss: 0.701734, acc.: 49.02%] [G loss: 0.713056]
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4660 [D loss: 0.696409, acc.: 50.20%] [G loss: 0.716634]
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4661 [D loss: 0.691242, acc.: 52.54%] [G loss: 0.729669]
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4662 [D loss: 0.693108, acc.: 46.88%] [G loss: 0.747515]
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4663 [D loss: 0.686697, acc.: 54.69%] [G loss: 0.755656]
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4664 [D loss: 0.688916, acc.: 52.93%] [G loss: 0.752551]
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4665 [D loss: 0.686610, acc.: 56.45%] [G loss: 0.756904]
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4666 [D loss: 0.684358, acc.: 55.27%] [G loss: 0.743899]
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4667 [D loss: 0.677527, acc.: 57.42%] [G loss: 0.739573]
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4668 [D loss: 0.675733, acc.: 59.18%] [G loss: 0.732621]
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4669 [D loss: 0.675898, acc.: 58.01%] [G loss: 0.722962]
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4670 [D loss: 0.697923, acc.: 49.02%] [G loss: 0.707600]
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4671 [D loss: 0.696943, acc.: 48.24%] [G loss: 0.702728]
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4672 [D loss: 0.692851, acc.: 50.20%] [G loss: 0.712360]
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4673 [D loss: 0.694737, acc.: 48.44%] [G loss: 0.731176]
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4674 [D loss: 0.686641, acc.: 51.56%] [G loss: 0.755102]
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4675 [D loss: 0.691392, acc.: 51.56%] [G loss: 0.744511]
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4676 [D loss: 0.692254, acc.: 48.44%] [G loss: 0.737195]
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4677 [D loss: 0.696647, acc.: 45.90%] [G loss: 0.732745]
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4678 [D loss: 0.696788, acc.: 48.44%] [G loss: 0.731576]
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4679 [D loss: 0.685963, acc.: 51.17%] [G loss: 0.735619]
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4680 [D loss: 0.691149, acc.: 51.37%] [G loss: 0.718897]
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4681 [D loss: 0.692671, acc.: 49.80%] [G loss: 0.724845]
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4682 [D loss: 0.687165, acc.: 51.95%] [G loss: 0.727035]
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4683 [D loss: 0.685563, acc.: 49.22%] [G loss: 0.723271]
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4684 [D loss: 0.684252, acc.: 51.37%] [G loss: 0.729464]
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4685 [D loss: 0.680813, acc.: 55.08%] [G loss: 0.737230]
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4686 [D loss: 0.684804, acc.: 54.10%] [G loss: 0.752908]
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4687 [D loss: 0.685113, acc.: 50.78%] [G loss: 0.742597]
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4688 [D loss: 0.688400, acc.: 49.22%] [G loss: 0.744209]
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4689 [D loss: 0.692681, acc.: 50.98%] [G loss: 0.756380]
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4690 [D loss: 0.703918, acc.: 46.88%] [G loss: 0.726379]
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4691 [D loss: 0.707088, acc.: 42.97%] [G loss: 0.727073]
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4692 [D loss: 0.697304, acc.: 50.00%] [G loss: 0.718726]
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4693 [D loss: 0.695565, acc.: 46.48%] [G loss: 0.711804]
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4694 [D loss: 0.695754, acc.: 49.02%] [G loss: 0.711249]
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4695 [D loss: 0.698818, acc.: 50.59%] [G loss: 0.707095]
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4696 [D loss: 0.689105, acc.: 53.71%] [G loss: 0.717177]
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4697 [D loss: 0.691932, acc.: 49.22%] [G loss: 0.730638]
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4698 [D loss: 0.687357, acc.: 52.93%] [G loss: 0.725408]
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4699 [D loss: 0.695591, acc.: 52.34%] [G loss: 0.723216]
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4700 [D loss: 0.693257, acc.: 51.17%] [G loss: 0.722811]
1/1 [==============================] - 0s 27ms/step
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4701 [D loss: 0.693526, acc.: 50.78%] [G loss: 0.724962]
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4702 [D loss: 0.690183, acc.: 52.73%] [G loss: 0.721683]
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4703 [D loss: 0.690265, acc.: 55.47%] [G loss: 0.718096]
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4704 [D loss: 0.697103, acc.: 50.98%] [G loss: 0.716862]
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4705 [D loss: 0.698095, acc.: 48.24%] [G loss: 0.714763]
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4706 [D loss: 0.695259, acc.: 47.66%] [G loss: 0.728269]
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4707 [D loss: 0.692389, acc.: 53.32%] [G loss: 0.730646]
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4708 [D loss: 0.695198, acc.: 50.98%] [G loss: 0.731584]
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4709 [D loss: 0.693744, acc.: 50.59%] [G loss: 0.741507]
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4710 [D loss: 0.689418, acc.: 55.08%] [G loss: 0.738410]
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4711 [D loss: 0.692565, acc.: 52.15%] [G loss: 0.731908]
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4712 [D loss: 0.695842, acc.: 51.76%] [G loss: 0.727834]
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4713 [D loss: 0.693637, acc.: 52.15%] [G loss: 0.727098]
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4714 [D loss: 0.689549, acc.: 53.52%] [G loss: 0.716491]
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4715 [D loss: 0.691916, acc.: 52.34%] [G loss: 0.722383]
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4716 [D loss: 0.697540, acc.: 48.44%] [G loss: 0.719373]
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4717 [D loss: 0.691189, acc.: 52.34%] [G loss: 0.727042]
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4718 [D loss: 0.690108, acc.: 53.71%] [G loss: 0.727584]
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4719 [D loss: 0.690346, acc.: 50.98%] [G loss: 0.725829]
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4720 [D loss: 0.686539, acc.: 54.49%] [G loss: 0.738273]
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4721 [D loss: 0.690037, acc.: 51.17%] [G loss: 0.747782]
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4722 [D loss: 0.690331, acc.: 52.93%] [G loss: 0.746364]
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4723 [D loss: 0.696127, acc.: 50.20%] [G loss: 0.745539]
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4724 [D loss: 0.692661, acc.: 50.20%] [G loss: 0.723536]
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4725 [D loss: 0.690601, acc.: 51.17%] [G loss: 0.720636]
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4726 [D loss: 0.688113, acc.: 50.98%] [G loss: 0.722061]
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4727 [D loss: 0.696174, acc.: 50.39%] [G loss: 0.708360]
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4728 [D loss: 0.689797, acc.: 52.34%] [G loss: 0.715083]
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4729 [D loss: 0.697412, acc.: 47.46%] [G loss: 0.711361]
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4730 [D loss: 0.700279, acc.: 46.68%] [G loss: 0.708474]
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4731 [D loss: 0.692866, acc.: 51.76%] [G loss: 0.730639]
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4732 [D loss: 0.691127, acc.: 54.10%] [G loss: 0.736434]
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4733 [D loss: 0.695555, acc.: 52.73%] [G loss: 0.737104]
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4734 [D loss: 0.694295, acc.: 49.41%] [G loss: 0.734090]
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4735 [D loss: 0.697332, acc.: 52.54%] [G loss: 0.723398]
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4736 [D loss: 0.691341, acc.: 49.41%] [G loss: 0.722235]
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4737 [D loss: 0.696600, acc.: 47.27%] [G loss: 0.720053]
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4738 [D loss: 0.693693, acc.: 51.76%] [G loss: 0.719125]
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4739 [D loss: 0.687625, acc.: 52.34%] [G loss: 0.728564]
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4740 [D loss: 0.690042, acc.: 50.78%] [G loss: 0.719253]
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4741 [D loss: 0.694838, acc.: 50.00%] [G loss: 0.726312]
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4742 [D loss: 0.696523, acc.: 47.27%] [G loss: 0.731959]
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4743 [D loss: 0.679683, acc.: 58.79%] [G loss: 0.747306]
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4744 [D loss: 0.684261, acc.: 52.34%] [G loss: 0.761534]
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4745 [D loss: 0.685157, acc.: 52.34%] [G loss: 0.752897]
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4746 [D loss: 0.687377, acc.: 53.32%] [G loss: 0.746562]
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4747 [D loss: 0.696298, acc.: 50.59%] [G loss: 0.745165]
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4748 [D loss: 0.690085, acc.: 51.17%] [G loss: 0.732014]
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4749 [D loss: 0.696746, acc.: 49.02%] [G loss: 0.724750]
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4750 [D loss: 0.686567, acc.: 53.71%] [G loss: 0.714012]
1/1 [==============================] - 0s 28ms/step
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4751 [D loss: 0.696538, acc.: 48.83%] [G loss: 0.708892]
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4752 [D loss: 0.686198, acc.: 54.10%] [G loss: 0.709928]
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4753 [D loss: 0.698754, acc.: 48.44%] [G loss: 0.726988]
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4754 [D loss: 0.689039, acc.: 50.98%] [G loss: 0.727723]
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4755 [D loss: 0.703482, acc.: 44.73%] [G loss: 0.726005]
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4756 [D loss: 0.696343, acc.: 48.24%] [G loss: 0.730289]
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4757 [D loss: 0.697211, acc.: 48.24%] [G loss: 0.740290]
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4758 [D loss: 0.697364, acc.: 46.09%] [G loss: 0.735412]
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4759 [D loss: 0.694610, acc.: 50.00%] [G loss: 0.737383]
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4760 [D loss: 0.688597, acc.: 51.56%] [G loss: 0.719474]
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4761 [D loss: 0.689384, acc.: 53.91%] [G loss: 0.719984]
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4762 [D loss: 0.688675, acc.: 50.20%] [G loss: 0.714465]
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4763 [D loss: 0.693699, acc.: 50.00%] [G loss: 0.709155]
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4764 [D loss: 0.690857, acc.: 52.54%] [G loss: 0.707229]
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4765 [D loss: 0.695335, acc.: 49.02%] [G loss: 0.717722]
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4766 [D loss: 0.692363, acc.: 51.17%] [G loss: 0.725851]
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4767 [D loss: 0.692683, acc.: 51.37%] [G loss: 0.723597]
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4768 [D loss: 0.689814, acc.: 49.22%] [G loss: 0.716871]
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4769 [D loss: 0.696010, acc.: 46.88%] [G loss: 0.713150]
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4770 [D loss: 0.694210, acc.: 51.37%] [G loss: 0.715593]
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4771 [D loss: 0.692198, acc.: 47.85%] [G loss: 0.718938]
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4772 [D loss: 0.689101, acc.: 50.78%] [G loss: 0.714718]
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4773 [D loss: 0.685563, acc.: 52.15%] [G loss: 0.714180]
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4774 [D loss: 0.688098, acc.: 52.54%] [G loss: 0.711778]
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4775 [D loss: 0.697025, acc.: 47.85%] [G loss: 0.715474]
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4776 [D loss: 0.690020, acc.: 52.15%] [G loss: 0.718778]
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4777 [D loss: 0.693183, acc.: 48.83%] [G loss: 0.727750]
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4778 [D loss: 0.684062, acc.: 51.17%] [G loss: 0.736636]
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4779 [D loss: 0.691568, acc.: 49.02%] [G loss: 0.729245]
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4780 [D loss: 0.687502, acc.: 50.59%] [G loss: 0.731646]
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4781 [D loss: 0.687977, acc.: 50.59%] [G loss: 0.736537]
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4782 [D loss: 0.690692, acc.: 48.83%] [G loss: 0.729944]
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4783 [D loss: 0.688063, acc.: 50.98%] [G loss: 0.732099]
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4784 [D loss: 0.689781, acc.: 51.17%] [G loss: 0.725247]
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4785 [D loss: 0.687554, acc.: 50.00%] [G loss: 0.716361]
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4786 [D loss: 0.684262, acc.: 52.93%] [G loss: 0.712987]
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4787 [D loss: 0.693872, acc.: 48.63%] [G loss: 0.718066]
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4788 [D loss: 0.689943, acc.: 51.37%] [G loss: 0.706420]
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4789 [D loss: 0.695014, acc.: 49.02%] [G loss: 0.733754]
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4790 [D loss: 0.693194, acc.: 46.48%] [G loss: 0.721888]
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4791 [D loss: 0.691491, acc.: 49.80%] [G loss: 0.740958]
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4792 [D loss: 0.689834, acc.: 50.78%] [G loss: 0.742196]
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4793 [D loss: 0.685408, acc.: 54.88%] [G loss: 0.743755]
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4794 [D loss: 0.695531, acc.: 45.90%] [G loss: 0.735505]
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4795 [D loss: 0.691234, acc.: 50.78%] [G loss: 0.728628]
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4796 [D loss: 0.688405, acc.: 49.02%] [G loss: 0.729986]
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4797 [D loss: 0.696949, acc.: 48.83%] [G loss: 0.722358]
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4798 [D loss: 0.692116, acc.: 48.05%] [G loss: 0.725214]
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4799 [D loss: 0.691461, acc.: 42.58%] [G loss: 0.728841]
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4800 [D loss: 0.688548, acc.: 49.41%] [G loss: 0.719304]
1/1 [==============================] - 0s 28ms/step
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4801 [D loss: 0.689430, acc.: 48.44%] [G loss: 0.730105]
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4802 [D loss: 0.691270, acc.: 48.05%] [G loss: 0.726357]
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4803 [D loss: 0.685860, acc.: 50.59%] [G loss: 0.733561]
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4804 [D loss: 0.683634, acc.: 51.56%] [G loss: 0.730250]
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4805 [D loss: 0.689822, acc.: 48.44%] [G loss: 0.737558]
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4806 [D loss: 0.686389, acc.: 48.83%] [G loss: 0.730123]
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4807 [D loss: 0.683632, acc.: 48.24%] [G loss: 0.739600]
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4808 [D loss: 0.692096, acc.: 49.80%] [G loss: 0.729018]
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4809 [D loss: 0.687094, acc.: 55.08%] [G loss: 0.736087]
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4810 [D loss: 0.692588, acc.: 45.51%] [G loss: 0.724537]
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4811 [D loss: 0.687528, acc.: 51.95%] [G loss: 0.717418]
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4812 [D loss: 0.700582, acc.: 45.70%] [G loss: 0.702288]
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4813 [D loss: 0.709337, acc.: 48.24%] [G loss: 0.711146]
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4814 [D loss: 0.694290, acc.: 47.07%] [G loss: 0.738809]
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4815 [D loss: 0.690854, acc.: 48.83%] [G loss: 0.738468]
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4816 [D loss: 0.695876, acc.: 50.59%] [G loss: 0.747473]
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4817 [D loss: 0.694143, acc.: 46.29%] [G loss: 0.750003]
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4818 [D loss: 0.692658, acc.: 49.22%] [G loss: 0.734201]
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4819 [D loss: 0.690618, acc.: 47.66%] [G loss: 0.734570]
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4820 [D loss: 0.686810, acc.: 51.56%] [G loss: 0.738063]
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4821 [D loss: 0.687089, acc.: 52.34%] [G loss: 0.726252]
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4822 [D loss: 0.685340, acc.: 53.91%] [G loss: 0.709877]
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4823 [D loss: 0.694519, acc.: 50.20%] [G loss: 0.703657]
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4824 [D loss: 0.696699, acc.: 51.95%] [G loss: 0.692876]
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4825 [D loss: 0.699416, acc.: 46.48%] [G loss: 0.690154]
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4826 [D loss: 0.694096, acc.: 51.76%] [G loss: 0.718511]
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4827 [D loss: 0.694075, acc.: 54.49%] [G loss: 0.736660]
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4828 [D loss: 0.688054, acc.: 51.17%] [G loss: 0.758764]
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4829 [D loss: 0.691779, acc.: 49.41%] [G loss: 0.762745]
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4830 [D loss: 0.696511, acc.: 49.61%] [G loss: 0.746863]
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4831 [D loss: 0.697111, acc.: 48.24%] [G loss: 0.743538]
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4832 [D loss: 0.695595, acc.: 49.41%] [G loss: 0.739394]
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4833 [D loss: 0.693419, acc.: 52.54%] [G loss: 0.735545]
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4834 [D loss: 0.692999, acc.: 52.15%] [G loss: 0.723167]
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4835 [D loss: 0.692461, acc.: 50.00%] [G loss: 0.717834]
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4836 [D loss: 0.699923, acc.: 45.70%] [G loss: 0.718844]
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4837 [D loss: 0.692798, acc.: 51.56%] [G loss: 0.704753]
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4838 [D loss: 0.696097, acc.: 50.39%] [G loss: 0.717460]
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4839 [D loss: 0.689995, acc.: 52.54%] [G loss: 0.725470]
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4840 [D loss: 0.693053, acc.: 48.83%] [G loss: 0.735708]
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4841 [D loss: 0.700317, acc.: 48.44%] [G loss: 0.724193]
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4842 [D loss: 0.697611, acc.: 47.46%] [G loss: 0.729371]
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4843 [D loss: 0.703380, acc.: 44.34%] [G loss: 0.715444]
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4844 [D loss: 0.699030, acc.: 46.29%] [G loss: 0.715340]
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4845 [D loss: 0.697266, acc.: 46.88%] [G loss: 0.725425]
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4846 [D loss: 0.694272, acc.: 49.80%] [G loss: 0.722013]
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4847 [D loss: 0.691805, acc.: 51.95%] [G loss: 0.720208]
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4848 [D loss: 0.696216, acc.: 50.20%] [G loss: 0.730497]
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4849 [D loss: 0.689063, acc.: 51.37%] [G loss: 0.729114]
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4850 [D loss: 0.693705, acc.: 51.56%] [G loss: 0.730764]
1/1 [==============================] - 0s 62ms/step
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4851 [D loss: 0.698773, acc.: 47.46%] [G loss: 0.732914]
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4852 [D loss: 0.689765, acc.: 49.61%] [G loss: 0.728036]
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4853 [D loss: 0.694624, acc.: 48.44%] [G loss: 0.729367]
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4854 [D loss: 0.696392, acc.: 49.02%] [G loss: 0.719038]
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4855 [D loss: 0.689210, acc.: 52.34%] [G loss: 0.716635]
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4856 [D loss: 0.695130, acc.: 47.46%] [G loss: 0.724339]
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4857 [D loss: 0.689936, acc.: 50.98%] [G loss: 0.718907]
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4858 [D loss: 0.690540, acc.: 52.73%] [G loss: 0.715762]
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4859 [D loss: 0.688937, acc.: 52.93%] [G loss: 0.721664]
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4860 [D loss: 0.692930, acc.: 51.17%] [G loss: 0.728548]
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4861 [D loss: 0.696924, acc.: 44.14%] [G loss: 0.733492]
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4862 [D loss: 0.695066, acc.: 46.29%] [G loss: 0.730879]
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4863 [D loss: 0.693008, acc.: 53.32%] [G loss: 0.742342]
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4864 [D loss: 0.685926, acc.: 56.05%] [G loss: 0.735421]
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4865 [D loss: 0.688737, acc.: 53.91%] [G loss: 0.734924]
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4866 [D loss: 0.694978, acc.: 48.63%] [G loss: 0.726247]
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4867 [D loss: 0.685938, acc.: 55.08%] [G loss: 0.728717]
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4868 [D loss: 0.694371, acc.: 48.24%] [G loss: 0.721212]
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4869 [D loss: 0.693942, acc.: 50.98%] [G loss: 0.719311]
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4870 [D loss: 0.694494, acc.: 50.20%] [G loss: 0.718275]
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4871 [D loss: 0.697782, acc.: 45.51%] [G loss: 0.719537]
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4872 [D loss: 0.699247, acc.: 50.78%] [G loss: 0.723970]
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4873 [D loss: 0.683978, acc.: 52.34%] [G loss: 0.733306]
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4874 [D loss: 0.679332, acc.: 55.47%] [G loss: 0.767549]
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4875 [D loss: 0.683387, acc.: 53.71%] [G loss: 0.769733]
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4876 [D loss: 0.690239, acc.: 50.78%] [G loss: 0.753496]
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4877 [D loss: 0.687692, acc.: 50.59%] [G loss: 0.746849]
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4878 [D loss: 0.676556, acc.: 55.47%] [G loss: 0.741661]
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4879 [D loss: 0.690156, acc.: 48.05%] [G loss: 0.724764]
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4880 [D loss: 0.686263, acc.: 49.61%] [G loss: 0.717431]
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4881 [D loss: 0.690740, acc.: 51.37%] [G loss: 0.713456]
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4882 [D loss: 0.693592, acc.: 49.22%] [G loss: 0.705945]
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4883 [D loss: 0.687167, acc.: 52.93%] [G loss: 0.703223]
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4884 [D loss: 0.686859, acc.: 50.00%] [G loss: 0.705085]
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4885 [D loss: 0.698044, acc.: 46.09%] [G loss: 0.715474]
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4886 [D loss: 0.684259, acc.: 51.56%] [G loss: 0.749498]
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4887 [D loss: 0.691322, acc.: 49.80%] [G loss: 0.745870]
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4888 [D loss: 0.690337, acc.: 51.56%] [G loss: 0.755679]
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4889 [D loss: 0.687985, acc.: 51.76%] [G loss: 0.753158]
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4890 [D loss: 0.697401, acc.: 48.44%] [G loss: 0.744530]
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4891 [D loss: 0.691329, acc.: 51.37%] [G loss: 0.738807]
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4892 [D loss: 0.696473, acc.: 46.48%] [G loss: 0.735795]
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4893 [D loss: 0.692360, acc.: 50.98%] [G loss: 0.731230]
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4894 [D loss: 0.689911, acc.: 48.63%] [G loss: 0.730998]
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4895 [D loss: 0.689537, acc.: 52.15%] [G loss: 0.728200]
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4896 [D loss: 0.691086, acc.: 51.37%] [G loss: 0.727711]
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4897 [D loss: 0.697943, acc.: 47.66%] [G loss: 0.737849]
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4898 [D loss: 0.676995, acc.: 57.42%] [G loss: 0.751007]
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4899 [D loss: 0.685710, acc.: 54.69%] [G loss: 0.753229]
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4900 [D loss: 0.688414, acc.: 53.32%] [G loss: 0.756662]
1/1 [==============================] - 0s 28ms/step
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4901 [D loss: 0.692542, acc.: 51.17%] [G loss: 0.749173]
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4902 [D loss: 0.696803, acc.: 47.27%] [G loss: 0.731475]
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4903 [D loss: 0.699106, acc.: 49.80%] [G loss: 0.728895]
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4904 [D loss: 0.693600, acc.: 49.61%] [G loss: 0.722786]
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4905 [D loss: 0.694013, acc.: 51.56%] [G loss: 0.713253]
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4906 [D loss: 0.698886, acc.: 46.88%] [G loss: 0.706599]
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4907 [D loss: 0.700305, acc.: 48.44%] [G loss: 0.693411]
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4908 [D loss: 0.703519, acc.: 46.48%] [G loss: 0.700726]
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4909 [D loss: 0.691488, acc.: 50.98%] [G loss: 0.718245]
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4910 [D loss: 0.687332, acc.: 54.30%] [G loss: 0.747160]
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4911 [D loss: 0.683451, acc.: 56.05%] [G loss: 0.773586]
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4912 [D loss: 0.691966, acc.: 53.12%] [G loss: 0.777123]
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4913 [D loss: 0.689103, acc.: 54.88%] [G loss: 0.758603]
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4914 [D loss: 0.687999, acc.: 54.30%] [G loss: 0.741287]
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4915 [D loss: 0.698345, acc.: 49.22%] [G loss: 0.731297]
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4916 [D loss: 0.697742, acc.: 50.00%] [G loss: 0.719323]
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4917 [D loss: 0.697933, acc.: 45.90%] [G loss: 0.697863]
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4918 [D loss: 0.707491, acc.: 47.46%] [G loss: 0.692649]
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4919 [D loss: 0.694739, acc.: 48.63%] [G loss: 0.716331]
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4920 [D loss: 0.687262, acc.: 50.98%] [G loss: 0.737411]
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4921 [D loss: 0.683421, acc.: 52.54%] [G loss: 0.787205]
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4922 [D loss: 0.692227, acc.: 49.61%] [G loss: 0.753847]
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4923 [D loss: 0.694625, acc.: 53.12%] [G loss: 0.737105]
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4924 [D loss: 0.691238, acc.: 51.17%] [G loss: 0.739036]
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4925 [D loss: 0.682798, acc.: 55.47%] [G loss: 0.749179]
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4926 [D loss: 0.690451, acc.: 52.15%] [G loss: 0.737036]
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4927 [D loss: 0.686964, acc.: 55.66%] [G loss: 0.734820]
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4928 [D loss: 0.694031, acc.: 46.09%] [G loss: 0.712854]
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4929 [D loss: 0.693817, acc.: 49.61%] [G loss: 0.696990]
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4930 [D loss: 0.697358, acc.: 49.02%] [G loss: 0.706618]
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4931 [D loss: 0.685333, acc.: 52.93%] [G loss: 0.730800]
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4932 [D loss: 0.688858, acc.: 50.78%] [G loss: 0.750873]
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4933 [D loss: 0.688635, acc.: 52.34%] [G loss: 0.769561]
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4934 [D loss: 0.694142, acc.: 51.95%] [G loss: 0.758028]
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4935 [D loss: 0.682812, acc.: 55.47%] [G loss: 0.736276]
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4936 [D loss: 0.685214, acc.: 53.71%] [G loss: 0.733935]
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4937 [D loss: 0.694230, acc.: 50.59%] [G loss: 0.736032]
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4938 [D loss: 0.693814, acc.: 49.61%] [G loss: 0.742341]
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4939 [D loss: 0.697979, acc.: 46.09%] [G loss: 0.731974]
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4940 [D loss: 0.690432, acc.: 46.68%] [G loss: 0.728886]
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4941 [D loss: 0.687385, acc.: 52.54%] [G loss: 0.723862]
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4942 [D loss: 0.682568, acc.: 55.86%] [G loss: 0.724937]
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4943 [D loss: 0.682282, acc.: 54.10%] [G loss: 0.746869]
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4944 [D loss: 0.684828, acc.: 55.47%] [G loss: 0.742020]
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4945 [D loss: 0.680202, acc.: 57.03%] [G loss: 0.760613]
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4946 [D loss: 0.698617, acc.: 48.05%] [G loss: 0.764465]
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4947 [D loss: 0.690970, acc.: 50.78%] [G loss: 0.738401]
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4948 [D loss: 0.697038, acc.: 52.93%] [G loss: 0.734618]
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4949 [D loss: 0.697398, acc.: 47.66%] [G loss: 0.714480]
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4950 [D loss: 0.702635, acc.: 47.27%] [G loss: 0.715747]
1/1 [==============================] - 0s 30ms/step
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4951 [D loss: 0.703771, acc.: 47.27%] [G loss: 0.706351]
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4952 [D loss: 0.703439, acc.: 45.31%] [G loss: 0.701551]
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4953 [D loss: 0.701996, acc.: 49.80%] [G loss: 0.708420]
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4954 [D loss: 0.692851, acc.: 52.15%] [G loss: 0.701649]
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4955 [D loss: 0.703246, acc.: 44.92%] [G loss: 0.707498]
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4956 [D loss: 0.697016, acc.: 49.80%] [G loss: 0.704513]
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4957 [D loss: 0.696570, acc.: 47.27%] [G loss: 0.712954]
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4958 [D loss: 0.689291, acc.: 52.54%] [G loss: 0.714130]
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4959 [D loss: 0.693085, acc.: 51.56%] [G loss: 0.718819]
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4960 [D loss: 0.689621, acc.: 53.52%] [G loss: 0.717387]
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4961 [D loss: 0.687113, acc.: 54.49%] [G loss: 0.720165]
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4962 [D loss: 0.690157, acc.: 54.69%] [G loss: 0.718738]
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4963 [D loss: 0.698655, acc.: 47.07%] [G loss: 0.727920]
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4964 [D loss: 0.694704, acc.: 47.66%] [G loss: 0.732230]
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4965 [D loss: 0.692973, acc.: 50.78%] [G loss: 0.724090]
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4966 [D loss: 0.687881, acc.: 50.20%] [G loss: 0.728426]
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4967 [D loss: 0.684443, acc.: 52.54%] [G loss: 0.726166]
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4968 [D loss: 0.690723, acc.: 50.20%] [G loss: 0.726600]
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4969 [D loss: 0.688296, acc.: 55.66%] [G loss: 0.727428]
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4970 [D loss: 0.687761, acc.: 53.52%] [G loss: 0.728530]
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4971 [D loss: 0.688134, acc.: 53.91%] [G loss: 0.735666]
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4972 [D loss: 0.684745, acc.: 53.52%] [G loss: 0.729279]
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4973 [D loss: 0.691393, acc.: 51.56%] [G loss: 0.741994]
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4974 [D loss: 0.682111, acc.: 57.03%] [G loss: 0.746906]
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4975 [D loss: 0.688133, acc.: 49.61%] [G loss: 0.738004]
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4976 [D loss: 0.685294, acc.: 51.76%] [G loss: 0.729762]
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4977 [D loss: 0.690760, acc.: 52.93%] [G loss: 0.725637]
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4978 [D loss: 0.685252, acc.: 52.93%] [G loss: 0.731379]
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4979 [D loss: 0.688597, acc.: 49.61%] [G loss: 0.723232]
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4980 [D loss: 0.688871, acc.: 50.98%] [G loss: 0.727222]
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4981 [D loss: 0.703335, acc.: 42.38%] [G loss: 0.718134]
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4982 [D loss: 0.698432, acc.: 47.07%] [G loss: 0.709219]
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4983 [D loss: 0.686194, acc.: 52.93%] [G loss: 0.719182]
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4984 [D loss: 0.695793, acc.: 48.44%] [G loss: 0.711020]
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4985 [D loss: 0.688508, acc.: 50.20%] [G loss: 0.727904]
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4986 [D loss: 0.690351, acc.: 49.02%] [G loss: 0.729625]
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4987 [D loss: 0.685738, acc.: 54.10%] [G loss: 0.730426]
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4988 [D loss: 0.684311, acc.: 48.44%] [G loss: 0.722858]
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4989 [D loss: 0.698282, acc.: 50.00%] [G loss: 0.732961]
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4990 [D loss: 0.689897, acc.: 53.12%] [G loss: 0.736505]
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4991 [D loss: 0.695850, acc.: 48.83%] [G loss: 0.750442]
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4992 [D loss: 0.694138, acc.: 48.83%] [G loss: 0.743574]
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4993 [D loss: 0.696026, acc.: 51.37%] [G loss: 0.740669]
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4994 [D loss: 0.696142, acc.: 46.88%] [G loss: 0.742469]
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4995 [D loss: 0.681248, acc.: 54.30%] [G loss: 0.731892]
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4996 [D loss: 0.695212, acc.: 47.46%] [G loss: 0.724513]
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4997 [D loss: 0.695616, acc.: 48.05%] [G loss: 0.717831]
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4998 [D loss: 0.688437, acc.: 54.88%] [G loss: 0.713102]
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4999 [D loss: 0.691902, acc.: 51.37%] [G loss: 0.697226]
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5000 [D loss: 0.710757, acc.: 45.12%] [G loss: 0.693039]
1/1 [==============================] - 0s 25ms/step
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5001 [D loss: 0.702348, acc.: 46.88%] [G loss: 0.710510]
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5002 [D loss: 0.700271, acc.: 46.68%] [G loss: 0.723601]
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5003 [D loss: 0.695423, acc.: 50.78%] [G loss: 0.730197]
8/8 [==============================] - 0s 4ms/step
5004 [D loss: 0.695181, acc.: 50.00%] [G loss: 0.728367]
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5005 [D loss: 0.697019, acc.: 47.46%] [G loss: 0.737064]
8/8 [==============================] - 0s 4ms/step
5006 [D loss: 0.689932, acc.: 54.10%] [G loss: 0.743285]
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5007 [D loss: 0.686478, acc.: 54.88%] [G loss: 0.746171]
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5008 [D loss: 0.684676, acc.: 56.25%] [G loss: 0.736660]
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5009 [D loss: 0.686840, acc.: 56.05%] [G loss: 0.739399]
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5010 [D loss: 0.694052, acc.: 49.22%] [G loss: 0.738043]
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5011 [D loss: 0.688889, acc.: 53.12%] [G loss: 0.735713]
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5012 [D loss: 0.682103, acc.: 56.25%] [G loss: 0.728841]
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5013 [D loss: 0.695261, acc.: 50.59%] [G loss: 0.718826]
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5014 [D loss: 0.702401, acc.: 43.75%] [G loss: 0.729192]
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5015 [D loss: 0.698853, acc.: 45.51%] [G loss: 0.720253]
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5016 [D loss: 0.698831, acc.: 48.44%] [G loss: 0.734739]
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5017 [D loss: 0.703998, acc.: 47.07%] [G loss: 0.726371]
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5018 [D loss: 0.703358, acc.: 45.12%] [G loss: 0.729946]
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5019 [D loss: 0.700373, acc.: 46.88%] [G loss: 0.722573]
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5020 [D loss: 0.699761, acc.: 48.63%] [G loss: 0.717789]
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5021 [D loss: 0.697477, acc.: 50.20%] [G loss: 0.719166]
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5022 [D loss: 0.699390, acc.: 48.44%] [G loss: 0.725757]
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5023 [D loss: 0.690994, acc.: 51.95%] [G loss: 0.726552]
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5024 [D loss: 0.697787, acc.: 43.36%] [G loss: 0.720045]
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5025 [D loss: 0.689645, acc.: 51.37%] [G loss: 0.714392]
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5026 [D loss: 0.688464, acc.: 54.69%] [G loss: 0.724702]
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5027 [D loss: 0.690991, acc.: 51.37%] [G loss: 0.730994]
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5028 [D loss: 0.687659, acc.: 52.73%] [G loss: 0.731247]
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5029 [D loss: 0.693339, acc.: 51.17%] [G loss: 0.730490]
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5030 [D loss: 0.690975, acc.: 51.56%] [G loss: 0.734320]
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5031 [D loss: 0.693540, acc.: 50.00%] [G loss: 0.731346]
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5032 [D loss: 0.693273, acc.: 48.63%] [G loss: 0.717205]
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5033 [D loss: 0.692977, acc.: 52.73%] [G loss: 0.717800]
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5034 [D loss: 0.688387, acc.: 53.32%] [G loss: 0.718134]
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5035 [D loss: 0.692236, acc.: 52.54%] [G loss: 0.705702]
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5036 [D loss: 0.692393, acc.: 50.98%] [G loss: 0.708976]
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5037 [D loss: 0.693547, acc.: 48.44%] [G loss: 0.703962]
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5038 [D loss: 0.697168, acc.: 50.78%] [G loss: 0.705514]
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5039 [D loss: 0.688070, acc.: 51.95%] [G loss: 0.716179]
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5040 [D loss: 0.692101, acc.: 51.17%] [G loss: 0.732949]
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5041 [D loss: 0.689560, acc.: 53.32%] [G loss: 0.740146]
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5042 [D loss: 0.688120, acc.: 56.45%] [G loss: 0.743454]
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5043 [D loss: 0.691922, acc.: 51.76%] [G loss: 0.733132]
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5044 [D loss: 0.693606, acc.: 50.20%] [G loss: 0.730770]
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5045 [D loss: 0.696973, acc.: 46.48%] [G loss: 0.728942]
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5046 [D loss: 0.692653, acc.: 50.20%] [G loss: 0.717548]
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5047 [D loss: 0.685909, acc.: 52.73%] [G loss: 0.713410]
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5048 [D loss: 0.694919, acc.: 49.41%] [G loss: 0.709345]
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5049 [D loss: 0.693447, acc.: 45.70%] [G loss: 0.719155]
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5050 [D loss: 0.696613, acc.: 49.02%] [G loss: 0.700221]
1/1 [==============================] - 0s 25ms/step
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5051 [D loss: 0.696388, acc.: 46.68%] [G loss: 0.723076]
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5052 [D loss: 0.695451, acc.: 47.66%] [G loss: 0.728025]
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5053 [D loss: 0.685215, acc.: 54.10%] [G loss: 0.734190]
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5054 [D loss: 0.686924, acc.: 52.15%] [G loss: 0.741720]
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5055 [D loss: 0.682289, acc.: 56.25%] [G loss: 0.741450]
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5056 [D loss: 0.686030, acc.: 53.32%] [G loss: 0.738670]
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5057 [D loss: 0.687276, acc.: 54.10%] [G loss: 0.735332]
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5058 [D loss: 0.680787, acc.: 58.20%] [G loss: 0.730476]
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5059 [D loss: 0.689296, acc.: 48.83%] [G loss: 0.722916]
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5060 [D loss: 0.697595, acc.: 47.46%] [G loss: 0.713949]
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5061 [D loss: 0.699439, acc.: 47.46%] [G loss: 0.713843]
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5062 [D loss: 0.697105, acc.: 52.15%] [G loss: 0.725199]
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5063 [D loss: 0.690959, acc.: 50.59%] [G loss: 0.733516]
8/8 [==============================] - 0s 4ms/step
5064 [D loss: 0.683666, acc.: 53.71%] [G loss: 0.749287]
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5065 [D loss: 0.689210, acc.: 50.39%] [G loss: 0.746493]
8/8 [==============================] - 0s 4ms/step
5066 [D loss: 0.689847, acc.: 51.56%] [G loss: 0.740271]
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5067 [D loss: 0.694064, acc.: 48.63%] [G loss: 0.735907]
8/8 [==============================] - 0s 4ms/step
5068 [D loss: 0.679953, acc.: 56.84%] [G loss: 0.747379]
8/8 [==============================] - 0s 4ms/step
5069 [D loss: 0.678614, acc.: 57.81%] [G loss: 0.733629]
8/8 [==============================] - 0s 4ms/step
5070 [D loss: 0.683614, acc.: 54.10%] [G loss: 0.726072]
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5071 [D loss: 0.690137, acc.: 50.20%] [G loss: 0.707788]
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5072 [D loss: 0.689766, acc.: 50.59%] [G loss: 0.702965]
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5073 [D loss: 0.684995, acc.: 53.52%] [G loss: 0.708112]
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5074 [D loss: 0.693041, acc.: 50.00%] [G loss: 0.709024]
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5075 [D loss: 0.688743, acc.: 53.52%] [G loss: 0.726028]
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5076 [D loss: 0.684167, acc.: 55.47%] [G loss: 0.723868]
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5077 [D loss: 0.680252, acc.: 56.25%] [G loss: 0.743736]
8/8 [==============================] - 0s 4ms/step
5078 [D loss: 0.690370, acc.: 49.02%] [G loss: 0.732379]
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5079 [D loss: 0.687107, acc.: 50.00%] [G loss: 0.722827]
8/8 [==============================] - 0s 4ms/step
5080 [D loss: 0.687560, acc.: 47.46%] [G loss: 0.722295]
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5081 [D loss: 0.692119, acc.: 45.51%] [G loss: 0.716830]
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5082 [D loss: 0.694170, acc.: 46.09%] [G loss: 0.712687]
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5083 [D loss: 0.694357, acc.: 46.68%] [G loss: 0.719315]
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5084 [D loss: 0.692272, acc.: 47.66%] [G loss: 0.715469]
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5085 [D loss: 0.690159, acc.: 50.78%] [G loss: 0.712057]
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5086 [D loss: 0.701967, acc.: 44.34%] [G loss: 0.718160]
8/8 [==============================] - 0s 4ms/step
5087 [D loss: 0.701390, acc.: 46.48%] [G loss: 0.734998]
8/8 [==============================] - 0s 4ms/step
5088 [D loss: 0.695728, acc.: 53.52%] [G loss: 0.737482]
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5089 [D loss: 0.691361, acc.: 52.54%] [G loss: 0.750765]
8/8 [==============================] - 0s 4ms/step
5090 [D loss: 0.689969, acc.: 49.41%] [G loss: 0.751274]
8/8 [==============================] - 0s 4ms/step
5091 [D loss: 0.689318, acc.: 50.98%] [G loss: 0.761946]
8/8 [==============================] - 0s 4ms/step
5092 [D loss: 0.687252, acc.: 50.20%] [G loss: 0.740221]
8/8 [==============================] - 0s 4ms/step
5093 [D loss: 0.694965, acc.: 53.12%] [G loss: 0.732161]
8/8 [==============================] - 0s 4ms/step
5094 [D loss: 0.695965, acc.: 51.17%] [G loss: 0.721108]
8/8 [==============================] - 0s 4ms/step
5095 [D loss: 0.694155, acc.: 49.41%] [G loss: 0.713427]
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5096 [D loss: 0.693907, acc.: 48.63%] [G loss: 0.708483]
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5097 [D loss: 0.696564, acc.: 51.37%] [G loss: 0.696688]
8/8 [==============================] - 0s 4ms/step
5098 [D loss: 0.708745, acc.: 43.36%] [G loss: 0.704926]
8/8 [==============================] - 0s 4ms/step
5099 [D loss: 0.704148, acc.: 44.34%] [G loss: 0.723576]
8/8 [==============================] - 0s 4ms/step
5100 [D loss: 0.693490, acc.: 49.61%] [G loss: 0.735442]
1/1 [==============================] - 0s 27ms/step
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5101 [D loss: 0.686422, acc.: 54.69%] [G loss: 0.754620]
8/8 [==============================] - 0s 4ms/step
5102 [D loss: 0.688881, acc.: 55.27%] [G loss: 0.759178]
8/8 [==============================] - 0s 4ms/step
5103 [D loss: 0.693393, acc.: 52.15%] [G loss: 0.744992]
8/8 [==============================] - 0s 5ms/step
5104 [D loss: 0.688463, acc.: 54.69%] [G loss: 0.744148]
8/8 [==============================] - 0s 4ms/step
5105 [D loss: 0.691821, acc.: 53.91%] [G loss: 0.729801]
8/8 [==============================] - 0s 4ms/step
5106 [D loss: 0.687708, acc.: 53.91%] [G loss: 0.729000]
8/8 [==============================] - 0s 4ms/step
5107 [D loss: 0.691720, acc.: 53.71%] [G loss: 0.713954]
8/8 [==============================] - 0s 4ms/step
5108 [D loss: 0.691809, acc.: 49.41%] [G loss: 0.699933]
8/8 [==============================] - 0s 4ms/step
5109 [D loss: 0.689389, acc.: 52.93%] [G loss: 0.710760]
8/8 [==============================] - 0s 4ms/step
5110 [D loss: 0.694118, acc.: 51.37%] [G loss: 0.714544]
8/8 [==============================] - 0s 4ms/step
5111 [D loss: 0.686345, acc.: 54.30%] [G loss: 0.736914]
8/8 [==============================] - 0s 4ms/step
5112 [D loss: 0.682176, acc.: 54.10%] [G loss: 0.743208]
8/8 [==============================] - 0s 4ms/step
5113 [D loss: 0.685040, acc.: 51.76%] [G loss: 0.753315]
8/8 [==============================] - 0s 4ms/step
5114 [D loss: 0.694562, acc.: 47.27%] [G loss: 0.735978]
8/8 [==============================] - 0s 4ms/step
5115 [D loss: 0.693149, acc.: 50.39%] [G loss: 0.730284]
8/8 [==============================] - 0s 4ms/step
5116 [D loss: 0.684419, acc.: 54.88%] [G loss: 0.729225]
8/8 [==============================] - 0s 4ms/step
5117 [D loss: 0.692248, acc.: 48.83%] [G loss: 0.723687]
8/8 [==============================] - 0s 4ms/step
5118 [D loss: 0.691468, acc.: 49.41%] [G loss: 0.706172]
8/8 [==============================] - 0s 4ms/step
5119 [D loss: 0.700198, acc.: 47.66%] [G loss: 0.709794]
8/8 [==============================] - 0s 4ms/step
5120 [D loss: 0.689142, acc.: 52.15%] [G loss: 0.725502]
8/8 [==============================] - 0s 4ms/step
5121 [D loss: 0.688382, acc.: 49.41%] [G loss: 0.728719]
8/8 [==============================] - 0s 4ms/step
5122 [D loss: 0.684832, acc.: 50.59%] [G loss: 0.740564]
8/8 [==============================] - 0s 4ms/step
5123 [D loss: 0.694039, acc.: 48.24%] [G loss: 0.749536]
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5124 [D loss: 0.702643, acc.: 45.70%] [G loss: 0.741800]
8/8 [==============================] - 0s 4ms/step
5125 [D loss: 0.685293, acc.: 50.98%] [G loss: 0.740410]
8/8 [==============================] - 0s 4ms/step
5126 [D loss: 0.698876, acc.: 49.22%] [G loss: 0.733510]
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5127 [D loss: 0.696424, acc.: 45.12%] [G loss: 0.734117]
8/8 [==============================] - 0s 4ms/step
5128 [D loss: 0.693637, acc.: 50.78%] [G loss: 0.723173]
8/8 [==============================] - 0s 4ms/step
5129 [D loss: 0.694106, acc.: 49.22%] [G loss: 0.741862]
8/8 [==============================] - 0s 4ms/step
5130 [D loss: 0.692987, acc.: 48.83%] [G loss: 0.726605]
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5131 [D loss: 0.693332, acc.: 48.24%] [G loss: 0.744271]
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5132 [D loss: 0.691831, acc.: 52.15%] [G loss: 0.744830]
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5133 [D loss: 0.686386, acc.: 51.37%] [G loss: 0.764270]
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5134 [D loss: 0.684266, acc.: 55.27%] [G loss: 0.775799]
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5135 [D loss: 0.686305, acc.: 50.00%] [G loss: 0.768323]
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5136 [D loss: 0.686116, acc.: 50.39%] [G loss: 0.758128]
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5137 [D loss: 0.685381, acc.: 52.54%] [G loss: 0.739082]
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5138 [D loss: 0.688903, acc.: 51.95%] [G loss: 0.729117]
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5139 [D loss: 0.701649, acc.: 46.09%] [G loss: 0.720048]
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5140 [D loss: 0.696859, acc.: 49.22%] [G loss: 0.709733]
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5141 [D loss: 0.699042, acc.: 50.59%] [G loss: 0.704377]
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5142 [D loss: 0.698382, acc.: 46.68%] [G loss: 0.720542]
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5143 [D loss: 0.698077, acc.: 47.27%] [G loss: 0.725489]
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5144 [D loss: 0.685425, acc.: 50.98%] [G loss: 0.735530]
8/8 [==============================] - 0s 4ms/step
5145 [D loss: 0.688836, acc.: 49.22%] [G loss: 0.746785]
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5146 [D loss: 0.690576, acc.: 52.54%] [G loss: 0.740778]
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5147 [D loss: 0.685907, acc.: 55.27%] [G loss: 0.740098]
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5148 [D loss: 0.677769, acc.: 59.77%] [G loss: 0.745779]
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5149 [D loss: 0.677199, acc.: 58.59%] [G loss: 0.741266]
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5150 [D loss: 0.687698, acc.: 51.95%] [G loss: 0.718361]
1/1 [==============================] - 0s 30ms/step
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5151 [D loss: 0.700632, acc.: 49.80%] [G loss: 0.708704]
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5152 [D loss: 0.701066, acc.: 45.70%] [G loss: 0.706620]
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5153 [D loss: 0.702925, acc.: 45.51%] [G loss: 0.711403]
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5154 [D loss: 0.691611, acc.: 50.00%] [G loss: 0.722806]
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5155 [D loss: 0.694187, acc.: 46.68%] [G loss: 0.737213]
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5156 [D loss: 0.694878, acc.: 48.44%] [G loss: 0.750131]
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5157 [D loss: 0.693501, acc.: 48.83%] [G loss: 0.749721]
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5158 [D loss: 0.677512, acc.: 57.62%] [G loss: 0.746518]
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5159 [D loss: 0.682948, acc.: 53.32%] [G loss: 0.753603]
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5160 [D loss: 0.684547, acc.: 51.17%] [G loss: 0.741904]
8/8 [==============================] - 0s 4ms/step
5161 [D loss: 0.687800, acc.: 49.02%] [G loss: 0.728118]
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5162 [D loss: 0.690998, acc.: 49.02%] [G loss: 0.715526]
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5163 [D loss: 0.687843, acc.: 49.02%] [G loss: 0.715625]
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5164 [D loss: 0.694694, acc.: 48.44%] [G loss: 0.711381]
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5165 [D loss: 0.704968, acc.: 45.70%] [G loss: 0.716093]
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5166 [D loss: 0.699558, acc.: 45.12%] [G loss: 0.720232]
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5167 [D loss: 0.689418, acc.: 49.61%] [G loss: 0.729453]
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5168 [D loss: 0.686402, acc.: 48.05%] [G loss: 0.739784]
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5169 [D loss: 0.693200, acc.: 46.88%] [G loss: 0.741352]
8/8 [==============================] - 0s 4ms/step
5170 [D loss: 0.685083, acc.: 50.00%] [G loss: 0.747904]
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5171 [D loss: 0.678543, acc.: 57.23%] [G loss: 0.747810]
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5172 [D loss: 0.685897, acc.: 49.80%] [G loss: 0.735754]
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5173 [D loss: 0.675557, acc.: 58.20%] [G loss: 0.738580]
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5174 [D loss: 0.690177, acc.: 51.37%] [G loss: 0.735533]
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5175 [D loss: 0.688544, acc.: 50.98%] [G loss: 0.723559]
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5176 [D loss: 0.689301, acc.: 50.39%] [G loss: 0.715402]
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5177 [D loss: 0.704189, acc.: 45.51%] [G loss: 0.705753]
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5178 [D loss: 0.703785, acc.: 46.29%] [G loss: 0.716218]
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5179 [D loss: 0.700276, acc.: 46.29%] [G loss: 0.736079]
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5180 [D loss: 0.690103, acc.: 50.39%] [G loss: 0.760137]
8/8 [==============================] - 0s 4ms/step
5181 [D loss: 0.687162, acc.: 51.37%] [G loss: 0.764835]
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5182 [D loss: 0.691073, acc.: 50.39%] [G loss: 0.760174]
8/8 [==============================] - 0s 4ms/step
5183 [D loss: 0.698421, acc.: 46.09%] [G loss: 0.747759]
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5184 [D loss: 0.688157, acc.: 55.08%] [G loss: 0.738363]
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5185 [D loss: 0.689379, acc.: 55.08%] [G loss: 0.736230]
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5186 [D loss: 0.677830, acc.: 55.66%] [G loss: 0.741563]
8/8 [==============================] - 0s 4ms/step
5187 [D loss: 0.685233, acc.: 56.45%] [G loss: 0.740665]
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5188 [D loss: 0.684843, acc.: 54.49%] [G loss: 0.718740]
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5189 [D loss: 0.687641, acc.: 56.64%] [G loss: 0.712776]
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5190 [D loss: 0.687900, acc.: 53.32%] [G loss: 0.727892]
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5191 [D loss: 0.685391, acc.: 56.25%] [G loss: 0.726104]
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5192 [D loss: 0.697337, acc.: 51.56%] [G loss: 0.729429]
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5193 [D loss: 0.697997, acc.: 48.44%] [G loss: 0.726608]
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5194 [D loss: 0.693450, acc.: 45.12%] [G loss: 0.711940]
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5195 [D loss: 0.697748, acc.: 46.68%] [G loss: 0.703276]
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5196 [D loss: 0.695105, acc.: 48.63%] [G loss: 0.708810]
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5197 [D loss: 0.693042, acc.: 46.88%] [G loss: 0.714653]
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5198 [D loss: 0.689834, acc.: 52.34%] [G loss: 0.716804]
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5199 [D loss: 0.693598, acc.: 52.34%] [G loss: 0.726174]
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5200 [D loss: 0.693895, acc.: 51.56%] [G loss: 0.728907]
1/1 [==============================] - 0s 32ms/step
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5201 [D loss: 0.686117, acc.: 53.12%] [G loss: 0.722906]
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5202 [D loss: 0.690139, acc.: 50.59%] [G loss: 0.722863]
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5203 [D loss: 0.688400, acc.: 53.91%] [G loss: 0.733775]
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5204 [D loss: 0.686451, acc.: 55.27%] [G loss: 0.719943]
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5205 [D loss: 0.684935, acc.: 56.05%] [G loss: 0.721434]
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5206 [D loss: 0.697653, acc.: 45.31%] [G loss: 0.720600]
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5207 [D loss: 0.701139, acc.: 46.09%] [G loss: 0.721893]
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5208 [D loss: 0.693498, acc.: 47.85%] [G loss: 0.729236]
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5209 [D loss: 0.687009, acc.: 49.22%] [G loss: 0.732171]
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5210 [D loss: 0.686210, acc.: 51.17%] [G loss: 0.739414]
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5211 [D loss: 0.680903, acc.: 56.25%] [G loss: 0.750847]
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5212 [D loss: 0.683895, acc.: 52.93%] [G loss: 0.761922]
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5213 [D loss: 0.678094, acc.: 56.64%] [G loss: 0.762211]
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5214 [D loss: 0.684616, acc.: 54.49%] [G loss: 0.748478]
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5215 [D loss: 0.687283, acc.: 53.71%] [G loss: 0.738776]
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5216 [D loss: 0.684309, acc.: 53.52%] [G loss: 0.736634]
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5217 [D loss: 0.696147, acc.: 50.59%] [G loss: 0.728357]
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5218 [D loss: 0.690072, acc.: 49.22%] [G loss: 0.721127]
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5219 [D loss: 0.697546, acc.: 44.14%] [G loss: 0.710788]
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5220 [D loss: 0.698705, acc.: 45.51%] [G loss: 0.724368]
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5221 [D loss: 0.692256, acc.: 49.80%] [G loss: 0.731797]
8/8 [==============================] - 0s 4ms/step
5222 [D loss: 0.690649, acc.: 47.07%] [G loss: 0.743353]
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5223 [D loss: 0.689273, acc.: 53.32%] [G loss: 0.732398]
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5224 [D loss: 0.693230, acc.: 52.54%] [G loss: 0.729084]
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5225 [D loss: 0.688091, acc.: 56.05%] [G loss: 0.734950]
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5226 [D loss: 0.691144, acc.: 51.95%] [G loss: 0.736352]
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5227 [D loss: 0.692570, acc.: 51.37%] [G loss: 0.730998]
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5228 [D loss: 0.691171, acc.: 49.02%] [G loss: 0.723465]
8/8 [==============================] - 0s 4ms/step
5229 [D loss: 0.685472, acc.: 53.52%] [G loss: 0.732053]
8/8 [==============================] - 0s 4ms/step
5230 [D loss: 0.691357, acc.: 51.76%] [G loss: 0.714278]
8/8 [==============================] - 0s 4ms/step
5231 [D loss: 0.688802, acc.: 49.80%] [G loss: 0.719370]
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5232 [D loss: 0.695639, acc.: 49.02%] [G loss: 0.726781]
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5233 [D loss: 0.700693, acc.: 48.24%] [G loss: 0.728541]
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5234 [D loss: 0.692861, acc.: 48.05%] [G loss: 0.730654]
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5235 [D loss: 0.694684, acc.: 49.80%] [G loss: 0.733542]
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5236 [D loss: 0.701221, acc.: 48.05%] [G loss: 0.730788]
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5237 [D loss: 0.695504, acc.: 48.83%] [G loss: 0.722572]
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5238 [D loss: 0.695040, acc.: 49.41%] [G loss: 0.725042]
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5239 [D loss: 0.689668, acc.: 48.83%] [G loss: 0.722606]
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5240 [D loss: 0.693139, acc.: 50.00%] [G loss: 0.712115]
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5241 [D loss: 0.689545, acc.: 53.71%] [G loss: 0.713184]
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5242 [D loss: 0.703416, acc.: 48.63%] [G loss: 0.725710]
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5243 [D loss: 0.691582, acc.: 50.59%] [G loss: 0.735891]
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5244 [D loss: 0.691016, acc.: 49.80%] [G loss: 0.729369]
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5245 [D loss: 0.692927, acc.: 50.78%] [G loss: 0.726181]
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5246 [D loss: 0.698171, acc.: 47.66%] [G loss: 0.714245]
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5247 [D loss: 0.696253, acc.: 45.90%] [G loss: 0.709493]
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5248 [D loss: 0.709017, acc.: 42.97%] [G loss: 0.705229]
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5249 [D loss: 0.705062, acc.: 44.53%] [G loss: 0.706515]
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5250 [D loss: 0.701184, acc.: 45.90%] [G loss: 0.711553]
1/1 [==============================] - 0s 28ms/step
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5251 [D loss: 0.696881, acc.: 48.83%] [G loss: 0.712959]
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5252 [D loss: 0.695158, acc.: 48.05%] [G loss: 0.723324]
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5253 [D loss: 0.694072, acc.: 49.80%] [G loss: 0.724336]
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5254 [D loss: 0.690889, acc.: 54.69%] [G loss: 0.727901]
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5255 [D loss: 0.688784, acc.: 54.49%] [G loss: 0.739285]
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5256 [D loss: 0.689593, acc.: 50.59%] [G loss: 0.740834]
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5257 [D loss: 0.687901, acc.: 55.66%] [G loss: 0.735250]
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5258 [D loss: 0.686653, acc.: 53.71%] [G loss: 0.729819]
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5259 [D loss: 0.692096, acc.: 50.00%] [G loss: 0.731636]
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5260 [D loss: 0.688631, acc.: 51.76%] [G loss: 0.721711]
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5261 [D loss: 0.691834, acc.: 52.73%] [G loss: 0.726636]
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5262 [D loss: 0.692279, acc.: 55.47%] [G loss: 0.719929]
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5263 [D loss: 0.696122, acc.: 49.22%] [G loss: 0.729102]
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5264 [D loss: 0.686465, acc.: 52.73%] [G loss: 0.734872]
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5265 [D loss: 0.693220, acc.: 50.00%] [G loss: 0.749822]
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5266 [D loss: 0.694979, acc.: 49.61%] [G loss: 0.749532]
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5267 [D loss: 0.692002, acc.: 53.71%] [G loss: 0.759977]
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5268 [D loss: 0.699869, acc.: 51.17%] [G loss: 0.739972]
8/8 [==============================] - 0s 4ms/step
5269 [D loss: 0.697561, acc.: 49.61%] [G loss: 0.733280]
8/8 [==============================] - 0s 4ms/step
5270 [D loss: 0.695458, acc.: 52.93%] [G loss: 0.734658]
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5271 [D loss: 0.686060, acc.: 54.10%] [G loss: 0.743770]
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5272 [D loss: 0.692540, acc.: 52.73%] [G loss: 0.729283]
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5273 [D loss: 0.687303, acc.: 53.32%] [G loss: 0.730732]
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5274 [D loss: 0.688848, acc.: 54.69%] [G loss: 0.738842]
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5275 [D loss: 0.683665, acc.: 55.08%] [G loss: 0.743370]
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5276 [D loss: 0.682308, acc.: 51.95%] [G loss: 0.743329]
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5277 [D loss: 0.682529, acc.: 53.32%] [G loss: 0.744635]
8/8 [==============================] - 0s 4ms/step
5278 [D loss: 0.691490, acc.: 49.41%] [G loss: 0.731940]
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5279 [D loss: 0.688226, acc.: 52.34%] [G loss: 0.734818]
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5280 [D loss: 0.695722, acc.: 48.44%] [G loss: 0.726908]
8/8 [==============================] - 0s 4ms/step
5281 [D loss: 0.696629, acc.: 45.70%] [G loss: 0.719790]
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5282 [D loss: 0.694019, acc.: 48.83%] [G loss: 0.713645]
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5283 [D loss: 0.705890, acc.: 42.97%] [G loss: 0.707697]
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5284 [D loss: 0.700252, acc.: 43.16%] [G loss: 0.703162]
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5285 [D loss: 0.698160, acc.: 46.48%] [G loss: 0.716164]
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5286 [D loss: 0.692133, acc.: 48.44%] [G loss: 0.736402]
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5287 [D loss: 0.688877, acc.: 51.76%] [G loss: 0.752402]
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5288 [D loss: 0.687235, acc.: 50.20%] [G loss: 0.754870]
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5289 [D loss: 0.693164, acc.: 49.80%] [G loss: 0.755722]
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5290 [D loss: 0.687936, acc.: 50.00%] [G loss: 0.738738]
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5291 [D loss: 0.683223, acc.: 57.42%] [G loss: 0.751782]
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5292 [D loss: 0.680897, acc.: 57.42%] [G loss: 0.739818]
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5293 [D loss: 0.680638, acc.: 54.49%] [G loss: 0.731657]
8/8 [==============================] - 0s 4ms/step
5294 [D loss: 0.693740, acc.: 50.20%] [G loss: 0.715434]
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5295 [D loss: 0.694539, acc.: 50.98%] [G loss: 0.710320]
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5296 [D loss: 0.693211, acc.: 50.00%] [G loss: 0.726983]
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5297 [D loss: 0.695945, acc.: 49.80%] [G loss: 0.733703]
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5298 [D loss: 0.686371, acc.: 51.17%] [G loss: 0.741781]
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5299 [D loss: 0.691649, acc.: 49.22%] [G loss: 0.747316]
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5300 [D loss: 0.688400, acc.: 51.95%] [G loss: 0.722820]
1/1 [==============================] - 0s 27ms/step
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5301 [D loss: 0.691523, acc.: 52.73%] [G loss: 0.724037]
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5302 [D loss: 0.695959, acc.: 50.20%] [G loss: 0.716083]
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5303 [D loss: 0.700451, acc.: 47.27%] [G loss: 0.707429]
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5304 [D loss: 0.691874, acc.: 48.44%] [G loss: 0.703243]
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5305 [D loss: 0.695894, acc.: 48.44%] [G loss: 0.701397]
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5306 [D loss: 0.697682, acc.: 46.68%] [G loss: 0.708198]
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5307 [D loss: 0.695532, acc.: 47.66%] [G loss: 0.725210]
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5308 [D loss: 0.685543, acc.: 52.54%] [G loss: 0.756160]
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5309 [D loss: 0.684811, acc.: 53.32%] [G loss: 0.769549]
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5310 [D loss: 0.678887, acc.: 53.32%] [G loss: 0.765266]
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5311 [D loss: 0.688044, acc.: 53.12%] [G loss: 0.766112]
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5312 [D loss: 0.685644, acc.: 51.17%] [G loss: 0.739994]
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5313 [D loss: 0.691630, acc.: 52.73%] [G loss: 0.732068]
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5314 [D loss: 0.685810, acc.: 54.30%] [G loss: 0.734443]
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5315 [D loss: 0.689823, acc.: 52.54%] [G loss: 0.711358]
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5316 [D loss: 0.694631, acc.: 50.98%] [G loss: 0.697870]
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5317 [D loss: 0.698909, acc.: 47.27%] [G loss: 0.692355]
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5318 [D loss: 0.704922, acc.: 45.31%] [G loss: 0.712937]
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5319 [D loss: 0.698986, acc.: 48.44%] [G loss: 0.735481]
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5320 [D loss: 0.694800, acc.: 46.88%] [G loss: 0.747869]
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5321 [D loss: 0.697955, acc.: 44.92%] [G loss: 0.738725]
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5322 [D loss: 0.700989, acc.: 46.29%] [G loss: 0.735089]
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5323 [D loss: 0.694345, acc.: 48.63%] [G loss: 0.725503]
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5324 [D loss: 0.696148, acc.: 47.27%] [G loss: 0.731980]
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5325 [D loss: 0.694359, acc.: 44.53%] [G loss: 0.728579]
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5326 [D loss: 0.686481, acc.: 53.12%] [G loss: 0.735701]
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5327 [D loss: 0.686636, acc.: 51.76%] [G loss: 0.732326]
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5328 [D loss: 0.676500, acc.: 56.25%] [G loss: 0.746241]
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5329 [D loss: 0.683989, acc.: 53.71%] [G loss: 0.748956]
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5330 [D loss: 0.673358, acc.: 57.03%] [G loss: 0.752337]
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5331 [D loss: 0.681149, acc.: 53.52%] [G loss: 0.750311]
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5332 [D loss: 0.683053, acc.: 54.30%] [G loss: 0.750164]
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5333 [D loss: 0.678732, acc.: 57.23%] [G loss: 0.740922]
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5334 [D loss: 0.691957, acc.: 49.80%] [G loss: 0.731018]
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5335 [D loss: 0.682216, acc.: 51.95%] [G loss: 0.729912]
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5336 [D loss: 0.689370, acc.: 50.78%] [G loss: 0.721711]
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5337 [D loss: 0.690626, acc.: 50.59%] [G loss: 0.711451]
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5338 [D loss: 0.696761, acc.: 48.44%] [G loss: 0.707728]
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5339 [D loss: 0.686588, acc.: 50.98%] [G loss: 0.709487]
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5340 [D loss: 0.696827, acc.: 50.39%] [G loss: 0.726550]
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5341 [D loss: 0.693188, acc.: 49.02%] [G loss: 0.720088]
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5342 [D loss: 0.691591, acc.: 50.00%] [G loss: 0.715181]
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5343 [D loss: 0.697070, acc.: 47.85%] [G loss: 0.721463]
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5344 [D loss: 0.687358, acc.: 52.15%] [G loss: 0.720626]
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5345 [D loss: 0.683797, acc.: 50.78%] [G loss: 0.716202]
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5346 [D loss: 0.691240, acc.: 45.51%] [G loss: 0.718079]
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5347 [D loss: 0.690008, acc.: 50.00%] [G loss: 0.742409]
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5348 [D loss: 0.689307, acc.: 49.80%] [G loss: 0.729477]
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5349 [D loss: 0.678726, acc.: 54.30%] [G loss: 0.740812]
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5350 [D loss: 0.684918, acc.: 52.54%] [G loss: 0.731982]
1/1 [==============================] - 0s 24ms/step
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5351 [D loss: 0.686292, acc.: 51.56%] [G loss: 0.732839]
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5352 [D loss: 0.685555, acc.: 49.61%] [G loss: 0.732588]
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5353 [D loss: 0.686958, acc.: 53.91%] [G loss: 0.725737]
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5354 [D loss: 0.690732, acc.: 51.17%] [G loss: 0.725654]
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5355 [D loss: 0.682544, acc.: 49.61%] [G loss: 0.719616]
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5356 [D loss: 0.695418, acc.: 46.88%] [G loss: 0.715300]
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5357 [D loss: 0.691195, acc.: 47.85%] [G loss: 0.719301]
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5358 [D loss: 0.701237, acc.: 46.88%] [G loss: 0.700460]
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5359 [D loss: 0.702928, acc.: 48.83%] [G loss: 0.708115]
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5360 [D loss: 0.711975, acc.: 46.68%] [G loss: 0.721749]
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5361 [D loss: 0.701344, acc.: 47.46%] [G loss: 0.735346]
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5362 [D loss: 0.692824, acc.: 52.54%] [G loss: 0.743587]
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5363 [D loss: 0.694700, acc.: 50.20%] [G loss: 0.726473]
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5364 [D loss: 0.695778, acc.: 50.20%] [G loss: 0.728827]
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5365 [D loss: 0.697912, acc.: 49.41%] [G loss: 0.731386]
8/8 [==============================] - 0s 4ms/step
5366 [D loss: 0.687709, acc.: 50.98%] [G loss: 0.725083]
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5367 [D loss: 0.691464, acc.: 50.39%] [G loss: 0.723328]
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5368 [D loss: 0.689877, acc.: 53.52%] [G loss: 0.726095]
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5369 [D loss: 0.692225, acc.: 50.20%] [G loss: 0.725017]
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5370 [D loss: 0.685247, acc.: 54.69%] [G loss: 0.733818]
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5371 [D loss: 0.691571, acc.: 51.56%] [G loss: 0.714818]
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5372 [D loss: 0.681963, acc.: 58.40%] [G loss: 0.722934]
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5373 [D loss: 0.690795, acc.: 51.56%] [G loss: 0.724949]
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5374 [D loss: 0.683381, acc.: 56.05%] [G loss: 0.731076]
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5375 [D loss: 0.692737, acc.: 49.80%] [G loss: 0.725056]
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5376 [D loss: 0.699383, acc.: 49.41%] [G loss: 0.728571]
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5377 [D loss: 0.696631, acc.: 49.22%] [G loss: 0.731586]
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5378 [D loss: 0.690599, acc.: 49.80%] [G loss: 0.731714]
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5379 [D loss: 0.692040, acc.: 48.83%] [G loss: 0.734713]
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5380 [D loss: 0.692698, acc.: 50.00%] [G loss: 0.726581]
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5381 [D loss: 0.688843, acc.: 51.56%] [G loss: 0.730420]
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5382 [D loss: 0.691649, acc.: 49.22%] [G loss: 0.711156]
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5383 [D loss: 0.690763, acc.: 51.37%] [G loss: 0.722783]
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5384 [D loss: 0.697170, acc.: 47.46%] [G loss: 0.716004]
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5385 [D loss: 0.693140, acc.: 50.39%] [G loss: 0.718745]
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5386 [D loss: 0.693477, acc.: 49.02%] [G loss: 0.710013]
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5387 [D loss: 0.691264, acc.: 51.95%] [G loss: 0.718734]
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5388 [D loss: 0.689031, acc.: 50.78%] [G loss: 0.722417]
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5389 [D loss: 0.687432, acc.: 53.32%] [G loss: 0.733401]
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5390 [D loss: 0.682114, acc.: 52.54%] [G loss: 0.730945]
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5391 [D loss: 0.686353, acc.: 52.15%] [G loss: 0.733970]
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5392 [D loss: 0.688081, acc.: 49.41%] [G loss: 0.733570]
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5393 [D loss: 0.688637, acc.: 50.59%] [G loss: 0.732733]
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5394 [D loss: 0.689220, acc.: 48.83%] [G loss: 0.720272]
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5395 [D loss: 0.685511, acc.: 50.39%] [G loss: 0.722026]
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5396 [D loss: 0.690280, acc.: 49.41%] [G loss: 0.729749]
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5397 [D loss: 0.687680, acc.: 50.20%] [G loss: 0.726018]
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5398 [D loss: 0.696184, acc.: 47.27%] [G loss: 0.729236]
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5399 [D loss: 0.691850, acc.: 50.20%] [G loss: 0.728843]
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5400 [D loss: 0.690397, acc.: 49.41%] [G loss: 0.735934]
1/1 [==============================] - 0s 27ms/step
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5401 [D loss: 0.698016, acc.: 48.83%] [G loss: 0.712351]
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5402 [D loss: 0.693284, acc.: 48.44%] [G loss: 0.726625]
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5403 [D loss: 0.689200, acc.: 48.44%] [G loss: 0.727798]
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5404 [D loss: 0.691450, acc.: 48.83%] [G loss: 0.724822]
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5405 [D loss: 0.690872, acc.: 49.80%] [G loss: 0.719969]
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5406 [D loss: 0.691425, acc.: 50.98%] [G loss: 0.719158]
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5407 [D loss: 0.706348, acc.: 42.58%] [G loss: 0.718471]
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5408 [D loss: 0.698016, acc.: 43.36%] [G loss: 0.701794]
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5409 [D loss: 0.713428, acc.: 41.80%] [G loss: 0.699747]
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5410 [D loss: 0.702790, acc.: 46.29%] [G loss: 0.706128]
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5411 [D loss: 0.708849, acc.: 42.38%] [G loss: 0.720152]
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5412 [D loss: 0.692794, acc.: 52.54%] [G loss: 0.728458]
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5413 [D loss: 0.692272, acc.: 50.98%] [G loss: 0.736775]
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5414 [D loss: 0.687976, acc.: 53.32%] [G loss: 0.740242]
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5415 [D loss: 0.685137, acc.: 55.86%] [G loss: 0.749097]
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5416 [D loss: 0.686669, acc.: 56.05%] [G loss: 0.758426]
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5417 [D loss: 0.691091, acc.: 51.37%] [G loss: 0.740372]
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5418 [D loss: 0.689499, acc.: 53.12%] [G loss: 0.739299]
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5419 [D loss: 0.691195, acc.: 53.32%] [G loss: 0.730237]
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5420 [D loss: 0.694837, acc.: 48.24%] [G loss: 0.730975]
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5421 [D loss: 0.694052, acc.: 50.98%] [G loss: 0.721090]
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5422 [D loss: 0.698289, acc.: 46.48%] [G loss: 0.725015]
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5423 [D loss: 0.703179, acc.: 44.73%] [G loss: 0.727703]
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5424 [D loss: 0.696857, acc.: 48.63%] [G loss: 0.740369]
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5425 [D loss: 0.696246, acc.: 51.76%] [G loss: 0.739906]
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5426 [D loss: 0.690359, acc.: 53.91%] [G loss: 0.736096]
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5427 [D loss: 0.693286, acc.: 50.00%] [G loss: 0.741252]
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5428 [D loss: 0.693892, acc.: 49.41%] [G loss: 0.728563]
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5429 [D loss: 0.689886, acc.: 56.64%] [G loss: 0.731331]
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5430 [D loss: 0.691427, acc.: 50.20%] [G loss: 0.719213]
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5431 [D loss: 0.699386, acc.: 46.68%] [G loss: 0.714771]
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5432 [D loss: 0.692243, acc.: 55.08%] [G loss: 0.712693]
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5433 [D loss: 0.697250, acc.: 49.22%] [G loss: 0.724053]
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5434 [D loss: 0.693552, acc.: 50.39%] [G loss: 0.728764]
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5435 [D loss: 0.680020, acc.: 55.47%] [G loss: 0.745959]
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5436 [D loss: 0.685457, acc.: 53.71%] [G loss: 0.742445]
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5437 [D loss: 0.694165, acc.: 48.83%] [G loss: 0.737783]
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5438 [D loss: 0.684970, acc.: 53.32%] [G loss: 0.744298]
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5439 [D loss: 0.690957, acc.: 49.61%] [G loss: 0.719913]
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5440 [D loss: 0.688021, acc.: 54.69%] [G loss: 0.712470]
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5441 [D loss: 0.689640, acc.: 51.37%] [G loss: 0.696998]
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5442 [D loss: 0.696960, acc.: 47.85%] [G loss: 0.702429]
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5443 [D loss: 0.699543, acc.: 46.88%] [G loss: 0.702261]
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5444 [D loss: 0.705679, acc.: 41.41%] [G loss: 0.716588]
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5445 [D loss: 0.699399, acc.: 42.77%] [G loss: 0.715022]
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5446 [D loss: 0.692930, acc.: 50.20%] [G loss: 0.730991]
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5447 [D loss: 0.699941, acc.: 45.90%] [G loss: 0.724185]
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5448 [D loss: 0.697568, acc.: 45.70%] [G loss: 0.726432]
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5449 [D loss: 0.689868, acc.: 51.76%] [G loss: 0.727181]
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5450 [D loss: 0.689491, acc.: 51.95%] [G loss: 0.729968]
1/1 [==============================] - 0s 36ms/step
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5451 [D loss: 0.693303, acc.: 47.85%] [G loss: 0.732495]
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5452 [D loss: 0.697085, acc.: 49.80%] [G loss: 0.718018]
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5453 [D loss: 0.692997, acc.: 49.61%] [G loss: 0.722525]
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5454 [D loss: 0.693011, acc.: 49.61%] [G loss: 0.721273]
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5455 [D loss: 0.691657, acc.: 51.76%] [G loss: 0.719512]
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5456 [D loss: 0.688429, acc.: 49.22%] [G loss: 0.722545]
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5457 [D loss: 0.693075, acc.: 48.63%] [G loss: 0.736878]
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5458 [D loss: 0.691322, acc.: 48.44%] [G loss: 0.747664]
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5459 [D loss: 0.686523, acc.: 54.10%] [G loss: 0.739979]
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5460 [D loss: 0.690994, acc.: 53.32%] [G loss: 0.737611]
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5461 [D loss: 0.681273, acc.: 53.32%] [G loss: 0.742241]
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5462 [D loss: 0.681432, acc.: 59.96%] [G loss: 0.740155]
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5463 [D loss: 0.693343, acc.: 48.05%] [G loss: 0.723474]
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5464 [D loss: 0.688899, acc.: 51.95%] [G loss: 0.713785]
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5465 [D loss: 0.690501, acc.: 48.44%] [G loss: 0.726096]
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5466 [D loss: 0.690699, acc.: 48.83%] [G loss: 0.741919]
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5467 [D loss: 0.684357, acc.: 54.10%] [G loss: 0.738246]
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5468 [D loss: 0.684054, acc.: 50.59%] [G loss: 0.736078]
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5469 [D loss: 0.684099, acc.: 52.73%] [G loss: 0.738509]
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5470 [D loss: 0.686222, acc.: 53.91%] [G loss: 0.728469]
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5471 [D loss: 0.685687, acc.: 49.02%] [G loss: 0.718034]
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5472 [D loss: 0.689860, acc.: 48.05%] [G loss: 0.733144]
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5473 [D loss: 0.693297, acc.: 51.37%] [G loss: 0.710776]
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5474 [D loss: 0.687208, acc.: 51.37%] [G loss: 0.710446]
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5475 [D loss: 0.700776, acc.: 44.92%] [G loss: 0.716085]
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5476 [D loss: 0.689344, acc.: 49.61%] [G loss: 0.719725]
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5477 [D loss: 0.691563, acc.: 46.88%] [G loss: 0.722418]
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5478 [D loss: 0.687323, acc.: 51.37%] [G loss: 0.729180]
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5479 [D loss: 0.699134, acc.: 42.58%] [G loss: 0.733373]
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5480 [D loss: 0.691932, acc.: 44.34%] [G loss: 0.733416]
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5481 [D loss: 0.693684, acc.: 47.66%] [G loss: 0.734298]
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5482 [D loss: 0.686457, acc.: 50.00%] [G loss: 0.727911]
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5483 [D loss: 0.679319, acc.: 50.39%] [G loss: 0.727120]
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5484 [D loss: 0.686830, acc.: 47.66%] [G loss: 0.731050]
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5485 [D loss: 0.691530, acc.: 47.46%] [G loss: 0.725497]
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5486 [D loss: 0.680620, acc.: 53.91%] [G loss: 0.724711]
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5487 [D loss: 0.683064, acc.: 50.78%] [G loss: 0.722386]
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5488 [D loss: 0.677482, acc.: 49.22%] [G loss: 0.727598]
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5489 [D loss: 0.683708, acc.: 49.41%] [G loss: 0.733578]
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5490 [D loss: 0.683852, acc.: 50.39%] [G loss: 0.745843]
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5491 [D loss: 0.684841, acc.: 51.37%] [G loss: 0.745130]
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5492 [D loss: 0.692283, acc.: 49.61%] [G loss: 0.735368]
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5493 [D loss: 0.688012, acc.: 50.98%] [G loss: 0.732362]
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5494 [D loss: 0.689266, acc.: 50.39%] [G loss: 0.727006]
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5495 [D loss: 0.692152, acc.: 47.27%] [G loss: 0.720219]
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5496 [D loss: 0.689745, acc.: 49.61%] [G loss: 0.717966]
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5497 [D loss: 0.679797, acc.: 54.49%] [G loss: 0.713849]
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5498 [D loss: 0.690280, acc.: 49.41%] [G loss: 0.706326]
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5499 [D loss: 0.690383, acc.: 49.22%] [G loss: 0.705517]
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5500 [D loss: 0.681144, acc.: 51.95%] [G loss: 0.706406]
1/1 [==============================] - 0s 27ms/step
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5501 [D loss: 0.691266, acc.: 47.46%] [G loss: 0.714313]
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5502 [D loss: 0.682365, acc.: 47.85%] [G loss: 0.715462]
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5503 [D loss: 0.679035, acc.: 50.78%] [G loss: 0.722588]
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5504 [D loss: 0.674278, acc.: 55.47%] [G loss: 0.725332]
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5505 [D loss: 0.680621, acc.: 49.02%] [G loss: 0.722020]
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5506 [D loss: 0.691445, acc.: 48.24%] [G loss: 0.722992]
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5507 [D loss: 0.686775, acc.: 46.88%] [G loss: 0.727788]
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5508 [D loss: 0.685390, acc.: 48.83%] [G loss: 0.720708]
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5509 [D loss: 0.682506, acc.: 48.24%] [G loss: 0.722670]
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5510 [D loss: 0.689769, acc.: 48.05%] [G loss: 0.721483]
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5511 [D loss: 0.686175, acc.: 47.85%] [G loss: 0.721636]
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5512 [D loss: 0.698458, acc.: 42.97%] [G loss: 0.720608]
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5513 [D loss: 0.687561, acc.: 46.48%] [G loss: 0.722810]
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5514 [D loss: 0.688385, acc.: 50.00%] [G loss: 0.721176]
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5515 [D loss: 0.691790, acc.: 48.63%] [G loss: 0.722033]
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5516 [D loss: 0.688631, acc.: 48.83%] [G loss: 0.732570]
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5517 [D loss: 0.675313, acc.: 54.69%] [G loss: 0.737253]
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5518 [D loss: 0.673305, acc.: 54.88%] [G loss: 0.746912]
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5519 [D loss: 0.678571, acc.: 57.62%] [G loss: 0.746246]
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5520 [D loss: 0.687917, acc.: 52.93%] [G loss: 0.750773]
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5521 [D loss: 0.682158, acc.: 55.27%] [G loss: 0.740127]
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5522 [D loss: 0.684285, acc.: 53.32%] [G loss: 0.731130]
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5523 [D loss: 0.680545, acc.: 54.49%] [G loss: 0.722730]
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5524 [D loss: 0.689083, acc.: 51.56%] [G loss: 0.723454]
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5525 [D loss: 0.691766, acc.: 49.61%] [G loss: 0.713065]
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5526 [D loss: 0.685309, acc.: 50.39%] [G loss: 0.714332]
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5527 [D loss: 0.684892, acc.: 49.80%] [G loss: 0.709873]
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5528 [D loss: 0.684781, acc.: 46.68%] [G loss: 0.719767]
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5529 [D loss: 0.691280, acc.: 48.05%] [G loss: 0.729889]
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5530 [D loss: 0.688104, acc.: 45.70%] [G loss: 0.738481]
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5531 [D loss: 0.683782, acc.: 50.39%] [G loss: 0.739328]
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5532 [D loss: 0.683166, acc.: 51.37%] [G loss: 0.739494]
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5533 [D loss: 0.672186, acc.: 54.69%] [G loss: 0.734781]
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5534 [D loss: 0.682750, acc.: 53.12%] [G loss: 0.734448]
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5535 [D loss: 0.688913, acc.: 53.52%] [G loss: 0.721973]
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5536 [D loss: 0.679977, acc.: 52.15%] [G loss: 0.724531]
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5537 [D loss: 0.679165, acc.: 51.56%] [G loss: 0.712591]
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5538 [D loss: 0.683372, acc.: 50.98%] [G loss: 0.715977]
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5539 [D loss: 0.684653, acc.: 50.59%] [G loss: 0.712623]
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5540 [D loss: 0.677520, acc.: 53.32%] [G loss: 0.729681]
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5541 [D loss: 0.692248, acc.: 48.63%] [G loss: 0.727687]
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5542 [D loss: 0.687484, acc.: 46.68%] [G loss: 0.732735]
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5543 [D loss: 0.684904, acc.: 49.61%] [G loss: 0.730366]
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5544 [D loss: 0.694212, acc.: 44.92%] [G loss: 0.725273]
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5545 [D loss: 0.688270, acc.: 49.22%] [G loss: 0.727125]
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5546 [D loss: 0.682894, acc.: 51.95%] [G loss: 0.722416]
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5547 [D loss: 0.682332, acc.: 55.08%] [G loss: 0.728389]
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5548 [D loss: 0.671728, acc.: 54.49%] [G loss: 0.726144]
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5549 [D loss: 0.669246, acc.: 51.95%] [G loss: 0.724750]
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5550 [D loss: 0.677364, acc.: 53.52%] [G loss: 0.736267]
1/1 [==============================] - 0s 26ms/step
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5551 [D loss: 0.683313, acc.: 50.98%] [G loss: 0.730731]
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5552 [D loss: 0.674767, acc.: 50.39%] [G loss: 0.748158]
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5553 [D loss: 0.690214, acc.: 48.24%] [G loss: 0.739304]
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5554 [D loss: 0.680765, acc.: 49.41%] [G loss: 0.741337]
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5555 [D loss: 0.693830, acc.: 45.12%] [G loss: 0.741120]
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5556 [D loss: 0.680793, acc.: 49.80%] [G loss: 0.732725]
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5557 [D loss: 0.686196, acc.: 49.02%] [G loss: 0.736109]
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5558 [D loss: 0.683720, acc.: 51.17%] [G loss: 0.741794]
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5559 [D loss: 0.691584, acc.: 49.61%] [G loss: 0.731703]
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5560 [D loss: 0.680304, acc.: 50.78%] [G loss: 0.723691]
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5561 [D loss: 0.688980, acc.: 48.05%] [G loss: 0.727355]
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5562 [D loss: 0.673933, acc.: 49.02%] [G loss: 0.725743]
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5563 [D loss: 0.691313, acc.: 48.44%] [G loss: 0.727867]
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5564 [D loss: 0.685474, acc.: 50.78%] [G loss: 0.736744]
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5565 [D loss: 0.675497, acc.: 50.39%] [G loss: 0.731468]
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5566 [D loss: 0.674803, acc.: 52.34%] [G loss: 0.737085]
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5567 [D loss: 0.684066, acc.: 50.20%] [G loss: 0.731444]
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5568 [D loss: 0.682579, acc.: 50.98%] [G loss: 0.727841]
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5569 [D loss: 0.680065, acc.: 49.02%] [G loss: 0.722491]
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5570 [D loss: 0.686037, acc.: 51.17%] [G loss: 0.726018]
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5571 [D loss: 0.681480, acc.: 50.00%] [G loss: 0.716540]
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5572 [D loss: 0.685647, acc.: 46.88%] [G loss: 0.728658]
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5573 [D loss: 0.684194, acc.: 48.83%] [G loss: 0.730498]
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5574 [D loss: 0.685299, acc.: 46.29%] [G loss: 0.734024]
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5575 [D loss: 0.676437, acc.: 52.73%] [G loss: 0.738738]
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5576 [D loss: 0.677921, acc.: 53.12%] [G loss: 0.735461]
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5577 [D loss: 0.686659, acc.: 50.00%] [G loss: 0.738071]
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5578 [D loss: 0.680715, acc.: 53.32%] [G loss: 0.731996]
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5579 [D loss: 0.684878, acc.: 48.24%] [G loss: 0.737491]
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5580 [D loss: 0.686765, acc.: 48.83%] [G loss: 0.726667]
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5581 [D loss: 0.682217, acc.: 51.76%] [G loss: 0.731555]
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5582 [D loss: 0.689791, acc.: 45.12%] [G loss: 0.721607]
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5583 [D loss: 0.690607, acc.: 50.59%] [G loss: 0.717411]
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5584 [D loss: 0.683093, acc.: 48.24%] [G loss: 0.724020]
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5585 [D loss: 0.689253, acc.: 48.44%] [G loss: 0.715998]
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5586 [D loss: 0.678660, acc.: 49.61%] [G loss: 0.727690]
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5587 [D loss: 0.685898, acc.: 51.95%] [G loss: 0.728928]
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5588 [D loss: 0.688092, acc.: 48.05%] [G loss: 0.734850]
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5589 [D loss: 0.685330, acc.: 48.05%] [G loss: 0.734735]
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5590 [D loss: 0.682283, acc.: 51.17%] [G loss: 0.737298]
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5591 [D loss: 0.684730, acc.: 52.34%] [G loss: 0.729123]
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5592 [D loss: 0.681297, acc.: 50.39%] [G loss: 0.728202]
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5593 [D loss: 0.674375, acc.: 48.44%] [G loss: 0.737231]
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5594 [D loss: 0.681546, acc.: 49.41%] [G loss: 0.731786]
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5595 [D loss: 0.676655, acc.: 52.34%] [G loss: 0.732934]
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5596 [D loss: 0.680837, acc.: 50.98%] [G loss: 0.730358]
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5597 [D loss: 0.682855, acc.: 50.59%] [G loss: 0.729222]
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5598 [D loss: 0.683076, acc.: 49.41%] [G loss: 0.729070]
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5599 [D loss: 0.679253, acc.: 51.37%] [G loss: 0.733071]
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5600 [D loss: 0.691846, acc.: 46.09%] [G loss: 0.731449]
1/1 [==============================] - 0s 28ms/step
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5601 [D loss: 0.678898, acc.: 53.91%] [G loss: 0.737901]
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5602 [D loss: 0.688248, acc.: 51.56%] [G loss: 0.736371]
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5603 [D loss: 0.679821, acc.: 51.56%] [G loss: 0.740612]
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5604 [D loss: 0.679956, acc.: 53.91%] [G loss: 0.743693]
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5605 [D loss: 0.687383, acc.: 52.15%] [G loss: 0.723406]
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5606 [D loss: 0.689914, acc.: 47.85%] [G loss: 0.737957]
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5607 [D loss: 0.684478, acc.: 51.76%] [G loss: 0.733527]
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5608 [D loss: 0.684993, acc.: 47.66%] [G loss: 0.728297]
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5609 [D loss: 0.675376, acc.: 54.69%] [G loss: 0.726868]
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5610 [D loss: 0.684202, acc.: 50.39%] [G loss: 0.717537]
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5611 [D loss: 0.683336, acc.: 52.73%] [G loss: 0.707995]
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5612 [D loss: 0.694025, acc.: 48.24%] [G loss: 0.721726]
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5613 [D loss: 0.686660, acc.: 46.68%] [G loss: 0.722921]
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5614 [D loss: 0.684789, acc.: 50.00%] [G loss: 0.732569]
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5615 [D loss: 0.675902, acc.: 53.12%] [G loss: 0.733046]
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5616 [D loss: 0.676388, acc.: 49.80%] [G loss: 0.725526]
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5617 [D loss: 0.696898, acc.: 45.12%] [G loss: 0.728137]
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5618 [D loss: 0.686322, acc.: 51.17%] [G loss: 0.747814]
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5619 [D loss: 0.669640, acc.: 54.69%] [G loss: 0.726751]
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5620 [D loss: 0.687209, acc.: 47.66%] [G loss: 0.726855]
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5621 [D loss: 0.684529, acc.: 50.20%] [G loss: 0.729083]
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5622 [D loss: 0.682286, acc.: 50.20%] [G loss: 0.724745]
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5623 [D loss: 0.690325, acc.: 47.07%] [G loss: 0.714844]
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5624 [D loss: 0.681053, acc.: 49.41%] [G loss: 0.716700]
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5625 [D loss: 0.693554, acc.: 46.48%] [G loss: 0.721153]
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5626 [D loss: 0.707319, acc.: 46.09%] [G loss: 0.701451]
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5627 [D loss: 0.718446, acc.: 48.63%] [G loss: 0.701231]
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5628 [D loss: 0.709372, acc.: 47.85%] [G loss: 0.707966]
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5629 [D loss: 0.695258, acc.: 47.85%] [G loss: 0.723249]
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5630 [D loss: 0.697955, acc.: 49.02%] [G loss: 0.728971]
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5631 [D loss: 0.692359, acc.: 48.24%] [G loss: 0.725017]
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5632 [D loss: 0.695622, acc.: 49.80%] [G loss: 0.724564]
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5633 [D loss: 0.682177, acc.: 54.69%] [G loss: 0.751550]
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5634 [D loss: 0.693117, acc.: 46.09%] [G loss: 0.725632]
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5635 [D loss: 0.689059, acc.: 43.95%] [G loss: 0.749504]
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5636 [D loss: 0.683009, acc.: 50.20%] [G loss: 0.752155]
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5637 [D loss: 0.692183, acc.: 52.15%] [G loss: 0.764056]
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5638 [D loss: 0.686559, acc.: 54.30%] [G loss: 0.762309]
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5639 [D loss: 0.679845, acc.: 58.40%] [G loss: 0.756475]
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5640 [D loss: 0.681802, acc.: 58.98%] [G loss: 0.742806]
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5641 [D loss: 0.687154, acc.: 51.76%] [G loss: 0.732580]
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5642 [D loss: 0.693163, acc.: 52.93%] [G loss: 0.710215]
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5643 [D loss: 0.699351, acc.: 50.39%] [G loss: 0.710854]
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5644 [D loss: 0.703887, acc.: 45.51%] [G loss: 0.732615]
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5645 [D loss: 0.699933, acc.: 46.88%] [G loss: 0.721327]
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5646 [D loss: 0.707268, acc.: 42.77%] [G loss: 0.717590]
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5647 [D loss: 0.690912, acc.: 50.78%] [G loss: 0.737366]
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5648 [D loss: 0.700448, acc.: 47.27%] [G loss: 0.725376]
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5649 [D loss: 0.700456, acc.: 47.27%] [G loss: 0.725058]
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5650 [D loss: 0.694206, acc.: 47.27%] [G loss: 0.728784]
1/1 [==============================] - 0s 30ms/step
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5651 [D loss: 0.693461, acc.: 47.27%] [G loss: 0.732981]
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5652 [D loss: 0.690396, acc.: 53.71%] [G loss: 0.719152]
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5653 [D loss: 0.687520, acc.: 53.32%] [G loss: 0.731880]
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5654 [D loss: 0.695597, acc.: 48.44%] [G loss: 0.724537]
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5655 [D loss: 0.690367, acc.: 48.83%] [G loss: 0.718129]
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5656 [D loss: 0.687564, acc.: 50.00%] [G loss: 0.740837]
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5657 [D loss: 0.683344, acc.: 54.30%] [G loss: 0.737789]
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5658 [D loss: 0.683614, acc.: 56.45%] [G loss: 0.732149]
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5659 [D loss: 0.676666, acc.: 53.52%] [G loss: 0.739601]
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5660 [D loss: 0.688731, acc.: 48.05%] [G loss: 0.731966]
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5661 [D loss: 0.693321, acc.: 46.09%] [G loss: 0.724698]
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5662 [D loss: 0.690646, acc.: 50.59%] [G loss: 0.720113]
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5663 [D loss: 0.695860, acc.: 50.20%] [G loss: 0.696410]
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5664 [D loss: 0.703085, acc.: 48.05%] [G loss: 0.697444]
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5665 [D loss: 0.701977, acc.: 48.44%] [G loss: 0.710575]
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5666 [D loss: 0.702285, acc.: 42.58%] [G loss: 0.722553]
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5667 [D loss: 0.691305, acc.: 51.56%] [G loss: 0.744431]
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5668 [D loss: 0.686513, acc.: 53.71%] [G loss: 0.751220]
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5669 [D loss: 0.688258, acc.: 50.78%] [G loss: 0.746933]
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5670 [D loss: 0.691279, acc.: 50.59%] [G loss: 0.734845]
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5671 [D loss: 0.684873, acc.: 54.69%] [G loss: 0.732191]
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5672 [D loss: 0.689249, acc.: 52.73%] [G loss: 0.729969]
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5673 [D loss: 0.677792, acc.: 54.30%] [G loss: 0.733553]
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5674 [D loss: 0.694360, acc.: 48.44%] [G loss: 0.710191]
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5675 [D loss: 0.702462, acc.: 45.90%] [G loss: 0.704882]
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5676 [D loss: 0.701767, acc.: 45.12%] [G loss: 0.716785]
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5677 [D loss: 0.699223, acc.: 44.14%] [G loss: 0.732866]
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5678 [D loss: 0.695423, acc.: 47.07%] [G loss: 0.750214]
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5679 [D loss: 0.687822, acc.: 50.20%] [G loss: 0.757744]
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5680 [D loss: 0.693969, acc.: 49.61%] [G loss: 0.752785]
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5681 [D loss: 0.700715, acc.: 47.85%] [G loss: 0.735331]
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5682 [D loss: 0.703349, acc.: 46.48%] [G loss: 0.728113]
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5683 [D loss: 0.697880, acc.: 46.29%] [G loss: 0.730882]
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5684 [D loss: 0.683992, acc.: 53.12%] [G loss: 0.728030]
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5685 [D loss: 0.687365, acc.: 52.34%] [G loss: 0.729075]
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5686 [D loss: 0.685172, acc.: 54.88%] [G loss: 0.730416]
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5687 [D loss: 0.690135, acc.: 50.39%] [G loss: 0.715595]
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5688 [D loss: 0.707034, acc.: 54.49%] [G loss: 0.715370]
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5689 [D loss: 0.699660, acc.: 54.49%] [G loss: 0.725302]
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5690 [D loss: 0.699594, acc.: 49.22%] [G loss: 0.725008]
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5691 [D loss: 0.694789, acc.: 50.59%] [G loss: 0.729421]
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5692 [D loss: 0.700949, acc.: 48.05%] [G loss: 0.719870]
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5693 [D loss: 0.695875, acc.: 47.46%] [G loss: 0.709657]
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5694 [D loss: 0.708320, acc.: 42.58%] [G loss: 0.723270]
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5695 [D loss: 0.701106, acc.: 46.09%] [G loss: 0.718817]
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5696 [D loss: 0.699543, acc.: 46.09%] [G loss: 0.747101]
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5697 [D loss: 0.695115, acc.: 49.41%] [G loss: 0.753608]
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5698 [D loss: 0.697527, acc.: 48.05%] [G loss: 0.750333]
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5699 [D loss: 0.691296, acc.: 50.59%] [G loss: 0.747781]
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5700 [D loss: 0.689061, acc.: 57.62%] [G loss: 0.733647]
1/1 [==============================] - 0s 27ms/step
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5701 [D loss: 0.690147, acc.: 51.17%] [G loss: 0.731480]
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5702 [D loss: 0.695262, acc.: 50.20%] [G loss: 0.717323]
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5703 [D loss: 0.706547, acc.: 45.90%] [G loss: 0.713578]
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5704 [D loss: 0.699428, acc.: 46.29%] [G loss: 0.706385]
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5705 [D loss: 0.701268, acc.: 43.95%] [G loss: 0.711684]
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5706 [D loss: 0.696722, acc.: 48.83%] [G loss: 0.724489]
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5707 [D loss: 0.699425, acc.: 46.48%] [G loss: 0.726981]
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5708 [D loss: 0.699542, acc.: 45.31%] [G loss: 0.743672]
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5709 [D loss: 0.697489, acc.: 48.83%] [G loss: 0.744946]
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5710 [D loss: 0.696952, acc.: 47.66%] [G loss: 0.746119]
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5711 [D loss: 0.687544, acc.: 52.93%] [G loss: 0.745536]
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5712 [D loss: 0.690952, acc.: 53.71%] [G loss: 0.746732]
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5713 [D loss: 0.692095, acc.: 53.52%] [G loss: 0.726379]
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5714 [D loss: 0.693853, acc.: 47.85%] [G loss: 0.725571]
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5715 [D loss: 0.694421, acc.: 52.15%] [G loss: 0.743803]
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5716 [D loss: 0.700380, acc.: 49.41%] [G loss: 0.750786]
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5717 [D loss: 0.695301, acc.: 51.17%] [G loss: 0.742545]
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5718 [D loss: 0.705455, acc.: 45.12%] [G loss: 0.735425]
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5719 [D loss: 0.699736, acc.: 45.12%] [G loss: 0.716984]
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5720 [D loss: 0.698507, acc.: 46.68%] [G loss: 0.724363]
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5721 [D loss: 0.694095, acc.: 46.68%] [G loss: 0.721045]
8/8 [==============================] - 0s 4ms/step
5722 [D loss: 0.684367, acc.: 55.47%] [G loss: 0.734284]
8/8 [==============================] - 0s 4ms/step
5723 [D loss: 0.689579, acc.: 51.37%] [G loss: 0.716624]
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5724 [D loss: 0.693222, acc.: 49.61%] [G loss: 0.704854]
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5725 [D loss: 0.695837, acc.: 48.44%] [G loss: 0.705252]
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5726 [D loss: 0.689631, acc.: 53.52%] [G loss: 0.709072]
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5727 [D loss: 0.693733, acc.: 46.88%] [G loss: 0.719294]
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5728 [D loss: 0.694563, acc.: 48.05%] [G loss: 0.726299]
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5729 [D loss: 0.693362, acc.: 48.24%] [G loss: 0.723437]
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5730 [D loss: 0.690769, acc.: 50.39%] [G loss: 0.718278]
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5731 [D loss: 0.692288, acc.: 50.39%] [G loss: 0.719620]
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5732 [D loss: 0.697741, acc.: 47.46%] [G loss: 0.713789]
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5733 [D loss: 0.697116, acc.: 49.41%] [G loss: 0.704717]
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5734 [D loss: 0.692970, acc.: 50.20%] [G loss: 0.708994]
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5735 [D loss: 0.694126, acc.: 48.63%] [G loss: 0.717448]
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5736 [D loss: 0.693135, acc.: 49.22%] [G loss: 0.721029]
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5737 [D loss: 0.690397, acc.: 49.80%] [G loss: 0.726814]
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5738 [D loss: 0.694996, acc.: 47.27%] [G loss: 0.748329]
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5739 [D loss: 0.681666, acc.: 56.05%] [G loss: 0.754461]
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5740 [D loss: 0.696693, acc.: 50.39%] [G loss: 0.752986]
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5741 [D loss: 0.682398, acc.: 54.30%] [G loss: 0.757625]
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5742 [D loss: 0.689992, acc.: 51.95%] [G loss: 0.750084]
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5743 [D loss: 0.696326, acc.: 51.17%] [G loss: 0.732246]
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5744 [D loss: 0.685723, acc.: 56.05%] [G loss: 0.731854]
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5745 [D loss: 0.688731, acc.: 52.34%] [G loss: 0.730105]
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5746 [D loss: 0.695841, acc.: 48.24%] [G loss: 0.719956]
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5747 [D loss: 0.694583, acc.: 53.71%] [G loss: 0.721576]
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5748 [D loss: 0.697097, acc.: 51.37%] [G loss: 0.723311]
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5749 [D loss: 0.691170, acc.: 52.15%] [G loss: 0.731412]
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5750 [D loss: 0.695520, acc.: 48.24%] [G loss: 0.745393]
1/1 [==============================] - 0s 30ms/step
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5751 [D loss: 0.685349, acc.: 56.45%] [G loss: 0.738610]
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5752 [D loss: 0.688252, acc.: 54.69%] [G loss: 0.738245]
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5753 [D loss: 0.689331, acc.: 50.00%] [G loss: 0.737256]
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5754 [D loss: 0.698389, acc.: 48.24%] [G loss: 0.730525]
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5755 [D loss: 0.688920, acc.: 49.80%] [G loss: 0.724661]
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5756 [D loss: 0.692107, acc.: 50.00%] [G loss: 0.717242]
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5757 [D loss: 0.691514, acc.: 50.59%] [G loss: 0.706756]
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5758 [D loss: 0.699134, acc.: 44.34%] [G loss: 0.713040]
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5759 [D loss: 0.695605, acc.: 47.66%] [G loss: 0.709050]
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5760 [D loss: 0.691733, acc.: 47.85%] [G loss: 0.723038]
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5761 [D loss: 0.686718, acc.: 48.63%] [G loss: 0.726202]
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5762 [D loss: 0.692399, acc.: 48.05%] [G loss: 0.733424]
8/8 [==============================] - 0s 4ms/step
5763 [D loss: 0.681468, acc.: 54.88%] [G loss: 0.735751]
8/8 [==============================] - 0s 5ms/step
5764 [D loss: 0.690843, acc.: 49.22%] [G loss: 0.737519]
8/8 [==============================] - 0s 4ms/step
5765 [D loss: 0.678163, acc.: 59.77%] [G loss: 0.740571]
8/8 [==============================] - 0s 4ms/step
5766 [D loss: 0.691332, acc.: 49.61%] [G loss: 0.730591]
8/8 [==============================] - 0s 4ms/step
5767 [D loss: 0.684782, acc.: 53.12%] [G loss: 0.726974]
8/8 [==============================] - 0s 4ms/step
5768 [D loss: 0.683408, acc.: 53.32%] [G loss: 0.728724]
8/8 [==============================] - 0s 4ms/step
5769 [D loss: 0.690497, acc.: 49.61%] [G loss: 0.718271]
8/8 [==============================] - 0s 4ms/step
5770 [D loss: 0.688707, acc.: 52.15%] [G loss: 0.718237]
8/8 [==============================] - 0s 4ms/step
5771 [D loss: 0.688602, acc.: 51.76%] [G loss: 0.711020]
8/8 [==============================] - 0s 4ms/step
5772 [D loss: 0.689909, acc.: 49.02%] [G loss: 0.725469]
8/8 [==============================] - 0s 4ms/step
5773 [D loss: 0.699590, acc.: 47.66%] [G loss: 0.724316]
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5774 [D loss: 0.690970, acc.: 49.80%] [G loss: 0.717542]
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5775 [D loss: 0.703066, acc.: 53.12%] [G loss: 0.698853]
8/8 [==============================] - 0s 4ms/step
5776 [D loss: 0.706629, acc.: 50.00%] [G loss: 0.710780]
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5777 [D loss: 0.691904, acc.: 52.54%] [G loss: 0.713432]
8/8 [==============================] - 0s 4ms/step
5778 [D loss: 0.696633, acc.: 48.83%] [G loss: 0.714881]
8/8 [==============================] - 0s 4ms/step
5779 [D loss: 0.696039, acc.: 48.83%] [G loss: 0.722529]
8/8 [==============================] - 0s 4ms/step
5780 [D loss: 0.698724, acc.: 50.00%] [G loss: 0.723510]
8/8 [==============================] - 0s 4ms/step
5781 [D loss: 0.699708, acc.: 50.20%] [G loss: 0.721924]
8/8 [==============================] - 0s 4ms/step
5782 [D loss: 0.692142, acc.: 50.98%] [G loss: 0.738859]
8/8 [==============================] - 0s 4ms/step
5783 [D loss: 0.693271, acc.: 52.15%] [G loss: 0.733480]
8/8 [==============================] - 0s 4ms/step
5784 [D loss: 0.693131, acc.: 50.20%] [G loss: 0.747715]
8/8 [==============================] - 0s 4ms/step
5785 [D loss: 0.695932, acc.: 50.98%] [G loss: 0.748330]
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5786 [D loss: 0.693807, acc.: 49.80%] [G loss: 0.751034]
8/8 [==============================] - 0s 4ms/step
5787 [D loss: 0.692009, acc.: 51.76%] [G loss: 0.742202]
8/8 [==============================] - 0s 4ms/step
5788 [D loss: 0.692638, acc.: 51.17%] [G loss: 0.738780]
8/8 [==============================] - 0s 4ms/step
5789 [D loss: 0.687978, acc.: 50.39%] [G loss: 0.738938]
8/8 [==============================] - 0s 4ms/step
5790 [D loss: 0.684290, acc.: 51.95%] [G loss: 0.732906]
8/8 [==============================] - 0s 4ms/step
5791 [D loss: 0.694636, acc.: 46.68%] [G loss: 0.744989]
8/8 [==============================] - 0s 4ms/step
5792 [D loss: 0.691129, acc.: 51.56%] [G loss: 0.716995]
8/8 [==============================] - 0s 4ms/step
5793 [D loss: 0.691119, acc.: 49.02%] [G loss: 0.711905]
8/8 [==============================] - 0s 4ms/step
5794 [D loss: 0.694601, acc.: 51.56%] [G loss: 0.714170]
8/8 [==============================] - 0s 4ms/step
5795 [D loss: 0.697201, acc.: 45.90%] [G loss: 0.725851]
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5796 [D loss: 0.691577, acc.: 50.20%] [G loss: 0.720635]
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5797 [D loss: 0.695425, acc.: 49.22%] [G loss: 0.725162]
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5798 [D loss: 0.692166, acc.: 48.63%] [G loss: 0.724967]
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5799 [D loss: 0.688827, acc.: 51.56%] [G loss: 0.722871]
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5800 [D loss: 0.693898, acc.: 49.22%] [G loss: 0.722917]
1/1 [==============================] - 0s 31ms/step
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5801 [D loss: 0.689635, acc.: 53.12%] [G loss: 0.713502]
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5802 [D loss: 0.692453, acc.: 50.00%] [G loss: 0.716612]
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5803 [D loss: 0.697077, acc.: 48.44%] [G loss: 0.713321]
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5804 [D loss: 0.687935, acc.: 52.93%] [G loss: 0.716896]
8/8 [==============================] - 0s 4ms/step
5805 [D loss: 0.686927, acc.: 52.54%] [G loss: 0.740194]
8/8 [==============================] - 0s 4ms/step
5806 [D loss: 0.692561, acc.: 50.39%] [G loss: 0.741684]
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5807 [D loss: 0.695089, acc.: 48.63%] [G loss: 0.739130]
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5808 [D loss: 0.697593, acc.: 48.44%] [G loss: 0.736399]
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5809 [D loss: 0.692285, acc.: 48.44%] [G loss: 0.740860]
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5810 [D loss: 0.686091, acc.: 53.32%] [G loss: 0.740161]
8/8 [==============================] - 0s 4ms/step
5811 [D loss: 0.685275, acc.: 53.12%] [G loss: 0.734089]
8/8 [==============================] - 0s 4ms/step
5812 [D loss: 0.681047, acc.: 55.08%] [G loss: 0.725175]
8/8 [==============================] - 0s 4ms/step
5813 [D loss: 0.684449, acc.: 51.56%] [G loss: 0.721292]
8/8 [==============================] - 0s 4ms/step
5814 [D loss: 0.683121, acc.: 51.37%] [G loss: 0.723575]
8/8 [==============================] - 0s 4ms/step
5815 [D loss: 0.679161, acc.: 52.73%] [G loss: 0.726227]
8/8 [==============================] - 0s 4ms/step
5816 [D loss: 0.685515, acc.: 50.00%] [G loss: 0.735016]
8/8 [==============================] - 0s 4ms/step
5817 [D loss: 0.684329, acc.: 54.88%] [G loss: 0.753046]
8/8 [==============================] - 0s 4ms/step
5818 [D loss: 0.684475, acc.: 51.37%] [G loss: 0.744740]
8/8 [==============================] - 0s 4ms/step
5819 [D loss: 0.692440, acc.: 51.76%] [G loss: 0.731494]
8/8 [==============================] - 0s 4ms/step
5820 [D loss: 0.692244, acc.: 49.41%] [G loss: 0.718360]
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5821 [D loss: 0.692081, acc.: 49.80%] [G loss: 0.734063]
8/8 [==============================] - 0s 4ms/step
5822 [D loss: 0.690160, acc.: 51.95%] [G loss: 0.720178]
8/8 [==============================] - 0s 4ms/step
5823 [D loss: 0.691717, acc.: 47.27%] [G loss: 0.707892]
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5824 [D loss: 0.696679, acc.: 49.41%] [G loss: 0.696104]
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5825 [D loss: 0.701376, acc.: 47.27%] [G loss: 0.700054]
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5826 [D loss: 0.700920, acc.: 46.68%] [G loss: 0.708846]
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5827 [D loss: 0.692509, acc.: 49.41%] [G loss: 0.723855]
8/8 [==============================] - 0s 4ms/step
5828 [D loss: 0.684010, acc.: 54.49%] [G loss: 0.742813]
8/8 [==============================] - 0s 4ms/step
5829 [D loss: 0.693048, acc.: 49.61%] [G loss: 0.744884]
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5830 [D loss: 0.690544, acc.: 50.59%] [G loss: 0.754201]
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5831 [D loss: 0.692624, acc.: 49.02%] [G loss: 0.750921]
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5832 [D loss: 0.695492, acc.: 49.80%] [G loss: 0.745300]
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5833 [D loss: 0.682176, acc.: 59.57%] [G loss: 0.745294]
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5834 [D loss: 0.679177, acc.: 56.64%] [G loss: 0.750327]
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5835 [D loss: 0.695943, acc.: 53.32%] [G loss: 0.720866]
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5836 [D loss: 0.697294, acc.: 49.22%] [G loss: 0.701982]
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5837 [D loss: 0.694155, acc.: 50.39%] [G loss: 0.702474]
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5838 [D loss: 0.699084, acc.: 47.66%] [G loss: 0.717816]
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5839 [D loss: 0.687983, acc.: 53.71%] [G loss: 0.753395]
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5840 [D loss: 0.690566, acc.: 53.32%] [G loss: 0.769022]
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5841 [D loss: 0.692288, acc.: 49.02%] [G loss: 0.763056]
8/8 [==============================] - 0s 4ms/step
5842 [D loss: 0.692880, acc.: 50.59%] [G loss: 0.745010]
8/8 [==============================] - 0s 4ms/step
5843 [D loss: 0.689874, acc.: 50.98%] [G loss: 0.736142]
8/8 [==============================] - 0s 4ms/step
5844 [D loss: 0.689869, acc.: 53.32%] [G loss: 0.738550]
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5845 [D loss: 0.691626, acc.: 50.20%] [G loss: 0.730303]
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5846 [D loss: 0.683066, acc.: 54.69%] [G loss: 0.727678]
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5847 [D loss: 0.679324, acc.: 56.25%] [G loss: 0.733176]
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5848 [D loss: 0.688670, acc.: 50.98%] [G loss: 0.717029]
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5849 [D loss: 0.687661, acc.: 49.61%] [G loss: 0.709322]
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5850 [D loss: 0.676981, acc.: 56.45%] [G loss: 0.705673]
1/1 [==============================] - 0s 32ms/step
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5851 [D loss: 0.687197, acc.: 49.61%] [G loss: 0.710481]
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5852 [D loss: 0.694393, acc.: 47.27%] [G loss: 0.714931]
8/8 [==============================] - 0s 4ms/step
5853 [D loss: 0.693201, acc.: 48.63%] [G loss: 0.724539]
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5854 [D loss: 0.685128, acc.: 51.95%] [G loss: 0.741539]
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5855 [D loss: 0.690032, acc.: 49.22%] [G loss: 0.739714]
8/8 [==============================] - 0s 4ms/step
5856 [D loss: 0.698172, acc.: 47.07%] [G loss: 0.725286]
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5857 [D loss: 0.702095, acc.: 49.61%] [G loss: 0.708944]
8/8 [==============================] - 0s 4ms/step
5858 [D loss: 0.700609, acc.: 47.66%] [G loss: 0.716096]
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5859 [D loss: 0.694742, acc.: 47.66%] [G loss: 0.710480]
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5860 [D loss: 0.693907, acc.: 47.85%] [G loss: 0.713975]
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5861 [D loss: 0.688918, acc.: 52.34%] [G loss: 0.718399]
8/8 [==============================] - 0s 4ms/step
5862 [D loss: 0.689391, acc.: 48.24%] [G loss: 0.717512]
8/8 [==============================] - 0s 4ms/step
5863 [D loss: 0.691066, acc.: 43.36%] [G loss: 0.723981]
8/8 [==============================] - 0s 4ms/step
5864 [D loss: 0.689157, acc.: 50.00%] [G loss: 0.742302]
8/8 [==============================] - 0s 4ms/step
5865 [D loss: 0.685540, acc.: 52.15%] [G loss: 0.750816]
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5866 [D loss: 0.674226, acc.: 56.25%] [G loss: 0.764079]
8/8 [==============================] - 0s 4ms/step
5867 [D loss: 0.684017, acc.: 53.91%] [G loss: 0.750467]
8/8 [==============================] - 0s 4ms/step
5868 [D loss: 0.679421, acc.: 57.81%] [G loss: 0.749568]
8/8 [==============================] - 0s 4ms/step
5869 [D loss: 0.671704, acc.: 57.23%] [G loss: 0.749130]
8/8 [==============================] - 0s 4ms/step
5870 [D loss: 0.671199, acc.: 58.40%] [G loss: 0.742270]
8/8 [==============================] - 0s 4ms/step
5871 [D loss: 0.672713, acc.: 56.05%] [G loss: 0.734956]
8/8 [==============================] - 0s 4ms/step
5872 [D loss: 0.693483, acc.: 48.44%] [G loss: 0.726184]
8/8 [==============================] - 0s 4ms/step
5873 [D loss: 0.684606, acc.: 51.76%] [G loss: 0.718283]
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5874 [D loss: 0.694515, acc.: 49.41%] [G loss: 0.722808]
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5875 [D loss: 0.676356, acc.: 58.01%] [G loss: 0.728882]
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5876 [D loss: 0.692454, acc.: 46.48%] [G loss: 0.721454]
8/8 [==============================] - 0s 4ms/step
5877 [D loss: 0.691587, acc.: 50.00%] [G loss: 0.729150]
8/8 [==============================] - 0s 4ms/step
5878 [D loss: 0.683661, acc.: 53.91%] [G loss: 0.724465]
8/8 [==============================] - 0s 4ms/step
5879 [D loss: 0.679968, acc.: 52.34%] [G loss: 0.743252]
8/8 [==============================] - 0s 4ms/step
5880 [D loss: 0.683501, acc.: 52.34%] [G loss: 0.729942]
8/8 [==============================] - 0s 4ms/step
5881 [D loss: 0.688170, acc.: 52.15%] [G loss: 0.730300]
8/8 [==============================] - 0s 4ms/step
5882 [D loss: 0.689027, acc.: 49.02%] [G loss: 0.726671]
8/8 [==============================] - 0s 4ms/step
5883 [D loss: 0.687532, acc.: 49.61%] [G loss: 0.719132]
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5884 [D loss: 0.691068, acc.: 47.85%] [G loss: 0.710196]
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5885 [D loss: 0.688565, acc.: 47.85%] [G loss: 0.716462]
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5886 [D loss: 0.692962, acc.: 48.24%] [G loss: 0.722543]
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5887 [D loss: 0.695039, acc.: 43.95%] [G loss: 0.722725]
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5888 [D loss: 0.695719, acc.: 48.05%] [G loss: 0.725750]
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5889 [D loss: 0.695868, acc.: 47.66%] [G loss: 0.747056]
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5890 [D loss: 0.690583, acc.: 50.98%] [G loss: 0.760978]
8/8 [==============================] - 0s 4ms/step
5891 [D loss: 0.689101, acc.: 51.37%] [G loss: 0.754903]
8/8 [==============================] - 0s 4ms/step
5892 [D loss: 0.689742, acc.: 50.20%] [G loss: 0.748108]
8/8 [==============================] - 0s 4ms/step
5893 [D loss: 0.681722, acc.: 51.17%] [G loss: 0.746794]
8/8 [==============================] - 0s 5ms/step
5894 [D loss: 0.685825, acc.: 51.95%] [G loss: 0.737538]
8/8 [==============================] - 0s 4ms/step
5895 [D loss: 0.689285, acc.: 52.34%] [G loss: 0.726889]
8/8 [==============================] - 0s 4ms/step
5896 [D loss: 0.694093, acc.: 46.29%] [G loss: 0.718839]
8/8 [==============================] - 0s 4ms/step
5897 [D loss: 0.694837, acc.: 49.61%] [G loss: 0.708459]
8/8 [==============================] - 0s 4ms/step
5898 [D loss: 0.689133, acc.: 52.93%] [G loss: 0.709944]
8/8 [==============================] - 0s 4ms/step
5899 [D loss: 0.697448, acc.: 45.31%] [G loss: 0.708555]
8/8 [==============================] - 0s 4ms/step
5900 [D loss: 0.685834, acc.: 49.80%] [G loss: 0.725378]
1/1 [==============================] - 0s 33ms/step
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5901 [D loss: 0.693221, acc.: 47.46%] [G loss: 0.740849]
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5902 [D loss: 0.681954, acc.: 52.73%] [G loss: 0.744919]
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5903 [D loss: 0.680633, acc.: 56.45%] [G loss: 0.752319]
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5904 [D loss: 0.679177, acc.: 53.91%] [G loss: 0.744588]
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5905 [D loss: 0.687441, acc.: 48.44%] [G loss: 0.746357]
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5906 [D loss: 0.688248, acc.: 50.78%] [G loss: 0.732599]
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5907 [D loss: 0.693729, acc.: 45.31%] [G loss: 0.726177]
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5908 [D loss: 0.681618, acc.: 48.24%] [G loss: 0.718810]
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5909 [D loss: 0.689635, acc.: 46.68%] [G loss: 0.723690]
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5910 [D loss: 0.689741, acc.: 48.05%] [G loss: 0.715687]
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5911 [D loss: 0.696744, acc.: 43.95%] [G loss: 0.726909]
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5912 [D loss: 0.689786, acc.: 48.24%] [G loss: 0.733110]
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5913 [D loss: 0.686156, acc.: 50.78%] [G loss: 0.741161]
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5914 [D loss: 0.674707, acc.: 54.69%] [G loss: 0.755703]
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5915 [D loss: 0.676174, acc.: 51.95%] [G loss: 0.759511]
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5916 [D loss: 0.692989, acc.: 48.83%] [G loss: 0.749371]
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5917 [D loss: 0.687711, acc.: 49.61%] [G loss: 0.739711]
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5918 [D loss: 0.684281, acc.: 48.63%] [G loss: 0.723917]
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5919 [D loss: 0.678638, acc.: 54.30%] [G loss: 0.733966]
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5920 [D loss: 0.685146, acc.: 51.56%] [G loss: 0.715788]
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5921 [D loss: 0.688737, acc.: 48.83%] [G loss: 0.696553]
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5922 [D loss: 0.682835, acc.: 49.61%] [G loss: 0.706158]
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5923 [D loss: 0.697067, acc.: 47.66%] [G loss: 0.714592]
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5924 [D loss: 0.692729, acc.: 48.63%] [G loss: 0.736632]
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5925 [D loss: 0.682710, acc.: 52.73%] [G loss: 0.755080]
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5926 [D loss: 0.690674, acc.: 47.85%] [G loss: 0.750700]
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5927 [D loss: 0.684009, acc.: 53.91%] [G loss: 0.747813]
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5928 [D loss: 0.687801, acc.: 49.80%] [G loss: 0.741665]
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5929 [D loss: 0.685301, acc.: 49.41%] [G loss: 0.739641]
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5930 [D loss: 0.684545, acc.: 52.34%] [G loss: 0.733374]
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5931 [D loss: 0.681831, acc.: 52.93%] [G loss: 0.724482]
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5932 [D loss: 0.685933, acc.: 52.93%] [G loss: 0.721468]
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5933 [D loss: 0.690742, acc.: 49.80%] [G loss: 0.718767]
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5934 [D loss: 0.688324, acc.: 51.56%] [G loss: 0.719278]
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5935 [D loss: 0.683831, acc.: 48.44%] [G loss: 0.723254]
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5936 [D loss: 0.688953, acc.: 47.46%] [G loss: 0.726892]
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5937 [D loss: 0.680860, acc.: 48.63%] [G loss: 0.740762]
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5938 [D loss: 0.677060, acc.: 52.93%] [G loss: 0.743982]
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5939 [D loss: 0.687895, acc.: 48.44%] [G loss: 0.743891]
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5940 [D loss: 0.689862, acc.: 49.41%] [G loss: 0.734925]
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5941 [D loss: 0.684275, acc.: 50.20%] [G loss: 0.732616]
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5942 [D loss: 0.678099, acc.: 51.76%] [G loss: 0.731155]
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5943 [D loss: 0.677256, acc.: 49.22%] [G loss: 0.724545]
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5944 [D loss: 0.689143, acc.: 50.00%] [G loss: 0.723210]
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5945 [D loss: 0.687373, acc.: 47.85%] [G loss: 0.727461]
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5946 [D loss: 0.691141, acc.: 48.83%] [G loss: 0.720224]
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5947 [D loss: 0.689947, acc.: 47.85%] [G loss: 0.723515]
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5948 [D loss: 0.681419, acc.: 49.41%] [G loss: 0.728423]
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5949 [D loss: 0.687166, acc.: 52.54%] [G loss: 0.727821]
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5950 [D loss: 0.688421, acc.: 50.39%] [G loss: 0.725036]
1/1 [==============================] - 0s 30ms/step
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5951 [D loss: 0.687305, acc.: 51.95%] [G loss: 0.721684]
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5952 [D loss: 0.687577, acc.: 47.07%] [G loss: 0.718469]
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5953 [D loss: 0.695058, acc.: 43.36%] [G loss: 0.727704]
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5954 [D loss: 0.681858, acc.: 52.15%] [G loss: 0.730711]
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5955 [D loss: 0.684922, acc.: 49.02%] [G loss: 0.734549]
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5956 [D loss: 0.686109, acc.: 49.80%] [G loss: 0.725034]
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5957 [D loss: 0.689119, acc.: 49.22%] [G loss: 0.732797]
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5958 [D loss: 0.672220, acc.: 55.27%] [G loss: 0.723773]
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5959 [D loss: 0.677811, acc.: 51.76%] [G loss: 0.742705]
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5960 [D loss: 0.679678, acc.: 53.91%] [G loss: 0.728599]
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5961 [D loss: 0.682647, acc.: 52.93%] [G loss: 0.726809]
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5962 [D loss: 0.687508, acc.: 50.59%] [G loss: 0.720482]
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5963 [D loss: 0.681791, acc.: 51.95%] [G loss: 0.722402]
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5964 [D loss: 0.693636, acc.: 47.85%] [G loss: 0.720896]
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5965 [D loss: 0.687080, acc.: 49.61%] [G loss: 0.713721]
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5966 [D loss: 0.686560, acc.: 47.07%] [G loss: 0.718028]
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5967 [D loss: 0.682754, acc.: 50.00%] [G loss: 0.723747]
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5968 [D loss: 0.689274, acc.: 50.59%] [G loss: 0.721374]
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5969 [D loss: 0.694587, acc.: 44.14%] [G loss: 0.717806]
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5970 [D loss: 0.695745, acc.: 49.61%] [G loss: 0.724773]
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5971 [D loss: 0.684958, acc.: 47.66%] [G loss: 0.742086]
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5972 [D loss: 0.675470, acc.: 53.71%] [G loss: 0.752450]
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5973 [D loss: 0.688871, acc.: 45.90%] [G loss: 0.754680]
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5974 [D loss: 0.681139, acc.: 50.39%] [G loss: 0.757849]
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5975 [D loss: 0.681248, acc.: 48.83%] [G loss: 0.740151]
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5976 [D loss: 0.695674, acc.: 45.31%] [G loss: 0.719052]
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5977 [D loss: 0.695059, acc.: 43.75%] [G loss: 0.720849]
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5978 [D loss: 0.692783, acc.: 50.39%] [G loss: 0.721784]
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5979 [D loss: 0.694281, acc.: 47.07%] [G loss: 0.720171]
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5980 [D loss: 0.695057, acc.: 48.63%] [G loss: 0.730305]
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5981 [D loss: 0.711360, acc.: 51.76%] [G loss: 0.719574]
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5982 [D loss: 0.704263, acc.: 48.63%] [G loss: 0.708782]
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5983 [D loss: 0.701015, acc.: 49.41%] [G loss: 0.712598]
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5984 [D loss: 0.712191, acc.: 46.29%] [G loss: 0.715673]
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5985 [D loss: 0.698236, acc.: 50.78%] [G loss: 0.710594]
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5986 [D loss: 0.697760, acc.: 48.83%] [G loss: 0.720074]
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5987 [D loss: 0.708424, acc.: 43.75%] [G loss: 0.708611]
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5988 [D loss: 0.694715, acc.: 49.41%] [G loss: 0.717340]
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5989 [D loss: 0.699074, acc.: 50.00%] [G loss: 0.730114]
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5990 [D loss: 0.697951, acc.: 49.41%] [G loss: 0.736880]
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5991 [D loss: 0.695818, acc.: 49.22%] [G loss: 0.746032]
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5992 [D loss: 0.697817, acc.: 52.54%] [G loss: 0.737957]
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5993 [D loss: 0.698426, acc.: 52.73%] [G loss: 0.739031]
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5994 [D loss: 0.695355, acc.: 51.17%] [G loss: 0.733052]
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5995 [D loss: 0.699743, acc.: 50.39%] [G loss: 0.727800]
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5996 [D loss: 0.692344, acc.: 49.41%] [G loss: 0.721364]
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5997 [D loss: 0.689312, acc.: 53.71%] [G loss: 0.714613]
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5998 [D loss: 0.693453, acc.: 48.63%] [G loss: 0.717987]
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5999 [D loss: 0.695680, acc.: 49.61%] [G loss: 0.713532]
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6000 [D loss: 0.695529, acc.: 48.83%] [G loss: 0.721469]
1/1 [==============================] - 0s 30ms/step
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6001 [D loss: 0.691862, acc.: 50.00%] [G loss: 0.741255]
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6002 [D loss: 0.690865, acc.: 52.15%] [G loss: 0.747642]
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6003 [D loss: 0.694113, acc.: 49.22%] [G loss: 0.746127]
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6004 [D loss: 0.688103, acc.: 51.76%] [G loss: 0.737756]
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6005 [D loss: 0.701588, acc.: 45.12%] [G loss: 0.733847]
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6006 [D loss: 0.694164, acc.: 48.24%] [G loss: 0.733579]
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6007 [D loss: 0.698563, acc.: 50.20%] [G loss: 0.720285]
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6008 [D loss: 0.692529, acc.: 52.34%] [G loss: 0.723363]
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6009 [D loss: 0.695598, acc.: 49.22%] [G loss: 0.733702]
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6010 [D loss: 0.695503, acc.: 47.85%] [G loss: 0.715404]
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6011 [D loss: 0.692801, acc.: 48.83%] [G loss: 0.740559]
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6012 [D loss: 0.683645, acc.: 55.47%] [G loss: 0.743077]
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6013 [D loss: 0.688178, acc.: 50.59%] [G loss: 0.745550]
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6014 [D loss: 0.687600, acc.: 52.73%] [G loss: 0.734018]
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6015 [D loss: 0.693652, acc.: 49.80%] [G loss: 0.714063]
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6016 [D loss: 0.698493, acc.: 49.41%] [G loss: 0.708434]
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6017 [D loss: 0.697319, acc.: 48.83%] [G loss: 0.705245]
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6018 [D loss: 0.699257, acc.: 47.85%] [G loss: 0.697270]
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6019 [D loss: 0.700194, acc.: 45.90%] [G loss: 0.700683]
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6020 [D loss: 0.704768, acc.: 46.68%] [G loss: 0.700045]
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6021 [D loss: 0.697375, acc.: 45.51%] [G loss: 0.707530]
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6022 [D loss: 0.696024, acc.: 49.02%] [G loss: 0.718942]
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6023 [D loss: 0.688172, acc.: 53.71%] [G loss: 0.741372]
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6024 [D loss: 0.695792, acc.: 50.20%] [G loss: 0.738162]
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6025 [D loss: 0.688121, acc.: 51.76%] [G loss: 0.738626]
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6026 [D loss: 0.692865, acc.: 50.39%] [G loss: 0.731881]
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6027 [D loss: 0.697310, acc.: 49.80%] [G loss: 0.726576]
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6028 [D loss: 0.696732, acc.: 46.88%] [G loss: 0.723981]
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6029 [D loss: 0.694319, acc.: 47.85%] [G loss: 0.716034]
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6030 [D loss: 0.694187, acc.: 45.90%] [G loss: 0.717855]
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6031 [D loss: 0.688611, acc.: 52.34%] [G loss: 0.712269]
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6032 [D loss: 0.693333, acc.: 50.78%] [G loss: 0.710003]
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6033 [D loss: 0.690741, acc.: 48.44%] [G loss: 0.715924]
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6034 [D loss: 0.690051, acc.: 53.32%] [G loss: 0.714984]
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6035 [D loss: 0.689835, acc.: 52.15%] [G loss: 0.730891]
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6036 [D loss: 0.691414, acc.: 49.80%] [G loss: 0.739775]
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6037 [D loss: 0.686972, acc.: 54.30%] [G loss: 0.745371]
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6038 [D loss: 0.691773, acc.: 50.20%] [G loss: 0.738181]
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6039 [D loss: 0.686895, acc.: 49.41%] [G loss: 0.735905]
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6040 [D loss: 0.686335, acc.: 48.83%] [G loss: 0.737347]
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6041 [D loss: 0.695733, acc.: 48.05%] [G loss: 0.740362]
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6042 [D loss: 0.686615, acc.: 50.00%] [G loss: 0.743523]
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6043 [D loss: 0.683626, acc.: 54.88%] [G loss: 0.739097]
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6044 [D loss: 0.678403, acc.: 56.84%] [G loss: 0.758779]
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6045 [D loss: 0.680967, acc.: 55.47%] [G loss: 0.739725]
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6046 [D loss: 0.687529, acc.: 50.78%] [G loss: 0.759733]
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6047 [D loss: 0.686778, acc.: 52.54%] [G loss: 0.725992]
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6048 [D loss: 0.684746, acc.: 51.56%] [G loss: 0.730701]
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6049 [D loss: 0.695122, acc.: 50.78%] [G loss: 0.743053]
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6050 [D loss: 0.699650, acc.: 44.92%] [G loss: 0.716464]
1/1 [==============================] - 0s 28ms/step
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6051 [D loss: 0.696205, acc.: 46.68%] [G loss: 0.717593]
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6052 [D loss: 0.700670, acc.: 45.70%] [G loss: 0.717968]
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6053 [D loss: 0.701164, acc.: 42.38%] [G loss: 0.712839]
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6054 [D loss: 0.700829, acc.: 45.12%] [G loss: 0.714096]
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6055 [D loss: 0.692578, acc.: 53.12%] [G loss: 0.711357]
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6056 [D loss: 0.687207, acc.: 50.39%] [G loss: 0.731678]
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6057 [D loss: 0.683928, acc.: 55.27%] [G loss: 0.725262]
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6058 [D loss: 0.687574, acc.: 51.76%] [G loss: 0.734369]
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6059 [D loss: 0.686950, acc.: 52.73%] [G loss: 0.724353]
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6060 [D loss: 0.692461, acc.: 51.17%] [G loss: 0.725273]
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6061 [D loss: 0.685952, acc.: 48.83%] [G loss: 0.724586]
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6062 [D loss: 0.697312, acc.: 46.68%] [G loss: 0.721025]
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6063 [D loss: 0.696801, acc.: 50.39%] [G loss: 0.716523]
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6064 [D loss: 0.693468, acc.: 49.02%] [G loss: 0.721636]
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6065 [D loss: 0.698983, acc.: 47.46%] [G loss: 0.735647]
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6066 [D loss: 0.691270, acc.: 53.32%] [G loss: 0.746554]
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6067 [D loss: 0.692138, acc.: 51.37%] [G loss: 0.737671]
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6068 [D loss: 0.689543, acc.: 54.49%] [G loss: 0.737377]
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6069 [D loss: 0.700310, acc.: 55.66%] [G loss: 0.732891]
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6070 [D loss: 0.694591, acc.: 52.34%] [G loss: 0.722074]
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6071 [D loss: 0.687536, acc.: 57.23%] [G loss: 0.727714]
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6072 [D loss: 0.700360, acc.: 50.59%] [G loss: 0.721535]
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6073 [D loss: 0.695650, acc.: 51.37%] [G loss: 0.720873]
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6074 [D loss: 0.695031, acc.: 49.02%] [G loss: 0.719552]
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6075 [D loss: 0.698675, acc.: 47.07%] [G loss: 0.703770]
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6076 [D loss: 0.706525, acc.: 42.58%] [G loss: 0.705459]
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6077 [D loss: 0.695626, acc.: 48.83%] [G loss: 0.715500]
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6078 [D loss: 0.700126, acc.: 44.73%] [G loss: 0.719983]
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6079 [D loss: 0.697952, acc.: 46.88%] [G loss: 0.736457]
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6080 [D loss: 0.685920, acc.: 55.08%] [G loss: 0.745297]
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6081 [D loss: 0.689842, acc.: 52.15%] [G loss: 0.740566]
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6082 [D loss: 0.684711, acc.: 55.27%] [G loss: 0.743232]
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6083 [D loss: 0.686721, acc.: 52.54%] [G loss: 0.746148]
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6084 [D loss: 0.689824, acc.: 51.17%] [G loss: 0.729738]
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6085 [D loss: 0.694102, acc.: 50.20%] [G loss: 0.719571]
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6086 [D loss: 0.704872, acc.: 43.55%] [G loss: 0.712469]
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6087 [D loss: 0.708894, acc.: 41.99%] [G loss: 0.702986]
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6088 [D loss: 0.705837, acc.: 42.58%] [G loss: 0.710776]
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6089 [D loss: 0.701852, acc.: 43.36%] [G loss: 0.727543]
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6090 [D loss: 0.690077, acc.: 50.39%] [G loss: 0.735569]
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6091 [D loss: 0.686008, acc.: 55.08%] [G loss: 0.747593]
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6092 [D loss: 0.687376, acc.: 55.47%] [G loss: 0.736748]
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6093 [D loss: 0.695698, acc.: 47.46%] [G loss: 0.730367]
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6094 [D loss: 0.688282, acc.: 55.27%] [G loss: 0.716045]
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6095 [D loss: 0.689555, acc.: 45.51%] [G loss: 0.710890]
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6096 [D loss: 0.692763, acc.: 48.24%] [G loss: 0.708345]
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6097 [D loss: 0.699382, acc.: 47.46%] [G loss: 0.703059]
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6098 [D loss: 0.690510, acc.: 49.41%] [G loss: 0.723144]
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6099 [D loss: 0.691154, acc.: 49.41%] [G loss: 0.720323]
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6100 [D loss: 0.693176, acc.: 48.05%] [G loss: 0.729374]
1/1 [==============================] - 0s 29ms/step
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6101 [D loss: 0.689028, acc.: 51.17%] [G loss: 0.733844]
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6102 [D loss: 0.689152, acc.: 54.30%] [G loss: 0.733074]
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6103 [D loss: 0.687463, acc.: 54.49%] [G loss: 0.731605]
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6104 [D loss: 0.686774, acc.: 52.54%] [G loss: 0.730802]
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6105 [D loss: 0.681321, acc.: 57.42%] [G loss: 0.728008]
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6106 [D loss: 0.693316, acc.: 51.56%] [G loss: 0.726995]
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6107 [D loss: 0.687364, acc.: 53.32%] [G loss: 0.721790]
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6108 [D loss: 0.691910, acc.: 46.29%] [G loss: 0.721240]
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6109 [D loss: 0.692768, acc.: 49.02%] [G loss: 0.723390]
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6110 [D loss: 0.695739, acc.: 47.07%] [G loss: 0.722985]
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6111 [D loss: 0.689821, acc.: 47.85%] [G loss: 0.724860]
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6112 [D loss: 0.692373, acc.: 47.46%] [G loss: 0.735528]
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6113 [D loss: 0.694150, acc.: 47.46%] [G loss: 0.729761]
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6114 [D loss: 0.696411, acc.: 46.09%] [G loss: 0.724832]
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6115 [D loss: 0.692076, acc.: 48.24%] [G loss: 0.728394]
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6116 [D loss: 0.694069, acc.: 52.54%] [G loss: 0.731789]
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6117 [D loss: 0.692229, acc.: 47.27%] [G loss: 0.726887]
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6118 [D loss: 0.691888, acc.: 48.24%] [G loss: 0.737474]
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6119 [D loss: 0.690496, acc.: 49.80%] [G loss: 0.746115]
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6120 [D loss: 0.694265, acc.: 53.12%] [G loss: 0.727137]
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6121 [D loss: 0.693389, acc.: 53.91%] [G loss: 0.728270]
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6122 [D loss: 0.694551, acc.: 53.91%] [G loss: 0.729678]
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6123 [D loss: 0.691535, acc.: 54.49%] [G loss: 0.737562]
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6124 [D loss: 0.692693, acc.: 54.10%] [G loss: 0.722552]
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6125 [D loss: 0.694028, acc.: 50.39%] [G loss: 0.717517]
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6126 [D loss: 0.691297, acc.: 53.52%] [G loss: 0.733124]
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6127 [D loss: 0.692029, acc.: 50.59%] [G loss: 0.743806]
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6128 [D loss: 0.697244, acc.: 46.48%] [G loss: 0.730744]
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6129 [D loss: 0.691746, acc.: 51.76%] [G loss: 0.731908]
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6130 [D loss: 0.694336, acc.: 49.02%] [G loss: 0.719309]
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6131 [D loss: 0.689997, acc.: 51.95%] [G loss: 0.721638]
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6132 [D loss: 0.684755, acc.: 56.45%] [G loss: 0.734684]
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6133 [D loss: 0.691403, acc.: 52.73%] [G loss: 0.728339]
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6134 [D loss: 0.695465, acc.: 50.78%] [G loss: 0.721277]
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6135 [D loss: 0.689318, acc.: 52.54%] [G loss: 0.736463]
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6136 [D loss: 0.694958, acc.: 47.85%] [G loss: 0.749658]
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6137 [D loss: 0.694705, acc.: 46.88%] [G loss: 0.753471]
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6138 [D loss: 0.693948, acc.: 53.12%] [G loss: 0.746175]
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6139 [D loss: 0.695356, acc.: 51.56%] [G loss: 0.730328]
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6140 [D loss: 0.682717, acc.: 58.59%] [G loss: 0.746642]
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6141 [D loss: 0.690660, acc.: 52.34%] [G loss: 0.713147]
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6142 [D loss: 0.690725, acc.: 50.59%] [G loss: 0.709984]
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6143 [D loss: 0.703220, acc.: 45.31%] [G loss: 0.716446]
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6144 [D loss: 0.702215, acc.: 45.70%] [G loss: 0.715229]
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6145 [D loss: 0.699755, acc.: 48.05%] [G loss: 0.724483]
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6146 [D loss: 0.685478, acc.: 52.54%] [G loss: 0.726548]
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6147 [D loss: 0.695508, acc.: 49.02%] [G loss: 0.725560]
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6148 [D loss: 0.690048, acc.: 50.20%] [G loss: 0.728597]
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6149 [D loss: 0.685966, acc.: 53.52%] [G loss: 0.728180]
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6150 [D loss: 0.684650, acc.: 51.76%] [G loss: 0.732424]
1/1 [==============================] - 0s 31ms/step
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6151 [D loss: 0.682328, acc.: 52.15%] [G loss: 0.732165]
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6152 [D loss: 0.688628, acc.: 52.73%] [G loss: 0.732173]
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6153 [D loss: 0.682488, acc.: 54.10%] [G loss: 0.728367]
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6154 [D loss: 0.686759, acc.: 51.17%] [G loss: 0.726570]
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6155 [D loss: 0.685360, acc.: 49.02%] [G loss: 0.729598]
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6156 [D loss: 0.683494, acc.: 54.30%] [G loss: 0.724449]
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6157 [D loss: 0.687615, acc.: 47.85%] [G loss: 0.731220]
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6158 [D loss: 0.684208, acc.: 52.73%] [G loss: 0.725628]
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6159 [D loss: 0.698457, acc.: 46.68%] [G loss: 0.726988]
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6160 [D loss: 0.697359, acc.: 44.14%] [G loss: 0.717657]
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6161 [D loss: 0.697620, acc.: 44.34%] [G loss: 0.716758]
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6162 [D loss: 0.687110, acc.: 46.88%] [G loss: 0.717858]
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6163 [D loss: 0.692065, acc.: 45.70%] [G loss: 0.712892]
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6164 [D loss: 0.707586, acc.: 43.55%] [G loss: 0.707023]
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6165 [D loss: 0.699656, acc.: 46.29%] [G loss: 0.715510]
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6166 [D loss: 0.695402, acc.: 48.24%] [G loss: 0.732079]
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6167 [D loss: 0.696007, acc.: 50.00%] [G loss: 0.726801]
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6168 [D loss: 0.693469, acc.: 50.98%] [G loss: 0.726103]
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6169 [D loss: 0.692175, acc.: 49.22%] [G loss: 0.736628]
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6170 [D loss: 0.689691, acc.: 55.66%] [G loss: 0.730120]
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6171 [D loss: 0.687076, acc.: 53.71%] [G loss: 0.722161]
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6172 [D loss: 0.691036, acc.: 51.56%] [G loss: 0.724462]
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6173 [D loss: 0.692553, acc.: 51.76%] [G loss: 0.726966]
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6174 [D loss: 0.688653, acc.: 54.10%] [G loss: 0.728041]
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6175 [D loss: 0.688023, acc.: 50.78%] [G loss: 0.730321]
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6176 [D loss: 0.689203, acc.: 49.22%] [G loss: 0.739530]
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6177 [D loss: 0.687997, acc.: 51.17%] [G loss: 0.731518]
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6178 [D loss: 0.698475, acc.: 48.05%] [G loss: 0.729128]
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6179 [D loss: 0.688843, acc.: 48.83%] [G loss: 0.720273]
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6180 [D loss: 0.693923, acc.: 44.73%] [G loss: 0.718047]
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6181 [D loss: 0.691068, acc.: 49.61%] [G loss: 0.724846]
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6182 [D loss: 0.690312, acc.: 51.95%] [G loss: 0.723617]
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6183 [D loss: 0.691923, acc.: 48.44%] [G loss: 0.721100]
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6184 [D loss: 0.687790, acc.: 49.80%] [G loss: 0.722902]
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6185 [D loss: 0.684799, acc.: 52.54%] [G loss: 0.732563]
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6186 [D loss: 0.694037, acc.: 52.34%] [G loss: 0.729395]
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6187 [D loss: 0.689090, acc.: 53.12%] [G loss: 0.738131]
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6188 [D loss: 0.690832, acc.: 49.61%] [G loss: 0.738330]
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6189 [D loss: 0.687099, acc.: 50.59%] [G loss: 0.730182]
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6190 [D loss: 0.684189, acc.: 49.80%] [G loss: 0.717645]
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6191 [D loss: 0.690734, acc.: 49.02%] [G loss: 0.718339]
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6192 [D loss: 0.682326, acc.: 50.39%] [G loss: 0.727431]
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6193 [D loss: 0.681182, acc.: 53.12%] [G loss: 0.721911]
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6194 [D loss: 0.695516, acc.: 47.85%] [G loss: 0.721480]
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6195 [D loss: 0.688955, acc.: 49.41%] [G loss: 0.729057]
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6196 [D loss: 0.677427, acc.: 56.84%] [G loss: 0.747497]
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6197 [D loss: 0.687093, acc.: 52.93%] [G loss: 0.748383]
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6198 [D loss: 0.688081, acc.: 50.20%] [G loss: 0.749813]
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6199 [D loss: 0.684951, acc.: 51.37%] [G loss: 0.747039]
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6200 [D loss: 0.686056, acc.: 51.95%] [G loss: 0.742626]
1/1 [==============================] - 0s 28ms/step
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6201 [D loss: 0.688029, acc.: 48.63%] [G loss: 0.737690]
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6202 [D loss: 0.689175, acc.: 44.14%] [G loss: 0.731618]
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6203 [D loss: 0.682107, acc.: 51.37%] [G loss: 0.716369]
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6204 [D loss: 0.683679, acc.: 50.00%] [G loss: 0.715434]
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6205 [D loss: 0.686569, acc.: 43.95%] [G loss: 0.720662]
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6206 [D loss: 0.688568, acc.: 50.78%] [G loss: 0.734614]
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6207 [D loss: 0.685826, acc.: 50.98%] [G loss: 0.734581]
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6208 [D loss: 0.679682, acc.: 49.80%] [G loss: 0.741997]
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6209 [D loss: 0.693227, acc.: 45.70%] [G loss: 0.743547]
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6210 [D loss: 0.693170, acc.: 49.41%] [G loss: 0.731083]
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6211 [D loss: 0.691921, acc.: 47.85%] [G loss: 0.719114]
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6212 [D loss: 0.685273, acc.: 50.78%] [G loss: 0.730715]
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6213 [D loss: 0.685410, acc.: 50.78%] [G loss: 0.736790]
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6214 [D loss: 0.685037, acc.: 50.78%] [G loss: 0.732840]
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6215 [D loss: 0.677519, acc.: 53.12%] [G loss: 0.737353]
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6216 [D loss: 0.688663, acc.: 50.00%] [G loss: 0.721958]
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6217 [D loss: 0.682134, acc.: 48.44%] [G loss: 0.721443]
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6218 [D loss: 0.673077, acc.: 51.95%] [G loss: 0.722019]
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6219 [D loss: 0.670865, acc.: 50.39%] [G loss: 0.724413]
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6220 [D loss: 0.693222, acc.: 44.53%] [G loss: 0.729069]
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6221 [D loss: 0.687511, acc.: 49.80%] [G loss: 0.736177]
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6222 [D loss: 0.673486, acc.: 52.93%] [G loss: 0.744958]
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6223 [D loss: 0.685058, acc.: 48.63%] [G loss: 0.735344]
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6224 [D loss: 0.685729, acc.: 49.22%] [G loss: 0.733998]
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6225 [D loss: 0.684058, acc.: 53.91%] [G loss: 0.721228]
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6226 [D loss: 0.679402, acc.: 51.37%] [G loss: 0.730777]
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6227 [D loss: 0.688207, acc.: 49.41%] [G loss: 0.725814]
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6228 [D loss: 0.684658, acc.: 50.20%] [G loss: 0.728255]
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6229 [D loss: 0.683869, acc.: 51.76%] [G loss: 0.728409]
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6230 [D loss: 0.703330, acc.: 47.85%] [G loss: 0.715907]
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6231 [D loss: 0.702463, acc.: 47.07%] [G loss: 0.722800]
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6232 [D loss: 0.694318, acc.: 47.66%] [G loss: 0.724438]
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6233 [D loss: 0.688558, acc.: 46.88%] [G loss: 0.720891]
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6234 [D loss: 0.694237, acc.: 49.61%] [G loss: 0.747751]
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6235 [D loss: 0.684381, acc.: 53.12%] [G loss: 0.750116]
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6236 [D loss: 0.690766, acc.: 50.59%] [G loss: 0.751714]
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6237 [D loss: 0.694435, acc.: 49.80%] [G loss: 0.736447]
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6238 [D loss: 0.706479, acc.: 48.83%] [G loss: 0.700084]
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6239 [D loss: 0.707669, acc.: 53.32%] [G loss: 0.705122]
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6240 [D loss: 0.701096, acc.: 44.73%] [G loss: 0.700194]
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6241 [D loss: 0.698794, acc.: 46.48%] [G loss: 0.694342]
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6242 [D loss: 0.705991, acc.: 45.31%] [G loss: 0.705045]
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6243 [D loss: 0.699816, acc.: 47.07%] [G loss: 0.727853]
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6244 [D loss: 0.693178, acc.: 51.56%] [G loss: 0.773898]
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6245 [D loss: 0.678789, acc.: 51.95%] [G loss: 0.776392]
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6246 [D loss: 0.698617, acc.: 47.07%] [G loss: 0.767432]
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6247 [D loss: 0.687491, acc.: 55.47%] [G loss: 0.760981]
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6248 [D loss: 0.689088, acc.: 55.66%] [G loss: 0.762305]
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6249 [D loss: 0.677573, acc.: 60.55%] [G loss: 0.749510]
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6250 [D loss: 0.686714, acc.: 52.73%] [G loss: 0.731249]
1/1 [==============================] - 0s 28ms/step
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6251 [D loss: 0.706588, acc.: 46.29%] [G loss: 0.677705]
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6252 [D loss: 0.708913, acc.: 45.12%] [G loss: 0.695328]
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6253 [D loss: 0.698392, acc.: 49.02%] [G loss: 0.742425]
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6254 [D loss: 0.680116, acc.: 55.86%] [G loss: 0.761894]
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6255 [D loss: 0.687072, acc.: 50.98%] [G loss: 0.765904]
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6256 [D loss: 0.691334, acc.: 48.44%] [G loss: 0.758435]
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6257 [D loss: 0.699264, acc.: 45.51%] [G loss: 0.742539]
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6258 [D loss: 0.691648, acc.: 51.37%] [G loss: 0.736176]
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6259 [D loss: 0.689536, acc.: 51.56%] [G loss: 0.735941]
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6260 [D loss: 0.681678, acc.: 54.88%] [G loss: 0.735594]
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6261 [D loss: 0.685551, acc.: 54.49%] [G loss: 0.717279]
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6262 [D loss: 0.679294, acc.: 54.49%] [G loss: 0.705856]
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6263 [D loss: 0.692076, acc.: 49.61%] [G loss: 0.699508]
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6264 [D loss: 0.681515, acc.: 50.98%] [G loss: 0.722419]
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6265 [D loss: 0.684626, acc.: 53.52%] [G loss: 0.734281]
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6266 [D loss: 0.684066, acc.: 50.98%] [G loss: 0.759810]
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6267 [D loss: 0.686277, acc.: 51.76%] [G loss: 0.770653]
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6268 [D loss: 0.678679, acc.: 55.08%] [G loss: 0.756150]
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6269 [D loss: 0.694869, acc.: 46.29%] [G loss: 0.736204]
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6270 [D loss: 0.686884, acc.: 52.15%] [G loss: 0.734786]
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6271 [D loss: 0.686209, acc.: 51.17%] [G loss: 0.734397]
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6272 [D loss: 0.680409, acc.: 50.98%] [G loss: 0.706444]
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6273 [D loss: 0.681689, acc.: 54.49%] [G loss: 0.710849]
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6274 [D loss: 0.681070, acc.: 53.52%] [G loss: 0.716544]
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6275 [D loss: 0.678289, acc.: 52.93%] [G loss: 0.726084]
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6276 [D loss: 0.681669, acc.: 50.39%] [G loss: 0.730038]
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6277 [D loss: 0.681168, acc.: 52.54%] [G loss: 0.737159]
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6278 [D loss: 0.686268, acc.: 49.61%] [G loss: 0.736442]
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6279 [D loss: 0.686438, acc.: 49.22%] [G loss: 0.745513]
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6280 [D loss: 0.688069, acc.: 49.02%] [G loss: 0.737989]
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6281 [D loss: 0.690511, acc.: 48.63%] [G loss: 0.731580]
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6282 [D loss: 0.687527, acc.: 49.61%] [G loss: 0.726441]
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6283 [D loss: 0.687358, acc.: 47.66%] [G loss: 0.736154]
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6284 [D loss: 0.681539, acc.: 50.39%] [G loss: 0.737422]
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6285 [D loss: 0.684119, acc.: 54.49%] [G loss: 0.742971]
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6286 [D loss: 0.685280, acc.: 47.66%] [G loss: 0.737620]
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6287 [D loss: 0.682117, acc.: 51.37%] [G loss: 0.738444]
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6288 [D loss: 0.680115, acc.: 53.52%] [G loss: 0.737261]
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6289 [D loss: 0.692491, acc.: 48.05%] [G loss: 0.738277]
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6290 [D loss: 0.680967, acc.: 47.66%] [G loss: 0.723539]
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6291 [D loss: 0.687995, acc.: 47.85%] [G loss: 0.729371]
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6292 [D loss: 0.689225, acc.: 48.05%] [G loss: 0.716066]
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6293 [D loss: 0.679929, acc.: 49.02%] [G loss: 0.719488]
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6294 [D loss: 0.697816, acc.: 42.58%] [G loss: 0.713874]
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6295 [D loss: 0.690488, acc.: 48.63%] [G loss: 0.732759]
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6296 [D loss: 0.689522, acc.: 50.39%] [G loss: 0.736926]
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6297 [D loss: 0.681895, acc.: 53.71%] [G loss: 0.748324]
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6298 [D loss: 0.688336, acc.: 50.98%] [G loss: 0.744044]
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6299 [D loss: 0.692804, acc.: 50.20%] [G loss: 0.742225]
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6300 [D loss: 0.688879, acc.: 47.66%] [G loss: 0.741693]
1/1 [==============================] - 0s 29ms/step
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6301 [D loss: 0.687284, acc.: 51.95%] [G loss: 0.750598]
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6302 [D loss: 0.695513, acc.: 48.24%] [G loss: 0.722238]
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6303 [D loss: 0.685395, acc.: 52.34%] [G loss: 0.732091]
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6304 [D loss: 0.684734, acc.: 52.54%] [G loss: 0.747416]
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6305 [D loss: 0.691682, acc.: 47.85%] [G loss: 0.740334]
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6306 [D loss: 0.680809, acc.: 54.30%] [G loss: 0.751808]
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6307 [D loss: 0.688496, acc.: 49.02%] [G loss: 0.759483]
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6308 [D loss: 0.685214, acc.: 53.52%] [G loss: 0.742324]
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6309 [D loss: 0.685414, acc.: 50.98%] [G loss: 0.750009]
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6310 [D loss: 0.688049, acc.: 51.56%] [G loss: 0.737811]
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6311 [D loss: 0.697060, acc.: 47.46%] [G loss: 0.710702]
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6312 [D loss: 0.704291, acc.: 46.29%] [G loss: 0.700498]
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6313 [D loss: 0.710222, acc.: 45.70%] [G loss: 0.693547]
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6314 [D loss: 0.703949, acc.: 48.63%] [G loss: 0.713336]
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6315 [D loss: 0.689250, acc.: 51.56%] [G loss: 0.744259]
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6316 [D loss: 0.683778, acc.: 59.18%] [G loss: 0.748030]
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6317 [D loss: 0.690789, acc.: 53.91%] [G loss: 0.738291]
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6318 [D loss: 0.688123, acc.: 55.27%] [G loss: 0.723352]
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6319 [D loss: 0.692676, acc.: 52.54%] [G loss: 0.741872]
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6320 [D loss: 0.700641, acc.: 45.90%] [G loss: 0.710581]
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6321 [D loss: 0.697540, acc.: 46.88%] [G loss: 0.704163]
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6322 [D loss: 0.699687, acc.: 47.66%] [G loss: 0.706873]
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6323 [D loss: 0.696525, acc.: 46.68%] [G loss: 0.719833]
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6324 [D loss: 0.694722, acc.: 47.66%] [G loss: 0.733601]
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6325 [D loss: 0.689271, acc.: 50.98%] [G loss: 0.761567]
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6326 [D loss: 0.689208, acc.: 49.41%] [G loss: 0.767933]
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6327 [D loss: 0.679202, acc.: 51.37%] [G loss: 0.772851]
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6328 [D loss: 0.682374, acc.: 54.88%] [G loss: 0.765259]
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6329 [D loss: 0.673836, acc.: 55.08%] [G loss: 0.766492]
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6330 [D loss: 0.667302, acc.: 59.38%] [G loss: 0.777711]
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6331 [D loss: 0.673763, acc.: 60.35%] [G loss: 0.760179]
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6332 [D loss: 0.671911, acc.: 55.66%] [G loss: 0.761626]
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6333 [D loss: 0.681039, acc.: 52.93%] [G loss: 0.715107]
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6334 [D loss: 0.689349, acc.: 47.27%] [G loss: 0.688287]
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6335 [D loss: 0.696292, acc.: 50.59%] [G loss: 0.723707]
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6336 [D loss: 0.691435, acc.: 52.15%] [G loss: 0.744348]
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6337 [D loss: 0.686321, acc.: 53.52%] [G loss: 0.783864]
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6338 [D loss: 0.681294, acc.: 53.71%] [G loss: 0.791082]
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6339 [D loss: 0.705792, acc.: 48.63%] [G loss: 0.768412]
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6340 [D loss: 0.691947, acc.: 47.66%] [G loss: 0.744135]
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6341 [D loss: 0.686865, acc.: 54.88%] [G loss: 0.753220]
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6342 [D loss: 0.686804, acc.: 53.12%] [G loss: 0.759885]
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6343 [D loss: 0.697941, acc.: 51.17%] [G loss: 0.721388]
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6344 [D loss: 0.693318, acc.: 44.53%] [G loss: 0.704409]
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6345 [D loss: 0.697498, acc.: 48.63%] [G loss: 0.704714]
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6346 [D loss: 0.696600, acc.: 48.83%] [G loss: 0.715993]
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6347 [D loss: 0.690843, acc.: 48.83%] [G loss: 0.736813]
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6348 [D loss: 0.688256, acc.: 51.76%] [G loss: 0.770883]
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6349 [D loss: 0.689800, acc.: 51.37%] [G loss: 0.758103]
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6350 [D loss: 0.678939, acc.: 51.56%] [G loss: 0.777130]
1/1 [==============================] - 0s 32ms/step
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6351 [D loss: 0.684077, acc.: 54.10%] [G loss: 0.748881]
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6352 [D loss: 0.705026, acc.: 46.09%] [G loss: 0.731874]
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6353 [D loss: 0.698312, acc.: 48.24%] [G loss: 0.724636]
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6354 [D loss: 0.702124, acc.: 48.24%] [G loss: 0.727709]
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6355 [D loss: 0.696194, acc.: 53.71%] [G loss: 0.727470]
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6356 [D loss: 0.694050, acc.: 52.73%] [G loss: 0.733597]
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6357 [D loss: 0.690425, acc.: 52.93%] [G loss: 0.739064]
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6358 [D loss: 0.687399, acc.: 58.01%] [G loss: 0.733557]
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6359 [D loss: 0.689563, acc.: 52.34%] [G loss: 0.727503]
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6360 [D loss: 0.686472, acc.: 53.71%] [G loss: 0.731912]
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6361 [D loss: 0.693401, acc.: 47.07%] [G loss: 0.729645]
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6362 [D loss: 0.690417, acc.: 50.98%] [G loss: 0.714936]
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6363 [D loss: 0.698091, acc.: 50.59%] [G loss: 0.714721]
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6364 [D loss: 0.691069, acc.: 52.93%] [G loss: 0.714054]
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6365 [D loss: 0.689208, acc.: 51.76%] [G loss: 0.711628]
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6366 [D loss: 0.683223, acc.: 50.78%] [G loss: 0.724846]
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6367 [D loss: 0.676444, acc.: 57.81%] [G loss: 0.737944]
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6368 [D loss: 0.682403, acc.: 51.37%] [G loss: 0.756674]
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6369 [D loss: 0.689296, acc.: 50.39%] [G loss: 0.748186]
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6370 [D loss: 0.689577, acc.: 50.20%] [G loss: 0.731596]
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6371 [D loss: 0.686604, acc.: 50.78%] [G loss: 0.732357]
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6372 [D loss: 0.686637, acc.: 50.39%] [G loss: 0.727864]
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6373 [D loss: 0.692367, acc.: 46.29%] [G loss: 0.720210]
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6374 [D loss: 0.695314, acc.: 48.05%] [G loss: 0.718484]
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6375 [D loss: 0.689156, acc.: 45.12%] [G loss: 0.713887]
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6376 [D loss: 0.683974, acc.: 50.39%] [G loss: 0.722387]
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6377 [D loss: 0.687549, acc.: 50.00%] [G loss: 0.729631]
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6378 [D loss: 0.682599, acc.: 52.15%] [G loss: 0.747052]
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6379 [D loss: 0.670124, acc.: 56.25%] [G loss: 0.755289]
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6380 [D loss: 0.688136, acc.: 48.05%] [G loss: 0.746192]
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6381 [D loss: 0.675100, acc.: 55.66%] [G loss: 0.750585]
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6382 [D loss: 0.687450, acc.: 50.78%] [G loss: 0.746863]
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6383 [D loss: 0.668133, acc.: 57.23%] [G loss: 0.753263]
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6384 [D loss: 0.682938, acc.: 51.17%] [G loss: 0.737843]
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6385 [D loss: 0.677677, acc.: 50.39%] [G loss: 0.730213]
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6386 [D loss: 0.690804, acc.: 46.88%] [G loss: 0.721992]
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6387 [D loss: 0.682894, acc.: 51.76%] [G loss: 0.722354]
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6388 [D loss: 0.688948, acc.: 47.46%] [G loss: 0.726548]
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6389 [D loss: 0.680590, acc.: 50.20%] [G loss: 0.734517]
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6390 [D loss: 0.686770, acc.: 48.63%] [G loss: 0.751632]
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6391 [D loss: 0.691295, acc.: 48.05%] [G loss: 0.742211]
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6392 [D loss: 0.683624, acc.: 51.76%] [G loss: 0.746204]
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6393 [D loss: 0.677549, acc.: 52.34%] [G loss: 0.752892]
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6394 [D loss: 0.686836, acc.: 49.61%] [G loss: 0.747175]
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6395 [D loss: 0.681596, acc.: 50.98%] [G loss: 0.735809]
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6396 [D loss: 0.684433, acc.: 52.34%] [G loss: 0.746065]
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6397 [D loss: 0.682378, acc.: 51.56%] [G loss: 0.742386]
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6398 [D loss: 0.691726, acc.: 47.07%] [G loss: 0.725385]
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6399 [D loss: 0.675338, acc.: 52.15%] [G loss: 0.729952]
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6400 [D loss: 0.685949, acc.: 51.17%] [G loss: 0.734367]
1/1 [==============================] - 0s 31ms/step
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6401 [D loss: 0.679235, acc.: 50.59%] [G loss: 0.736761]
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6402 [D loss: 0.680307, acc.: 50.59%] [G loss: 0.734310]
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6403 [D loss: 0.684096, acc.: 52.54%] [G loss: 0.734213]
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6404 [D loss: 0.675290, acc.: 53.52%] [G loss: 0.747894]
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6405 [D loss: 0.677893, acc.: 53.91%] [G loss: 0.740741]
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6406 [D loss: 0.679637, acc.: 56.45%] [G loss: 0.726724]
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6407 [D loss: 0.683573, acc.: 52.15%] [G loss: 0.722585]
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6408 [D loss: 0.690556, acc.: 50.59%] [G loss: 0.722984]
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6409 [D loss: 0.680668, acc.: 49.80%] [G loss: 0.719126]
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6410 [D loss: 0.678415, acc.: 51.37%] [G loss: 0.713196]
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6411 [D loss: 0.687890, acc.: 50.59%] [G loss: 0.726182]
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6412 [D loss: 0.686299, acc.: 48.24%] [G loss: 0.739906]
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6413 [D loss: 0.687503, acc.: 50.59%] [G loss: 0.743601]
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6414 [D loss: 0.681846, acc.: 49.80%] [G loss: 0.743915]
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6415 [D loss: 0.682660, acc.: 49.41%] [G loss: 0.736987]
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6416 [D loss: 0.693815, acc.: 46.48%] [G loss: 0.735893]
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6417 [D loss: 0.681808, acc.: 50.00%] [G loss: 0.728806]
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6418 [D loss: 0.691556, acc.: 47.85%] [G loss: 0.728052]
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6419 [D loss: 0.680342, acc.: 49.22%] [G loss: 0.725939]
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6420 [D loss: 0.693641, acc.: 44.73%] [G loss: 0.737931]
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6421 [D loss: 0.694045, acc.: 48.44%] [G loss: 0.732126]
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6422 [D loss: 0.694984, acc.: 53.12%] [G loss: 0.737997]
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6423 [D loss: 0.698591, acc.: 51.95%] [G loss: 0.739176]
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6424 [D loss: 0.695534, acc.: 53.12%] [G loss: 0.746165]
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6425 [D loss: 0.682631, acc.: 54.49%] [G loss: 0.756295]
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6426 [D loss: 0.691040, acc.: 49.22%] [G loss: 0.739416]
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6427 [D loss: 0.682437, acc.: 53.32%] [G loss: 0.741032]
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6428 [D loss: 0.681635, acc.: 51.76%] [G loss: 0.741742]
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6429 [D loss: 0.693811, acc.: 46.29%] [G loss: 0.718242]
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6430 [D loss: 0.680681, acc.: 51.17%] [G loss: 0.718242]
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6431 [D loss: 0.694596, acc.: 48.44%] [G loss: 0.728943]
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6432 [D loss: 0.684912, acc.: 50.59%] [G loss: 0.744705]
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6433 [D loss: 0.684284, acc.: 55.47%] [G loss: 0.746312]
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6434 [D loss: 0.686443, acc.: 53.12%] [G loss: 0.729863]
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6435 [D loss: 0.677091, acc.: 57.62%] [G loss: 0.747778]
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6436 [D loss: 0.680682, acc.: 54.69%] [G loss: 0.730414]
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6437 [D loss: 0.690253, acc.: 48.24%] [G loss: 0.729659]
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6438 [D loss: 0.689990, acc.: 50.39%] [G loss: 0.714937]
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6439 [D loss: 0.688371, acc.: 50.78%] [G loss: 0.733420]
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6440 [D loss: 0.689214, acc.: 48.24%] [G loss: 0.733405]
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6441 [D loss: 0.689563, acc.: 48.44%] [G loss: 0.740786]
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6442 [D loss: 0.685408, acc.: 50.78%] [G loss: 0.752139]
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6443 [D loss: 0.676378, acc.: 53.71%] [G loss: 0.746176]
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6444 [D loss: 0.674559, acc.: 56.25%] [G loss: 0.757520]
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6445 [D loss: 0.681254, acc.: 50.39%] [G loss: 0.740694]
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6446 [D loss: 0.682598, acc.: 51.95%] [G loss: 0.735979]
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6447 [D loss: 0.690471, acc.: 49.02%] [G loss: 0.736629]
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6448 [D loss: 0.691492, acc.: 48.83%] [G loss: 0.742070]
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6449 [D loss: 0.700186, acc.: 48.05%] [G loss: 0.709175]
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6450 [D loss: 0.697919, acc.: 49.02%] [G loss: 0.722807]
1/1 [==============================] - 0s 44ms/step
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6451 [D loss: 0.695115, acc.: 46.88%] [G loss: 0.738515]
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6452 [D loss: 0.684115, acc.: 49.22%] [G loss: 0.743587]
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6453 [D loss: 0.692258, acc.: 50.98%] [G loss: 0.729850]
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6454 [D loss: 0.689462, acc.: 49.02%] [G loss: 0.729410]
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6455 [D loss: 0.691039, acc.: 51.37%] [G loss: 0.729710]
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6456 [D loss: 0.698328, acc.: 47.66%] [G loss: 0.716311]
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6457 [D loss: 0.692231, acc.: 51.76%] [G loss: 0.728431]
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6458 [D loss: 0.692929, acc.: 52.73%] [G loss: 0.735062]
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6459 [D loss: 0.696689, acc.: 46.68%] [G loss: 0.734614]
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6460 [D loss: 0.695350, acc.: 45.70%] [G loss: 0.741250]
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6461 [D loss: 0.692828, acc.: 47.66%] [G loss: 0.739289]
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6462 [D loss: 0.692937, acc.: 47.07%] [G loss: 0.751854]
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6463 [D loss: 0.691256, acc.: 48.05%] [G loss: 0.734954]
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6464 [D loss: 0.691187, acc.: 48.63%] [G loss: 0.754585]
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6465 [D loss: 0.688355, acc.: 46.48%] [G loss: 0.745800]
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6466 [D loss: 0.688282, acc.: 49.22%] [G loss: 0.760165]
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6467 [D loss: 0.673979, acc.: 53.52%] [G loss: 0.777046]
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6468 [D loss: 0.681915, acc.: 53.71%] [G loss: 0.769925]
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6469 [D loss: 0.675501, acc.: 54.30%] [G loss: 0.731668]
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6470 [D loss: 0.683439, acc.: 52.54%] [G loss: 0.731174]
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6471 [D loss: 0.687034, acc.: 52.34%] [G loss: 0.733503]
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6472 [D loss: 0.687371, acc.: 49.41%] [G loss: 0.721504]
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6473 [D loss: 0.682674, acc.: 48.44%] [G loss: 0.731018]
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6474 [D loss: 0.685039, acc.: 50.78%] [G loss: 0.718384]
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6475 [D loss: 0.687252, acc.: 51.17%] [G loss: 0.742460]
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6476 [D loss: 0.682380, acc.: 52.34%] [G loss: 0.752781]
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6477 [D loss: 0.687743, acc.: 49.22%] [G loss: 0.748417]
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6478 [D loss: 0.687633, acc.: 49.22%] [G loss: 0.751568]
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6479 [D loss: 0.695893, acc.: 49.22%] [G loss: 0.737190]
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6480 [D loss: 0.687629, acc.: 52.15%] [G loss: 0.739432]
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6481 [D loss: 0.676937, acc.: 51.76%] [G loss: 0.734273]
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6482 [D loss: 0.677361, acc.: 51.95%] [G loss: 0.725542]
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6483 [D loss: 0.695640, acc.: 45.70%] [G loss: 0.725856]
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6484 [D loss: 0.686176, acc.: 47.07%] [G loss: 0.731878]
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6485 [D loss: 0.684226, acc.: 47.85%] [G loss: 0.735603]
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6486 [D loss: 0.665998, acc.: 58.20%] [G loss: 0.738164]
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6487 [D loss: 0.675191, acc.: 55.66%] [G loss: 0.753058]
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6488 [D loss: 0.675132, acc.: 53.52%] [G loss: 0.758824]
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6489 [D loss: 0.676662, acc.: 55.27%] [G loss: 0.738461]
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6490 [D loss: 0.677330, acc.: 54.10%] [G loss: 0.740006]
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6491 [D loss: 0.672338, acc.: 52.15%] [G loss: 0.729246]
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6492 [D loss: 0.687405, acc.: 49.41%] [G loss: 0.716469]
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6493 [D loss: 0.693231, acc.: 46.68%] [G loss: 0.706644]
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6494 [D loss: 0.690331, acc.: 48.63%] [G loss: 0.720356]
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6495 [D loss: 0.701881, acc.: 46.09%] [G loss: 0.718524]
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6496 [D loss: 0.702589, acc.: 46.68%] [G loss: 0.718249]
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6497 [D loss: 0.696716, acc.: 46.68%] [G loss: 0.726726]
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6498 [D loss: 0.690341, acc.: 49.61%] [G loss: 0.722184]
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6499 [D loss: 0.683993, acc.: 47.85%] [G loss: 0.739115]
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6500 [D loss: 0.682822, acc.: 51.56%] [G loss: 0.744310]
1/1 [==============================] - 0s 27ms/step
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6501 [D loss: 0.682891, acc.: 52.73%] [G loss: 0.741029]
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6502 [D loss: 0.675444, acc.: 56.45%] [G loss: 0.755231]
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6503 [D loss: 0.673492, acc.: 53.52%] [G loss: 0.759495]
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6504 [D loss: 0.672406, acc.: 51.56%] [G loss: 0.794129]
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6505 [D loss: 0.679565, acc.: 52.15%] [G loss: 0.765463]
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6506 [D loss: 0.682313, acc.: 51.56%] [G loss: 0.774786]
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6507 [D loss: 0.684173, acc.: 52.15%] [G loss: 0.768774]
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6508 [D loss: 0.686953, acc.: 50.59%] [G loss: 0.746783]
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6509 [D loss: 0.688922, acc.: 51.56%] [G loss: 0.737014]
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6510 [D loss: 0.686374, acc.: 53.71%] [G loss: 0.728253]
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6511 [D loss: 0.695191, acc.: 49.22%] [G loss: 0.717395]
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6512 [D loss: 0.694942, acc.: 50.20%] [G loss: 0.701387]
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6513 [D loss: 0.691906, acc.: 46.29%] [G loss: 0.722432]
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6514 [D loss: 0.693720, acc.: 46.88%] [G loss: 0.742282]
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6515 [D loss: 0.683737, acc.: 52.15%] [G loss: 0.771933]
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6516 [D loss: 0.686642, acc.: 50.00%] [G loss: 0.784069]
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6517 [D loss: 0.701268, acc.: 48.44%] [G loss: 0.761098]
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6518 [D loss: 0.685505, acc.: 53.71%] [G loss: 0.756053]
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6519 [D loss: 0.677420, acc.: 56.45%] [G loss: 0.767766]
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6520 [D loss: 0.686301, acc.: 50.00%] [G loss: 0.729310]
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6521 [D loss: 0.690033, acc.: 52.34%] [G loss: 0.714842]
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6522 [D loss: 0.687694, acc.: 46.29%] [G loss: 0.719458]
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6523 [D loss: 0.687055, acc.: 50.59%] [G loss: 0.726686]
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6524 [D loss: 0.678816, acc.: 52.54%] [G loss: 0.748857]
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6525 [D loss: 0.690417, acc.: 50.98%] [G loss: 0.742944]
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6526 [D loss: 0.691864, acc.: 48.05%] [G loss: 0.753449]
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6527 [D loss: 0.679485, acc.: 50.98%] [G loss: 0.730513]
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6528 [D loss: 0.691600, acc.: 49.02%] [G loss: 0.733323]
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6529 [D loss: 0.691756, acc.: 46.68%] [G loss: 0.715242]
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6530 [D loss: 0.684441, acc.: 51.17%] [G loss: 0.719266]
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6531 [D loss: 0.682286, acc.: 48.63%] [G loss: 0.720163]
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6532 [D loss: 0.689819, acc.: 45.70%] [G loss: 0.720176]
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6533 [D loss: 0.690740, acc.: 49.02%] [G loss: 0.733904]
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6534 [D loss: 0.688466, acc.: 49.41%] [G loss: 0.746373]
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6535 [D loss: 0.691869, acc.: 47.27%] [G loss: 0.754999]
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6536 [D loss: 0.679550, acc.: 51.17%] [G loss: 0.752483]
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6537 [D loss: 0.689674, acc.: 46.88%] [G loss: 0.743674]
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6538 [D loss: 0.692623, acc.: 52.34%] [G loss: 0.732127]
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6539 [D loss: 0.702947, acc.: 48.44%] [G loss: 0.731013]
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6540 [D loss: 0.693012, acc.: 48.44%] [G loss: 0.730520]
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6541 [D loss: 0.686120, acc.: 49.61%] [G loss: 0.734820]
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6542 [D loss: 0.684345, acc.: 51.17%] [G loss: 0.741258]
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6543 [D loss: 0.678286, acc.: 51.95%] [G loss: 0.745807]
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6544 [D loss: 0.684119, acc.: 52.73%] [G loss: 0.755721]
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6545 [D loss: 0.678216, acc.: 53.71%] [G loss: 0.753373]
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6546 [D loss: 0.690414, acc.: 51.17%] [G loss: 0.756228]
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6547 [D loss: 0.684854, acc.: 51.95%] [G loss: 0.765140]
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6548 [D loss: 0.694731, acc.: 49.80%] [G loss: 0.729364]
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6549 [D loss: 0.684459, acc.: 49.02%] [G loss: 0.725569]
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6550 [D loss: 0.681426, acc.: 53.52%] [G loss: 0.718156]
1/1 [==============================] - 0s 30ms/step
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6551 [D loss: 0.694476, acc.: 45.31%] [G loss: 0.715538]
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6552 [D loss: 0.669934, acc.: 53.52%] [G loss: 0.712986]
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6553 [D loss: 0.686376, acc.: 48.05%] [G loss: 0.721047]
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6554 [D loss: 0.686658, acc.: 50.39%] [G loss: 0.708767]
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6555 [D loss: 0.672566, acc.: 53.71%] [G loss: 0.731973]
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6556 [D loss: 0.670218, acc.: 52.15%] [G loss: 0.728634]
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6557 [D loss: 0.682044, acc.: 51.17%] [G loss: 0.741428]
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6558 [D loss: 0.672856, acc.: 53.12%] [G loss: 0.732125]
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6559 [D loss: 0.685292, acc.: 52.93%] [G loss: 0.723601]
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6560 [D loss: 0.684614, acc.: 48.83%] [G loss: 0.716031]
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6561 [D loss: 0.675800, acc.: 50.00%] [G loss: 0.729663]
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6562 [D loss: 0.673287, acc.: 53.12%] [G loss: 0.734685]
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6563 [D loss: 0.686318, acc.: 53.12%] [G loss: 0.728649]
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6564 [D loss: 0.691613, acc.: 49.22%] [G loss: 0.734593]
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6565 [D loss: 0.685984, acc.: 49.61%] [G loss: 0.733233]
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6566 [D loss: 0.679868, acc.: 51.95%] [G loss: 0.731975]
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6567 [D loss: 0.695563, acc.: 45.31%] [G loss: 0.742550]
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6568 [D loss: 0.687920, acc.: 47.27%] [G loss: 0.735503]
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6569 [D loss: 0.684948, acc.: 46.09%] [G loss: 0.733386]
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6570 [D loss: 0.676868, acc.: 50.98%] [G loss: 0.736419]
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6571 [D loss: 0.696137, acc.: 46.29%] [G loss: 0.723933]
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6572 [D loss: 0.682399, acc.: 50.00%] [G loss: 0.725422]
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6573 [D loss: 0.693239, acc.: 47.27%] [G loss: 0.725022]
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6574 [D loss: 0.678748, acc.: 51.56%] [G loss: 0.734198]
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6575 [D loss: 0.682890, acc.: 51.17%] [G loss: 0.741703]
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6576 [D loss: 0.683107, acc.: 49.61%] [G loss: 0.746592]
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6577 [D loss: 0.685843, acc.: 47.27%] [G loss: 0.741136]
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6578 [D loss: 0.669699, acc.: 52.34%] [G loss: 0.744474]
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6579 [D loss: 0.684744, acc.: 50.78%] [G loss: 0.733921]
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6580 [D loss: 0.682759, acc.: 51.17%] [G loss: 0.734615]
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6581 [D loss: 0.686040, acc.: 48.63%] [G loss: 0.729271]
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6582 [D loss: 0.683332, acc.: 46.48%] [G loss: 0.722152]
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6583 [D loss: 0.677470, acc.: 52.73%] [G loss: 0.724752]
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6584 [D loss: 0.691636, acc.: 45.70%] [G loss: 0.734916]
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6585 [D loss: 0.676028, acc.: 49.41%] [G loss: 0.725145]
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6586 [D loss: 0.684000, acc.: 43.55%] [G loss: 0.723247]
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6587 [D loss: 0.674711, acc.: 48.63%] [G loss: 0.737839]
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6588 [D loss: 0.685102, acc.: 47.07%] [G loss: 0.739850]
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6589 [D loss: 0.678252, acc.: 52.93%] [G loss: 0.741554]
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6590 [D loss: 0.685019, acc.: 51.17%] [G loss: 0.746622]
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6591 [D loss: 0.683263, acc.: 47.27%] [G loss: 0.741703]
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6592 [D loss: 0.677611, acc.: 51.37%] [G loss: 0.731367]
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6593 [D loss: 0.684047, acc.: 50.59%] [G loss: 0.729400]
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6594 [D loss: 0.671338, acc.: 54.10%] [G loss: 0.738114]
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6595 [D loss: 0.690547, acc.: 45.12%] [G loss: 0.719958]
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6596 [D loss: 0.692677, acc.: 48.05%] [G loss: 0.705823]
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6597 [D loss: 0.692401, acc.: 47.85%] [G loss: 0.719138]
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6598 [D loss: 0.689667, acc.: 47.07%] [G loss: 0.721950]
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6599 [D loss: 0.681617, acc.: 50.78%] [G loss: 0.735570]
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6600 [D loss: 0.692830, acc.: 46.29%] [G loss: 0.760064]
1/1 [==============================] - 0s 33ms/step
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6601 [D loss: 0.689567, acc.: 46.48%] [G loss: 0.748571]
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6602 [D loss: 0.674349, acc.: 54.69%] [G loss: 0.752940]
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6603 [D loss: 0.676804, acc.: 50.78%] [G loss: 0.766393]
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6604 [D loss: 0.671389, acc.: 51.17%] [G loss: 0.769437]
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6605 [D loss: 0.685319, acc.: 49.80%] [G loss: 0.784208]
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6606 [D loss: 0.661040, acc.: 55.66%] [G loss: 0.757842]
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6607 [D loss: 0.685403, acc.: 51.17%] [G loss: 0.735668]
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6608 [D loss: 0.690500, acc.: 48.63%] [G loss: 0.750569]
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6609 [D loss: 0.678950, acc.: 55.08%] [G loss: 0.748846]
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6610 [D loss: 0.676683, acc.: 54.30%] [G loss: 0.748728]
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6611 [D loss: 0.685929, acc.: 51.56%] [G loss: 0.744817]
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6612 [D loss: 0.687812, acc.: 47.85%] [G loss: 0.724273]
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6613 [D loss: 0.689441, acc.: 48.44%] [G loss: 0.717101]
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6614 [D loss: 0.686728, acc.: 49.41%] [G loss: 0.722406]
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6615 [D loss: 0.692556, acc.: 47.66%] [G loss: 0.709241]
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6616 [D loss: 0.678619, acc.: 50.39%] [G loss: 0.724879]
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6617 [D loss: 0.678153, acc.: 50.78%] [G loss: 0.730860]
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6618 [D loss: 0.687828, acc.: 46.68%] [G loss: 0.729955]
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6619 [D loss: 0.682203, acc.: 48.24%] [G loss: 0.736249]
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6620 [D loss: 0.681138, acc.: 46.48%] [G loss: 0.745753]
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6621 [D loss: 0.688365, acc.: 50.00%] [G loss: 0.744019]
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6622 [D loss: 0.679934, acc.: 49.61%] [G loss: 0.748554]
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6623 [D loss: 0.687826, acc.: 49.80%] [G loss: 0.739264]
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6624 [D loss: 0.686271, acc.: 49.80%] [G loss: 0.737067]
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6625 [D loss: 0.692301, acc.: 45.90%] [G loss: 0.726746]
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6626 [D loss: 0.687885, acc.: 49.22%] [G loss: 0.738541]
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6627 [D loss: 0.688809, acc.: 48.05%] [G loss: 0.733600]
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6628 [D loss: 0.687056, acc.: 48.24%] [G loss: 0.742216]
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6629 [D loss: 0.681271, acc.: 50.00%] [G loss: 0.738022]
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6630 [D loss: 0.678792, acc.: 51.56%] [G loss: 0.743662]
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6631 [D loss: 0.685499, acc.: 50.59%] [G loss: 0.744811]
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6632 [D loss: 0.686639, acc.: 50.20%] [G loss: 0.742930]
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6633 [D loss: 0.674989, acc.: 52.54%] [G loss: 0.744599]
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6634 [D loss: 0.689199, acc.: 48.83%] [G loss: 0.735343]
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6635 [D loss: 0.685327, acc.: 51.37%] [G loss: 0.738651]
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6636 [D loss: 0.679076, acc.: 54.30%] [G loss: 0.734100]
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6637 [D loss: 0.687406, acc.: 48.63%] [G loss: 0.727631]
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6638 [D loss: 0.682749, acc.: 48.05%] [G loss: 0.721283]
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6639 [D loss: 0.680996, acc.: 47.46%] [G loss: 0.726600]
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6640 [D loss: 0.689976, acc.: 49.41%] [G loss: 0.737328]
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6641 [D loss: 0.679535, acc.: 53.52%] [G loss: 0.733214]
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6642 [D loss: 0.682536, acc.: 50.98%] [G loss: 0.734833]
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6643 [D loss: 0.695390, acc.: 49.41%] [G loss: 0.727355]
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6644 [D loss: 0.679902, acc.: 50.39%] [G loss: 0.719316]
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6645 [D loss: 0.696832, acc.: 45.31%] [G loss: 0.726580]
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6646 [D loss: 0.677224, acc.: 51.95%] [G loss: 0.729894]
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6647 [D loss: 0.681430, acc.: 49.02%] [G loss: 0.727515]
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6648 [D loss: 0.695385, acc.: 46.68%] [G loss: 0.732831]
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6649 [D loss: 0.684859, acc.: 45.70%] [G loss: 0.723292]
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6650 [D loss: 0.683450, acc.: 52.73%] [G loss: 0.729205]
1/1 [==============================] - 0s 32ms/step
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6651 [D loss: 0.682648, acc.: 50.39%] [G loss: 0.738585]
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6652 [D loss: 0.686234, acc.: 52.93%] [G loss: 0.742871]
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6653 [D loss: 0.684956, acc.: 51.76%] [G loss: 0.727528]
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6654 [D loss: 0.676036, acc.: 49.80%] [G loss: 0.726776]
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6655 [D loss: 0.677043, acc.: 52.73%] [G loss: 0.729717]
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6656 [D loss: 0.686495, acc.: 50.20%] [G loss: 0.717557]
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6657 [D loss: 0.692113, acc.: 47.66%] [G loss: 0.711316]
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6658 [D loss: 0.699657, acc.: 49.02%] [G loss: 0.703100]
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6659 [D loss: 0.706424, acc.: 50.39%] [G loss: 0.723876]
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6660 [D loss: 0.695603, acc.: 48.44%] [G loss: 0.726175]
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6661 [D loss: 0.694238, acc.: 45.90%] [G loss: 0.731920]
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6662 [D loss: 0.686512, acc.: 46.48%] [G loss: 0.736658]
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6663 [D loss: 0.697799, acc.: 45.90%] [G loss: 0.738099]
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6664 [D loss: 0.691389, acc.: 46.68%] [G loss: 0.741101]
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6665 [D loss: 0.697867, acc.: 44.73%] [G loss: 0.722137]
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6666 [D loss: 0.691757, acc.: 45.90%] [G loss: 0.728628]
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6667 [D loss: 0.697028, acc.: 49.02%] [G loss: 0.732283]
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6668 [D loss: 0.687714, acc.: 48.63%] [G loss: 0.755812]
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6669 [D loss: 0.688760, acc.: 50.98%] [G loss: 0.757070]
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6670 [D loss: 0.703036, acc.: 50.00%] [G loss: 0.760221]
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6671 [D loss: 0.687821, acc.: 49.41%] [G loss: 0.755980]
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6672 [D loss: 0.687122, acc.: 51.17%] [G loss: 0.801491]
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6673 [D loss: 0.682601, acc.: 58.59%] [G loss: 0.768337]
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6674 [D loss: 0.698701, acc.: 52.73%] [G loss: 0.730542]
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6675 [D loss: 0.692923, acc.: 53.12%] [G loss: 0.718723]
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6676 [D loss: 0.698742, acc.: 47.66%] [G loss: 0.708416]
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6677 [D loss: 0.715913, acc.: 43.36%] [G loss: 0.678982]
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6678 [D loss: 0.705739, acc.: 40.43%] [G loss: 0.700720]
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6679 [D loss: 0.706017, acc.: 41.41%] [G loss: 0.733499]
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6680 [D loss: 0.702900, acc.: 45.12%] [G loss: 0.731334]
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6681 [D loss: 0.694570, acc.: 44.34%] [G loss: 0.729565]
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6682 [D loss: 0.697441, acc.: 44.34%] [G loss: 0.736480]
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6683 [D loss: 0.701185, acc.: 45.70%] [G loss: 0.732467]
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6684 [D loss: 0.693264, acc.: 51.37%] [G loss: 0.738442]
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6685 [D loss: 0.692930, acc.: 49.41%] [G loss: 0.728967]
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6686 [D loss: 0.688435, acc.: 49.41%] [G loss: 0.741011]
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6687 [D loss: 0.683294, acc.: 54.49%] [G loss: 0.726236]
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6688 [D loss: 0.683150, acc.: 54.88%] [G loss: 0.733851]
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6689 [D loss: 0.679778, acc.: 58.20%] [G loss: 0.745002]
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6690 [D loss: 0.686998, acc.: 50.59%] [G loss: 0.743637]
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6691 [D loss: 0.683846, acc.: 51.37%] [G loss: 0.740220]
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6692 [D loss: 0.677202, acc.: 54.69%] [G loss: 0.737256]
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6693 [D loss: 0.695462, acc.: 46.48%] [G loss: 0.741673]
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6694 [D loss: 0.684600, acc.: 51.76%] [G loss: 0.735784]
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6695 [D loss: 0.689521, acc.: 51.56%] [G loss: 0.739414]
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6696 [D loss: 0.684674, acc.: 50.20%] [G loss: 0.732195]
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6697 [D loss: 0.683906, acc.: 50.78%] [G loss: 0.740802]
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6698 [D loss: 0.680353, acc.: 52.73%] [G loss: 0.751403]
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6699 [D loss: 0.679683, acc.: 50.00%] [G loss: 0.742844]
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6700 [D loss: 0.675318, acc.: 57.81%] [G loss: 0.749212]
1/1 [==============================] - 0s 27ms/step
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6701 [D loss: 0.681731, acc.: 53.91%] [G loss: 0.740850]
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6702 [D loss: 0.681265, acc.: 54.10%] [G loss: 0.739834]
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6703 [D loss: 0.685906, acc.: 48.63%] [G loss: 0.727201]
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6704 [D loss: 0.682359, acc.: 47.27%] [G loss: 0.729335]
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6705 [D loss: 0.687321, acc.: 46.09%] [G loss: 0.718139]
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6706 [D loss: 0.686320, acc.: 48.24%] [G loss: 0.723783]
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6707 [D loss: 0.673427, acc.: 51.56%] [G loss: 0.730816]
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6708 [D loss: 0.680333, acc.: 50.20%] [G loss: 0.735628]
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6709 [D loss: 0.687146, acc.: 53.12%] [G loss: 0.746283]
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6710 [D loss: 0.672489, acc.: 56.25%] [G loss: 0.745202]
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6711 [D loss: 0.692371, acc.: 49.61%] [G loss: 0.730084]
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6712 [D loss: 0.674491, acc.: 52.34%] [G loss: 0.726065]
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6713 [D loss: 0.679238, acc.: 51.76%] [G loss: 0.719970]
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6714 [D loss: 0.687457, acc.: 46.68%] [G loss: 0.704483]
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6715 [D loss: 0.687806, acc.: 48.05%] [G loss: 0.712900]
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6716 [D loss: 0.692606, acc.: 47.85%] [G loss: 0.724544]
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6717 [D loss: 0.689283, acc.: 48.05%] [G loss: 0.726104]
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6718 [D loss: 0.683651, acc.: 50.39%] [G loss: 0.748097]
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6719 [D loss: 0.682352, acc.: 52.15%] [G loss: 0.757683]
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6720 [D loss: 0.680425, acc.: 52.73%] [G loss: 0.756937]
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6721 [D loss: 0.683618, acc.: 49.80%] [G loss: 0.762160]
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6722 [D loss: 0.677388, acc.: 57.23%] [G loss: 0.745922]
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6723 [D loss: 0.680364, acc.: 51.56%] [G loss: 0.746551]
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6724 [D loss: 0.696014, acc.: 47.27%] [G loss: 0.742319]
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6725 [D loss: 0.708189, acc.: 48.44%] [G loss: 0.683415]
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6726 [D loss: 0.723458, acc.: 50.59%] [G loss: 0.689960]
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6727 [D loss: 0.713351, acc.: 46.68%] [G loss: 0.710262]
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6728 [D loss: 0.697407, acc.: 46.48%] [G loss: 0.726506]
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6729 [D loss: 0.697349, acc.: 44.53%] [G loss: 0.769228]
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6730 [D loss: 0.686321, acc.: 54.10%] [G loss: 0.760181]
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6731 [D loss: 0.685083, acc.: 52.73%] [G loss: 0.768288]
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6732 [D loss: 0.694202, acc.: 53.71%] [G loss: 0.765266]
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6733 [D loss: 0.690614, acc.: 52.54%] [G loss: 0.748996]
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6734 [D loss: 0.685694, acc.: 53.71%] [G loss: 0.742445]
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6735 [D loss: 0.699581, acc.: 50.39%] [G loss: 0.751106]
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6736 [D loss: 0.704831, acc.: 46.09%] [G loss: 0.733152]
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6737 [D loss: 0.695754, acc.: 45.90%] [G loss: 0.737686]
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6738 [D loss: 0.680181, acc.: 52.73%] [G loss: 0.754404]
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6739 [D loss: 0.687493, acc.: 50.00%] [G loss: 0.751268]
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6740 [D loss: 0.687445, acc.: 50.20%] [G loss: 0.756583]
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6741 [D loss: 0.683621, acc.: 52.54%] [G loss: 0.758713]
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6742 [D loss: 0.688829, acc.: 50.78%] [G loss: 0.743611]
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6743 [D loss: 0.676385, acc.: 56.05%] [G loss: 0.744356]
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6744 [D loss: 0.685455, acc.: 52.15%] [G loss: 0.735962]
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6745 [D loss: 0.678609, acc.: 57.23%] [G loss: 0.752288]
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6746 [D loss: 0.685269, acc.: 54.30%] [G loss: 0.736351]
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6747 [D loss: 0.685066, acc.: 51.95%] [G loss: 0.735809]
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6748 [D loss: 0.686540, acc.: 52.54%] [G loss: 0.714648]
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6749 [D loss: 0.693918, acc.: 45.12%] [G loss: 0.720243]
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6750 [D loss: 0.700297, acc.: 43.55%] [G loss: 0.708799]
1/1 [==============================] - 0s 26ms/step
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6751 [D loss: 0.698565, acc.: 44.53%] [G loss: 0.710426]
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6752 [D loss: 0.703936, acc.: 43.75%] [G loss: 0.719403]
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6753 [D loss: 0.690625, acc.: 49.61%] [G loss: 0.738464]
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6754 [D loss: 0.694833, acc.: 49.61%] [G loss: 0.750975]
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6755 [D loss: 0.687360, acc.: 55.47%] [G loss: 0.758408]
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6756 [D loss: 0.691679, acc.: 51.56%] [G loss: 0.748335]
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6757 [D loss: 0.691000, acc.: 53.52%] [G loss: 0.734163]
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6758 [D loss: 0.688520, acc.: 54.88%] [G loss: 0.732736]
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6759 [D loss: 0.688890, acc.: 54.88%] [G loss: 0.727793]
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6760 [D loss: 0.694927, acc.: 49.61%] [G loss: 0.715870]
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6761 [D loss: 0.695297, acc.: 52.54%] [G loss: 0.720882]
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6762 [D loss: 0.691526, acc.: 50.00%] [G loss: 0.765630]
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6763 [D loss: 0.697744, acc.: 48.63%] [G loss: 0.754248]
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6764 [D loss: 0.697677, acc.: 52.15%] [G loss: 0.747551]
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6765 [D loss: 0.689150, acc.: 52.34%] [G loss: 0.736745]
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6766 [D loss: 0.684972, acc.: 52.54%] [G loss: 0.761320]
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6767 [D loss: 0.692391, acc.: 49.41%] [G loss: 0.723728]
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6768 [D loss: 0.684860, acc.: 50.98%] [G loss: 0.723092]
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6769 [D loss: 0.688406, acc.: 48.83%] [G loss: 0.756437]
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6770 [D loss: 0.676595, acc.: 51.56%] [G loss: 0.778922]
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6771 [D loss: 0.682685, acc.: 51.95%] [G loss: 0.774579]
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6772 [D loss: 0.685793, acc.: 49.41%] [G loss: 0.765998]
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6773 [D loss: 0.683564, acc.: 51.56%] [G loss: 0.757004]
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6774 [D loss: 0.672476, acc.: 56.25%] [G loss: 0.781880]
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6775 [D loss: 0.688169, acc.: 50.59%] [G loss: 0.744519]
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6776 [D loss: 0.677438, acc.: 56.45%] [G loss: 0.726146]
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6777 [D loss: 0.692864, acc.: 47.66%] [G loss: 0.734745]
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6778 [D loss: 0.685949, acc.: 46.29%] [G loss: 0.724891]
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6779 [D loss: 0.683973, acc.: 51.17%] [G loss: 0.739987]
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6780 [D loss: 0.691193, acc.: 45.51%] [G loss: 0.736592]
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6781 [D loss: 0.685027, acc.: 47.07%] [G loss: 0.735660]
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6782 [D loss: 0.683030, acc.: 50.20%] [G loss: 0.729545]
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6783 [D loss: 0.678279, acc.: 51.17%] [G loss: 0.737787]
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6784 [D loss: 0.680105, acc.: 51.56%] [G loss: 0.722551]
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6785 [D loss: 0.688218, acc.: 46.48%] [G loss: 0.722237]
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6786 [D loss: 0.689697, acc.: 50.00%] [G loss: 0.708105]
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6787 [D loss: 0.684920, acc.: 46.88%] [G loss: 0.718389]
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6788 [D loss: 0.686077, acc.: 48.83%] [G loss: 0.727261]
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6789 [D loss: 0.692290, acc.: 43.75%] [G loss: 0.741030]
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6790 [D loss: 0.682500, acc.: 47.85%] [G loss: 0.732100]
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6791 [D loss: 0.687687, acc.: 48.24%] [G loss: 0.734930]
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6792 [D loss: 0.689086, acc.: 47.85%] [G loss: 0.745975]
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6793 [D loss: 0.679043, acc.: 54.88%] [G loss: 0.745636]
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6794 [D loss: 0.690802, acc.: 47.27%] [G loss: 0.735790]
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6795 [D loss: 0.685062, acc.: 50.39%] [G loss: 0.728381]
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6796 [D loss: 0.684577, acc.: 50.00%] [G loss: 0.732332]
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6797 [D loss: 0.686100, acc.: 48.05%] [G loss: 0.740860]
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6798 [D loss: 0.701211, acc.: 46.68%] [G loss: 0.745417]
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6799 [D loss: 0.675331, acc.: 52.34%] [G loss: 0.744214]
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6800 [D loss: 0.689188, acc.: 49.41%] [G loss: 0.735549]
1/1 [==============================] - 0s 32ms/step
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6801 [D loss: 0.674923, acc.: 51.56%] [G loss: 0.736352]
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6802 [D loss: 0.688501, acc.: 48.24%] [G loss: 0.731258]
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6803 [D loss: 0.678038, acc.: 53.12%] [G loss: 0.729475]
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6804 [D loss: 0.675255, acc.: 50.00%] [G loss: 0.727332]
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6805 [D loss: 0.700016, acc.: 46.29%] [G loss: 0.711612]
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6806 [D loss: 0.687652, acc.: 46.68%] [G loss: 0.702477]
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6807 [D loss: 0.698455, acc.: 48.83%] [G loss: 0.713169]
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6808 [D loss: 0.703438, acc.: 44.73%] [G loss: 0.705126]
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6809 [D loss: 0.696754, acc.: 46.68%] [G loss: 0.725021]
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6810 [D loss: 0.686732, acc.: 51.76%] [G loss: 0.753313]
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6811 [D loss: 0.683980, acc.: 49.61%] [G loss: 0.765795]
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6812 [D loss: 0.688685, acc.: 50.59%] [G loss: 0.748028]
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6813 [D loss: 0.679162, acc.: 55.86%] [G loss: 0.758976]
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6814 [D loss: 0.686849, acc.: 52.73%] [G loss: 0.750264]
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6815 [D loss: 0.689695, acc.: 51.56%] [G loss: 0.745018]
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6816 [D loss: 0.692448, acc.: 47.46%] [G loss: 0.731091]
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6817 [D loss: 0.692624, acc.: 51.56%] [G loss: 0.745074]
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6818 [D loss: 0.691787, acc.: 51.56%] [G loss: 0.739530]
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6819 [D loss: 0.690805, acc.: 52.73%] [G loss: 0.742197]
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6820 [D loss: 0.694616, acc.: 49.61%] [G loss: 0.755033]
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6821 [D loss: 0.699058, acc.: 46.09%] [G loss: 0.737584]
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6822 [D loss: 0.684697, acc.: 50.59%] [G loss: 0.741764]
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6823 [D loss: 0.692918, acc.: 49.80%] [G loss: 0.738731]
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6824 [D loss: 0.688584, acc.: 49.41%] [G loss: 0.744338]
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6825 [D loss: 0.682770, acc.: 55.47%] [G loss: 0.738378]
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6826 [D loss: 0.698063, acc.: 48.05%] [G loss: 0.743325]
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6827 [D loss: 0.687890, acc.: 53.32%] [G loss: 0.732711]
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6828 [D loss: 0.681560, acc.: 56.05%] [G loss: 0.726192]
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6829 [D loss: 0.686698, acc.: 50.00%] [G loss: 0.727989]
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6830 [D loss: 0.698764, acc.: 48.83%] [G loss: 0.736429]
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6831 [D loss: 0.689411, acc.: 52.93%] [G loss: 0.733309]
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6832 [D loss: 0.699617, acc.: 52.93%] [G loss: 0.729371]
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6833 [D loss: 0.696244, acc.: 51.17%] [G loss: 0.750612]
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6834 [D loss: 0.697221, acc.: 47.66%] [G loss: 0.719817]
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6835 [D loss: 0.690984, acc.: 48.83%] [G loss: 0.726859]
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6836 [D loss: 0.692059, acc.: 49.41%] [G loss: 0.751806]
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6837 [D loss: 0.687491, acc.: 50.00%] [G loss: 0.748224]
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6838 [D loss: 0.679518, acc.: 58.40%] [G loss: 0.752486]
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6839 [D loss: 0.688444, acc.: 50.20%] [G loss: 0.740611]
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6840 [D loss: 0.699601, acc.: 44.73%] [G loss: 0.722766]
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6841 [D loss: 0.695927, acc.: 44.73%] [G loss: 0.720720]
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6842 [D loss: 0.690386, acc.: 48.63%] [G loss: 0.719491]
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6843 [D loss: 0.688923, acc.: 50.98%] [G loss: 0.726336]
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6844 [D loss: 0.687366, acc.: 49.41%] [G loss: 0.741633]
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6845 [D loss: 0.692327, acc.: 49.61%] [G loss: 0.740630]
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6846 [D loss: 0.687867, acc.: 46.48%] [G loss: 0.745746]
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6847 [D loss: 0.690487, acc.: 49.61%] [G loss: 0.732050]
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6848 [D loss: 0.693348, acc.: 51.76%] [G loss: 0.744452]
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6849 [D loss: 0.695751, acc.: 49.02%] [G loss: 0.715433]
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6850 [D loss: 0.698621, acc.: 47.07%] [G loss: 0.717153]
1/1 [==============================] - 0s 30ms/step
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6851 [D loss: 0.720017, acc.: 48.83%] [G loss: 0.695423]
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6852 [D loss: 0.699862, acc.: 46.48%] [G loss: 0.704145]
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6853 [D loss: 0.698820, acc.: 45.90%] [G loss: 0.721371]
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6854 [D loss: 0.690843, acc.: 49.22%] [G loss: 0.757057]
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6855 [D loss: 0.691695, acc.: 51.17%] [G loss: 0.767892]
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6856 [D loss: 0.689217, acc.: 50.98%] [G loss: 0.767628]
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6857 [D loss: 0.684901, acc.: 52.34%] [G loss: 0.759542]
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6858 [D loss: 0.690384, acc.: 53.52%] [G loss: 0.757797]
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6859 [D loss: 0.673789, acc.: 57.81%] [G loss: 0.755618]
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6860 [D loss: 0.679148, acc.: 55.47%] [G loss: 0.737237]
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6861 [D loss: 0.684433, acc.: 53.32%] [G loss: 0.748369]
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6862 [D loss: 0.678175, acc.: 51.37%] [G loss: 0.748141]
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6863 [D loss: 0.680490, acc.: 50.78%] [G loss: 0.759868]
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6864 [D loss: 0.687425, acc.: 53.32%] [G loss: 0.745585]
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6865 [D loss: 0.688396, acc.: 49.41%] [G loss: 0.742556]
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6866 [D loss: 0.697669, acc.: 45.90%] [G loss: 0.751948]
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6867 [D loss: 0.701545, acc.: 46.48%] [G loss: 0.763263]
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6868 [D loss: 0.702148, acc.: 42.97%] [G loss: 0.735774]
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6869 [D loss: 0.698350, acc.: 48.44%] [G loss: 0.742401]
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6870 [D loss: 0.689991, acc.: 50.98%] [G loss: 0.755313]
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6871 [D loss: 0.701617, acc.: 46.68%] [G loss: 0.703179]
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6872 [D loss: 0.703470, acc.: 50.00%] [G loss: 0.702740]
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6873 [D loss: 0.707651, acc.: 46.88%] [G loss: 0.737930]
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6874 [D loss: 0.687429, acc.: 53.32%] [G loss: 0.771046]
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6875 [D loss: 0.685470, acc.: 53.52%] [G loss: 0.767895]
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6876 [D loss: 0.693538, acc.: 48.63%] [G loss: 0.757853]
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6877 [D loss: 0.683985, acc.: 53.91%] [G loss: 0.761367]
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6878 [D loss: 0.692332, acc.: 52.73%] [G loss: 0.740698]
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6879 [D loss: 0.674663, acc.: 55.47%] [G loss: 0.737813]
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6880 [D loss: 0.692463, acc.: 45.90%] [G loss: 0.731473]
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6881 [D loss: 0.686386, acc.: 55.27%] [G loss: 0.733189]
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6882 [D loss: 0.695400, acc.: 48.44%] [G loss: 0.739355]
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6883 [D loss: 0.680026, acc.: 51.56%] [G loss: 0.744589]
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6884 [D loss: 0.687830, acc.: 51.56%] [G loss: 0.741317]
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6885 [D loss: 0.690363, acc.: 52.34%] [G loss: 0.745512]
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6886 [D loss: 0.690082, acc.: 48.05%] [G loss: 0.735268]
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6887 [D loss: 0.692294, acc.: 47.46%] [G loss: 0.729348]
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6888 [D loss: 0.687829, acc.: 48.44%] [G loss: 0.726998]
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6889 [D loss: 0.696040, acc.: 50.78%] [G loss: 0.704431]
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6890 [D loss: 0.722376, acc.: 48.44%] [G loss: 0.692325]
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6891 [D loss: 0.704068, acc.: 47.85%] [G loss: 0.695399]
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6892 [D loss: 0.704530, acc.: 45.31%] [G loss: 0.703360]
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6893 [D loss: 0.694826, acc.: 49.22%] [G loss: 0.725805]
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6894 [D loss: 0.693481, acc.: 53.71%] [G loss: 0.742962]
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6895 [D loss: 0.694009, acc.: 49.41%] [G loss: 0.757314]
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6896 [D loss: 0.697599, acc.: 48.83%] [G loss: 0.737801]
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6897 [D loss: 0.699109, acc.: 47.66%] [G loss: 0.738775]
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6898 [D loss: 0.699377, acc.: 50.00%] [G loss: 0.727680]
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6899 [D loss: 0.693500, acc.: 49.80%] [G loss: 0.726010]
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6900 [D loss: 0.691258, acc.: 51.56%] [G loss: 0.727652]
1/1 [==============================] - 0s 29ms/step
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6901 [D loss: 0.697286, acc.: 48.83%] [G loss: 0.713239]
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6902 [D loss: 0.693512, acc.: 50.78%] [G loss: 0.711634]
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6903 [D loss: 0.693478, acc.: 46.29%] [G loss: 0.732703]
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6904 [D loss: 0.693233, acc.: 49.61%] [G loss: 0.729986]
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6905 [D loss: 0.697090, acc.: 50.59%] [G loss: 0.732077]
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6906 [D loss: 0.691902, acc.: 51.56%] [G loss: 0.730229]
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6907 [D loss: 0.691773, acc.: 48.24%] [G loss: 0.747216]
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6908 [D loss: 0.692725, acc.: 49.80%] [G loss: 0.721989]
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6909 [D loss: 0.684292, acc.: 51.95%] [G loss: 0.727333]
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6910 [D loss: 0.686838, acc.: 48.83%] [G loss: 0.725743]
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6911 [D loss: 0.683057, acc.: 54.88%] [G loss: 0.724048]
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6912 [D loss: 0.685829, acc.: 52.93%] [G loss: 0.727258]
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6913 [D loss: 0.698394, acc.: 46.09%] [G loss: 0.720128]
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6914 [D loss: 0.692787, acc.: 48.63%] [G loss: 0.711343]
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6915 [D loss: 0.689542, acc.: 50.98%] [G loss: 0.720616]
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6916 [D loss: 0.689995, acc.: 48.05%] [G loss: 0.724219]
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6917 [D loss: 0.691945, acc.: 48.05%] [G loss: 0.723979]
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6918 [D loss: 0.695364, acc.: 45.12%] [G loss: 0.715973]
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6919 [D loss: 0.690876, acc.: 48.44%] [G loss: 0.712387]
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6920 [D loss: 0.692194, acc.: 47.27%] [G loss: 0.714294]
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6921 [D loss: 0.693102, acc.: 50.20%] [G loss: 0.726737]
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6922 [D loss: 0.684263, acc.: 51.37%] [G loss: 0.725642]
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6923 [D loss: 0.685426, acc.: 50.59%] [G loss: 0.731116]
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6924 [D loss: 0.679523, acc.: 51.37%] [G loss: 0.733849]
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6925 [D loss: 0.680169, acc.: 50.59%] [G loss: 0.738099]
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6926 [D loss: 0.687494, acc.: 48.05%] [G loss: 0.725651]
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6927 [D loss: 0.678875, acc.: 54.10%] [G loss: 0.728474]
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6928 [D loss: 0.694121, acc.: 47.85%] [G loss: 0.725955]
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6929 [D loss: 0.699248, acc.: 45.31%] [G loss: 0.720932]
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6930 [D loss: 0.689872, acc.: 49.41%] [G loss: 0.725772]
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6931 [D loss: 0.689151, acc.: 48.83%] [G loss: 0.723491]
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6932 [D loss: 0.680272, acc.: 51.95%] [G loss: 0.734529]
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6933 [D loss: 0.673967, acc.: 55.27%] [G loss: 0.739278]
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6934 [D loss: 0.684560, acc.: 51.76%] [G loss: 0.740897]
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6935 [D loss: 0.682000, acc.: 52.73%] [G loss: 0.739510]
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6936 [D loss: 0.680119, acc.: 54.69%] [G loss: 0.739430]
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6937 [D loss: 0.679677, acc.: 52.54%] [G loss: 0.735179]
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6938 [D loss: 0.678951, acc.: 50.98%] [G loss: 0.737997]
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6939 [D loss: 0.683381, acc.: 51.56%] [G loss: 0.724935]
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6940 [D loss: 0.685222, acc.: 52.34%] [G loss: 0.732703]
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6941 [D loss: 0.692334, acc.: 49.02%] [G loss: 0.718886]
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6942 [D loss: 0.690390, acc.: 44.14%] [G loss: 0.714484]
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6943 [D loss: 0.695499, acc.: 45.51%] [G loss: 0.722853]
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6944 [D loss: 0.686616, acc.: 50.20%] [G loss: 0.735196]
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6945 [D loss: 0.686823, acc.: 55.27%] [G loss: 0.736773]
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6946 [D loss: 0.689098, acc.: 48.44%] [G loss: 0.733956]
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6947 [D loss: 0.692315, acc.: 51.17%] [G loss: 0.731592]
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6948 [D loss: 0.687588, acc.: 52.15%] [G loss: 0.730362]
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6949 [D loss: 0.698943, acc.: 46.29%] [G loss: 0.711552]
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6950 [D loss: 0.694399, acc.: 48.83%] [G loss: 0.712009]
1/1 [==============================] - 0s 32ms/step
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6951 [D loss: 0.702805, acc.: 46.68%] [G loss: 0.703416]
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6952 [D loss: 0.699750, acc.: 44.14%] [G loss: 0.712711]
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6953 [D loss: 0.695253, acc.: 49.41%] [G loss: 0.728496]
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6954 [D loss: 0.691722, acc.: 48.05%] [G loss: 0.742590]
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6955 [D loss: 0.687839, acc.: 48.63%] [G loss: 0.749560]
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6956 [D loss: 0.691015, acc.: 49.61%] [G loss: 0.749875]
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6957 [D loss: 0.693867, acc.: 48.24%] [G loss: 0.731165]
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6958 [D loss: 0.691508, acc.: 50.59%] [G loss: 0.732501]
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6959 [D loss: 0.681883, acc.: 54.88%] [G loss: 0.728954]
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6960 [D loss: 0.684864, acc.: 50.39%] [G loss: 0.731948]
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6961 [D loss: 0.693752, acc.: 48.83%] [G loss: 0.717719]
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6962 [D loss: 0.696631, acc.: 48.63%] [G loss: 0.734615]
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6963 [D loss: 0.692556, acc.: 51.56%] [G loss: 0.727164]
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6964 [D loss: 0.694565, acc.: 51.76%] [G loss: 0.746529]
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6965 [D loss: 0.705374, acc.: 44.34%] [G loss: 0.742526]
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6966 [D loss: 0.698462, acc.: 48.63%] [G loss: 0.730408]
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6967 [D loss: 0.696103, acc.: 53.52%] [G loss: 0.748803]
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6968 [D loss: 0.685990, acc.: 55.27%] [G loss: 0.731311]
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6969 [D loss: 0.699265, acc.: 49.22%] [G loss: 0.714679]
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6970 [D loss: 0.692172, acc.: 52.15%] [G loss: 0.717258]
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6971 [D loss: 0.697347, acc.: 49.61%] [G loss: 0.722974]
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6972 [D loss: 0.698331, acc.: 45.90%] [G loss: 0.734414]
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6973 [D loss: 0.697581, acc.: 50.20%] [G loss: 0.746212]
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6974 [D loss: 0.706933, acc.: 37.89%] [G loss: 0.736953]
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6975 [D loss: 0.704376, acc.: 43.36%] [G loss: 0.726213]
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6976 [D loss: 0.695343, acc.: 49.22%] [G loss: 0.728486]
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6977 [D loss: 0.689428, acc.: 52.34%] [G loss: 0.723980]
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6978 [D loss: 0.696401, acc.: 49.61%] [G loss: 0.728773]
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6979 [D loss: 0.697925, acc.: 48.24%] [G loss: 0.712424]
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6980 [D loss: 0.692142, acc.: 50.39%] [G loss: 0.708666]
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6981 [D loss: 0.689533, acc.: 50.78%] [G loss: 0.731185]
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6982 [D loss: 0.697370, acc.: 48.05%] [G loss: 0.735165]
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6983 [D loss: 0.693407, acc.: 49.61%] [G loss: 0.734602]
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6984 [D loss: 0.701333, acc.: 43.36%] [G loss: 0.742747]
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6985 [D loss: 0.694915, acc.: 49.41%] [G loss: 0.740169]
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6986 [D loss: 0.693528, acc.: 49.41%] [G loss: 0.726970]
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6987 [D loss: 0.691057, acc.: 50.98%] [G loss: 0.744049]
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6988 [D loss: 0.689450, acc.: 48.44%] [G loss: 0.729174]
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6989 [D loss: 0.688827, acc.: 52.73%] [G loss: 0.736664]
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6990 [D loss: 0.688918, acc.: 51.76%] [G loss: 0.723674]
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6991 [D loss: 0.693217, acc.: 48.83%] [G loss: 0.704673]
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6992 [D loss: 0.688043, acc.: 51.17%] [G loss: 0.709766]
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6993 [D loss: 0.689086, acc.: 51.95%] [G loss: 0.705755]
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6994 [D loss: 0.695195, acc.: 47.07%] [G loss: 0.725121]
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6995 [D loss: 0.688102, acc.: 50.59%] [G loss: 0.721425]
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6996 [D loss: 0.683216, acc.: 49.80%] [G loss: 0.722031]
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6997 [D loss: 0.684009, acc.: 53.12%] [G loss: 0.738041]
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6998 [D loss: 0.687580, acc.: 55.86%] [G loss: 0.732613]
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6999 [D loss: 0.679206, acc.: 58.01%] [G loss: 0.730704]
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7000 [D loss: 0.688498, acc.: 52.73%] [G loss: 0.726595]
1/1 [==============================] - 0s 31ms/step
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7001 [D loss: 0.686739, acc.: 50.98%] [G loss: 0.708329]
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7002 [D loss: 0.688720, acc.: 49.02%] [G loss: 0.713721]
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7003 [D loss: 0.690566, acc.: 49.41%] [G loss: 0.719180]
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7004 [D loss: 0.694483, acc.: 47.27%] [G loss: 0.728336]
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7005 [D loss: 0.685270, acc.: 49.80%] [G loss: 0.737722]
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7006 [D loss: 0.689365, acc.: 52.73%] [G loss: 0.735892]
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7007 [D loss: 0.693417, acc.: 49.61%] [G loss: 0.736736]
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7008 [D loss: 0.680883, acc.: 52.34%] [G loss: 0.723718]
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7009 [D loss: 0.685383, acc.: 50.78%] [G loss: 0.727909]
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7010 [D loss: 0.684065, acc.: 51.76%] [G loss: 0.727463]
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7011 [D loss: 0.678583, acc.: 52.73%] [G loss: 0.722383]
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7012 [D loss: 0.680423, acc.: 50.39%] [G loss: 0.732059]
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7013 [D loss: 0.689615, acc.: 49.02%] [G loss: 0.722770]
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7014 [D loss: 0.683300, acc.: 53.12%] [G loss: 0.722665]
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7015 [D loss: 0.685770, acc.: 51.37%] [G loss: 0.723431]
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7016 [D loss: 0.686567, acc.: 54.30%] [G loss: 0.725278]
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7017 [D loss: 0.692234, acc.: 50.98%] [G loss: 0.719190]
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7018 [D loss: 0.692654, acc.: 50.20%] [G loss: 0.732492]
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7019 [D loss: 0.683217, acc.: 49.41%] [G loss: 0.738444]
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7020 [D loss: 0.680771, acc.: 51.95%] [G loss: 0.737639]
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7021 [D loss: 0.675906, acc.: 54.49%] [G loss: 0.742449]
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7022 [D loss: 0.690292, acc.: 51.17%] [G loss: 0.743876]
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7023 [D loss: 0.682351, acc.: 53.32%] [G loss: 0.749243]
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7024 [D loss: 0.691328, acc.: 47.27%] [G loss: 0.731333]
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7025 [D loss: 0.688634, acc.: 50.20%] [G loss: 0.722398]
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7026 [D loss: 0.691592, acc.: 49.80%] [G loss: 0.722598]
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7027 [D loss: 0.690441, acc.: 50.39%] [G loss: 0.713631]
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7028 [D loss: 0.697604, acc.: 46.29%] [G loss: 0.707586]
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7029 [D loss: 0.700897, acc.: 43.55%] [G loss: 0.716174]
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7030 [D loss: 0.699594, acc.: 48.24%] [G loss: 0.728474]
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7031 [D loss: 0.689934, acc.: 51.56%] [G loss: 0.732455]
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7032 [D loss: 0.690589, acc.: 52.34%] [G loss: 0.729519]
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7033 [D loss: 0.702847, acc.: 45.51%] [G loss: 0.734630]
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7034 [D loss: 0.694879, acc.: 50.78%] [G loss: 0.719502]
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7035 [D loss: 0.696225, acc.: 49.22%] [G loss: 0.714551]
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7036 [D loss: 0.694061, acc.: 49.22%] [G loss: 0.717327]
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7037 [D loss: 0.694302, acc.: 48.44%] [G loss: 0.726626]
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7038 [D loss: 0.697202, acc.: 48.05%] [G loss: 0.719826]
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7039 [D loss: 0.692460, acc.: 55.08%] [G loss: 0.729025]
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7040 [D loss: 0.686993, acc.: 51.17%] [G loss: 0.751618]
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7041 [D loss: 0.697140, acc.: 47.07%] [G loss: 0.729674]
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7042 [D loss: 0.696900, acc.: 48.44%] [G loss: 0.732107]
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7043 [D loss: 0.689636, acc.: 56.45%] [G loss: 0.728350]
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7044 [D loss: 0.686627, acc.: 51.56%] [G loss: 0.743691]
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7045 [D loss: 0.687016, acc.: 52.73%] [G loss: 0.743719]
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7046 [D loss: 0.689906, acc.: 49.61%] [G loss: 0.751578]
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7047 [D loss: 0.685454, acc.: 51.37%] [G loss: 0.729902]
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7048 [D loss: 0.687423, acc.: 49.22%] [G loss: 0.727388]
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7049 [D loss: 0.686136, acc.: 52.93%] [G loss: 0.739447]
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7050 [D loss: 0.695956, acc.: 46.29%] [G loss: 0.719248]
1/1 [==============================] - 0s 33ms/step
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7051 [D loss: 0.698533, acc.: 44.73%] [G loss: 0.725547]
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7052 [D loss: 0.699542, acc.: 41.21%] [G loss: 0.740225]
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7053 [D loss: 0.699307, acc.: 43.95%] [G loss: 0.728511]
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7054 [D loss: 0.695309, acc.: 46.88%] [G loss: 0.736020]
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7055 [D loss: 0.700242, acc.: 45.31%] [G loss: 0.728576]
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7056 [D loss: 0.698545, acc.: 47.46%] [G loss: 0.721668]
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7057 [D loss: 0.696554, acc.: 45.70%] [G loss: 0.736299]
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7058 [D loss: 0.693591, acc.: 50.00%] [G loss: 0.735798]
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7059 [D loss: 0.692067, acc.: 48.24%] [G loss: 0.745128]
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7060 [D loss: 0.689376, acc.: 54.49%] [G loss: 0.748733]
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7061 [D loss: 0.684067, acc.: 52.54%] [G loss: 0.745590]
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7062 [D loss: 0.688539, acc.: 52.34%] [G loss: 0.748138]
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7063 [D loss: 0.677012, acc.: 59.96%] [G loss: 0.738732]
8/8 [==============================] - 0s 4ms/step
7064 [D loss: 0.685123, acc.: 54.30%] [G loss: 0.730912]
8/8 [==============================] - 0s 4ms/step
7065 [D loss: 0.692118, acc.: 51.37%] [G loss: 0.715566]
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7066 [D loss: 0.682669, acc.: 53.91%] [G loss: 0.710989]
8/8 [==============================] - 0s 4ms/step
7067 [D loss: 0.697690, acc.: 44.53%] [G loss: 0.715368]
8/8 [==============================] - 0s 4ms/step
7068 [D loss: 0.706266, acc.: 45.70%] [G loss: 0.722174]
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7069 [D loss: 0.700263, acc.: 47.07%] [G loss: 0.733709]
8/8 [==============================] - 0s 4ms/step
7070 [D loss: 0.699908, acc.: 46.48%] [G loss: 0.743633]
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7071 [D loss: 0.698483, acc.: 48.83%] [G loss: 0.732559]
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7072 [D loss: 0.694633, acc.: 51.37%] [G loss: 0.732078]
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7073 [D loss: 0.692602, acc.: 49.80%] [G loss: 0.736360]
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7074 [D loss: 0.697747, acc.: 46.09%] [G loss: 0.717251]
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7075 [D loss: 0.701363, acc.: 47.66%] [G loss: 0.703204]
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7076 [D loss: 0.700547, acc.: 47.66%] [G loss: 0.704909]
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7077 [D loss: 0.699835, acc.: 44.73%] [G loss: 0.714792]
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7078 [D loss: 0.691898, acc.: 51.76%] [G loss: 0.736652]
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7079 [D loss: 0.688107, acc.: 51.95%] [G loss: 0.747307]
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7080 [D loss: 0.691847, acc.: 52.34%] [G loss: 0.744812]
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7081 [D loss: 0.682920, acc.: 54.30%] [G loss: 0.755239]
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7082 [D loss: 0.687369, acc.: 54.30%] [G loss: 0.739639]
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7083 [D loss: 0.696223, acc.: 45.70%] [G loss: 0.729304]
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7084 [D loss: 0.697401, acc.: 45.70%] [G loss: 0.728944]
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7085 [D loss: 0.687587, acc.: 50.59%] [G loss: 0.744847]
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7086 [D loss: 0.692016, acc.: 53.52%] [G loss: 0.748112]
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7087 [D loss: 0.686789, acc.: 52.73%] [G loss: 0.760731]
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7088 [D loss: 0.695351, acc.: 51.17%] [G loss: 0.759865]
8/8 [==============================] - 0s 4ms/step
7089 [D loss: 0.684207, acc.: 53.52%] [G loss: 0.762330]
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7090 [D loss: 0.683655, acc.: 52.73%] [G loss: 0.761637]
8/8 [==============================] - 0s 4ms/step
7091 [D loss: 0.687797, acc.: 49.02%] [G loss: 0.742892]
8/8 [==============================] - 0s 4ms/step
7092 [D loss: 0.685618, acc.: 51.17%] [G loss: 0.743898]
8/8 [==============================] - 0s 4ms/step
7093 [D loss: 0.691915, acc.: 48.83%] [G loss: 0.713194]
8/8 [==============================] - 0s 4ms/step
7094 [D loss: 0.704049, acc.: 45.51%] [G loss: 0.702077]
8/8 [==============================] - 0s 4ms/step
7095 [D loss: 0.703037, acc.: 41.60%] [G loss: 0.700607]
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7096 [D loss: 0.700322, acc.: 42.77%] [G loss: 0.709371]
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7097 [D loss: 0.700391, acc.: 45.70%] [G loss: 0.720808]
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7098 [D loss: 0.703887, acc.: 49.41%] [G loss: 0.720949]
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7099 [D loss: 0.704206, acc.: 48.44%] [G loss: 0.737184]
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7100 [D loss: 0.687709, acc.: 52.15%] [G loss: 0.759803]
1/1 [==============================] - 0s 32ms/step
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7101 [D loss: 0.681770, acc.: 56.84%] [G loss: 0.765887]
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7102 [D loss: 0.683499, acc.: 56.64%] [G loss: 0.760849]
8/8 [==============================] - 0s 4ms/step
7103 [D loss: 0.676918, acc.: 57.42%] [G loss: 0.789022]
8/8 [==============================] - 0s 4ms/step
7104 [D loss: 0.678983, acc.: 58.59%] [G loss: 0.776262]
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7105 [D loss: 0.684355, acc.: 53.71%] [G loss: 0.736337]
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7106 [D loss: 0.702651, acc.: 48.44%] [G loss: 0.705532]
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7107 [D loss: 0.698599, acc.: 46.88%] [G loss: 0.715969]
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7108 [D loss: 0.690672, acc.: 46.48%] [G loss: 0.748883]
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7109 [D loss: 0.684869, acc.: 49.41%] [G loss: 0.775081]
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7110 [D loss: 0.685748, acc.: 50.39%] [G loss: 0.765581]
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7111 [D loss: 0.689657, acc.: 53.32%] [G loss: 0.758874]
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7112 [D loss: 0.688584, acc.: 53.12%] [G loss: 0.744496]
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7113 [D loss: 0.686928, acc.: 51.56%] [G loss: 0.737651]
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7114 [D loss: 0.693355, acc.: 47.85%] [G loss: 0.747135]
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7115 [D loss: 0.689598, acc.: 52.15%] [G loss: 0.732854]
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7116 [D loss: 0.696427, acc.: 48.83%] [G loss: 0.705026]
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7117 [D loss: 0.703059, acc.: 46.68%] [G loss: 0.706742]
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7118 [D loss: 0.713432, acc.: 45.12%] [G loss: 0.699765]
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7119 [D loss: 0.698726, acc.: 47.07%] [G loss: 0.721256]
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7120 [D loss: 0.702701, acc.: 47.85%] [G loss: 0.736873]
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7121 [D loss: 0.692750, acc.: 48.63%] [G loss: 0.755529]
8/8 [==============================] - 0s 4ms/step
7122 [D loss: 0.707384, acc.: 43.55%] [G loss: 0.750301]
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7123 [D loss: 0.701851, acc.: 46.48%] [G loss: 0.743176]
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7124 [D loss: 0.697962, acc.: 49.02%] [G loss: 0.739568]
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7125 [D loss: 0.693659, acc.: 51.95%] [G loss: 0.742325]
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7126 [D loss: 0.696130, acc.: 49.22%] [G loss: 0.729733]
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7127 [D loss: 0.694903, acc.: 49.61%] [G loss: 0.718411]
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7128 [D loss: 0.699632, acc.: 44.92%] [G loss: 0.705302]
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7129 [D loss: 0.700568, acc.: 45.90%] [G loss: 0.721372]
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7130 [D loss: 0.696900, acc.: 44.92%] [G loss: 0.748927]
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7131 [D loss: 0.690070, acc.: 51.76%] [G loss: 0.758367]
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7132 [D loss: 0.687237, acc.: 54.30%] [G loss: 0.754353]
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7133 [D loss: 0.688253, acc.: 55.27%] [G loss: 0.740485]
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7134 [D loss: 0.686028, acc.: 55.08%] [G loss: 0.742848]
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7135 [D loss: 0.696042, acc.: 45.12%] [G loss: 0.727345]
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7136 [D loss: 0.689418, acc.: 55.47%] [G loss: 0.706944]
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7137 [D loss: 0.695849, acc.: 47.66%] [G loss: 0.711510]
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7138 [D loss: 0.695220, acc.: 47.85%] [G loss: 0.710187]
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7139 [D loss: 0.693348, acc.: 49.61%] [G loss: 0.717930]
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7140 [D loss: 0.681791, acc.: 51.17%] [G loss: 0.720882]
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7141 [D loss: 0.690083, acc.: 49.80%] [G loss: 0.754996]
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7142 [D loss: 0.684974, acc.: 54.69%] [G loss: 0.741380]
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7143 [D loss: 0.690383, acc.: 50.20%] [G loss: 0.745866]
8/8 [==============================] - 0s 4ms/step
7144 [D loss: 0.681259, acc.: 53.32%] [G loss: 0.749808]
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7145 [D loss: 0.682870, acc.: 55.08%] [G loss: 0.758466]
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7146 [D loss: 0.686478, acc.: 49.80%] [G loss: 0.730062]
8/8 [==============================] - 0s 4ms/step
7147 [D loss: 0.685416, acc.: 52.54%] [G loss: 0.709136]
8/8 [==============================] - 0s 4ms/step
7148 [D loss: 0.687673, acc.: 48.83%] [G loss: 0.722605]
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7149 [D loss: 0.694744, acc.: 48.63%] [G loss: 0.712769]
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7150 [D loss: 0.685090, acc.: 49.61%] [G loss: 0.716430]
1/1 [==============================] - 0s 31ms/step
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7151 [D loss: 0.691919, acc.: 45.12%] [G loss: 0.729041]
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7152 [D loss: 0.693319, acc.: 47.66%] [G loss: 0.723228]
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7153 [D loss: 0.690256, acc.: 48.63%] [G loss: 0.739720]
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7154 [D loss: 0.688687, acc.: 50.39%] [G loss: 0.740435]
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7155 [D loss: 0.695848, acc.: 45.51%] [G loss: 0.745579]
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7156 [D loss: 0.688469, acc.: 50.78%] [G loss: 0.729964]
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7157 [D loss: 0.676639, acc.: 52.93%] [G loss: 0.740092]
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7158 [D loss: 0.687982, acc.: 51.95%] [G loss: 0.731268]
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7159 [D loss: 0.694057, acc.: 52.15%] [G loss: 0.719189]
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7160 [D loss: 0.695214, acc.: 52.73%] [G loss: 0.727015]
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7161 [D loss: 0.696936, acc.: 47.07%] [G loss: 0.718659]
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7162 [D loss: 0.699787, acc.: 48.24%] [G loss: 0.723293]
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7163 [D loss: 0.694126, acc.: 48.44%] [G loss: 0.736735]
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7164 [D loss: 0.691896, acc.: 50.78%] [G loss: 0.734251]
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7165 [D loss: 0.693822, acc.: 47.66%] [G loss: 0.720333]
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7166 [D loss: 0.695166, acc.: 48.44%] [G loss: 0.718333]
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7167 [D loss: 0.685089, acc.: 51.56%] [G loss: 0.708091]
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7168 [D loss: 0.690800, acc.: 48.83%] [G loss: 0.710466]
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7169 [D loss: 0.686370, acc.: 51.17%] [G loss: 0.726224]
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7170 [D loss: 0.687261, acc.: 50.78%] [G loss: 0.716202]
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7171 [D loss: 0.682821, acc.: 54.30%] [G loss: 0.734479]
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7172 [D loss: 0.681631, acc.: 50.98%] [G loss: 0.734850]
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7173 [D loss: 0.685098, acc.: 50.98%] [G loss: 0.736130]
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7174 [D loss: 0.692289, acc.: 46.29%] [G loss: 0.728767]
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7175 [D loss: 0.696087, acc.: 50.20%] [G loss: 0.715979]
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7176 [D loss: 0.686680, acc.: 51.76%] [G loss: 0.719174]
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7177 [D loss: 0.693058, acc.: 44.73%] [G loss: 0.713852]
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7178 [D loss: 0.687613, acc.: 50.20%] [G loss: 0.720319]
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7179 [D loss: 0.686767, acc.: 51.76%] [G loss: 0.724679]
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7180 [D loss: 0.695111, acc.: 48.24%] [G loss: 0.733977]
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7181 [D loss: 0.693940, acc.: 46.29%] [G loss: 0.750098]
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7182 [D loss: 0.676620, acc.: 54.30%] [G loss: 0.753281]
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7183 [D loss: 0.688319, acc.: 48.24%] [G loss: 0.748177]
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7184 [D loss: 0.687681, acc.: 47.46%] [G loss: 0.749532]
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7185 [D loss: 0.691450, acc.: 49.22%] [G loss: 0.728350]
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7186 [D loss: 0.693931, acc.: 47.07%] [G loss: 0.727057]
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7187 [D loss: 0.688317, acc.: 52.73%] [G loss: 0.725392]
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7188 [D loss: 0.696361, acc.: 46.88%] [G loss: 0.706918]
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7189 [D loss: 0.699528, acc.: 47.27%] [G loss: 0.710055]
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7190 [D loss: 0.690460, acc.: 50.20%] [G loss: 0.730835]
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7191 [D loss: 0.689200, acc.: 54.69%] [G loss: 0.745577]
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7192 [D loss: 0.688605, acc.: 51.76%] [G loss: 0.743308]
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7193 [D loss: 0.683232, acc.: 54.88%] [G loss: 0.738999]
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7194 [D loss: 0.695608, acc.: 43.55%] [G loss: 0.717486]
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7195 [D loss: 0.698537, acc.: 46.68%] [G loss: 0.729244]
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7196 [D loss: 0.691873, acc.: 48.83%] [G loss: 0.717663]
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7197 [D loss: 0.689087, acc.: 50.00%] [G loss: 0.720786]
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7198 [D loss: 0.690105, acc.: 52.73%] [G loss: 0.710063]
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7199 [D loss: 0.689358, acc.: 51.95%] [G loss: 0.720079]
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7200 [D loss: 0.685517, acc.: 50.98%] [G loss: 0.719487]
1/1 [==============================] - 0s 35ms/step
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7201 [D loss: 0.686689, acc.: 52.34%] [G loss: 0.719226]
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7202 [D loss: 0.689451, acc.: 53.91%] [G loss: 0.713258]
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7203 [D loss: 0.691383, acc.: 50.78%] [G loss: 0.729585]
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7204 [D loss: 0.693084, acc.: 51.95%] [G loss: 0.727275]
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7205 [D loss: 0.694127, acc.: 47.46%] [G loss: 0.726637]
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7206 [D loss: 0.686022, acc.: 51.76%] [G loss: 0.728127]
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7207 [D loss: 0.691380, acc.: 49.02%] [G loss: 0.712558]
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7208 [D loss: 0.696892, acc.: 48.44%] [G loss: 0.716968]
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7209 [D loss: 0.691138, acc.: 46.29%] [G loss: 0.713452]
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7210 [D loss: 0.693716, acc.: 46.09%] [G loss: 0.722173]
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7211 [D loss: 0.697445, acc.: 46.09%] [G loss: 0.731585]
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7212 [D loss: 0.682790, acc.: 52.54%] [G loss: 0.744521]
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7213 [D loss: 0.683821, acc.: 50.98%] [G loss: 0.754888]
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7214 [D loss: 0.682130, acc.: 52.34%] [G loss: 0.754848]
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7215 [D loss: 0.677388, acc.: 53.91%] [G loss: 0.743314]
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7216 [D loss: 0.665075, acc.: 58.59%] [G loss: 0.752076]
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7217 [D loss: 0.683183, acc.: 51.17%] [G loss: 0.741915]
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7218 [D loss: 0.678695, acc.: 53.91%] [G loss: 0.729199]
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7219 [D loss: 0.680653, acc.: 46.29%] [G loss: 0.729639]
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7220 [D loss: 0.687719, acc.: 50.78%] [G loss: 0.734207]
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7221 [D loss: 0.688368, acc.: 47.66%] [G loss: 0.736026]
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7222 [D loss: 0.699129, acc.: 51.17%] [G loss: 0.746822]
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7223 [D loss: 0.697556, acc.: 50.00%] [G loss: 0.753001]
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7224 [D loss: 0.695340, acc.: 47.85%] [G loss: 0.737865]
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7225 [D loss: 0.695210, acc.: 49.61%] [G loss: 0.725619]
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7226 [D loss: 0.697136, acc.: 47.27%] [G loss: 0.727374]
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7227 [D loss: 0.693290, acc.: 47.46%] [G loss: 0.724513]
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7228 [D loss: 0.694533, acc.: 49.80%] [G loss: 0.718879]
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7229 [D loss: 0.692646, acc.: 50.00%] [G loss: 0.719357]
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7230 [D loss: 0.691061, acc.: 49.41%] [G loss: 0.735439]
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7231 [D loss: 0.687047, acc.: 51.37%] [G loss: 0.736028]
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7232 [D loss: 0.686300, acc.: 55.27%] [G loss: 0.741142]
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7233 [D loss: 0.683531, acc.: 51.17%] [G loss: 0.754489]
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7234 [D loss: 0.687160, acc.: 52.34%] [G loss: 0.730895]
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7235 [D loss: 0.684486, acc.: 52.54%] [G loss: 0.731232]
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7236 [D loss: 0.693110, acc.: 50.00%] [G loss: 0.719465]
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7237 [D loss: 0.697148, acc.: 45.90%] [G loss: 0.706148]
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7238 [D loss: 0.700367, acc.: 45.51%] [G loss: 0.709788]
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7239 [D loss: 0.690078, acc.: 50.39%] [G loss: 0.719639]
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7240 [D loss: 0.692301, acc.: 47.07%] [G loss: 0.732382]
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7241 [D loss: 0.694764, acc.: 50.59%] [G loss: 0.733146]
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7242 [D loss: 0.691617, acc.: 50.98%] [G loss: 0.734768]
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7243 [D loss: 0.692526, acc.: 47.85%] [G loss: 0.728012]
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7244 [D loss: 0.686108, acc.: 50.59%] [G loss: 0.734863]
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7245 [D loss: 0.691541, acc.: 47.07%] [G loss: 0.729696]
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7246 [D loss: 0.687457, acc.: 47.85%] [G loss: 0.716630]
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7247 [D loss: 0.694776, acc.: 46.68%] [G loss: 0.717752]
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7248 [D loss: 0.693012, acc.: 45.70%] [G loss: 0.709160]
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7249 [D loss: 0.688609, acc.: 48.44%] [G loss: 0.714156]
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7250 [D loss: 0.688990, acc.: 50.59%] [G loss: 0.725538]
1/1 [==============================] - 0s 30ms/step
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7251 [D loss: 0.686164, acc.: 53.32%] [G loss: 0.735585]
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7252 [D loss: 0.684562, acc.: 53.52%] [G loss: 0.746215]
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7253 [D loss: 0.676666, acc.: 55.66%] [G loss: 0.751636]
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7254 [D loss: 0.683963, acc.: 50.78%] [G loss: 0.743765]
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7255 [D loss: 0.681930, acc.: 51.17%] [G loss: 0.755503]
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7256 [D loss: 0.697518, acc.: 48.44%] [G loss: 0.736352]
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7257 [D loss: 0.686630, acc.: 51.76%] [G loss: 0.729671]
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7258 [D loss: 0.685362, acc.: 52.54%] [G loss: 0.735184]
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7259 [D loss: 0.683711, acc.: 50.59%] [G loss: 0.729467]
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7260 [D loss: 0.695363, acc.: 48.63%] [G loss: 0.725695]
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7261 [D loss: 0.691300, acc.: 49.41%] [G loss: 0.724777]
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7262 [D loss: 0.679117, acc.: 52.73%] [G loss: 0.727782]
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7263 [D loss: 0.687700, acc.: 50.59%] [G loss: 0.718372]
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7264 [D loss: 0.679296, acc.: 52.93%] [G loss: 0.715074]
8/8 [==============================] - 0s 4ms/step
7265 [D loss: 0.684930, acc.: 51.95%] [G loss: 0.718977]
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7266 [D loss: 0.688840, acc.: 46.88%] [G loss: 0.725960]
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7267 [D loss: 0.689261, acc.: 47.85%] [G loss: 0.729693]
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7268 [D loss: 0.684548, acc.: 50.20%] [G loss: 0.723945]
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7269 [D loss: 0.690407, acc.: 48.24%] [G loss: 0.734232]
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7270 [D loss: 0.683175, acc.: 50.98%] [G loss: 0.737449]
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7271 [D loss: 0.685187, acc.: 51.76%] [G loss: 0.736578]
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7272 [D loss: 0.696088, acc.: 43.75%] [G loss: 0.723564]
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7273 [D loss: 0.697235, acc.: 47.46%] [G loss: 0.713120]
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7274 [D loss: 0.698873, acc.: 48.63%] [G loss: 0.725457]
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7275 [D loss: 0.689425, acc.: 49.80%] [G loss: 0.720783]
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7276 [D loss: 0.688494, acc.: 51.17%] [G loss: 0.741141]
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7277 [D loss: 0.693411, acc.: 48.44%] [G loss: 0.729864]
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7278 [D loss: 0.683759, acc.: 50.98%] [G loss: 0.746738]
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7279 [D loss: 0.694121, acc.: 49.61%] [G loss: 0.740006]
8/8 [==============================] - 0s 4ms/step
7280 [D loss: 0.688761, acc.: 51.17%] [G loss: 0.734825]
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7281 [D loss: 0.693107, acc.: 51.17%] [G loss: 0.727594]
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7282 [D loss: 0.685116, acc.: 51.56%] [G loss: 0.740351]
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7283 [D loss: 0.690770, acc.: 50.39%] [G loss: 0.729534]
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7284 [D loss: 0.685319, acc.: 51.17%] [G loss: 0.724214]
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7285 [D loss: 0.693024, acc.: 49.22%] [G loss: 0.739473]
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7286 [D loss: 0.697736, acc.: 50.78%] [G loss: 0.728681]
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7287 [D loss: 0.695516, acc.: 50.00%] [G loss: 0.733355]
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7288 [D loss: 0.696663, acc.: 47.66%] [G loss: 0.734213]
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7289 [D loss: 0.692123, acc.: 49.02%] [G loss: 0.728434]
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7290 [D loss: 0.700200, acc.: 47.66%] [G loss: 0.738570]
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7291 [D loss: 0.693789, acc.: 49.22%] [G loss: 0.739089]
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7292 [D loss: 0.684959, acc.: 51.17%] [G loss: 0.733859]
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7293 [D loss: 0.685802, acc.: 51.56%] [G loss: 0.734201]
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7294 [D loss: 0.687479, acc.: 54.10%] [G loss: 0.744338]
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7295 [D loss: 0.693526, acc.: 50.39%] [G loss: 0.715868]
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7296 [D loss: 0.698374, acc.: 49.02%] [G loss: 0.713165]
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7297 [D loss: 0.700911, acc.: 46.48%] [G loss: 0.716370]
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7298 [D loss: 0.708921, acc.: 43.36%] [G loss: 0.711184]
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7299 [D loss: 0.701744, acc.: 43.95%] [G loss: 0.717395]
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7300 [D loss: 0.700582, acc.: 48.83%] [G loss: 0.732948]
1/1 [==============================] - 0s 30ms/step
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7301 [D loss: 0.693843, acc.: 48.83%] [G loss: 0.746719]
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7302 [D loss: 0.691103, acc.: 51.76%] [G loss: 0.755718]
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7303 [D loss: 0.693424, acc.: 47.85%] [G loss: 0.766035]
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7304 [D loss: 0.695658, acc.: 50.00%] [G loss: 0.731560]
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7305 [D loss: 0.698580, acc.: 48.05%] [G loss: 0.726920]
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7306 [D loss: 0.697798, acc.: 48.44%] [G loss: 0.703187]
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7307 [D loss: 0.696525, acc.: 49.61%] [G loss: 0.713735]
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7308 [D loss: 0.693555, acc.: 46.29%] [G loss: 0.716845]
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7309 [D loss: 0.692662, acc.: 45.70%] [G loss: 0.722752]
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7310 [D loss: 0.694912, acc.: 46.29%] [G loss: 0.721270]
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7311 [D loss: 0.687257, acc.: 50.78%] [G loss: 0.735687]
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7312 [D loss: 0.694373, acc.: 47.66%] [G loss: 0.749290]
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7313 [D loss: 0.691490, acc.: 50.39%] [G loss: 0.732404]
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7314 [D loss: 0.682893, acc.: 51.95%] [G loss: 0.721823]
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7315 [D loss: 0.683905, acc.: 52.34%] [G loss: 0.720926]
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7316 [D loss: 0.684114, acc.: 54.30%] [G loss: 0.716669]
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7317 [D loss: 0.691297, acc.: 47.27%] [G loss: 0.704846]
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7318 [D loss: 0.680426, acc.: 53.12%] [G loss: 0.718565]
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7319 [D loss: 0.688483, acc.: 51.76%] [G loss: 0.734708]
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7320 [D loss: 0.682262, acc.: 52.15%] [G loss: 0.749451]
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7321 [D loss: 0.685552, acc.: 44.73%] [G loss: 0.741724]
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7322 [D loss: 0.684132, acc.: 50.00%] [G loss: 0.739275]
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7323 [D loss: 0.694243, acc.: 46.48%] [G loss: 0.732085]
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7324 [D loss: 0.690022, acc.: 50.39%] [G loss: 0.728870]
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7325 [D loss: 0.683439, acc.: 52.34%] [G loss: 0.727052]
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7326 [D loss: 0.684721, acc.: 48.44%] [G loss: 0.717372]
8/8 [==============================] - 0s 4ms/step
7327 [D loss: 0.684781, acc.: 50.20%] [G loss: 0.711892]
8/8 [==============================] - 0s 4ms/step
7328 [D loss: 0.687898, acc.: 46.88%] [G loss: 0.714583]
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7329 [D loss: 0.693131, acc.: 46.09%] [G loss: 0.722073]
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7330 [D loss: 0.682797, acc.: 50.39%] [G loss: 0.728212]
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7331 [D loss: 0.690793, acc.: 44.53%] [G loss: 0.742711]
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7332 [D loss: 0.684612, acc.: 49.80%] [G loss: 0.739198]
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7333 [D loss: 0.685845, acc.: 48.44%] [G loss: 0.744745]
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7334 [D loss: 0.684388, acc.: 49.22%] [G loss: 0.732532]
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7335 [D loss: 0.699044, acc.: 43.75%] [G loss: 0.716730]
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7336 [D loss: 0.696571, acc.: 44.92%] [G loss: 0.712527]
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7337 [D loss: 0.693328, acc.: 48.05%] [G loss: 0.718658]
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7338 [D loss: 0.690731, acc.: 45.90%] [G loss: 0.752455]
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7339 [D loss: 0.680898, acc.: 53.91%] [G loss: 0.741273]
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7340 [D loss: 0.685185, acc.: 50.59%] [G loss: 0.748110]
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7341 [D loss: 0.691350, acc.: 48.83%] [G loss: 0.730438]
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7342 [D loss: 0.690472, acc.: 51.76%] [G loss: 0.728687]
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7343 [D loss: 0.687533, acc.: 52.54%] [G loss: 0.722092]
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7344 [D loss: 0.686827, acc.: 46.29%] [G loss: 0.729757]
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7345 [D loss: 0.679112, acc.: 53.12%] [G loss: 0.719884]
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7346 [D loss: 0.690529, acc.: 47.07%] [G loss: 0.738509]
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7347 [D loss: 0.682560, acc.: 51.56%] [G loss: 0.728049]
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7348 [D loss: 0.691757, acc.: 48.44%] [G loss: 0.730878]
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7349 [D loss: 0.688083, acc.: 48.44%] [G loss: 0.739771]
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7350 [D loss: 0.693532, acc.: 46.68%] [G loss: 0.755207]
1/1 [==============================] - 0s 35ms/step
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7351 [D loss: 0.688051, acc.: 48.44%] [G loss: 0.749868]
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7352 [D loss: 0.691436, acc.: 46.68%] [G loss: 0.743213]
8/8 [==============================] - 0s 4ms/step
7353 [D loss: 0.693005, acc.: 44.92%] [G loss: 0.726411]
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7354 [D loss: 0.685866, acc.: 51.95%] [G loss: 0.738183]
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7355 [D loss: 0.690385, acc.: 51.37%] [G loss: 0.722908]
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7356 [D loss: 0.693069, acc.: 50.20%] [G loss: 0.723824]
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7357 [D loss: 0.692039, acc.: 47.27%] [G loss: 0.725313]
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7358 [D loss: 0.684583, acc.: 48.63%] [G loss: 0.730073]
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7359 [D loss: 0.694868, acc.: 48.24%] [G loss: 0.728491]
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7360 [D loss: 0.689347, acc.: 51.17%] [G loss: 0.731779]
8/8 [==============================] - 0s 4ms/step
7361 [D loss: 0.687267, acc.: 48.24%] [G loss: 0.729179]
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7362 [D loss: 0.686186, acc.: 48.83%] [G loss: 0.743334]
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7363 [D loss: 0.686879, acc.: 50.20%] [G loss: 0.735492]
8/8 [==============================] - 0s 4ms/step
7364 [D loss: 0.686471, acc.: 46.68%] [G loss: 0.739363]
8/8 [==============================] - 0s 4ms/step
7365 [D loss: 0.684694, acc.: 51.17%] [G loss: 0.730485]
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7366 [D loss: 0.684184, acc.: 50.20%] [G loss: 0.730253]
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7367 [D loss: 0.687958, acc.: 50.39%] [G loss: 0.720125]
8/8 [==============================] - 0s 4ms/step
7368 [D loss: 0.676903, acc.: 51.76%] [G loss: 0.725466]
8/8 [==============================] - 0s 4ms/step
7369 [D loss: 0.687426, acc.: 50.59%] [G loss: 0.732828]
8/8 [==============================] - 0s 4ms/step
7370 [D loss: 0.687202, acc.: 46.48%] [G loss: 0.735333]
8/8 [==============================] - 0s 4ms/step
7371 [D loss: 0.675658, acc.: 53.52%] [G loss: 0.741744]
8/8 [==============================] - 0s 4ms/step
7372 [D loss: 0.681254, acc.: 50.78%] [G loss: 0.737717]
8/8 [==============================] - 0s 4ms/step
7373 [D loss: 0.686441, acc.: 48.05%] [G loss: 0.736947]
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7374 [D loss: 0.680505, acc.: 48.24%] [G loss: 0.735645]
8/8 [==============================] - 0s 4ms/step
7375 [D loss: 0.691509, acc.: 47.66%] [G loss: 0.729522]
8/8 [==============================] - 0s 4ms/step
7376 [D loss: 0.681848, acc.: 51.76%] [G loss: 0.730678]
8/8 [==============================] - 0s 4ms/step
7377 [D loss: 0.694583, acc.: 45.70%] [G loss: 0.725231]
8/8 [==============================] - 0s 4ms/step
7378 [D loss: 0.689277, acc.: 47.66%] [G loss: 0.729837]
8/8 [==============================] - 0s 4ms/step
7379 [D loss: 0.687079, acc.: 44.53%] [G loss: 0.722819]
8/8 [==============================] - 0s 4ms/step
7380 [D loss: 0.689317, acc.: 50.20%] [G loss: 0.727001]
8/8 [==============================] - 0s 4ms/step
7381 [D loss: 0.685715, acc.: 48.63%] [G loss: 0.726368]
8/8 [==============================] - 0s 4ms/step
7382 [D loss: 0.680887, acc.: 49.02%] [G loss: 0.745482]
8/8 [==============================] - 0s 4ms/step
7383 [D loss: 0.683476, acc.: 50.59%] [G loss: 0.736603]
8/8 [==============================] - 0s 4ms/step
7384 [D loss: 0.684134, acc.: 50.59%] [G loss: 0.745894]
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7385 [D loss: 0.674478, acc.: 54.69%] [G loss: 0.736937]
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7386 [D loss: 0.691573, acc.: 46.09%] [G loss: 0.725646]
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7387 [D loss: 0.690220, acc.: 44.92%] [G loss: 0.727779]
8/8 [==============================] - 0s 4ms/step
7388 [D loss: 0.686973, acc.: 46.09%] [G loss: 0.719854]
8/8 [==============================] - 0s 4ms/step
7389 [D loss: 0.684798, acc.: 45.12%] [G loss: 0.709526]
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7390 [D loss: 0.694998, acc.: 44.92%] [G loss: 0.712565]
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7391 [D loss: 0.693818, acc.: 45.51%] [G loss: 0.715890]
8/8 [==============================] - 0s 4ms/step
7392 [D loss: 0.700115, acc.: 42.97%] [G loss: 0.724753]
8/8 [==============================] - 0s 4ms/step
7393 [D loss: 0.694658, acc.: 45.31%] [G loss: 0.731230]
8/8 [==============================] - 0s 4ms/step
7394 [D loss: 0.690419, acc.: 47.07%] [G loss: 0.735764]
8/8 [==============================] - 0s 4ms/step
7395 [D loss: 0.680106, acc.: 53.12%] [G loss: 0.749637]
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7396 [D loss: 0.684617, acc.: 51.95%] [G loss: 0.774831]
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7397 [D loss: 0.676846, acc.: 52.54%] [G loss: 0.737449]
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7398 [D loss: 0.681221, acc.: 50.59%] [G loss: 0.783633]
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7399 [D loss: 0.690707, acc.: 49.22%] [G loss: 0.738020]
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7400 [D loss: 0.684251, acc.: 49.80%] [G loss: 0.732018]
1/1 [==============================] - 0s 27ms/step
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7401 [D loss: 0.693339, acc.: 49.22%] [G loss: 0.717665]
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7402 [D loss: 0.692814, acc.: 47.07%] [G loss: 0.714970]
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7403 [D loss: 0.702101, acc.: 41.99%] [G loss: 0.721350]
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7404 [D loss: 0.700132, acc.: 44.92%] [G loss: 0.722516]
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7405 [D loss: 0.696186, acc.: 47.85%] [G loss: 0.741297]
8/8 [==============================] - 0s 4ms/step
7406 [D loss: 0.694505, acc.: 45.31%] [G loss: 0.742392]
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7407 [D loss: 0.696983, acc.: 45.31%] [G loss: 0.740518]
8/8 [==============================] - 0s 4ms/step
7408 [D loss: 0.689622, acc.: 51.76%] [G loss: 0.728482]
8/8 [==============================] - 0s 4ms/step
7409 [D loss: 0.693350, acc.: 49.80%] [G loss: 0.727101]
8/8 [==============================] - 0s 4ms/step
7410 [D loss: 0.694156, acc.: 49.80%] [G loss: 0.722219]
8/8 [==============================] - 0s 4ms/step
7411 [D loss: 0.701045, acc.: 45.90%] [G loss: 0.700857]
8/8 [==============================] - 0s 4ms/step
7412 [D loss: 0.707885, acc.: 39.84%] [G loss: 0.708682]
8/8 [==============================] - 0s 4ms/step
7413 [D loss: 0.702586, acc.: 44.53%] [G loss: 0.732902]
8/8 [==============================] - 0s 4ms/step
7414 [D loss: 0.688782, acc.: 53.91%] [G loss: 0.739788]
8/8 [==============================] - 0s 4ms/step
7415 [D loss: 0.692532, acc.: 48.05%] [G loss: 0.744984]
8/8 [==============================] - 0s 4ms/step
7416 [D loss: 0.693116, acc.: 47.66%] [G loss: 0.744660]
8/8 [==============================] - 0s 4ms/step
7417 [D loss: 0.689769, acc.: 54.30%] [G loss: 0.727797]
8/8 [==============================] - 0s 4ms/step
7418 [D loss: 0.688762, acc.: 51.56%] [G loss: 0.725876]
8/8 [==============================] - 0s 4ms/step
7419 [D loss: 0.691356, acc.: 51.37%] [G loss: 0.711871]
8/8 [==============================] - 0s 4ms/step
7420 [D loss: 0.691138, acc.: 46.68%] [G loss: 0.701552]
8/8 [==============================] - 0s 4ms/step
7421 [D loss: 0.697460, acc.: 46.29%] [G loss: 0.698815]
8/8 [==============================] - 0s 4ms/step
7422 [D loss: 0.692473, acc.: 47.27%] [G loss: 0.706648]
8/8 [==============================] - 0s 4ms/step
7423 [D loss: 0.685420, acc.: 51.95%] [G loss: 0.724405]
8/8 [==============================] - 0s 5ms/step
7424 [D loss: 0.689042, acc.: 51.17%] [G loss: 0.735575]
8/8 [==============================] - 0s 4ms/step
7425 [D loss: 0.682933, acc.: 50.00%] [G loss: 0.748393]
8/8 [==============================] - 0s 4ms/step
7426 [D loss: 0.690609, acc.: 49.41%] [G loss: 0.752513]
8/8 [==============================] - 0s 4ms/step
7427 [D loss: 0.681017, acc.: 52.93%] [G loss: 0.749028]
8/8 [==============================] - 0s 4ms/step
7428 [D loss: 0.692427, acc.: 49.41%] [G loss: 0.745482]
8/8 [==============================] - 0s 4ms/step
7429 [D loss: 0.680326, acc.: 54.88%] [G loss: 0.720994]
8/8 [==============================] - 0s 4ms/step
7430 [D loss: 0.685584, acc.: 50.00%] [G loss: 0.730164]
8/8 [==============================] - 0s 4ms/step
7431 [D loss: 0.685366, acc.: 47.07%] [G loss: 0.716062]
8/8 [==============================] - 0s 4ms/step
7432 [D loss: 0.692987, acc.: 44.73%] [G loss: 0.711480]
8/8 [==============================] - 0s 4ms/step
7433 [D loss: 0.690408, acc.: 46.68%] [G loss: 0.730535]
8/8 [==============================] - 0s 4ms/step
7434 [D loss: 0.687746, acc.: 47.46%] [G loss: 0.740626]
8/8 [==============================] - 0s 4ms/step
7435 [D loss: 0.676092, acc.: 51.17%] [G loss: 0.738626]
8/8 [==============================] - 0s 4ms/step
7436 [D loss: 0.693512, acc.: 45.70%] [G loss: 0.727591]
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7437 [D loss: 0.682521, acc.: 49.61%] [G loss: 0.733996]
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7438 [D loss: 0.687111, acc.: 46.88%] [G loss: 0.734340]
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7439 [D loss: 0.676513, acc.: 49.22%] [G loss: 0.734095]
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7440 [D loss: 0.685492, acc.: 48.05%] [G loss: 0.726125]
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7441 [D loss: 0.692694, acc.: 45.51%] [G loss: 0.728177]
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7442 [D loss: 0.682676, acc.: 49.22%] [G loss: 0.729458]
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7443 [D loss: 0.678367, acc.: 51.37%] [G loss: 0.738401]
8/8 [==============================] - 0s 4ms/step
7444 [D loss: 0.684653, acc.: 52.54%] [G loss: 0.734282]
8/8 [==============================] - 0s 4ms/step
7445 [D loss: 0.689343, acc.: 50.59%] [G loss: 0.731609]
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7446 [D loss: 0.687444, acc.: 50.78%] [G loss: 0.733582]
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7447 [D loss: 0.685542, acc.: 49.61%] [G loss: 0.731313]
8/8 [==============================] - 0s 4ms/step
7448 [D loss: 0.686438, acc.: 50.20%] [G loss: 0.739363]
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7449 [D loss: 0.682159, acc.: 52.73%] [G loss: 0.732361]
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7450 [D loss: 0.683334, acc.: 51.56%] [G loss: 0.726818]
1/1 [==============================] - 0s 30ms/step
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7451 [D loss: 0.683737, acc.: 49.61%] [G loss: 0.730967]
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7452 [D loss: 0.683582, acc.: 51.37%] [G loss: 0.722165]
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7453 [D loss: 0.683060, acc.: 50.00%] [G loss: 0.706062]
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7454 [D loss: 0.689561, acc.: 50.39%] [G loss: 0.720468]
8/8 [==============================] - 0s 4ms/step
7455 [D loss: 0.682668, acc.: 49.22%] [G loss: 0.716347]
8/8 [==============================] - 0s 4ms/step
7456 [D loss: 0.692340, acc.: 44.73%] [G loss: 0.718336]
8/8 [==============================] - 0s 4ms/step
7457 [D loss: 0.686112, acc.: 48.63%] [G loss: 0.720600]
8/8 [==============================] - 0s 4ms/step
7458 [D loss: 0.684841, acc.: 45.12%] [G loss: 0.727821]
8/8 [==============================] - 0s 4ms/step
7459 [D loss: 0.686107, acc.: 51.17%] [G loss: 0.727013]
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7460 [D loss: 0.680653, acc.: 48.24%] [G loss: 0.729557]
8/8 [==============================] - 0s 4ms/step
7461 [D loss: 0.677151, acc.: 49.22%] [G loss: 0.734235]
8/8 [==============================] - 0s 4ms/step
7462 [D loss: 0.695308, acc.: 46.88%] [G loss: 0.721752]
8/8 [==============================] - 0s 4ms/step
7463 [D loss: 0.676098, acc.: 51.95%] [G loss: 0.729473]
8/8 [==============================] - 0s 4ms/step
7464 [D loss: 0.686627, acc.: 44.53%] [G loss: 0.738240]
8/8 [==============================] - 0s 4ms/step
7465 [D loss: 0.687147, acc.: 50.98%] [G loss: 0.730832]
8/8 [==============================] - 0s 4ms/step
7466 [D loss: 0.688134, acc.: 46.09%] [G loss: 0.718738]
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7467 [D loss: 0.681584, acc.: 47.07%] [G loss: 0.723783]
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7468 [D loss: 0.677820, acc.: 48.83%] [G loss: 0.728771]
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7469 [D loss: 0.668989, acc.: 48.83%] [G loss: 0.723293]
8/8 [==============================] - 0s 4ms/step
7470 [D loss: 0.678397, acc.: 44.92%] [G loss: 0.729159]
8/8 [==============================] - 0s 4ms/step
7471 [D loss: 0.678076, acc.: 48.83%] [G loss: 0.723673]
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7472 [D loss: 0.683432, acc.: 48.24%] [G loss: 0.720290]
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7473 [D loss: 0.670843, acc.: 49.80%] [G loss: 0.733335]
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7474 [D loss: 0.692142, acc.: 45.70%] [G loss: 0.736044]
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7475 [D loss: 0.685123, acc.: 46.48%] [G loss: 0.734953]
8/8 [==============================] - 0s 4ms/step
7476 [D loss: 0.687968, acc.: 49.80%] [G loss: 0.726308]
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7477 [D loss: 0.686040, acc.: 50.20%] [G loss: 0.734286]
8/8 [==============================] - 0s 4ms/step
7478 [D loss: 0.680715, acc.: 51.17%] [G loss: 0.733653]
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7479 [D loss: 0.674778, acc.: 50.20%] [G loss: 0.732011]
8/8 [==============================] - 0s 4ms/step
7480 [D loss: 0.668213, acc.: 49.61%] [G loss: 0.729753]
8/8 [==============================] - 0s 4ms/step
7481 [D loss: 0.683286, acc.: 48.05%] [G loss: 0.722934]
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7482 [D loss: 0.682468, acc.: 50.98%] [G loss: 0.719607]
8/8 [==============================] - 0s 4ms/step
7483 [D loss: 0.677209, acc.: 46.88%] [G loss: 0.727185]
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7484 [D loss: 0.688577, acc.: 46.48%] [G loss: 0.726823]
8/8 [==============================] - 0s 4ms/step
7485 [D loss: 0.684829, acc.: 49.41%] [G loss: 0.727600]
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7486 [D loss: 0.687105, acc.: 48.05%] [G loss: 0.725828]
8/8 [==============================] - 0s 4ms/step
7487 [D loss: 0.689761, acc.: 47.66%] [G loss: 0.719198]
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7488 [D loss: 0.681992, acc.: 47.46%] [G loss: 0.719986]
8/8 [==============================] - 0s 4ms/step
7489 [D loss: 0.680113, acc.: 46.68%] [G loss: 0.720089]
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7490 [D loss: 0.684559, acc.: 45.31%] [G loss: 0.718075]
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7491 [D loss: 0.680841, acc.: 48.83%] [G loss: 0.710342]
8/8 [==============================] - 0s 4ms/step
7492 [D loss: 0.682014, acc.: 50.39%] [G loss: 0.723685]
8/8 [==============================] - 0s 4ms/step
7493 [D loss: 0.679780, acc.: 48.63%] [G loss: 0.717917]
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7494 [D loss: 0.691323, acc.: 44.92%] [G loss: 0.727509]
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7495 [D loss: 0.694061, acc.: 43.95%] [G loss: 0.722765]
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7496 [D loss: 0.678431, acc.: 50.20%] [G loss: 0.723078]
8/8 [==============================] - 0s 4ms/step
7497 [D loss: 0.687995, acc.: 45.12%] [G loss: 0.734414]
8/8 [==============================] - 0s 4ms/step
7498 [D loss: 0.678483, acc.: 50.98%] [G loss: 0.729562]
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7499 [D loss: 0.684937, acc.: 50.39%] [G loss: 0.737265]
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7500 [D loss: 0.679953, acc.: 50.39%] [G loss: 0.738922]
1/1 [==============================] - 0s 27ms/step
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7501 [D loss: 0.676234, acc.: 51.37%] [G loss: 0.731912]
8/8 [==============================] - 0s 4ms/step
7502 [D loss: 0.682226, acc.: 49.22%] [G loss: 0.731487]
8/8 [==============================] - 0s 4ms/step
7503 [D loss: 0.687985, acc.: 48.44%] [G loss: 0.721885]
8/8 [==============================] - 0s 4ms/step
7504 [D loss: 0.688593, acc.: 50.20%] [G loss: 0.726388]
8/8 [==============================] - 0s 4ms/step
7505 [D loss: 0.680154, acc.: 51.76%] [G loss: 0.727422]
8/8 [==============================] - 0s 4ms/step
7506 [D loss: 0.687817, acc.: 45.90%] [G loss: 0.724191]
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7507 [D loss: 0.688821, acc.: 49.02%] [G loss: 0.727991]
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7508 [D loss: 0.688088, acc.: 45.90%] [G loss: 0.727007]
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7509 [D loss: 0.681931, acc.: 45.70%] [G loss: 0.732909]
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7510 [D loss: 0.680592, acc.: 47.27%] [G loss: 0.729856]
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7511 [D loss: 0.682942, acc.: 47.46%] [G loss: 0.732288]
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7512 [D loss: 0.682203, acc.: 51.17%] [G loss: 0.735472]
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7513 [D loss: 0.681327, acc.: 46.68%] [G loss: 0.721703]
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7514 [D loss: 0.668037, acc.: 53.71%] [G loss: 0.732153]
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7515 [D loss: 0.677684, acc.: 50.00%] [G loss: 0.729014]
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7516 [D loss: 0.691185, acc.: 44.73%] [G loss: 0.734719]
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7517 [D loss: 0.672893, acc.: 53.52%] [G loss: 0.728401]
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7518 [D loss: 0.682954, acc.: 51.17%] [G loss: 0.729777]
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7519 [D loss: 0.685237, acc.: 49.41%] [G loss: 0.729550]
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7520 [D loss: 0.685021, acc.: 48.44%] [G loss: 0.728988]
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7521 [D loss: 0.688071, acc.: 48.24%] [G loss: 0.733403]
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7522 [D loss: 0.688284, acc.: 45.12%] [G loss: 0.732225]
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7523 [D loss: 0.686446, acc.: 50.78%] [G loss: 0.729867]
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7524 [D loss: 0.684473, acc.: 48.44%] [G loss: 0.727458]
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7525 [D loss: 0.686876, acc.: 49.61%] [G loss: 0.729550]
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7526 [D loss: 0.674552, acc.: 52.73%] [G loss: 0.727545]
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7527 [D loss: 0.675266, acc.: 48.24%] [G loss: 0.730265]
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7528 [D loss: 0.685146, acc.: 53.52%] [G loss: 0.720579]
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7529 [D loss: 0.666717, acc.: 52.54%] [G loss: 0.720777]
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7530 [D loss: 0.693138, acc.: 45.12%] [G loss: 0.724013]
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7531 [D loss: 0.678915, acc.: 49.41%] [G loss: 0.725907]
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7532 [D loss: 0.684373, acc.: 47.27%] [G loss: 0.730059]
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7533 [D loss: 0.681147, acc.: 47.66%] [G loss: 0.717416]
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7534 [D loss: 0.694082, acc.: 45.51%] [G loss: 0.724757]
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7535 [D loss: 0.674296, acc.: 49.61%] [G loss: 0.729091]
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7536 [D loss: 0.678433, acc.: 49.41%] [G loss: 0.728000]
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7537 [D loss: 0.676383, acc.: 48.83%] [G loss: 0.741249]
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7538 [D loss: 0.682677, acc.: 51.76%] [G loss: 0.735205]
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7539 [D loss: 0.683701, acc.: 50.59%] [G loss: 0.729696]
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7540 [D loss: 0.685823, acc.: 48.24%] [G loss: 0.713909]
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7541 [D loss: 0.688320, acc.: 45.70%] [G loss: 0.720464]
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7542 [D loss: 0.683271, acc.: 48.24%] [G loss: 0.720609]
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7543 [D loss: 0.689936, acc.: 47.07%] [G loss: 0.718180]
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7544 [D loss: 0.689722, acc.: 50.20%] [G loss: 0.711749]
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7545 [D loss: 0.689445, acc.: 45.70%] [G loss: 0.717950]
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7546 [D loss: 0.670818, acc.: 48.24%] [G loss: 0.723079]
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7547 [D loss: 0.690827, acc.: 46.29%] [G loss: 0.734528]
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7548 [D loss: 0.681660, acc.: 50.59%] [G loss: 0.740244]
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7549 [D loss: 0.681631, acc.: 51.17%] [G loss: 0.743095]
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7550 [D loss: 0.679313, acc.: 47.85%] [G loss: 0.741435]
1/1 [==============================] - 0s 28ms/step
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7551 [D loss: 0.670951, acc.: 51.95%] [G loss: 0.740974]
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7552 [D loss: 0.678674, acc.: 50.00%] [G loss: 0.725271]
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7553 [D loss: 0.672821, acc.: 47.66%] [G loss: 0.719866]
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7554 [D loss: 0.663851, acc.: 50.98%] [G loss: 0.740476]
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7555 [D loss: 0.690084, acc.: 47.46%] [G loss: 0.725499]
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7556 [D loss: 0.684587, acc.: 49.22%] [G loss: 0.743559]
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7557 [D loss: 0.674684, acc.: 51.95%] [G loss: 0.731911]
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7558 [D loss: 0.690484, acc.: 47.27%] [G loss: 0.733155]
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7559 [D loss: 0.676665, acc.: 49.02%] [G loss: 0.740237]
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7560 [D loss: 0.683486, acc.: 47.27%] [G loss: 0.729014]
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7561 [D loss: 0.683611, acc.: 50.20%] [G loss: 0.736750]
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7562 [D loss: 0.676134, acc.: 48.63%] [G loss: 0.739710]
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7563 [D loss: 0.687895, acc.: 46.29%] [G loss: 0.747852]
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7564 [D loss: 0.678147, acc.: 50.00%] [G loss: 0.730311]
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7565 [D loss: 0.680490, acc.: 50.39%] [G loss: 0.727237]
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7566 [D loss: 0.679961, acc.: 46.88%] [G loss: 0.728260]
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7567 [D loss: 0.682311, acc.: 49.61%] [G loss: 0.739854]
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7568 [D loss: 0.694581, acc.: 47.46%] [G loss: 0.738157]
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7569 [D loss: 0.688832, acc.: 45.31%] [G loss: 0.732395]
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7570 [D loss: 0.676542, acc.: 51.76%] [G loss: 0.723569]
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7571 [D loss: 0.682132, acc.: 47.66%] [G loss: 0.728844]
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7572 [D loss: 0.686795, acc.: 49.61%] [G loss: 0.721532]
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7573 [D loss: 0.672126, acc.: 52.15%] [G loss: 0.737260]
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7574 [D loss: 0.678419, acc.: 48.05%] [G loss: 0.728593]
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7575 [D loss: 0.680119, acc.: 49.80%] [G loss: 0.724346]
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7576 [D loss: 0.681809, acc.: 49.80%] [G loss: 0.731814]
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7577 [D loss: 0.679389, acc.: 50.00%] [G loss: 0.734341]
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7578 [D loss: 0.681747, acc.: 45.90%] [G loss: 0.722713]
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7579 [D loss: 0.690738, acc.: 43.36%] [G loss: 0.721000]
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7580 [D loss: 0.673859, acc.: 47.85%] [G loss: 0.729797]
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7581 [D loss: 0.680952, acc.: 48.83%] [G loss: 0.726835]
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7582 [D loss: 0.679298, acc.: 45.70%] [G loss: 0.743828]
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7583 [D loss: 0.678346, acc.: 49.22%] [G loss: 0.718945]
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7584 [D loss: 0.686501, acc.: 46.29%] [G loss: 0.722033]
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7585 [D loss: 0.683014, acc.: 48.83%] [G loss: 0.734261]
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7586 [D loss: 0.674611, acc.: 50.98%] [G loss: 0.742631]
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7587 [D loss: 0.676481, acc.: 46.68%] [G loss: 0.739614]
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7588 [D loss: 0.682658, acc.: 51.56%] [G loss: 0.742339]
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7589 [D loss: 0.682891, acc.: 49.02%] [G loss: 0.732848]
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7590 [D loss: 0.677881, acc.: 48.44%] [G loss: 0.733167]
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7591 [D loss: 0.695766, acc.: 44.14%] [G loss: 0.722644]
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7592 [D loss: 0.674333, acc.: 48.05%] [G loss: 0.722592]
8/8 [==============================] - 0s 4ms/step
7593 [D loss: 0.680801, acc.: 47.66%] [G loss: 0.718895]
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7594 [D loss: 0.678716, acc.: 47.46%] [G loss: 0.726357]
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7595 [D loss: 0.677558, acc.: 47.27%] [G loss: 0.723888]
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7596 [D loss: 0.677801, acc.: 48.83%] [G loss: 0.723061]
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7597 [D loss: 0.680829, acc.: 47.85%] [G loss: 0.724291]
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7598 [D loss: 0.678748, acc.: 51.56%] [G loss: 0.723055]
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7599 [D loss: 0.688789, acc.: 48.83%] [G loss: 0.727793]
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7600 [D loss: 0.683127, acc.: 49.22%] [G loss: 0.733774]
1/1 [==============================] - 0s 26ms/step
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7601 [D loss: 0.681062, acc.: 49.41%] [G loss: 0.732667]
8/8 [==============================] - 0s 4ms/step
7602 [D loss: 0.682312, acc.: 51.76%] [G loss: 0.731282]
8/8 [==============================] - 0s 4ms/step
7603 [D loss: 0.675582, acc.: 52.54%] [G loss: 0.739761]
8/8 [==============================] - 0s 4ms/step
7604 [D loss: 0.673550, acc.: 51.17%] [G loss: 0.731968]
8/8 [==============================] - 0s 4ms/step
7605 [D loss: 0.678854, acc.: 45.70%] [G loss: 0.734525]
8/8 [==============================] - 0s 4ms/step
7606 [D loss: 0.682386, acc.: 48.63%] [G loss: 0.728974]
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7607 [D loss: 0.681330, acc.: 44.73%] [G loss: 0.722909]
8/8 [==============================] - 0s 4ms/step
7608 [D loss: 0.679196, acc.: 48.44%] [G loss: 0.722217]
8/8 [==============================] - 0s 4ms/step
7609 [D loss: 0.680635, acc.: 45.31%] [G loss: 0.721708]
8/8 [==============================] - 0s 4ms/step
7610 [D loss: 0.689599, acc.: 44.34%] [G loss: 0.723575]
8/8 [==============================] - 0s 4ms/step
7611 [D loss: 0.677592, acc.: 47.07%] [G loss: 0.733894]
8/8 [==============================] - 0s 4ms/step
7612 [D loss: 0.681339, acc.: 49.22%] [G loss: 0.743420]
8/8 [==============================] - 0s 4ms/step
7613 [D loss: 0.674205, acc.: 47.85%] [G loss: 0.738643]
8/8 [==============================] - 0s 4ms/step
7614 [D loss: 0.679488, acc.: 51.56%] [G loss: 0.734322]
8/8 [==============================] - 0s 4ms/step
7615 [D loss: 0.681813, acc.: 51.76%] [G loss: 0.729379]
8/8 [==============================] - 0s 4ms/step
7616 [D loss: 0.700245, acc.: 44.73%] [G loss: 0.705069]
8/8 [==============================] - 0s 4ms/step
7617 [D loss: 0.710970, acc.: 47.85%] [G loss: 0.694076]
8/8 [==============================] - 0s 4ms/step
7618 [D loss: 0.702262, acc.: 50.20%] [G loss: 0.723349]
8/8 [==============================] - 0s 4ms/step
7619 [D loss: 0.688265, acc.: 48.83%] [G loss: 0.729259]
8/8 [==============================] - 0s 4ms/step
7620 [D loss: 0.692679, acc.: 45.90%] [G loss: 0.738479]
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7621 [D loss: 0.695535, acc.: 46.29%] [G loss: 0.743333]
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7622 [D loss: 0.704772, acc.: 47.27%] [G loss: 0.733451]
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7623 [D loss: 0.702607, acc.: 42.97%] [G loss: 0.737531]
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7624 [D loss: 0.692416, acc.: 46.29%] [G loss: 0.750073]
8/8 [==============================] - 0s 4ms/step
7625 [D loss: 0.700193, acc.: 47.46%] [G loss: 0.742728]
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7626 [D loss: 0.694723, acc.: 51.56%] [G loss: 0.751144]
8/8 [==============================] - 0s 4ms/step
7627 [D loss: 0.704175, acc.: 42.38%] [G loss: 0.741982]
8/8 [==============================] - 0s 4ms/step
7628 [D loss: 0.695197, acc.: 49.02%] [G loss: 0.738935]
8/8 [==============================] - 0s 4ms/step
7629 [D loss: 0.698310, acc.: 46.09%] [G loss: 0.737424]
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7630 [D loss: 0.695103, acc.: 50.00%] [G loss: 0.764250]
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7631 [D loss: 0.694488, acc.: 51.37%] [G loss: 0.729367]
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7632 [D loss: 0.696988, acc.: 50.59%] [G loss: 0.726544]
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7633 [D loss: 0.695600, acc.: 47.85%] [G loss: 0.734460]
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7634 [D loss: 0.699312, acc.: 46.29%] [G loss: 0.746544]
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7635 [D loss: 0.693450, acc.: 50.39%] [G loss: 0.748308]
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7636 [D loss: 0.689472, acc.: 50.59%] [G loss: 0.752491]
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7637 [D loss: 0.691287, acc.: 50.20%] [G loss: 0.743574]
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7638 [D loss: 0.690989, acc.: 50.00%] [G loss: 0.733552]
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7639 [D loss: 0.686205, acc.: 52.93%] [G loss: 0.733659]
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7640 [D loss: 0.695532, acc.: 44.92%] [G loss: 0.703534]
8/8 [==============================] - 0s 4ms/step
7641 [D loss: 0.700039, acc.: 49.80%] [G loss: 0.704601]
8/8 [==============================] - 0s 4ms/step
7642 [D loss: 0.700558, acc.: 47.85%] [G loss: 0.723556]
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7643 [D loss: 0.695652, acc.: 46.48%] [G loss: 0.745262]
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7644 [D loss: 0.695916, acc.: 46.48%] [G loss: 0.767822]
8/8 [==============================] - 0s 4ms/step
7645 [D loss: 0.687979, acc.: 50.20%] [G loss: 0.764304]
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7646 [D loss: 0.692174, acc.: 48.63%] [G loss: 0.747959]
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7647 [D loss: 0.689694, acc.: 48.24%] [G loss: 0.808571]
8/8 [==============================] - 0s 4ms/step
7648 [D loss: 0.690989, acc.: 50.20%] [G loss: 0.741357]
8/8 [==============================] - 0s 4ms/step
7649 [D loss: 0.693988, acc.: 45.70%] [G loss: 0.735214]
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7650 [D loss: 0.694440, acc.: 49.61%] [G loss: 0.730753]
1/1 [==============================] - 0s 35ms/step
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7651 [D loss: 0.675219, acc.: 53.71%] [G loss: 0.725843]
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7652 [D loss: 0.693415, acc.: 46.29%] [G loss: 0.729839]
8/8 [==============================] - 0s 4ms/step
7653 [D loss: 0.695198, acc.: 43.95%] [G loss: 0.720771]
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7654 [D loss: 0.692777, acc.: 44.34%] [G loss: 0.715673]
8/8 [==============================] - 0s 4ms/step
7655 [D loss: 0.700110, acc.: 44.92%] [G loss: 0.728173]
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7656 [D loss: 0.693112, acc.: 48.05%] [G loss: 0.732814]
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7657 [D loss: 0.694538, acc.: 48.83%] [G loss: 0.746205]
8/8 [==============================] - 0s 4ms/step
7658 [D loss: 0.686894, acc.: 51.56%] [G loss: 0.770562]
8/8 [==============================] - 0s 4ms/step
7659 [D loss: 0.688720, acc.: 54.49%] [G loss: 0.750725]
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7660 [D loss: 0.689909, acc.: 52.15%] [G loss: 0.739636]
8/8 [==============================] - 0s 4ms/step
7661 [D loss: 0.691098, acc.: 51.37%] [G loss: 0.735115]
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7662 [D loss: 0.693515, acc.: 47.27%] [G loss: 0.717246]
8/8 [==============================] - 0s 4ms/step
7663 [D loss: 0.693426, acc.: 50.20%] [G loss: 0.710122]
8/8 [==============================] - 0s 4ms/step
7664 [D loss: 0.695859, acc.: 45.12%] [G loss: 0.708894]
8/8 [==============================] - 0s 4ms/step
7665 [D loss: 0.692893, acc.: 47.27%] [G loss: 0.718344]
8/8 [==============================] - 0s 4ms/step
7666 [D loss: 0.685818, acc.: 48.63%] [G loss: 0.757212]
8/8 [==============================] - 0s 4ms/step
7667 [D loss: 0.672578, acc.: 54.88%] [G loss: 0.778440]
8/8 [==============================] - 0s 4ms/step
7668 [D loss: 0.672534, acc.: 51.95%] [G loss: 0.788400]
8/8 [==============================] - 0s 4ms/step
7669 [D loss: 0.685931, acc.: 52.54%] [G loss: 0.776438]
8/8 [==============================] - 0s 4ms/step
7670 [D loss: 0.678675, acc.: 52.34%] [G loss: 0.760192]
8/8 [==============================] - 0s 4ms/step
7671 [D loss: 0.695693, acc.: 45.12%] [G loss: 0.736488]
8/8 [==============================] - 0s 4ms/step
7672 [D loss: 0.681816, acc.: 52.73%] [G loss: 0.754681]
8/8 [==============================] - 0s 4ms/step
7673 [D loss: 0.678973, acc.: 53.32%] [G loss: 0.737769]
8/8 [==============================] - 0s 4ms/step
7674 [D loss: 0.678452, acc.: 48.44%] [G loss: 0.722587]
8/8 [==============================] - 0s 4ms/step
7675 [D loss: 0.687622, acc.: 48.44%] [G loss: 0.729556]
8/8 [==============================] - 0s 4ms/step
7676 [D loss: 0.692331, acc.: 45.51%] [G loss: 0.737470]
8/8 [==============================] - 0s 4ms/step
7677 [D loss: 0.682976, acc.: 51.56%] [G loss: 0.743453]
8/8 [==============================] - 0s 4ms/step
7678 [D loss: 0.693944, acc.: 48.63%] [G loss: 0.751611]
8/8 [==============================] - 0s 4ms/step
7679 [D loss: 0.687690, acc.: 47.66%] [G loss: 0.735035]
8/8 [==============================] - 0s 4ms/step
7680 [D loss: 0.689016, acc.: 49.41%] [G loss: 0.738762]
8/8 [==============================] - 0s 4ms/step
7681 [D loss: 0.680697, acc.: 54.69%] [G loss: 0.745090]
8/8 [==============================] - 0s 4ms/step
7682 [D loss: 0.681775, acc.: 50.20%] [G loss: 0.735911]
8/8 [==============================] - 0s 4ms/step
7683 [D loss: 0.687097, acc.: 49.41%] [G loss: 0.724879]
8/8 [==============================] - 0s 4ms/step
7684 [D loss: 0.679640, acc.: 57.62%] [G loss: 0.724469]
8/8 [==============================] - 0s 4ms/step
7685 [D loss: 0.682827, acc.: 52.54%] [G loss: 0.732881]
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7686 [D loss: 0.688811, acc.: 51.56%] [G loss: 0.761119]
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7687 [D loss: 0.678357, acc.: 51.95%] [G loss: 0.770834]
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7688 [D loss: 0.678537, acc.: 55.86%] [G loss: 0.756851]
8/8 [==============================] - 0s 4ms/step
7689 [D loss: 0.696930, acc.: 47.46%] [G loss: 0.740438]
8/8 [==============================] - 0s 4ms/step
7690 [D loss: 0.686847, acc.: 48.63%] [G loss: 0.750971]
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7691 [D loss: 0.688860, acc.: 47.27%] [G loss: 0.747594]
8/8 [==============================] - 0s 4ms/step
7692 [D loss: 0.698394, acc.: 41.41%] [G loss: 0.724575]
8/8 [==============================] - 0s 4ms/step
7693 [D loss: 0.706229, acc.: 37.70%] [G loss: 0.721381]
8/8 [==============================] - 0s 4ms/step
7694 [D loss: 0.709253, acc.: 39.84%] [G loss: 0.724932]
8/8 [==============================] - 0s 4ms/step
7695 [D loss: 0.705105, acc.: 42.97%] [G loss: 0.781006]
8/8 [==============================] - 0s 4ms/step
7696 [D loss: 0.693428, acc.: 50.78%] [G loss: 0.813311]
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7697 [D loss: 0.695133, acc.: 50.00%] [G loss: 0.783274]
8/8 [==============================] - 0s 4ms/step
7698 [D loss: 0.699839, acc.: 46.88%] [G loss: 0.765909]
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7699 [D loss: 0.700811, acc.: 50.20%] [G loss: 0.783401]
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7700 [D loss: 0.702551, acc.: 44.92%] [G loss: 0.721730]
1/1 [==============================] - 0s 29ms/step
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7701 [D loss: 0.690862, acc.: 53.52%] [G loss: 0.729975]
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7702 [D loss: 0.689004, acc.: 53.12%] [G loss: 0.748747]
8/8 [==============================] - 0s 4ms/step
7703 [D loss: 0.693071, acc.: 52.54%] [G loss: 0.751797]
8/8 [==============================] - 0s 4ms/step
7704 [D loss: 0.695459, acc.: 47.46%] [G loss: 0.734092]
8/8 [==============================] - 0s 4ms/step
7705 [D loss: 0.692421, acc.: 48.05%] [G loss: 0.733751]
8/8 [==============================] - 0s 4ms/step
7706 [D loss: 0.685221, acc.: 51.17%] [G loss: 0.752886]
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7707 [D loss: 0.682606, acc.: 51.95%] [G loss: 0.747869]
8/8 [==============================] - 0s 4ms/step
7708 [D loss: 0.691662, acc.: 51.76%] [G loss: 0.737490]
8/8 [==============================] - 0s 4ms/step
7709 [D loss: 0.683449, acc.: 53.52%] [G loss: 0.721355]
8/8 [==============================] - 0s 4ms/step
7710 [D loss: 0.683983, acc.: 49.41%] [G loss: 0.729660]
8/8 [==============================] - 0s 4ms/step
7711 [D loss: 0.681787, acc.: 51.37%] [G loss: 0.727131]
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7712 [D loss: 0.684911, acc.: 51.76%] [G loss: 0.719911]
8/8 [==============================] - 0s 4ms/step
7713 [D loss: 0.690337, acc.: 50.00%] [G loss: 0.718546]
8/8 [==============================] - 0s 4ms/step
7714 [D loss: 0.690240, acc.: 43.55%] [G loss: 0.739255]
8/8 [==============================] - 0s 4ms/step
7715 [D loss: 0.682478, acc.: 50.00%] [G loss: 0.726043]
8/8 [==============================] - 0s 4ms/step
7716 [D loss: 0.682748, acc.: 47.85%] [G loss: 0.731133]
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7717 [D loss: 0.685272, acc.: 50.39%] [G loss: 0.731203]
8/8 [==============================] - 0s 4ms/step
7718 [D loss: 0.695221, acc.: 46.29%] [G loss: 0.731467]
8/8 [==============================] - 0s 4ms/step
7719 [D loss: 0.692667, acc.: 50.78%] [G loss: 0.720065]
8/8 [==============================] - 0s 4ms/step
7720 [D loss: 0.683129, acc.: 51.17%] [G loss: 0.714708]
8/8 [==============================] - 0s 4ms/step
7721 [D loss: 0.673158, acc.: 51.56%] [G loss: 0.721102]
8/8 [==============================] - 0s 4ms/step
7722 [D loss: 0.680616, acc.: 50.59%] [G loss: 0.731898]
8/8 [==============================] - 0s 4ms/step
7723 [D loss: 0.677975, acc.: 49.41%] [G loss: 0.736506]
8/8 [==============================] - 0s 4ms/step
7724 [D loss: 0.681366, acc.: 49.80%] [G loss: 0.724899]
8/8 [==============================] - 0s 4ms/step
7725 [D loss: 0.678748, acc.: 51.56%] [G loss: 0.742227]
8/8 [==============================] - 0s 4ms/step
7726 [D loss: 0.683196, acc.: 53.32%] [G loss: 0.734775]
8/8 [==============================] - 0s 4ms/step
7727 [D loss: 0.685200, acc.: 48.63%] [G loss: 0.730309]
8/8 [==============================] - 0s 4ms/step
7728 [D loss: 0.686179, acc.: 51.37%] [G loss: 0.723364]
8/8 [==============================] - 0s 4ms/step
7729 [D loss: 0.674692, acc.: 53.32%] [G loss: 0.728633]
8/8 [==============================] - 0s 4ms/step
7730 [D loss: 0.677928, acc.: 50.98%] [G loss: 0.726626]
8/8 [==============================] - 0s 4ms/step
7731 [D loss: 0.688724, acc.: 47.27%] [G loss: 0.729478]
8/8 [==============================] - 0s 4ms/step
7732 [D loss: 0.684072, acc.: 46.09%] [G loss: 0.727716]
8/8 [==============================] - 0s 4ms/step
7733 [D loss: 0.694049, acc.: 43.36%] [G loss: 0.722317]
8/8 [==============================] - 0s 4ms/step
7734 [D loss: 0.682611, acc.: 46.68%] [G loss: 0.731858]
8/8 [==============================] - 0s 4ms/step
7735 [D loss: 0.671853, acc.: 50.98%] [G loss: 0.731961]
8/8 [==============================] - 0s 4ms/step
7736 [D loss: 0.688438, acc.: 47.07%] [G loss: 0.730391]
8/8 [==============================] - 0s 4ms/step
7737 [D loss: 0.676648, acc.: 53.91%] [G loss: 0.741977]
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7738 [D loss: 0.679042, acc.: 51.37%] [G loss: 0.733551]
8/8 [==============================] - 0s 4ms/step
7739 [D loss: 0.682439, acc.: 49.22%] [G loss: 0.746472]
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7740 [D loss: 0.681880, acc.: 51.56%] [G loss: 0.741315]
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7741 [D loss: 0.680124, acc.: 46.29%] [G loss: 0.738232]
8/8 [==============================] - 0s 4ms/step
7742 [D loss: 0.688261, acc.: 47.66%] [G loss: 0.737753]
8/8 [==============================] - 0s 4ms/step
7743 [D loss: 0.686127, acc.: 48.44%] [G loss: 0.734213]
8/8 [==============================] - 0s 4ms/step
7744 [D loss: 0.691261, acc.: 43.75%] [G loss: 0.730370]
8/8 [==============================] - 0s 4ms/step
7745 [D loss: 0.685543, acc.: 46.88%] [G loss: 0.741058]
8/8 [==============================] - 0s 4ms/step
7746 [D loss: 0.680156, acc.: 48.63%] [G loss: 0.735762]
8/8 [==============================] - 0s 4ms/step
7747 [D loss: 0.677590, acc.: 52.54%] [G loss: 0.738974]
8/8 [==============================] - 0s 4ms/step
7748 [D loss: 0.686646, acc.: 45.70%] [G loss: 0.739205]
8/8 [==============================] - 0s 4ms/step
7749 [D loss: 0.685878, acc.: 47.85%] [G loss: 0.728001]
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7750 [D loss: 0.678461, acc.: 49.61%] [G loss: 0.731524]
1/1 [==============================] - 0s 24ms/step
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7751 [D loss: 0.684790, acc.: 47.46%] [G loss: 0.715343]
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7752 [D loss: 0.687693, acc.: 45.12%] [G loss: 0.716272]
8/8 [==============================] - 0s 4ms/step
7753 [D loss: 0.679812, acc.: 45.70%] [G loss: 0.735685]
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7754 [D loss: 0.676140, acc.: 50.98%] [G loss: 0.727614]
8/8 [==============================] - 0s 4ms/step
7755 [D loss: 0.671375, acc.: 51.56%] [G loss: 0.741619]
8/8 [==============================] - 0s 4ms/step
7756 [D loss: 0.683343, acc.: 47.07%] [G loss: 0.733195]
8/8 [==============================] - 0s 4ms/step
7757 [D loss: 0.684355, acc.: 46.68%] [G loss: 0.733618]
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7758 [D loss: 0.675213, acc.: 47.07%] [G loss: 0.739010]
8/8 [==============================] - 0s 4ms/step
7759 [D loss: 0.676167, acc.: 51.17%] [G loss: 0.731214]
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7760 [D loss: 0.680580, acc.: 50.98%] [G loss: 0.730546]
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7761 [D loss: 0.685325, acc.: 46.88%] [G loss: 0.729840]
8/8 [==============================] - 0s 4ms/step
7762 [D loss: 0.682913, acc.: 49.41%] [G loss: 0.730239]
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7763 [D loss: 0.672697, acc.: 47.85%] [G loss: 0.731680]
8/8 [==============================] - 0s 4ms/step
7764 [D loss: 0.686328, acc.: 50.59%] [G loss: 0.730138]
8/8 [==============================] - 0s 4ms/step
7765 [D loss: 0.675262, acc.: 49.61%] [G loss: 0.725211]
8/8 [==============================] - 0s 4ms/step
7766 [D loss: 0.690051, acc.: 45.70%] [G loss: 0.721633]
8/8 [==============================] - 0s 4ms/step
7767 [D loss: 0.679037, acc.: 48.83%] [G loss: 0.721975]
8/8 [==============================] - 0s 4ms/step
7768 [D loss: 0.686785, acc.: 47.07%] [G loss: 0.709440]
8/8 [==============================] - 0s 4ms/step
7769 [D loss: 0.696490, acc.: 41.99%] [G loss: 0.721606]
8/8 [==============================] - 0s 4ms/step
7770 [D loss: 0.678726, acc.: 49.61%] [G loss: 0.726976]
8/8 [==============================] - 0s 4ms/step
7771 [D loss: 0.686156, acc.: 47.07%] [G loss: 0.734228]
8/8 [==============================] - 0s 4ms/step
7772 [D loss: 0.677414, acc.: 50.39%] [G loss: 0.719518]
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7773 [D loss: 0.686446, acc.: 47.85%] [G loss: 0.732913]
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7774 [D loss: 0.675819, acc.: 51.37%] [G loss: 0.729050]
8/8 [==============================] - 0s 4ms/step
7775 [D loss: 0.690543, acc.: 45.70%] [G loss: 0.724434]
8/8 [==============================] - 0s 4ms/step
7776 [D loss: 0.682669, acc.: 49.02%] [G loss: 0.725615]
8/8 [==============================] - 0s 4ms/step
7777 [D loss: 0.692178, acc.: 47.66%] [G loss: 0.729037]
8/8 [==============================] - 0s 4ms/step
7778 [D loss: 0.686720, acc.: 45.70%] [G loss: 0.734443]
8/8 [==============================] - 0s 4ms/step
7779 [D loss: 0.687129, acc.: 47.46%] [G loss: 0.725862]
8/8 [==============================] - 0s 4ms/step
7780 [D loss: 0.688892, acc.: 47.27%] [G loss: 0.732865]
8/8 [==============================] - 0s 4ms/step
7781 [D loss: 0.675867, acc.: 52.73%] [G loss: 0.738122]
8/8 [==============================] - 0s 4ms/step
7782 [D loss: 0.665141, acc.: 53.32%] [G loss: 0.738820]
8/8 [==============================] - 0s 4ms/step
7783 [D loss: 0.676679, acc.: 51.17%] [G loss: 0.731061]
8/8 [==============================] - 0s 4ms/step
7784 [D loss: 0.684957, acc.: 45.70%] [G loss: 0.741097]
8/8 [==============================] - 0s 4ms/step
7785 [D loss: 0.678508, acc.: 48.44%] [G loss: 0.727708]
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7786 [D loss: 0.691737, acc.: 47.46%] [G loss: 0.726527]
8/8 [==============================] - 0s 4ms/step
7787 [D loss: 0.679303, acc.: 52.34%] [G loss: 0.717825]
8/8 [==============================] - 0s 4ms/step
7788 [D loss: 0.690197, acc.: 44.53%] [G loss: 0.735239]
8/8 [==============================] - 0s 4ms/step
7789 [D loss: 0.689629, acc.: 47.66%] [G loss: 0.726070]
8/8 [==============================] - 0s 4ms/step
7790 [D loss: 0.722111, acc.: 49.02%] [G loss: 0.715880]
8/8 [==============================] - 0s 4ms/step
7791 [D loss: 0.716338, acc.: 48.44%] [G loss: 0.715571]
8/8 [==============================] - 0s 4ms/step
7792 [D loss: 0.692183, acc.: 50.78%] [G loss: 0.735492]
8/8 [==============================] - 0s 4ms/step
7793 [D loss: 0.687621, acc.: 50.39%] [G loss: 0.742733]
8/8 [==============================] - 0s 4ms/step
7794 [D loss: 0.686847, acc.: 50.98%] [G loss: 0.746464]
8/8 [==============================] - 0s 4ms/step
7795 [D loss: 0.693318, acc.: 47.46%] [G loss: 0.732651]
8/8 [==============================] - 0s 4ms/step
7796 [D loss: 0.691541, acc.: 50.00%] [G loss: 0.752535]
8/8 [==============================] - 0s 4ms/step
7797 [D loss: 0.687170, acc.: 49.02%] [G loss: 0.742433]
8/8 [==============================] - 0s 4ms/step
7798 [D loss: 0.691910, acc.: 48.24%] [G loss: 0.736207]
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7799 [D loss: 0.691106, acc.: 47.85%] [G loss: 0.739405]
8/8 [==============================] - 0s 4ms/step
7800 [D loss: 0.688482, acc.: 49.80%] [G loss: 0.721597]
1/1 [==============================] - 0s 34ms/step
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7801 [D loss: 0.697411, acc.: 49.22%] [G loss: 0.711446]
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7802 [D loss: 0.698860, acc.: 46.09%] [G loss: 0.695052]
8/8 [==============================] - 0s 4ms/step
7803 [D loss: 0.704417, acc.: 41.80%] [G loss: 0.701468]
8/8 [==============================] - 0s 4ms/step
7804 [D loss: 0.702646, acc.: 42.58%] [G loss: 0.708827]
8/8 [==============================] - 0s 4ms/step
7805 [D loss: 0.700060, acc.: 46.29%] [G loss: 0.719476]
8/8 [==============================] - 0s 4ms/step
7806 [D loss: 0.693734, acc.: 45.12%] [G loss: 0.732055]
8/8 [==============================] - 0s 4ms/step
7807 [D loss: 0.693041, acc.: 44.73%] [G loss: 0.744842]
8/8 [==============================] - 0s 4ms/step
7808 [D loss: 0.696003, acc.: 46.09%] [G loss: 0.738470]
8/8 [==============================] - 0s 4ms/step
7809 [D loss: 0.695449, acc.: 49.80%] [G loss: 0.726286]
8/8 [==============================] - 0s 4ms/step
7810 [D loss: 0.691333, acc.: 50.98%] [G loss: 0.730489]
8/8 [==============================] - 0s 4ms/step
7811 [D loss: 0.703642, acc.: 55.47%] [G loss: 0.752915]
8/8 [==============================] - 0s 4ms/step
7812 [D loss: 0.696512, acc.: 50.00%] [G loss: 0.722711]
8/8 [==============================] - 0s 4ms/step
7813 [D loss: 0.690659, acc.: 53.52%] [G loss: 0.731274]
8/8 [==============================] - 0s 4ms/step
7814 [D loss: 0.693037, acc.: 51.95%] [G loss: 0.730027]
8/8 [==============================] - 0s 4ms/step
7815 [D loss: 0.699704, acc.: 46.29%] [G loss: 0.734362]
8/8 [==============================] - 0s 4ms/step
7816 [D loss: 0.695791, acc.: 49.61%] [G loss: 0.733042]
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7817 [D loss: 0.694758, acc.: 46.09%] [G loss: 0.732448]
8/8 [==============================] - 0s 4ms/step
7818 [D loss: 0.682996, acc.: 53.12%] [G loss: 0.749831]
8/8 [==============================] - 0s 4ms/step
7819 [D loss: 0.694854, acc.: 49.02%] [G loss: 0.762846]
8/8 [==============================] - 0s 4ms/step
7820 [D loss: 0.692472, acc.: 48.05%] [G loss: 0.736031]
8/8 [==============================] - 0s 4ms/step
7821 [D loss: 0.688002, acc.: 52.34%] [G loss: 0.727253]
8/8 [==============================] - 0s 4ms/step
7822 [D loss: 0.685814, acc.: 52.73%] [G loss: 0.730677]
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7823 [D loss: 0.694168, acc.: 46.88%] [G loss: 0.726566]
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7824 [D loss: 0.697004, acc.: 48.24%] [G loss: 0.716350]
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7825 [D loss: 0.691422, acc.: 55.08%] [G loss: 0.717712]
8/8 [==============================] - 0s 4ms/step
7826 [D loss: 0.689415, acc.: 49.61%] [G loss: 0.731197]
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7827 [D loss: 0.687621, acc.: 55.66%] [G loss: 0.760128]
8/8 [==============================] - 0s 4ms/step
7828 [D loss: 0.684910, acc.: 51.95%] [G loss: 0.766523]
8/8 [==============================] - 0s 4ms/step
7829 [D loss: 0.685582, acc.: 55.08%] [G loss: 0.770259]
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7830 [D loss: 0.683983, acc.: 53.71%] [G loss: 0.748768]
8/8 [==============================] - 0s 4ms/step
7831 [D loss: 0.695447, acc.: 57.62%] [G loss: 0.733267]
8/8 [==============================] - 0s 4ms/step
7832 [D loss: 0.681862, acc.: 58.98%] [G loss: 0.737765]
8/8 [==============================] - 0s 4ms/step
7833 [D loss: 0.701626, acc.: 45.51%] [G loss: 0.710378]
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7834 [D loss: 0.702237, acc.: 49.41%] [G loss: 0.719112]
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7835 [D loss: 0.691055, acc.: 52.93%] [G loss: 0.737455]
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7836 [D loss: 0.687382, acc.: 55.08%] [G loss: 0.750427]
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7837 [D loss: 0.693989, acc.: 51.17%] [G loss: 0.760400]
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7838 [D loss: 0.688401, acc.: 54.49%] [G loss: 0.744405]
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7839 [D loss: 0.692527, acc.: 49.80%] [G loss: 0.731419]
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7840 [D loss: 0.690867, acc.: 50.98%] [G loss: 0.733236]
8/8 [==============================] - 0s 4ms/step
7841 [D loss: 0.699870, acc.: 44.34%] [G loss: 0.698182]
8/8 [==============================] - 0s 4ms/step
7842 [D loss: 0.704171, acc.: 44.73%] [G loss: 0.693024]
8/8 [==============================] - 0s 4ms/step
7843 [D loss: 0.697861, acc.: 45.90%] [G loss: 0.708593]
8/8 [==============================] - 0s 4ms/step
7844 [D loss: 0.702115, acc.: 40.43%] [G loss: 0.719682]
8/8 [==============================] - 0s 4ms/step
7845 [D loss: 0.691063, acc.: 48.83%] [G loss: 0.736700]
8/8 [==============================] - 0s 4ms/step
7846 [D loss: 0.689433, acc.: 50.20%] [G loss: 0.753407]
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7847 [D loss: 0.692727, acc.: 51.95%] [G loss: 0.743915]
8/8 [==============================] - 0s 4ms/step
7848 [D loss: 0.698446, acc.: 45.31%] [G loss: 0.731153]
8/8 [==============================] - 0s 4ms/step
7849 [D loss: 0.697168, acc.: 47.46%] [G loss: 0.723756]
8/8 [==============================] - 0s 4ms/step
7850 [D loss: 0.692916, acc.: 54.30%] [G loss: 0.732620]
1/1 [==============================] - 0s 35ms/step
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7851 [D loss: 0.690413, acc.: 54.49%] [G loss: 0.724668]
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7852 [D loss: 0.691674, acc.: 53.91%] [G loss: 0.720847]
8/8 [==============================] - 0s 4ms/step
7853 [D loss: 0.697266, acc.: 50.78%] [G loss: 0.721588]
8/8 [==============================] - 0s 4ms/step
7854 [D loss: 0.685774, acc.: 55.08%] [G loss: 0.734929]
8/8 [==============================] - 0s 4ms/step
7855 [D loss: 0.695559, acc.: 50.39%] [G loss: 0.746523]
8/8 [==============================] - 0s 4ms/step
7856 [D loss: 0.690672, acc.: 49.02%] [G loss: 0.742323]
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7857 [D loss: 0.691330, acc.: 49.80%] [G loss: 0.741973]
8/8 [==============================] - 0s 4ms/step
7858 [D loss: 0.690027, acc.: 52.34%] [G loss: 0.739547]
8/8 [==============================] - 0s 4ms/step
7859 [D loss: 0.680299, acc.: 53.71%] [G loss: 0.740401]
8/8 [==============================] - 0s 4ms/step
7860 [D loss: 0.703107, acc.: 42.97%] [G loss: 0.709999]
8/8 [==============================] - 0s 4ms/step
7861 [D loss: 0.686771, acc.: 50.20%] [G loss: 0.732435]
8/8 [==============================] - 0s 4ms/step
7862 [D loss: 0.702678, acc.: 46.29%] [G loss: 0.735761]
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7863 [D loss: 0.697745, acc.: 50.39%] [G loss: 0.729691]
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7864 [D loss: 0.692912, acc.: 50.98%] [G loss: 0.719102]
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7865 [D loss: 0.700014, acc.: 48.83%] [G loss: 0.718354]
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7866 [D loss: 0.686591, acc.: 56.25%] [G loss: 0.731875]
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7867 [D loss: 0.695745, acc.: 50.59%] [G loss: 0.725248]
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7868 [D loss: 0.699366, acc.: 45.70%] [G loss: 0.718489]
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7869 [D loss: 0.699085, acc.: 46.09%] [G loss: 0.728609]
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7870 [D loss: 0.701943, acc.: 44.14%] [G loss: 0.724538]
8/8 [==============================] - 0s 4ms/step
7871 [D loss: 0.699086, acc.: 47.85%] [G loss: 0.740316]
8/8 [==============================] - 0s 4ms/step
7872 [D loss: 0.694425, acc.: 49.80%] [G loss: 0.753767]
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7873 [D loss: 0.695027, acc.: 48.44%] [G loss: 0.737213]
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7874 [D loss: 0.699303, acc.: 52.15%] [G loss: 0.738498]
8/8 [==============================] - 0s 4ms/step
7875 [D loss: 0.681906, acc.: 55.27%] [G loss: 0.750915]
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7876 [D loss: 0.702010, acc.: 47.46%] [G loss: 0.721313]
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7877 [D loss: 0.689901, acc.: 51.76%] [G loss: 0.739974]
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7878 [D loss: 0.677794, acc.: 56.45%] [G loss: 0.753824]
8/8 [==============================] - 0s 4ms/step
7879 [D loss: 0.678287, acc.: 55.47%] [G loss: 0.788490]
8/8 [==============================] - 0s 4ms/step
7880 [D loss: 0.682993, acc.: 52.93%] [G loss: 0.768521]
8/8 [==============================] - 0s 4ms/step
7881 [D loss: 0.687381, acc.: 53.52%] [G loss: 0.762901]
8/8 [==============================] - 0s 4ms/step
7882 [D loss: 0.691815, acc.: 48.44%] [G loss: 0.757915]
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7883 [D loss: 0.679787, acc.: 55.66%] [G loss: 0.747521]
8/8 [==============================] - 0s 4ms/step
7884 [D loss: 0.689123, acc.: 50.00%] [G loss: 0.719020]
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7885 [D loss: 0.691750, acc.: 46.29%] [G loss: 0.704635]
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7886 [D loss: 0.695744, acc.: 47.27%] [G loss: 0.704114]
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7887 [D loss: 0.696785, acc.: 48.44%] [G loss: 0.735737]
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7888 [D loss: 0.689053, acc.: 52.15%] [G loss: 0.758997]
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7889 [D loss: 0.696836, acc.: 48.83%] [G loss: 0.766999]
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7890 [D loss: 0.692193, acc.: 50.20%] [G loss: 0.758093]
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7891 [D loss: 0.689454, acc.: 48.83%] [G loss: 0.745873]
8/8 [==============================] - 0s 4ms/step
7892 [D loss: 0.682851, acc.: 53.12%] [G loss: 0.748400]
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7893 [D loss: 0.677678, acc.: 54.69%] [G loss: 0.761138]
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7894 [D loss: 0.687621, acc.: 50.78%] [G loss: 0.736313]
8/8 [==============================] - 0s 4ms/step
7895 [D loss: 0.691315, acc.: 46.48%] [G loss: 0.726585]
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7896 [D loss: 0.687235, acc.: 47.85%] [G loss: 0.716683]
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7897 [D loss: 0.685139, acc.: 52.34%] [G loss: 0.724548]
8/8 [==============================] - 0s 4ms/step
7898 [D loss: 0.684637, acc.: 50.59%] [G loss: 0.724247]
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7899 [D loss: 0.695689, acc.: 47.07%] [G loss: 0.731669]
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7900 [D loss: 0.694118, acc.: 47.07%] [G loss: 0.720654]
1/1 [==============================] - 0s 32ms/step
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7901 [D loss: 0.699505, acc.: 45.51%] [G loss: 0.704966]
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7902 [D loss: 0.710875, acc.: 43.95%] [G loss: 0.710359]
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7903 [D loss: 0.702180, acc.: 46.09%] [G loss: 0.699586]
8/8 [==============================] - 0s 4ms/step
7904 [D loss: 0.701112, acc.: 45.90%] [G loss: 0.715518]
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7905 [D loss: 0.705073, acc.: 43.16%] [G loss: 0.712062]
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7906 [D loss: 0.703901, acc.: 45.90%] [G loss: 0.719485]
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7907 [D loss: 0.703493, acc.: 41.80%] [G loss: 0.738569]
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7908 [D loss: 0.694416, acc.: 51.17%] [G loss: 0.731609]
8/8 [==============================] - 0s 4ms/step
7909 [D loss: 0.691357, acc.: 51.76%] [G loss: 0.738124]
8/8 [==============================] - 0s 4ms/step
7910 [D loss: 0.696672, acc.: 49.61%] [G loss: 0.735296]
8/8 [==============================] - 0s 4ms/step
7911 [D loss: 0.697018, acc.: 51.37%] [G loss: 0.739078]
8/8 [==============================] - 0s 4ms/step
7912 [D loss: 0.692932, acc.: 49.02%] [G loss: 0.740684]
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7913 [D loss: 0.684005, acc.: 53.91%] [G loss: 0.726887]
8/8 [==============================] - 0s 4ms/step
7914 [D loss: 0.691823, acc.: 50.98%] [G loss: 0.724173]
8/8 [==============================] - 0s 4ms/step
7915 [D loss: 0.683103, acc.: 52.93%] [G loss: 0.737755]
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7916 [D loss: 0.682716, acc.: 57.81%] [G loss: 0.743029]
8/8 [==============================] - 0s 4ms/step
7917 [D loss: 0.688629, acc.: 51.56%] [G loss: 0.749134]
8/8 [==============================] - 0s 4ms/step
7918 [D loss: 0.690900, acc.: 49.80%] [G loss: 0.731277]
8/8 [==============================] - 0s 4ms/step
7919 [D loss: 0.691966, acc.: 49.22%] [G loss: 0.722692]
8/8 [==============================] - 0s 4ms/step
7920 [D loss: 0.696157, acc.: 46.48%] [G loss: 0.734895]
8/8 [==============================] - 0s 4ms/step
7921 [D loss: 0.696082, acc.: 45.90%] [G loss: 0.721220]
8/8 [==============================] - 0s 4ms/step
7922 [D loss: 0.692052, acc.: 47.46%] [G loss: 0.739152]
8/8 [==============================] - 0s 4ms/step
7923 [D loss: 0.689971, acc.: 48.63%] [G loss: 0.734115]
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7924 [D loss: 0.688533, acc.: 51.37%] [G loss: 0.747839]
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7925 [D loss: 0.690620, acc.: 47.07%] [G loss: 0.730808]
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7926 [D loss: 0.695811, acc.: 46.88%] [G loss: 0.724181]
8/8 [==============================] - 0s 4ms/step
7927 [D loss: 0.693580, acc.: 47.66%] [G loss: 0.728241]
8/8 [==============================] - 0s 4ms/step
7928 [D loss: 0.696957, acc.: 46.68%] [G loss: 0.708372]
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7929 [D loss: 0.699813, acc.: 46.88%] [G loss: 0.711973]
8/8 [==============================] - 0s 4ms/step
7930 [D loss: 0.691290, acc.: 50.78%] [G loss: 0.722134]
8/8 [==============================] - 0s 4ms/step
7931 [D loss: 0.693647, acc.: 50.00%] [G loss: 0.722259]
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7932 [D loss: 0.698241, acc.: 46.29%] [G loss: 0.717511]
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7933 [D loss: 0.692738, acc.: 53.12%] [G loss: 0.722219]
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7934 [D loss: 0.692658, acc.: 53.52%] [G loss: 0.717449]
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7935 [D loss: 0.692463, acc.: 52.93%] [G loss: 0.705871]
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7936 [D loss: 0.699286, acc.: 50.00%] [G loss: 0.715158]
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7937 [D loss: 0.695036, acc.: 49.22%] [G loss: 0.725349]
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7938 [D loss: 0.692768, acc.: 53.32%] [G loss: 0.733382]
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7939 [D loss: 0.692425, acc.: 49.61%] [G loss: 0.736781]
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7940 [D loss: 0.691078, acc.: 51.95%] [G loss: 0.726018]
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7941 [D loss: 0.689797, acc.: 51.95%] [G loss: 0.733239]
8/8 [==============================] - 0s 4ms/step
7942 [D loss: 0.695259, acc.: 51.17%] [G loss: 0.719188]
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7943 [D loss: 0.697843, acc.: 46.48%] [G loss: 0.700795]
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7944 [D loss: 0.698730, acc.: 45.12%] [G loss: 0.705343]
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7945 [D loss: 0.701927, acc.: 44.73%] [G loss: 0.709228]
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7946 [D loss: 0.697113, acc.: 46.88%] [G loss: 0.727456]
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7947 [D loss: 0.687815, acc.: 50.98%] [G loss: 0.746334]
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7948 [D loss: 0.692539, acc.: 50.78%] [G loss: 0.744724]
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7949 [D loss: 0.688491, acc.: 50.98%] [G loss: 0.742253]
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7950 [D loss: 0.692599, acc.: 50.59%] [G loss: 0.741526]
1/1 [==============================] - 0s 29ms/step
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7951 [D loss: 0.686986, acc.: 52.54%] [G loss: 0.734262]
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7952 [D loss: 0.695038, acc.: 46.88%] [G loss: 0.707392]
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7953 [D loss: 0.697219, acc.: 46.88%] [G loss: 0.703956]
8/8 [==============================] - 0s 4ms/step
7954 [D loss: 0.693759, acc.: 49.22%] [G loss: 0.712070]
8/8 [==============================] - 0s 4ms/step
7955 [D loss: 0.694405, acc.: 47.27%] [G loss: 0.711313]
8/8 [==============================] - 0s 4ms/step
7956 [D loss: 0.691829, acc.: 49.80%] [G loss: 0.727433]
8/8 [==============================] - 0s 4ms/step
7957 [D loss: 0.691663, acc.: 47.46%] [G loss: 0.732751]
8/8 [==============================] - 0s 4ms/step
7958 [D loss: 0.689797, acc.: 48.83%] [G loss: 0.728095]
8/8 [==============================] - 0s 4ms/step
7959 [D loss: 0.688060, acc.: 49.80%] [G loss: 0.727296]
8/8 [==============================] - 0s 4ms/step
7960 [D loss: 0.691259, acc.: 49.80%] [G loss: 0.712770]
8/8 [==============================] - 0s 4ms/step
7961 [D loss: 0.696660, acc.: 49.22%] [G loss: 0.713054]
8/8 [==============================] - 0s 4ms/step
7962 [D loss: 0.694316, acc.: 53.32%] [G loss: 0.719673]
8/8 [==============================] - 0s 4ms/step
7963 [D loss: 0.687150, acc.: 50.20%] [G loss: 0.738465]
8/8 [==============================] - 0s 4ms/step
7964 [D loss: 0.682069, acc.: 55.27%] [G loss: 0.746599]
8/8 [==============================] - 0s 4ms/step
7965 [D loss: 0.693886, acc.: 48.83%] [G loss: 0.747773]
8/8 [==============================] - 0s 4ms/step
7966 [D loss: 0.681548, acc.: 49.80%] [G loss: 0.758569]
8/8 [==============================] - 0s 4ms/step
7967 [D loss: 0.691848, acc.: 46.48%] [G loss: 0.762144]
8/8 [==============================] - 0s 4ms/step
7968 [D loss: 0.687510, acc.: 48.63%] [G loss: 0.741508]
8/8 [==============================] - 0s 4ms/step
7969 [D loss: 0.685513, acc.: 52.34%] [G loss: 0.732108]
8/8 [==============================] - 0s 4ms/step
7970 [D loss: 0.695043, acc.: 47.07%] [G loss: 0.732461]
8/8 [==============================] - 0s 4ms/step
7971 [D loss: 0.697174, acc.: 48.63%] [G loss: 0.708830]
8/8 [==============================] - 0s 4ms/step
7972 [D loss: 0.701514, acc.: 43.16%] [G loss: 0.709660]
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7973 [D loss: 0.700526, acc.: 41.02%] [G loss: 0.706277]
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7974 [D loss: 0.697655, acc.: 44.73%] [G loss: 0.721982]
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7975 [D loss: 0.683107, acc.: 53.12%] [G loss: 0.739705]
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7976 [D loss: 0.683674, acc.: 51.37%] [G loss: 0.749180]
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7977 [D loss: 0.687782, acc.: 55.47%] [G loss: 0.731886]
8/8 [==============================] - 0s 4ms/step
7978 [D loss: 0.684839, acc.: 52.34%] [G loss: 0.742042]
8/8 [==============================] - 0s 4ms/step
7979 [D loss: 0.685018, acc.: 55.08%] [G loss: 0.732013]
8/8 [==============================] - 0s 4ms/step
7980 [D loss: 0.685467, acc.: 51.17%] [G loss: 0.730935]
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7981 [D loss: 0.683768, acc.: 51.37%] [G loss: 0.714009]
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7982 [D loss: 0.692111, acc.: 48.44%] [G loss: 0.706143]
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7983 [D loss: 0.685960, acc.: 52.15%] [G loss: 0.717122]
8/8 [==============================] - 0s 4ms/step
7984 [D loss: 0.685959, acc.: 47.27%] [G loss: 0.738626]
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7985 [D loss: 0.680932, acc.: 49.61%] [G loss: 0.724888]
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7986 [D loss: 0.692374, acc.: 49.80%] [G loss: 0.736042]
8/8 [==============================] - 0s 4ms/step
7987 [D loss: 0.693197, acc.: 47.85%] [G loss: 0.746162]
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7988 [D loss: 0.684077, acc.: 54.10%] [G loss: 0.751147]
8/8 [==============================] - 0s 4ms/step
7989 [D loss: 0.686549, acc.: 52.15%] [G loss: 0.750815]
8/8 [==============================] - 0s 4ms/step
7990 [D loss: 0.687380, acc.: 50.20%] [G loss: 0.741128]
8/8 [==============================] - 0s 4ms/step
7991 [D loss: 0.680192, acc.: 50.98%] [G loss: 0.754918]
8/8 [==============================] - 0s 4ms/step
7992 [D loss: 0.687758, acc.: 48.44%] [G loss: 0.761095]
8/8 [==============================] - 0s 4ms/step
7993 [D loss: 0.688399, acc.: 50.59%] [G loss: 0.735157]
8/8 [==============================] - 0s 4ms/step
7994 [D loss: 0.678320, acc.: 54.10%] [G loss: 0.753645]
8/8 [==============================] - 0s 4ms/step
7995 [D loss: 0.689246, acc.: 52.34%] [G loss: 0.723533]
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7996 [D loss: 0.695475, acc.: 45.70%] [G loss: 0.732967]
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7997 [D loss: 0.691407, acc.: 48.24%] [G loss: 0.724739]
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7998 [D loss: 0.694364, acc.: 42.97%] [G loss: 0.728824]
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7999 [D loss: 0.696912, acc.: 43.95%] [G loss: 0.725375]
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8000 [D loss: 0.692928, acc.: 41.99%] [G loss: 0.719324]
1/1 [==============================] - 0s 28ms/step
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8001 [D loss: 0.694919, acc.: 43.16%] [G loss: 0.722178]
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8002 [D loss: 0.695184, acc.: 46.09%] [G loss: 0.718765]
8/8 [==============================] - 0s 4ms/step
8003 [D loss: 0.688417, acc.: 47.85%] [G loss: 0.729625]
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8004 [D loss: 0.683282, acc.: 48.05%] [G loss: 0.731299]
8/8 [==============================] - 0s 4ms/step
8005 [D loss: 0.688519, acc.: 49.22%] [G loss: 0.723369]
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8006 [D loss: 0.685346, acc.: 48.83%] [G loss: 0.726640]
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8007 [D loss: 0.690621, acc.: 47.66%] [G loss: 0.727797]
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8008 [D loss: 0.686881, acc.: 51.76%] [G loss: 0.722936]
8/8 [==============================] - 0s 4ms/step
8009 [D loss: 0.684732, acc.: 49.02%] [G loss: 0.722078]
8/8 [==============================] - 0s 4ms/step
8010 [D loss: 0.687206, acc.: 45.70%] [G loss: 0.728989]
8/8 [==============================] - 0s 4ms/step
8011 [D loss: 0.677072, acc.: 53.52%] [G loss: 0.729930]
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8012 [D loss: 0.696285, acc.: 44.14%] [G loss: 0.730896]
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8013 [D loss: 0.675337, acc.: 50.39%] [G loss: 0.734596]
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8014 [D loss: 0.682143, acc.: 50.39%] [G loss: 0.738280]
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8015 [D loss: 0.676274, acc.: 50.00%] [G loss: 0.741998]
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8016 [D loss: 0.678118, acc.: 51.95%] [G loss: 0.737013]
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8017 [D loss: 0.683495, acc.: 51.17%] [G loss: 0.735003]
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8018 [D loss: 0.683567, acc.: 51.37%] [G loss: 0.738820]
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8019 [D loss: 0.679621, acc.: 49.22%] [G loss: 0.733040]
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8020 [D loss: 0.679582, acc.: 50.59%] [G loss: 0.732842]
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8021 [D loss: 0.671977, acc.: 50.98%] [G loss: 0.734790]
8/8 [==============================] - 0s 4ms/step
8022 [D loss: 0.674870, acc.: 53.71%] [G loss: 0.743858]
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8023 [D loss: 0.691934, acc.: 46.68%] [G loss: 0.745597]
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8024 [D loss: 0.678510, acc.: 53.52%] [G loss: 0.745554]
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8025 [D loss: 0.689457, acc.: 47.85%] [G loss: 0.735603]
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8026 [D loss: 0.683643, acc.: 50.59%] [G loss: 0.724814]
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8027 [D loss: 0.685794, acc.: 49.02%] [G loss: 0.722667]
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8028 [D loss: 0.688539, acc.: 46.29%] [G loss: 0.713799]
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8029 [D loss: 0.691371, acc.: 46.88%] [G loss: 0.707816]
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8030 [D loss: 0.688332, acc.: 47.07%] [G loss: 0.717103]
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8031 [D loss: 0.695982, acc.: 46.48%] [G loss: 0.728882]
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8032 [D loss: 0.683668, acc.: 47.46%] [G loss: 0.736212]
8/8 [==============================] - 0s 4ms/step
8033 [D loss: 0.683974, acc.: 52.73%] [G loss: 0.742047]
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8034 [D loss: 0.680397, acc.: 53.71%] [G loss: 0.739563]
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8035 [D loss: 0.682019, acc.: 51.56%] [G loss: 0.761390]
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8036 [D loss: 0.679798, acc.: 53.91%] [G loss: 0.756049]
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8037 [D loss: 0.688430, acc.: 53.71%] [G loss: 0.745126]
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8038 [D loss: 0.690513, acc.: 50.59%] [G loss: 0.737889]
8/8 [==============================] - 0s 4ms/step
8039 [D loss: 0.682755, acc.: 54.30%] [G loss: 0.732053]
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8040 [D loss: 0.683407, acc.: 53.91%] [G loss: 0.731505]
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8041 [D loss: 0.701994, acc.: 45.12%] [G loss: 0.725084]
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8042 [D loss: 0.688634, acc.: 51.76%] [G loss: 0.759894]
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8043 [D loss: 0.703880, acc.: 44.34%] [G loss: 0.720739]
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8044 [D loss: 0.704751, acc.: 49.41%] [G loss: 0.732136]
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8045 [D loss: 0.690180, acc.: 52.54%] [G loss: 0.755389]
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8046 [D loss: 0.700102, acc.: 52.15%] [G loss: 0.733852]
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8047 [D loss: 0.689481, acc.: 49.80%] [G loss: 0.745627]
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8048 [D loss: 0.699094, acc.: 52.93%] [G loss: 0.729433]
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8049 [D loss: 0.696340, acc.: 48.63%] [G loss: 0.741926]
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8050 [D loss: 0.693058, acc.: 48.24%] [G loss: 0.736238]
1/1 [==============================] - 0s 28ms/step
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8051 [D loss: 0.695897, acc.: 46.68%] [G loss: 0.733881]
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8052 [D loss: 0.692924, acc.: 48.63%] [G loss: 0.727313]
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8053 [D loss: 0.685608, acc.: 50.78%] [G loss: 0.737534]
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8054 [D loss: 0.686022, acc.: 52.15%] [G loss: 0.723373]
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8055 [D loss: 0.694102, acc.: 47.46%] [G loss: 0.712283]
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8056 [D loss: 0.696885, acc.: 46.68%] [G loss: 0.715722]
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8057 [D loss: 0.685266, acc.: 52.34%] [G loss: 0.726960]
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8058 [D loss: 0.691943, acc.: 49.22%] [G loss: 0.725972]
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8059 [D loss: 0.686617, acc.: 51.95%] [G loss: 0.719086]
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8060 [D loss: 0.699809, acc.: 45.51%] [G loss: 0.722826]
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8061 [D loss: 0.687922, acc.: 49.80%] [G loss: 0.721856]
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8062 [D loss: 0.688180, acc.: 47.46%] [G loss: 0.714398]
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8063 [D loss: 0.686564, acc.: 47.46%] [G loss: 0.723078]
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8064 [D loss: 0.694158, acc.: 47.66%] [G loss: 0.718401]
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8065 [D loss: 0.682173, acc.: 48.24%] [G loss: 0.723523]
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8066 [D loss: 0.681150, acc.: 47.46%] [G loss: 0.734156]
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8067 [D loss: 0.693331, acc.: 44.73%] [G loss: 0.725497]
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8068 [D loss: 0.687381, acc.: 51.76%] [G loss: 0.723900]
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8069 [D loss: 0.684894, acc.: 51.76%] [G loss: 0.722944]
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8070 [D loss: 0.689271, acc.: 46.09%] [G loss: 0.733678]
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8071 [D loss: 0.687776, acc.: 48.44%] [G loss: 0.743945]
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8072 [D loss: 0.682285, acc.: 52.34%] [G loss: 0.736121]
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8073 [D loss: 0.672476, acc.: 52.15%] [G loss: 0.740820]
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8074 [D loss: 0.681966, acc.: 51.17%] [G loss: 0.736741]
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8075 [D loss: 0.669473, acc.: 54.49%] [G loss: 0.739743]
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8076 [D loss: 0.686229, acc.: 50.98%] [G loss: 0.735826]
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8077 [D loss: 0.679693, acc.: 54.88%] [G loss: 0.733492]
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8078 [D loss: 0.684877, acc.: 47.85%] [G loss: 0.731135]
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8079 [D loss: 0.670144, acc.: 51.76%] [G loss: 0.730200]
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8080 [D loss: 0.685514, acc.: 47.66%] [G loss: 0.731918]
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8081 [D loss: 0.685660, acc.: 48.44%] [G loss: 0.738892]
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8082 [D loss: 0.691066, acc.: 47.85%] [G loss: 0.725986]
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8083 [D loss: 0.683651, acc.: 50.39%] [G loss: 0.729842]
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8084 [D loss: 0.684439, acc.: 49.80%] [G loss: 0.734618]
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8085 [D loss: 0.683606, acc.: 47.85%] [G loss: 0.739382]
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8086 [D loss: 0.678240, acc.: 53.52%] [G loss: 0.722998]
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8087 [D loss: 0.691115, acc.: 48.05%] [G loss: 0.729224]
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8088 [D loss: 0.695392, acc.: 44.34%] [G loss: 0.720303]
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8089 [D loss: 0.686876, acc.: 47.46%] [G loss: 0.731958]
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8090 [D loss: 0.682533, acc.: 49.61%] [G loss: 0.740791]
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8091 [D loss: 0.682032, acc.: 49.61%] [G loss: 0.727288]
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8092 [D loss: 0.690592, acc.: 45.12%] [G loss: 0.729246]
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8093 [D loss: 0.687121, acc.: 47.85%] [G loss: 0.730341]
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8094 [D loss: 0.683870, acc.: 52.15%] [G loss: 0.722288]
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8095 [D loss: 0.672967, acc.: 51.95%] [G loss: 0.725438]
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8096 [D loss: 0.677868, acc.: 49.22%] [G loss: 0.714237]
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8097 [D loss: 0.684577, acc.: 48.44%] [G loss: 0.708461]
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8098 [D loss: 0.690150, acc.: 45.51%] [G loss: 0.734412]
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8099 [D loss: 0.680819, acc.: 51.37%] [G loss: 0.732968]
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8100 [D loss: 0.685503, acc.: 46.88%] [G loss: 0.746625]
1/1 [==============================] - 0s 29ms/step
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8101 [D loss: 0.679558, acc.: 51.56%] [G loss: 0.741043]
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8102 [D loss: 0.676469, acc.: 50.59%] [G loss: 0.738277]
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8103 [D loss: 0.680998, acc.: 48.63%] [G loss: 0.729757]
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8104 [D loss: 0.681592, acc.: 48.83%] [G loss: 0.738702]
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8105 [D loss: 0.668182, acc.: 49.41%] [G loss: 0.733807]
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8106 [D loss: 0.682149, acc.: 52.15%] [G loss: 0.729799]
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8107 [D loss: 0.672821, acc.: 50.59%] [G loss: 0.735270]
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8108 [D loss: 0.695925, acc.: 46.29%] [G loss: 0.721978]
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8109 [D loss: 0.686040, acc.: 47.85%] [G loss: 0.732351]
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8110 [D loss: 0.689749, acc.: 45.31%] [G loss: 0.727947]
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8111 [D loss: 0.684942, acc.: 53.71%] [G loss: 0.734915]
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8112 [D loss: 0.676477, acc.: 51.56%] [G loss: 0.744279]
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8113 [D loss: 0.681168, acc.: 52.15%] [G loss: 0.742730]
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8114 [D loss: 0.690926, acc.: 46.09%] [G loss: 0.735360]
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8115 [D loss: 0.680048, acc.: 46.48%] [G loss: 0.740316]
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8116 [D loss: 0.684837, acc.: 47.07%] [G loss: 0.728027]
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8117 [D loss: 0.674773, acc.: 51.76%] [G loss: 0.726297]
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8118 [D loss: 0.680248, acc.: 46.48%] [G loss: 0.723390]
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8119 [D loss: 0.687284, acc.: 48.24%] [G loss: 0.724807]
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8120 [D loss: 0.672678, acc.: 53.32%] [G loss: 0.739534]
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8121 [D loss: 0.675669, acc.: 52.34%] [G loss: 0.742009]
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8122 [D loss: 0.673529, acc.: 50.59%] [G loss: 0.738608]
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8123 [D loss: 0.670021, acc.: 54.88%] [G loss: 0.734526]
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8124 [D loss: 0.685841, acc.: 48.83%] [G loss: 0.718149]
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8125 [D loss: 0.679392, acc.: 50.20%] [G loss: 0.723701]
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8126 [D loss: 0.682714, acc.: 47.85%] [G loss: 0.728861]
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8127 [D loss: 0.690682, acc.: 41.60%] [G loss: 0.720812]
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8128 [D loss: 0.689989, acc.: 45.51%] [G loss: 0.725166]
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8129 [D loss: 0.690140, acc.: 48.44%] [G loss: 0.726323]
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8130 [D loss: 0.682400, acc.: 45.90%] [G loss: 0.733420]
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8131 [D loss: 0.688105, acc.: 51.95%] [G loss: 0.738961]
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8132 [D loss: 0.682023, acc.: 47.85%] [G loss: 0.741474]
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8133 [D loss: 0.684867, acc.: 50.78%] [G loss: 0.743214]
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8134 [D loss: 0.671945, acc.: 53.52%] [G loss: 0.744397]
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8135 [D loss: 0.684247, acc.: 48.83%] [G loss: 0.738909]
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8136 [D loss: 0.690961, acc.: 47.85%] [G loss: 0.749830]
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8137 [D loss: 0.675672, acc.: 51.95%] [G loss: 0.737548]
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8138 [D loss: 0.686633, acc.: 47.46%] [G loss: 0.755625]
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8139 [D loss: 0.664359, acc.: 53.32%] [G loss: 0.741447]
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8140 [D loss: 0.683234, acc.: 47.46%] [G loss: 0.750029]
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8141 [D loss: 0.675153, acc.: 49.22%] [G loss: 0.752074]
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8142 [D loss: 0.676246, acc.: 51.56%] [G loss: 0.750911]
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8143 [D loss: 0.752961, acc.: 46.48%] [G loss: 0.698767]
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8144 [D loss: 0.697520, acc.: 44.73%] [G loss: 0.722840]
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8145 [D loss: 0.704736, acc.: 44.53%] [G loss: 0.713699]
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8146 [D loss: 0.719980, acc.: 43.36%] [G loss: 0.770398]
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8147 [D loss: 0.679436, acc.: 52.93%] [G loss: 0.808974]
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8148 [D loss: 0.688022, acc.: 49.41%] [G loss: 0.766341]
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8149 [D loss: 0.687543, acc.: 51.76%] [G loss: 0.748111]
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8150 [D loss: 0.684831, acc.: 51.56%] [G loss: 0.755000]
1/1 [==============================] - 0s 29ms/step
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8151 [D loss: 0.687568, acc.: 49.41%] [G loss: 0.744273]
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8152 [D loss: 0.678436, acc.: 53.91%] [G loss: 0.735621]
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8153 [D loss: 0.694635, acc.: 48.05%] [G loss: 0.716104]
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8154 [D loss: 0.701883, acc.: 48.24%] [G loss: 0.708071]
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8155 [D loss: 0.694441, acc.: 50.39%] [G loss: 0.735711]
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8156 [D loss: 0.690325, acc.: 52.54%] [G loss: 0.746552]
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8157 [D loss: 0.689084, acc.: 49.22%] [G loss: 0.757542]
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8158 [D loss: 0.692398, acc.: 50.59%] [G loss: 0.742748]
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8159 [D loss: 0.693440, acc.: 50.20%] [G loss: 0.736453]
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8160 [D loss: 0.689986, acc.: 54.49%] [G loss: 0.738715]
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8161 [D loss: 0.690199, acc.: 52.54%] [G loss: 0.733104]
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8162 [D loss: 0.697503, acc.: 48.44%] [G loss: 0.707474]
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8163 [D loss: 0.702566, acc.: 41.99%] [G loss: 0.711480]
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8164 [D loss: 0.697582, acc.: 44.92%] [G loss: 0.719361]
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8165 [D loss: 0.693774, acc.: 51.17%] [G loss: 0.753607]
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8166 [D loss: 0.686975, acc.: 51.17%] [G loss: 0.769910]
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8167 [D loss: 0.693741, acc.: 46.48%] [G loss: 0.756883]
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8168 [D loss: 0.695339, acc.: 47.46%] [G loss: 0.750739]
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8169 [D loss: 0.691078, acc.: 48.63%] [G loss: 0.746142]
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8170 [D loss: 0.683316, acc.: 51.37%] [G loss: 0.759472]
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8171 [D loss: 0.691965, acc.: 50.20%] [G loss: 0.732442]
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8172 [D loss: 0.681699, acc.: 50.00%] [G loss: 0.728636]
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8173 [D loss: 0.694561, acc.: 49.61%] [G loss: 0.726366]
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8174 [D loss: 0.697230, acc.: 47.07%] [G loss: 0.727799]
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8175 [D loss: 0.684594, acc.: 53.32%] [G loss: 0.732522]
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8176 [D loss: 0.692337, acc.: 46.09%] [G loss: 0.729103]
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8177 [D loss: 0.685085, acc.: 50.39%] [G loss: 0.732107]
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8178 [D loss: 0.684611, acc.: 48.44%] [G loss: 0.752565]
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8179 [D loss: 0.693284, acc.: 46.88%] [G loss: 0.727982]
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8180 [D loss: 0.690563, acc.: 50.39%] [G loss: 0.727519]
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8181 [D loss: 0.690534, acc.: 49.02%] [G loss: 0.733370]
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8182 [D loss: 0.691357, acc.: 51.17%] [G loss: 0.721993]
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8183 [D loss: 0.687990, acc.: 51.56%] [G loss: 0.738654]
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8184 [D loss: 0.691306, acc.: 51.17%] [G loss: 0.742413]
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8185 [D loss: 0.694207, acc.: 52.93%] [G loss: 0.726429]
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8186 [D loss: 0.688809, acc.: 51.37%] [G loss: 0.737518]
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8187 [D loss: 0.689620, acc.: 50.78%] [G loss: 0.735674]
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8188 [D loss: 0.697222, acc.: 47.46%] [G loss: 0.732287]
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8189 [D loss: 0.707660, acc.: 49.61%] [G loss: 0.729309]
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8190 [D loss: 0.699812, acc.: 41.41%] [G loss: 0.731731]
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8191 [D loss: 0.696347, acc.: 48.63%] [G loss: 0.738570]
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8192 [D loss: 0.702894, acc.: 44.73%] [G loss: 0.731071]
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8193 [D loss: 0.702292, acc.: 46.68%] [G loss: 0.723498]
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8194 [D loss: 0.699038, acc.: 48.83%] [G loss: 0.720464]
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8195 [D loss: 0.697626, acc.: 46.48%] [G loss: 0.726090]
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8196 [D loss: 0.701889, acc.: 44.14%] [G loss: 0.719977]
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8197 [D loss: 0.695891, acc.: 50.00%] [G loss: 0.715410]
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8198 [D loss: 0.698635, acc.: 44.73%] [G loss: 0.715109]
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8199 [D loss: 0.692823, acc.: 47.07%] [G loss: 0.728378]
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8200 [D loss: 0.685936, acc.: 54.49%] [G loss: 0.743081]
1/1 [==============================] - 0s 36ms/step
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8201 [D loss: 0.683169, acc.: 54.69%] [G loss: 0.752734]
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8202 [D loss: 0.689396, acc.: 50.78%] [G loss: 0.754673]
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8203 [D loss: 0.685203, acc.: 50.98%] [G loss: 0.747232]
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8204 [D loss: 0.684985, acc.: 54.30%] [G loss: 0.747210]
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8205 [D loss: 0.684420, acc.: 52.73%] [G loss: 0.738195]
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8206 [D loss: 0.678774, acc.: 50.39%] [G loss: 0.729091]
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8207 [D loss: 0.690761, acc.: 50.59%] [G loss: 0.725542]
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8208 [D loss: 0.689788, acc.: 48.05%] [G loss: 0.721354]
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8209 [D loss: 0.683448, acc.: 49.22%] [G loss: 0.737662]
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8210 [D loss: 0.678313, acc.: 53.12%] [G loss: 0.732552]
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8211 [D loss: 0.683848, acc.: 50.78%] [G loss: 0.747805]
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8212 [D loss: 0.683854, acc.: 52.54%] [G loss: 0.733971]
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8213 [D loss: 0.677123, acc.: 53.12%] [G loss: 0.734023]
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8214 [D loss: 0.691629, acc.: 48.63%] [G loss: 0.725167]
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8215 [D loss: 0.684409, acc.: 48.63%] [G loss: 0.742562]
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8216 [D loss: 0.688032, acc.: 45.70%] [G loss: 0.730057]
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8217 [D loss: 0.697686, acc.: 43.36%] [G loss: 0.734721]
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8218 [D loss: 0.685333, acc.: 44.34%] [G loss: 0.749079]
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8219 [D loss: 0.677652, acc.: 48.44%] [G loss: 0.738201]
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8220 [D loss: 0.698604, acc.: 47.85%] [G loss: 0.736890]
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8221 [D loss: 0.680272, acc.: 54.30%] [G loss: 0.734432]
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8222 [D loss: 0.683473, acc.: 49.41%] [G loss: 0.732686]
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8223 [D loss: 0.677722, acc.: 51.76%] [G loss: 0.728481]
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8224 [D loss: 0.683069, acc.: 47.27%] [G loss: 0.738851]
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8225 [D loss: 0.681566, acc.: 51.37%] [G loss: 0.739350]
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8226 [D loss: 0.693470, acc.: 48.44%] [G loss: 0.737990]
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8227 [D loss: 0.696104, acc.: 51.37%] [G loss: 0.728475]
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8228 [D loss: 0.693200, acc.: 53.32%] [G loss: 0.727180]
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8229 [D loss: 0.688644, acc.: 53.12%] [G loss: 0.739781]
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8230 [D loss: 0.689062, acc.: 49.22%] [G loss: 0.755182]
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8231 [D loss: 0.690876, acc.: 45.90%] [G loss: 0.720724]
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8232 [D loss: 0.681229, acc.: 51.37%] [G loss: 0.737553]
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8233 [D loss: 0.686479, acc.: 50.00%] [G loss: 0.734025]
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8234 [D loss: 0.688106, acc.: 50.78%] [G loss: 0.725565]
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8235 [D loss: 0.694992, acc.: 42.97%] [G loss: 0.722148]
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8236 [D loss: 0.680054, acc.: 50.78%] [G loss: 0.730644]
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8237 [D loss: 0.682103, acc.: 48.83%] [G loss: 0.734747]
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8238 [D loss: 0.692561, acc.: 45.90%] [G loss: 0.716499]
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8239 [D loss: 0.682469, acc.: 51.56%] [G loss: 0.722518]
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8240 [D loss: 0.686055, acc.: 45.12%] [G loss: 0.741275]
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8241 [D loss: 0.684948, acc.: 46.88%] [G loss: 0.744567]
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8242 [D loss: 0.682280, acc.: 51.95%] [G loss: 0.747865]
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8243 [D loss: 0.683436, acc.: 50.59%] [G loss: 0.736822]
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8244 [D loss: 0.686777, acc.: 48.83%] [G loss: 0.736154]
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8245 [D loss: 0.682418, acc.: 53.52%] [G loss: 0.726846]
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8246 [D loss: 0.689496, acc.: 53.12%] [G loss: 0.723866]
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8247 [D loss: 0.696537, acc.: 47.66%] [G loss: 0.715517]
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8248 [D loss: 0.694489, acc.: 48.83%] [G loss: 0.721164]
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8249 [D loss: 0.692802, acc.: 48.44%] [G loss: 0.737545]
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8250 [D loss: 0.697747, acc.: 49.80%] [G loss: 0.734164]
1/1 [==============================] - 0s 35ms/step
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8251 [D loss: 0.697110, acc.: 45.51%] [G loss: 0.728736]
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8252 [D loss: 0.701740, acc.: 42.77%] [G loss: 0.723383]
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8253 [D loss: 0.700657, acc.: 42.58%] [G loss: 0.710290]
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8254 [D loss: 0.696491, acc.: 49.41%] [G loss: 0.710269]
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8255 [D loss: 0.696002, acc.: 46.68%] [G loss: 0.736235]
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8256 [D loss: 0.693380, acc.: 44.92%] [G loss: 0.727671]
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8257 [D loss: 0.696420, acc.: 40.43%] [G loss: 0.741258]
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8258 [D loss: 0.693915, acc.: 48.83%] [G loss: 0.741431]
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8259 [D loss: 0.692944, acc.: 47.07%] [G loss: 0.731952]
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8260 [D loss: 0.692111, acc.: 45.12%] [G loss: 0.739738]
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8261 [D loss: 0.693157, acc.: 48.05%] [G loss: 0.741241]
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8262 [D loss: 0.690425, acc.: 47.66%] [G loss: 0.733535]
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8263 [D loss: 0.691095, acc.: 48.05%] [G loss: 0.720992]
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8264 [D loss: 0.695313, acc.: 46.68%] [G loss: 0.726346]
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8265 [D loss: 0.692296, acc.: 49.02%] [G loss: 0.716172]
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8266 [D loss: 0.692608, acc.: 52.34%] [G loss: 0.728615]
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8267 [D loss: 0.692662, acc.: 51.95%] [G loss: 0.723597]
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8268 [D loss: 0.686790, acc.: 56.45%] [G loss: 0.736936]
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8269 [D loss: 0.695048, acc.: 51.76%] [G loss: 0.744646]
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8270 [D loss: 0.690519, acc.: 50.59%] [G loss: 0.721852]
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8271 [D loss: 0.692219, acc.: 51.76%] [G loss: 0.721621]
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8272 [D loss: 0.695673, acc.: 52.34%] [G loss: 0.713929]
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8273 [D loss: 0.696152, acc.: 49.22%] [G loss: 0.705451]
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8274 [D loss: 0.698363, acc.: 47.66%] [G loss: 0.687805]
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8275 [D loss: 0.693648, acc.: 47.66%] [G loss: 0.698622]
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8276 [D loss: 0.699372, acc.: 44.92%] [G loss: 0.717636]
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8277 [D loss: 0.699652, acc.: 44.92%] [G loss: 0.725035]
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8278 [D loss: 0.704637, acc.: 42.19%] [G loss: 0.724122]
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8279 [D loss: 0.706303, acc.: 41.80%] [G loss: 0.721813]
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8280 [D loss: 0.695578, acc.: 47.66%] [G loss: 0.725906]
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8281 [D loss: 0.694512, acc.: 49.22%] [G loss: 0.721672]
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8282 [D loss: 0.685411, acc.: 54.88%] [G loss: 0.735656]
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8283 [D loss: 0.686591, acc.: 50.20%] [G loss: 0.740699]
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8284 [D loss: 0.685937, acc.: 55.86%] [G loss: 0.754091]
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8285 [D loss: 0.682508, acc.: 56.25%] [G loss: 0.770224]
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8286 [D loss: 0.685446, acc.: 53.52%] [G loss: 0.766049]
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8287 [D loss: 0.679798, acc.: 52.54%] [G loss: 0.773438]
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8288 [D loss: 0.680603, acc.: 55.08%] [G loss: 0.752249]
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8289 [D loss: 0.684552, acc.: 52.15%] [G loss: 0.755473]
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8290 [D loss: 0.677985, acc.: 57.62%] [G loss: 0.744933]
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8291 [D loss: 0.676329, acc.: 53.12%] [G loss: 0.731651]
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8292 [D loss: 0.695589, acc.: 46.68%] [G loss: 0.718159]
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8293 [D loss: 0.707681, acc.: 42.77%] [G loss: 0.682980]
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8294 [D loss: 0.699195, acc.: 46.68%] [G loss: 0.713537]
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8295 [D loss: 0.692399, acc.: 52.15%] [G loss: 0.727967]
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8296 [D loss: 0.682176, acc.: 55.86%] [G loss: 0.754635]
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8297 [D loss: 0.696824, acc.: 51.37%] [G loss: 0.749213]
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8298 [D loss: 0.691987, acc.: 49.22%] [G loss: 0.755466]
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8299 [D loss: 0.696660, acc.: 47.46%] [G loss: 0.734179]
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8300 [D loss: 0.702050, acc.: 45.31%] [G loss: 0.712651]
1/1 [==============================] - 0s 27ms/step
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8301 [D loss: 0.700660, acc.: 45.51%] [G loss: 0.703646]
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8302 [D loss: 0.709244, acc.: 41.80%] [G loss: 0.699683]
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8303 [D loss: 0.703057, acc.: 44.34%] [G loss: 0.718969]
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8304 [D loss: 0.694206, acc.: 45.70%] [G loss: 0.749567]
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8305 [D loss: 0.686533, acc.: 48.44%] [G loss: 0.763502]
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8306 [D loss: 0.688469, acc.: 51.56%] [G loss: 0.757030]
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8307 [D loss: 0.701237, acc.: 53.91%] [G loss: 0.740211]
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8308 [D loss: 0.688511, acc.: 55.27%] [G loss: 0.748483]
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8309 [D loss: 0.688470, acc.: 53.32%] [G loss: 0.754163]
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8310 [D loss: 0.691102, acc.: 49.02%] [G loss: 0.726995]
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8311 [D loss: 0.694588, acc.: 49.80%] [G loss: 0.726904]
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8312 [D loss: 0.685366, acc.: 50.59%] [G loss: 0.756709]
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8313 [D loss: 0.679060, acc.: 51.37%] [G loss: 0.782935]
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8314 [D loss: 0.689616, acc.: 46.48%] [G loss: 0.773092]
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8315 [D loss: 0.692453, acc.: 45.31%] [G loss: 0.759675]
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8316 [D loss: 0.689904, acc.: 47.46%] [G loss: 0.752876]
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8317 [D loss: 0.699827, acc.: 43.55%] [G loss: 0.738006]
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8318 [D loss: 0.695005, acc.: 48.24%] [G loss: 0.724010]
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8319 [D loss: 0.695656, acc.: 45.70%] [G loss: 0.724071]
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8320 [D loss: 0.692165, acc.: 46.68%] [G loss: 0.732173]
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8321 [D loss: 0.683157, acc.: 53.12%] [G loss: 0.732944]
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8322 [D loss: 0.680476, acc.: 55.47%] [G loss: 0.750985]
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8323 [D loss: 0.681995, acc.: 52.54%] [G loss: 0.735126]
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8324 [D loss: 0.678212, acc.: 53.71%] [G loss: 0.737999]
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8325 [D loss: 0.676105, acc.: 51.56%] [G loss: 0.742449]
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8326 [D loss: 0.686535, acc.: 46.48%] [G loss: 0.742698]
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8327 [D loss: 0.679835, acc.: 48.05%] [G loss: 0.732723]
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8328 [D loss: 0.679677, acc.: 52.54%] [G loss: 0.727195]
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8329 [D loss: 0.685924, acc.: 49.41%] [G loss: 0.725464]
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8330 [D loss: 0.686298, acc.: 43.75%] [G loss: 0.718690]
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8331 [D loss: 0.696548, acc.: 45.51%] [G loss: 0.734628]
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8332 [D loss: 0.692601, acc.: 41.21%] [G loss: 0.724334]
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8333 [D loss: 0.686705, acc.: 47.85%] [G loss: 0.741523]
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8334 [D loss: 0.678802, acc.: 51.95%] [G loss: 0.754364]
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8335 [D loss: 0.679480, acc.: 56.05%] [G loss: 0.758799]
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8336 [D loss: 0.679881, acc.: 54.88%] [G loss: 0.758366]
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8337 [D loss: 0.680325, acc.: 54.30%] [G loss: 0.759435]
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8338 [D loss: 0.661038, acc.: 61.13%] [G loss: 0.761512]
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8339 [D loss: 0.681771, acc.: 51.56%] [G loss: 0.740899]
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8340 [D loss: 0.685766, acc.: 51.37%] [G loss: 0.735693]
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8341 [D loss: 0.683702, acc.: 47.85%] [G loss: 0.719696]
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8342 [D loss: 0.684231, acc.: 50.59%] [G loss: 0.729996]
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8343 [D loss: 0.690423, acc.: 47.85%] [G loss: 0.741022]
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8344 [D loss: 0.691371, acc.: 47.07%] [G loss: 0.763287]
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8345 [D loss: 0.676468, acc.: 51.37%] [G loss: 0.758841]
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8346 [D loss: 0.681191, acc.: 47.46%] [G loss: 0.742525]
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8347 [D loss: 0.695169, acc.: 45.31%] [G loss: 0.733996]
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8348 [D loss: 0.702884, acc.: 50.98%] [G loss: 0.714977]
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8349 [D loss: 0.711984, acc.: 50.59%] [G loss: 0.720632]
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8350 [D loss: 0.685208, acc.: 51.56%] [G loss: 0.735104]
1/1 [==============================] - 0s 26ms/step
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8351 [D loss: 0.685242, acc.: 50.59%] [G loss: 0.734942]
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8352 [D loss: 0.693816, acc.: 47.46%] [G loss: 0.723391]
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8353 [D loss: 0.686956, acc.: 52.73%] [G loss: 0.713924]
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8354 [D loss: 0.689156, acc.: 49.41%] [G loss: 0.720252]
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8355 [D loss: 0.692739, acc.: 46.29%] [G loss: 0.717607]
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8356 [D loss: 0.679070, acc.: 49.61%] [G loss: 0.731115]
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8357 [D loss: 0.683230, acc.: 49.80%] [G loss: 0.727383]
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8358 [D loss: 0.680016, acc.: 49.02%] [G loss: 0.733605]
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8359 [D loss: 0.688807, acc.: 48.44%] [G loss: 0.737845]
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8360 [D loss: 0.686302, acc.: 50.98%] [G loss: 0.730500]
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8361 [D loss: 0.679576, acc.: 51.95%] [G loss: 0.743048]
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8362 [D loss: 0.679248, acc.: 51.56%] [G loss: 0.733491]
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8363 [D loss: 0.681519, acc.: 50.20%] [G loss: 0.737813]
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8364 [D loss: 0.686054, acc.: 50.39%] [G loss: 0.731532]
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8365 [D loss: 0.690383, acc.: 47.66%] [G loss: 0.726876]
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8366 [D loss: 0.699157, acc.: 47.07%] [G loss: 0.719638]
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8367 [D loss: 0.684487, acc.: 50.00%] [G loss: 0.735467]
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8368 [D loss: 0.686862, acc.: 46.68%] [G loss: 0.730202]
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8369 [D loss: 0.689938, acc.: 49.02%] [G loss: 0.740468]
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8370 [D loss: 0.696537, acc.: 45.70%] [G loss: 0.729301]
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8371 [D loss: 0.690913, acc.: 47.66%] [G loss: 0.733487]
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8372 [D loss: 0.697004, acc.: 47.46%] [G loss: 0.742359]
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8373 [D loss: 0.685459, acc.: 49.80%] [G loss: 0.742386]
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8374 [D loss: 0.696628, acc.: 45.12%] [G loss: 0.729822]
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8375 [D loss: 0.680730, acc.: 53.12%] [G loss: 0.728844]
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8376 [D loss: 0.689238, acc.: 50.20%] [G loss: 0.718648]
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8377 [D loss: 0.689700, acc.: 51.95%] [G loss: 0.730919]
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8378 [D loss: 0.691158, acc.: 52.54%] [G loss: 0.748852]
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8379 [D loss: 0.684261, acc.: 51.56%] [G loss: 0.752829]
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8380 [D loss: 0.681613, acc.: 50.98%] [G loss: 0.768930]
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8381 [D loss: 0.698178, acc.: 43.75%] [G loss: 0.745934]
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8382 [D loss: 0.688568, acc.: 49.80%] [G loss: 0.752374]
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8383 [D loss: 0.691311, acc.: 48.83%] [G loss: 0.744727]
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8384 [D loss: 0.701407, acc.: 47.85%] [G loss: 0.719146]
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8385 [D loss: 0.689472, acc.: 45.51%] [G loss: 0.719489]
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8386 [D loss: 0.696350, acc.: 46.48%] [G loss: 0.711301]
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8387 [D loss: 0.702224, acc.: 45.51%] [G loss: 0.714107]
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8388 [D loss: 0.702933, acc.: 45.12%] [G loss: 0.741378]
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8389 [D loss: 0.697947, acc.: 46.68%] [G loss: 0.756709]
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8390 [D loss: 0.691573, acc.: 44.73%] [G loss: 0.769746]
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8391 [D loss: 0.686546, acc.: 46.29%] [G loss: 0.793480]
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8392 [D loss: 0.694980, acc.: 43.16%] [G loss: 0.780304]
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8393 [D loss: 0.688860, acc.: 50.59%] [G loss: 0.756346]
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8394 [D loss: 0.687491, acc.: 51.17%] [G loss: 0.754210]
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8395 [D loss: 0.688915, acc.: 50.78%] [G loss: 0.728904]
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8396 [D loss: 0.681519, acc.: 48.05%] [G loss: 0.724754]
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8397 [D loss: 0.689647, acc.: 47.27%] [G loss: 0.764612]
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8398 [D loss: 0.675153, acc.: 51.56%] [G loss: 0.761892]
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8399 [D loss: 0.678613, acc.: 54.30%] [G loss: 0.756474]
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8400 [D loss: 0.687855, acc.: 47.85%] [G loss: 0.789284]
1/1 [==============================] - 0s 32ms/step
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8401 [D loss: 0.693985, acc.: 46.68%] [G loss: 0.741269]
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8402 [D loss: 0.682341, acc.: 49.41%] [G loss: 0.744066]
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8403 [D loss: 0.670440, acc.: 53.12%] [G loss: 0.766159]
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8404 [D loss: 0.704906, acc.: 41.99%] [G loss: 0.710821]
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8405 [D loss: 0.700083, acc.: 48.63%] [G loss: 0.714299]
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8406 [D loss: 0.687985, acc.: 50.20%] [G loss: 0.729520]
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8407 [D loss: 0.687007, acc.: 51.56%] [G loss: 0.735644]
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8408 [D loss: 0.694369, acc.: 48.24%] [G loss: 0.737563]
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8409 [D loss: 0.687018, acc.: 50.78%] [G loss: 0.747490]
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8410 [D loss: 0.687630, acc.: 44.14%] [G loss: 0.749903]
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8411 [D loss: 0.692454, acc.: 48.24%] [G loss: 0.735267]
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8412 [D loss: 0.693581, acc.: 44.53%] [G loss: 0.735091]
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8413 [D loss: 0.686969, acc.: 47.46%] [G loss: 0.729341]
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8414 [D loss: 0.696483, acc.: 43.75%] [G loss: 0.722202]
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8415 [D loss: 0.690922, acc.: 44.73%] [G loss: 0.723389]
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8416 [D loss: 0.688823, acc.: 49.41%] [G loss: 0.729750]
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8417 [D loss: 0.688640, acc.: 49.41%] [G loss: 0.735276]
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8418 [D loss: 0.688519, acc.: 50.98%] [G loss: 0.735393]
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8419 [D loss: 0.684728, acc.: 52.93%] [G loss: 0.741740]
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8420 [D loss: 0.681942, acc.: 50.20%] [G loss: 0.737848]
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8421 [D loss: 0.682322, acc.: 53.52%] [G loss: 0.737536]
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8422 [D loss: 0.674945, acc.: 50.78%] [G loss: 0.745826]
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8423 [D loss: 0.685466, acc.: 50.59%] [G loss: 0.732697]
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8424 [D loss: 0.673272, acc.: 52.15%] [G loss: 0.727322]
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8425 [D loss: 0.683992, acc.: 47.27%] [G loss: 0.725129]
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8426 [D loss: 0.670945, acc.: 50.59%] [G loss: 0.726310]
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8427 [D loss: 0.688846, acc.: 47.07%] [G loss: 0.729727]
8/8 [==============================] - 0s 4ms/step
8428 [D loss: 0.689654, acc.: 45.12%] [G loss: 0.731157]
8/8 [==============================] - 0s 4ms/step
8429 [D loss: 0.689688, acc.: 49.22%] [G loss: 0.732064]
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8430 [D loss: 0.691835, acc.: 47.66%] [G loss: 0.720633]
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8431 [D loss: 0.675969, acc.: 52.54%] [G loss: 0.729275]
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8432 [D loss: 0.678173, acc.: 46.48%] [G loss: 0.722366]
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8433 [D loss: 0.686878, acc.: 48.05%] [G loss: 0.723650]
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8434 [D loss: 0.694054, acc.: 45.51%] [G loss: 0.716750]
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8435 [D loss: 0.685344, acc.: 51.37%] [G loss: 0.732059]
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8436 [D loss: 0.677538, acc.: 47.66%] [G loss: 0.722869]
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8437 [D loss: 0.676558, acc.: 48.83%] [G loss: 0.730307]
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8438 [D loss: 0.686592, acc.: 47.66%] [G loss: 0.737307]
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8439 [D loss: 0.674919, acc.: 48.44%] [G loss: 0.742997]
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8440 [D loss: 0.687556, acc.: 48.83%] [G loss: 0.739476]
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8441 [D loss: 0.680428, acc.: 51.95%] [G loss: 0.736496]
8/8 [==============================] - 0s 4ms/step
8442 [D loss: 0.682213, acc.: 48.05%] [G loss: 0.733848]
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8443 [D loss: 0.689343, acc.: 46.68%] [G loss: 0.739166]
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8444 [D loss: 0.681698, acc.: 49.61%] [G loss: 0.748540]
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8445 [D loss: 0.679785, acc.: 47.85%] [G loss: 0.743455]
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8446 [D loss: 0.681434, acc.: 49.22%] [G loss: 0.727682]
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8447 [D loss: 0.688158, acc.: 48.44%] [G loss: 0.730495]
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8448 [D loss: 0.680987, acc.: 47.27%] [G loss: 0.725084]
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8449 [D loss: 0.689916, acc.: 48.24%] [G loss: 0.726118]
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8450 [D loss: 0.678475, acc.: 49.80%] [G loss: 0.724762]
1/1 [==============================] - 0s 36ms/step
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8451 [D loss: 0.684147, acc.: 47.66%] [G loss: 0.724265]
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8452 [D loss: 0.686133, acc.: 50.20%] [G loss: 0.740056]
8/8 [==============================] - 0s 4ms/step
8453 [D loss: 0.685172, acc.: 45.90%] [G loss: 0.727358]
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8454 [D loss: 0.692464, acc.: 46.09%] [G loss: 0.732529]
8/8 [==============================] - 0s 4ms/step
8455 [D loss: 0.686839, acc.: 50.20%] [G loss: 0.737744]
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8456 [D loss: 0.679262, acc.: 52.93%] [G loss: 0.729572]
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8457 [D loss: 0.675426, acc.: 48.83%] [G loss: 0.730966]
8/8 [==============================] - 0s 4ms/step
8458 [D loss: 0.681571, acc.: 50.20%] [G loss: 0.724149]
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8459 [D loss: 0.686106, acc.: 47.46%] [G loss: 0.740230]
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8460 [D loss: 0.666289, acc.: 51.37%] [G loss: 0.735509]
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8461 [D loss: 0.683561, acc.: 46.68%] [G loss: 0.731761]
8/8 [==============================] - 0s 4ms/step
8462 [D loss: 0.688656, acc.: 46.48%] [G loss: 0.730039]
8/8 [==============================] - 0s 4ms/step
8463 [D loss: 0.684807, acc.: 48.24%] [G loss: 0.739755]
8/8 [==============================] - 0s 4ms/step
8464 [D loss: 0.682788, acc.: 46.88%] [G loss: 0.751770]
8/8 [==============================] - 0s 4ms/step
8465 [D loss: 0.684817, acc.: 49.41%] [G loss: 0.734888]
8/8 [==============================] - 0s 4ms/step
8466 [D loss: 0.679481, acc.: 50.39%] [G loss: 0.734539]
8/8 [==============================] - 0s 4ms/step
8467 [D loss: 0.682617, acc.: 46.48%] [G loss: 0.739516]
8/8 [==============================] - 0s 4ms/step
8468 [D loss: 0.677158, acc.: 50.78%] [G loss: 0.733364]
8/8 [==============================] - 0s 4ms/step
8469 [D loss: 0.687613, acc.: 45.70%] [G loss: 0.732965]
8/8 [==============================] - 0s 4ms/step
8470 [D loss: 0.684316, acc.: 43.16%] [G loss: 0.736454]
8/8 [==============================] - 0s 4ms/step
8471 [D loss: 0.690724, acc.: 46.48%] [G loss: 0.740257]
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8472 [D loss: 0.686995, acc.: 49.41%] [G loss: 0.738920]
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8473 [D loss: 0.681795, acc.: 47.85%] [G loss: 0.733204]
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8474 [D loss: 0.685941, acc.: 46.48%] [G loss: 0.734670]
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8475 [D loss: 0.682027, acc.: 47.66%] [G loss: 0.736999]
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8476 [D loss: 0.675267, acc.: 51.37%] [G loss: 0.743104]
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8477 [D loss: 0.684153, acc.: 50.00%] [G loss: 0.746376]
8/8 [==============================] - 0s 4ms/step
8478 [D loss: 0.680598, acc.: 49.61%] [G loss: 0.735481]
8/8 [==============================] - 0s 4ms/step
8479 [D loss: 0.682564, acc.: 53.32%] [G loss: 0.753276]
8/8 [==============================] - 0s 4ms/step
8480 [D loss: 0.687428, acc.: 48.05%] [G loss: 0.747901]
8/8 [==============================] - 0s 4ms/step
8481 [D loss: 0.669148, acc.: 53.71%] [G loss: 0.743765]
8/8 [==============================] - 0s 4ms/step
8482 [D loss: 0.683500, acc.: 50.78%] [G loss: 0.742517]
8/8 [==============================] - 0s 4ms/step
8483 [D loss: 0.678786, acc.: 51.17%] [G loss: 0.738209]
8/8 [==============================] - 0s 4ms/step
8484 [D loss: 0.682295, acc.: 46.68%] [G loss: 0.725322]
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8485 [D loss: 0.667933, acc.: 50.00%] [G loss: 0.741362]
8/8 [==============================] - 0s 4ms/step
8486 [D loss: 0.687837, acc.: 45.51%] [G loss: 0.738550]
8/8 [==============================] - 0s 4ms/step
8487 [D loss: 0.669721, acc.: 51.76%] [G loss: 0.738872]
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8488 [D loss: 0.681023, acc.: 50.59%] [G loss: 0.745040]
8/8 [==============================] - 0s 4ms/step
8489 [D loss: 0.683551, acc.: 51.17%] [G loss: 0.731531]
8/8 [==============================] - 0s 4ms/step
8490 [D loss: 0.677443, acc.: 50.78%] [G loss: 0.729533]
8/8 [==============================] - 0s 4ms/step
8491 [D loss: 0.685489, acc.: 49.02%] [G loss: 0.729635]
8/8 [==============================] - 0s 4ms/step
8492 [D loss: 0.685803, acc.: 49.22%] [G loss: 0.730018]
8/8 [==============================] - 0s 4ms/step
8493 [D loss: 0.691077, acc.: 47.66%] [G loss: 0.731318]
8/8 [==============================] - 0s 4ms/step
8494 [D loss: 0.681296, acc.: 51.37%] [G loss: 0.737135]
8/8 [==============================] - 0s 4ms/step
8495 [D loss: 0.687702, acc.: 45.31%] [G loss: 0.732266]
8/8 [==============================] - 0s 4ms/step
8496 [D loss: 0.678403, acc.: 49.61%] [G loss: 0.735410]
8/8 [==============================] - 0s 4ms/step
8497 [D loss: 0.680586, acc.: 50.00%] [G loss: 0.736577]
8/8 [==============================] - 0s 4ms/step
8498 [D loss: 0.682196, acc.: 50.39%] [G loss: 0.734496]
8/8 [==============================] - 0s 4ms/step
8499 [D loss: 0.685400, acc.: 50.59%] [G loss: 0.742976]
8/8 [==============================] - 0s 4ms/step
8500 [D loss: 0.684091, acc.: 48.83%] [G loss: 0.726997]
1/1 [==============================] - 0s 35ms/step
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8501 [D loss: 0.688106, acc.: 48.44%] [G loss: 0.732572]
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8502 [D loss: 0.681684, acc.: 49.80%] [G loss: 0.735583]
8/8 [==============================] - 0s 4ms/step
8503 [D loss: 0.690142, acc.: 45.51%] [G loss: 0.743759]
8/8 [==============================] - 0s 4ms/step
8504 [D loss: 0.672528, acc.: 53.12%] [G loss: 0.732986]
8/8 [==============================] - 0s 4ms/step
8505 [D loss: 0.676164, acc.: 48.05%] [G loss: 0.732737]
8/8 [==============================] - 0s 4ms/step
8506 [D loss: 0.682183, acc.: 44.92%] [G loss: 0.727001]
8/8 [==============================] - 0s 4ms/step
8507 [D loss: 0.686843, acc.: 47.27%] [G loss: 0.743084]
8/8 [==============================] - 0s 4ms/step
8508 [D loss: 0.672894, acc.: 51.76%] [G loss: 0.724664]
8/8 [==============================] - 0s 4ms/step
8509 [D loss: 0.679340, acc.: 46.68%] [G loss: 0.738230]
8/8 [==============================] - 0s 4ms/step
8510 [D loss: 0.671139, acc.: 48.83%] [G loss: 0.730811]
8/8 [==============================] - 0s 4ms/step
8511 [D loss: 0.684105, acc.: 50.00%] [G loss: 0.740952]
8/8 [==============================] - 0s 4ms/step
8512 [D loss: 0.677705, acc.: 47.66%] [G loss: 0.740478]
8/8 [==============================] - 0s 4ms/step
8513 [D loss: 0.692459, acc.: 43.16%] [G loss: 0.727738]
8/8 [==============================] - 0s 4ms/step
8514 [D loss: 0.687593, acc.: 48.83%] [G loss: 0.737252]
8/8 [==============================] - 0s 4ms/step
8515 [D loss: 0.678125, acc.: 47.85%] [G loss: 0.741124]
8/8 [==============================] - 0s 4ms/step
8516 [D loss: 0.686901, acc.: 44.53%] [G loss: 0.728069]
8/8 [==============================] - 0s 4ms/step
8517 [D loss: 0.676694, acc.: 49.22%] [G loss: 0.734504]
8/8 [==============================] - 0s 4ms/step
8518 [D loss: 0.686801, acc.: 46.88%] [G loss: 0.726459]
8/8 [==============================] - 0s 4ms/step
8519 [D loss: 0.685149, acc.: 45.90%] [G loss: 0.734576]
8/8 [==============================] - 0s 4ms/step
8520 [D loss: 0.666845, acc.: 54.49%] [G loss: 0.739909]
8/8 [==============================] - 0s 4ms/step
8521 [D loss: 0.672585, acc.: 51.56%] [G loss: 0.742801]
8/8 [==============================] - 0s 4ms/step
8522 [D loss: 0.680001, acc.: 52.34%] [G loss: 0.735131]
8/8 [==============================] - 0s 4ms/step
8523 [D loss: 0.684649, acc.: 54.88%] [G loss: 0.734456]
8/8 [==============================] - 0s 4ms/step
8524 [D loss: 0.681642, acc.: 50.00%] [G loss: 0.730963]
8/8 [==============================] - 0s 4ms/step
8525 [D loss: 0.686306, acc.: 46.48%] [G loss: 0.730396]
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8526 [D loss: 0.673380, acc.: 55.66%] [G loss: 0.725046]
8/8 [==============================] - 0s 4ms/step
8527 [D loss: 0.677092, acc.: 51.37%] [G loss: 0.714117]
8/8 [==============================] - 0s 4ms/step
8528 [D loss: 0.687973, acc.: 46.68%] [G loss: 0.727857]
8/8 [==============================] - 0s 4ms/step
8529 [D loss: 0.682782, acc.: 43.55%] [G loss: 0.717259]
8/8 [==============================] - 0s 4ms/step
8530 [D loss: 0.675003, acc.: 48.44%] [G loss: 0.733227]
8/8 [==============================] - 0s 4ms/step
8531 [D loss: 0.681284, acc.: 43.55%] [G loss: 0.734734]
8/8 [==============================] - 0s 4ms/step
8532 [D loss: 0.666547, acc.: 51.95%] [G loss: 0.734066]
8/8 [==============================] - 0s 4ms/step
8533 [D loss: 0.679505, acc.: 50.98%] [G loss: 0.733501]
8/8 [==============================] - 0s 4ms/step
8534 [D loss: 0.687705, acc.: 50.20%] [G loss: 0.727721]
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8535 [D loss: 0.686400, acc.: 50.39%] [G loss: 0.732291]
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8536 [D loss: 0.685831, acc.: 50.78%] [G loss: 0.737623]
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8537 [D loss: 0.679283, acc.: 49.02%] [G loss: 0.736549]
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8538 [D loss: 0.672331, acc.: 51.37%] [G loss: 0.723794]
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8539 [D loss: 0.684243, acc.: 45.70%] [G loss: 0.722033]
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8540 [D loss: 0.682243, acc.: 49.02%] [G loss: 0.717355]
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8541 [D loss: 0.683159, acc.: 49.61%] [G loss: 0.725154]
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8542 [D loss: 0.682434, acc.: 47.27%] [G loss: 0.740120]
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8543 [D loss: 0.678183, acc.: 46.29%] [G loss: 0.728441]
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8544 [D loss: 0.677096, acc.: 50.98%] [G loss: 0.749975]
8/8 [==============================] - 0s 4ms/step
8545 [D loss: 0.680086, acc.: 50.98%] [G loss: 0.733443]
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8546 [D loss: 0.705448, acc.: 45.51%] [G loss: 0.707611]
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8547 [D loss: 0.716069, acc.: 48.05%] [G loss: 0.705263]
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8548 [D loss: 0.704385, acc.: 43.16%] [G loss: 0.713679]
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8549 [D loss: 0.711512, acc.: 45.31%] [G loss: 0.706798]
8/8 [==============================] - 0s 4ms/step
8550 [D loss: 0.693344, acc.: 44.92%] [G loss: 0.738503]
1/1 [==============================] - 0s 34ms/step
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8551 [D loss: 0.692627, acc.: 48.24%] [G loss: 0.742954]
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8552 [D loss: 0.697942, acc.: 47.27%] [G loss: 0.739014]
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8553 [D loss: 0.691315, acc.: 53.12%] [G loss: 0.746321]
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8554 [D loss: 0.686410, acc.: 50.98%] [G loss: 0.747953]
8/8 [==============================] - 0s 4ms/step
8555 [D loss: 0.693303, acc.: 48.63%] [G loss: 0.741128]
8/8 [==============================] - 0s 4ms/step
8556 [D loss: 0.686130, acc.: 49.80%] [G loss: 0.764489]
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8557 [D loss: 0.684547, acc.: 48.44%] [G loss: 0.765411]
8/8 [==============================] - 0s 4ms/step
8558 [D loss: 0.682762, acc.: 50.59%] [G loss: 0.776078]
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8559 [D loss: 0.695128, acc.: 50.39%] [G loss: 0.724376]
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8560 [D loss: 0.693197, acc.: 44.73%] [G loss: 0.726405]
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8561 [D loss: 0.692347, acc.: 47.07%] [G loss: 0.744101]
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8562 [D loss: 0.699602, acc.: 46.09%] [G loss: 0.741202]
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8563 [D loss: 0.700709, acc.: 50.00%] [G loss: 0.720687]
8/8 [==============================] - 0s 4ms/step
8564 [D loss: 0.709675, acc.: 42.19%] [G loss: 0.701935]
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8565 [D loss: 0.711349, acc.: 41.99%] [G loss: 0.701783]
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8566 [D loss: 0.704749, acc.: 45.70%] [G loss: 0.736593]
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8567 [D loss: 0.697029, acc.: 45.70%] [G loss: 0.756739]
8/8 [==============================] - 0s 4ms/step
8568 [D loss: 0.688366, acc.: 48.24%] [G loss: 0.733599]
8/8 [==============================] - 0s 4ms/step
8569 [D loss: 0.695870, acc.: 49.22%] [G loss: 0.735893]
8/8 [==============================] - 0s 4ms/step
8570 [D loss: 0.687655, acc.: 57.03%] [G loss: 0.753640]
8/8 [==============================] - 0s 4ms/step
8571 [D loss: 0.703350, acc.: 46.68%] [G loss: 0.719517]
8/8 [==============================] - 0s 4ms/step
8572 [D loss: 0.689752, acc.: 50.59%] [G loss: 0.731975]
8/8 [==============================] - 0s 4ms/step
8573 [D loss: 0.678698, acc.: 51.76%] [G loss: 0.766728]
8/8 [==============================] - 0s 4ms/step
8574 [D loss: 0.675015, acc.: 51.76%] [G loss: 0.770471]
8/8 [==============================] - 0s 4ms/step
8575 [D loss: 0.682841, acc.: 50.20%] [G loss: 0.772587]
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8576 [D loss: 0.691260, acc.: 47.46%] [G loss: 0.751658]
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8577 [D loss: 0.669405, acc.: 55.27%] [G loss: 0.760050]
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8578 [D loss: 0.687303, acc.: 52.54%] [G loss: 0.741676]
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8579 [D loss: 0.692017, acc.: 43.55%] [G loss: 0.728378]
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8580 [D loss: 0.686082, acc.: 48.83%] [G loss: 0.731584]
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8581 [D loss: 0.689861, acc.: 46.48%] [G loss: 0.726460]
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8582 [D loss: 0.691410, acc.: 49.41%] [G loss: 0.744944]
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8583 [D loss: 0.682608, acc.: 50.59%] [G loss: 0.749363]
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8584 [D loss: 0.682236, acc.: 48.24%] [G loss: 0.762069]
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8585 [D loss: 0.685107, acc.: 52.34%] [G loss: 0.756238]
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8586 [D loss: 0.676505, acc.: 50.78%] [G loss: 0.758646]
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8587 [D loss: 0.677131, acc.: 52.93%] [G loss: 0.759997]
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8588 [D loss: 0.683609, acc.: 51.56%] [G loss: 0.759032]
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8589 [D loss: 0.691474, acc.: 45.31%] [G loss: 0.737513]
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8590 [D loss: 0.695911, acc.: 44.34%] [G loss: 0.742611]
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8591 [D loss: 0.695539, acc.: 42.19%] [G loss: 0.742492]
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8592 [D loss: 0.693002, acc.: 41.80%] [G loss: 0.739345]
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8593 [D loss: 0.726704, acc.: 41.02%] [G loss: 0.708437]
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8594 [D loss: 0.710306, acc.: 48.44%] [G loss: 0.741841]
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8595 [D loss: 0.683662, acc.: 52.93%] [G loss: 0.766369]
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8596 [D loss: 0.683451, acc.: 51.17%] [G loss: 0.781035]
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8597 [D loss: 0.683091, acc.: 51.37%] [G loss: 0.766191]
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8598 [D loss: 0.696458, acc.: 49.61%] [G loss: 0.752450]
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8599 [D loss: 0.682863, acc.: 52.34%] [G loss: 0.734914]
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8600 [D loss: 0.680701, acc.: 52.93%] [G loss: 0.740381]
1/1 [==============================] - 0s 38ms/step
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8601 [D loss: 0.695168, acc.: 48.05%] [G loss: 0.721116]
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8602 [D loss: 0.685193, acc.: 49.61%] [G loss: 0.732042]
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8603 [D loss: 0.697251, acc.: 45.51%] [G loss: 0.745011]
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8604 [D loss: 0.690159, acc.: 49.41%] [G loss: 0.756225]
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8605 [D loss: 0.675301, acc.: 55.66%] [G loss: 0.768182]
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8606 [D loss: 0.677646, acc.: 55.66%] [G loss: 0.779973]
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8607 [D loss: 0.687072, acc.: 54.10%] [G loss: 0.762674]
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8608 [D loss: 0.681196, acc.: 50.00%] [G loss: 0.753440]
8/8 [==============================] - 0s 4ms/step
8609 [D loss: 0.688507, acc.: 53.52%] [G loss: 0.745932]
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8610 [D loss: 0.687567, acc.: 50.98%] [G loss: 0.737909]
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8611 [D loss: 0.692208, acc.: 44.92%] [G loss: 0.733255]
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8612 [D loss: 0.689890, acc.: 44.53%] [G loss: 0.735224]
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8613 [D loss: 0.701561, acc.: 41.21%] [G loss: 0.729799]
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8614 [D loss: 0.688248, acc.: 48.83%] [G loss: 0.748212]
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8615 [D loss: 0.689501, acc.: 45.31%] [G loss: 0.751754]
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8616 [D loss: 0.686397, acc.: 47.46%] [G loss: 0.766418]
8/8 [==============================] - 0s 4ms/step
8617 [D loss: 0.678615, acc.: 55.27%] [G loss: 0.761170]
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8618 [D loss: 0.672854, acc.: 54.10%] [G loss: 0.783846]
8/8 [==============================] - 0s 4ms/step
8619 [D loss: 0.685542, acc.: 47.66%] [G loss: 0.744188]
8/8 [==============================] - 0s 4ms/step
8620 [D loss: 0.680163, acc.: 49.80%] [G loss: 0.738696]
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8621 [D loss: 0.683408, acc.: 53.12%] [G loss: 0.738543]
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8622 [D loss: 0.684031, acc.: 55.27%] [G loss: 0.723978]
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8623 [D loss: 0.693790, acc.: 50.00%] [G loss: 0.718716]
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8624 [D loss: 0.702781, acc.: 44.34%] [G loss: 0.719017]
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8625 [D loss: 0.700980, acc.: 42.77%] [G loss: 0.704456]
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8626 [D loss: 0.700776, acc.: 44.73%] [G loss: 0.703533]
8/8 [==============================] - 0s 4ms/step
8627 [D loss: 0.704739, acc.: 42.38%] [G loss: 0.710356]
8/8 [==============================] - 0s 4ms/step
8628 [D loss: 0.704268, acc.: 44.92%] [G loss: 0.719978]
8/8 [==============================] - 0s 4ms/step
8629 [D loss: 0.700589, acc.: 46.68%] [G loss: 0.737343]
8/8 [==============================] - 0s 4ms/step
8630 [D loss: 0.689098, acc.: 47.07%] [G loss: 0.766229]
8/8 [==============================] - 0s 4ms/step
8631 [D loss: 0.692006, acc.: 51.37%] [G loss: 0.754245]
8/8 [==============================] - 0s 4ms/step
8632 [D loss: 0.688639, acc.: 52.15%] [G loss: 0.740732]
8/8 [==============================] - 0s 4ms/step
8633 [D loss: 0.686284, acc.: 54.30%] [G loss: 0.733068]
8/8 [==============================] - 0s 4ms/step
8634 [D loss: 0.687033, acc.: 55.47%] [G loss: 0.729692]
8/8 [==============================] - 0s 4ms/step
8635 [D loss: 0.699109, acc.: 51.37%] [G loss: 0.728284]
8/8 [==============================] - 0s 4ms/step
8636 [D loss: 0.695525, acc.: 49.80%] [G loss: 0.738114]
8/8 [==============================] - 0s 4ms/step
8637 [D loss: 0.698355, acc.: 49.02%] [G loss: 0.729826]
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8638 [D loss: 0.699883, acc.: 47.07%] [G loss: 0.734275]
8/8 [==============================] - 0s 4ms/step
8639 [D loss: 0.694300, acc.: 47.85%] [G loss: 0.730592]
8/8 [==============================] - 0s 4ms/step
8640 [D loss: 0.702390, acc.: 41.60%] [G loss: 0.726196]
8/8 [==============================] - 0s 4ms/step
8641 [D loss: 0.689971, acc.: 50.39%] [G loss: 0.730314]
8/8 [==============================] - 0s 4ms/step
8642 [D loss: 0.696746, acc.: 47.46%] [G loss: 0.730297]
8/8 [==============================] - 0s 4ms/step
8643 [D loss: 0.688620, acc.: 53.71%] [G loss: 0.743160]
8/8 [==============================] - 0s 4ms/step
8644 [D loss: 0.688612, acc.: 50.59%] [G loss: 0.751305]
8/8 [==============================] - 0s 4ms/step
8645 [D loss: 0.686347, acc.: 55.66%] [G loss: 0.756601]
8/8 [==============================] - 0s 4ms/step
8646 [D loss: 0.683602, acc.: 55.27%] [G loss: 0.746718]
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8647 [D loss: 0.692489, acc.: 48.24%] [G loss: 0.749194]
8/8 [==============================] - 0s 4ms/step
8648 [D loss: 0.691644, acc.: 46.29%] [G loss: 0.732495]
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8649 [D loss: 0.683687, acc.: 49.41%] [G loss: 0.729658]
8/8 [==============================] - 0s 4ms/step
8650 [D loss: 0.696506, acc.: 43.95%] [G loss: 0.727588]
1/1 [==============================] - 0s 35ms/step
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8651 [D loss: 0.696225, acc.: 42.58%] [G loss: 0.728365]
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8652 [D loss: 0.689355, acc.: 47.27%] [G loss: 0.727648]
8/8 [==============================] - 0s 4ms/step
8653 [D loss: 0.696260, acc.: 42.97%] [G loss: 0.731919]
8/8 [==============================] - 0s 4ms/step
8654 [D loss: 0.703040, acc.: 42.77%] [G loss: 0.721389]
8/8 [==============================] - 0s 4ms/step
8655 [D loss: 0.695791, acc.: 47.46%] [G loss: 0.726967]
8/8 [==============================] - 0s 4ms/step
8656 [D loss: 0.696584, acc.: 51.56%] [G loss: 0.732080]
8/8 [==============================] - 0s 4ms/step
8657 [D loss: 0.700016, acc.: 50.20%] [G loss: 0.730777]
8/8 [==============================] - 0s 4ms/step
8658 [D loss: 0.688106, acc.: 56.64%] [G loss: 0.746045]
8/8 [==============================] - 0s 4ms/step
8659 [D loss: 0.699674, acc.: 52.15%] [G loss: 0.737797]
8/8 [==============================] - 0s 4ms/step
8660 [D loss: 0.697711, acc.: 52.93%] [G loss: 0.737613]
8/8 [==============================] - 0s 4ms/step
8661 [D loss: 0.696252, acc.: 54.10%] [G loss: 0.730249]
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8662 [D loss: 0.691759, acc.: 51.95%] [G loss: 0.723085]
8/8 [==============================] - 0s 4ms/step
8663 [D loss: 0.699070, acc.: 48.24%] [G loss: 0.711375]
8/8 [==============================] - 0s 4ms/step
8664 [D loss: 0.703339, acc.: 45.70%] [G loss: 0.704739]
8/8 [==============================] - 0s 4ms/step
8665 [D loss: 0.701086, acc.: 46.48%] [G loss: 0.706167]
8/8 [==============================] - 0s 4ms/step
8666 [D loss: 0.706657, acc.: 44.53%] [G loss: 0.729161]
8/8 [==============================] - 0s 4ms/step
8667 [D loss: 0.698246, acc.: 47.07%] [G loss: 0.728995]
8/8 [==============================] - 0s 4ms/step
8668 [D loss: 0.698317, acc.: 45.51%] [G loss: 0.734965]
8/8 [==============================] - 0s 4ms/step
8669 [D loss: 0.688381, acc.: 54.10%] [G loss: 0.735800]
8/8 [==============================] - 0s 5ms/step
8670 [D loss: 0.693986, acc.: 49.80%] [G loss: 0.726394]
8/8 [==============================] - 0s 4ms/step
8671 [D loss: 0.695920, acc.: 45.51%] [G loss: 0.713694]
8/8 [==============================] - 0s 4ms/step
8672 [D loss: 0.695239, acc.: 45.70%] [G loss: 0.725488]
8/8 [==============================] - 0s 4ms/step
8673 [D loss: 0.687402, acc.: 49.80%] [G loss: 0.753560]
8/8 [==============================] - 0s 4ms/step
8674 [D loss: 0.695808, acc.: 47.66%] [G loss: 0.735624]
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8675 [D loss: 0.697620, acc.: 42.77%] [G loss: 0.743948]
8/8 [==============================] - 0s 4ms/step
8676 [D loss: 0.697760, acc.: 44.34%] [G loss: 0.743623]
8/8 [==============================] - 0s 4ms/step
8677 [D loss: 0.699020, acc.: 46.48%] [G loss: 0.737080]
8/8 [==============================] - 0s 4ms/step
8678 [D loss: 0.690532, acc.: 47.46%] [G loss: 0.743866]
8/8 [==============================] - 0s 4ms/step
8679 [D loss: 0.691930, acc.: 49.02%] [G loss: 0.740094]
8/8 [==============================] - 0s 4ms/step
8680 [D loss: 0.689736, acc.: 52.34%] [G loss: 0.739171]
8/8 [==============================] - 0s 4ms/step
8681 [D loss: 0.678366, acc.: 50.98%] [G loss: 0.773188]
8/8 [==============================] - 0s 4ms/step
8682 [D loss: 0.690502, acc.: 49.80%] [G loss: 0.777605]
8/8 [==============================] - 0s 4ms/step
8683 [D loss: 0.682360, acc.: 50.98%] [G loss: 0.789369]
8/8 [==============================] - 0s 4ms/step
8684 [D loss: 0.680204, acc.: 52.93%] [G loss: 0.801663]
8/8 [==============================] - 0s 4ms/step
8685 [D loss: 0.687010, acc.: 50.00%] [G loss: 0.795183]
8/8 [==============================] - 0s 4ms/step
8686 [D loss: 0.683143, acc.: 55.08%] [G loss: 0.756266]
8/8 [==============================] - 0s 4ms/step
8687 [D loss: 0.685470, acc.: 57.03%] [G loss: 0.739783]
8/8 [==============================] - 0s 4ms/step
8688 [D loss: 0.691904, acc.: 52.34%] [G loss: 0.719472]
8/8 [==============================] - 0s 4ms/step
8689 [D loss: 0.691905, acc.: 47.27%] [G loss: 0.715874]
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8690 [D loss: 0.690515, acc.: 49.61%] [G loss: 0.736218]
8/8 [==============================] - 0s 4ms/step
8691 [D loss: 0.695138, acc.: 48.83%] [G loss: 0.762079]
8/8 [==============================] - 0s 4ms/step
8692 [D loss: 0.682385, acc.: 48.44%] [G loss: 0.787677]
8/8 [==============================] - 0s 4ms/step
8693 [D loss: 0.687778, acc.: 48.83%] [G loss: 0.759747]
8/8 [==============================] - 0s 4ms/step
8694 [D loss: 0.694224, acc.: 45.12%] [G loss: 0.746777]
8/8 [==============================] - 0s 4ms/step
8695 [D loss: 0.693397, acc.: 47.85%] [G loss: 0.777629]
8/8 [==============================] - 0s 4ms/step
8696 [D loss: 0.681658, acc.: 44.14%] [G loss: 0.725929]
8/8 [==============================] - 0s 4ms/step
8697 [D loss: 0.696668, acc.: 39.65%] [G loss: 0.731073]
8/8 [==============================] - 0s 4ms/step
8698 [D loss: 0.673834, acc.: 49.41%] [G loss: 0.737578]
8/8 [==============================] - 0s 4ms/step
8699 [D loss: 0.688950, acc.: 49.80%] [G loss: 0.752905]
8/8 [==============================] - 0s 4ms/step
8700 [D loss: 0.687796, acc.: 50.00%] [G loss: 0.752322]
1/1 [==============================] - 0s 31ms/step
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8701 [D loss: 0.684719, acc.: 51.37%] [G loss: 0.747701]
8/8 [==============================] - 0s 4ms/step
8702 [D loss: 0.688868, acc.: 50.39%] [G loss: 0.751147]
8/8 [==============================] - 0s 4ms/step
8703 [D loss: 0.679446, acc.: 50.39%] [G loss: 0.730637]
8/8 [==============================] - 0s 4ms/step
8704 [D loss: 0.688848, acc.: 49.80%] [G loss: 0.728075]
8/8 [==============================] - 0s 4ms/step
8705 [D loss: 0.684657, acc.: 49.41%] [G loss: 0.720272]
8/8 [==============================] - 0s 4ms/step
8706 [D loss: 0.689775, acc.: 44.92%] [G loss: 0.722445]
8/8 [==============================] - 0s 4ms/step
8707 [D loss: 0.682604, acc.: 49.22%] [G loss: 0.724916]
8/8 [==============================] - 0s 4ms/step
8708 [D loss: 0.683777, acc.: 49.02%] [G loss: 0.723234]
8/8 [==============================] - 0s 4ms/step
8709 [D loss: 0.692005, acc.: 49.41%] [G loss: 0.726950]
8/8 [==============================] - 0s 4ms/step
8710 [D loss: 0.694045, acc.: 43.75%] [G loss: 0.730086]
8/8 [==============================] - 0s 4ms/step
8711 [D loss: 0.677517, acc.: 51.37%] [G loss: 0.729993]
8/8 [==============================] - 0s 4ms/step
8712 [D loss: 0.683353, acc.: 49.80%] [G loss: 0.737635]
8/8 [==============================] - 0s 4ms/step
8713 [D loss: 0.678256, acc.: 49.22%] [G loss: 0.747380]
8/8 [==============================] - 0s 4ms/step
8714 [D loss: 0.683761, acc.: 50.00%] [G loss: 0.749874]
8/8 [==============================] - 0s 4ms/step
8715 [D loss: 0.687689, acc.: 47.46%] [G loss: 0.742869]
8/8 [==============================] - 0s 4ms/step
8716 [D loss: 0.686791, acc.: 50.20%] [G loss: 0.743816]
8/8 [==============================] - 0s 4ms/step
8717 [D loss: 0.690159, acc.: 47.85%] [G loss: 0.741952]
8/8 [==============================] - 0s 4ms/step
8718 [D loss: 0.676637, acc.: 52.54%] [G loss: 0.747430]
8/8 [==============================] - 0s 4ms/step
8719 [D loss: 0.678275, acc.: 50.39%] [G loss: 0.750420]
8/8 [==============================] - 0s 4ms/step
8720 [D loss: 0.687872, acc.: 46.88%] [G loss: 0.734339]
8/8 [==============================] - 0s 4ms/step
8721 [D loss: 0.679704, acc.: 48.83%] [G loss: 0.741877]
8/8 [==============================] - 0s 4ms/step
8722 [D loss: 0.670392, acc.: 51.37%] [G loss: 0.728793]
8/8 [==============================] - 0s 4ms/step
8723 [D loss: 0.681224, acc.: 50.00%] [G loss: 0.742522]
8/8 [==============================] - 0s 4ms/step
8724 [D loss: 0.686519, acc.: 50.78%] [G loss: 0.748304]
8/8 [==============================] - 0s 4ms/step
8725 [D loss: 0.688691, acc.: 52.15%] [G loss: 0.740099]
8/8 [==============================] - 0s 4ms/step
8726 [D loss: 0.680909, acc.: 52.34%] [G loss: 0.747242]
8/8 [==============================] - 0s 4ms/step
8727 [D loss: 0.678593, acc.: 51.76%] [G loss: 0.741801]
8/8 [==============================] - 0s 4ms/step
8728 [D loss: 0.669426, acc.: 51.17%] [G loss: 0.742304]
8/8 [==============================] - 0s 4ms/step
8729 [D loss: 0.673900, acc.: 51.17%] [G loss: 0.729740]
8/8 [==============================] - 0s 4ms/step
8730 [D loss: 0.691517, acc.: 42.77%] [G loss: 0.767495]
8/8 [==============================] - 0s 4ms/step
8731 [D loss: 0.688493, acc.: 45.51%] [G loss: 0.734554]
8/8 [==============================] - 0s 4ms/step
8732 [D loss: 0.686070, acc.: 48.63%] [G loss: 0.726316]
8/8 [==============================] - 0s 4ms/step
8733 [D loss: 0.661474, acc.: 55.08%] [G loss: 0.730576]
8/8 [==============================] - 0s 4ms/step
8734 [D loss: 0.691957, acc.: 41.80%] [G loss: 0.722305]
8/8 [==============================] - 0s 4ms/step
8735 [D loss: 0.686821, acc.: 46.48%] [G loss: 0.724100]
8/8 [==============================] - 0s 4ms/step
8736 [D loss: 0.672426, acc.: 48.63%] [G loss: 0.728339]
8/8 [==============================] - 0s 4ms/step
8737 [D loss: 0.689541, acc.: 49.02%] [G loss: 0.742037]
8/8 [==============================] - 0s 4ms/step
8738 [D loss: 0.688161, acc.: 47.27%] [G loss: 0.740821]
8/8 [==============================] - 0s 4ms/step
8739 [D loss: 0.677508, acc.: 52.93%] [G loss: 0.731167]
8/8 [==============================] - 0s 4ms/step
8740 [D loss: 0.684796, acc.: 51.95%] [G loss: 0.748807]
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8741 [D loss: 0.682012, acc.: 48.44%] [G loss: 0.739424]
8/8 [==============================] - 0s 4ms/step
8742 [D loss: 0.690740, acc.: 50.98%] [G loss: 0.738974]
8/8 [==============================] - 0s 4ms/step
8743 [D loss: 0.679850, acc.: 51.17%] [G loss: 0.741134]
8/8 [==============================] - 0s 5ms/step
8744 [D loss: 0.682223, acc.: 47.07%] [G loss: 0.733594]
8/8 [==============================] - 0s 4ms/step
8745 [D loss: 0.677485, acc.: 48.83%] [G loss: 0.731767]
8/8 [==============================] - 0s 4ms/step
8746 [D loss: 0.688042, acc.: 48.44%] [G loss: 0.740319]
8/8 [==============================] - 0s 4ms/step
8747 [D loss: 0.693216, acc.: 45.90%] [G loss: 0.739087]
8/8 [==============================] - 0s 4ms/step
8748 [D loss: 0.676781, acc.: 49.41%] [G loss: 0.745041]
8/8 [==============================] - 0s 4ms/step
8749 [D loss: 0.690544, acc.: 48.63%] [G loss: 0.737003]
8/8 [==============================] - 0s 4ms/step
8750 [D loss: 0.678502, acc.: 51.37%] [G loss: 0.736945]
1/1 [==============================] - 0s 32ms/step
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8751 [D loss: 0.678045, acc.: 52.34%] [G loss: 0.752044]
8/8 [==============================] - 0s 5ms/step
8752 [D loss: 0.693740, acc.: 43.55%] [G loss: 0.732249]
8/8 [==============================] - 0s 5ms/step
8753 [D loss: 0.669839, acc.: 48.83%] [G loss: 0.724498]
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8754 [D loss: 0.681771, acc.: 49.80%] [G loss: 0.728979]
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8755 [D loss: 0.693420, acc.: 46.68%] [G loss: 0.727708]
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8756 [D loss: 0.685050, acc.: 51.17%] [G loss: 0.742463]
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8757 [D loss: 0.677294, acc.: 51.17%] [G loss: 0.734066]
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8758 [D loss: 0.675661, acc.: 49.02%] [G loss: 0.736168]
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8759 [D loss: 0.683570, acc.: 48.63%] [G loss: 0.730677]
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8760 [D loss: 0.681797, acc.: 55.86%] [G loss: 0.742085]
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8761 [D loss: 0.684264, acc.: 49.02%] [G loss: 0.736511]
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8762 [D loss: 0.687947, acc.: 51.37%] [G loss: 0.731201]
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8763 [D loss: 0.681832, acc.: 49.02%] [G loss: 0.743939]
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8764 [D loss: 0.669707, acc.: 52.15%] [G loss: 0.736552]
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8765 [D loss: 0.679022, acc.: 49.41%] [G loss: 0.737432]
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8766 [D loss: 0.676747, acc.: 47.66%] [G loss: 0.735665]
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8767 [D loss: 0.678488, acc.: 48.24%] [G loss: 0.730767]
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8768 [D loss: 0.677757, acc.: 46.68%] [G loss: 0.736097]
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8769 [D loss: 0.690688, acc.: 44.53%] [G loss: 0.730771]
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8770 [D loss: 0.679566, acc.: 48.83%] [G loss: 0.738468]
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8771 [D loss: 0.675945, acc.: 50.59%] [G loss: 0.733552]
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8772 [D loss: 0.682971, acc.: 45.51%] [G loss: 0.727382]
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8773 [D loss: 0.684340, acc.: 46.29%] [G loss: 0.732058]
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8774 [D loss: 0.678378, acc.: 55.08%] [G loss: 0.737009]
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8775 [D loss: 0.686529, acc.: 47.66%] [G loss: 0.752373]
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8776 [D loss: 0.681259, acc.: 50.00%] [G loss: 0.755047]
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8777 [D loss: 0.676808, acc.: 51.17%] [G loss: 0.741261]
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8778 [D loss: 0.674418, acc.: 49.80%] [G loss: 0.739712]
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8779 [D loss: 0.674616, acc.: 46.29%] [G loss: 0.730739]
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8780 [D loss: 0.680649, acc.: 48.05%] [G loss: 0.728288]
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8781 [D loss: 0.679996, acc.: 48.44%] [G loss: 0.724569]
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8782 [D loss: 0.679670, acc.: 51.56%] [G loss: 0.718710]
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8783 [D loss: 0.688336, acc.: 48.44%] [G loss: 0.726770]
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8784 [D loss: 0.697616, acc.: 46.09%] [G loss: 0.730537]
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8785 [D loss: 0.690920, acc.: 46.48%] [G loss: 0.734128]
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8786 [D loss: 0.733937, acc.: 44.34%] [G loss: 0.733341]
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8787 [D loss: 0.691491, acc.: 43.95%] [G loss: 0.754559]
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8788 [D loss: 0.685357, acc.: 50.39%] [G loss: 0.748860]
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8789 [D loss: 0.688219, acc.: 48.63%] [G loss: 0.765866]
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8790 [D loss: 0.694289, acc.: 46.88%] [G loss: 0.757097]
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8791 [D loss: 0.687824, acc.: 50.59%] [G loss: 0.732659]
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8792 [D loss: 0.693256, acc.: 43.75%] [G loss: 0.724117]
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8793 [D loss: 0.696181, acc.: 45.51%] [G loss: 0.747213]
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8794 [D loss: 0.696691, acc.: 45.90%] [G loss: 0.726116]
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8795 [D loss: 0.694693, acc.: 49.61%] [G loss: 0.722460]
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8796 [D loss: 0.698329, acc.: 43.95%] [G loss: 0.729111]
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8797 [D loss: 0.695838, acc.: 48.44%] [G loss: 0.746678]
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8798 [D loss: 0.691107, acc.: 53.52%] [G loss: 0.745991]
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8799 [D loss: 0.689876, acc.: 52.73%] [G loss: 0.728983]
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8800 [D loss: 0.690852, acc.: 51.56%] [G loss: 0.722647]
1/1 [==============================] - 0s 34ms/step
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8801 [D loss: 0.690431, acc.: 48.63%] [G loss: 0.717720]
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8802 [D loss: 0.706482, acc.: 42.77%] [G loss: 0.723064]
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8803 [D loss: 0.696385, acc.: 48.44%] [G loss: 0.736322]
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8804 [D loss: 0.696614, acc.: 45.51%] [G loss: 0.749714]
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8805 [D loss: 0.690626, acc.: 48.24%] [G loss: 0.790246]
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8806 [D loss: 0.689894, acc.: 50.00%] [G loss: 0.755714]
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8807 [D loss: 0.698738, acc.: 44.92%] [G loss: 0.751153]
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8808 [D loss: 0.691344, acc.: 49.41%] [G loss: 0.743134]
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8809 [D loss: 0.689642, acc.: 52.15%] [G loss: 0.752294]
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8810 [D loss: 0.693845, acc.: 50.59%] [G loss: 0.727776]
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8811 [D loss: 0.698625, acc.: 44.14%] [G loss: 0.726681]
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8812 [D loss: 0.693102, acc.: 48.83%] [G loss: 0.735355]
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8813 [D loss: 0.689264, acc.: 54.10%] [G loss: 0.749295]
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8814 [D loss: 0.689264, acc.: 52.73%] [G loss: 0.741730]
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8815 [D loss: 0.694713, acc.: 49.61%] [G loss: 0.749681]
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8816 [D loss: 0.694488, acc.: 47.85%] [G loss: 0.735629]
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8817 [D loss: 0.690713, acc.: 49.02%] [G loss: 0.749280]
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8818 [D loss: 0.692613, acc.: 50.20%] [G loss: 0.735334]
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8819 [D loss: 0.692955, acc.: 47.07%] [G loss: 0.726049]
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8820 [D loss: 0.695822, acc.: 50.59%] [G loss: 0.727474]
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8821 [D loss: 0.694076, acc.: 46.88%] [G loss: 0.739226]
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8822 [D loss: 0.700803, acc.: 47.07%] [G loss: 0.743734]
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8823 [D loss: 0.700304, acc.: 48.05%] [G loss: 0.738456]
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8824 [D loss: 0.693349, acc.: 49.22%] [G loss: 0.745575]
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8825 [D loss: 0.694269, acc.: 50.20%] [G loss: 0.736815]
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8826 [D loss: 0.678246, acc.: 55.86%] [G loss: 0.750181]
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8827 [D loss: 0.684588, acc.: 50.78%] [G loss: 0.725912]
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8828 [D loss: 0.688621, acc.: 48.24%] [G loss: 0.736873]
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8829 [D loss: 0.692103, acc.: 47.46%] [G loss: 0.740709]
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8830 [D loss: 0.674948, acc.: 53.52%] [G loss: 0.775335]
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8831 [D loss: 0.682742, acc.: 52.54%] [G loss: 0.764590]
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8832 [D loss: 0.686043, acc.: 48.83%] [G loss: 0.754348]
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8833 [D loss: 0.681456, acc.: 54.49%] [G loss: 0.776106]
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8834 [D loss: 0.684436, acc.: 52.34%] [G loss: 0.742395]
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8835 [D loss: 0.695046, acc.: 46.29%] [G loss: 0.721099]
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8836 [D loss: 0.694697, acc.: 50.98%] [G loss: 0.709866]
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8837 [D loss: 0.679428, acc.: 48.05%] [G loss: 0.729283]
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8838 [D loss: 0.690488, acc.: 48.83%] [G loss: 0.729945]
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8839 [D loss: 0.688583, acc.: 49.61%] [G loss: 0.724211]
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8840 [D loss: 0.684879, acc.: 49.61%] [G loss: 0.731644]
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8841 [D loss: 0.687974, acc.: 46.88%] [G loss: 0.733559]
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8842 [D loss: 0.682508, acc.: 50.98%] [G loss: 0.741305]
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8843 [D loss: 0.676751, acc.: 50.78%] [G loss: 0.731172]
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8844 [D loss: 0.683765, acc.: 47.46%] [G loss: 0.727812]
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8845 [D loss: 0.675927, acc.: 51.76%] [G loss: 0.726561]
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8846 [D loss: 0.682571, acc.: 51.56%] [G loss: 0.719468]
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8847 [D loss: 0.691740, acc.: 47.66%] [G loss: 0.715276]
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8848 [D loss: 0.696475, acc.: 43.95%] [G loss: 0.725135]
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8849 [D loss: 0.696000, acc.: 46.09%] [G loss: 0.726501]
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8850 [D loss: 0.691368, acc.: 48.83%] [G loss: 0.730997]
1/1 [==============================] - 0s 31ms/step
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8851 [D loss: 0.688365, acc.: 49.80%] [G loss: 0.729867]
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8852 [D loss: 0.687743, acc.: 47.07%] [G loss: 0.726259]
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8853 [D loss: 0.696457, acc.: 45.51%] [G loss: 0.724594]
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8854 [D loss: 0.686199, acc.: 43.95%] [G loss: 0.742738]
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8855 [D loss: 0.683728, acc.: 51.37%] [G loss: 0.731761]
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8856 [D loss: 0.685044, acc.: 43.95%] [G loss: 0.734785]
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8857 [D loss: 0.683689, acc.: 48.05%] [G loss: 0.727207]
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8858 [D loss: 0.691442, acc.: 49.22%] [G loss: 0.725094]
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8859 [D loss: 0.723822, acc.: 43.16%] [G loss: 0.706681]
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8860 [D loss: 0.701965, acc.: 53.52%] [G loss: 0.747258]
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8861 [D loss: 0.693471, acc.: 49.80%] [G loss: 0.741039]
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8862 [D loss: 0.699126, acc.: 46.68%] [G loss: 0.765673]
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8863 [D loss: 0.692970, acc.: 51.56%] [G loss: 0.773900]
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8864 [D loss: 0.691978, acc.: 46.68%] [G loss: 0.760698]
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8865 [D loss: 0.686554, acc.: 54.30%] [G loss: 0.749794]
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8866 [D loss: 0.691987, acc.: 47.85%] [G loss: 0.745911]
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8867 [D loss: 0.693347, acc.: 50.20%] [G loss: 0.732991]
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8868 [D loss: 0.694320, acc.: 46.29%] [G loss: 0.731160]
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8869 [D loss: 0.691221, acc.: 50.00%] [G loss: 0.732724]
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8870 [D loss: 0.694841, acc.: 46.88%] [G loss: 0.736134]
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8871 [D loss: 0.687156, acc.: 53.32%] [G loss: 0.748470]
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8872 [D loss: 0.688085, acc.: 52.34%] [G loss: 0.758063]
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8873 [D loss: 0.686058, acc.: 53.32%] [G loss: 0.747452]
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8874 [D loss: 0.679746, acc.: 56.25%] [G loss: 0.780019]
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8875 [D loss: 0.683901, acc.: 57.03%] [G loss: 0.780143]
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8876 [D loss: 0.682044, acc.: 52.93%] [G loss: 0.756025]
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8877 [D loss: 0.670136, acc.: 57.42%] [G loss: 0.767831]
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8878 [D loss: 0.673016, acc.: 53.32%] [G loss: 0.768495]
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8879 [D loss: 0.683082, acc.: 52.15%] [G loss: 0.794153]
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8880 [D loss: 0.678871, acc.: 53.32%] [G loss: 0.805919]
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8881 [D loss: 0.689209, acc.: 47.85%] [G loss: 0.780131]
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8882 [D loss: 0.683513, acc.: 51.95%] [G loss: 0.779023]
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8883 [D loss: 0.684697, acc.: 52.34%] [G loss: 0.759616]
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8884 [D loss: 0.689039, acc.: 50.39%] [G loss: 0.732123]
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8885 [D loss: 0.713161, acc.: 45.31%] [G loss: 0.735375]
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8886 [D loss: 0.691296, acc.: 48.24%] [G loss: 0.761804]
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8887 [D loss: 0.701044, acc.: 46.48%] [G loss: 0.747732]
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8888 [D loss: 0.698279, acc.: 43.36%] [G loss: 0.733384]
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8889 [D loss: 0.687161, acc.: 54.88%] [G loss: 0.738244]
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8890 [D loss: 0.690641, acc.: 51.37%] [G loss: 0.725070]
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8891 [D loss: 0.695444, acc.: 48.44%] [G loss: 0.714754]
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8892 [D loss: 0.689636, acc.: 51.76%] [G loss: 0.723162]
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8893 [D loss: 0.695053, acc.: 49.80%] [G loss: 0.709692]
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8894 [D loss: 0.684150, acc.: 53.91%] [G loss: 0.731768]
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8895 [D loss: 0.699498, acc.: 45.70%] [G loss: 0.720105]
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8896 [D loss: 0.704076, acc.: 44.92%] [G loss: 0.717478]
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8897 [D loss: 0.702070, acc.: 44.92%] [G loss: 0.718260]
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8898 [D loss: 0.696036, acc.: 47.46%] [G loss: 0.721604]
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8899 [D loss: 0.684739, acc.: 52.93%] [G loss: 0.754548]
8/8 [==============================] - 0s 4ms/step
8900 [D loss: 0.692671, acc.: 50.78%] [G loss: 0.733390]
1/1 [==============================] - 0s 34ms/step
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8901 [D loss: 0.694721, acc.: 50.00%] [G loss: 0.726669]
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8902 [D loss: 0.703106, acc.: 46.68%] [G loss: 0.718604]
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8903 [D loss: 0.701994, acc.: 44.73%] [G loss: 0.715936]
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8904 [D loss: 0.694138, acc.: 48.63%] [G loss: 0.723953]
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8905 [D loss: 0.694595, acc.: 51.17%] [G loss: 0.744277]
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8906 [D loss: 0.691042, acc.: 51.17%] [G loss: 0.738775]
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8907 [D loss: 0.686976, acc.: 55.27%] [G loss: 0.721706]
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8908 [D loss: 0.690309, acc.: 53.32%] [G loss: 0.732303]
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8909 [D loss: 0.695723, acc.: 49.22%] [G loss: 0.726578]
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8910 [D loss: 0.690829, acc.: 53.32%] [G loss: 0.715329]
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8911 [D loss: 0.690932, acc.: 52.34%] [G loss: 0.733221]
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8912 [D loss: 0.698783, acc.: 51.37%] [G loss: 0.722915]
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8913 [D loss: 0.699728, acc.: 48.05%] [G loss: 0.713600]
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8914 [D loss: 0.698854, acc.: 47.07%] [G loss: 0.718353]
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8915 [D loss: 0.693536, acc.: 51.37%] [G loss: 0.723705]
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8916 [D loss: 0.695311, acc.: 49.41%] [G loss: 0.736270]
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8917 [D loss: 0.697230, acc.: 43.16%] [G loss: 0.735714]
8/8 [==============================] - 0s 4ms/step
8918 [D loss: 0.685871, acc.: 49.41%] [G loss: 0.749784]
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8919 [D loss: 0.683589, acc.: 50.98%] [G loss: 0.751807]
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8920 [D loss: 0.682271, acc.: 50.39%] [G loss: 0.760958]
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8921 [D loss: 0.692205, acc.: 49.61%] [G loss: 0.757406]
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8922 [D loss: 0.685083, acc.: 51.76%] [G loss: 0.752011]
8/8 [==============================] - 0s 4ms/step
8923 [D loss: 0.693241, acc.: 49.80%] [G loss: 0.731878]
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8924 [D loss: 0.686474, acc.: 50.59%] [G loss: 0.730132]
8/8 [==============================] - 0s 4ms/step
8925 [D loss: 0.689933, acc.: 48.05%] [G loss: 0.736993]
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8926 [D loss: 0.684354, acc.: 55.27%] [G loss: 0.717182]
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8927 [D loss: 0.688654, acc.: 49.61%] [G loss: 0.724112]
8/8 [==============================] - 0s 4ms/step
8928 [D loss: 0.687726, acc.: 52.93%] [G loss: 0.718189]
8/8 [==============================] - 0s 4ms/step
8929 [D loss: 0.694157, acc.: 46.88%] [G loss: 0.709656]
8/8 [==============================] - 0s 5ms/step
8930 [D loss: 0.696894, acc.: 44.34%] [G loss: 0.717264]
8/8 [==============================] - 0s 4ms/step
8931 [D loss: 0.693445, acc.: 47.85%] [G loss: 0.716331]
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8932 [D loss: 0.690354, acc.: 50.20%] [G loss: 0.725197]
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8933 [D loss: 0.694842, acc.: 47.66%] [G loss: 0.719829]
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8934 [D loss: 0.694999, acc.: 46.48%] [G loss: 0.729194]
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8935 [D loss: 0.692175, acc.: 48.63%] [G loss: 0.721271]
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8936 [D loss: 0.699941, acc.: 42.77%] [G loss: 0.726951]
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8937 [D loss: 0.690890, acc.: 49.02%] [G loss: 0.730653]
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8938 [D loss: 0.696829, acc.: 46.88%] [G loss: 0.723677]
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8939 [D loss: 0.685364, acc.: 49.61%] [G loss: 0.731500]
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8940 [D loss: 0.690460, acc.: 50.59%] [G loss: 0.742047]
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8941 [D loss: 0.694802, acc.: 47.85%] [G loss: 0.728270]
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8942 [D loss: 0.688353, acc.: 50.59%] [G loss: 0.752179]
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8943 [D loss: 0.696773, acc.: 45.12%] [G loss: 0.736615]
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8944 [D loss: 0.691893, acc.: 49.80%] [G loss: 0.736940]
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8945 [D loss: 0.687945, acc.: 51.95%] [G loss: 0.747288]
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8946 [D loss: 0.687046, acc.: 50.20%] [G loss: 0.751409]
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8947 [D loss: 0.687066, acc.: 51.17%] [G loss: 0.752202]
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8948 [D loss: 0.685499, acc.: 49.22%] [G loss: 0.739531]
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8949 [D loss: 0.688500, acc.: 48.83%] [G loss: 0.750254]
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8950 [D loss: 0.687250, acc.: 48.24%] [G loss: 0.742915]
1/1 [==============================] - 0s 31ms/step
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8951 [D loss: 0.689996, acc.: 46.88%] [G loss: 0.729691]
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8952 [D loss: 0.688464, acc.: 49.22%] [G loss: 0.739500]
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8953 [D loss: 0.688177, acc.: 48.24%] [G loss: 0.724903]
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8954 [D loss: 0.692010, acc.: 48.83%] [G loss: 0.728461]
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8955 [D loss: 0.691325, acc.: 52.15%] [G loss: 0.728096]
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8956 [D loss: 0.685462, acc.: 49.61%] [G loss: 0.725452]
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8957 [D loss: 0.685145, acc.: 53.32%] [G loss: 0.730673]
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8958 [D loss: 0.682581, acc.: 51.37%] [G loss: 0.735861]
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8959 [D loss: 0.676757, acc.: 54.49%] [G loss: 0.728882]
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8960 [D loss: 0.678198, acc.: 51.95%] [G loss: 0.750568]
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8961 [D loss: 0.680918, acc.: 51.56%] [G loss: 0.748822]
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8962 [D loss: 0.677684, acc.: 49.80%] [G loss: 0.759879]
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8963 [D loss: 0.690077, acc.: 49.61%] [G loss: 0.749717]
8/8 [==============================] - 0s 4ms/step
8964 [D loss: 0.690103, acc.: 48.44%] [G loss: 0.733299]
8/8 [==============================] - 0s 4ms/step
8965 [D loss: 0.689157, acc.: 46.29%] [G loss: 0.727389]
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8966 [D loss: 0.690880, acc.: 49.61%] [G loss: 0.719289]
8/8 [==============================] - 0s 4ms/step
8967 [D loss: 0.692646, acc.: 48.83%] [G loss: 0.725895]
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8968 [D loss: 0.691869, acc.: 48.05%] [G loss: 0.749887]
8/8 [==============================] - 0s 4ms/step
8969 [D loss: 0.691474, acc.: 48.63%] [G loss: 0.744466]
8/8 [==============================] - 0s 4ms/step
8970 [D loss: 0.700867, acc.: 46.88%] [G loss: 0.735885]
8/8 [==============================] - 0s 4ms/step
8971 [D loss: 0.707538, acc.: 42.77%] [G loss: 0.728628]
8/8 [==============================] - 0s 4ms/step
8972 [D loss: 0.703111, acc.: 43.16%] [G loss: 0.734067]
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8973 [D loss: 0.701184, acc.: 45.70%] [G loss: 0.734274]
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8974 [D loss: 0.685833, acc.: 56.25%] [G loss: 0.777176]
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8975 [D loss: 0.688131, acc.: 52.93%] [G loss: 0.742380]
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8976 [D loss: 0.687567, acc.: 53.32%] [G loss: 0.747449]
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8977 [D loss: 0.683668, acc.: 54.10%] [G loss: 0.756623]
8/8 [==============================] - 0s 4ms/step
8978 [D loss: 0.700098, acc.: 50.78%] [G loss: 0.728998]
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8979 [D loss: 0.699663, acc.: 48.05%] [G loss: 0.716595]
8/8 [==============================] - 0s 4ms/step
8980 [D loss: 0.691644, acc.: 50.39%] [G loss: 0.721459]
8/8 [==============================] - 0s 4ms/step
8981 [D loss: 0.691826, acc.: 47.46%] [G loss: 0.731030]
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8982 [D loss: 0.700167, acc.: 44.14%] [G loss: 0.715327]
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8983 [D loss: 0.692964, acc.: 48.24%] [G loss: 0.715189]
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8984 [D loss: 0.692601, acc.: 45.70%] [G loss: 0.723158]
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8985 [D loss: 0.683384, acc.: 50.78%] [G loss: 0.724925]
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8986 [D loss: 0.686713, acc.: 46.88%] [G loss: 0.737859]
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8987 [D loss: 0.682710, acc.: 51.95%] [G loss: 0.766622]
8/8 [==============================] - 0s 4ms/step
8988 [D loss: 0.670984, acc.: 55.47%] [G loss: 0.778254]
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8989 [D loss: 0.681986, acc.: 53.52%] [G loss: 0.780145]
8/8 [==============================] - 0s 4ms/step
8990 [D loss: 0.674655, acc.: 55.08%] [G loss: 0.782858]
8/8 [==============================] - 0s 5ms/step
8991 [D loss: 0.678346, acc.: 55.27%] [G loss: 0.777378]
8/8 [==============================] - 0s 4ms/step
8992 [D loss: 0.670726, acc.: 56.05%] [G loss: 0.781200]
8/8 [==============================] - 0s 4ms/step
8993 [D loss: 0.692650, acc.: 50.00%] [G loss: 0.734862]
8/8 [==============================] - 0s 4ms/step
8994 [D loss: 0.690892, acc.: 50.00%] [G loss: 0.731344]
8/8 [==============================] - 0s 4ms/step
8995 [D loss: 0.718808, acc.: 44.53%] [G loss: 0.729609]
8/8 [==============================] - 0s 4ms/step
8996 [D loss: 0.699593, acc.: 51.95%] [G loss: 0.768907]
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8997 [D loss: 0.685915, acc.: 51.37%] [G loss: 0.775391]
8/8 [==============================] - 0s 4ms/step
8998 [D loss: 0.683730, acc.: 54.69%] [G loss: 0.791502]
8/8 [==============================] - 0s 4ms/step
8999 [D loss: 0.692441, acc.: 51.17%] [G loss: 0.790356]
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9000 [D loss: 0.696400, acc.: 47.07%] [G loss: 0.752781]
1/1 [==============================] - 0s 37ms/step
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9001 [D loss: 0.692441, acc.: 49.80%] [G loss: 0.734912]
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9002 [D loss: 0.707171, acc.: 43.95%] [G loss: 0.724541]
8/8 [==============================] - 0s 4ms/step
9003 [D loss: 0.697781, acc.: 47.66%] [G loss: 0.735748]
8/8 [==============================] - 0s 4ms/step
9004 [D loss: 0.700063, acc.: 45.12%] [G loss: 0.755638]
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9005 [D loss: 0.698231, acc.: 49.80%] [G loss: 0.744460]
8/8 [==============================] - 0s 4ms/step
9006 [D loss: 0.693015, acc.: 49.80%] [G loss: 0.732505]
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9007 [D loss: 0.694306, acc.: 49.22%] [G loss: 0.742974]
8/8 [==============================] - 0s 4ms/step
9008 [D loss: 0.691416, acc.: 51.76%] [G loss: 0.724909]
8/8 [==============================] - 0s 4ms/step
9009 [D loss: 0.688079, acc.: 52.73%] [G loss: 0.718823]
8/8 [==============================] - 0s 4ms/step
9010 [D loss: 0.694180, acc.: 50.59%] [G loss: 0.717709]
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9011 [D loss: 0.691973, acc.: 51.56%] [G loss: 0.727637]
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9012 [D loss: 0.693911, acc.: 50.98%] [G loss: 0.747645]
8/8 [==============================] - 0s 4ms/step
9013 [D loss: 0.693380, acc.: 52.73%] [G loss: 0.750519]
8/8 [==============================] - 0s 4ms/step
9014 [D loss: 0.693670, acc.: 49.80%] [G loss: 0.731007]
8/8 [==============================] - 0s 4ms/step
9015 [D loss: 0.697518, acc.: 46.68%] [G loss: 0.712386]
8/8 [==============================] - 0s 4ms/step
9016 [D loss: 0.685420, acc.: 49.80%] [G loss: 0.727611]
8/8 [==============================] - 0s 4ms/step
9017 [D loss: 0.702311, acc.: 42.77%] [G loss: 0.724913]
8/8 [==============================] - 0s 4ms/step
9018 [D loss: 0.692405, acc.: 47.85%] [G loss: 0.730447]
8/8 [==============================] - 0s 4ms/step
9019 [D loss: 0.687140, acc.: 50.78%] [G loss: 0.743313]
8/8 [==============================] - 0s 4ms/step
9020 [D loss: 0.678241, acc.: 53.12%] [G loss: 0.778824]
8/8 [==============================] - 0s 4ms/step
9021 [D loss: 0.692767, acc.: 48.83%] [G loss: 0.746623]
8/8 [==============================] - 0s 4ms/step
9022 [D loss: 0.674513, acc.: 56.84%] [G loss: 0.752517]
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9023 [D loss: 0.691561, acc.: 51.95%] [G loss: 0.767442]
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9024 [D loss: 0.676558, acc.: 57.03%] [G loss: 0.730413]
8/8 [==============================] - 0s 4ms/step
9025 [D loss: 0.690481, acc.: 52.73%] [G loss: 0.739545]
8/8 [==============================] - 0s 4ms/step
9026 [D loss: 0.697468, acc.: 47.07%] [G loss: 0.726246]
8/8 [==============================] - 0s 4ms/step
9027 [D loss: 0.692239, acc.: 48.63%] [G loss: 0.735606]
8/8 [==============================] - 0s 4ms/step
9028 [D loss: 0.698763, acc.: 44.92%] [G loss: 0.753789]
8/8 [==============================] - 0s 4ms/step
9029 [D loss: 0.699575, acc.: 46.29%] [G loss: 0.748281]
8/8 [==============================] - 0s 4ms/step
9030 [D loss: 0.695028, acc.: 50.59%] [G loss: 0.736571]
8/8 [==============================] - 0s 4ms/step
9031 [D loss: 0.689706, acc.: 49.22%] [G loss: 0.740070]
8/8 [==============================] - 0s 4ms/step
9032 [D loss: 0.682125, acc.: 52.34%] [G loss: 0.756326]
8/8 [==============================] - 0s 4ms/step
9033 [D loss: 0.691584, acc.: 54.69%] [G loss: 0.750521]
8/8 [==============================] - 0s 4ms/step
9034 [D loss: 0.703120, acc.: 48.83%] [G loss: 0.727839]
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9035 [D loss: 0.694577, acc.: 51.56%] [G loss: 0.746706]
8/8 [==============================] - 0s 4ms/step
9036 [D loss: 0.684999, acc.: 49.80%] [G loss: 0.765685]
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9037 [D loss: 0.680573, acc.: 52.73%] [G loss: 0.751380]
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9038 [D loss: 0.688475, acc.: 50.20%] [G loss: 0.770696]
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9039 [D loss: 0.686288, acc.: 51.56%] [G loss: 0.758659]
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9040 [D loss: 0.680996, acc.: 52.15%] [G loss: 0.748574]
8/8 [==============================] - 0s 4ms/step
9041 [D loss: 0.695502, acc.: 45.70%] [G loss: 0.726435]
8/8 [==============================] - 0s 4ms/step
9042 [D loss: 0.691740, acc.: 48.83%] [G loss: 0.719778]
8/8 [==============================] - 0s 4ms/step
9043 [D loss: 0.689055, acc.: 48.24%] [G loss: 0.727803]
8/8 [==============================] - 0s 4ms/step
9044 [D loss: 0.692619, acc.: 46.88%] [G loss: 0.750221]
8/8 [==============================] - 0s 4ms/step
9045 [D loss: 0.675121, acc.: 50.59%] [G loss: 0.750870]
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9046 [D loss: 0.685532, acc.: 50.39%] [G loss: 0.759557]
8/8 [==============================] - 0s 4ms/step
9047 [D loss: 0.683008, acc.: 49.02%] [G loss: 0.741448]
8/8 [==============================] - 0s 4ms/step
9048 [D loss: 0.687476, acc.: 51.95%] [G loss: 0.744144]
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9049 [D loss: 0.680902, acc.: 51.37%] [G loss: 0.753924]
8/8 [==============================] - 0s 4ms/step
9050 [D loss: 0.675300, acc.: 52.73%] [G loss: 0.744697]
1/1 [==============================] - 0s 55ms/step
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9051 [D loss: 0.686233, acc.: 51.56%] [G loss: 0.741643]
8/8 [==============================] - 0s 4ms/step
9052 [D loss: 0.682240, acc.: 50.39%] [G loss: 0.731750]
8/8 [==============================] - 0s 4ms/step
9053 [D loss: 0.686594, acc.: 46.48%] [G loss: 0.733136]
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9054 [D loss: 0.706875, acc.: 46.48%] [G loss: 0.715291]
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9055 [D loss: 0.700813, acc.: 44.92%] [G loss: 0.697550]
8/8 [==============================] - 0s 4ms/step
9056 [D loss: 0.703152, acc.: 42.19%] [G loss: 0.708617]
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9057 [D loss: 0.697026, acc.: 43.75%] [G loss: 0.710016]
8/8 [==============================] - 0s 4ms/step
9058 [D loss: 0.697884, acc.: 44.34%] [G loss: 0.722095]
8/8 [==============================] - 0s 4ms/step
9059 [D loss: 0.696111, acc.: 46.88%] [G loss: 0.735922]
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9060 [D loss: 0.691573, acc.: 47.66%] [G loss: 0.741163]
8/8 [==============================] - 0s 4ms/step
9061 [D loss: 0.695760, acc.: 47.66%] [G loss: 0.722603]
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9062 [D loss: 0.695110, acc.: 48.24%] [G loss: 0.733479]
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9063 [D loss: 0.692503, acc.: 47.07%] [G loss: 0.722964]
8/8 [==============================] - 0s 4ms/step
9064 [D loss: 0.686534, acc.: 51.76%] [G loss: 0.734187]
8/8 [==============================] - 0s 4ms/step
9065 [D loss: 0.695153, acc.: 50.39%] [G loss: 0.727617]
8/8 [==============================] - 0s 4ms/step
9066 [D loss: 0.694986, acc.: 47.66%] [G loss: 0.740908]
8/8 [==============================] - 0s 4ms/step
9067 [D loss: 0.689034, acc.: 53.12%] [G loss: 0.771780]
8/8 [==============================] - 0s 4ms/step
9068 [D loss: 0.689773, acc.: 50.59%] [G loss: 0.757181]
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9069 [D loss: 0.697994, acc.: 48.83%] [G loss: 0.737186]
8/8 [==============================] - 0s 4ms/step
9070 [D loss: 0.683421, acc.: 57.81%] [G loss: 0.745003]
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9071 [D loss: 0.687728, acc.: 50.59%] [G loss: 0.727956]
8/8 [==============================] - 0s 4ms/step
9072 [D loss: 0.696478, acc.: 49.22%] [G loss: 0.718949]
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9073 [D loss: 0.694291, acc.: 49.61%] [G loss: 0.722432]
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9074 [D loss: 0.696781, acc.: 49.80%] [G loss: 0.740181]
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9075 [D loss: 0.692381, acc.: 50.98%] [G loss: 0.745480]
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9076 [D loss: 0.693398, acc.: 50.78%] [G loss: 0.741937]
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9077 [D loss: 0.704206, acc.: 46.68%] [G loss: 0.720755]
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9078 [D loss: 0.700755, acc.: 45.12%] [G loss: 0.710654]
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9079 [D loss: 0.700870, acc.: 46.09%] [G loss: 0.709833]
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9080 [D loss: 0.700478, acc.: 45.51%] [G loss: 0.713597]
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9081 [D loss: 0.700257, acc.: 44.53%] [G loss: 0.700641]
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9082 [D loss: 0.698016, acc.: 47.27%] [G loss: 0.715690]
8/8 [==============================] - 0s 4ms/step
9083 [D loss: 0.686337, acc.: 53.32%] [G loss: 0.765842]
8/8 [==============================] - 0s 4ms/step
9084 [D loss: 0.685025, acc.: 51.76%] [G loss: 0.765693]
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9085 [D loss: 0.684289, acc.: 52.34%] [G loss: 0.749568]
8/8 [==============================] - 0s 4ms/step
9086 [D loss: 0.690404, acc.: 50.20%] [G loss: 0.741440]
8/8 [==============================] - 0s 4ms/step
9087 [D loss: 0.680998, acc.: 51.76%] [G loss: 0.746863]
8/8 [==============================] - 0s 4ms/step
9088 [D loss: 0.688827, acc.: 52.34%] [G loss: 0.727092]
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9089 [D loss: 0.682832, acc.: 52.15%] [G loss: 0.711234]
8/8 [==============================] - 0s 4ms/step
9090 [D loss: 0.693868, acc.: 45.31%] [G loss: 0.726490]
8/8 [==============================] - 0s 4ms/step
9091 [D loss: 0.693786, acc.: 42.97%] [G loss: 0.724079]
8/8 [==============================] - 0s 4ms/step
9092 [D loss: 0.680590, acc.: 49.80%] [G loss: 0.734849]
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9093 [D loss: 0.683823, acc.: 49.80%] [G loss: 0.746260]
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9094 [D loss: 0.688956, acc.: 49.22%] [G loss: 0.743506]
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9095 [D loss: 0.673915, acc.: 50.39%] [G loss: 0.744636]
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9096 [D loss: 0.669293, acc.: 58.20%] [G loss: 0.765717]
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9097 [D loss: 0.685060, acc.: 51.56%] [G loss: 0.743095]
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9098 [D loss: 0.683192, acc.: 49.80%] [G loss: 0.729760]
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9099 [D loss: 0.682032, acc.: 50.20%] [G loss: 0.741143]
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9100 [D loss: 0.688480, acc.: 47.85%] [G loss: 0.738604]
1/1 [==============================] - 0s 31ms/step
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9101 [D loss: 0.693628, acc.: 51.37%] [G loss: 0.746391]
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9102 [D loss: 0.711307, acc.: 49.41%] [G loss: 0.742227]
8/8 [==============================] - 0s 5ms/step
9103 [D loss: 0.697656, acc.: 52.93%] [G loss: 0.747668]
8/8 [==============================] - 0s 4ms/step
9104 [D loss: 0.694878, acc.: 49.80%] [G loss: 0.743576]
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9105 [D loss: 0.694449, acc.: 47.27%] [G loss: 0.742320]
8/8 [==============================] - 0s 4ms/step
9106 [D loss: 0.702439, acc.: 47.27%] [G loss: 0.719506]
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9107 [D loss: 0.694110, acc.: 51.17%] [G loss: 0.712752]
8/8 [==============================] - 0s 4ms/step
9108 [D loss: 0.692614, acc.: 47.46%] [G loss: 0.746342]
8/8 [==============================] - 0s 4ms/step
9109 [D loss: 0.687941, acc.: 51.95%] [G loss: 0.731852]
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9110 [D loss: 0.697475, acc.: 45.70%] [G loss: 0.738263]
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9111 [D loss: 0.694898, acc.: 44.14%] [G loss: 0.730917]
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9112 [D loss: 0.689105, acc.: 50.39%] [G loss: 0.736576]
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9113 [D loss: 0.688484, acc.: 53.91%] [G loss: 0.734576]
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9114 [D loss: 0.692686, acc.: 43.95%] [G loss: 0.727141]
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9115 [D loss: 0.680004, acc.: 54.49%] [G loss: 0.726944]
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9116 [D loss: 0.678819, acc.: 53.32%] [G loss: 0.744842]
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9117 [D loss: 0.682885, acc.: 52.73%] [G loss: 0.754747]
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9118 [D loss: 0.682422, acc.: 55.27%] [G loss: 0.749275]
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9119 [D loss: 0.686148, acc.: 52.15%] [G loss: 0.733968]
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9120 [D loss: 0.692222, acc.: 49.61%] [G loss: 0.720445]
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9121 [D loss: 0.682293, acc.: 50.00%] [G loss: 0.729428]
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9122 [D loss: 0.677821, acc.: 52.93%] [G loss: 0.752641]
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9123 [D loss: 0.691114, acc.: 50.20%] [G loss: 0.745161]
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9124 [D loss: 0.684507, acc.: 50.20%] [G loss: 0.730664]
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9125 [D loss: 0.684853, acc.: 49.80%] [G loss: 0.731484]
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9126 [D loss: 0.688863, acc.: 50.00%] [G loss: 0.767109]
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9127 [D loss: 0.681799, acc.: 52.73%] [G loss: 0.776125]
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9128 [D loss: 0.688061, acc.: 50.59%] [G loss: 0.754581]
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9129 [D loss: 0.682875, acc.: 50.39%] [G loss: 0.732536]
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9130 [D loss: 0.680735, acc.: 50.78%] [G loss: 0.734914]
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9131 [D loss: 0.689912, acc.: 48.44%] [G loss: 0.732381]
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9132 [D loss: 0.700567, acc.: 50.39%] [G loss: 0.709797]
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9133 [D loss: 0.701279, acc.: 46.48%] [G loss: 0.732091]
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9134 [D loss: 0.702339, acc.: 49.61%] [G loss: 0.724578]
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9135 [D loss: 0.681434, acc.: 53.12%] [G loss: 0.775627]
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9136 [D loss: 0.696184, acc.: 49.02%] [G loss: 0.776738]
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9137 [D loss: 0.688339, acc.: 50.78%] [G loss: 0.750394]
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9138 [D loss: 0.692077, acc.: 51.37%] [G loss: 0.747658]
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9139 [D loss: 0.688333, acc.: 54.30%] [G loss: 0.733019]
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9140 [D loss: 0.695633, acc.: 47.85%] [G loss: 0.721020]
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9141 [D loss: 0.686634, acc.: 50.20%] [G loss: 0.731245]
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9142 [D loss: 0.681325, acc.: 48.63%] [G loss: 0.724118]
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9143 [D loss: 0.688575, acc.: 52.15%] [G loss: 0.738197]
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9144 [D loss: 0.684686, acc.: 53.12%] [G loss: 0.736346]
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9145 [D loss: 0.690175, acc.: 49.41%] [G loss: 0.752634]
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9146 [D loss: 0.684735, acc.: 47.85%] [G loss: 0.752196]
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9147 [D loss: 0.683947, acc.: 52.34%] [G loss: 0.777056]
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9148 [D loss: 0.693149, acc.: 46.48%] [G loss: 0.726643]
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9149 [D loss: 0.695370, acc.: 45.12%] [G loss: 0.726921]
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9150 [D loss: 0.689861, acc.: 47.46%] [G loss: 0.726757]
1/1 [==============================] - 0s 33ms/step
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9151 [D loss: 0.688918, acc.: 49.02%] [G loss: 0.739170]
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9152 [D loss: 0.690677, acc.: 44.14%] [G loss: 0.730809]
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9153 [D loss: 0.698312, acc.: 44.14%] [G loss: 0.737192]
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9154 [D loss: 0.684231, acc.: 47.07%] [G loss: 0.738785]
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9155 [D loss: 0.689276, acc.: 50.59%] [G loss: 0.739355]
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9156 [D loss: 0.686381, acc.: 49.02%] [G loss: 0.730932]
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9157 [D loss: 0.683457, acc.: 46.09%] [G loss: 0.731204]
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9158 [D loss: 0.682273, acc.: 50.20%] [G loss: 0.741805]
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9159 [D loss: 0.682984, acc.: 48.63%] [G loss: 0.719806]
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9160 [D loss: 0.687464, acc.: 46.88%] [G loss: 0.746383]
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9161 [D loss: 0.685345, acc.: 47.66%] [G loss: 0.744285]
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9162 [D loss: 0.681136, acc.: 52.34%] [G loss: 0.740457]
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9163 [D loss: 0.690887, acc.: 50.39%] [G loss: 0.716636]
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9164 [D loss: 0.688299, acc.: 48.83%] [G loss: 0.729184]
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9165 [D loss: 0.672357, acc.: 52.15%] [G loss: 0.744181]
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9166 [D loss: 0.682035, acc.: 50.20%] [G loss: 0.760407]
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9167 [D loss: 0.678433, acc.: 50.59%] [G loss: 0.747609]
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9168 [D loss: 0.682757, acc.: 48.83%] [G loss: 0.775319]
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9169 [D loss: 0.677679, acc.: 52.73%] [G loss: 0.784161]
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9170 [D loss: 0.682499, acc.: 50.20%] [G loss: 0.735631]
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9171 [D loss: 0.677652, acc.: 53.91%] [G loss: 0.744635]
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9172 [D loss: 0.691118, acc.: 46.29%] [G loss: 0.762477]
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9173 [D loss: 0.691273, acc.: 45.31%] [G loss: 0.716884]
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9174 [D loss: 0.692636, acc.: 44.34%] [G loss: 0.734889]
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9175 [D loss: 0.683668, acc.: 44.92%] [G loss: 0.753417]
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9176 [D loss: 0.678192, acc.: 49.22%] [G loss: 0.745274]
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9177 [D loss: 0.685766, acc.: 48.44%] [G loss: 0.734503]
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9178 [D loss: 0.684513, acc.: 48.24%] [G loss: 0.740256]
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9179 [D loss: 0.674526, acc.: 54.88%] [G loss: 0.740541]
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9180 [D loss: 0.681192, acc.: 51.76%] [G loss: 0.744837]
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9181 [D loss: 0.678934, acc.: 50.98%] [G loss: 0.745519]
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9182 [D loss: 0.684745, acc.: 50.98%] [G loss: 0.749385]
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9183 [D loss: 0.686569, acc.: 49.80%] [G loss: 0.734685]
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9184 [D loss: 0.699064, acc.: 46.29%] [G loss: 0.749087]
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9185 [D loss: 0.690186, acc.: 45.12%] [G loss: 0.730429]
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9186 [D loss: 0.697923, acc.: 44.73%] [G loss: 0.723917]
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9187 [D loss: 0.708707, acc.: 49.61%] [G loss: 0.727739]
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9188 [D loss: 0.693905, acc.: 46.09%] [G loss: 0.736751]
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9189 [D loss: 0.701015, acc.: 43.16%] [G loss: 0.740464]
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9190 [D loss: 0.695994, acc.: 44.73%] [G loss: 0.736663]
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9191 [D loss: 0.695672, acc.: 48.63%] [G loss: 0.739221]
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9192 [D loss: 0.695441, acc.: 45.90%] [G loss: 0.746037]
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9193 [D loss: 0.697488, acc.: 47.46%] [G loss: 0.739880]
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9194 [D loss: 0.692777, acc.: 45.31%] [G loss: 0.732540]
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9195 [D loss: 0.683802, acc.: 49.41%] [G loss: 0.747229]
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9196 [D loss: 0.685775, acc.: 54.30%] [G loss: 0.740433]
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9197 [D loss: 0.681943, acc.: 51.76%] [G loss: 0.725990]
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9198 [D loss: 0.692355, acc.: 47.27%] [G loss: 0.745021]
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9199 [D loss: 0.689938, acc.: 48.44%] [G loss: 0.728411]
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9200 [D loss: 0.694692, acc.: 43.16%] [G loss: 0.717611]
1/1 [==============================] - 0s 34ms/step
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9201 [D loss: 0.694973, acc.: 48.05%] [G loss: 0.711957]
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9202 [D loss: 0.701717, acc.: 45.51%] [G loss: 0.713137]
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9203 [D loss: 0.693081, acc.: 51.17%] [G loss: 0.707349]
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9204 [D loss: 0.691766, acc.: 48.24%] [G loss: 0.734588]
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9205 [D loss: 0.686510, acc.: 52.93%] [G loss: 0.726475]
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9206 [D loss: 0.684774, acc.: 52.93%] [G loss: 0.741654]
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9207 [D loss: 0.690549, acc.: 53.71%] [G loss: 0.737943]
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9208 [D loss: 0.685920, acc.: 51.37%] [G loss: 0.759679]
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9209 [D loss: 0.694988, acc.: 51.95%] [G loss: 0.737712]
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9210 [D loss: 0.679468, acc.: 50.78%] [G loss: 0.762611]
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9211 [D loss: 0.699512, acc.: 50.59%] [G loss: 0.732278]
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9212 [D loss: 0.685786, acc.: 52.73%] [G loss: 0.747756]
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9213 [D loss: 0.684862, acc.: 53.52%] [G loss: 0.746045]
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9214 [D loss: 0.678137, acc.: 56.05%] [G loss: 0.746678]
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9215 [D loss: 0.677552, acc.: 53.12%] [G loss: 0.753905]
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9216 [D loss: 0.690194, acc.: 45.90%] [G loss: 0.747716]
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9217 [D loss: 0.690016, acc.: 45.90%] [G loss: 0.769971]
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9218 [D loss: 0.684930, acc.: 54.69%] [G loss: 0.766369]
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9219 [D loss: 0.672769, acc.: 53.71%] [G loss: 0.763192]
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9220 [D loss: 0.682741, acc.: 47.66%] [G loss: 0.764836]
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9221 [D loss: 0.686884, acc.: 47.66%] [G loss: 0.764751]
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9222 [D loss: 0.674479, acc.: 51.37%] [G loss: 0.742531]
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9223 [D loss: 0.693130, acc.: 48.24%] [G loss: 0.758411]
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9224 [D loss: 0.687648, acc.: 51.56%] [G loss: 0.752332]
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9225 [D loss: 0.673217, acc.: 50.98%] [G loss: 0.746269]
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9226 [D loss: 0.687100, acc.: 48.24%] [G loss: 0.746239]
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9227 [D loss: 0.685293, acc.: 48.83%] [G loss: 0.729429]
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9228 [D loss: 0.692479, acc.: 45.51%] [G loss: 0.721765]
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9229 [D loss: 0.682603, acc.: 46.88%] [G loss: 0.740616]
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9230 [D loss: 0.689436, acc.: 46.29%] [G loss: 0.745418]
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9231 [D loss: 0.680689, acc.: 49.02%] [G loss: 0.743444]
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9232 [D loss: 0.690432, acc.: 49.02%] [G loss: 0.732282]
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9233 [D loss: 0.678953, acc.: 52.73%] [G loss: 0.746418]
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9234 [D loss: 0.696892, acc.: 44.34%] [G loss: 0.732736]
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9235 [D loss: 0.685195, acc.: 45.70%] [G loss: 0.732480]
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9236 [D loss: 0.678858, acc.: 48.63%] [G loss: 0.752437]
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9237 [D loss: 0.670332, acc.: 52.15%] [G loss: 0.751684]
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9238 [D loss: 0.676227, acc.: 49.61%] [G loss: 0.751354]
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9239 [D loss: 0.685805, acc.: 51.17%] [G loss: 0.753883]
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9240 [D loss: 0.668788, acc.: 56.25%] [G loss: 0.750660]
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9241 [D loss: 0.685767, acc.: 52.73%] [G loss: 0.734525]
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9242 [D loss: 0.678469, acc.: 49.41%] [G loss: 0.731595]
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9243 [D loss: 0.681128, acc.: 47.85%] [G loss: 0.736848]
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9244 [D loss: 0.686259, acc.: 45.90%] [G loss: 0.744354]
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9245 [D loss: 0.689714, acc.: 44.92%] [G loss: 0.732610]
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9246 [D loss: 0.691419, acc.: 44.34%] [G loss: 0.723297]
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9247 [D loss: 0.701288, acc.: 43.75%] [G loss: 0.712597]
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9248 [D loss: 0.705218, acc.: 45.12%] [G loss: 0.706114]
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9249 [D loss: 0.709672, acc.: 44.14%] [G loss: 0.714008]
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9250 [D loss: 0.687351, acc.: 50.59%] [G loss: 0.733229]
1/1 [==============================] - 0s 54ms/step
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9251 [D loss: 0.687167, acc.: 48.24%] [G loss: 0.739841]
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9252 [D loss: 0.676258, acc.: 52.93%] [G loss: 0.770248]
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9253 [D loss: 0.686666, acc.: 51.95%] [G loss: 0.765000]
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9254 [D loss: 0.683618, acc.: 50.98%] [G loss: 0.771095]
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9255 [D loss: 0.694242, acc.: 44.73%] [G loss: 0.738501]
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9256 [D loss: 0.679711, acc.: 54.30%] [G loss: 0.779580]
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9257 [D loss: 0.701228, acc.: 46.48%] [G loss: 0.752439]
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9258 [D loss: 0.686640, acc.: 51.76%] [G loss: 0.797484]
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9259 [D loss: 0.685789, acc.: 52.34%] [G loss: 0.787523]
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9260 [D loss: 0.684561, acc.: 49.80%] [G loss: 0.772784]
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9261 [D loss: 0.695468, acc.: 47.27%] [G loss: 0.794054]
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9262 [D loss: 0.686843, acc.: 54.69%] [G loss: 0.819665]
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9263 [D loss: 0.709028, acc.: 48.05%] [G loss: 0.734803]
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9264 [D loss: 0.682245, acc.: 51.17%] [G loss: 0.754379]
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9265 [D loss: 0.682299, acc.: 53.12%] [G loss: 0.796045]
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9266 [D loss: 0.691405, acc.: 49.22%] [G loss: 0.775768]
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9267 [D loss: 0.680194, acc.: 55.47%] [G loss: 0.757803]
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9268 [D loss: 0.691496, acc.: 45.90%] [G loss: 0.761852]
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9269 [D loss: 0.700819, acc.: 45.70%] [G loss: 0.776243]
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9270 [D loss: 0.682241, acc.: 46.29%] [G loss: 0.743694]
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9271 [D loss: 0.688568, acc.: 51.37%] [G loss: 0.722816]
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9272 [D loss: 0.684144, acc.: 58.40%] [G loss: 0.727716]
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9273 [D loss: 0.685918, acc.: 52.93%] [G loss: 0.718586]
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9274 [D loss: 0.696501, acc.: 47.85%] [G loss: 0.719318]
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9275 [D loss: 0.687693, acc.: 47.07%] [G loss: 0.714187]
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9276 [D loss: 0.677097, acc.: 56.64%] [G loss: 0.742559]
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9277 [D loss: 0.683657, acc.: 52.15%] [G loss: 0.751266]
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9278 [D loss: 0.686059, acc.: 53.91%] [G loss: 0.739014]
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9279 [D loss: 0.687665, acc.: 50.78%] [G loss: 0.760901]
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9280 [D loss: 0.676590, acc.: 51.76%] [G loss: 0.767223]
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9281 [D loss: 0.683038, acc.: 52.93%] [G loss: 0.767276]
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9282 [D loss: 0.696230, acc.: 54.30%] [G loss: 0.754359]
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9283 [D loss: 0.685790, acc.: 56.25%] [G loss: 0.753873]
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9284 [D loss: 0.698763, acc.: 51.95%] [G loss: 0.731156]
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9285 [D loss: 0.715235, acc.: 46.09%] [G loss: 0.724354]
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9286 [D loss: 0.688155, acc.: 51.17%] [G loss: 0.770227]
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9287 [D loss: 0.683295, acc.: 56.64%] [G loss: 0.824204]
8/8 [==============================] - 0s 4ms/step
9288 [D loss: 0.698597, acc.: 48.63%] [G loss: 0.796207]
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9289 [D loss: 0.705569, acc.: 44.73%] [G loss: 0.749969]
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9290 [D loss: 0.691354, acc.: 54.88%] [G loss: 0.801215]
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9291 [D loss: 0.704786, acc.: 46.68%] [G loss: 0.726172]
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9292 [D loss: 0.695831, acc.: 50.59%] [G loss: 0.726511]
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9293 [D loss: 0.698702, acc.: 48.05%] [G loss: 0.732887]
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9294 [D loss: 0.693444, acc.: 49.80%] [G loss: 0.731674]
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9295 [D loss: 0.693364, acc.: 47.66%] [G loss: 0.736043]
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9296 [D loss: 0.698167, acc.: 44.53%] [G loss: 0.733005]
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9297 [D loss: 0.685681, acc.: 53.52%] [G loss: 0.740376]
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9298 [D loss: 0.684923, acc.: 54.69%] [G loss: 0.738466]
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9299 [D loss: 0.686276, acc.: 55.86%] [G loss: 0.727290]
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9300 [D loss: 0.688908, acc.: 51.56%] [G loss: 0.709251]
1/1 [==============================] - 0s 33ms/step
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9301 [D loss: 0.690996, acc.: 48.24%] [G loss: 0.725888]
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9302 [D loss: 0.682553, acc.: 53.32%] [G loss: 0.741480]
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9303 [D loss: 0.689559, acc.: 51.17%] [G loss: 0.721892]
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9304 [D loss: 0.684575, acc.: 51.56%] [G loss: 0.728051]
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9305 [D loss: 0.685490, acc.: 54.30%] [G loss: 0.737332]
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9306 [D loss: 0.686829, acc.: 48.24%] [G loss: 0.724635]
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9307 [D loss: 0.691136, acc.: 48.44%] [G loss: 0.721434]
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9308 [D loss: 0.687602, acc.: 52.34%] [G loss: 0.719594]
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9309 [D loss: 0.695608, acc.: 48.83%] [G loss: 0.726474]
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9310 [D loss: 0.691767, acc.: 49.41%] [G loss: 0.722741]
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9311 [D loss: 0.699412, acc.: 48.24%] [G loss: 0.709823]
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9312 [D loss: 0.703004, acc.: 45.12%] [G loss: 0.703374]
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9313 [D loss: 0.705502, acc.: 43.55%] [G loss: 0.710492]
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9314 [D loss: 0.696558, acc.: 46.48%] [G loss: 0.727650]
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9315 [D loss: 0.692079, acc.: 49.22%] [G loss: 0.736067]
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9316 [D loss: 0.693796, acc.: 50.00%] [G loss: 0.730581]
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9317 [D loss: 0.690833, acc.: 47.27%] [G loss: 0.717050]
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9318 [D loss: 0.690726, acc.: 50.20%] [G loss: 0.727634]
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9319 [D loss: 0.693241, acc.: 49.22%] [G loss: 0.713485]
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9320 [D loss: 0.696427, acc.: 47.85%] [G loss: 0.715721]
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9321 [D loss: 0.701424, acc.: 45.12%] [G loss: 0.709048]
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9322 [D loss: 0.693924, acc.: 50.78%] [G loss: 0.729836]
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9323 [D loss: 0.697687, acc.: 45.70%] [G loss: 0.740682]
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9324 [D loss: 0.694604, acc.: 48.05%] [G loss: 0.748374]
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9325 [D loss: 0.692786, acc.: 51.17%] [G loss: 0.744390]
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9326 [D loss: 0.686957, acc.: 50.59%] [G loss: 0.753108]
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9327 [D loss: 0.681694, acc.: 53.32%] [G loss: 0.767150]
8/8 [==============================] - 0s 4ms/step
9328 [D loss: 0.689971, acc.: 51.17%] [G loss: 0.729616]
8/8 [==============================] - 0s 4ms/step
9329 [D loss: 0.685698, acc.: 49.80%] [G loss: 0.744353]
8/8 [==============================] - 0s 4ms/step
9330 [D loss: 0.693739, acc.: 45.31%] [G loss: 0.750333]
8/8 [==============================] - 0s 4ms/step
9331 [D loss: 0.697678, acc.: 44.53%] [G loss: 0.756057]
8/8 [==============================] - 0s 5ms/step
9332 [D loss: 0.694641, acc.: 48.05%] [G loss: 0.734376]
8/8 [==============================] - 0s 4ms/step
9333 [D loss: 0.694913, acc.: 48.24%] [G loss: 0.729767]
8/8 [==============================] - 0s 4ms/step
9334 [D loss: 0.689299, acc.: 53.12%] [G loss: 0.740742]
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9335 [D loss: 0.687054, acc.: 54.69%] [G loss: 0.733278]
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9336 [D loss: 0.694466, acc.: 52.54%] [G loss: 0.735762]
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9337 [D loss: 0.688745, acc.: 53.12%] [G loss: 0.735602]
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9338 [D loss: 0.690702, acc.: 48.24%] [G loss: 0.747430]
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9339 [D loss: 0.681215, acc.: 52.73%] [G loss: 0.761721]
8/8 [==============================] - 0s 4ms/step
9340 [D loss: 0.678203, acc.: 58.98%] [G loss: 0.758694]
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9341 [D loss: 0.675063, acc.: 57.62%] [G loss: 0.768652]
8/8 [==============================] - 0s 4ms/step
9342 [D loss: 0.681912, acc.: 58.01%] [G loss: 0.763531]
8/8 [==============================] - 0s 4ms/step
9343 [D loss: 0.691654, acc.: 53.32%] [G loss: 0.735233]
8/8 [==============================] - 0s 4ms/step
9344 [D loss: 0.686221, acc.: 50.78%] [G loss: 0.747830]
8/8 [==============================] - 0s 4ms/step
9345 [D loss: 0.696811, acc.: 49.61%] [G loss: 0.756317]
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9346 [D loss: 0.689341, acc.: 49.41%] [G loss: 0.757466]
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9347 [D loss: 0.684183, acc.: 49.41%] [G loss: 0.759657]
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9348 [D loss: 0.698765, acc.: 43.55%] [G loss: 0.743806]
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9349 [D loss: 0.705580, acc.: 41.80%] [G loss: 0.737678]
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9350 [D loss: 0.696264, acc.: 46.09%] [G loss: 0.745613]
1/1 [==============================] - 0s 33ms/step
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9351 [D loss: 0.698492, acc.: 44.53%] [G loss: 0.744937]
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9352 [D loss: 0.690072, acc.: 50.59%] [G loss: 0.789051]
8/8 [==============================] - 0s 4ms/step
9353 [D loss: 0.680698, acc.: 58.40%] [G loss: 0.785091]
8/8 [==============================] - 0s 4ms/step
9354 [D loss: 0.698733, acc.: 52.54%] [G loss: 0.749686]
8/8 [==============================] - 0s 4ms/step
9355 [D loss: 0.696771, acc.: 48.05%] [G loss: 0.736000]
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9356 [D loss: 0.701041, acc.: 51.76%] [G loss: 0.718055]
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9357 [D loss: 0.701553, acc.: 48.83%] [G loss: 0.708078]
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9358 [D loss: 0.709794, acc.: 48.83%] [G loss: 0.734671]
8/8 [==============================] - 0s 4ms/step
9359 [D loss: 0.692859, acc.: 52.93%] [G loss: 0.738627]
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9360 [D loss: 0.686065, acc.: 53.71%] [G loss: 0.741797]
8/8 [==============================] - 0s 4ms/step
9361 [D loss: 0.693884, acc.: 49.80%] [G loss: 0.729534]
8/8 [==============================] - 0s 4ms/step
9362 [D loss: 0.693604, acc.: 51.76%] [G loss: 0.724082]
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9363 [D loss: 0.703565, acc.: 47.07%] [G loss: 0.719872]
8/8 [==============================] - 0s 4ms/step
9364 [D loss: 0.705456, acc.: 42.19%] [G loss: 0.717897]
8/8 [==============================] - 0s 4ms/step
9365 [D loss: 0.705354, acc.: 46.48%] [G loss: 0.718726]
8/8 [==============================] - 0s 4ms/step
9366 [D loss: 0.694240, acc.: 49.22%] [G loss: 0.731678]
8/8 [==============================] - 0s 4ms/step
9367 [D loss: 0.690219, acc.: 52.15%] [G loss: 0.742730]
8/8 [==============================] - 0s 4ms/step
9368 [D loss: 0.690807, acc.: 52.34%] [G loss: 0.758722]
8/8 [==============================] - 0s 4ms/step
9369 [D loss: 0.676054, acc.: 60.35%] [G loss: 0.771942]
8/8 [==============================] - 0s 4ms/step
9370 [D loss: 0.682128, acc.: 53.71%] [G loss: 0.760394]
8/8 [==============================] - 0s 4ms/step
9371 [D loss: 0.679197, acc.: 54.69%] [G loss: 0.776334]
8/8 [==============================] - 0s 4ms/step
9372 [D loss: 0.682062, acc.: 52.15%] [G loss: 0.768860]
8/8 [==============================] - 0s 4ms/step
9373 [D loss: 0.689502, acc.: 47.66%] [G loss: 0.736112]
8/8 [==============================] - 0s 4ms/step
9374 [D loss: 0.684430, acc.: 49.22%] [G loss: 0.750534]
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9375 [D loss: 0.697487, acc.: 45.90%] [G loss: 0.742059]
8/8 [==============================] - 0s 4ms/step
9376 [D loss: 0.687728, acc.: 47.07%] [G loss: 0.737843]
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9377 [D loss: 0.694913, acc.: 46.09%] [G loss: 0.746562]
8/8 [==============================] - 0s 4ms/step
9378 [D loss: 0.690292, acc.: 47.27%] [G loss: 0.745288]
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9379 [D loss: 0.693258, acc.: 47.66%] [G loss: 0.770200]
8/8 [==============================] - 0s 4ms/step
9380 [D loss: 0.688802, acc.: 49.22%] [G loss: 0.756628]
8/8 [==============================] - 0s 4ms/step
9381 [D loss: 0.689715, acc.: 48.83%] [G loss: 0.745827]
8/8 [==============================] - 0s 4ms/step
9382 [D loss: 0.696131, acc.: 47.46%] [G loss: 0.736352]
8/8 [==============================] - 0s 4ms/step
9383 [D loss: 0.711340, acc.: 50.78%] [G loss: 0.717416]
8/8 [==============================] - 0s 4ms/step
9384 [D loss: 0.699092, acc.: 46.29%] [G loss: 0.727461]
8/8 [==============================] - 0s 4ms/step
9385 [D loss: 0.694842, acc.: 49.41%] [G loss: 0.722570]
8/8 [==============================] - 0s 4ms/step
9386 [D loss: 0.701112, acc.: 42.97%] [G loss: 0.712963]
8/8 [==============================] - 0s 4ms/step
9387 [D loss: 0.694174, acc.: 49.22%] [G loss: 0.720332]
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9388 [D loss: 0.693857, acc.: 49.22%] [G loss: 0.726480]
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9389 [D loss: 0.693487, acc.: 50.39%] [G loss: 0.731736]
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9390 [D loss: 0.691428, acc.: 50.78%] [G loss: 0.725171]
8/8 [==============================] - 0s 4ms/step
9391 [D loss: 0.690867, acc.: 53.32%] [G loss: 0.720121]
8/8 [==============================] - 0s 4ms/step
9392 [D loss: 0.694207, acc.: 51.76%] [G loss: 0.718249]
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9393 [D loss: 0.695521, acc.: 47.46%] [G loss: 0.717797]
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9394 [D loss: 0.696896, acc.: 47.46%] [G loss: 0.717059]
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9395 [D loss: 0.701510, acc.: 47.85%] [G loss: 0.694483]
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9396 [D loss: 0.701316, acc.: 46.48%] [G loss: 0.707961]
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9397 [D loss: 0.700047, acc.: 47.07%] [G loss: 0.728987]
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9398 [D loss: 0.695360, acc.: 48.83%] [G loss: 0.731570]
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9399 [D loss: 0.698874, acc.: 49.22%] [G loss: 0.733084]
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9400 [D loss: 0.694097, acc.: 49.02%] [G loss: 0.727811]
1/1 [==============================] - 0s 29ms/step
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9401 [D loss: 0.700196, acc.: 46.88%] [G loss: 0.724491]
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9402 [D loss: 0.689085, acc.: 52.15%] [G loss: 0.729789]
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9403 [D loss: 0.691557, acc.: 51.17%] [G loss: 0.727598]
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9404 [D loss: 0.690276, acc.: 48.63%] [G loss: 0.727252]
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9405 [D loss: 0.692798, acc.: 50.98%] [G loss: 0.728036]
8/8 [==============================] - 0s 4ms/step
9406 [D loss: 0.689341, acc.: 48.24%] [G loss: 0.720369]
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9407 [D loss: 0.689592, acc.: 49.41%] [G loss: 0.734480]
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9408 [D loss: 0.685566, acc.: 52.54%] [G loss: 0.732619]
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9409 [D loss: 0.690587, acc.: 50.00%] [G loss: 0.736361]
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9410 [D loss: 0.690484, acc.: 46.68%] [G loss: 0.745005]
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9411 [D loss: 0.689672, acc.: 47.46%] [G loss: 0.736833]
8/8 [==============================] - 0s 4ms/step
9412 [D loss: 0.679026, acc.: 52.73%] [G loss: 0.738568]
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9413 [D loss: 0.695133, acc.: 50.39%] [G loss: 0.743540]
8/8 [==============================] - 0s 4ms/step
9414 [D loss: 0.691494, acc.: 45.12%] [G loss: 0.731913]
8/8 [==============================] - 0s 4ms/step
9415 [D loss: 0.685136, acc.: 54.88%] [G loss: 0.727384]
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9416 [D loss: 0.692585, acc.: 44.34%] [G loss: 0.725847]
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9417 [D loss: 0.684783, acc.: 51.95%] [G loss: 0.732672]
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9418 [D loss: 0.685233, acc.: 49.22%] [G loss: 0.745464]
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9419 [D loss: 0.684432, acc.: 52.15%] [G loss: 0.741946]
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9420 [D loss: 0.677508, acc.: 53.32%] [G loss: 0.760162]
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9421 [D loss: 0.684030, acc.: 51.37%] [G loss: 0.735329]
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9422 [D loss: 0.689343, acc.: 45.90%] [G loss: 0.733439]
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9423 [D loss: 0.684831, acc.: 46.88%] [G loss: 0.736438]
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9424 [D loss: 0.686841, acc.: 49.02%] [G loss: 0.743534]
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9425 [D loss: 0.688533, acc.: 48.63%] [G loss: 0.733385]
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9426 [D loss: 0.679331, acc.: 47.07%] [G loss: 0.740890]
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9427 [D loss: 0.703379, acc.: 44.92%] [G loss: 0.711343]
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9428 [D loss: 0.700066, acc.: 45.90%] [G loss: 0.720892]
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9429 [D loss: 0.701574, acc.: 49.61%] [G loss: 0.724744]
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9430 [D loss: 0.706492, acc.: 54.88%] [G loss: 0.736484]
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9431 [D loss: 0.698796, acc.: 52.34%] [G loss: 0.754606]
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9432 [D loss: 0.690369, acc.: 56.45%] [G loss: 0.746410]
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9433 [D loss: 0.690584, acc.: 54.88%] [G loss: 0.736961]
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9434 [D loss: 0.694489, acc.: 52.54%] [G loss: 0.728384]
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9435 [D loss: 0.697663, acc.: 49.80%] [G loss: 0.734970]
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9436 [D loss: 0.689446, acc.: 57.03%] [G loss: 0.760287]
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9437 [D loss: 0.680344, acc.: 55.47%] [G loss: 0.781686]
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9438 [D loss: 0.683954, acc.: 53.91%] [G loss: 0.759079]
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9439 [D loss: 0.677271, acc.: 54.69%] [G loss: 0.766350]
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9440 [D loss: 0.684477, acc.: 55.66%] [G loss: 0.786424]
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9441 [D loss: 0.688703, acc.: 51.95%] [G loss: 0.720961]
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9442 [D loss: 0.697778, acc.: 46.68%] [G loss: 0.742297]
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9443 [D loss: 0.700685, acc.: 46.88%] [G loss: 0.736985]
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9444 [D loss: 0.697854, acc.: 49.61%] [G loss: 0.752239]
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9445 [D loss: 0.698613, acc.: 48.63%] [G loss: 0.745764]
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9446 [D loss: 0.698902, acc.: 48.63%] [G loss: 0.744284]
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9447 [D loss: 0.693196, acc.: 51.56%] [G loss: 0.748637]
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9448 [D loss: 0.687399, acc.: 57.23%] [G loss: 0.761247]
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9449 [D loss: 0.700113, acc.: 50.39%] [G loss: 0.717917]
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9450 [D loss: 0.699181, acc.: 47.27%] [G loss: 0.720019]
1/1 [==============================] - 0s 28ms/step
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9451 [D loss: 0.691674, acc.: 51.17%] [G loss: 0.743000]
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9452 [D loss: 0.689028, acc.: 54.69%] [G loss: 0.739416]
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9453 [D loss: 0.688171, acc.: 55.66%] [G loss: 0.734412]
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9454 [D loss: 0.680141, acc.: 58.59%] [G loss: 0.751508]
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9455 [D loss: 0.700243, acc.: 47.46%] [G loss: 0.709519]
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9456 [D loss: 0.698493, acc.: 46.88%] [G loss: 0.695224]
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9457 [D loss: 0.700676, acc.: 48.05%] [G loss: 0.712531]
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9458 [D loss: 0.691248, acc.: 47.85%] [G loss: 0.722474]
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9459 [D loss: 0.697629, acc.: 46.48%] [G loss: 0.732898]
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9460 [D loss: 0.692802, acc.: 51.56%] [G loss: 0.735193]
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9461 [D loss: 0.696785, acc.: 53.12%] [G loss: 0.726035]
8/8 [==============================] - 0s 4ms/step
9462 [D loss: 0.680975, acc.: 55.66%] [G loss: 0.738819]
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9463 [D loss: 0.698418, acc.: 46.88%] [G loss: 0.720161]
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9464 [D loss: 0.695547, acc.: 46.88%] [G loss: 0.717693]
8/8 [==============================] - 0s 4ms/step
9465 [D loss: 0.688723, acc.: 50.39%] [G loss: 0.737613]
8/8 [==============================] - 0s 4ms/step
9466 [D loss: 0.686312, acc.: 49.41%] [G loss: 0.757108]
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9467 [D loss: 0.686152, acc.: 52.73%] [G loss: 0.771038]
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9468 [D loss: 0.680070, acc.: 54.88%] [G loss: 0.778658]
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9469 [D loss: 0.688989, acc.: 53.91%] [G loss: 0.755536]
8/8 [==============================] - 0s 4ms/step
9470 [D loss: 0.686702, acc.: 54.30%] [G loss: 0.748436]
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9471 [D loss: 0.687478, acc.: 50.59%] [G loss: 0.723301]
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9472 [D loss: 0.691214, acc.: 50.78%] [G loss: 0.724324]
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9473 [D loss: 0.697142, acc.: 48.63%] [G loss: 0.724833]
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9474 [D loss: 0.690031, acc.: 46.48%] [G loss: 0.720961]
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9475 [D loss: 0.689919, acc.: 50.20%] [G loss: 0.765967]
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9476 [D loss: 0.690173, acc.: 49.22%] [G loss: 0.793315]
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9477 [D loss: 0.702937, acc.: 44.92%] [G loss: 0.741357]
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9478 [D loss: 0.692435, acc.: 50.39%] [G loss: 0.753673]
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9479 [D loss: 0.686276, acc.: 50.39%] [G loss: 0.766596]
8/8 [==============================] - 0s 4ms/step
9480 [D loss: 0.695636, acc.: 43.55%] [G loss: 0.734544]
8/8 [==============================] - 0s 4ms/step
9481 [D loss: 0.685521, acc.: 47.66%] [G loss: 0.757080]
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9482 [D loss: 0.682714, acc.: 48.63%] [G loss: 0.780159]
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9483 [D loss: 0.690246, acc.: 48.05%] [G loss: 0.784313]
8/8 [==============================] - 0s 4ms/step
9484 [D loss: 0.679940, acc.: 53.32%] [G loss: 0.777962]
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9485 [D loss: 0.684375, acc.: 50.98%] [G loss: 0.757031]
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9486 [D loss: 0.682874, acc.: 52.93%] [G loss: 0.766182]
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9487 [D loss: 0.683091, acc.: 52.54%] [G loss: 0.748417]
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9488 [D loss: 0.691368, acc.: 48.83%] [G loss: 0.725696]
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9489 [D loss: 0.683101, acc.: 52.73%] [G loss: 0.724005]
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9490 [D loss: 0.687330, acc.: 50.98%] [G loss: 0.737165]
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9491 [D loss: 0.701472, acc.: 46.48%] [G loss: 0.717921]
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9492 [D loss: 0.697740, acc.: 50.78%] [G loss: 0.717146]
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9493 [D loss: 0.693879, acc.: 45.31%] [G loss: 0.721238]
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9494 [D loss: 0.692446, acc.: 49.22%] [G loss: 0.727468]
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9495 [D loss: 0.690003, acc.: 52.54%] [G loss: 0.740315]
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9496 [D loss: 0.687278, acc.: 50.00%] [G loss: 0.718802]
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9497 [D loss: 0.684886, acc.: 56.05%] [G loss: 0.730614]
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9498 [D loss: 0.682909, acc.: 55.27%] [G loss: 0.741179]
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9499 [D loss: 0.687923, acc.: 50.98%] [G loss: 0.736803]
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9500 [D loss: 0.686449, acc.: 52.73%] [G loss: 0.720968]
1/1 [==============================] - 0s 33ms/step
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9501 [D loss: 0.689424, acc.: 51.17%] [G loss: 0.729586]
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9502 [D loss: 0.687017, acc.: 52.54%] [G loss: 0.724085]
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9503 [D loss: 0.685919, acc.: 51.37%] [G loss: 0.729459]
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9504 [D loss: 0.686103, acc.: 47.46%] [G loss: 0.740216]
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9505 [D loss: 0.687423, acc.: 47.85%] [G loss: 0.750089]
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9506 [D loss: 0.692526, acc.: 50.78%] [G loss: 0.733509]
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9507 [D loss: 0.695786, acc.: 45.12%] [G loss: 0.716104]
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9508 [D loss: 0.706232, acc.: 41.80%] [G loss: 0.716514]
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9509 [D loss: 0.693677, acc.: 50.39%] [G loss: 0.728780]
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9510 [D loss: 0.686042, acc.: 48.05%] [G loss: 0.777030]
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9511 [D loss: 0.683506, acc.: 47.27%] [G loss: 0.743035]
8/8 [==============================] - 0s 4ms/step
9512 [D loss: 0.689267, acc.: 52.54%] [G loss: 0.742207]
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9513 [D loss: 0.690176, acc.: 50.59%] [G loss: 0.745239]
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9514 [D loss: 0.688713, acc.: 53.12%] [G loss: 0.739934]
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9515 [D loss: 0.689180, acc.: 49.41%] [G loss: 0.745893]
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9516 [D loss: 0.685670, acc.: 50.98%] [G loss: 0.735331]
8/8 [==============================] - 0s 4ms/step
9517 [D loss: 0.697485, acc.: 46.88%] [G loss: 0.736316]
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9518 [D loss: 0.686279, acc.: 48.05%] [G loss: 0.743887]
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9519 [D loss: 0.687271, acc.: 52.34%] [G loss: 0.759188]
8/8 [==============================] - 0s 4ms/step
9520 [D loss: 0.686334, acc.: 51.56%] [G loss: 0.738458]
8/8 [==============================] - 0s 4ms/step
9521 [D loss: 0.691268, acc.: 50.59%] [G loss: 0.742557]
8/8 [==============================] - 0s 4ms/step
9522 [D loss: 0.678486, acc.: 51.56%] [G loss: 0.736405]
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9523 [D loss: 0.691561, acc.: 47.07%] [G loss: 0.745849]
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9524 [D loss: 0.686143, acc.: 47.07%] [G loss: 0.738357]
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9525 [D loss: 0.680108, acc.: 50.39%] [G loss: 0.740700]
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9526 [D loss: 0.683288, acc.: 53.32%] [G loss: 0.744307]
8/8 [==============================] - 0s 4ms/step
9527 [D loss: 0.693009, acc.: 46.88%] [G loss: 0.743506]
8/8 [==============================] - 0s 4ms/step
9528 [D loss: 0.681838, acc.: 52.54%] [G loss: 0.739940]
8/8 [==============================] - 0s 4ms/step
9529 [D loss: 0.687703, acc.: 48.44%] [G loss: 0.733264]
8/8 [==============================] - 0s 4ms/step
9530 [D loss: 0.694311, acc.: 48.05%] [G loss: 0.714387]
8/8 [==============================] - 0s 4ms/step
9531 [D loss: 0.685498, acc.: 46.68%] [G loss: 0.728043]
8/8 [==============================] - 0s 4ms/step
9532 [D loss: 0.692324, acc.: 49.41%] [G loss: 0.741379]
8/8 [==============================] - 0s 4ms/step
9533 [D loss: 0.682614, acc.: 52.15%] [G loss: 0.755314]
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9534 [D loss: 0.680010, acc.: 52.54%] [G loss: 0.752987]
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9535 [D loss: 0.676615, acc.: 50.78%] [G loss: 0.760076]
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9536 [D loss: 0.690527, acc.: 51.95%] [G loss: 0.761144]
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9537 [D loss: 0.671120, acc.: 55.08%] [G loss: 0.740915]
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9538 [D loss: 0.679108, acc.: 54.30%] [G loss: 0.742510]
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9539 [D loss: 0.680639, acc.: 51.76%] [G loss: 0.716092]
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9540 [D loss: 0.688246, acc.: 47.85%] [G loss: 0.712879]
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9541 [D loss: 0.701459, acc.: 45.51%] [G loss: 0.732052]
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9542 [D loss: 0.699610, acc.: 44.53%] [G loss: 0.742531]
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9543 [D loss: 0.694098, acc.: 45.90%] [G loss: 0.755344]
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9544 [D loss: 0.686503, acc.: 47.07%] [G loss: 0.754175]
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9545 [D loss: 0.682356, acc.: 54.10%] [G loss: 0.768029]
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9546 [D loss: 0.685053, acc.: 52.15%] [G loss: 0.753446]
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9547 [D loss: 0.703084, acc.: 47.46%] [G loss: 0.740762]
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9548 [D loss: 0.705552, acc.: 44.73%] [G loss: 0.751268]
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9549 [D loss: 0.691267, acc.: 50.59%] [G loss: 0.776906]
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9550 [D loss: 0.687302, acc.: 52.15%] [G loss: 0.781574]
1/1 [==============================] - 0s 32ms/step
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9551 [D loss: 0.770770, acc.: 49.02%] [G loss: 0.744581]
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9552 [D loss: 0.693437, acc.: 50.78%] [G loss: 0.728897]
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9553 [D loss: 0.695070, acc.: 47.27%] [G loss: 0.736851]
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9554 [D loss: 0.693247, acc.: 51.37%] [G loss: 0.747005]
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9555 [D loss: 0.697184, acc.: 47.46%] [G loss: 0.746275]
8/8 [==============================] - 0s 4ms/step
9556 [D loss: 0.688326, acc.: 51.37%] [G loss: 0.739760]
8/8 [==============================] - 0s 4ms/step
9557 [D loss: 0.698096, acc.: 45.51%] [G loss: 0.737265]
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9558 [D loss: 0.696563, acc.: 47.66%] [G loss: 0.723103]
8/8 [==============================] - 0s 4ms/step
9559 [D loss: 0.696458, acc.: 48.83%] [G loss: 0.744294]
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9560 [D loss: 0.686238, acc.: 50.78%] [G loss: 0.751017]
8/8 [==============================] - 0s 4ms/step
9561 [D loss: 0.688422, acc.: 51.76%] [G loss: 0.761488]
8/8 [==============================] - 0s 4ms/step
9562 [D loss: 0.690329, acc.: 50.98%] [G loss: 0.744908]
8/8 [==============================] - 0s 4ms/step
9563 [D loss: 0.680220, acc.: 52.73%] [G loss: 0.754207]
8/8 [==============================] - 0s 5ms/step
9564 [D loss: 0.687850, acc.: 45.70%] [G loss: 0.742294]
8/8 [==============================] - 0s 4ms/step
9565 [D loss: 0.692080, acc.: 50.20%] [G loss: 0.760245]
8/8 [==============================] - 0s 4ms/step
9566 [D loss: 0.691493, acc.: 48.05%] [G loss: 0.754548]
8/8 [==============================] - 0s 4ms/step
9567 [D loss: 0.692528, acc.: 48.83%] [G loss: 0.741798]
8/8 [==============================] - 0s 4ms/step
9568 [D loss: 0.696521, acc.: 50.39%] [G loss: 0.753048]
8/8 [==============================] - 0s 4ms/step
9569 [D loss: 0.706259, acc.: 44.92%] [G loss: 0.720301]
8/8 [==============================] - 0s 4ms/step
9570 [D loss: 0.700875, acc.: 48.63%] [G loss: 0.733104]
8/8 [==============================] - 0s 4ms/step
9571 [D loss: 0.689398, acc.: 52.15%] [G loss: 0.761166]
8/8 [==============================] - 0s 4ms/step
9572 [D loss: 0.693303, acc.: 49.02%] [G loss: 0.757194]
8/8 [==============================] - 0s 4ms/step
9573 [D loss: 0.701071, acc.: 45.12%] [G loss: 0.728182]
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9574 [D loss: 0.689938, acc.: 51.37%] [G loss: 0.734767]
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9575 [D loss: 0.689494, acc.: 52.34%] [G loss: 0.732741]
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9576 [D loss: 0.703977, acc.: 43.95%] [G loss: 0.704477]
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9577 [D loss: 0.707196, acc.: 40.62%] [G loss: 0.702205]
8/8 [==============================] - 0s 4ms/step
9578 [D loss: 0.700834, acc.: 45.12%] [G loss: 0.743663]
8/8 [==============================] - 0s 4ms/step
9579 [D loss: 0.691989, acc.: 49.41%] [G loss: 0.754436]
8/8 [==============================] - 0s 4ms/step
9580 [D loss: 0.699597, acc.: 43.75%] [G loss: 0.752144]
8/8 [==============================] - 0s 4ms/step
9581 [D loss: 0.693918, acc.: 46.09%] [G loss: 0.753630]
8/8 [==============================] - 0s 4ms/step
9582 [D loss: 0.693208, acc.: 52.15%] [G loss: 0.754523]
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9583 [D loss: 0.685898, acc.: 51.95%] [G loss: 0.751755]
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9584 [D loss: 0.692490, acc.: 51.17%] [G loss: 0.719655]
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9585 [D loss: 0.696236, acc.: 48.44%] [G loss: 0.720513]
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9586 [D loss: 0.689978, acc.: 50.39%] [G loss: 0.739836]
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9587 [D loss: 0.677920, acc.: 54.88%] [G loss: 0.752299]
8/8 [==============================] - 0s 4ms/step
9588 [D loss: 0.684179, acc.: 52.15%] [G loss: 0.765526]
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9589 [D loss: 0.693640, acc.: 51.17%] [G loss: 0.749110]
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9590 [D loss: 0.690982, acc.: 50.78%] [G loss: 0.741511]
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9591 [D loss: 0.694730, acc.: 50.98%] [G loss: 0.740191]
8/8 [==============================] - 0s 4ms/step
9592 [D loss: 0.696142, acc.: 50.20%] [G loss: 0.727142]
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9593 [D loss: 0.695795, acc.: 48.44%] [G loss: 0.731010]
8/8 [==============================] - 0s 4ms/step
9594 [D loss: 0.690604, acc.: 49.41%] [G loss: 0.713189]
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9595 [D loss: 0.695440, acc.: 47.85%] [G loss: 0.720447]
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9596 [D loss: 0.689519, acc.: 49.02%] [G loss: 0.733819]
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9597 [D loss: 0.688474, acc.: 50.98%] [G loss: 0.736087]
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9598 [D loss: 0.681502, acc.: 47.07%] [G loss: 0.778499]
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9599 [D loss: 0.682646, acc.: 54.88%] [G loss: 0.762589]
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9600 [D loss: 0.685745, acc.: 50.20%] [G loss: 0.755113]
1/1 [==============================] - 0s 32ms/step
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9601 [D loss: 0.686434, acc.: 50.00%] [G loss: 0.773976]
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9602 [D loss: 0.684694, acc.: 50.59%] [G loss: 0.745033]
8/8 [==============================] - 0s 4ms/step
9603 [D loss: 0.685508, acc.: 49.80%] [G loss: 0.753033]
8/8 [==============================] - 0s 4ms/step
9604 [D loss: 0.681536, acc.: 55.86%] [G loss: 0.726274]
8/8 [==============================] - 0s 4ms/step
9605 [D loss: 0.695176, acc.: 49.41%] [G loss: 0.721527]
8/8 [==============================] - 0s 4ms/step
9606 [D loss: 0.698958, acc.: 49.61%] [G loss: 0.712804]
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9607 [D loss: 0.687339, acc.: 52.73%] [G loss: 0.726650]
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9608 [D loss: 0.678534, acc.: 54.49%] [G loss: 0.746753]
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9609 [D loss: 0.702812, acc.: 47.66%] [G loss: 0.731722]
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9610 [D loss: 0.685629, acc.: 50.39%] [G loss: 0.728808]
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9611 [D loss: 0.689096, acc.: 47.27%] [G loss: 0.729669]
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9612 [D loss: 0.684617, acc.: 48.63%] [G loss: 0.729216]
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9613 [D loss: 0.687161, acc.: 48.63%] [G loss: 0.723951]
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9614 [D loss: 0.683479, acc.: 49.02%] [G loss: 0.712007]
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9615 [D loss: 0.687201, acc.: 47.85%] [G loss: 0.724078]
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9616 [D loss: 0.686678, acc.: 49.02%] [G loss: 0.735388]
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9617 [D loss: 0.691828, acc.: 49.41%] [G loss: 0.733920]
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9618 [D loss: 0.686291, acc.: 45.31%] [G loss: 0.733768]
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9619 [D loss: 0.684953, acc.: 48.83%] [G loss: 0.736448]
8/8 [==============================] - 0s 4ms/step
9620 [D loss: 0.680108, acc.: 49.80%] [G loss: 0.729760]
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9621 [D loss: 0.688069, acc.: 45.51%] [G loss: 0.726782]
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9622 [D loss: 0.692085, acc.: 44.92%] [G loss: 0.737253]
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9623 [D loss: 0.691163, acc.: 47.66%] [G loss: 0.738401]
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9624 [D loss: 0.685050, acc.: 53.52%] [G loss: 0.731941]
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9625 [D loss: 0.684357, acc.: 47.85%] [G loss: 0.727767]
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9626 [D loss: 0.678666, acc.: 49.61%] [G loss: 0.730444]
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9627 [D loss: 0.676206, acc.: 53.91%] [G loss: 0.745666]
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9628 [D loss: 0.681790, acc.: 47.85%] [G loss: 0.728970]
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9629 [D loss: 0.669770, acc.: 54.49%] [G loss: 0.746770]
8/8 [==============================] - 0s 4ms/step
9630 [D loss: 0.688311, acc.: 47.85%] [G loss: 0.726404]
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9631 [D loss: 0.684889, acc.: 50.39%] [G loss: 0.730755]
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9632 [D loss: 0.693063, acc.: 49.02%] [G loss: 0.730264]
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9633 [D loss: 0.685670, acc.: 46.09%] [G loss: 0.727543]
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9634 [D loss: 0.671782, acc.: 51.17%] [G loss: 0.722817]
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9635 [D loss: 0.681441, acc.: 48.63%] [G loss: 0.732205]
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9636 [D loss: 0.673622, acc.: 47.46%] [G loss: 0.719984]
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9637 [D loss: 0.688350, acc.: 50.20%] [G loss: 0.731091]
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9638 [D loss: 0.681277, acc.: 46.29%] [G loss: 0.723771]
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9639 [D loss: 0.690166, acc.: 47.07%] [G loss: 0.725654]
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9640 [D loss: 0.690677, acc.: 43.55%] [G loss: 0.717918]
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9641 [D loss: 0.684587, acc.: 47.66%] [G loss: 0.726949]
8/8 [==============================] - 0s 4ms/step
9642 [D loss: 0.676023, acc.: 48.83%] [G loss: 0.728739]
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9643 [D loss: 0.691746, acc.: 47.66%] [G loss: 0.730169]
8/8 [==============================] - 0s 4ms/step
9644 [D loss: 0.683511, acc.: 49.80%] [G loss: 0.726236]
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9645 [D loss: 0.682304, acc.: 50.39%] [G loss: 0.731975]
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9646 [D loss: 0.677584, acc.: 51.56%] [G loss: 0.730268]
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9647 [D loss: 0.663761, acc.: 52.93%] [G loss: 0.742421]
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9648 [D loss: 0.677343, acc.: 51.37%] [G loss: 0.743448]
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9649 [D loss: 0.663258, acc.: 57.03%] [G loss: 0.736695]
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9650 [D loss: 0.667171, acc.: 53.52%] [G loss: 0.738660]
1/1 [==============================] - 0s 33ms/step
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9651 [D loss: 0.675566, acc.: 49.80%] [G loss: 0.741342]
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9652 [D loss: 0.680284, acc.: 47.27%] [G loss: 0.743912]
8/8 [==============================] - 0s 4ms/step
9653 [D loss: 0.686567, acc.: 47.27%] [G loss: 0.742221]
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9654 [D loss: 0.682878, acc.: 52.15%] [G loss: 0.727658]
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9655 [D loss: 0.688808, acc.: 49.02%] [G loss: 0.724050]
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9656 [D loss: 0.682315, acc.: 46.29%] [G loss: 0.731538]
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9657 [D loss: 0.681358, acc.: 50.20%] [G loss: 0.726258]
8/8 [==============================] - 0s 4ms/step
9658 [D loss: 0.676035, acc.: 51.17%] [G loss: 0.736906]
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9659 [D loss: 0.655043, acc.: 53.71%] [G loss: 0.738650]
8/8 [==============================] - 0s 4ms/step
9660 [D loss: 0.681867, acc.: 45.31%] [G loss: 0.744467]
8/8 [==============================] - 0s 4ms/step
9661 [D loss: 0.681407, acc.: 49.61%] [G loss: 0.735280]
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9662 [D loss: 0.679564, acc.: 46.48%] [G loss: 0.738062]
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9663 [D loss: 0.678364, acc.: 48.63%] [G loss: 0.736908]
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9664 [D loss: 0.677720, acc.: 43.75%] [G loss: 0.738597]
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9665 [D loss: 0.689819, acc.: 47.46%] [G loss: 0.735170]
8/8 [==============================] - 0s 4ms/step
9666 [D loss: 0.691977, acc.: 46.48%] [G loss: 0.726274]
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9667 [D loss: 0.678480, acc.: 51.37%] [G loss: 0.737039]
8/8 [==============================] - 0s 4ms/step
9668 [D loss: 0.682591, acc.: 48.44%] [G loss: 0.733776]
8/8 [==============================] - 0s 4ms/step
9669 [D loss: 0.682078, acc.: 49.41%] [G loss: 0.748600]
8/8 [==============================] - 0s 4ms/step
9670 [D loss: 0.679724, acc.: 50.39%] [G loss: 0.737484]
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9671 [D loss: 0.677669, acc.: 52.93%] [G loss: 0.735497]
8/8 [==============================] - 0s 4ms/step
9672 [D loss: 0.680362, acc.: 48.24%] [G loss: 0.729294]
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9673 [D loss: 0.689074, acc.: 45.90%] [G loss: 0.717387]
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9674 [D loss: 0.685345, acc.: 48.83%] [G loss: 0.719075]
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9675 [D loss: 0.679561, acc.: 49.41%] [G loss: 0.726313]
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9676 [D loss: 0.684603, acc.: 45.90%] [G loss: 0.735123]
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9677 [D loss: 0.683110, acc.: 49.80%] [G loss: 0.738786]
8/8 [==============================] - 0s 4ms/step
9678 [D loss: 0.688639, acc.: 45.31%] [G loss: 0.736611]
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9679 [D loss: 0.680811, acc.: 53.32%] [G loss: 0.739242]
8/8 [==============================] - 0s 4ms/step
9680 [D loss: 0.679166, acc.: 47.85%] [G loss: 0.757791]
8/8 [==============================] - 0s 4ms/step
9681 [D loss: 0.687813, acc.: 51.17%] [G loss: 0.754157]
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9682 [D loss: 0.688178, acc.: 48.05%] [G loss: 0.744440]
8/8 [==============================] - 0s 4ms/step
9683 [D loss: 0.681803, acc.: 52.93%] [G loss: 0.742331]
8/8 [==============================] - 0s 4ms/step
9684 [D loss: 0.674458, acc.: 51.95%] [G loss: 0.756706]
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9685 [D loss: 0.667321, acc.: 54.10%] [G loss: 0.750456]
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9686 [D loss: 0.675994, acc.: 51.95%] [G loss: 0.734585]
8/8 [==============================] - 0s 4ms/step
9687 [D loss: 0.695850, acc.: 46.88%] [G loss: 0.733943]
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9688 [D loss: 0.684729, acc.: 46.29%] [G loss: 0.744706]
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9689 [D loss: 0.672701, acc.: 48.83%] [G loss: 0.758894]
8/8 [==============================] - 0s 4ms/step
9690 [D loss: 0.688153, acc.: 47.85%] [G loss: 0.743732]
8/8 [==============================] - 0s 4ms/step
9691 [D loss: 0.686615, acc.: 46.88%] [G loss: 0.737525]
8/8 [==============================] - 0s 4ms/step
9692 [D loss: 0.683386, acc.: 48.24%] [G loss: 0.730197]
8/8 [==============================] - 0s 4ms/step
9693 [D loss: 0.688471, acc.: 49.41%] [G loss: 0.729367]
8/8 [==============================] - 0s 4ms/step
9694 [D loss: 0.696203, acc.: 40.43%] [G loss: 0.730331]
8/8 [==============================] - 0s 4ms/step
9695 [D loss: 0.687555, acc.: 48.05%] [G loss: 0.715312]
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9696 [D loss: 0.683072, acc.: 46.88%] [G loss: 0.726413]
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9697 [D loss: 0.684829, acc.: 49.22%] [G loss: 0.717497]
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9698 [D loss: 0.677998, acc.: 50.20%] [G loss: 0.724440]
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9699 [D loss: 0.680336, acc.: 46.68%] [G loss: 0.727446]
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9700 [D loss: 0.693005, acc.: 42.97%] [G loss: 0.724438]
1/1 [==============================] - 0s 30ms/step
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9701 [D loss: 0.679358, acc.: 49.41%] [G loss: 0.724600]
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9702 [D loss: 0.685000, acc.: 49.61%] [G loss: 0.723560]
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9703 [D loss: 0.698360, acc.: 46.88%] [G loss: 0.716606]
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9704 [D loss: 0.674629, acc.: 50.39%] [G loss: 0.733146]
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9705 [D loss: 0.682060, acc.: 47.27%] [G loss: 0.731317]
8/8 [==============================] - 0s 4ms/step
9706 [D loss: 0.669245, acc.: 47.85%] [G loss: 0.738119]
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9707 [D loss: 0.670292, acc.: 50.59%] [G loss: 0.744693]
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9708 [D loss: 0.681930, acc.: 48.63%] [G loss: 0.738232]
8/8 [==============================] - 0s 4ms/step
9709 [D loss: 0.682543, acc.: 48.83%] [G loss: 0.746812]
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9710 [D loss: 0.682535, acc.: 46.88%] [G loss: 0.738888]
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9711 [D loss: 0.677865, acc.: 55.08%] [G loss: 0.745067]
8/8 [==============================] - 0s 4ms/step
9712 [D loss: 0.682622, acc.: 49.80%] [G loss: 0.741014]
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9713 [D loss: 0.685677, acc.: 48.24%] [G loss: 0.726029]
8/8 [==============================] - 0s 4ms/step
9714 [D loss: 0.685367, acc.: 46.09%] [G loss: 0.721981]
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9715 [D loss: 0.681278, acc.: 42.38%] [G loss: 0.743239]
8/8 [==============================] - 0s 4ms/step
9716 [D loss: 0.678677, acc.: 44.14%] [G loss: 0.736669]
8/8 [==============================] - 0s 4ms/step
9717 [D loss: 0.678695, acc.: 49.22%] [G loss: 0.737399]
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9718 [D loss: 0.677258, acc.: 49.22%] [G loss: 0.741470]
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9719 [D loss: 0.674081, acc.: 48.44%] [G loss: 0.733112]
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9720 [D loss: 0.687814, acc.: 52.15%] [G loss: 0.731914]
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9721 [D loss: 0.675196, acc.: 52.34%] [G loss: 0.746895]
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9722 [D loss: 0.683709, acc.: 47.27%] [G loss: 0.741537]
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9723 [D loss: 0.683469, acc.: 45.90%] [G loss: 0.733404]
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9724 [D loss: 0.675389, acc.: 52.15%] [G loss: 0.745515]
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9725 [D loss: 0.675372, acc.: 52.34%] [G loss: 0.736807]
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9726 [D loss: 0.675816, acc.: 50.98%] [G loss: 0.741585]
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9727 [D loss: 0.678611, acc.: 49.61%] [G loss: 0.727475]
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9728 [D loss: 0.677997, acc.: 49.80%] [G loss: 0.743496]
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9729 [D loss: 0.678756, acc.: 46.48%] [G loss: 0.734121]
8/8 [==============================] - 0s 4ms/step
9730 [D loss: 0.672540, acc.: 45.31%] [G loss: 0.728154]
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9731 [D loss: 0.680906, acc.: 47.85%] [G loss: 0.719682]
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9732 [D loss: 0.673032, acc.: 48.44%] [G loss: 0.724259]
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9733 [D loss: 0.688502, acc.: 47.85%] [G loss: 0.737468]
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9734 [D loss: 0.686678, acc.: 50.00%] [G loss: 0.733797]
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9735 [D loss: 0.669282, acc.: 52.93%] [G loss: 0.739971]
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9736 [D loss: 0.683401, acc.: 46.68%] [G loss: 0.743912]
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9737 [D loss: 0.685715, acc.: 48.44%] [G loss: 0.741188]
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9738 [D loss: 0.675826, acc.: 54.10%] [G loss: 0.732962]
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9739 [D loss: 0.676148, acc.: 50.59%] [G loss: 0.743547]
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9740 [D loss: 0.681169, acc.: 51.17%] [G loss: 0.733777]
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9741 [D loss: 0.678177, acc.: 48.63%] [G loss: 0.748698]
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9742 [D loss: 0.675156, acc.: 52.15%] [G loss: 0.741251]
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9743 [D loss: 0.679660, acc.: 48.05%] [G loss: 0.735079]
8/8 [==============================] - 0s 4ms/step
9744 [D loss: 0.682698, acc.: 45.70%] [G loss: 0.745243]
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9745 [D loss: 0.682050, acc.: 47.46%] [G loss: 0.736811]
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9746 [D loss: 0.676191, acc.: 50.39%] [G loss: 0.733213]
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9747 [D loss: 0.675232, acc.: 50.98%] [G loss: 0.737297]
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9748 [D loss: 0.687053, acc.: 48.44%] [G loss: 0.733761]
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9749 [D loss: 0.677376, acc.: 46.48%] [G loss: 0.722021]
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9750 [D loss: 0.684907, acc.: 45.70%] [G loss: 0.717576]
1/1 [==============================] - 0s 36ms/step
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9751 [D loss: 0.680762, acc.: 44.53%] [G loss: 0.728976]
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9752 [D loss: 0.674527, acc.: 48.63%] [G loss: 0.745247]
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9753 [D loss: 0.671064, acc.: 48.24%] [G loss: 0.741111]
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9754 [D loss: 0.687041, acc.: 47.66%] [G loss: 0.740684]
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9755 [D loss: 0.679298, acc.: 46.88%] [G loss: 0.725720]
8/8 [==============================] - 0s 4ms/step
9756 [D loss: 0.681664, acc.: 48.63%] [G loss: 0.738341]
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9757 [D loss: 0.680700, acc.: 48.83%] [G loss: 0.742126]
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9758 [D loss: 0.724654, acc.: 48.24%] [G loss: 0.706744]
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9759 [D loss: 0.739998, acc.: 41.41%] [G loss: 0.720228]
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9760 [D loss: 0.698820, acc.: 43.75%] [G loss: 0.762872]
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9761 [D loss: 0.686314, acc.: 51.76%] [G loss: 0.789201]
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9762 [D loss: 0.684455, acc.: 49.61%] [G loss: 0.795295]
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9763 [D loss: 0.689342, acc.: 46.48%] [G loss: 0.764232]
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9764 [D loss: 0.691769, acc.: 47.85%] [G loss: 0.754418]
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9765 [D loss: 0.688288, acc.: 49.61%] [G loss: 0.731220]
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9766 [D loss: 0.684649, acc.: 48.24%] [G loss: 0.724415]
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9767 [D loss: 0.693502, acc.: 47.66%] [G loss: 0.727844]
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9768 [D loss: 0.698968, acc.: 41.99%] [G loss: 0.709243]
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9769 [D loss: 0.693478, acc.: 46.09%] [G loss: 0.734374]
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9770 [D loss: 0.677080, acc.: 51.17%] [G loss: 0.759973]
8/8 [==============================] - 0s 4ms/step
9771 [D loss: 0.695054, acc.: 48.24%] [G loss: 0.761378]
8/8 [==============================] - 0s 4ms/step
9772 [D loss: 0.687654, acc.: 45.12%] [G loss: 0.779123]
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9773 [D loss: 0.693292, acc.: 42.97%] [G loss: 0.753619]
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9774 [D loss: 0.692377, acc.: 43.55%] [G loss: 0.747285]
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9775 [D loss: 0.683704, acc.: 49.80%] [G loss: 0.737476]
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9776 [D loss: 0.682357, acc.: 50.59%] [G loss: 0.729522]
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9777 [D loss: 0.682827, acc.: 54.30%] [G loss: 0.716565]
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9778 [D loss: 0.689117, acc.: 52.93%] [G loss: 0.710567]
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9779 [D loss: 0.689286, acc.: 49.22%] [G loss: 0.709025]
8/8 [==============================] - 0s 4ms/step
9780 [D loss: 0.683166, acc.: 50.98%] [G loss: 0.748625]
8/8 [==============================] - 0s 4ms/step
9781 [D loss: 0.675721, acc.: 52.93%] [G loss: 0.753198]
8/8 [==============================] - 0s 4ms/step
9782 [D loss: 0.689664, acc.: 49.80%] [G loss: 0.748739]
8/8 [==============================] - 0s 4ms/step
9783 [D loss: 0.686715, acc.: 51.76%] [G loss: 0.737165]
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9784 [D loss: 0.683976, acc.: 46.88%] [G loss: 0.753684]
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9785 [D loss: 0.681334, acc.: 46.48%] [G loss: 0.765693]
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9786 [D loss: 0.675061, acc.: 49.22%] [G loss: 0.761305]
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9787 [D loss: 0.691536, acc.: 44.53%] [G loss: 0.735066]
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9788 [D loss: 0.688611, acc.: 45.12%] [G loss: 0.746867]
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9789 [D loss: 0.672759, acc.: 51.56%] [G loss: 0.750488]
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9790 [D loss: 0.674916, acc.: 49.61%] [G loss: 0.765531]
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9791 [D loss: 0.682286, acc.: 50.98%] [G loss: 0.757118]
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9792 [D loss: 0.692720, acc.: 44.92%] [G loss: 0.750793]
8/8 [==============================] - 0s 4ms/step
9793 [D loss: 0.679774, acc.: 51.37%] [G loss: 0.768666]
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9794 [D loss: 0.688675, acc.: 44.53%] [G loss: 0.758236]
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9795 [D loss: 0.688141, acc.: 51.37%] [G loss: 0.762717]
8/8 [==============================] - 0s 4ms/step
9796 [D loss: 0.682263, acc.: 49.80%] [G loss: 0.740064]
8/8 [==============================] - 0s 4ms/step
9797 [D loss: 0.688004, acc.: 47.07%] [G loss: 0.742990]
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9798 [D loss: 0.679320, acc.: 49.61%] [G loss: 0.752994]
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9799 [D loss: 0.684502, acc.: 48.44%] [G loss: 0.734004]
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9800 [D loss: 0.692609, acc.: 45.70%] [G loss: 0.736790]
1/1 [==============================] - 0s 33ms/step
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9801 [D loss: 0.693718, acc.: 38.28%] [G loss: 0.710424]
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9802 [D loss: 0.705331, acc.: 41.41%] [G loss: 0.704903]
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9803 [D loss: 0.732359, acc.: 49.41%] [G loss: 0.741635]
8/8 [==============================] - 0s 4ms/step
9804 [D loss: 0.690922, acc.: 51.17%] [G loss: 0.787100]
8/8 [==============================] - 0s 4ms/step
9805 [D loss: 0.692283, acc.: 46.29%] [G loss: 0.759425]
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9806 [D loss: 0.692942, acc.: 44.14%] [G loss: 0.812196]
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9807 [D loss: 0.711095, acc.: 39.45%] [G loss: 0.720493]
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9808 [D loss: 0.695754, acc.: 51.37%] [G loss: 0.752176]
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9809 [D loss: 0.686391, acc.: 52.73%] [G loss: 0.782620]
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9810 [D loss: 0.684073, acc.: 52.73%] [G loss: 0.764790]
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9811 [D loss: 0.673227, acc.: 55.08%] [G loss: 0.768324]
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9812 [D loss: 0.693180, acc.: 48.44%] [G loss: 0.779282]
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9813 [D loss: 0.682413, acc.: 55.27%] [G loss: 0.772125]
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9814 [D loss: 0.682676, acc.: 51.95%] [G loss: 0.749200]
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9815 [D loss: 0.689001, acc.: 50.39%] [G loss: 0.715001]
8/8 [==============================] - 0s 4ms/step
9816 [D loss: 0.685152, acc.: 51.56%] [G loss: 0.719710]
8/8 [==============================] - 0s 4ms/step
9817 [D loss: 0.685994, acc.: 49.61%] [G loss: 0.723401]
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9818 [D loss: 0.694358, acc.: 48.63%] [G loss: 0.720294]
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9819 [D loss: 0.690917, acc.: 51.37%] [G loss: 0.737678]
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9820 [D loss: 0.689667, acc.: 50.98%] [G loss: 0.754902]
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9821 [D loss: 0.688386, acc.: 49.61%] [G loss: 0.766338]
8/8 [==============================] - 0s 4ms/step
9822 [D loss: 0.690377, acc.: 48.83%] [G loss: 0.772223]
8/8 [==============================] - 0s 4ms/step
9823 [D loss: 0.698667, acc.: 42.58%] [G loss: 0.759717]
8/8 [==============================] - 0s 4ms/step
9824 [D loss: 0.692721, acc.: 45.70%] [G loss: 0.747100]
8/8 [==============================] - 0s 4ms/step
9825 [D loss: 0.683882, acc.: 54.88%] [G loss: 0.791946]
8/8 [==============================] - 0s 4ms/step
9826 [D loss: 0.695583, acc.: 48.24%] [G loss: 0.719010]
8/8 [==============================] - 0s 4ms/step
9827 [D loss: 0.689401, acc.: 46.48%] [G loss: 0.714101]
8/8 [==============================] - 0s 4ms/step
9828 [D loss: 0.682646, acc.: 50.78%] [G loss: 0.744464]
8/8 [==============================] - 0s 4ms/step
9829 [D loss: 0.685179, acc.: 51.37%] [G loss: 0.745095]
8/8 [==============================] - 0s 4ms/step
9830 [D loss: 0.686657, acc.: 51.17%] [G loss: 0.751253]
8/8 [==============================] - 0s 4ms/step
9831 [D loss: 0.689234, acc.: 51.37%] [G loss: 0.737428]
8/8 [==============================] - 0s 4ms/step
9832 [D loss: 0.682560, acc.: 46.68%] [G loss: 0.739687]
8/8 [==============================] - 0s 4ms/step
9833 [D loss: 0.684552, acc.: 49.61%] [G loss: 0.724012]
8/8 [==============================] - 0s 4ms/step
9834 [D loss: 0.683471, acc.: 51.95%] [G loss: 0.740485]
8/8 [==============================] - 0s 5ms/step
9835 [D loss: 0.683036, acc.: 49.22%] [G loss: 0.730782]
8/8 [==============================] - 0s 4ms/step
9836 [D loss: 0.691694, acc.: 46.29%] [G loss: 0.720180]
8/8 [==============================] - 0s 5ms/step
9837 [D loss: 0.691499, acc.: 50.98%] [G loss: 0.720524]
8/8 [==============================] - 0s 4ms/step
9838 [D loss: 0.688119, acc.: 49.02%] [G loss: 0.726706]
8/8 [==============================] - 0s 4ms/step
9839 [D loss: 0.682587, acc.: 50.78%] [G loss: 0.763210]
8/8 [==============================] - 0s 4ms/step
9840 [D loss: 0.681550, acc.: 52.73%] [G loss: 0.744648]
8/8 [==============================] - 0s 4ms/step
9841 [D loss: 0.671472, acc.: 51.37%] [G loss: 0.760247]
8/8 [==============================] - 0s 4ms/step
9842 [D loss: 0.675756, acc.: 51.17%] [G loss: 0.741374]
8/8 [==============================] - 0s 4ms/step
9843 [D loss: 0.678820, acc.: 49.22%] [G loss: 0.725169]
8/8 [==============================] - 0s 4ms/step
9844 [D loss: 0.687758, acc.: 49.80%] [G loss: 0.729049]
8/8 [==============================] - 0s 4ms/step
9845 [D loss: 0.691139, acc.: 46.48%] [G loss: 0.732190]
8/8 [==============================] - 0s 4ms/step
9846 [D loss: 0.686728, acc.: 47.07%] [G loss: 0.726793]
8/8 [==============================] - 0s 4ms/step
9847 [D loss: 0.677906, acc.: 50.78%] [G loss: 0.725051]
8/8 [==============================] - 0s 4ms/step
9848 [D loss: 0.678229, acc.: 48.24%] [G loss: 0.724917]
8/8 [==============================] - 0s 4ms/step
9849 [D loss: 0.685995, acc.: 49.02%] [G loss: 0.719328]
8/8 [==============================] - 0s 4ms/step
9850 [D loss: 0.694842, acc.: 47.07%] [G loss: 0.733887]
1/1 [==============================] - 0s 41ms/step
8/8 [==============================] - 0s 4ms/step
9851 [D loss: 0.693096, acc.: 50.98%] [G loss: 0.728552]
8/8 [==============================] - 0s 4ms/step
9852 [D loss: 0.686536, acc.: 51.76%] [G loss: 0.744238]
8/8 [==============================] - 0s 4ms/step
9853 [D loss: 0.683347, acc.: 51.76%] [G loss: 0.747834]
8/8 [==============================] - 0s 4ms/step
9854 [D loss: 0.690270, acc.: 49.22%] [G loss: 0.784927]
8/8 [==============================] - 0s 4ms/step
9855 [D loss: 0.687910, acc.: 48.05%] [G loss: 0.741290]
8/8 [==============================] - 0s 5ms/step
9856 [D loss: 0.675308, acc.: 52.34%] [G loss: 0.766916]
8/8 [==============================] - 0s 5ms/step
9857 [D loss: 0.687266, acc.: 49.22%] [G loss: 0.763087]
8/8 [==============================] - 0s 4ms/step
9858 [D loss: 0.675770, acc.: 53.52%] [G loss: 0.764781]
8/8 [==============================] - 0s 4ms/step
9859 [D loss: 0.682934, acc.: 50.78%] [G loss: 0.782887]
8/8 [==============================] - 0s 4ms/step
9860 [D loss: 0.683236, acc.: 50.98%] [G loss: 0.767285]
8/8 [==============================] - 0s 4ms/step
9861 [D loss: 0.677928, acc.: 52.34%] [G loss: 0.757361]
8/8 [==============================] - 0s 4ms/step
9862 [D loss: 0.689539, acc.: 49.41%] [G loss: 0.746285]
8/8 [==============================] - 0s 5ms/step
9863 [D loss: 0.716439, acc.: 39.26%] [G loss: 0.705814]
8/8 [==============================] - 0s 5ms/step
9864 [D loss: 0.714959, acc.: 46.29%] [G loss: 0.727190]
8/8 [==============================] - 0s 4ms/step
9865 [D loss: 0.710811, acc.: 48.44%] [G loss: 0.800335]
8/8 [==============================] - 0s 4ms/step
9866 [D loss: 0.701152, acc.: 42.97%] [G loss: 0.810740]
8/8 [==============================] - 0s 4ms/step
9867 [D loss: 0.698257, acc.: 51.56%] [G loss: 0.769525]
8/8 [==============================] - 0s 4ms/step
9868 [D loss: 0.691376, acc.: 47.66%] [G loss: 0.778235]
8/8 [==============================] - 0s 4ms/step
9869 [D loss: 0.691943, acc.: 51.95%] [G loss: 0.788136]
8/8 [==============================] - 0s 4ms/step
9870 [D loss: 0.691021, acc.: 53.32%] [G loss: 0.753458]
8/8 [==============================] - 0s 4ms/step
9871 [D loss: 0.688168, acc.: 52.93%] [G loss: 0.744568]
8/8 [==============================] - 0s 4ms/step
9872 [D loss: 0.689419, acc.: 50.59%] [G loss: 0.728240]
8/8 [==============================] - 0s 4ms/step
9873 [D loss: 0.687575, acc.: 52.93%] [G loss: 0.749209]
8/8 [==============================] - 0s 4ms/step
9874 [D loss: 0.685297, acc.: 52.54%] [G loss: 0.777487]
8/8 [==============================] - 0s 4ms/step
9875 [D loss: 0.689435, acc.: 49.41%] [G loss: 0.758700]
8/8 [==============================] - 0s 5ms/step
9876 [D loss: 0.695446, acc.: 48.44%] [G loss: 0.724741]
8/8 [==============================] - 0s 4ms/step
9877 [D loss: 0.688112, acc.: 50.98%] [G loss: 0.741123]
8/8 [==============================] - 0s 4ms/step
9878 [D loss: 0.694900, acc.: 45.31%] [G loss: 0.714546]
8/8 [==============================] - 0s 4ms/step
9879 [D loss: 0.703569, acc.: 41.21%] [G loss: 0.707854]
8/8 [==============================] - 0s 4ms/step
9880 [D loss: 0.712218, acc.: 45.51%] [G loss: 0.706585]
8/8 [==============================] - 0s 4ms/step
9881 [D loss: 0.691348, acc.: 46.68%] [G loss: 0.734307]
8/8 [==============================] - 0s 4ms/step
9882 [D loss: 0.676552, acc.: 51.37%] [G loss: 0.755796]
8/8 [==============================] - 0s 4ms/step
9883 [D loss: 0.669663, acc.: 52.73%] [G loss: 0.761958]
8/8 [==============================] - 0s 4ms/step
9884 [D loss: 0.680240, acc.: 50.20%] [G loss: 0.757890]
8/8 [==============================] - 0s 4ms/step
9885 [D loss: 0.687995, acc.: 49.22%] [G loss: 0.766545]
8/8 [==============================] - 0s 4ms/step
9886 [D loss: 0.677465, acc.: 54.30%] [G loss: 0.756592]
8/8 [==============================] - 0s 4ms/step
9887 [D loss: 0.677168, acc.: 52.34%] [G loss: 0.756465]
8/8 [==============================] - 0s 4ms/step
9888 [D loss: 0.680550, acc.: 50.78%] [G loss: 0.738033]
8/8 [==============================] - 0s 4ms/step
9889 [D loss: 0.687078, acc.: 50.20%] [G loss: 0.726432]
8/8 [==============================] - 0s 4ms/step
9890 [D loss: 0.685422, acc.: 46.88%] [G loss: 0.740521]
8/8 [==============================] - 0s 4ms/step
9891 [D loss: 0.694491, acc.: 43.55%] [G loss: 0.736049]
8/8 [==============================] - 0s 4ms/step
9892 [D loss: 0.692404, acc.: 48.44%] [G loss: 0.724360]
8/8 [==============================] - 0s 4ms/step
9893 [D loss: 0.689799, acc.: 48.05%] [G loss: 0.727989]
8/8 [==============================] - 0s 4ms/step
9894 [D loss: 0.694344, acc.: 43.95%] [G loss: 0.726164]
8/8 [==============================] - 0s 4ms/step
9895 [D loss: 0.687979, acc.: 46.48%] [G loss: 0.740325]
8/8 [==============================] - 0s 4ms/step
9896 [D loss: 0.689084, acc.: 44.53%] [G loss: 0.741676]
8/8 [==============================] - 0s 4ms/step
9897 [D loss: 0.675931, acc.: 52.54%] [G loss: 0.754193]
8/8 [==============================] - 0s 4ms/step
9898 [D loss: 0.670857, acc.: 53.12%] [G loss: 0.751037]
8/8 [==============================] - 0s 4ms/step
9899 [D loss: 0.672847, acc.: 55.08%] [G loss: 0.760634]
8/8 [==============================] - 0s 4ms/step
9900 [D loss: 0.701604, acc.: 48.24%] [G loss: 0.727263]
1/1 [==============================] - 0s 35ms/step
8/8 [==============================] - 0s 4ms/step
9901 [D loss: 0.709004, acc.: 51.17%] [G loss: 0.709122]
8/8 [==============================] - 0s 4ms/step
9902 [D loss: 0.709689, acc.: 51.37%] [G loss: 0.712804]
8/8 [==============================] - 0s 4ms/step
9903 [D loss: 0.687434, acc.: 53.71%] [G loss: 0.738169]
8/8 [==============================] - 0s 4ms/step
9904 [D loss: 0.685301, acc.: 53.71%] [G loss: 0.750180]
8/8 [==============================] - 0s 4ms/step
9905 [D loss: 0.685281, acc.: 50.20%] [G loss: 0.764171]
8/8 [==============================] - 0s 4ms/step
9906 [D loss: 0.690158, acc.: 50.39%] [G loss: 0.750267]
8/8 [==============================] - 0s 4ms/step
9907 [D loss: 0.692576, acc.: 49.80%] [G loss: 0.739269]
8/8 [==============================] - 0s 5ms/step
9908 [D loss: 0.690582, acc.: 50.39%] [G loss: 0.751633]
8/8 [==============================] - 0s 4ms/step
9909 [D loss: 0.684501, acc.: 49.61%] [G loss: 0.738128]
8/8 [==============================] - 0s 4ms/step
9910 [D loss: 0.699240, acc.: 45.31%] [G loss: 0.730330]
8/8 [==============================] - 0s 4ms/step
9911 [D loss: 0.697357, acc.: 48.63%] [G loss: 0.734352]
8/8 [==============================] - 0s 4ms/step
9912 [D loss: 0.682540, acc.: 54.10%] [G loss: 0.729962]
8/8 [==============================] - 0s 4ms/step
9913 [D loss: 0.695806, acc.: 49.80%] [G loss: 0.739175]
8/8 [==============================] - 0s 4ms/step
9914 [D loss: 0.684050, acc.: 50.98%] [G loss: 0.742661]
8/8 [==============================] - 0s 4ms/step
9915 [D loss: 0.686355, acc.: 53.91%] [G loss: 0.742056]
8/8 [==============================] - 0s 4ms/step
9916 [D loss: 0.680471, acc.: 55.66%] [G loss: 0.738485]
8/8 [==============================] - 0s 4ms/step
9917 [D loss: 0.695338, acc.: 51.76%] [G loss: 0.718370]
8/8 [==============================] - 0s 4ms/step
9918 [D loss: 0.691710, acc.: 46.09%] [G loss: 0.716800]
8/8 [==============================] - 0s 4ms/step
9919 [D loss: 0.690325, acc.: 44.92%] [G loss: 0.719639]
8/8 [==============================] - 0s 5ms/step
9920 [D loss: 0.696186, acc.: 48.83%] [G loss: 0.727829]
8/8 [==============================] - 0s 4ms/step
9921 [D loss: 0.703571, acc.: 44.53%] [G loss: 0.736813]
8/8 [==============================] - 0s 4ms/step
9922 [D loss: 0.693405, acc.: 46.48%] [G loss: 0.753017]
8/8 [==============================] - 0s 4ms/step
9923 [D loss: 0.692122, acc.: 53.52%] [G loss: 0.761256]
8/8 [==============================] - 0s 4ms/step
9924 [D loss: 0.689421, acc.: 55.08%] [G loss: 0.763694]
8/8 [==============================] - 0s 4ms/step
9925 [D loss: 0.693807, acc.: 51.37%] [G loss: 0.775163]
8/8 [==============================] - 0s 4ms/step
9926 [D loss: 0.688550, acc.: 52.15%] [G loss: 0.768215]
8/8 [==============================] - 0s 5ms/step
9927 [D loss: 0.692098, acc.: 49.41%] [G loss: 0.769349]
8/8 [==============================] - 0s 4ms/step
9928 [D loss: 0.684694, acc.: 54.10%] [G loss: 0.784646]
8/8 [==============================] - 0s 4ms/step
9929 [D loss: 0.686333, acc.: 51.95%] [G loss: 0.782353]
8/8 [==============================] - 0s 4ms/step
9930 [D loss: 0.689479, acc.: 51.56%] [G loss: 0.767494]
8/8 [==============================] - 0s 4ms/step
9931 [D loss: 0.672618, acc.: 58.79%] [G loss: 0.793837]
8/8 [==============================] - 0s 4ms/step
9932 [D loss: 0.700514, acc.: 46.48%] [G loss: 0.718772]
8/8 [==============================] - 0s 4ms/step
9933 [D loss: 0.694965, acc.: 46.09%] [G loss: 0.709783]
8/8 [==============================] - 0s 4ms/step
9934 [D loss: 0.689475, acc.: 48.44%] [G loss: 0.749532]
8/8 [==============================] - 0s 4ms/step
9935 [D loss: 0.684445, acc.: 52.15%] [G loss: 0.759150]
8/8 [==============================] - 0s 4ms/step
9936 [D loss: 0.679294, acc.: 50.20%] [G loss: 0.769511]
8/8 [==============================] - 0s 4ms/step
9937 [D loss: 0.686749, acc.: 46.88%] [G loss: 0.746150]
8/8 [==============================] - 0s 4ms/step
9938 [D loss: 0.689964, acc.: 49.80%] [G loss: 0.768580]
8/8 [==============================] - 0s 4ms/step
9939 [D loss: 0.686477, acc.: 51.37%] [G loss: 0.763762]
8/8 [==============================] - 0s 4ms/step
9940 [D loss: 0.668635, acc.: 59.57%] [G loss: 0.767783]
8/8 [==============================] - 0s 4ms/step
9941 [D loss: 0.684165, acc.: 46.88%] [G loss: 0.726479]
8/8 [==============================] - 0s 4ms/step
9942 [D loss: 0.680968, acc.: 51.95%] [G loss: 0.735395]
8/8 [==============================] - 0s 4ms/step
9943 [D loss: 0.690772, acc.: 48.24%] [G loss: 0.746412]
8/8 [==============================] - 0s 4ms/step
9944 [D loss: 0.675519, acc.: 47.27%] [G loss: 0.744588]
8/8 [==============================] - 0s 4ms/step
9945 [D loss: 0.679509, acc.: 53.91%] [G loss: 0.751541]
8/8 [==============================] - 0s 4ms/step
9946 [D loss: 0.679154, acc.: 51.95%] [G loss: 0.746769]
8/8 [==============================] - 0s 4ms/step
9947 [D loss: 0.693341, acc.: 49.22%] [G loss: 0.743254]
8/8 [==============================] - 0s 4ms/step
9948 [D loss: 0.697114, acc.: 43.95%] [G loss: 0.727815]
8/8 [==============================] - 0s 4ms/step
9949 [D loss: 0.682823, acc.: 50.98%] [G loss: 0.728190]
8/8 [==============================] - 0s 4ms/step
9950 [D loss: 0.687391, acc.: 50.00%] [G loss: 0.723266]
1/1 [==============================] - 0s 37ms/step
8/8 [==============================] - 0s 4ms/step
9951 [D loss: 0.700840, acc.: 39.65%] [G loss: 0.716987]
8/8 [==============================] - 0s 4ms/step
9952 [D loss: 0.686989, acc.: 48.44%] [G loss: 0.731965]
8/8 [==============================] - 0s 4ms/step
9953 [D loss: 0.683444, acc.: 51.17%] [G loss: 0.734980]
8/8 [==============================] - 0s 4ms/step
9954 [D loss: 0.691172, acc.: 50.39%] [G loss: 0.750540]
8/8 [==============================] - 0s 4ms/step
9955 [D loss: 0.692480, acc.: 49.02%] [G loss: 0.730501]
8/8 [==============================] - 0s 4ms/step
9956 [D loss: 0.718829, acc.: 49.02%] [G loss: 0.691162]
8/8 [==============================] - 0s 4ms/step
9957 [D loss: 0.706069, acc.: 46.68%] [G loss: 0.705809]
8/8 [==============================] - 0s 4ms/step
9958 [D loss: 0.698183, acc.: 44.34%] [G loss: 0.737074]
8/8 [==============================] - 0s 4ms/step
9959 [D loss: 0.686360, acc.: 49.02%] [G loss: 0.753998]
8/8 [==============================] - 0s 4ms/step
9960 [D loss: 0.686261, acc.: 53.52%] [G loss: 0.740589]
8/8 [==============================] - 0s 4ms/step
9961 [D loss: 0.688929, acc.: 51.37%] [G loss: 0.747868]
8/8 [==============================] - 0s 4ms/step
9962 [D loss: 0.687854, acc.: 47.85%] [G loss: 0.727234]
8/8 [==============================] - 0s 4ms/step
9963 [D loss: 0.690621, acc.: 47.66%] [G loss: 0.742723]
8/8 [==============================] - 0s 4ms/step
9964 [D loss: 0.690151, acc.: 49.80%] [G loss: 0.760750]
8/8 [==============================] - 0s 4ms/step
9965 [D loss: 0.685884, acc.: 50.98%] [G loss: 0.739094]
8/8 [==============================] - 0s 4ms/step
9966 [D loss: 0.688874, acc.: 49.61%] [G loss: 0.721708]
8/8 [==============================] - 0s 5ms/step
9967 [D loss: 0.692701, acc.: 50.39%] [G loss: 0.727572]
8/8 [==============================] - 0s 4ms/step
9968 [D loss: 0.696914, acc.: 46.29%] [G loss: 0.719609]
8/8 [==============================] - 0s 4ms/step
9969 [D loss: 0.685236, acc.: 50.00%] [G loss: 0.740082]
8/8 [==============================] - 0s 4ms/step
9970 [D loss: 0.687462, acc.: 49.41%] [G loss: 0.745374]
8/8 [==============================] - 0s 4ms/step
9971 [D loss: 0.688677, acc.: 47.85%] [G loss: 0.736249]
8/8 [==============================] - 0s 4ms/step
9972 [D loss: 0.686039, acc.: 51.56%] [G loss: 0.732021]
8/8 [==============================] - 0s 4ms/step
9973 [D loss: 0.697359, acc.: 47.66%] [G loss: 0.721219]
8/8 [==============================] - 0s 4ms/step
9974 [D loss: 0.700519, acc.: 46.68%] [G loss: 0.716620]
8/8 [==============================] - 0s 4ms/step
9975 [D loss: 0.707961, acc.: 46.48%] [G loss: 0.683270]
8/8 [==============================] - 0s 4ms/step
9976 [D loss: 0.705593, acc.: 48.83%] [G loss: 0.697429]
8/8 [==============================] - 0s 4ms/step
9977 [D loss: 0.695496, acc.: 47.07%] [G loss: 0.719499]
8/8 [==============================] - 0s 4ms/step
9978 [D loss: 0.691154, acc.: 51.37%] [G loss: 0.740910]
8/8 [==============================] - 0s 4ms/step
9979 [D loss: 0.680988, acc.: 53.52%] [G loss: 0.754176]
8/8 [==============================] - 0s 4ms/step
9980 [D loss: 0.688176, acc.: 50.20%] [G loss: 0.746997]
8/8 [==============================] - 0s 4ms/step
9981 [D loss: 0.684053, acc.: 52.34%] [G loss: 0.770381]
8/8 [==============================] - 0s 4ms/step
9982 [D loss: 0.681399, acc.: 54.88%] [G loss: 0.753794]
8/8 [==============================] - 0s 4ms/step
9983 [D loss: 0.682063, acc.: 54.10%] [G loss: 0.746377]
8/8 [==============================] - 0s 4ms/step
9984 [D loss: 0.686644, acc.: 49.22%] [G loss: 0.729927]
8/8 [==============================] - 0s 4ms/step
9985 [D loss: 0.681938, acc.: 51.17%] [G loss: 0.735992]
8/8 [==============================] - 0s 4ms/step
9986 [D loss: 0.676329, acc.: 53.71%] [G loss: 0.744013]
8/8 [==============================] - 0s 4ms/step
9987 [D loss: 0.677784, acc.: 51.37%] [G loss: 0.750335]
8/8 [==============================] - 0s 4ms/step
9988 [D loss: 0.684947, acc.: 43.16%] [G loss: 0.735570]
8/8 [==============================] - 0s 4ms/step
9989 [D loss: 0.695688, acc.: 45.70%] [G loss: 0.746807]
8/8 [==============================] - 0s 4ms/step
9990 [D loss: 0.677682, acc.: 48.63%] [G loss: 0.736330]
8/8 [==============================] - 0s 4ms/step
9991 [D loss: 0.680224, acc.: 46.88%] [G loss: 0.748999]
8/8 [==============================] - 0s 4ms/step
9992 [D loss: 0.686546, acc.: 50.00%] [G loss: 0.729154]
8/8 [==============================] - 0s 4ms/step
9993 [D loss: 0.681849, acc.: 48.44%] [G loss: 0.739243]
8/8 [==============================] - 0s 4ms/step
9994 [D loss: 0.675513, acc.: 50.98%] [G loss: 0.748405]
8/8 [==============================] - 0s 4ms/step
9995 [D loss: 0.680945, acc.: 49.61%] [G loss: 0.748479]
8/8 [==============================] - 0s 4ms/step
9996 [D loss: 0.682446, acc.: 53.32%] [G loss: 0.756552]
8/8 [==============================] - 0s 4ms/step
9997 [D loss: 0.665835, acc.: 55.47%] [G loss: 0.740264]
8/8 [==============================] - 0s 4ms/step
9998 [D loss: 0.678920, acc.: 50.59%] [G loss: 0.741509]
8/8 [==============================] - 0s 4ms/step
9999 [D loss: 0.681118, acc.: 48.63%] [G loss: 0.735608]

Plot Loss

plot_losses(cgan.d_losses, cgan.g_losses)

Plot Accuracy

plot_accuracy(cgan.d_accuracy)

Generated Images at Different Epochs (Remove Batch Normalization Layer from the Generator)

100 Epochs:

1000 Epochs:

2950 Epochs:

5000 Epochs:

10000 Epochs:

Results

The generator's loss fluctuates significantly during the first 1500 epochs, ranging from 4.5 to 23, before steadily decreasing to around 0.7. This fluctuation suggests that the generator's output quality varied widely early in training. Over time, as the generator's performance improved, the loss stabilized around 0.7.

The discriminator’s accuracy, initially high at around 90% for the first 1500 epochs, gradually decreased to a stable range of 50% to 60%. This decline indicates that as the generator improved, it became more challenging for the discriminator to differentiate between real and generated images, leading to a more balanced but less confident prediction.

About 90% of the classes are now distinguishable, and the quality of the images has improved. This is evident from the reduced number of patches in the generated alphabets, indicating clearer and more refined images.

Wasserstein GAN

What is Wasserstein GAN

---

Wasserstein Generative Adversarial Network (WGAN) is a variant of the standard GAN that aims to improve the stability of training and the quality of generated samples. WGANs use the Wasserstein distance (also known as Earth-Mover's distance) instead of the Jensen-Shannon (JS) divergence to measure the distance between the real and generated data distributions.

The generator's objective is to minimize the critic's score for the generated samples.

The critic's objective is to maximize the difference between its scores for real and generated samples.

Difference between WGAN and DCGAN

---

• WGAN can use various architectures for the generator and discriminator, similar to DCGAN. However, it requires a different discriminator called a "critic" that does not output probabilities but rather real-valued scores.

• WGAN uses the Wasserstein distance instead of the JS divergence.

• WGAN improves training stability by clipping the weights of the critic to enforce the Lipschitz constraint, which is required for the Wasserstein distance to be valid.

Why Wasserstein Distance Could Be Better than JS Divergence

---

Gradient Issues

JS divergence can lead to vanishing gradients when the real and generated distributions do not overlap significantly. The Wasserstein distance, on the other hand, provides meaningful gradients even when the distributions are disjoint, allowing for more stable and continuous training.

Training Stability

The Wasserstein distance has better theoretical properties that contribute to more stable training dynamics. It provides a smoother and more informative measure of the distance between distributions, leading to more reliable updates to the generator.

Mode Collapse

WGANs are less prone to mode collapse, a common problem in standard GANs where the generator produces a limited variety of outputs. The Wasserstein distance helps in maintaining diverse generations by providing better feedback to the generator about the quality of the generated samples.

---

References

https://jonathan-hui.medium.com/gan-wasserstein-gan-wgan-gp-6a1a2aa1b490

https://towardsdatascience.com/deep-convolutional-vs-wasserstein-generative-adversarial-network-183fbcfdce1f

https://stackoverflow.com/questions/62111642/difference-between-dcgan-wgan

https://www.geeksforgeeks.org/difference-between-gan-vs-dcgan/

Base Model

class WGAN():
    def __init__(self):
        self.img_rows = 28
        self.img_cols = 28
        self.channels = 1
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = 100

        # Following parameter and optimizer set as recommended in paper
        self.n_critic = 5
        self.clip_value = 0.01
        optimizer = RMSprop(lr=0.00005)

        # Build and compile the critic
        self.critic = self.build_critic()
        self.critic.compile(loss=self.wasserstein_loss,
            optimizer=optimizer,
            metrics=['accuracy'])

        # Build the generator
        self.generator = self.build_generator()

        # The generator takes noise as input and generated imgs
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)

        # For the combined model we will only train the generator
        self.critic.trainable = False

        # The critic takes generated images as input and determines validity
        valid = self.critic(img)

        # The combined model  (stacked generator and critic)
        self.combined = Model(z, valid)
        self.combined.compile(loss=self.wasserstein_loss,
            optimizer=optimizer,
            metrics=['accuracy'])

        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Wasserstein distance per epoch
        self.wasserstein_distances = []

    def wasserstein_loss(self, y_true, y_pred):
        return K.mean(y_true * y_pred)

    def build_generator(self):

        model = Sequential()

        model.add(Dense(128 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 128)))
        model.add(UpSampling2D())
        
        model.add(Conv2D(128, kernel_size=4, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        model.add(UpSampling2D())
        
        model.add(Conv2D(64, kernel_size=4, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(Conv2D(self.channels, kernel_size=4, padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)

    def build_critic(self):

        model = Sequential()

        model.add(Conv2D(16, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.25))
        model.add(Conv2D(32, kernel_size=3, strides=2, padding="same"))
        model.add(ZeroPadding2D(padding=((0,1),(0,1))))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.25))
        model.add(Conv2D(64, kernel_size=3, strides=2, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.25))
        model.add(Conv2D(128, kernel_size=3, strides=1, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.25))
        model.add(Flatten())
        model.add(Dense(1))

        model.summary()

        img = Input(shape=self.img_shape)
        validity = model(img)

        return Model(img, validity)

    def train(self, epochs, batch_size=128, sample_interval=50):

        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values
        y_train = preprocessed_df.iloc[:, 0].values
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)

        # Adversarial ground truths
        valid = -np.ones((batch_size, 1))
        fake = np.ones((batch_size, 1))

        for epoch in range(epochs):

            for _ in range(self.n_critic):

                # ---------------------
                #  Train Discriminator
                # ---------------------

                # Select a random batch of images
                idx = np.random.randint(0, X_train.shape[0], batch_size)
                imgs = X_train[idx]
                
                # Sample noise as generator input
                noise = np.random.normal(0, 1, (batch_size, self.latent_dim))

                # Generate a batch of new images
                gen_imgs = self.generator.predict(noise)

                # Train the critic
                d_loss_real = self.critic.train_on_batch(imgs, valid)
                d_loss_fake = self.critic.train_on_batch(gen_imgs, fake)
                d_loss = 0.5 * np.add(d_loss_fake, d_loss_real)

                # Clip critic weights
                for l in self.critic.layers:
                    weights = l.get_weights()
                    weights = [np.clip(w, -self.clip_value, self.clip_value) for w in weights]
                    l.set_weights(weights)


            # ---------------------
            #  Train Generator
            # ---------------------

            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Calculate and store Wasserstein distance for this epoch
            wasserstein_distance = -np.mean(self.d_losses[-self.n_critic:])  # Negative because we minimize negative loss
            self.wasserstein_distances.append(wasserstein_distance)
            
            # Plot the progress
            print ("%d [D loss: %f] [G loss: %f] [Wasserstein Distance: %f]" % (epoch, 1 - d_loss[0], 1 - g_loss[0], wasserstein_distance))

            # If at save interval => save generated image samples
            if epoch % sample_interval == 0:
                self.sample_images(epoch)

    def sample_images(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/wgan', exist_ok=True)
        os.makedirs('generated_images/wgan/base', exist_ok=True)
        fig.savefig("generated_images/wgan/base/wgan_{:d}.png".format(epoch))
        plt.close()

wgan = WGAN()
wgan.train(epochs=3000, batch_size=256, sample_interval=50)

Model: "sequential_10"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_35 (Conv2D)          (None, 14, 14, 16)        160       
                                                                 
 leaky_re_lu_36 (LeakyReLU)  (None, 14, 14, 16)        0         
                                                                 
 dropout_11 (Dropout)        (None, 14, 14, 16)        0         
                                                                 
 conv2d_36 (Conv2D)          (None, 7, 7, 32)          4640      
                                                                 
 zero_padding2d (ZeroPadding  (None, 8, 8, 32)         0         
 2D)                                                             
                                                                 
 batch_normalization_14 (Bat  (None, 8, 8, 32)         128       
 chNormalization)                                                
                                                                 
 leaky_re_lu_37 (LeakyReLU)  (None, 8, 8, 32)          0         
                                                                 
 dropout_12 (Dropout)        (None, 8, 8, 32)          0         
                                                                 
 conv2d_37 (Conv2D)          (None, 4, 4, 64)          18496     
                                                                 
 batch_normalization_15 (Bat  (None, 4, 4, 64)         256       
 chNormalization)                                                
                                                                 
 leaky_re_lu_38 (LeakyReLU)  (None, 4, 4, 64)          0         
                                                                 
 dropout_13 (Dropout)        (None, 4, 4, 64)          0         
                                                                 
 conv2d_38 (Conv2D)          (None, 4, 4, 128)         73856     
                                                                 
 batch_normalization_16 (Bat  (None, 4, 4, 128)        512       
 chNormalization)                                                
                                                                 
 leaky_re_lu_39 (LeakyReLU)  (None, 4, 4, 128)         0         
                                                                 
 dropout_14 (Dropout)        (None, 4, 4, 128)         0         
                                                                 
 flatten_13 (Flatten)        (None, 2048)              0         
                                                                 
 dense_20 (Dense)            (None, 1)                 2049      
                                                                 
=================================================================
Total params: 100,097
Trainable params: 99,649
Non-trainable params: 448
_________________________________________________________________
Model: "sequential_11"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_21 (Dense)            (None, 6272)              633472    
                                                                 
 reshape_10 (Reshape)        (None, 7, 7, 128)         0         
                                                                 
 up_sampling2d_8 (UpSampling  (None, 14, 14, 128)      0         
 2D)                                                             
                                                                 
 conv2d_39 (Conv2D)          (None, 14, 14, 128)       262272    
                                                                 
 batch_normalization_17 (Bat  (None, 14, 14, 128)      512       
 chNormalization)                                                
                                                                 
 activation_11 (Activation)  (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_9 (UpSampling  (None, 28, 28, 128)      0         
 2D)                                                             
                                                                 
 conv2d_40 (Conv2D)          (None, 28, 28, 64)        131136    
                                                                 
 batch_normalization_18 (Bat  (None, 28, 28, 64)       256       
 chNormalization)                                                
                                                                 
 activation_12 (Activation)  (None, 28, 28, 64)        0         
                                                                 
 conv2d_41 (Conv2D)          (None, 28, 28, 1)         1025      
                                                                 
 activation_13 (Activation)  (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 1,028,673
Trainable params: 1,028,289
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
0 [D loss: 0.999919] [G loss: 1.000214] [Wasserstein Distance: -0.000081]
1/1 [==============================] - 0s 107ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1 [D loss: 0.999923] [G loss: 1.000174] [Wasserstein Distance: -0.000079]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2 [D loss: 0.999925] [G loss: 1.000164] [Wasserstein Distance: -0.000078]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
3 [D loss: 0.999923] [G loss: 1.000157] [Wasserstein Distance: -0.000078]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
4 [D loss: 0.999923] [G loss: 1.000156] [Wasserstein Distance: -0.000077]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
5 [D loss: 0.999924] [G loss: 1.000153] [Wasserstein Distance: -0.000077]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
6 [D loss: 0.999924] [G loss: 1.000155] [Wasserstein Distance: -0.000076]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
7 [D loss: 0.999926] [G loss: 1.000152] [Wasserstein Distance: -0.000076]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8 [D loss: 0.999925] [G loss: 1.000147] [Wasserstein Distance: -0.000076]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
9 [D loss: 0.999926] [G loss: 1.000146] [Wasserstein Distance: -0.000075]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
10 [D loss: 0.999925] [G loss: 1.000142] [Wasserstein Distance: -0.000075]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
11 [D loss: 0.999925] [G loss: 1.000138] [Wasserstein Distance: -0.000075]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
12 [D loss: 0.999927] [G loss: 1.000136] [Wasserstein Distance: -0.000075]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
13 [D loss: 0.999928] [G loss: 1.000131] [Wasserstein Distance: -0.000074]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
14 [D loss: 0.999930] [G loss: 1.000128] [Wasserstein Distance: -0.000073]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
15 [D loss: 0.999933] [G loss: 1.000119] [Wasserstein Distance: -0.000071]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
16 [D loss: 0.999939] [G loss: 1.000111] [Wasserstein Distance: -0.000068]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
17 [D loss: 0.999941] [G loss: 1.000103] [Wasserstein Distance: -0.000066]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
18 [D loss: 0.999944] [G loss: 1.000100] [Wasserstein Distance: -0.000062]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
19 [D loss: 0.999946] [G loss: 1.000096] [Wasserstein Distance: -0.000059]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
20 [D loss: 0.999948] [G loss: 1.000092] [Wasserstein Distance: -0.000056]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
21 [D loss: 0.999953] [G loss: 1.000082] [Wasserstein Distance: -0.000053]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
22 [D loss: 0.999952] [G loss: 1.000077] [Wasserstein Distance: -0.000051]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
23 [D loss: 0.999957] [G loss: 1.000074] [Wasserstein Distance: -0.000049]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
24 [D loss: 0.999958] [G loss: 1.000073] [Wasserstein Distance: -0.000046]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
25 [D loss: 0.999961] [G loss: 1.000070] [Wasserstein Distance: -0.000044]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
26 [D loss: 0.999961] [G loss: 1.000070] [Wasserstein Distance: -0.000042]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
27 [D loss: 0.999963] [G loss: 1.000072] [Wasserstein Distance: -0.000040]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
28 [D loss: 0.999965] [G loss: 1.000071] [Wasserstein Distance: -0.000038]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
29 [D loss: 0.999966] [G loss: 1.000069] [Wasserstein Distance: -0.000037]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
30 [D loss: 0.999967] [G loss: 1.000069] [Wasserstein Distance: -0.000036]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
31 [D loss: 0.999968] [G loss: 1.000069] [Wasserstein Distance: -0.000034]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
32 [D loss: 0.999969] [G loss: 1.000070] [Wasserstein Distance: -0.000033]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
33 [D loss: 0.999970] [G loss: 1.000069] [Wasserstein Distance: -0.000032]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
34 [D loss: 0.999970] [G loss: 1.000069] [Wasserstein Distance: -0.000031]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
35 [D loss: 0.999971] [G loss: 1.000069] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
36 [D loss: 0.999971] [G loss: 1.000068] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
37 [D loss: 0.999971] [G loss: 1.000067] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
38 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
39 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
40 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
41 [D loss: 0.999972] [G loss: 1.000069] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
42 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
43 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
44 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
45 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
46 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
47 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
48 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
49 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
50 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
51 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
52 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
53 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
54 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
55 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
56 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
57 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
58 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
59 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
60 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
61 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
62 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
63 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
64 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
65 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
66 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
67 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
68 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
69 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
70 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
71 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
72 [D loss: 0.999979] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
73 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
74 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
75 [D loss: 0.999979] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
76 [D loss: 0.999979] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
77 [D loss: 0.999979] [G loss: 1.000056] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
78 [D loss: 0.999980] [G loss: 1.000053] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
79 [D loss: 0.999981] [G loss: 1.000051] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
80 [D loss: 0.999983] [G loss: 1.000051] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
81 [D loss: 0.999981] [G loss: 1.000053] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
82 [D loss: 0.999982] [G loss: 1.000049] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
83 [D loss: 0.999982] [G loss: 1.000044] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
84 [D loss: 0.999984] [G loss: 1.000048] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
85 [D loss: 0.999983] [G loss: 1.000039] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
86 [D loss: 0.999983] [G loss: 1.000041] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
87 [D loss: 0.999984] [G loss: 1.000044] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
88 [D loss: 0.999985] [G loss: 1.000038] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
89 [D loss: 0.999985] [G loss: 1.000034] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
90 [D loss: 0.999985] [G loss: 1.000034] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
91 [D loss: 0.999986] [G loss: 1.000034] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
92 [D loss: 0.999986] [G loss: 1.000037] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
93 [D loss: 0.999986] [G loss: 1.000036] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
94 [D loss: 0.999987] [G loss: 1.000036] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
95 [D loss: 0.999989] [G loss: 1.000037] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
96 [D loss: 0.999993] [G loss: 1.000036] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
97 [D loss: 0.999995] [G loss: 1.000035] [Wasserstein Distance: -0.000010]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
98 [D loss: 0.999993] [G loss: 1.000041] [Wasserstein Distance: -0.000009]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
99 [D loss: 0.999996] [G loss: 1.000033] [Wasserstein Distance: -0.000007]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
100 [D loss: 0.999996] [G loss: 1.000038] [Wasserstein Distance: -0.000005]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
101 [D loss: 0.999999] [G loss: 1.000030] [Wasserstein Distance: -0.000004]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
102 [D loss: 0.999999] [G loss: 1.000034] [Wasserstein Distance: -0.000003]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
103 [D loss: 0.999996] [G loss: 1.000039] [Wasserstein Distance: -0.000003]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
104 [D loss: 0.999999] [G loss: 1.000038] [Wasserstein Distance: -0.000002]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
105 [D loss: 0.999999] [G loss: 1.000037] [Wasserstein Distance: -0.000002]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
106 [D loss: 1.000002] [G loss: 1.000043] [Wasserstein Distance: -0.000001]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
107 [D loss: 0.999998] [G loss: 1.000046] [Wasserstein Distance: -0.000001]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
108 [D loss: 1.000003] [G loss: 1.000039] [Wasserstein Distance: 0.000000]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
109 [D loss: 0.999999] [G loss: 1.000044] [Wasserstein Distance: 0.000000]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
110 [D loss: 0.999995] [G loss: 1.000044] [Wasserstein Distance: -0.000000]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
111 [D loss: 0.999996] [G loss: 1.000044] [Wasserstein Distance: -0.000002]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
112 [D loss: 0.999992] [G loss: 1.000051] [Wasserstein Distance: -0.000003]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
113 [D loss: 0.999996] [G loss: 1.000048] [Wasserstein Distance: -0.000004]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
114 [D loss: 0.999990] [G loss: 1.000053] [Wasserstein Distance: -0.000006]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
115 [D loss: 0.999991] [G loss: 1.000054] [Wasserstein Distance: -0.000007]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
116 [D loss: 0.999990] [G loss: 1.000054] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
117 [D loss: 0.999991] [G loss: 1.000059] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
118 [D loss: 0.999991] [G loss: 1.000059] [Wasserstein Distance: -0.000009]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
119 [D loss: 0.999990] [G loss: 1.000058] [Wasserstein Distance: -0.000009]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
120 [D loss: 0.999987] [G loss: 1.000056] [Wasserstein Distance: -0.000010]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
121 [D loss: 0.999988] [G loss: 1.000059] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
122 [D loss: 0.999985] [G loss: 1.000058] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
123 [D loss: 0.999988] [G loss: 1.000057] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
124 [D loss: 0.999980] [G loss: 1.000060] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
125 [D loss: 0.999981] [G loss: 1.000061] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
126 [D loss: 0.999984] [G loss: 1.000057] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
127 [D loss: 0.999982] [G loss: 1.000060] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
128 [D loss: 0.999981] [G loss: 1.000056] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
129 [D loss: 0.999982] [G loss: 1.000060] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
130 [D loss: 0.999981] [G loss: 1.000061] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
131 [D loss: 0.999982] [G loss: 1.000060] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
132 [D loss: 0.999982] [G loss: 1.000059] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
133 [D loss: 0.999980] [G loss: 1.000057] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
134 [D loss: 0.999981] [G loss: 1.000061] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
135 [D loss: 0.999978] [G loss: 1.000059] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
136 [D loss: 0.999978] [G loss: 1.000056] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
137 [D loss: 0.999979] [G loss: 1.000060] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
138 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
139 [D loss: 0.999980] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
140 [D loss: 0.999980] [G loss: 1.000057] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
141 [D loss: 0.999978] [G loss: 1.000058] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
142 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
143 [D loss: 0.999979] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
144 [D loss: 0.999979] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
145 [D loss: 0.999978] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
146 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
147 [D loss: 0.999978] [G loss: 1.000058] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 30ms/step
148 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
149 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
150 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 30ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
151 [D loss: 0.999980] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
152 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
153 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
154 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
155 [D loss: 0.999979] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
156 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
157 [D loss: 0.999980] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
158 [D loss: 0.999979] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
159 [D loss: 0.999976] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
160 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
161 [D loss: 0.999980] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
162 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
163 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
164 [D loss: 0.999979] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
165 [D loss: 0.999977] [G loss: 1.000058] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
166 [D loss: 0.999980] [G loss: 1.000057] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
167 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
168 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
169 [D loss: 0.999979] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
170 [D loss: 0.999978] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
171 [D loss: 0.999980] [G loss: 1.000058] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
172 [D loss: 0.999980] [G loss: 1.000059] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
173 [D loss: 0.999982] [G loss: 1.000059] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
174 [D loss: 0.999980] [G loss: 1.000059] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
175 [D loss: 0.999980] [G loss: 1.000059] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
176 [D loss: 0.999980] [G loss: 1.000058] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
177 [D loss: 0.999980] [G loss: 1.000058] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
178 [D loss: 0.999978] [G loss: 1.000058] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
179 [D loss: 0.999980] [G loss: 1.000059] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
180 [D loss: 0.999981] [G loss: 1.000060] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
181 [D loss: 0.999980] [G loss: 1.000057] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
182 [D loss: 0.999979] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
183 [D loss: 0.999980] [G loss: 1.000059] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
184 [D loss: 0.999979] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
185 [D loss: 0.999981] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
186 [D loss: 0.999979] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
187 [D loss: 0.999980] [G loss: 1.000062] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
188 [D loss: 0.999979] [G loss: 1.000062] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
189 [D loss: 0.999978] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
190 [D loss: 0.999981] [G loss: 1.000062] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
191 [D loss: 0.999980] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
192 [D loss: 0.999980] [G loss: 1.000067] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
193 [D loss: 0.999981] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
194 [D loss: 0.999982] [G loss: 1.000064] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
195 [D loss: 0.999981] [G loss: 1.000064] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
196 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
197 [D loss: 0.999980] [G loss: 1.000064] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
198 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
199 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
200 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 33ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
201 [D loss: 0.999978] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
202 [D loss: 0.999979] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
203 [D loss: 0.999980] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
204 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
205 [D loss: 0.999980] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
206 [D loss: 0.999979] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
207 [D loss: 0.999978] [G loss: 1.000065] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
208 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
209 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
210 [D loss: 0.999978] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
211 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
212 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
213 [D loss: 0.999979] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
214 [D loss: 0.999979] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
215 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
216 [D loss: 0.999978] [G loss: 1.000066] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
217 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
218 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
219 [D loss: 0.999981] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
220 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
221 [D loss: 0.999980] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
222 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
223 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
224 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
225 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
226 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
227 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
228 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
229 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
230 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
231 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
232 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
233 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
234 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
235 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
236 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
237 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
238 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
239 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
240 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
241 [D loss: 0.999978] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
242 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
243 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
244 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
245 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
246 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
247 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
248 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
249 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
250 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 34ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
251 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
252 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
253 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
254 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
255 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
256 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
257 [D loss: 0.999972] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
258 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
259 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
260 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
261 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
262 [D loss: 0.999974] [G loss: 1.000057] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
263 [D loss: 0.999976] [G loss: 1.000057] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
264 [D loss: 0.999973] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
265 [D loss: 0.999973] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
266 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
267 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
268 [D loss: 0.999974] [G loss: 1.000057] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
269 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
270 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
271 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
272 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
273 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
274 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
275 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
276 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
277 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
278 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
279 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
280 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
281 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
282 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
283 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
284 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
285 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
286 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
287 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
288 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
289 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
290 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
291 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
292 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
293 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
294 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
295 [D loss: 0.999972] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
296 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
297 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
298 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
299 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
300 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 35ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
301 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
302 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
303 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
304 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
305 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
306 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
307 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
308 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
309 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
310 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
311 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
312 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
313 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
314 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
315 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
316 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
317 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
318 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
319 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
320 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
321 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
322 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
323 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
324 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
325 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
326 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
327 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
328 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
329 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
330 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
331 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
332 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
333 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
334 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
335 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
336 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
337 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
338 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
339 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
340 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
341 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
342 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
343 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
344 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
345 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
346 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
347 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
348 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
349 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
350 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 31ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
351 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
352 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
353 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
354 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
355 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
356 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
357 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
358 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
359 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
360 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
361 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
362 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
363 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
364 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
365 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
366 [D loss: 0.999971] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
367 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
368 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
369 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
370 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
371 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
372 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
373 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
374 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
375 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
376 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
377 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
378 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
379 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
380 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
381 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
382 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
383 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
384 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
385 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
386 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
387 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
388 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
389 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
390 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
391 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
392 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
393 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
394 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
395 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
396 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
397 [D loss: 0.999972] [G loss: 1.000060] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
398 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
399 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
400 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
401 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
402 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
403 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
404 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
405 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
406 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
407 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
408 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
409 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
410 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
411 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
412 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
413 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
414 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
415 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
416 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
417 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
418 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
419 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
420 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
421 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
422 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
423 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
424 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
425 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
426 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
427 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
428 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
429 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
430 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
431 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
432 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
433 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
434 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
435 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
436 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
437 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
438 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
439 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
440 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
441 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
442 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
443 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
444 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
445 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
446 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
447 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
448 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
449 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
450 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
451 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
452 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
453 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
454 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
455 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
456 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
457 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
458 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
459 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
460 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
461 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
462 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
463 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
464 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
465 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
466 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
467 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
468 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
469 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
470 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
471 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
472 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
473 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
474 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
475 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
476 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
477 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
478 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
479 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
480 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
481 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
482 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
483 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
484 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
485 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
486 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
487 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
488 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
489 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
490 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
491 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
492 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
493 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
494 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
495 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
496 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
497 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
498 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
499 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
500 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
501 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
502 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
503 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
504 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
505 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
506 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
507 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
508 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
509 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
510 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
511 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
512 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
513 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
514 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
515 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
516 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
517 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
518 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
519 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
520 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
521 [D loss: 0.999973] [G loss: 1.000058] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
522 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
523 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
524 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
525 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
526 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
527 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
528 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
529 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
530 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
531 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
532 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
533 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
534 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
535 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
536 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
537 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
538 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
539 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
540 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
541 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
542 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
543 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
544 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
545 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
546 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
547 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
548 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
549 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
550 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
551 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
552 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
553 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
554 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
555 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
556 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
557 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
558 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
559 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
560 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
561 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
562 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
563 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
564 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
565 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
566 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
567 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
568 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
569 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
570 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
571 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
572 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
573 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
574 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
575 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
576 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
577 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
578 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
579 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
580 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
581 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
582 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
583 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
584 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
585 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
586 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
587 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
588 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
589 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
590 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
591 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
592 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
593 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
594 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
595 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
596 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
597 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
598 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
599 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
600 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 36ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
601 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
602 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
603 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
604 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
605 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
606 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
607 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
608 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
609 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
610 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
611 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
612 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
613 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
614 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
615 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
616 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
617 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
618 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
619 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
620 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
621 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
622 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
623 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
624 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
625 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
626 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
627 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
628 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
629 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
630 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
631 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
632 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
633 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
634 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
635 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
636 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
637 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
638 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
639 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
640 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
641 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
642 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
643 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
644 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
645 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
646 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
647 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
648 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
649 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
650 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 36ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
651 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
652 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
653 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
654 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
655 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
656 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
657 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
658 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
659 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
660 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
661 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
662 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
663 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
664 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
665 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
666 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
667 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
668 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
669 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
670 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
671 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
672 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
673 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
674 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
675 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
676 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
677 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
678 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
679 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
680 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
681 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
682 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
683 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
684 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
685 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
686 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
687 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
688 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
689 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
690 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
691 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
692 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
693 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
694 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
695 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
696 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
697 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
698 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
699 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
700 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 34ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
701 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
702 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
703 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
704 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
705 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
706 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
707 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
708 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
709 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
710 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
711 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
712 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
713 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
714 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
715 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
716 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
717 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
718 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
719 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
720 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
721 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
722 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
723 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
724 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
725 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
726 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
727 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
728 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
729 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
730 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
731 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
732 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
733 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
734 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
735 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
736 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
737 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
738 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
739 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
740 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
741 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
742 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
743 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
744 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
745 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
746 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
747 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
748 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
749 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
750 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 33ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
751 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
752 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
753 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
754 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
755 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
756 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
757 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
758 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
759 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
760 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
761 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
762 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
763 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
764 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
765 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
766 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
767 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
768 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
769 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
770 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
771 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
772 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
773 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
774 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
775 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
776 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
777 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
778 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
779 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
780 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
781 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
782 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
783 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
784 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
785 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
786 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
787 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
788 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
789 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
790 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
791 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
792 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
793 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
794 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
795 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
796 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
797 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
798 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
799 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
800 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 30ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
801 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
802 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
803 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
804 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
805 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
806 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
807 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
808 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
809 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
810 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
811 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
812 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
813 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
814 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
815 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
816 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
817 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
818 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
819 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
820 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
821 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
822 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
823 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
824 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
825 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
826 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
827 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
828 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
829 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
830 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
831 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
832 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
833 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
834 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
835 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
836 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
837 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
838 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
839 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
840 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
841 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
842 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
843 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
844 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
845 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
846 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
847 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
848 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
849 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
850 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 31ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
851 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
852 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
853 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
854 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
855 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
856 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
857 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
858 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
859 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
860 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
861 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
862 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
863 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
864 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
865 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
866 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
867 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
868 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
869 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
870 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
871 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
872 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
873 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
874 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
875 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
876 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
877 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
878 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
879 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
880 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
881 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
882 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
883 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
884 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
885 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
886 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
887 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
888 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
889 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
890 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
891 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
892 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
893 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
894 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
895 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
896 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
897 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
898 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
899 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
900 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 35ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
901 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
902 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
903 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
904 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
905 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
906 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
907 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
908 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
909 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
910 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
911 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
912 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
913 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
914 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
915 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
916 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
917 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
918 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
919 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
920 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
921 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
922 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
923 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
924 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
925 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
926 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
927 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
928 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
929 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
930 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
931 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
932 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
933 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
934 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
935 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
936 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
937 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
938 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
939 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
940 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
941 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
942 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
943 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
944 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
945 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
946 [D loss: 0.999971] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
947 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
948 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
949 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
950 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
1/1 [==============================] - 0s 37ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
951 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
952 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
953 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
954 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
955 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
956 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
957 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
958 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
959 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
960 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
961 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
962 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
963 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
964 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
965 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
966 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
967 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
968 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
969 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
970 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
971 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
972 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
973 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
974 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
975 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
976 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
977 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
978 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
979 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
980 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
981 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
982 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
983 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
984 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
985 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
986 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
987 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
988 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
989 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
990 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 5ms/step
991 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
992 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
993 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
994 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
995 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
996 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
997 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
998 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
999 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
1000 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 33ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1001 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1002 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1003 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1004 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1005 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1006 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1007 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1008 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
1009 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1010 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1011 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1012 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1013 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1014 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1015 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1016 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1017 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1018 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1019 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1020 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1021 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1022 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1023 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1024 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1025 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1026 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1027 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1028 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1029 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1030 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1031 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1032 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1033 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1034 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1035 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1036 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1037 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1038 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1039 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1040 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1041 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1042 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1043 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1044 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1045 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1046 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1047 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1048 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1049 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1050 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1051 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1052 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1053 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1054 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1055 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1056 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1057 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1058 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1059 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1060 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1061 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1062 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1063 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1064 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1065 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
1066 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1067 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1068 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1069 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1070 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1071 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1072 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1073 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1074 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1075 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1076 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1077 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1078 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1079 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1080 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1081 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1082 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
1083 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1084 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1085 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1086 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1087 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1088 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1089 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1090 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1091 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1092 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1093 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1094 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1095 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1096 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1097 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1098 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1099 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1100 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 36ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1101 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1102 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1103 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1104 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1105 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1106 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1107 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1108 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1109 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1110 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1111 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1112 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1113 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1114 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1115 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1116 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1117 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1118 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1119 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1120 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1121 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1122 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1123 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1124 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1125 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1126 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1127 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1128 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1129 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1130 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1131 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1132 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1133 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1134 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1135 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1136 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1137 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1138 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1139 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1140 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1141 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1142 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1143 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1144 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1145 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1146 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1147 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1148 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1149 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1150 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 40ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1151 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1152 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1153 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1154 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1155 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1156 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1157 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1158 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1159 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1160 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1161 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1162 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1163 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1164 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1165 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1166 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1167 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1168 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1169 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1170 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1171 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1172 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1173 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1174 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1175 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1176 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1177 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1178 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1179 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1180 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1181 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1182 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1183 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1184 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1185 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1186 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1187 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1188 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1189 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1190 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1191 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1192 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1193 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1194 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1195 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1196 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1197 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1198 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1199 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1200 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 32ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
1201 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1202 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1203 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1204 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1205 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1206 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1207 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1208 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 5ms/step
1209 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1210 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1211 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1212 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1213 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1214 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1215 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
1216 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1217 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1218 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1219 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1220 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1221 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1222 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1223 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1224 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1225 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1226 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1227 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1228 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1229 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1230 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1231 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1232 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1233 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1234 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1235 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1236 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1237 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1238 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1239 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1240 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1241 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1242 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1243 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1244 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1245 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1246 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1247 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1248 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1249 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1250 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 40ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1251 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1252 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1253 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1254 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1255 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1256 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1257 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1258 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1259 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1260 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1261 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1262 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1263 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1264 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1265 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1266 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1267 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1268 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1269 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1270 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1271 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1272 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1273 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1274 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1275 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1276 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1277 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1278 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1279 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1280 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1281 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1282 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1283 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1284 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1285 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1286 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1287 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1288 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1289 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1290 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1291 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1292 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1293 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1294 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1295 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1296 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1297 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1298 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1299 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1300 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 30ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1301 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1302 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1303 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1304 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1305 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1306 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1307 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1308 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1309 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1310 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1311 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1312 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1313 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1314 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1315 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1316 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1317 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1318 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1319 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1320 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1321 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1322 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1323 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1324 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1325 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1326 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1327 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1328 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1329 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1330 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1331 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1332 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1333 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1334 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1335 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1336 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1337 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1338 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1339 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1340 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1341 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1342 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1343 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1344 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1345 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1346 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1347 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1348 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1349 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1350 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 37ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1351 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1352 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1353 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1354 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1355 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1356 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1357 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1358 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1359 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1360 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1361 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1362 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1363 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1364 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1365 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1366 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1367 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1368 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1369 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1370 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1371 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1372 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1373 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1374 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1375 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1376 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1377 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1378 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1379 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1380 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1381 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1382 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1383 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1384 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1385 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1386 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1387 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1388 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1389 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1390 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1391 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1392 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1393 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1394 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1395 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1396 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1397 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1398 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
1399 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1400 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 33ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1401 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1402 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1403 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1404 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1405 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1406 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1407 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1408 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1409 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1410 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1411 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1412 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1413 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1414 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1415 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1416 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1417 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1418 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1419 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1420 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1421 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1422 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1423 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1424 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1425 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1426 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1427 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1428 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1429 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1430 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1431 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1432 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1433 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1434 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1435 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1436 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1437 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1438 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1439 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1440 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1441 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1442 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1443 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1444 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1445 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1446 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1447 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1448 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1449 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1450 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 40ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1451 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1452 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1453 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1454 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1455 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1456 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1457 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1458 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1459 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1460 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1461 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1462 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1463 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1464 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1465 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1466 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1467 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1468 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1469 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1470 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1471 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1472 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1473 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1474 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1475 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1476 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1477 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1478 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1479 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1480 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1481 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1482 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1483 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1484 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1485 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1486 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1487 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1488 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1489 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1490 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1491 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1492 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1493 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1494 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1495 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1496 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1497 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1498 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1499 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1500 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 39ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1501 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1502 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1503 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1504 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1505 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1506 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1507 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1508 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1509 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1510 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1511 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1512 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1513 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1514 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1515 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
1516 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1517 [D loss: 0.999973] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1518 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1519 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1520 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1521 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1522 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1523 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1524 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1525 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1526 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1527 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1528 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1529 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1530 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1531 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1532 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1533 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1534 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1535 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1536 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1537 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1538 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1539 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1540 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1541 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1542 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1543 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1544 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1545 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1546 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1547 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1548 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1549 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
1550 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 34ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1551 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1552 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1553 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1554 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1555 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1556 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1557 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1558 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1559 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1560 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1561 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1562 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1563 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1564 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1565 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1566 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1567 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1568 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1569 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1570 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1571 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1572 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1573 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1574 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1575 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1576 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1577 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1578 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1579 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1580 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1581 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1582 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1583 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1584 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1585 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1586 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1587 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1588 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1589 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1590 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1591 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1592 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1593 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1594 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1595 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1596 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1597 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1598 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1599 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1600 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 34ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1601 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1602 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1603 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1604 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1605 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1606 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1607 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1608 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1609 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1610 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1611 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1612 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1613 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1614 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1615 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1616 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1617 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1618 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1619 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1620 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1621 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1622 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1623 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1624 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1625 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
1626 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1627 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1628 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1629 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1630 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1631 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1632 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1633 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1634 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1635 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1636 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1637 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1638 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1639 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1640 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1641 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1642 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1643 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1644 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1645 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1646 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1647 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1648 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1649 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1650 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 47ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1651 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1652 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1653 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1654 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1655 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1656 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1657 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
1658 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1659 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1660 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1661 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1662 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1663 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1664 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1665 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1666 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1667 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1668 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1669 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1670 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1671 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1672 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1673 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1674 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1675 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1676 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1677 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1678 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1679 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1680 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1681 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1682 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1683 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1684 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1685 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1686 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1687 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
1688 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1689 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
1690 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1691 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1692 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1693 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1694 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1695 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1696 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1697 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1698 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1699 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1700 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 34ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 11ms/step
1701 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1702 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1703 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1704 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1705 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1706 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1707 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1708 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1709 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1710 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1711 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1712 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1713 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1714 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1715 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1716 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1717 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1718 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1719 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1720 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1721 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1722 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1723 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1724 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1725 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1726 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1727 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1728 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1729 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1730 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1731 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1732 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1733 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1734 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1735 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1736 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1737 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1738 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1739 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1740 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1741 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1742 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1743 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1744 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1745 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1746 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1747 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1748 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1749 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1750 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 41ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1751 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1752 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1753 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1754 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1755 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1756 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
1757 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1758 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
1759 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1760 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1761 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1762 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1763 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1764 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1765 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1766 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1767 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1768 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1769 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1770 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1771 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1772 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1773 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1774 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1775 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1776 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1777 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1778 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1779 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1780 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1781 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1782 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1783 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1784 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1785 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1786 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1787 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1788 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1789 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1790 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1791 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1792 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1793 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1794 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1795 [D loss: 0.999972] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1796 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1797 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1798 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1799 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1800 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 39ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1801 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1802 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1803 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1804 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1805 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1806 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1807 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1808 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1809 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1810 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1811 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1812 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1813 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1814 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1815 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1816 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1817 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1818 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1819 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1820 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1821 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1822 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1823 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1824 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
1825 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1826 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1827 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1828 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1829 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1830 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1831 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1832 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1833 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1834 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1835 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1836 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1837 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1838 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1839 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1840 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1841 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1842 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
1843 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1844 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1845 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1846 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1847 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1848 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1849 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1850 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 36ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1851 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1852 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1853 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
1854 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1855 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1856 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1857 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1858 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1859 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1860 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1861 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1862 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1863 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1864 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1865 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1866 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1867 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1868 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1869 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1870 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1871 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1872 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1873 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1874 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1875 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1876 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1877 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1878 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1879 [D loss: 0.999971] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1880 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1881 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1882 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1883 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1884 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1885 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1886 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1887 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1888 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1889 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1890 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1891 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1892 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1893 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1894 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1895 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1896 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1897 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1898 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1899 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1900 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 39ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1901 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1902 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
1903 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1904 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1905 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1906 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1907 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1908 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1909 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1910 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1911 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
1912 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1913 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1914 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1915 [D loss: 0.999971] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
1916 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1917 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1918 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
1919 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1920 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1921 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1922 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1923 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1924 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1925 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1926 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1927 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1928 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
1929 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1930 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1931 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1932 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1933 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1934 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1935 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1936 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1937 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1938 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1939 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
1940 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1941 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1942 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1943 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1944 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1945 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1946 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1947 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1948 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1949 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
1950 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 41ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1951 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1952 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1953 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1954 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1955 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
1956 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1957 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1958 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1959 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1960 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1961 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1962 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1963 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1964 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
1965 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1966 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
1967 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1968 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
1969 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1970 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
1971 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1972 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1973 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1974 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1975 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1976 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1977 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1978 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1979 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1980 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1981 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1982 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1983 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1984 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1985 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1986 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
1987 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1988 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1989 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1990 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1991 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
1992 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1993 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1994 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1995 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1996 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
1997 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
1998 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
1999 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2000 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 42ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2001 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2002 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2003 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2004 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2005 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2006 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2007 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2008 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2009 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2010 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2011 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2012 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2013 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2014 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2015 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2016 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2017 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2018 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2019 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
2020 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2021 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2022 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2023 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2024 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2025 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2026 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2027 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2028 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2029 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2030 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2031 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2032 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2033 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2034 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2035 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2036 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2037 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2038 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2039 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2040 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2041 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2042 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2043 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2044 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2045 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
2046 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2047 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2048 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2049 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2050 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 38ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2051 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2052 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2053 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2054 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2055 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2056 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2057 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2058 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2059 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2060 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2061 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2062 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2063 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2064 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2065 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2066 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2067 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2068 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2069 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2070 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2071 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2072 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2073 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2074 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2075 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2076 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2077 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2078 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2079 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2080 [D loss: 0.999972] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2081 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2082 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2083 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2084 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2085 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2086 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2087 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2088 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2089 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2090 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2091 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2092 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2093 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2094 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2095 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2096 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2097 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2098 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2099 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2100 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 44ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2101 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2102 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2103 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2104 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2105 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2106 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2107 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2108 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2109 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2110 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2111 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2112 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2113 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2114 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2115 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2116 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2117 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2118 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2119 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2120 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2121 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2122 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2123 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2124 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2125 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
2126 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2127 [D loss: 0.999971] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2128 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2129 [D loss: 0.999970] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2130 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2131 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2132 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2133 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2134 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2135 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2136 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2137 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2138 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2139 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2140 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2141 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2142 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2143 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2144 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
2145 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2146 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2147 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2148 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2149 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2150 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 41ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2151 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2152 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2153 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2154 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2155 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2156 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2157 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2158 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2159 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2160 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2161 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2162 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2163 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2164 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2165 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2166 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2167 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2168 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2169 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2170 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2171 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2172 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2173 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2174 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2175 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2176 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2177 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2178 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2179 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2180 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2181 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2182 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2183 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2184 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2185 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2186 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2187 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2188 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2189 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2190 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2191 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2192 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2193 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2194 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2195 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2196 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2197 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2198 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2199 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2200 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 36ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2201 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2202 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2203 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2204 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2205 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2206 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2207 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2208 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2209 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2210 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2211 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2212 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
2213 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2214 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2215 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2216 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2217 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2218 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2219 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
2220 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2221 [D loss: 0.999972] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2222 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2223 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2224 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2225 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2226 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2227 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2228 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2229 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2230 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2231 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2232 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2233 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2234 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2235 [D loss: 0.999971] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2236 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2237 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2238 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2239 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2240 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2241 [D loss: 0.999971] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2242 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2243 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2244 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2245 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2246 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2247 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2248 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2249 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2250 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 38ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2251 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2252 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2253 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2254 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2255 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
2256 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2257 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2258 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2259 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2260 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2261 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2262 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
2263 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2264 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2265 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 4ms/step
2266 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2267 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2268 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2269 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2270 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2271 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2272 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2273 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2274 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2275 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2276 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2277 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2278 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2279 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2280 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2281 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2282 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2283 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2284 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2285 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2286 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2287 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2288 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2289 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2290 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2291 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2292 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2293 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2294 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2295 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2296 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2297 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2298 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2299 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2300 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 39ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2301 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2302 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2303 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2304 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2305 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2306 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2307 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2308 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2309 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2310 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2311 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2312 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2313 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2314 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2315 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2316 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2317 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2318 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2319 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2320 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2321 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2322 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2323 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2324 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2325 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2326 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2327 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2328 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2329 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2330 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2331 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2332 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2333 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2334 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2335 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2336 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2337 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2338 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2339 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2340 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2341 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2342 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2343 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2344 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2345 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2346 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2347 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2348 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2349 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2350 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 37ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2351 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2352 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2353 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2354 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2355 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2356 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2357 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2358 [D loss: 0.999972] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2359 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2360 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2361 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2362 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2363 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2364 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2365 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2366 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2367 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2368 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2369 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2370 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2371 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2372 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2373 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2374 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
2375 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2376 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2377 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2378 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2379 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2380 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2381 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2382 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2383 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2384 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2385 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2386 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2387 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2388 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2389 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2390 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2391 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2392 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2393 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2394 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2395 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2396 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2397 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2398 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2399 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2400 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 39ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2401 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2402 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2403 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2404 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2405 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2406 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2407 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2408 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2409 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2410 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2411 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2412 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2413 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2414 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2415 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2416 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2417 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2418 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2419 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2420 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2421 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2422 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2423 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2424 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2425 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2426 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2427 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2428 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2429 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2430 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2431 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2432 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2433 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2434 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2435 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2436 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2437 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2438 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2439 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2440 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2441 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2442 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2443 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2444 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2445 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2446 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2447 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2448 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2449 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2450 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 40ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 10ms/step
2451 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2452 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
2453 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2454 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2455 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2456 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2457 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2458 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2459 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2460 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2461 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2462 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2463 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2464 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2465 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2466 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2467 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2468 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2469 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2470 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2471 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2472 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2473 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2474 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2475 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2476 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2477 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2478 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2479 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2480 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2481 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2482 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2483 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2484 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2485 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2486 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2487 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2488 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2489 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2490 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2491 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2492 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2493 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2494 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2495 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2496 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2497 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2498 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2499 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2500 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 46ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2501 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2502 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2503 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2504 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2505 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2506 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2507 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2508 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2509 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2510 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2511 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2512 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2513 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2514 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2515 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2516 [D loss: 0.999971] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2517 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2518 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2519 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2520 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2521 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2522 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2523 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2524 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2525 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2526 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2527 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2528 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2529 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2530 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2531 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2532 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2533 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2534 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2535 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2536 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2537 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2538 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2539 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2540 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2541 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2542 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2543 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2544 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2545 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2546 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2547 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2548 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2549 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2550 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 45ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2551 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2552 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2553 [D loss: 0.999971] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2554 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2555 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2556 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2557 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2558 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
2559 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2560 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2561 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2562 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2563 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2564 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2565 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2566 [D loss: 0.999971] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2567 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2568 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2569 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2570 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2571 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2572 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2573 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2574 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2575 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2576 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2577 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2578 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2579 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2580 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2581 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2582 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2583 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2584 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2585 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2586 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2587 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2588 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2589 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2590 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2591 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2592 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2593 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2594 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2595 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2596 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2597 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2598 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2599 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2600 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 37ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2601 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2602 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2603 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2604 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2605 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2606 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2607 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2608 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2609 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2610 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2611 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2612 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2613 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2614 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2615 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2616 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2617 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2618 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2619 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2620 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2621 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2622 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2623 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2624 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2625 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2626 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2627 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2628 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2629 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2630 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2631 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2632 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2633 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2634 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2635 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2636 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2637 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2638 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2639 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2640 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2641 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2642 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2643 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2644 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2645 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2646 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2647 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2648 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2649 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2650 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 55ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2651 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2652 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2653 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
2654 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2655 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2656 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2657 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2658 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2659 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2660 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2661 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2662 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2663 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2664 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
2665 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2666 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2667 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2668 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2669 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2670 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2671 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2672 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2673 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2674 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2675 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2676 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2677 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2678 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2679 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2680 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2681 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2682 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2683 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2684 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2685 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2686 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2687 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2688 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2689 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2690 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2691 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2692 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2693 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2694 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2695 [D loss: 0.999971] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2696 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2697 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2698 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2699 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2700 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 46ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 7ms/step
2701 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2702 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2703 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2704 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2705 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2706 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2707 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2708 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2709 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2710 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2711 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2712 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2713 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2714 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2715 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2716 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 4ms/step
2717 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2718 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2719 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2720 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2721 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2722 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2723 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2724 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2725 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2726 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2727 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2728 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2729 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2730 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2731 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2732 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2733 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2734 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2735 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2736 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2737 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2738 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2739 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2740 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2741 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2742 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2743 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2744 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2745 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2746 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2747 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2748 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2749 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2750 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 33ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 7ms/step
2751 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2752 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
2753 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2754 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2755 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2756 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2757 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2758 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2759 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2760 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2761 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2762 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2763 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2764 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2765 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2766 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2767 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2768 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2769 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2770 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2771 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2772 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2773 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2774 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2775 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2776 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2777 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2778 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2779 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2780 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2781 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2782 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2783 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2784 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2785 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
2786 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2787 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2788 [D loss: 0.999971] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2789 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2790 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2791 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2792 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2793 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2794 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2795 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2796 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2797 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2798 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2799 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2800 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 40ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
2801 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2802 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2803 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2804 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2805 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2806 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2807 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2808 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2809 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2810 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2811 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2812 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2813 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2814 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2815 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
2816 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2817 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2818 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2819 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2820 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2821 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2822 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2823 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2824 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2825 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2826 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2827 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2828 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2829 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2830 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2831 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2832 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2833 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2834 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2835 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2836 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2837 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2838 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2839 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2840 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2841 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2842 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
2843 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2844 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2845 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2846 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2847 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2848 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2849 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2850 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 38ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 7ms/step
2851 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2852 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2853 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2854 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2855 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2856 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2857 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2858 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2859 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2860 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2861 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2862 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2863 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2864 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2865 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
2866 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2867 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2868 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2869 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2870 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2871 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2872 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2873 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
2874 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2875 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2876 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2877 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2878 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2879 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2880 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2881 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2882 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2883 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2884 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2885 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2886 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2887 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2888 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 3ms/step
2889 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2890 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2891 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2892 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2893 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2894 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2895 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2896 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2897 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2898 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2899 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2900 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 38ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2901 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2902 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2903 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2904 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2905 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2906 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2907 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2908 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2909 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2910 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2911 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2912 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2913 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2914 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2915 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2916 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2917 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2918 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2919 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2920 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2921 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2922 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2923 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2924 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2925 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2926 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2927 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2928 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2929 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2930 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2931 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2932 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2933 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2934 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2935 [D loss: 0.999970] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2936 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2937 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2938 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 3ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2939 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2940 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2941 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2942 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2943 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2944 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
2945 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2946 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
2947 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2948 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2949 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2950 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 41ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2951 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2952 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2953 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2954 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2955 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2956 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2957 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2958 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2959 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2960 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2961 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2962 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2963 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2964 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2965 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2966 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2967 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2968 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2969 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2970 [D loss: 0.999971] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2971 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2972 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2973 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2974 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2975 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2976 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2977 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2978 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2979 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2980 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2981 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2982 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2983 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
2984 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2985 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2986 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2987 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 9ms/step
2988 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2989 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2990 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2991 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
2992 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2993 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2994 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2995 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
2996 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2997 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 4ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 4ms/step
2998 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 5ms/step
8/8 [==============================] - 0s 6ms/step
8/8 [==============================] - 0s 6ms/step
2999 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000027]

Plot Loss

plot_losses(wgan.d_losses, wgan.g_losses)

Plot Wasserstein Distance

plot_wasserstein_distance(wgan.wasserstein_distances)

Generated Images at Different Epochs (Base Model)

At 100 Epochs

At 1000 Epochs

At 2950 Epochs

Results

Discriminator: The discriminator starts with a high training loss, indicating initial difficulty in distinguishing between real and generated images. This sharp drop in loss shows that the discriminator has significantly improved its ability to differentiate real from fake images. However, the subsequent increase before leveling off at a steady value of 0.00003 suggests that the discriminator has reached a point of equilibrium, where its performance has stabilized. Generator: The generator begins with a low negative loss, reflecting poor initial sample quality. The sudden increase in loss indicates an improvement in performance, although the generator is still producing samples that are not ideal. The stabilization of the generator's loss at 0.00006 suggests that while the generator has achieved a relative stability, it is still generating samples that could be further refined.

Wasserstein Distance The Wasserstein distance’s behavior indicates periods of instability followed by improved performance. A negative Wasserstein distance indicates successful training progress, as it shows that the generator is now producing samples that are closer to the real data distribution. The stabilization of the distance reflects that the generator and discriminator have reached a more balanced and effective state.

Generated Images The generated images exhibit noticeable improvement compared to earlier epochs, showing that the model has made progress in learning the data distribution. However, these images still lack clear details and do not closely resemble the real samples. This suggests that while the generator is learning, it is not yet producing high-quality images.

The training dynamics indicate that both the generator and discriminator have reached a point of relative stability, as evidenced by the stabilization of their respective losses and the Wasserstein distance. However, the generated images still fall short in quality and detail. This mismatch suggests that there is room for further improvement in the generator's performance. To further improve the quality of the generated images, we plan to experiment with using Tanh activation function with normalization to the range of (-1,1) instead of sigmoid (0,1).

Removing Dropout and Batchnormalization Layers From the Critic

Potential Improvements

Stability in Training:

Removing dropout and batch normalization layers can lead to more stable gradient updates. Dropout, while useful in regular neural networks to prevent overfitting, can introduce noise and instability in the gradients, which might disrupt the delicate balance required for effective WGAN training.

Preserving Gradient Flow:

Batch normalization can sometimes interfere with the learning process by altering the gradient flow through the network. Since WGANs rely on smooth and continuous updates to the weights to approximate the Wasserstein distance, ensuring an unimpeded gradient flow can lead to better convergence properties. By removing batch normalization, we allow the critic to provide more accurate gradient information to the generator.

Simplification of the Critic Architecture:

Simplifying the critic's architecture by removing dropout and batch normalization can lead to a more direct and effective learning process. This reduced complexity allows the critic to focus purely on distinguishing real and generated samples without the additional regularization constraints imposed by these layers.

class WGAN():
    def __init__(self):
        self.img_rows = 28
        self.img_cols = 28
        self.channels = 1
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = 100

        # Following parameter and optimizer set as recommended in paper
        self.n_critic = 5
        self.clip_value = 0.01
        optimizer = RMSprop(lr=0.00005)

        # Build and compile the critic
        self.critic = self.build_critic()
        self.critic.compile(loss=self.wasserstein_loss,
            optimizer=optimizer,
            metrics=['accuracy'])

        # Build the generator
        self.generator = self.build_generator()

        # The generator takes noise as input and generated imgs
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)

        # For the combined model we will only train the generator
        self.critic.trainable = False

        # The critic takes generated images as input and determines validity
        valid = self.critic(img)

        # The combined model  (stacked generator and critic)
        self.combined = Model(z, valid)
        self.combined.compile(loss=self.wasserstein_loss,
            optimizer=optimizer,
            metrics=['accuracy'])

        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Wasserstein distance per epoch
        self.wasserstein_distances = []

    def wasserstein_loss(self, y_true, y_pred):
        return K.mean(y_true * y_pred)

    def build_generator(self):

        model = Sequential()

        model.add(Dense(1500 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 1500)))
        model.add(UpSampling2D())
        
        model.add(Conv2D(128, kernel_size=4, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        model.add(UpSampling2D())
        
        model.add(Conv2D(64, kernel_size=4, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(Conv2D(self.channels, kernel_size=4, padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)

    def build_critic(self):

        model = Sequential()

        model.add(Conv2D(16, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Conv2D(32, kernel_size=3, strides=2, padding="same"))
        model.add(ZeroPadding2D(padding=((0,1),(0,1))))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Conv2D(64, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Conv2D(128, kernel_size=3, strides=1, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Flatten())
        model.add(Dense(1))

        model.summary()

        img = Input(shape=self.img_shape)
        validity = model(img)

        return Model(img, validity)

    def train(self, epochs, batch_size=128, sample_interval=50):

        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values
        y_train = preprocessed_df.iloc[:, 0].values
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)

        # Adversarial ground truths
        valid = -np.ones((batch_size, 1))
        fake = np.ones((batch_size, 1))

        for epoch in range(epochs):

            for _ in range(self.n_critic):

                # ---------------------
                #  Train Discriminator
                # ---------------------

                # Select a random batch of images
                idx = np.random.randint(0, X_train.shape[0], batch_size)
                imgs = X_train[idx]
                
                # Sample noise as generator input
                noise = np.random.normal(0, 1, (batch_size, self.latent_dim))

                # Generate a batch of new images
                gen_imgs = self.generator.predict(noise)

                # Train the critic
                d_loss_real = self.critic.train_on_batch(imgs, valid)
                d_loss_fake = self.critic.train_on_batch(gen_imgs, fake)
                d_loss = 0.5 * np.add(d_loss_fake, d_loss_real)

                # Clip critic weights
                for l in self.critic.layers:
                    weights = l.get_weights()
                    weights = [np.clip(w, -self.clip_value, self.clip_value) for w in weights]
                    l.set_weights(weights)

            # ---------------------
            #  Train Generator
            # ---------------------

            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Calculate and store Wasserstein distance for this epoch
            wasserstein_distance = -np.mean(self.d_losses[-self.n_critic:])  # Negative because we minimize negative loss
            self.wasserstein_distances.append(wasserstein_distance)
            
            # Plot the progress
            print ("%d [D loss: %f] [G loss: %f] [Wasserstein Distance: %f]" % (epoch, 1 - d_loss[0], 1 - g_loss[0], wasserstein_distance))

            # If at save interval => save generated image samples
            if epoch % sample_interval == 0:
                self.sample_images(epoch)

    def sample_images(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/wgan', exist_ok=True)
        os.makedirs('generated_images/wgan/rmvBatchDropout', exist_ok=True)
        fig.savefig("generated_images/wgan/rmvBatchDropout/wgan_{:d}.png".format(epoch))
        plt.close()

wgan = WGAN()
wgan.train(epochs=3000, batch_size=256, sample_interval=50)

Model: "sequential_12"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_42 (Conv2D)          (None, 14, 14, 16)        160       
                                                                 
 leaky_re_lu_40 (LeakyReLU)  (None, 14, 14, 16)        0         
                                                                 
 conv2d_43 (Conv2D)          (None, 7, 7, 32)          4640      
                                                                 
 zero_padding2d_1 (ZeroPaddi  (None, 8, 8, 32)         0         
 ng2D)                                                           
                                                                 
 leaky_re_lu_41 (LeakyReLU)  (None, 8, 8, 32)          0         
                                                                 
 conv2d_44 (Conv2D)          (None, 4, 4, 64)          18496     
                                                                 
 leaky_re_lu_42 (LeakyReLU)  (None, 4, 4, 64)          0         
                                                                 
 conv2d_45 (Conv2D)          (None, 4, 4, 128)         73856     
                                                                 
 leaky_re_lu_43 (LeakyReLU)  (None, 4, 4, 128)         0         
                                                                 
 flatten_14 (Flatten)        (None, 2048)              0         
                                                                 
 dense_22 (Dense)            (None, 1)                 2049      
                                                                 
=================================================================
Total params: 99,201
Trainable params: 99,201
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_13"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_23 (Dense)            (None, 73500)             7423500   
                                                                 
 reshape_11 (Reshape)        (None, 7, 7, 1500)        0         
                                                                 
 up_sampling2d_10 (UpSamplin  (None, 14, 14, 1500)     0         
 g2D)                                                            
                                                                 
 conv2d_46 (Conv2D)          (None, 14, 14, 128)       3072128   
                                                                 
 batch_normalization_19 (Bat  (None, 14, 14, 128)      512       
 chNormalization)                                                
                                                                 
 activation_14 (Activation)  (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_11 (UpSamplin  (None, 28, 28, 128)      0         
 g2D)                                                            
                                                                 
 conv2d_47 (Conv2D)          (None, 28, 28, 64)        131136    
                                                                 
 batch_normalization_20 (Bat  (None, 28, 28, 64)       256       
 chNormalization)                                                
                                                                 
 activation_15 (Activation)  (None, 28, 28, 64)        0         
                                                                 
 conv2d_48 (Conv2D)          (None, 28, 28, 1)         1025      
                                                                 
 activation_16 (Activation)  (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 10,628,557
Trainable params: 10,628,173
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 0s 19ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
0 [D loss: 0.999925] [G loss: 1.000147] [Wasserstein Distance: -0.000075]
1/1 [==============================] - 0s 125ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1 [D loss: 0.999935] [G loss: 1.000141] [Wasserstein Distance: -0.000070]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2 [D loss: 0.999936] [G loss: 1.000133] [Wasserstein Distance: -0.000068]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
3 [D loss: 0.999936] [G loss: 1.000131] [Wasserstein Distance: -0.000067]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
4 [D loss: 0.999935] [G loss: 1.000127] [Wasserstein Distance: -0.000067]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
5 [D loss: 0.999937] [G loss: 1.000126] [Wasserstein Distance: -0.000064]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
6 [D loss: 0.999940] [G loss: 1.000123] [Wasserstein Distance: -0.000063]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
7 [D loss: 0.999941] [G loss: 1.000120] [Wasserstein Distance: -0.000062]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8 [D loss: 0.999943] [G loss: 1.000117] [Wasserstein Distance: -0.000061]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
9 [D loss: 0.999946] [G loss: 1.000111] [Wasserstein Distance: -0.000059]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
10 [D loss: 0.999950] [G loss: 1.000109] [Wasserstein Distance: -0.000056]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
11 [D loss: 0.999950] [G loss: 1.000103] [Wasserstein Distance: -0.000054]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
12 [D loss: 0.999954] [G loss: 1.000099] [Wasserstein Distance: -0.000051]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
13 [D loss: 0.999959] [G loss: 1.000092] [Wasserstein Distance: -0.000048]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
14 [D loss: 0.999962] [G loss: 1.000082] [Wasserstein Distance: -0.000045]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
15 [D loss: 0.999968] [G loss: 1.000078] [Wasserstein Distance: -0.000041]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
16 [D loss: 0.999980] [G loss: 1.000060] [Wasserstein Distance: -0.000035]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
17 [D loss: 0.999990] [G loss: 1.000043] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
18 [D loss: 1.000004] [G loss: 1.000018] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
19 [D loss: 1.000018] [G loss: 0.999999] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
20 [D loss: 1.000033] [G loss: 0.999971] [Wasserstein Distance: 0.000005]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
21 [D loss: 1.000010] [G loss: 0.999966] [Wasserstein Distance: 0.000011]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
22 [D loss: 0.999966] [G loss: 1.000012] [Wasserstein Distance: 0.000006]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
23 [D loss: 0.999965] [G loss: 1.000047] [Wasserstein Distance: -0.000001]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
24 [D loss: 0.999982] [G loss: 1.000053] [Wasserstein Distance: -0.000009]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
25 [D loss: 1.000004] [G loss: 1.000037] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
26 [D loss: 1.000042] [G loss: 0.999994] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
27 [D loss: 1.000058] [G loss: 0.999980] [Wasserstein Distance: 0.000010]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
28 [D loss: 1.000073] [G loss: 0.999956] [Wasserstein Distance: 0.000032]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
29 [D loss: 1.000091] [G loss: 0.999931] [Wasserstein Distance: 0.000054]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
30 [D loss: 1.000067] [G loss: 0.999924] [Wasserstein Distance: 0.000066]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
31 [D loss: 1.000078] [G loss: 0.999920] [Wasserstein Distance: 0.000074]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
32 [D loss: 1.000020] [G loss: 0.999938] [Wasserstein Distance: 0.000066]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
33 [D loss: 0.999972] [G loss: 0.999969] [Wasserstein Distance: 0.000046]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
34 [D loss: 0.999978] [G loss: 0.999991] [Wasserstein Distance: 0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
35 [D loss: 0.999972] [G loss: 1.000015] [Wasserstein Distance: 0.000004]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
36 [D loss: 1.000012] [G loss: 1.000010] [Wasserstein Distance: -0.000009]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
37 [D loss: 0.999997] [G loss: 1.000020] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
38 [D loss: 1.000066] [G loss: 1.000031] [Wasserstein Distance: 0.000005]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
39 [D loss: 0.999999] [G loss: 1.000058] [Wasserstein Distance: 0.000009]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
40 [D loss: 1.000093] [G loss: 1.000059] [Wasserstein Distance: 0.000033]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
41 [D loss: 1.000032] [G loss: 1.000067] [Wasserstein Distance: 0.000037]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
42 [D loss: 1.000137] [G loss: 1.000078] [Wasserstein Distance: 0.000066]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
43 [D loss: 1.000038] [G loss: 1.000110] [Wasserstein Distance: 0.000060]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
44 [D loss: 1.000192] [G loss: 1.000125] [Wasserstein Distance: 0.000099]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
45 [D loss: 0.999963] [G loss: 1.000189] [Wasserstein Distance: 0.000073]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
46 [D loss: 1.000171] [G loss: 1.000167] [Wasserstein Distance: 0.000100]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
47 [D loss: 0.999940] [G loss: 1.000246] [Wasserstein Distance: 0.000061]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
48 [D loss: 1.000136] [G loss: 1.000212] [Wasserstein Distance: 0.000081]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
49 [D loss: 0.999991] [G loss: 1.000252] [Wasserstein Distance: 0.000040]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
50 [D loss: 1.000015] [G loss: 1.000262] [Wasserstein Distance: 0.000051]
1/1 [==============================] - 0s 45ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
51 [D loss: 0.999983] [G loss: 1.000276] [Wasserstein Distance: 0.000013]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
52 [D loss: 1.000041] [G loss: 1.000246] [Wasserstein Distance: 0.000033]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
53 [D loss: 1.000013] [G loss: 1.000263] [Wasserstein Distance: 0.000009]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
54 [D loss: 1.000022] [G loss: 1.000265] [Wasserstein Distance: 0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
55 [D loss: 1.000001] [G loss: 1.000273] [Wasserstein Distance: 0.000012]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
56 [D loss: 1.000017] [G loss: 1.000252] [Wasserstein Distance: 0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
57 [D loss: 1.000002] [G loss: 1.000277] [Wasserstein Distance: 0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
58 [D loss: 1.000048] [G loss: 1.000251] [Wasserstein Distance: 0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
59 [D loss: 0.999974] [G loss: 1.000276] [Wasserstein Distance: 0.000008]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
60 [D loss: 1.000043] [G loss: 1.000244] [Wasserstein Distance: 0.000017]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
61 [D loss: 0.999985] [G loss: 1.000288] [Wasserstein Distance: 0.000010]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
62 [D loss: 1.000013] [G loss: 1.000270] [Wasserstein Distance: 0.000013]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
63 [D loss: 1.000002] [G loss: 1.000269] [Wasserstein Distance: 0.000003]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
64 [D loss: 1.000012] [G loss: 1.000248] [Wasserstein Distance: 0.000011]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
65 [D loss: 0.999986] [G loss: 1.000288] [Wasserstein Distance: -0.000000]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
66 [D loss: 1.000012] [G loss: 1.000256] [Wasserstein Distance: 0.000005]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
67 [D loss: 0.999996] [G loss: 1.000261] [Wasserstein Distance: 0.000002]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
68 [D loss: 0.999991] [G loss: 1.000278] [Wasserstein Distance: -0.000001]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
69 [D loss: 0.999998] [G loss: 1.000256] [Wasserstein Distance: -0.000003]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
70 [D loss: 0.999980] [G loss: 1.000287] [Wasserstein Distance: -0.000005]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
71 [D loss: 1.000019] [G loss: 1.000248] [Wasserstein Distance: -0.000003]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
72 [D loss: 0.999986] [G loss: 1.000266] [Wasserstein Distance: -0.000005]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
73 [D loss: 1.000002] [G loss: 1.000236] [Wasserstein Distance: -0.000003]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
74 [D loss: 0.999984] [G loss: 1.000264] [Wasserstein Distance: -0.000006]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
75 [D loss: 0.999998] [G loss: 1.000250] [Wasserstein Distance: -0.000002]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
76 [D loss: 0.999989] [G loss: 1.000232] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
77 [D loss: 1.000000] [G loss: 1.000223] [Wasserstein Distance: -0.000005]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
78 [D loss: 0.999970] [G loss: 1.000248] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
79 [D loss: 1.000002] [G loss: 1.000207] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
80 [D loss: 0.999986] [G loss: 1.000223] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
81 [D loss: 0.999999] [G loss: 1.000194] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
82 [D loss: 0.999989] [G loss: 1.000212] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
83 [D loss: 0.999988] [G loss: 1.000204] [Wasserstein Distance: -0.000007]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
84 [D loss: 0.999989] [G loss: 1.000200] [Wasserstein Distance: -0.000010]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
85 [D loss: 0.999993] [G loss: 1.000188] [Wasserstein Distance: -0.000009]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
86 [D loss: 0.999986] [G loss: 1.000200] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
87 [D loss: 0.999995] [G loss: 1.000174] [Wasserstein Distance: -0.000010]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
88 [D loss: 0.999984] [G loss: 1.000195] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
89 [D loss: 0.999988] [G loss: 1.000182] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
90 [D loss: 0.999985] [G loss: 1.000187] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
91 [D loss: 0.999992] [G loss: 1.000170] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
92 [D loss: 0.999985] [G loss: 1.000171] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
93 [D loss: 0.999989] [G loss: 1.000164] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
94 [D loss: 0.999987] [G loss: 1.000175] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
95 [D loss: 0.999988] [G loss: 1.000155] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
96 [D loss: 0.999986] [G loss: 1.000164] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
97 [D loss: 0.999995] [G loss: 1.000134] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
98 [D loss: 0.999986] [G loss: 1.000158] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
99 [D loss: 0.999990] [G loss: 1.000154] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
100 [D loss: 0.999992] [G loss: 1.000141] [Wasserstein Distance: -0.000010]
1/1 [==============================] - 0s 45ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
101 [D loss: 0.999983] [G loss: 1.000150] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
102 [D loss: 0.999990] [G loss: 1.000121] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
103 [D loss: 0.999986] [G loss: 1.000145] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
104 [D loss: 0.999993] [G loss: 1.000124] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
105 [D loss: 0.999986] [G loss: 1.000142] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
106 [D loss: 0.999994] [G loss: 1.000124] [Wasserstein Distance: -0.000010]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
107 [D loss: 0.999986] [G loss: 1.000132] [Wasserstein Distance: -0.000011]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
108 [D loss: 0.999989] [G loss: 1.000115] [Wasserstein Distance: -0.000010]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
109 [D loss: 0.999984] [G loss: 1.000125] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
110 [D loss: 0.999989] [G loss: 1.000112] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
111 [D loss: 0.999982] [G loss: 1.000120] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
112 [D loss: 0.999984] [G loss: 1.000119] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
113 [D loss: 0.999979] [G loss: 1.000111] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
114 [D loss: 0.999987] [G loss: 1.000107] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
115 [D loss: 0.999983] [G loss: 1.000113] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
116 [D loss: 0.999988] [G loss: 1.000101] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
117 [D loss: 0.999982] [G loss: 1.000108] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
118 [D loss: 0.999985] [G loss: 1.000100] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
119 [D loss: 0.999982] [G loss: 1.000097] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
120 [D loss: 0.999986] [G loss: 1.000089] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
121 [D loss: 0.999986] [G loss: 1.000094] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
122 [D loss: 0.999984] [G loss: 1.000090] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
123 [D loss: 0.999988] [G loss: 1.000076] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
124 [D loss: 0.999985] [G loss: 1.000077] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
125 [D loss: 0.999990] [G loss: 1.000071] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
126 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
127 [D loss: 0.999983] [G loss: 1.000074] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
128 [D loss: 0.999984] [G loss: 1.000069] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
129 [D loss: 0.999989] [G loss: 1.000065] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
130 [D loss: 0.999982] [G loss: 1.000079] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
131 [D loss: 0.999988] [G loss: 1.000070] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
132 [D loss: 0.999983] [G loss: 1.000072] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
133 [D loss: 0.999985] [G loss: 1.000078] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
134 [D loss: 0.999982] [G loss: 1.000079] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
135 [D loss: 0.999987] [G loss: 1.000079] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
136 [D loss: 0.999984] [G loss: 1.000076] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
137 [D loss: 0.999988] [G loss: 1.000072] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
138 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
139 [D loss: 0.999990] [G loss: 1.000062] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
140 [D loss: 0.999986] [G loss: 1.000078] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
141 [D loss: 0.999985] [G loss: 1.000074] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
142 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
143 [D loss: 0.999990] [G loss: 1.000067] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
144 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
145 [D loss: 0.999975] [G loss: 1.000084] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
146 [D loss: 0.999979] [G loss: 1.000073] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
147 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
148 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
149 [D loss: 0.999978] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
150 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 46ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
151 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
152 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
153 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
154 [D loss: 0.999973] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
155 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
156 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
157 [D loss: 0.999973] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
158 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
159 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
160 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
161 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
162 [D loss: 0.999972] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
163 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
164 [D loss: 0.999971] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
165 [D loss: 0.999972] [G loss: 1.000071] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
166 [D loss: 0.999972] [G loss: 1.000071] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
167 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
168 [D loss: 0.999972] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
169 [D loss: 0.999972] [G loss: 1.000073] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
170 [D loss: 0.999970] [G loss: 1.000074] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
171 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
172 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
173 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
174 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
175 [D loss: 0.999972] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
176 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
177 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
178 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
179 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
180 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
181 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
182 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
183 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
184 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
185 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
186 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
187 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
188 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
189 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
190 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
191 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
192 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
193 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
194 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
195 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
196 [D loss: 0.999976] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
197 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
198 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
199 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
200 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 42ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
201 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
202 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
203 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
204 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
205 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
206 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
207 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
208 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
209 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
210 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
211 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
212 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
213 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
214 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
215 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
216 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
217 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
218 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
219 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
220 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
221 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
222 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
223 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
224 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
225 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
226 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
227 [D loss: 0.999971] [G loss: 1.000060] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
228 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
229 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
230 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
231 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
232 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
233 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
234 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
235 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
236 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
237 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
238 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
239 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
240 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
241 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
242 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
243 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
244 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
245 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
246 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
247 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
248 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
249 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
250 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 56ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
251 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
252 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
253 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
254 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
255 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
256 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
257 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
258 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
259 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
260 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
261 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
262 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
263 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
264 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
265 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
266 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
267 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
268 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
269 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
270 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
271 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
272 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
273 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
274 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
275 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
276 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
277 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
278 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
279 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
280 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
281 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
282 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
283 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
284 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
285 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
286 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
287 [D loss: 0.999973] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
288 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
289 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
290 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
291 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
292 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
293 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
294 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
295 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
296 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
297 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
298 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
299 [D loss: 0.999973] [G loss: 1.000057] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
300 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 41ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
301 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
302 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
303 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
304 [D loss: 0.999976] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
305 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
306 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
307 [D loss: 0.999974] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
308 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
309 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
310 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
311 [D loss: 0.999976] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
312 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
313 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
314 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
315 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
316 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
317 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
318 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
319 [D loss: 0.999974] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
320 [D loss: 0.999976] [G loss: 1.000052] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
321 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
322 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
323 [D loss: 0.999976] [G loss: 1.000054] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
324 [D loss: 0.999973] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
325 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
326 [D loss: 0.999976] [G loss: 1.000054] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
327 [D loss: 0.999977] [G loss: 1.000054] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
328 [D loss: 0.999976] [G loss: 1.000054] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
329 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
330 [D loss: 0.999976] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
331 [D loss: 0.999975] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
332 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
333 [D loss: 0.999975] [G loss: 1.000053] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
334 [D loss: 0.999976] [G loss: 1.000051] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
335 [D loss: 0.999975] [G loss: 1.000054] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
336 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
337 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
338 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
339 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
340 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
341 [D loss: 0.999974] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
342 [D loss: 0.999976] [G loss: 1.000054] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
343 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
344 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
345 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
346 [D loss: 0.999977] [G loss: 1.000051] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
347 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
348 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
349 [D loss: 0.999977] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
350 [D loss: 0.999976] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 63ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
351 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
352 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
353 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
354 [D loss: 0.999975] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
355 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
356 [D loss: 0.999978] [G loss: 1.000053] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
357 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
358 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
359 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
360 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
361 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
362 [D loss: 0.999978] [G loss: 1.000057] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
363 [D loss: 0.999978] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
364 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
365 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
366 [D loss: 0.999977] [G loss: 1.000056] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
367 [D loss: 0.999976] [G loss: 1.000054] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
368 [D loss: 0.999979] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
369 [D loss: 0.999978] [G loss: 1.000052] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
370 [D loss: 0.999980] [G loss: 1.000050] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
371 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
372 [D loss: 0.999977] [G loss: 1.000053] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
373 [D loss: 0.999978] [G loss: 1.000056] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
374 [D loss: 0.999978] [G loss: 1.000054] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
375 [D loss: 0.999979] [G loss: 1.000054] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
376 [D loss: 0.999979] [G loss: 1.000053] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
377 [D loss: 0.999980] [G loss: 1.000052] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
378 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
379 [D loss: 0.999978] [G loss: 1.000052] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
380 [D loss: 0.999977] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
381 [D loss: 0.999977] [G loss: 1.000051] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
382 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
383 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
384 [D loss: 0.999980] [G loss: 1.000046] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
385 [D loss: 0.999978] [G loss: 1.000046] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
386 [D loss: 0.999980] [G loss: 1.000047] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
387 [D loss: 0.999979] [G loss: 1.000050] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
388 [D loss: 0.999979] [G loss: 1.000049] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
389 [D loss: 0.999977] [G loss: 1.000050] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
390 [D loss: 0.999977] [G loss: 1.000053] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
391 [D loss: 0.999979] [G loss: 1.000049] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
392 [D loss: 0.999981] [G loss: 1.000047] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
393 [D loss: 0.999978] [G loss: 1.000054] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
394 [D loss: 0.999979] [G loss: 1.000051] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
395 [D loss: 0.999981] [G loss: 1.000048] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
396 [D loss: 0.999979] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
397 [D loss: 0.999980] [G loss: 1.000045] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
398 [D loss: 0.999982] [G loss: 1.000046] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
399 [D loss: 0.999981] [G loss: 1.000045] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
400 [D loss: 0.999978] [G loss: 1.000048] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 45ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
401 [D loss: 0.999982] [G loss: 1.000042] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
402 [D loss: 0.999979] [G loss: 1.000048] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
403 [D loss: 0.999978] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
404 [D loss: 0.999981] [G loss: 1.000042] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
405 [D loss: 0.999980] [G loss: 1.000045] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
406 [D loss: 0.999979] [G loss: 1.000047] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
407 [D loss: 0.999981] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
408 [D loss: 0.999980] [G loss: 1.000047] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
409 [D loss: 0.999980] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
410 [D loss: 0.999982] [G loss: 1.000047] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
411 [D loss: 0.999981] [G loss: 1.000040] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
412 [D loss: 0.999979] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
413 [D loss: 0.999978] [G loss: 1.000046] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
414 [D loss: 0.999978] [G loss: 1.000043] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
415 [D loss: 0.999981] [G loss: 1.000050] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
416 [D loss: 0.999980] [G loss: 1.000052] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
417 [D loss: 0.999981] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
418 [D loss: 0.999982] [G loss: 1.000044] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
419 [D loss: 0.999981] [G loss: 1.000048] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
420 [D loss: 0.999980] [G loss: 1.000047] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
421 [D loss: 0.999979] [G loss: 1.000046] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
422 [D loss: 0.999983] [G loss: 1.000041] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
423 [D loss: 0.999980] [G loss: 1.000050] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
424 [D loss: 0.999981] [G loss: 1.000048] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
425 [D loss: 0.999981] [G loss: 1.000047] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
426 [D loss: 0.999985] [G loss: 1.000044] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
427 [D loss: 0.999979] [G loss: 1.000051] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
428 [D loss: 0.999980] [G loss: 1.000047] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
429 [D loss: 0.999978] [G loss: 1.000047] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
430 [D loss: 0.999983] [G loss: 1.000041] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
431 [D loss: 0.999980] [G loss: 1.000044] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
432 [D loss: 0.999979] [G loss: 1.000047] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
433 [D loss: 0.999982] [G loss: 1.000051] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
434 [D loss: 0.999980] [G loss: 1.000049] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
435 [D loss: 0.999982] [G loss: 1.000051] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
436 [D loss: 0.999983] [G loss: 1.000047] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
437 [D loss: 0.999981] [G loss: 1.000048] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
438 [D loss: 0.999983] [G loss: 1.000048] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
439 [D loss: 0.999982] [G loss: 1.000046] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
440 [D loss: 0.999981] [G loss: 1.000054] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
441 [D loss: 0.999983] [G loss: 1.000042] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
442 [D loss: 0.999982] [G loss: 1.000049] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
443 [D loss: 0.999981] [G loss: 1.000046] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
444 [D loss: 0.999982] [G loss: 1.000043] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
445 [D loss: 0.999982] [G loss: 1.000045] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
446 [D loss: 0.999980] [G loss: 1.000050] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
447 [D loss: 0.999980] [G loss: 1.000045] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
448 [D loss: 0.999983] [G loss: 1.000043] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
449 [D loss: 0.999980] [G loss: 1.000046] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
450 [D loss: 0.999982] [G loss: 1.000052] [Wasserstein Distance: -0.000019]
1/1 [==============================] - 0s 44ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
451 [D loss: 0.999980] [G loss: 1.000050] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
452 [D loss: 0.999984] [G loss: 1.000051] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
453 [D loss: 0.999980] [G loss: 1.000052] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
454 [D loss: 0.999981] [G loss: 1.000046] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
455 [D loss: 0.999980] [G loss: 1.000050] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
456 [D loss: 0.999981] [G loss: 1.000048] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
457 [D loss: 0.999982] [G loss: 1.000043] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
458 [D loss: 0.999979] [G loss: 1.000051] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
459 [D loss: 0.999979] [G loss: 1.000045] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
460 [D loss: 0.999981] [G loss: 1.000050] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
461 [D loss: 0.999980] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
462 [D loss: 0.999981] [G loss: 1.000048] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
463 [D loss: 0.999982] [G loss: 1.000046] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
464 [D loss: 0.999979] [G loss: 1.000051] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
465 [D loss: 0.999983] [G loss: 1.000049] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
466 [D loss: 0.999980] [G loss: 1.000052] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
467 [D loss: 0.999979] [G loss: 1.000048] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
468 [D loss: 0.999981] [G loss: 1.000049] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
469 [D loss: 0.999980] [G loss: 1.000052] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
470 [D loss: 0.999977] [G loss: 1.000054] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
471 [D loss: 0.999980] [G loss: 1.000048] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
472 [D loss: 0.999980] [G loss: 1.000047] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
473 [D loss: 0.999979] [G loss: 1.000050] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
474 [D loss: 0.999981] [G loss: 1.000050] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
475 [D loss: 0.999978] [G loss: 1.000051] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
476 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
477 [D loss: 0.999976] [G loss: 1.000051] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
478 [D loss: 0.999982] [G loss: 1.000052] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
479 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
480 [D loss: 0.999981] [G loss: 1.000051] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
481 [D loss: 0.999978] [G loss: 1.000056] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
482 [D loss: 0.999979] [G loss: 1.000045] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
483 [D loss: 0.999980] [G loss: 1.000051] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
484 [D loss: 0.999979] [G loss: 1.000053] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
485 [D loss: 0.999980] [G loss: 1.000051] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
486 [D loss: 0.999981] [G loss: 1.000048] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
487 [D loss: 0.999979] [G loss: 1.000058] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 24ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
488 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
489 [D loss: 0.999980] [G loss: 1.000054] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
490 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
491 [D loss: 0.999980] [G loss: 1.000051] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
492 [D loss: 0.999978] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
493 [D loss: 0.999977] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
494 [D loss: 0.999977] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
495 [D loss: 0.999981] [G loss: 1.000052] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
496 [D loss: 0.999978] [G loss: 1.000054] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
497 [D loss: 0.999978] [G loss: 1.000050] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
498 [D loss: 0.999979] [G loss: 1.000050] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
499 [D loss: 0.999978] [G loss: 1.000052] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
500 [D loss: 0.999978] [G loss: 1.000057] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 49ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
501 [D loss: 0.999976] [G loss: 1.000052] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
502 [D loss: 0.999978] [G loss: 1.000051] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
503 [D loss: 0.999977] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
504 [D loss: 0.999979] [G loss: 1.000050] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
505 [D loss: 0.999978] [G loss: 1.000056] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
506 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
507 [D loss: 0.999977] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
508 [D loss: 0.999975] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
509 [D loss: 0.999979] [G loss: 1.000049] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
510 [D loss: 0.999976] [G loss: 1.000054] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
511 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
512 [D loss: 0.999978] [G loss: 1.000057] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
513 [D loss: 0.999980] [G loss: 1.000051] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
514 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
515 [D loss: 0.999975] [G loss: 1.000053] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
516 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
517 [D loss: 0.999979] [G loss: 1.000046] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
518 [D loss: 0.999976] [G loss: 1.000051] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
519 [D loss: 0.999978] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
520 [D loss: 0.999977] [G loss: 1.000056] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
521 [D loss: 0.999980] [G loss: 1.000049] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
522 [D loss: 0.999976] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
523 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
524 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
525 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
526 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
527 [D loss: 0.999978] [G loss: 1.000049] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
528 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
529 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
530 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
531 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
532 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
533 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
534 [D loss: 0.999976] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
535 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
536 [D loss: 0.999978] [G loss: 1.000051] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
537 [D loss: 0.999977] [G loss: 1.000056] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
538 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
539 [D loss: 0.999978] [G loss: 1.000058] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
540 [D loss: 0.999976] [G loss: 1.000047] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
541 [D loss: 0.999976] [G loss: 1.000051] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
542 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
543 [D loss: 0.999978] [G loss: 1.000051] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
544 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
545 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
546 [D loss: 0.999978] [G loss: 1.000049] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
547 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
548 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
549 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
550 [D loss: 0.999978] [G loss: 1.000054] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 41ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
551 [D loss: 0.999973] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
552 [D loss: 0.999978] [G loss: 1.000052] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
553 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
554 [D loss: 0.999979] [G loss: 1.000052] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
555 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
556 [D loss: 0.999974] [G loss: 1.000056] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
557 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
558 [D loss: 0.999974] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
559 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
560 [D loss: 0.999978] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
561 [D loss: 0.999974] [G loss: 1.000055] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
562 [D loss: 0.999976] [G loss: 1.000053] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
563 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
564 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
565 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
566 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
567 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
568 [D loss: 0.999973] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
569 [D loss: 0.999976] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
570 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
571 [D loss: 0.999977] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
572 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
573 [D loss: 0.999974] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
574 [D loss: 0.999975] [G loss: 1.000051] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
575 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
576 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
577 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
578 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
579 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
580 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
581 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
582 [D loss: 0.999977] [G loss: 1.000053] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
583 [D loss: 0.999973] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
584 [D loss: 0.999979] [G loss: 1.000050] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
585 [D loss: 0.999976] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
586 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
587 [D loss: 0.999976] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
588 [D loss: 0.999977] [G loss: 1.000055] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
589 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
590 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
591 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
592 [D loss: 0.999976] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
593 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
594 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
595 [D loss: 0.999976] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
596 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
597 [D loss: 0.999977] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
598 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
599 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
600 [D loss: 0.999976] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 46ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
601 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
602 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
603 [D loss: 0.999973] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
604 [D loss: 0.999977] [G loss: 1.000050] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
605 [D loss: 0.999973] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
606 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
607 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
608 [D loss: 0.999976] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
609 [D loss: 0.999977] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
610 [D loss: 0.999979] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
611 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
612 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
613 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
614 [D loss: 0.999977] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
615 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
616 [D loss: 0.999978] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
617 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
618 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
619 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
620 [D loss: 0.999974] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
621 [D loss: 0.999973] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
622 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
623 [D loss: 0.999972] [G loss: 1.000058] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
624 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
625 [D loss: 0.999977] [G loss: 1.000054] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
626 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
627 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
628 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
629 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
630 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
631 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
632 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
633 [D loss: 0.999973] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
634 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
635 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
636 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
637 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
638 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
639 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
640 [D loss: 0.999975] [G loss: 1.000056] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
641 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
642 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
643 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
644 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
645 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
646 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
647 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
648 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
649 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
650 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 46ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
651 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
652 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
653 [D loss: 0.999970] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
654 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
655 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
656 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
657 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
658 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
659 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
660 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
661 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
662 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
663 [D loss: 0.999979] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
664 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
665 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
666 [D loss: 0.999973] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
667 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
668 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
669 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
670 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
671 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
672 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
673 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
674 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
675 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
676 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
677 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
678 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
679 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
680 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
681 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
682 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
683 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
684 [D loss: 0.999970] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
685 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
686 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
687 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
688 [D loss: 0.999972] [G loss: 1.000064] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
689 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
690 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
691 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
692 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
693 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
694 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
695 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
696 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
697 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
698 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
699 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
700 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 53ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
701 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
702 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
703 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
704 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
705 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
706 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
707 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
708 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
709 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
710 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
711 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
712 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
713 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
714 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
715 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
716 [D loss: 0.999971] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
717 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
718 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
719 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
720 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
721 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
722 [D loss: 0.999967] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
723 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
724 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
725 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
726 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
727 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
728 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
729 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
730 [D loss: 0.999971] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
731 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
732 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
733 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
734 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
735 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
736 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
737 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
738 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
739 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
740 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
741 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
742 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
743 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
744 [D loss: 0.999974] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
745 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
746 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
747 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
748 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
749 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
750 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 49ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
751 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
752 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
753 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
754 [D loss: 0.999973] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
755 [D loss: 0.999969] [G loss: 1.000074] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
756 [D loss: 0.999972] [G loss: 1.000071] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
757 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
758 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
759 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
760 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
761 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
762 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
763 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
764 [D loss: 0.999972] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
765 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
766 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
767 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
768 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
769 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
770 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
771 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
772 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
773 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
774 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
775 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
776 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
777 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
778 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
779 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
780 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
781 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
782 [D loss: 0.999979] [G loss: 1.000057] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
783 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
784 [D loss: 0.999973] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
785 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
786 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
787 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
788 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
789 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
790 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
791 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
792 [D loss: 0.999973] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
793 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
794 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
795 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
796 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
797 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
798 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
799 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
800 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 52ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
801 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
802 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
803 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
804 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
805 [D loss: 0.999973] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
806 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
807 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
808 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
809 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
810 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
811 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
812 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
813 [D loss: 0.999972] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
814 [D loss: 0.999972] [G loss: 1.000076] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
815 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
816 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
817 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
818 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
819 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
820 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
821 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
822 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
823 [D loss: 0.999972] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
824 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
825 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
826 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
827 [D loss: 0.999972] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
828 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
829 [D loss: 0.999974] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
830 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
831 [D loss: 0.999980] [G loss: 1.000054] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
832 [D loss: 0.999979] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
833 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
834 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
835 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
836 [D loss: 0.999973] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
837 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
838 [D loss: 0.999977] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
839 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
840 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
841 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
842 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
843 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
844 [D loss: 0.999973] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
845 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
846 [D loss: 0.999970] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
847 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
848 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
849 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
850 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 64ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
851 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
852 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
853 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
854 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
855 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
856 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
857 [D loss: 0.999972] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
858 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
859 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
860 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
861 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
862 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
863 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
864 [D loss: 0.999972] [G loss: 1.000079] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
865 [D loss: 0.999972] [G loss: 1.000076] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
866 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
867 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
868 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
869 [D loss: 0.999972] [G loss: 1.000074] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
870 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
871 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
872 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
873 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
874 [D loss: 0.999972] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
875 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
876 [D loss: 0.999972] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
877 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
878 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
879 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
880 [D loss: 0.999978] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
881 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
882 [D loss: 0.999972] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
883 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
884 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
885 [D loss: 0.999972] [G loss: 1.000074] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
886 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
887 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
888 [D loss: 0.999973] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
889 [D loss: 0.999973] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
890 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
891 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
892 [D loss: 0.999972] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
893 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
894 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
895 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
896 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
897 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
898 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
899 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
900 [D loss: 0.999979] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 40ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
901 [D loss: 0.999969] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
902 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
903 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
904 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
905 [D loss: 0.999973] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
906 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
907 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
908 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
909 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
910 [D loss: 0.999972] [G loss: 1.000079] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
911 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
912 [D loss: 0.999979] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
913 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
914 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
915 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
916 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
917 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
918 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
919 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
920 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
921 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
922 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
923 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
924 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
925 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
926 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
927 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
928 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
929 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
930 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
931 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
932 [D loss: 0.999971] [G loss: 1.000080] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
933 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
934 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
935 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
936 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
937 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
938 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
939 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
940 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
941 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
942 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
943 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
944 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
945 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
946 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
947 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
948 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
949 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
950 [D loss: 0.999977] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 63ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
951 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
952 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
953 [D loss: 0.999972] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
954 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
955 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
956 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
957 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
958 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
959 [D loss: 0.999974] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
960 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
961 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
962 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
963 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
964 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
965 [D loss: 0.999973] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
966 [D loss: 0.999972] [G loss: 1.000077] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
967 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
968 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
969 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
970 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
971 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
972 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
973 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
974 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
975 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
976 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
977 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
978 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
979 [D loss: 0.999972] [G loss: 1.000076] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
980 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
981 [D loss: 0.999977] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
982 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
983 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
984 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
985 [D loss: 0.999973] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
986 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
987 [D loss: 0.999971] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
988 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
989 [D loss: 0.999978] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
990 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
991 [D loss: 0.999973] [G loss: 1.000080] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
992 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
993 [D loss: 0.999972] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
994 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
995 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
996 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
997 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
998 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
999 [D loss: 0.999974] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1000 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 46ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1001 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1002 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1003 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1004 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1005 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1006 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1007 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1008 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1009 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1010 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1011 [D loss: 0.999972] [G loss: 1.000083] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1012 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1013 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1014 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1015 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1016 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1017 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1018 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1019 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1020 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1021 [D loss: 0.999972] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1022 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1023 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1024 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1025 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1026 [D loss: 0.999974] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1027 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1028 [D loss: 0.999977] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1029 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1030 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1031 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1032 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1033 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1034 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1035 [D loss: 0.999972] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1036 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1037 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1038 [D loss: 0.999972] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1039 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1040 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1041 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1042 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1043 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1044 [D loss: 0.999970] [G loss: 1.000083] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1045 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1046 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1047 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1048 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1049 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1050 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 47ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1051 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1052 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1053 [D loss: 0.999979] [G loss: 1.000065] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1054 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1055 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1056 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1057 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1058 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1059 [D loss: 0.999972] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1060 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1061 [D loss: 0.999978] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1062 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1063 [D loss: 0.999982] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1064 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1065 [D loss: 0.999978] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1066 [D loss: 0.999978] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1067 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1068 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1069 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1070 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1071 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1072 [D loss: 0.999981] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1073 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1074 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1075 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1076 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1077 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1078 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1079 [D loss: 0.999977] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1080 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1081 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1082 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1083 [D loss: 0.999977] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1084 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1085 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1086 [D loss: 0.999973] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1087 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1088 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1089 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1090 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1091 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1092 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1093 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1094 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1095 [D loss: 0.999985] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1096 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1097 [D loss: 0.999977] [G loss: 1.000071] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1098 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1099 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1100 [D loss: 0.999973] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 48ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1101 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1102 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1103 [D loss: 0.999977] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1104 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1105 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1106 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1107 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1108 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1109 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1110 [D loss: 0.999978] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1111 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1112 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1113 [D loss: 0.999978] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1114 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1115 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1116 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1117 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1118 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1119 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1120 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1121 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1122 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1123 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1124 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1125 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1126 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1127 [D loss: 0.999974] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1128 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1129 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1130 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1131 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1132 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1133 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1134 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1135 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1136 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1137 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1138 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1139 [D loss: 0.999973] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1140 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1141 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1142 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1143 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1144 [D loss: 0.999984] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1145 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1146 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1147 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1148 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1149 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1150 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 50ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1151 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1152 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1153 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1154 [D loss: 0.999974] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1155 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1156 [D loss: 0.999973] [G loss: 1.000084] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1157 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1158 [D loss: 0.999981] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1159 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1160 [D loss: 0.999980] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1161 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1162 [D loss: 0.999972] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1163 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1164 [D loss: 0.999979] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1165 [D loss: 0.999980] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1166 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1167 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1168 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1169 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1170 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1171 [D loss: 0.999980] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1172 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1173 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1174 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1175 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1176 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1177 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1178 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1179 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1180 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1181 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1182 [D loss: 0.999973] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1183 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1184 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1185 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1186 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1187 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1188 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1189 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1190 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1191 [D loss: 0.999978] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1192 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1193 [D loss: 0.999980] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1194 [D loss: 0.999969] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1195 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1196 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1197 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1198 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1199 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1200 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 50ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1201 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1202 [D loss: 0.999977] [G loss: 1.000070] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1203 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1204 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1205 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1206 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1207 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1208 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1209 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1210 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1211 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1212 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1213 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1214 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1215 [D loss: 0.999972] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1216 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1217 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1218 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1219 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1220 [D loss: 0.999972] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1221 [D loss: 0.999972] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1222 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1223 [D loss: 0.999974] [G loss: 1.000080] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1224 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1225 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1226 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1227 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1228 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1229 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1230 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1231 [D loss: 0.999971] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1232 [D loss: 0.999973] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1233 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1234 [D loss: 0.999979] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1235 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1236 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1237 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1238 [D loss: 0.999980] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1239 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1240 [D loss: 0.999982] [G loss: 1.000059] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1241 [D loss: 0.999982] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1242 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1243 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1244 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1245 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1246 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1247 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1248 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1249 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1250 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 52ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1251 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1252 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1253 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1254 [D loss: 0.999975] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1255 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1256 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1257 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1258 [D loss: 0.999978] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1259 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1260 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1261 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1262 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1263 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1264 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1265 [D loss: 0.999981] [G loss: 1.000071] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1266 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1267 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1268 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1269 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1270 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1271 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1272 [D loss: 0.999980] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1273 [D loss: 0.999973] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1274 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1275 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1276 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1277 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1278 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1279 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1280 [D loss: 0.999978] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1281 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1282 [D loss: 0.999982] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1283 [D loss: 0.999979] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1284 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1285 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1286 [D loss: 0.999974] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1287 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1288 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1289 [D loss: 0.999981] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1290 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1291 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1292 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1293 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1294 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1295 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1296 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1297 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1298 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1299 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1300 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 53ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1301 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1302 [D loss: 0.999973] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1303 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1304 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1305 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1306 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1307 [D loss: 0.999973] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1308 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1309 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1310 [D loss: 0.999979] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1311 [D loss: 0.999979] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1312 [D loss: 0.999978] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1313 [D loss: 0.999978] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1314 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1315 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1316 [D loss: 0.999979] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1317 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1318 [D loss: 0.999980] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1319 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1320 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1321 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1322 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1323 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1324 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1325 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1326 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1327 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1328 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1329 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1330 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1331 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1332 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1333 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1334 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1335 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1336 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1337 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1338 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1339 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1340 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1341 [D loss: 0.999979] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1342 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1343 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1344 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1345 [D loss: 0.999981] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1346 [D loss: 0.999978] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1347 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1348 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1349 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1350 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 54ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1351 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1352 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1353 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1354 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1355 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1356 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1357 [D loss: 0.999979] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1358 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1359 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1360 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1361 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1362 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1363 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1364 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1365 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1366 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1367 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1368 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1369 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1370 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1371 [D loss: 0.999979] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1372 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1373 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1374 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1375 [D loss: 0.999985] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1376 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1377 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1378 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1379 [D loss: 0.999973] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1380 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1381 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1382 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1383 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1384 [D loss: 0.999983] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1385 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1386 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1387 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1388 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1389 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1390 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1391 [D loss: 0.999980] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1392 [D loss: 0.999978] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1393 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1394 [D loss: 0.999972] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1395 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1396 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1397 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1398 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1399 [D loss: 0.999982] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1400 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 54ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1401 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1402 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1403 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1404 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1405 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1406 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1407 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1408 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1409 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1410 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1411 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1412 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
1413 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1414 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1415 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1416 [D loss: 0.999982] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1417 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1418 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1419 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1420 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1421 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1422 [D loss: 0.999980] [G loss: 1.000071] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1423 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1424 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1425 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1426 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1427 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1428 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1429 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1430 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1431 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
1432 [D loss: 0.999984] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1433 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1434 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1435 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1436 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1437 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1438 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1439 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1440 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1441 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1442 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1443 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1444 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1445 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1446 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1447 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1448 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1449 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1450 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 49ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1451 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1452 [D loss: 0.999981] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1453 [D loss: 0.999973] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1454 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1455 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1456 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1457 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1458 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1459 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1460 [D loss: 0.999983] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1461 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1462 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1463 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1464 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1465 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1466 [D loss: 0.999984] [G loss: 1.000059] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1467 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1468 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1469 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1470 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1471 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1472 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1473 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1474 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1475 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1476 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1477 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1478 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1479 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1480 [D loss: 0.999973] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1481 [D loss: 0.999982] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1482 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1483 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1484 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1485 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1486 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1487 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1488 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1489 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1490 [D loss: 0.999978] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1491 [D loss: 0.999982] [G loss: 1.000070] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1492 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1493 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1494 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1495 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1496 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1497 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1498 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1499 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1500 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 52ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1501 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1502 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1503 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1504 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1505 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1506 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1507 [D loss: 0.999982] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1508 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1509 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1510 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1511 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1512 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1513 [D loss: 0.999975] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1514 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1515 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1516 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1517 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1518 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1519 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1520 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1521 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1522 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1523 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1524 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1525 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1526 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1527 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1528 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1529 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1530 [D loss: 0.999981] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1531 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1532 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1533 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1534 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1535 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1536 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1537 [D loss: 0.999980] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1538 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1539 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1540 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1541 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1542 [D loss: 0.999981] [G loss: 1.000075] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1543 [D loss: 0.999982] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1544 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1545 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1546 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1547 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1548 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1549 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1550 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 51ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1551 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1552 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1553 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1554 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1555 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1556 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1557 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1558 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1559 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1560 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1561 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1562 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1563 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1564 [D loss: 0.999981] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1565 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1566 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1567 [D loss: 0.999981] [G loss: 1.000073] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1568 [D loss: 0.999983] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1569 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1570 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1571 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1572 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1573 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1574 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1575 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1576 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1577 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1578 [D loss: 0.999983] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
1579 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1580 [D loss: 0.999980] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1581 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1582 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1583 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1584 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1585 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1586 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1587 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1588 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1589 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1590 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1591 [D loss: 0.999982] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1592 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1593 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1594 [D loss: 0.999987] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1595 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1596 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1597 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1598 [D loss: 0.999975] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
1599 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1600 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 66ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1601 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1602 [D loss: 0.999985] [G loss: 1.000072] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1603 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1604 [D loss: 0.999983] [G loss: 1.000070] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1605 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1606 [D loss: 0.999983] [G loss: 1.000069] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1607 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1608 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1609 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1610 [D loss: 0.999978] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1611 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1612 [D loss: 0.999982] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1613 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1614 [D loss: 0.999995] [G loss: 1.000058] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1615 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1616 [D loss: 0.999982] [G loss: 1.000086] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1617 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1618 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1619 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1620 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1621 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1622 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1623 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1624 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1625 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1626 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1627 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1628 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1629 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1630 [D loss: 0.999983] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1631 [D loss: 0.999981] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1632 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1633 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1634 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1635 [D loss: 0.999974] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1636 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1637 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1638 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1639 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1640 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1641 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1642 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1643 [D loss: 0.999973] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1644 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1645 [D loss: 0.999979] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1646 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1647 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1648 [D loss: 0.999980] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1649 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1650 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 51ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1651 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1652 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1653 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1654 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1655 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1656 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1657 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1658 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1659 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1660 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1661 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1662 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1663 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1664 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1665 [D loss: 0.999984] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1666 [D loss: 0.999982] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1667 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1668 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1669 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1670 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1671 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1672 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1673 [D loss: 0.999983] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1674 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1675 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1676 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1677 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1678 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1679 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1680 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1681 [D loss: 0.999982] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1682 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1683 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1684 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1685 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1686 [D loss: 0.999980] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1687 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1688 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1689 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1690 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1691 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1692 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1693 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1694 [D loss: 0.999983] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1695 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1696 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1697 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1698 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1699 [D loss: 0.999982] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1700 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 73ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1701 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1702 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1703 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1704 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1705 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1706 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1707 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1708 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1709 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1710 [D loss: 0.999989] [G loss: 1.000068] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1711 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1712 [D loss: 0.999982] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1713 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1714 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1715 [D loss: 0.999987] [G loss: 1.000071] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1716 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1717 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1718 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1719 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1720 [D loss: 0.999980] [G loss: 1.000072] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1721 [D loss: 0.999983] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1722 [D loss: 0.999982] [G loss: 1.000076] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1723 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1724 [D loss: 0.999987] [G loss: 1.000079] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1725 [D loss: 0.999985] [G loss: 1.000060] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1726 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
1727 [D loss: 0.999982] [G loss: 1.000069] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1728 [D loss: 0.999982] [G loss: 1.000080] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1729 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1730 [D loss: 0.999982] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1731 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1732 [D loss: 0.999984] [G loss: 1.000074] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1733 [D loss: 0.999981] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1734 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
1735 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1736 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1737 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1738 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1739 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1740 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1741 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1742 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1743 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1744 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1745 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1746 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1747 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1748 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1749 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1750 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 55ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
1751 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1752 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1753 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1754 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1755 [D loss: 0.999982] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1756 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1757 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1758 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1759 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1760 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1761 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1762 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1763 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1764 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1765 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1766 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1767 [D loss: 0.999975] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1768 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1769 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1770 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1771 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1772 [D loss: 0.999983] [G loss: 1.000074] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1773 [D loss: 0.999982] [G loss: 1.000077] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1774 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1775 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1776 [D loss: 0.999982] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1777 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1778 [D loss: 0.999974] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1779 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1780 [D loss: 0.999974] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1781 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1782 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1783 [D loss: 0.999986] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1784 [D loss: 0.999973] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1785 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1786 [D loss: 0.999980] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1787 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1788 [D loss: 0.999973] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1789 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1790 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1791 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1792 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1793 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1794 [D loss: 0.999984] [G loss: 1.000075] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1795 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1796 [D loss: 0.999973] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1797 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1798 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1799 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1800 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 45ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1801 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1802 [D loss: 0.999984] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1803 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1804 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1805 [D loss: 0.999982] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
1806 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1807 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1808 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1809 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1810 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1811 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1812 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1813 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
1814 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1815 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1816 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1817 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1818 [D loss: 0.999984] [G loss: 1.000073] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1819 [D loss: 0.999984] [G loss: 1.000069] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1820 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1821 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1822 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1823 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1824 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1825 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1826 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1827 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1828 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1829 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1830 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1831 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1832 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1833 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1834 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1835 [D loss: 0.999968] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1836 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1837 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1838 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1839 [D loss: 0.999974] [G loss: 1.000086] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1840 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1841 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1842 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1843 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1844 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1845 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1846 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1847 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1848 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1849 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1850 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 56ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1851 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1852 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1853 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1854 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1855 [D loss: 0.999986] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1856 [D loss: 0.999983] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1857 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1858 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1859 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1860 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1861 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1862 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1863 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1864 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1865 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1866 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1867 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1868 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1869 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1870 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1871 [D loss: 0.999975] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1872 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1873 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1874 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1875 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1876 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1877 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1878 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1879 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1880 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1881 [D loss: 0.999983] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1882 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1883 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1884 [D loss: 0.999989] [G loss: 1.000057] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1885 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
1886 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1887 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1888 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1889 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1890 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1891 [D loss: 0.999985] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1892 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1893 [D loss: 1.000000] [G loss: 1.000041] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1894 [D loss: 0.999973] [G loss: 1.000090] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1895 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1896 [D loss: 0.999987] [G loss: 1.000075] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1897 [D loss: 0.999975] [G loss: 1.000090] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
1898 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1899 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1900 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 57ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1901 [D loss: 0.999983] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1902 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1903 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1904 [D loss: 0.999972] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
1905 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1906 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1907 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1908 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1909 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1910 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1911 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1912 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1913 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1914 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1915 [D loss: 0.999984] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1916 [D loss: 0.999984] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1917 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1918 [D loss: 0.999984] [G loss: 1.000066] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1919 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1920 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1921 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1922 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1923 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1924 [D loss: 0.999982] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1925 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1926 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1927 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
1928 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1929 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1930 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1931 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1932 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1933 [D loss: 0.999985] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1934 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1935 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
1936 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1937 [D loss: 0.999982] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1938 [D loss: 0.999974] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1939 [D loss: 0.999984] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
1940 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1941 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1942 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1943 [D loss: 0.999984] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1944 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1945 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1946 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1947 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1948 [D loss: 0.999981] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1949 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1950 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 60ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1951 [D loss: 0.999982] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
1952 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1953 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1954 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1955 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1956 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1957 [D loss: 0.999985] [G loss: 1.000070] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
1958 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1959 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1960 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1961 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1962 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
1963 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1964 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1965 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1966 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1967 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1968 [D loss: 0.999991] [G loss: 1.000062] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
1969 [D loss: 0.999987] [G loss: 1.000092] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1970 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1971 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
1972 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1973 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
1974 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
1975 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
1976 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1977 [D loss: 0.999973] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1978 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1979 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
1980 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1981 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1982 [D loss: 0.999983] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1983 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1984 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1985 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1986 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1987 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
1988 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1989 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
1990 [D loss: 0.999970] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
1991 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1992 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
1993 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
1994 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1995 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
1996 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1997 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1998 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
1999 [D loss: 0.999982] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2000 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 63ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2001 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2002 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2003 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2004 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2005 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2006 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2007 [D loss: 0.999973] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2008 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 14ms/step
2009 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2010 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2011 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2012 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2013 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2014 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2015 [D loss: 0.999972] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2016 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2017 [D loss: 0.999975] [G loss: 1.000095] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2018 [D loss: 0.999973] [G loss: 1.000089] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2019 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2020 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2021 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2022 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2023 [D loss: 0.999972] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2024 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2025 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
2026 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2027 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2028 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2029 [D loss: 0.999982] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2030 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2031 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2032 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2033 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2034 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2035 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2036 [D loss: 0.999983] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2037 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2038 [D loss: 0.999985] [G loss: 1.000063] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
2039 [D loss: 0.999986] [G loss: 1.000076] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2040 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2041 [D loss: 0.999989] [G loss: 1.000068] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2042 [D loss: 0.999982] [G loss: 1.000080] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2043 [D loss: 0.999975] [G loss: 1.000094] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2044 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2045 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2046 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2047 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2048 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2049 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2050 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 63ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2051 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2052 [D loss: 0.999983] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2053 [D loss: 0.999975] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2054 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2055 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2056 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2057 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2058 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
2059 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2060 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2061 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2062 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2063 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2064 [D loss: 0.999985] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2065 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2066 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2067 [D loss: 0.999982] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2068 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2069 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2070 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2071 [D loss: 0.999970] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2072 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2073 [D loss: 0.999984] [G loss: 1.000062] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2074 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2075 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2076 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2077 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2078 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2079 [D loss: 0.999982] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2080 [D loss: 0.999985] [G loss: 1.000074] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2081 [D loss: 0.999973] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2082 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2083 [D loss: 0.999974] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2084 [D loss: 0.999972] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2085 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2086 [D loss: 0.999983] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2087 [D loss: 0.999982] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2088 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2089 [D loss: 0.999986] [G loss: 1.000067] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2090 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2091 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2092 [D loss: 0.999972] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2093 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2094 [D loss: 0.999984] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2095 [D loss: 0.999983] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2096 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2097 [D loss: 0.999979] [G loss: 1.000072] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
2098 [D loss: 0.999984] [G loss: 1.000077] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
2099 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2100 [D loss: 0.999988] [G loss: 1.000067] [Wasserstein Distance: -0.000017]
1/1 [==============================] - 0s 60ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2101 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2102 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2103 [D loss: 0.999973] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
2104 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2105 [D loss: 0.999983] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2106 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2107 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2108 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2109 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2110 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2111 [D loss: 0.999982] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2112 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2113 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2114 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2115 [D loss: 0.999985] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2116 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2117 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2118 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2119 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2120 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2121 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2122 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2123 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2124 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2125 [D loss: 0.999983] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2126 [D loss: 0.999973] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
2127 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2128 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2129 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2130 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2131 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2132 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2133 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2134 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2135 [D loss: 0.999982] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2136 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2137 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2138 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2139 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2140 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2141 [D loss: 0.999973] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2142 [D loss: 0.999972] [G loss: 1.000086] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2143 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
2144 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2145 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2146 [D loss: 0.999968] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2147 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
2148 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2149 [D loss: 0.999983] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2150 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 57ms/step
8/8 [==============================] - 0s 27ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2151 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2152 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2153 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2154 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2155 [D loss: 0.999973] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2156 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2157 [D loss: 0.999982] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2158 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2159 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2160 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2161 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2162 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2163 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2164 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
2165 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2166 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2167 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2168 [D loss: 0.999986] [G loss: 1.000064] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2169 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2170 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2171 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2172 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2173 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2174 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2175 [D loss: 0.999979] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2176 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2177 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2178 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2179 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2180 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2181 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2182 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2183 [D loss: 0.999975] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2184 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2185 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2186 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2187 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2188 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2189 [D loss: 0.999973] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2190 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2191 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2192 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2193 [D loss: 0.999982] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2194 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2195 [D loss: 0.999985] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2196 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2197 [D loss: 0.999972] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2198 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2199 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2200 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 62ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2201 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2202 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2203 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2204 [D loss: 0.999983] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2205 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2206 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2207 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2208 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2209 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2210 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2211 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2212 [D loss: 0.999990] [G loss: 1.000070] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2213 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2214 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2215 [D loss: 0.999971] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2216 [D loss: 0.999985] [G loss: 1.000074] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2217 [D loss: 0.999983] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2218 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2219 [D loss: 0.999982] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2220 [D loss: 0.999974] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2221 [D loss: 0.999975] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2222 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2223 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2224 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2225 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2226 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2227 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2228 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2229 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2230 [D loss: 0.999974] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2231 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2232 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2233 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2234 [D loss: 0.999969] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2235 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2236 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2237 [D loss: 0.999983] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2238 [D loss: 0.999982] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2239 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2240 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2241 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2242 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2243 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2244 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2245 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2246 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2247 [D loss: 0.999974] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2248 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2249 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2250 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 60ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2251 [D loss: 0.999989] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2252 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2253 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2254 [D loss: 0.999984] [G loss: 1.000067] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2255 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2256 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2257 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2258 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2259 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2260 [D loss: 0.999983] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2261 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2262 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2263 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2264 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2265 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2266 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2267 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2268 [D loss: 0.999981] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2269 [D loss: 0.999986] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2270 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2271 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2272 [D loss: 0.999984] [G loss: 1.000087] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2273 [D loss: 0.999984] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2274 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2275 [D loss: 0.999984] [G loss: 1.000070] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2276 [D loss: 0.999980] [G loss: 1.000072] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2277 [D loss: 0.999973] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2278 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2279 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2280 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2281 [D loss: 0.999979] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2282 [D loss: 0.999983] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2283 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2284 [D loss: 0.999984] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2285 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2286 [D loss: 0.999972] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2287 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2288 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2289 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2290 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2291 [D loss: 0.999986] [G loss: 1.000072] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2292 [D loss: 0.999986] [G loss: 1.000069] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2293 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2294 [D loss: 0.999975] [G loss: 1.000095] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2295 [D loss: 0.999985] [G loss: 1.000084] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2296 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2297 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2298 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2299 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2300 [D loss: 0.999973] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 108ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2301 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2302 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2303 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2304 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2305 [D loss: 0.999974] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2306 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2307 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2308 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2309 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2310 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2311 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2312 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
2313 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2314 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2315 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2316 [D loss: 0.999983] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2317 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2318 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2319 [D loss: 0.999981] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2320 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2321 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2322 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2323 [D loss: 0.999982] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2324 [D loss: 0.999980] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2325 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2326 [D loss: 0.999983] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2327 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2328 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
2329 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
2330 [D loss: 0.999986] [G loss: 1.000073] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2331 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2332 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2333 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2334 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2335 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2336 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2337 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2338 [D loss: 0.999984] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2339 [D loss: 0.999982] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2340 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2341 [D loss: 0.999975] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2342 [D loss: 0.999990] [G loss: 1.000074] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2343 [D loss: 0.999982] [G loss: 1.000075] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2344 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2345 [D loss: 0.999983] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2346 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2347 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2348 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2349 [D loss: 0.999984] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2350 [D loss: 0.999982] [G loss: 1.000072] [Wasserstein Distance: -0.000019]
1/1 [==============================] - 0s 59ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2351 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2352 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2353 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2354 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2355 [D loss: 0.999983] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2356 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2357 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2358 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2359 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2360 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2361 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2362 [D loss: 0.999984] [G loss: 1.000073] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2363 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2364 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2365 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2366 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2367 [D loss: 0.999982] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2368 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2369 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2370 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2371 [D loss: 0.999984] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2372 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2373 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2374 [D loss: 0.999983] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2375 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2376 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2377 [D loss: 0.999983] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2378 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2379 [D loss: 0.999984] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2380 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2381 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2382 [D loss: 0.999997] [G loss: 1.000028] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2383 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2384 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2385 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2386 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2387 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2388 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2389 [D loss: 0.999983] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2390 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2391 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2392 [D loss: 0.999982] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2393 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2394 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2395 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2396 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2397 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2398 [D loss: 0.999986] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2399 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2400 [D loss: 0.999974] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 72ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2401 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2402 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2403 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2404 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2405 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2406 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2407 [D loss: 0.999983] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2408 [D loss: 0.999984] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2409 [D loss: 0.999985] [G loss: 1.000070] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2410 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2411 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2412 [D loss: 0.999982] [G loss: 1.000078] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2413 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2414 [D loss: 0.999980] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2415 [D loss: 0.999983] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2416 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
2417 [D loss: 0.999983] [G loss: 1.000079] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2418 [D loss: 0.999983] [G loss: 1.000079] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2419 [D loss: 0.999982] [G loss: 1.000079] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2420 [D loss: 0.999975] [G loss: 1.000093] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2421 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2422 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2423 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2424 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2425 [D loss: 0.999986] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2426 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2427 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2428 [D loss: 0.999981] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2429 [D loss: 0.999984] [G loss: 1.000078] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2430 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2431 [D loss: 0.999973] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2432 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2433 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2434 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2435 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2436 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2437 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2438 [D loss: 0.999983] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2439 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2440 [D loss: 0.999983] [G loss: 1.000074] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2441 [D loss: 0.999984] [G loss: 1.000083] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2442 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2443 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2444 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2445 [D loss: 0.999980] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2446 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2447 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2448 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2449 [D loss: 0.999981] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
2450 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 58ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2451 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2452 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2453 [D loss: 0.999974] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2454 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2455 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2456 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2457 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2458 [D loss: 0.999983] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2459 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2460 [D loss: 0.999967] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2461 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2462 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2463 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2464 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2465 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2466 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2467 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2468 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2469 [D loss: 0.999973] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2470 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2471 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
2472 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2473 [D loss: 0.999982] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2474 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2475 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2476 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2477 [D loss: 0.999987] [G loss: 1.000071] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
2478 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2479 [D loss: 0.999973] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2480 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2481 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2482 [D loss: 0.999973] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2483 [D loss: 0.999972] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2484 [D loss: 0.999984] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2485 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2486 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2487 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2488 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2489 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2490 [D loss: 0.999983] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2491 [D loss: 0.999983] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2492 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2493 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2494 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2495 [D loss: 0.999983] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2496 [D loss: 0.999973] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2497 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2498 [D loss: 0.999982] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2499 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2500 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 55ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2501 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2502 [D loss: 0.999985] [G loss: 1.000077] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2503 [D loss: 0.999986] [G loss: 1.000066] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2504 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2505 [D loss: 0.999995] [G loss: 1.000036] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2506 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2507 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2508 [D loss: 0.999985] [G loss: 1.000078] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2509 [D loss: 0.999984] [G loss: 1.000081] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2510 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2511 [D loss: 0.999984] [G loss: 1.000086] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2512 [D loss: 0.999982] [G loss: 1.000087] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2513 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2514 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2515 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2516 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2517 [D loss: 0.999975] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2518 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2519 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2520 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2521 [D loss: 0.999984] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2522 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2523 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2524 [D loss: 0.999973] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2525 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2526 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2527 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2528 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2529 [D loss: 0.999972] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2530 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2531 [D loss: 0.999984] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2532 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2533 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2534 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2535 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2536 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2537 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2538 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2539 [D loss: 0.999996] [G loss: 1.000058] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2540 [D loss: 0.999992] [G loss: 1.000070] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2541 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2542 [D loss: 0.999994] [G loss: 1.000057] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2543 [D loss: 0.999970] [G loss: 1.000100] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2544 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2545 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2546 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2547 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
2548 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2549 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2550 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 72ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2551 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2552 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2553 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2554 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2555 [D loss: 0.999985] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2556 [D loss: 0.999983] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2557 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2558 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2559 [D loss: 0.999986] [G loss: 1.000081] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2560 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2561 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2562 [D loss: 0.999972] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2563 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2564 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2565 [D loss: 0.999990] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2566 [D loss: 0.999973] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2567 [D loss: 0.999985] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2568 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2569 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2570 [D loss: 0.999975] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2571 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2572 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2573 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2574 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2575 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2576 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2577 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2578 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2579 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2580 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2581 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2582 [D loss: 0.999982] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2583 [D loss: 0.999984] [G loss: 1.000085] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2584 [D loss: 0.999984] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2585 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2586 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2587 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2588 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2589 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2590 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2591 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2592 [D loss: 0.999983] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2593 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2594 [D loss: 0.999974] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2595 [D loss: 0.999982] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2596 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2597 [D loss: 0.999984] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2598 [D loss: 0.999981] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2599 [D loss: 0.999972] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2600 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 67ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2601 [D loss: 0.999971] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2602 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2603 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2604 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2605 [D loss: 0.999982] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2606 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2607 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 11ms/step
2608 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2609 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2610 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2611 [D loss: 0.999983] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2612 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2613 [D loss: 0.999984] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2614 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2615 [D loss: 0.999984] [G loss: 1.000075] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2616 [D loss: 0.999986] [G loss: 1.000072] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2617 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2618 [D loss: 0.999986] [G loss: 1.000080] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2619 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2620 [D loss: 0.999983] [G loss: 1.000075] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2621 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2622 [D loss: 0.999983] [G loss: 1.000078] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2623 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2624 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2625 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2626 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2627 [D loss: 0.999984] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2628 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2629 [D loss: 0.999982] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2630 [D loss: 0.999984] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2631 [D loss: 0.999983] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2632 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2633 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2634 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2635 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2636 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2637 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2638 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2639 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2640 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2641 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2642 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2643 [D loss: 0.999982] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2644 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2645 [D loss: 0.999981] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2646 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2647 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2648 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2649 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2650 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 62ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2651 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2652 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2653 [D loss: 0.999989] [G loss: 1.000065] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
2654 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2655 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2656 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2657 [D loss: 0.999981] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2658 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2659 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2660 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2661 [D loss: 0.999983] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2662 [D loss: 0.999973] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2663 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2664 [D loss: 0.999980] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2665 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2666 [D loss: 0.999981] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2667 [D loss: 0.999971] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2668 [D loss: 0.999988] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
2669 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2670 [D loss: 0.999973] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2671 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2672 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2673 [D loss: 0.999982] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2674 [D loss: 0.999982] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2675 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2676 [D loss: 0.999973] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2677 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2678 [D loss: 0.999981] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2679 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2680 [D loss: 0.999983] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2681 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2682 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2683 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2684 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2685 [D loss: 0.999974] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2686 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2687 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2688 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2689 [D loss: 0.999983] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2690 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2691 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2692 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2693 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2694 [D loss: 0.999973] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2695 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2696 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2697 [D loss: 0.999983] [G loss: 1.000072] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2698 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2699 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2700 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 63ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2701 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2702 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2703 [D loss: 0.999975] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2704 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2705 [D loss: 0.999982] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2706 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2707 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2708 [D loss: 0.999974] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2709 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2710 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2711 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2712 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2713 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2714 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2715 [D loss: 0.999985] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2716 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2717 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2718 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2719 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2720 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2721 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2722 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2723 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2724 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2725 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2726 [D loss: 0.999984] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2727 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2728 [D loss: 0.999985] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2729 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2730 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2731 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2732 [D loss: 0.999982] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2733 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2734 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2735 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2736 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2737 [D loss: 0.999989] [G loss: 1.000073] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2738 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2739 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2740 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2741 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2742 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2743 [D loss: 0.999972] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2744 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2745 [D loss: 0.999985] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2746 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2747 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2748 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2749 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2750 [D loss: 0.999974] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 62ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2751 [D loss: 0.999982] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2752 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2753 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2754 [D loss: 0.999983] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2755 [D loss: 0.999984] [G loss: 1.000075] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2756 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2757 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2758 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2759 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2760 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2761 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2762 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2763 [D loss: 0.999982] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2764 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2765 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2766 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2767 [D loss: 0.999985] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2768 [D loss: 0.999980] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2769 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2770 [D loss: 0.999979] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2771 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2772 [D loss: 0.999980] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2773 [D loss: 0.999983] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2774 [D loss: 0.999982] [G loss: 1.000074] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2775 [D loss: 0.999970] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2776 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2777 [D loss: 0.999981] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2778 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2779 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2780 [D loss: 0.999973] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2781 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 10ms/step
2782 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2783 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2784 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2785 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2786 [D loss: 0.999988] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2787 [D loss: 0.999983] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2788 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2789 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2790 [D loss: 0.999971] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2791 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2792 [D loss: 0.999973] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
2793 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2794 [D loss: 0.999985] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2795 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2796 [D loss: 0.999980] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2797 [D loss: 0.999982] [G loss: 1.000090] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2798 [D loss: 0.999972] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2799 [D loss: 0.999972] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2800 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 61ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2801 [D loss: 0.999982] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2802 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2803 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2804 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2805 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2806 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2807 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2808 [D loss: 0.999973] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2809 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2810 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2811 [D loss: 0.999983] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2812 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2813 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2814 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2815 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2816 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2817 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2818 [D loss: 0.999985] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2819 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2820 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2821 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2822 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2823 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2824 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2825 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2826 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2827 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2828 [D loss: 0.999986] [G loss: 1.000078] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2829 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2830 [D loss: 0.999983] [G loss: 1.000078] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2831 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2832 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2833 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2834 [D loss: 0.999982] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2835 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
2836 [D loss: 0.999972] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2837 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2838 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2839 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2840 [D loss: 0.999993] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2841 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2842 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2843 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2844 [D loss: 0.999990] [G loss: 1.000077] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2845 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2846 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2847 [D loss: 0.999983] [G loss: 1.000082] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2848 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2849 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2850 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
1/1 [==============================] - 0s 58ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2851 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2852 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2853 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2854 [D loss: 0.999982] [G loss: 1.000083] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2855 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2856 [D loss: 0.999985] [G loss: 1.000074] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2857 [D loss: 0.999980] [G loss: 1.000091] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2858 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2859 [D loss: 0.999988] [G loss: 1.000080] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2860 [D loss: 0.999975] [G loss: 1.000096] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2861 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2862 [D loss: 0.999984] [G loss: 1.000085] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2863 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2864 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2865 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2866 [D loss: 0.999982] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2867 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2868 [D loss: 0.999982] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2869 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2870 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2871 [D loss: 0.999982] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2872 [D loss: 0.999974] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2873 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2874 [D loss: 0.999986] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2875 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2876 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2877 [D loss: 0.999990] [G loss: 1.000074] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2878 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2879 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2880 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2881 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2882 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2883 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2884 [D loss: 0.999980] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2885 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2886 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2887 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2888 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2889 [D loss: 0.999972] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2890 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2891 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2892 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2893 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2894 [D loss: 0.999975] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2895 [D loss: 0.999974] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2896 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2897 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2898 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2899 [D loss: 0.999982] [G loss: 1.000071] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2900 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 68ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2901 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2902 [D loss: 0.999974] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2903 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2904 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2905 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2906 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2907 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2908 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2909 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2910 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2911 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
2912 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2913 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2914 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2915 [D loss: 0.999985] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2916 [D loss: 0.999980] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2917 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2918 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2919 [D loss: 0.999989] [G loss: 1.000064] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2920 [D loss: 0.999982] [G loss: 1.000091] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2921 [D loss: 0.999974] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2922 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2923 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2924 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2925 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2926 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2927 [D loss: 0.999982] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2928 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2929 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2930 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2931 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2932 [D loss: 0.999983] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2933 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2934 [D loss: 0.999982] [G loss: 1.000082] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2935 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2936 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2937 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2938 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2939 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2940 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2941 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
2942 [D loss: 0.999984] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2943 [D loss: 0.999984] [G loss: 1.000072] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2944 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
2945 [D loss: 0.999973] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2946 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2947 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2948 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2949 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2950 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 69ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2951 [D loss: 0.999981] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2952 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2953 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2954 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2955 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2956 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2957 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2958 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2959 [D loss: 0.999980] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2960 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2961 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2962 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2963 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2964 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2965 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
2966 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
2967 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2968 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
2969 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2970 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2971 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2972 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
2973 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2974 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2975 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2976 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2977 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2978 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2979 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2980 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2981 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2982 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2983 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2984 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
2985 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2986 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
2987 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2988 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2989 [D loss: 0.999981] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2990 [D loss: 0.999974] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
2991 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2992 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2993 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2994 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2995 [D loss: 0.999978] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2996 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2997 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
2998 [D loss: 0.999984] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2999 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000021]

Plot Loss

plot_losses(wgan.d_losses, wgan.g_losses)

Plot Wasserstein Distance

plot_wasserstein_distance(wgan.wasserstein_distances)

Generated Images at Different Epochs (Removing Dropout and Batchnormalization Layers From the Critic)

At 100 Epochs

At 1000 Epochs

At 2950 Epochs

Results

Training losses The graph shows similar output as the base model but now that we changed to Tanh activation with normalization to (-1,1), the loss values has improved for both discriminator and generator. However, towards the end of the graph for generator, we can see that the losses start to decrease, which means that the generator may be overfitting or the model is not learning effectively anymore. This decrease in loss might suggest that the generator is producing samples that are too similar to each other, or that the discriminator is not providing useful feedback to the generator.

Wasserstein Distance The Wasserstein distance’s behavior indicates periods of instability followed by improved performance. A negative Wasserstein distance indicates successful training progress, as it shows that the generator is now producing samples that are closer to the real data distribution. The stabilization of the distance reflects that the generator and discriminator have reached a more balanced and effective state. The trend over epoch shows that the Wasserstein distance is starting to increase which means that the generator's performance might be leveling off or improving at a slower rate.

Generated Images The generated images shows improvement as the epoch increases. The generated images at 2950 epoch is more detailed and. This indicates that the generator has learned to capture finer features of the handwritten digits. There is clear improvement in overall quality which demonstrates the models ability to learn to generate images that are similar to the real dataset.

In summary, while the training losses and Wasserstein distance suggest that the model has reached a point of balance and is experiencing some stability issues, the generated images demonstrate that the generator has successfully improved its output quality. This combination of evaluations suggests that the GAN has made significant strides in learning to generate realistic images. To further improve the quality of the generated images, we plan to experiment with removing dropout and batch normalization layers from the critic.

Using Tanh activation with normalization to the range of (-1, 1)

Potential Improvements

Normalization to (-1, 1) and Tanh Activation

Normalizing the input data to the range of (-1, 1) and using Tanh activation functions can significantly benefit the learning process. Tanh activation, which outputs values in the range (-1, 1), aligns well with the normalization range, ensuring that the data is centered around zero.

This can help in maintaining a stable training process by avoiding issues like saturation and vanishing gradients, which are common with activations that output larger ranges.

Tanh activation function encourages stronger gradient signals compared to the sigmoid function, especially when inputs are centered around zero. This can lead to more efficient and faster convergence during training, ultimately improving the quality of the generated images.

class WGAN():
    def __init__(self):
        self.img_rows = 28
        self.img_cols = 28
        self.channels = 1
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = 100

        # Following parameter and optimizer set as recommended in paper
        self.n_critic = 5
        self.clip_value = 0.01
        optimizer = RMSprop(lr=0.00005)

        # Build and compile the critic
        self.critic = self.build_critic()
        self.critic.compile(loss=self.wasserstein_loss,
            optimizer=optimizer,
            metrics=['accuracy'])

        # Build the generator
        self.generator = self.build_generator()

        # The generator takes noise as input and generated imgs
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)

        # For the combined model we will only train the generator
        self.critic.trainable = False

        # The critic takes generated images as input and determines validity
        valid = self.critic(img)

        # The combined model  (stacked generator and critic)
        self.combined = Model(z, valid)
        self.combined.compile(loss=self.wasserstein_loss,
            optimizer=optimizer,
            metrics=['accuracy'])

        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Wasserstein distance per epoch
        self.wasserstein_distances = []

    def wasserstein_loss(self, y_true, y_pred):
        return K.mean(y_true * y_pred)

    def build_generator(self):

        model = Sequential()

        model.add(Dense(1500 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 1500)))
        model.add(UpSampling2D())
        
        model.add(Conv2D(128, kernel_size=4, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        model.add(UpSampling2D())
        
        model.add(Conv2D(64, kernel_size=4, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(Conv2D(self.channels, kernel_size=4, padding="same"))
        model.add(Activation("tanh"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)

    def build_critic(self):

        model = Sequential()

        model.add(Conv2D(16, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Conv2D(32, kernel_size=3, strides=2, padding="same"))
        model.add(ZeroPadding2D(padding=((0,1),(0,1))))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Conv2D(64, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Conv2D(128, kernel_size=3, strides=1, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Flatten())
        model.add(Dense(1))

        model.summary()

        img = Input(shape=self.img_shape)
        validity = model(img)

        return Model(img, validity)

    def train(self, epochs, batch_size=128, sample_interval=50):

        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values
        y_train = preprocessed_df.iloc[:, 0].values
        X_train = X_train * 2.0 - 1.0  # Scale to [-1, 1]
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)

        # Adversarial ground truths
        valid = -np.ones((batch_size, 1))
        fake = np.ones((batch_size, 1))

        for epoch in range(epochs):

            for _ in range(self.n_critic):

                # ---------------------
                #  Train Discriminator
                # ---------------------

                # Select a random batch of images
                idx = np.random.randint(0, X_train.shape[0], batch_size)
                imgs = X_train[idx]
                
                # Sample noise as generator input
                noise = np.random.normal(0, 1, (batch_size, self.latent_dim))

                # Generate a batch of new images
                gen_imgs = self.generator.predict(noise)

                # Train the critic
                d_loss_real = self.critic.train_on_batch(imgs, valid)
                d_loss_fake = self.critic.train_on_batch(gen_imgs, fake)
                d_loss = 0.5 * np.add(d_loss_fake, d_loss_real)

                # Clip critic weights
                for l in self.critic.layers:
                    weights = l.get_weights()
                    weights = [np.clip(w, -self.clip_value, self.clip_value) for w in weights]
                    l.set_weights(weights)
                    
            # ---------------------
            #  Train Generator
            # ---------------------

            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Calculate and store Wasserstein distance for this epoch
            wasserstein_distance = -np.mean(self.d_losses[-self.n_critic:])  # Negative because we minimize negative loss
            self.wasserstein_distances.append(wasserstein_distance)
            
            # Plot the progress
            print ("%d [D loss: %f] [G loss: %f] [Wasserstein Distance: %f]" % (epoch, 1 - d_loss[0], 1 - g_loss[0], wasserstein_distance))

            # If at save interval => save generated image samples
            if epoch % sample_interval == 0:
                self.sample_images(epoch)

    def sample_images(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/wgan', exist_ok=True)
        os.makedirs('generated_images/wgan/tanh', exist_ok=True)
        fig.savefig("generated_images/wgan/tanh/wgan_{:d}.png".format(epoch))
        plt.close()

wgan = WGAN()
wgan.train(epochs=3000, batch_size=256, sample_interval=50)

Model: "sequential_14"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_49 (Conv2D)          (None, 14, 14, 16)        160       
                                                                 
 leaky_re_lu_44 (LeakyReLU)  (None, 14, 14, 16)        0         
                                                                 
 conv2d_50 (Conv2D)          (None, 7, 7, 32)          4640      
                                                                 
 zero_padding2d_2 (ZeroPaddi  (None, 8, 8, 32)         0         
 ng2D)                                                           
                                                                 
 leaky_re_lu_45 (LeakyReLU)  (None, 8, 8, 32)          0         
                                                                 
 conv2d_51 (Conv2D)          (None, 4, 4, 64)          18496     
                                                                 
 leaky_re_lu_46 (LeakyReLU)  (None, 4, 4, 64)          0         
                                                                 
 conv2d_52 (Conv2D)          (None, 4, 4, 128)         73856     
                                                                 
 leaky_re_lu_47 (LeakyReLU)  (None, 4, 4, 128)         0         
                                                                 
 flatten_15 (Flatten)        (None, 2048)              0         
                                                                 
 dense_24 (Dense)            (None, 1)                 2049      
                                                                 
=================================================================
Total params: 99,201
Trainable params: 99,201
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_15"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_25 (Dense)            (None, 73500)             7423500   
                                                                 
 reshape_12 (Reshape)        (None, 7, 7, 1500)        0         
                                                                 
 up_sampling2d_12 (UpSamplin  (None, 14, 14, 1500)     0         
 g2D)                                                            
                                                                 
 conv2d_53 (Conv2D)          (None, 14, 14, 128)       3072128   
                                                                 
 batch_normalization_21 (Bat  (None, 14, 14, 128)      512       
 chNormalization)                                                
                                                                 
 activation_17 (Activation)  (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_13 (UpSamplin  (None, 28, 28, 128)      0         
 g2D)                                                            
                                                                 
 conv2d_54 (Conv2D)          (None, 28, 28, 64)        131136    
                                                                 
 batch_normalization_22 (Bat  (None, 28, 28, 64)       256       
 chNormalization)                                                
                                                                 
 activation_18 (Activation)  (None, 28, 28, 64)        0         
                                                                 
 conv2d_55 (Conv2D)          (None, 28, 28, 1)         1025      
                                                                 
 activation_19 (Activation)  (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 10,628,557
Trainable params: 10,628,173
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 1s 38ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
0 [D loss: 0.999925] [G loss: 1.000149] [Wasserstein Distance: -0.000075]
1/1 [==============================] - 0s 146ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1 [D loss: 0.999942] [G loss: 1.000142] [Wasserstein Distance: -0.000067]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
2 [D loss: 0.999944] [G loss: 1.000142] [Wasserstein Distance: -0.000063]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
3 [D loss: 0.999946] [G loss: 1.000140] [Wasserstein Distance: -0.000061]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
4 [D loss: 0.999945] [G loss: 1.000142] [Wasserstein Distance: -0.000060]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
5 [D loss: 0.999946] [G loss: 1.000139] [Wasserstein Distance: -0.000055]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
6 [D loss: 0.999949] [G loss: 1.000138] [Wasserstein Distance: -0.000054]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
7 [D loss: 0.999953] [G loss: 1.000136] [Wasserstein Distance: -0.000052]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8 [D loss: 0.999957] [G loss: 1.000139] [Wasserstein Distance: -0.000050]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
9 [D loss: 0.999962] [G loss: 1.000142] [Wasserstein Distance: -0.000047]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
10 [D loss: 0.999967] [G loss: 1.000150] [Wasserstein Distance: -0.000042]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
11 [D loss: 0.999977] [G loss: 1.000156] [Wasserstein Distance: -0.000037]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
12 [D loss: 0.999988] [G loss: 1.000166] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
13 [D loss: 0.999990] [G loss: 1.000174] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
14 [D loss: 0.999988] [G loss: 1.000189] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
15 [D loss: 1.000015] [G loss: 1.000198] [Wasserstein Distance: -0.000008]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
16 [D loss: 0.999966] [G loss: 1.000219] [Wasserstein Distance: -0.000010]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
17 [D loss: 1.000020] [G loss: 1.000222] [Wasserstein Distance: -0.000004]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
18 [D loss: 0.999951] [G loss: 1.000236] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
19 [D loss: 1.000002] [G loss: 1.000227] [Wasserstein Distance: -0.000009]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
20 [D loss: 0.999961] [G loss: 1.000226] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
21 [D loss: 0.999983] [G loss: 1.000217] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
22 [D loss: 0.999983] [G loss: 1.000204] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
23 [D loss: 0.999979] [G loss: 1.000203] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
24 [D loss: 0.999987] [G loss: 1.000199] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
25 [D loss: 0.999985] [G loss: 1.000197] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
26 [D loss: 0.999967] [G loss: 1.000215] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
27 [D loss: 0.999970] [G loss: 1.000224] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
28 [D loss: 0.999960] [G loss: 1.000231] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
29 [D loss: 0.999955] [G loss: 1.000231] [Wasserstein Distance: -0.000033]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
30 [D loss: 0.999961] [G loss: 1.000224] [Wasserstein Distance: -0.000037]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
31 [D loss: 0.999958] [G loss: 1.000221] [Wasserstein Distance: -0.000039]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
32 [D loss: 0.999961] [G loss: 1.000225] [Wasserstein Distance: -0.000041]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
33 [D loss: 0.999954] [G loss: 1.000214] [Wasserstein Distance: -0.000042]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
34 [D loss: 0.999956] [G loss: 1.000207] [Wasserstein Distance: -0.000042]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
35 [D loss: 0.999956] [G loss: 1.000203] [Wasserstein Distance: -0.000043]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
36 [D loss: 0.999962] [G loss: 1.000189] [Wasserstein Distance: -0.000042]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
37 [D loss: 0.999963] [G loss: 1.000181] [Wasserstein Distance: -0.000042]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
38 [D loss: 0.999968] [G loss: 1.000174] [Wasserstein Distance: -0.000039]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
39 [D loss: 0.999962] [G loss: 1.000173] [Wasserstein Distance: -0.000038]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
40 [D loss: 0.999966] [G loss: 1.000165] [Wasserstein Distance: -0.000036]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
41 [D loss: 0.999967] [G loss: 1.000161] [Wasserstein Distance: -0.000035]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
42 [D loss: 0.999968] [G loss: 1.000153] [Wasserstein Distance: -0.000034]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
43 [D loss: 0.999969] [G loss: 1.000145] [Wasserstein Distance: -0.000034]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
44 [D loss: 0.999966] [G loss: 1.000145] [Wasserstein Distance: -0.000033]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
45 [D loss: 0.999966] [G loss: 1.000148] [Wasserstein Distance: -0.000033]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
46 [D loss: 0.999966] [G loss: 1.000144] [Wasserstein Distance: -0.000033]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
47 [D loss: 0.999968] [G loss: 1.000134] [Wasserstein Distance: -0.000033]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
48 [D loss: 0.999965] [G loss: 1.000129] [Wasserstein Distance: -0.000034]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
49 [D loss: 0.999971] [G loss: 1.000125] [Wasserstein Distance: -0.000033]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
50 [D loss: 0.999969] [G loss: 1.000125] [Wasserstein Distance: -0.000032]
1/1 [==============================] - 0s 66ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
51 [D loss: 0.999969] [G loss: 1.000115] [Wasserstein Distance: -0.000032]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
52 [D loss: 0.999971] [G loss: 1.000117] [Wasserstein Distance: -0.000031]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
53 [D loss: 0.999972] [G loss: 1.000113] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
54 [D loss: 0.999970] [G loss: 1.000114] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
55 [D loss: 0.999971] [G loss: 1.000109] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
56 [D loss: 0.999969] [G loss: 1.000108] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
57 [D loss: 0.999974] [G loss: 1.000102] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
58 [D loss: 0.999971] [G loss: 1.000103] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
59 [D loss: 0.999969] [G loss: 1.000100] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
60 [D loss: 0.999971] [G loss: 1.000099] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
61 [D loss: 0.999971] [G loss: 1.000097] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
62 [D loss: 0.999969] [G loss: 1.000095] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
63 [D loss: 0.999971] [G loss: 1.000092] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
64 [D loss: 0.999971] [G loss: 1.000086] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
65 [D loss: 0.999969] [G loss: 1.000086] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
66 [D loss: 0.999970] [G loss: 1.000087] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
67 [D loss: 0.999972] [G loss: 1.000085] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
68 [D loss: 0.999969] [G loss: 1.000087] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
69 [D loss: 0.999971] [G loss: 1.000084] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
70 [D loss: 0.999970] [G loss: 1.000077] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
71 [D loss: 0.999972] [G loss: 1.000081] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
72 [D loss: 0.999970] [G loss: 1.000082] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
73 [D loss: 0.999972] [G loss: 1.000078] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
74 [D loss: 0.999969] [G loss: 1.000078] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
75 [D loss: 0.999970] [G loss: 1.000081] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
76 [D loss: 0.999972] [G loss: 1.000083] [Wasserstein Distance: -0.000030]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
77 [D loss: 0.999974] [G loss: 1.000080] [Wasserstein Distance: -0.000029]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
78 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
79 [D loss: 0.999972] [G loss: 1.000078] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
80 [D loss: 0.999972] [G loss: 1.000079] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
81 [D loss: 0.999971] [G loss: 1.000075] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
82 [D loss: 0.999971] [G loss: 1.000075] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
83 [D loss: 0.999973] [G loss: 1.000074] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
84 [D loss: 0.999971] [G loss: 1.000075] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
85 [D loss: 0.999972] [G loss: 1.000073] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
86 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
87 [D loss: 0.999972] [G loss: 1.000073] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
88 [D loss: 0.999974] [G loss: 1.000071] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
89 [D loss: 0.999972] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
90 [D loss: 0.999973] [G loss: 1.000073] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
91 [D loss: 0.999972] [G loss: 1.000071] [Wasserstein Distance: -0.000028]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
92 [D loss: 0.999973] [G loss: 1.000071] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
93 [D loss: 0.999974] [G loss: 1.000071] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
94 [D loss: 0.999973] [G loss: 1.000072] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
95 [D loss: 0.999973] [G loss: 1.000071] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
96 [D loss: 0.999973] [G loss: 1.000071] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
97 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
98 [D loss: 0.999972] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
99 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
100 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
1/1 [==============================] - 0s 69ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
101 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
102 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
103 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
104 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
105 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
106 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
107 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
108 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
109 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
110 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
111 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
112 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
113 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
114 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
115 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
116 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
117 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
118 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
119 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
120 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
121 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
122 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
123 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
124 [D loss: 0.999972] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
125 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
126 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
127 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
128 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
129 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
130 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
131 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
132 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
133 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
134 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
135 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
136 [D loss: 0.999974] [G loss: 1.000071] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
137 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
138 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
139 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
140 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
141 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
142 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
143 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
144 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
145 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
146 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
147 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 35ms/step
8/8 [==============================] - 0s 10ms/step
148 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
149 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
150 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 63ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
151 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
152 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
153 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
154 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
155 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
156 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
157 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
158 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
159 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
160 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
161 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
162 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
163 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
164 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
165 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
166 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
167 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
168 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
169 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
170 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
171 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
172 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
173 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
174 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
175 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
176 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
177 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
178 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
179 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
180 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
181 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
182 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
183 [D loss: 0.999972] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
184 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
185 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
186 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
187 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
188 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
189 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
190 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
191 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
192 [D loss: 0.999973] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
193 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
194 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
195 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
196 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
197 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
198 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
199 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
200 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 60ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
201 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
202 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
203 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
204 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
205 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
206 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
207 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
208 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
209 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
210 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
211 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
212 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
213 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
214 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
215 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
216 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
217 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
218 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
219 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
220 [D loss: 0.999977] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
221 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
222 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
223 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
224 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
225 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
226 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
227 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
228 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
229 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
230 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
231 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
232 [D loss: 0.999977] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
233 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
234 [D loss: 0.999979] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
235 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
236 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
237 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
238 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
239 [D loss: 0.999980] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
240 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
241 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
242 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
243 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
244 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
245 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
246 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
247 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
248 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
249 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
250 [D loss: 0.999981] [G loss: 1.000060] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 65ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
251 [D loss: 0.999981] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
252 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
253 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
254 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
255 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
256 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
257 [D loss: 0.999978] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
258 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
259 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
260 [D loss: 0.999979] [G loss: 1.000053] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
261 [D loss: 0.999991] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
262 [D loss: 0.999987] [G loss: 1.000063] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
263 [D loss: 0.999981] [G loss: 1.000075] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
264 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
265 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
266 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
267 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
268 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
269 [D loss: 0.999977] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
270 [D loss: 0.999987] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
271 [D loss: 0.999987] [G loss: 1.000060] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
272 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
273 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
274 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
275 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
276 [D loss: 0.999978] [G loss: 1.000054] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
277 [D loss: 0.999989] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
278 [D loss: 0.999999] [G loss: 1.000053] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
279 [D loss: 0.999983] [G loss: 1.000081] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
280 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
281 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
282 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
283 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
284 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
285 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
286 [D loss: 0.999979] [G loss: 1.000056] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
287 [D loss: 0.999984] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
288 [D loss: 0.999991] [G loss: 1.000047] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
289 [D loss: 0.999995] [G loss: 1.000078] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
290 [D loss: 0.999984] [G loss: 1.000063] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
291 [D loss: 0.999978] [G loss: 1.000072] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
292 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
293 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
294 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
295 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
296 [D loss: 0.999978] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
297 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
298 [D loss: 0.999982] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
299 [D loss: 0.999997] [G loss: 1.000052] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
300 [D loss: 0.999999] [G loss: 1.000073] [Wasserstein Distance: -0.000013]
1/1 [==============================] - 0s 61ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
301 [D loss: 0.999982] [G loss: 1.000070] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
302 [D loss: 0.999978] [G loss: 1.000070] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
303 [D loss: 0.999980] [G loss: 1.000063] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
304 [D loss: 0.999987] [G loss: 1.000077] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
305 [D loss: 0.999992] [G loss: 1.000055] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
306 [D loss: 0.999984] [G loss: 1.000073] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
307 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
308 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
309 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
310 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
311 [D loss: 0.999981] [G loss: 1.000065] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
312 [D loss: 0.999982] [G loss: 1.000054] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
313 [D loss: 0.999987] [G loss: 1.000068] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
314 [D loss: 0.999999] [G loss: 1.000046] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
315 [D loss: 0.999988] [G loss: 1.000072] [Wasserstein Distance: -0.000012]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
316 [D loss: 0.999980] [G loss: 1.000063] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
317 [D loss: 0.999981] [G loss: 1.000068] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
318 [D loss: 0.999982] [G loss: 1.000058] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
319 [D loss: 0.999983] [G loss: 1.000074] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
320 [D loss: 0.999995] [G loss: 1.000050] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
321 [D loss: 0.999982] [G loss: 1.000070] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
322 [D loss: 0.999982] [G loss: 1.000061] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
323 [D loss: 0.999981] [G loss: 1.000068] [Wasserstein Distance: -0.000015]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
324 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
325 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
326 [D loss: 0.999978] [G loss: 1.000056] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
327 [D loss: 0.999983] [G loss: 1.000067] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
328 [D loss: 0.999984] [G loss: 1.000062] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
329 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
330 [D loss: 0.999981] [G loss: 1.000055] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
331 [D loss: 0.999984] [G loss: 1.000063] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
332 [D loss: 0.999985] [G loss: 1.000058] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
333 [D loss: 0.999990] [G loss: 1.000069] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
334 [D loss: 0.999989] [G loss: 1.000063] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
335 [D loss: 0.999980] [G loss: 1.000067] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
336 [D loss: 0.999978] [G loss: 1.000067] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
337 [D loss: 0.999980] [G loss: 1.000062] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
338 [D loss: 0.999991] [G loss: 1.000071] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
339 [D loss: 0.999993] [G loss: 1.000056] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
340 [D loss: 0.999989] [G loss: 1.000076] [Wasserstein Distance: -0.000014]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
341 [D loss: 0.999983] [G loss: 1.000064] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
342 [D loss: 0.999979] [G loss: 1.000065] [Wasserstein Distance: -0.000013]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
343 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
344 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
345 [D loss: 0.999978] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
346 [D loss: 0.999984] [G loss: 1.000056] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
347 [D loss: 0.999994] [G loss: 1.000070] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
348 [D loss: 0.999987] [G loss: 1.000064] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
349 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
350 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000016]
1/1 [==============================] - 0s 61ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
351 [D loss: 0.999978] [G loss: 1.000065] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
352 [D loss: 0.999979] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
353 [D loss: 0.999981] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
354 [D loss: 0.999988] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
355 [D loss: 0.999985] [G loss: 1.000063] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
356 [D loss: 0.999980] [G loss: 1.000066] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
357 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
358 [D loss: 0.999978] [G loss: 1.000065] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
359 [D loss: 0.999977] [G loss: 1.000058] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
360 [D loss: 0.999978] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
361 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
362 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
363 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
364 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
365 [D loss: 0.999980] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
366 [D loss: 0.999989] [G loss: 1.000055] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
367 [D loss: 0.999992] [G loss: 1.000070] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
368 [D loss: 0.999981] [G loss: 1.000068] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
369 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
370 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
371 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
372 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
373 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
374 [D loss: 0.999979] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
375 [D loss: 0.999984] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
376 [D loss: 0.999990] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
377 [D loss: 0.999979] [G loss: 1.000067] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
378 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
379 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
380 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
381 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
382 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
383 [D loss: 0.999979] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
384 [D loss: 0.999981] [G loss: 1.000068] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
385 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
386 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
387 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
388 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
389 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
390 [D loss: 0.999979] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
391 [D loss: 0.999986] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
392 [D loss: 0.999989] [G loss: 1.000061] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
393 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
394 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
395 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
396 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
397 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
398 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
399 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
400 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 70ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
401 [D loss: 0.999977] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
402 [D loss: 0.999982] [G loss: 1.000057] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
403 [D loss: 0.999983] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
404 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
405 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
406 [D loss: 0.999975] [G loss: 1.000058] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
407 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
408 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
409 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
410 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
411 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
412 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
413 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
414 [D loss: 0.999979] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
415 [D loss: 0.999984] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
416 [D loss: 0.999991] [G loss: 1.000053] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
417 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
418 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
419 [D loss: 0.999978] [G loss: 1.000065] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
420 [D loss: 0.999979] [G loss: 1.000058] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
421 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
422 [D loss: 0.999979] [G loss: 1.000058] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
423 [D loss: 0.999979] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
424 [D loss: 0.999987] [G loss: 1.000048] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
425 [D loss: 0.999980] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
426 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
427 [D loss: 0.999977] [G loss: 1.000058] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
428 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
429 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
430 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
431 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
432 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
433 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
434 [D loss: 0.999978] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
435 [D loss: 0.999976] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
436 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
437 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
438 [D loss: 0.999975] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
439 [D loss: 0.999977] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
440 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
441 [D loss: 0.999980] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
442 [D loss: 0.999984] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
443 [D loss: 0.999984] [G loss: 1.000055] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
444 [D loss: 0.999978] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
445 [D loss: 0.999975] [G loss: 1.000062] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
446 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
447 [D loss: 0.999974] [G loss: 1.000056] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
448 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
449 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
450 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 75ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
451 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
452 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
453 [D loss: 0.999975] [G loss: 1.000057] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
454 [D loss: 0.999978] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
455 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
456 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
457 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
458 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
459 [D loss: 0.999982] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
460 [D loss: 0.999984] [G loss: 1.000052] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
461 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
462 [D loss: 0.999979] [G loss: 1.000055] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
463 [D loss: 0.999981] [G loss: 1.000068] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
464 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
465 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
466 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
467 [D loss: 0.999972] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
468 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
469 [D loss: 0.999979] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
470 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
471 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
472 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
473 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
474 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
475 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
476 [D loss: 0.999974] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
477 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
478 [D loss: 0.999980] [G loss: 1.000057] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
479 [D loss: 0.999985] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
480 [D loss: 0.999987] [G loss: 1.000058] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
481 [D loss: 0.999981] [G loss: 1.000068] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
482 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
483 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
484 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
485 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
486 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
487 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
488 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
489 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
490 [D loss: 0.999977] [G loss: 1.000055] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
491 [D loss: 0.999983] [G loss: 1.000070] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
492 [D loss: 0.999981] [G loss: 1.000054] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
493 [D loss: 0.999982] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
494 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
495 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
496 [D loss: 0.999976] [G loss: 1.000057] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
497 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
498 [D loss: 0.999974] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
499 [D loss: 0.999976] [G loss: 1.000059] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
500 [D loss: 0.999975] [G loss: 1.000060] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 87ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
501 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
502 [D loss: 0.999977] [G loss: 1.000056] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
503 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
504 [D loss: 0.999976] [G loss: 1.000058] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
505 [D loss: 0.999979] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
506 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
507 [D loss: 0.999981] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
508 [D loss: 0.999986] [G loss: 1.000050] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
509 [D loss: 0.999981] [G loss: 1.000064] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
510 [D loss: 0.999977] [G loss: 1.000061] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
511 [D loss: 0.999976] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
512 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
513 [D loss: 0.999978] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
514 [D loss: 0.999979] [G loss: 1.000050] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
515 [D loss: 0.999980] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
516 [D loss: 0.999979] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
517 [D loss: 0.999981] [G loss: 1.000063] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
518 [D loss: 0.999986] [G loss: 1.000051] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
519 [D loss: 0.999980] [G loss: 1.000070] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
520 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
521 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
522 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
523 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
524 [D loss: 0.999975] [G loss: 1.000054] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
525 [D loss: 0.999981] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
526 [D loss: 0.999980] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
527 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
528 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
529 [D loss: 0.999974] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
530 [D loss: 0.999974] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
531 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
532 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
533 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
534 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
535 [D loss: 0.999980] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
536 [D loss: 0.999986] [G loss: 1.000052] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
537 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
538 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
539 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
540 [D loss: 0.999981] [G loss: 1.000059] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
541 [D loss: 0.999984] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
542 [D loss: 0.999981] [G loss: 1.000057] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
543 [D loss: 0.999979] [G loss: 1.000064] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
544 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
545 [D loss: 0.999974] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
546 [D loss: 0.999975] [G loss: 1.000059] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
547 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
548 [D loss: 0.999981] [G loss: 1.000057] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
549 [D loss: 0.999980] [G loss: 1.000068] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
550 [D loss: 0.999978] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 74ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
551 [D loss: 0.999977] [G loss: 1.000065] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
552 [D loss: 0.999979] [G loss: 1.000062] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
553 [D loss: 0.999980] [G loss: 1.000057] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
554 [D loss: 0.999982] [G loss: 1.000058] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
555 [D loss: 0.999982] [G loss: 1.000061] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
556 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
557 [D loss: 0.999980] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
558 [D loss: 0.999978] [G loss: 1.000065] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
559 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
560 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
561 [D loss: 0.999976] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
562 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
563 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
564 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
565 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
566 [D loss: 0.999977] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
567 [D loss: 0.999981] [G loss: 1.000060] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
568 [D loss: 0.999982] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
569 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
570 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
571 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
572 [D loss: 0.999974] [G loss: 1.000065] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
573 [D loss: 0.999977] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
574 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
575 [D loss: 0.999978] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
576 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
577 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
578 [D loss: 0.999977] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
579 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
580 [D loss: 0.999980] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
581 [D loss: 0.999977] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
582 [D loss: 0.999979] [G loss: 1.000054] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
583 [D loss: 0.999977] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
584 [D loss: 0.999979] [G loss: 1.000058] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
585 [D loss: 0.999978] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
586 [D loss: 0.999977] [G loss: 1.000060] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
587 [D loss: 0.999978] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
588 [D loss: 0.999974] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
589 [D loss: 0.999973] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
590 [D loss: 0.999972] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
591 [D loss: 0.999975] [G loss: 1.000063] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
592 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
593 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
594 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
595 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
596 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
597 [D loss: 0.999980] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
598 [D loss: 0.999986] [G loss: 1.000059] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
599 [D loss: 0.999978] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
600 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 74ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
601 [D loss: 0.999974] [G loss: 1.000068] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
602 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
603 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
604 [D loss: 0.999977] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
605 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
606 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
607 [D loss: 0.999977] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
608 [D loss: 0.999978] [G loss: 1.000061] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
609 [D loss: 0.999978] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
610 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
611 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
612 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
613 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
614 [D loss: 0.999972] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
615 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
616 [D loss: 0.999982] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
617 [D loss: 0.999978] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
618 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
619 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
620 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
621 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
622 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
623 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
624 [D loss: 0.999975] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
625 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
626 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
627 [D loss: 0.999980] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
628 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
629 [D loss: 0.999978] [G loss: 1.000064] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
630 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
631 [D loss: 0.999974] [G loss: 1.000063] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
632 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
633 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
634 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
635 [D loss: 0.999975] [G loss: 1.000064] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
636 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
637 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
638 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
639 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
640 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
641 [D loss: 0.999983] [G loss: 1.000061] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
642 [D loss: 0.999980] [G loss: 1.000065] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
643 [D loss: 0.999979] [G loss: 1.000065] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
644 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
645 [D loss: 0.999977] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
646 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
647 [D loss: 0.999973] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
648 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
649 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
650 [D loss: 0.999981] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 100ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
651 [D loss: 0.999988] [G loss: 1.000059] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
652 [D loss: 0.999981] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
653 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
654 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 18ms/step
655 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
656 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
657 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
658 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
659 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
660 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
661 [D loss: 0.999984] [G loss: 1.000056] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
662 [D loss: 0.999982] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
663 [D loss: 0.999979] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
664 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
665 [D loss: 0.999978] [G loss: 1.000063] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
666 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
667 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
668 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
669 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
670 [D loss: 0.999976] [G loss: 1.000066] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
671 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
672 [D loss: 0.999974] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
673 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
674 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
675 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
676 [D loss: 0.999977] [G loss: 1.000059] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
677 [D loss: 0.999980] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
678 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
679 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
680 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
681 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
682 [D loss: 0.999976] [G loss: 1.000065] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
683 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
684 [D loss: 0.999975] [G loss: 1.000067] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
685 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
686 [D loss: 0.999981] [G loss: 1.000060] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
687 [D loss: 0.999986] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
688 [D loss: 0.999980] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
689 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
690 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
691 [D loss: 0.999972] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
692 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
693 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 12ms/step
694 [D loss: 0.999976] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
695 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
696 [D loss: 0.999976] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
697 [D loss: 0.999973] [G loss: 1.000071] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
698 [D loss: 0.999982] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
699 [D loss: 0.999975] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
700 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 74ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
701 [D loss: 0.999973] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
702 [D loss: 0.999975] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
703 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
704 [D loss: 0.999980] [G loss: 1.000065] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
705 [D loss: 0.999982] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
706 [D loss: 0.999984] [G loss: 1.000060] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
707 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
708 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
709 [D loss: 0.999975] [G loss: 1.000070] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
710 [D loss: 0.999973] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
711 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
712 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
713 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
714 [D loss: 0.999979] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
715 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
716 [D loss: 0.999978] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
717 [D loss: 0.999977] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
718 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
719 [D loss: 0.999976] [G loss: 1.000062] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
720 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
721 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
722 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
723 [D loss: 0.999981] [G loss: 1.000063] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
724 [D loss: 0.999987] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
725 [D loss: 0.999984] [G loss: 1.000065] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
726 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
727 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
728 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
729 [D loss: 0.999980] [G loss: 1.000068] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
730 [D loss: 0.999981] [G loss: 1.000066] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
731 [D loss: 0.999980] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
732 [D loss: 0.999981] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
733 [D loss: 0.999984] [G loss: 1.000065] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
734 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
735 [D loss: 0.999978] [G loss: 1.000066] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
736 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
737 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
738 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
739 [D loss: 0.999978] [G loss: 1.000066] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
740 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
741 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
742 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
743 [D loss: 0.999977] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
744 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
745 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
746 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
747 [D loss: 0.999973] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
748 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
749 [D loss: 0.999972] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
750 [D loss: 0.999975] [G loss: 1.000069] [Wasserstein Distance: -0.000026]
1/1 [==============================] - 0s 75ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
751 [D loss: 0.999975] [G loss: 1.000068] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
752 [D loss: 0.999979] [G loss: 1.000066] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
753 [D loss: 0.999976] [G loss: 1.000064] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
754 [D loss: 0.999980] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
755 [D loss: 0.999985] [G loss: 1.000060] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
756 [D loss: 0.999982] [G loss: 1.000064] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
757 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
758 [D loss: 0.999978] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
759 [D loss: 0.999988] [G loss: 1.000061] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
760 [D loss: 0.999979] [G loss: 1.000070] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
761 [D loss: 0.999977] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
762 [D loss: 0.999978] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
763 [D loss: 0.999979] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
764 [D loss: 0.999981] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
765 [D loss: 0.999983] [G loss: 1.000064] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
766 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
767 [D loss: 0.999984] [G loss: 1.000066] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
768 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
769 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
770 [D loss: 0.999979] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
771 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
772 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
773 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
774 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
775 [D loss: 0.999973] [G loss: 1.000073] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
776 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
777 [D loss: 0.999978] [G loss: 1.000068] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
778 [D loss: 0.999983] [G loss: 1.000067] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
779 [D loss: 0.999983] [G loss: 1.000067] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
780 [D loss: 0.999982] [G loss: 1.000074] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
781 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
782 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
783 [D loss: 0.999982] [G loss: 1.000067] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
784 [D loss: 0.999979] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
785 [D loss: 0.999979] [G loss: 1.000067] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
786 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
787 [D loss: 0.999980] [G loss: 1.000063] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
788 [D loss: 0.999980] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
789 [D loss: 0.999983] [G loss: 1.000067] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
790 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
791 [D loss: 0.999974] [G loss: 1.000070] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
792 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
793 [D loss: 0.999974] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
794 [D loss: 0.999974] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
795 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
796 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
797 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
798 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
799 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
800 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 75ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
801 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
802 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
803 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
804 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
805 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
806 [D loss: 0.999988] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
807 [D loss: 0.999985] [G loss: 1.000066] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
808 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
809 [D loss: 0.999980] [G loss: 1.000069] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
810 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
811 [D loss: 0.999982] [G loss: 1.000067] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
812 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
813 [D loss: 0.999977] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
814 [D loss: 0.999983] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
815 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
816 [D loss: 0.999977] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
817 [D loss: 0.999976] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
818 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
819 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
820 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
821 [D loss: 0.999979] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
822 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
823 [D loss: 0.999977] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
824 [D loss: 0.999979] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
825 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
826 [D loss: 0.999974] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
827 [D loss: 0.999975] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
828 [D loss: 0.999973] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
829 [D loss: 0.999981] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
830 [D loss: 0.999984] [G loss: 1.000068] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
831 [D loss: 0.999982] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
832 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
833 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
834 [D loss: 0.999974] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
835 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
836 [D loss: 0.999974] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
837 [D loss: 0.999977] [G loss: 1.000067] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
838 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
839 [D loss: 0.999979] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
840 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
841 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
842 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
843 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
844 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
845 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
846 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
847 [D loss: 0.999978] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
848 [D loss: 0.999987] [G loss: 1.000064] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
849 [D loss: 0.999983] [G loss: 1.000071] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
850 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 72ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
851 [D loss: 0.999979] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
852 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
853 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
854 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
855 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
856 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
857 [D loss: 0.999973] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
858 [D loss: 0.999972] [G loss: 1.000074] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
859 [D loss: 0.999973] [G loss: 1.000080] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
860 [D loss: 0.999980] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
861 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
862 [D loss: 0.999986] [G loss: 1.000069] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
863 [D loss: 0.999980] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
864 [D loss: 0.999979] [G loss: 1.000075] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
865 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
866 [D loss: 0.999977] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
867 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
868 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
869 [D loss: 0.999973] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
870 [D loss: 0.999976] [G loss: 1.000069] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
871 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
872 [D loss: 0.999980] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
873 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
874 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
875 [D loss: 0.999983] [G loss: 1.000072] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
876 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
877 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
878 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
879 [D loss: 0.999974] [G loss: 1.000072] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
880 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
881 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
882 [D loss: 0.999981] [G loss: 1.000071] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
883 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
884 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
885 [D loss: 0.999978] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
886 [D loss: 0.999981] [G loss: 1.000063] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
887 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
888 [D loss: 0.999981] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
889 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
890 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
891 [D loss: 0.999977] [G loss: 1.000071] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
892 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
893 [D loss: 0.999976] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
894 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
895 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
896 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
897 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
898 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
899 [D loss: 0.999980] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
900 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 73ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
901 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
902 [D loss: 0.999980] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
903 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
904 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
905 [D loss: 0.999974] [G loss: 1.000073] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
906 [D loss: 0.999986] [G loss: 1.000069] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
907 [D loss: 0.999984] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
908 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
909 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
910 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
911 [D loss: 0.999991] [G loss: 1.000061] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
912 [D loss: 0.999983] [G loss: 1.000072] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
913 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
914 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
915 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
916 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
917 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
918 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
919 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
920 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
921 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
922 [D loss: 0.999986] [G loss: 1.000071] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
923 [D loss: 0.999988] [G loss: 1.000058] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
924 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
925 [D loss: 0.999978] [G loss: 1.000071] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
926 [D loss: 0.999981] [G loss: 1.000074] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
927 [D loss: 0.999981] [G loss: 1.000070] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
928 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
929 [D loss: 0.999976] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
930 [D loss: 0.999972] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
931 [D loss: 0.999975] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
932 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
933 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
934 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
935 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
936 [D loss: 0.999979] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
937 [D loss: 0.999972] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
938 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
939 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
940 [D loss: 0.999978] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
941 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
942 [D loss: 0.999977] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
943 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
944 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
945 [D loss: 0.999976] [G loss: 1.000072] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
946 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
947 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
948 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
949 [D loss: 0.999978] [G loss: 1.000069] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
950 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 66ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
951 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
952 [D loss: 0.999973] [G loss: 1.000075] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
953 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
954 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
955 [D loss: 0.999978] [G loss: 1.000073] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
956 [D loss: 0.999985] [G loss: 1.000070] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
957 [D loss: 0.999985] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
958 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
959 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
960 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
961 [D loss: 0.999977] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
962 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
963 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
964 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
965 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
966 [D loss: 0.999981] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
967 [D loss: 0.999983] [G loss: 1.000071] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
968 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
969 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
970 [D loss: 0.999983] [G loss: 1.000073] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
971 [D loss: 0.999987] [G loss: 1.000068] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
972 [D loss: 0.999987] [G loss: 1.000073] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
973 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
974 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
975 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
976 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
977 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
978 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
979 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
980 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
981 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
982 [D loss: 0.999972] [G loss: 1.000082] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
983 [D loss: 0.999973] [G loss: 1.000082] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
984 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
985 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
986 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
987 [D loss: 0.999975] [G loss: 1.000074] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
988 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
989 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
990 [D loss: 0.999982] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
991 [D loss: 0.999983] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
992 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
993 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
994 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
995 [D loss: 0.999975] [G loss: 1.000075] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
996 [D loss: 0.999986] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
997 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
998 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
999 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1000 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 118ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1001 [D loss: 0.999976] [G loss: 1.000071] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1002 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1003 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
1004 [D loss: 0.999976] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1005 [D loss: 0.999975] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1006 [D loss: 0.999979] [G loss: 1.000068] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
1007 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1008 [D loss: 0.999976] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1009 [D loss: 0.999975] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1010 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1011 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1012 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1013 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1014 [D loss: 0.999980] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1015 [D loss: 0.999979] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1016 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1017 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1018 [D loss: 0.999974] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1019 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1020 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1021 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1022 [D loss: 0.999975] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1023 [D loss: 0.999977] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1024 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1025 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1026 [D loss: 0.999974] [G loss: 1.000079] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1027 [D loss: 0.999976] [G loss: 1.000075] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1028 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1029 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1030 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1031 [D loss: 0.999981] [G loss: 1.000072] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1032 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1033 [D loss: 0.999975] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1034 [D loss: 0.999975] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1035 [D loss: 0.999977] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1036 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1037 [D loss: 0.999986] [G loss: 1.000067] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1038 [D loss: 0.999981] [G loss: 1.000075] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1039 [D loss: 0.999982] [G loss: 1.000078] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1040 [D loss: 0.999986] [G loss: 1.000067] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1041 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1042 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1043 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1044 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1045 [D loss: 0.999981] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1046 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1047 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1048 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1049 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1050 [D loss: 0.999974] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 70ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1051 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1052 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1053 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1054 [D loss: 0.999972] [G loss: 1.000083] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1055 [D loss: 0.999973] [G loss: 1.000083] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1056 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1057 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1058 [D loss: 0.999975] [G loss: 1.000082] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1059 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1060 [D loss: 0.999974] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1061 [D loss: 0.999981] [G loss: 1.000070] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1062 [D loss: 0.999995] [G loss: 1.000075] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1063 [D loss: 0.999981] [G loss: 1.000071] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1064 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1065 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1066 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1067 [D loss: 0.999974] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1068 [D loss: 0.999976] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1069 [D loss: 0.999974] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1070 [D loss: 0.999980] [G loss: 1.000073] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1071 [D loss: 0.999985] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1072 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1073 [D loss: 0.999974] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1074 [D loss: 0.999971] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1075 [D loss: 0.999975] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1076 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1077 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1078 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1079 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1080 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1081 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1082 [D loss: 0.999978] [G loss: 1.000077] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1083 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1084 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1085 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1086 [D loss: 0.999977] [G loss: 1.000076] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1087 [D loss: 0.999977] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1088 [D loss: 0.999979] [G loss: 1.000077] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1089 [D loss: 0.999984] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1090 [D loss: 0.999981] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1091 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1092 [D loss: 0.999979] [G loss: 1.000070] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1093 [D loss: 0.999972] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1094 [D loss: 0.999974] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1095 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1096 [D loss: 0.999979] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1097 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1098 [D loss: 0.999989] [G loss: 1.000068] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1099 [D loss: 0.999983] [G loss: 1.000080] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1100 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000018]
1/1 [==============================] - 0s 85ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1101 [D loss: 0.999980] [G loss: 1.000079] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1102 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1103 [D loss: 0.999974] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1104 [D loss: 0.999978] [G loss: 1.000081] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1105 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1106 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1107 [D loss: 0.999983] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1108 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1109 [D loss: 0.999977] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1110 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1111 [D loss: 0.999978] [G loss: 1.000074] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1112 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1113 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1114 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1115 [D loss: 0.999974] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1116 [D loss: 0.999975] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1117 [D loss: 0.999974] [G loss: 1.000084] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1118 [D loss: 0.999973] [G loss: 1.000089] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1119 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1120 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1121 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1122 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1123 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1124 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1125 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1126 [D loss: 0.999980] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1127 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1128 [D loss: 0.999975] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1129 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1130 [D loss: 0.999983] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1131 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1132 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
1133 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1134 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1135 [D loss: 0.999982] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1136 [D loss: 0.999978] [G loss: 1.000079] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1137 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1138 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1139 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1140 [D loss: 0.999975] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1141 [D loss: 0.999978] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1142 [D loss: 0.999988] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1143 [D loss: 0.999981] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1144 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1145 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1146 [D loss: 0.999975] [G loss: 1.000077] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1147 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1148 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1149 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1150 [D loss: 0.999978] [G loss: 1.000078] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 84ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1151 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1152 [D loss: 0.999986] [G loss: 1.000077] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1153 [D loss: 0.999977] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1154 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1155 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1156 [D loss: 0.999975] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1157 [D loss: 0.999979] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1158 [D loss: 0.999979] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1159 [D loss: 0.999976] [G loss: 1.000078] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1160 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1161 [D loss: 0.999973] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1162 [D loss: 0.999977] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1163 [D loss: 0.999976] [G loss: 1.000081] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1164 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1165 [D loss: 0.999979] [G loss: 1.000079] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1166 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1167 [D loss: 0.999976] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1168 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1169 [D loss: 0.999985] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1170 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1171 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1172 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1173 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1174 [D loss: 0.999977] [G loss: 1.000081] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1175 [D loss: 0.999989] [G loss: 1.000074] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1176 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
1177 [D loss: 0.999978] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1178 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1179 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1180 [D loss: 0.999983] [G loss: 1.000073] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1181 [D loss: 0.999984] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1182 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1183 [D loss: 0.999975] [G loss: 1.000085] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1184 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1185 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1186 [D loss: 0.999976] [G loss: 1.000083] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1187 [D loss: 0.999978] [G loss: 1.000080] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1188 [D loss: 0.999976] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1189 [D loss: 0.999972] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1190 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1191 [D loss: 0.999974] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1192 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1193 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1194 [D loss: 0.999975] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1195 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1196 [D loss: 0.999982] [G loss: 1.000075] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1197 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1198 [D loss: 0.999979] [G loss: 1.000081] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1199 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1200 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 73ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1201 [D loss: 0.999974] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1202 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1203 [D loss: 0.999972] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1204 [D loss: 0.999976] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1205 [D loss: 0.999980] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1206 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1207 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1208 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1209 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1210 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1211 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1212 [D loss: 0.999975] [G loss: 1.000093] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1213 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1214 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1215 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1216 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1217 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1218 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1219 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1220 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1221 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1222 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1223 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1224 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1225 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1226 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1227 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1228 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1229 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
1230 [D loss: 0.999973] [G loss: 1.000087] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1231 [D loss: 0.999973] [G loss: 1.000088] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1232 [D loss: 0.999971] [G loss: 1.000094] [Wasserstein Distance: -0.000027]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1233 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1234 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1235 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1236 [D loss: 0.999980] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1237 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1238 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1239 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1240 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1241 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1242 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1243 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1244 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1245 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1246 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1247 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1248 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1249 [D loss: 0.999976] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1250 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 98ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
1251 [D loss: 0.999977] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1252 [D loss: 0.999986] [G loss: 1.000080] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1253 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1254 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1255 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1256 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1257 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1258 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1259 [D loss: 0.999975] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1260 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1261 [D loss: 0.999980] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1262 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1263 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1264 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1265 [D loss: 0.999981] [G loss: 1.000080] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1266 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1267 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1268 [D loss: 0.999976] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1269 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1270 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1271 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1272 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1273 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1274 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1275 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1276 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1277 [D loss: 0.999974] [G loss: 1.000090] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1278 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1279 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1280 [D loss: 0.999977] [G loss: 1.000085] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1281 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1282 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1283 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1284 [D loss: 0.999983] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1285 [D loss: 0.999981] [G loss: 1.000082] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1286 [D loss: 0.999982] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1287 [D loss: 0.999981] [G loss: 1.000083] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1288 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1289 [D loss: 0.999976] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1290 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1291 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1292 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1293 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1294 [D loss: 0.999973] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1295 [D loss: 0.999975] [G loss: 1.000090] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
1296 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1297 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1298 [D loss: 0.999974] [G loss: 1.000088] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1299 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 13ms/step
1300 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 96ms/step
8/8 [==============================] - 0s 26ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 24ms/step
8/8 [==============================] - 0s 12ms/step
1301 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1302 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1303 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1304 [D loss: 0.999983] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1305 [D loss: 0.999980] [G loss: 1.000077] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1306 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1307 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1308 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1309 [D loss: 0.999973] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1310 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1311 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1312 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1313 [D loss: 0.999978] [G loss: 1.000082] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1314 [D loss: 0.999974] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1315 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
1316 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1317 [D loss: 0.999972] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1318 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1319 [D loss: 0.999971] [G loss: 1.000089] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1320 [D loss: 0.999975] [G loss: 1.000093] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1321 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000026]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1322 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1323 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1324 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1325 [D loss: 0.999977] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1326 [D loss: 0.999978] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1327 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1328 [D loss: 0.999974] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1329 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1330 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1331 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1332 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1333 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1334 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1335 [D loss: 0.999979] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1336 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1337 [D loss: 0.999975] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1338 [D loss: 0.999973] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1339 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1340 [D loss: 0.999979] [G loss: 1.000085] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1341 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1342 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1343 [D loss: 0.999982] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1344 [D loss: 0.999984] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1345 [D loss: 0.999982] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1346 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1347 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1348 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1349 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1350 [D loss: 0.999974] [G loss: 1.000082] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 65ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1351 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1352 [D loss: 0.999981] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1353 [D loss: 0.999978] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1354 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1355 [D loss: 0.999985] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1356 [D loss: 0.999984] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1357 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1358 [D loss: 0.999975] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1359 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1360 [D loss: 0.999978] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1361 [D loss: 0.999974] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1362 [D loss: 0.999977] [G loss: 1.000088] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1363 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1364 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1365 [D loss: 0.999979] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1366 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1367 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1368 [D loss: 0.999975] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1369 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1370 [D loss: 0.999974] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1371 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1372 [D loss: 0.999976] [G loss: 1.000087] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
1373 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
1374 [D loss: 0.999975] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1375 [D loss: 0.999974] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1376 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1377 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1378 [D loss: 0.999977] [G loss: 1.000087] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
1379 [D loss: 0.999979] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1380 [D loss: 0.999978] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1381 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1382 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1383 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1384 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1385 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1386 [D loss: 0.999974] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1387 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1388 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1389 [D loss: 0.999977] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1390 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1391 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1392 [D loss: 0.999981] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1393 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1394 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1395 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1396 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1397 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1398 [D loss: 0.999981] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1399 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1400 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 69ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1401 [D loss: 0.999975] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1402 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1403 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
1404 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1405 [D loss: 0.999981] [G loss: 1.000079] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1406 [D loss: 0.999983] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1407 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1408 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1409 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1410 [D loss: 0.999982] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1411 [D loss: 0.999990] [G loss: 1.000079] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
1412 [D loss: 0.999982] [G loss: 1.000093] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1413 [D loss: 0.999975] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1414 [D loss: 0.999974] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1415 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1416 [D loss: 0.999975] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1417 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1418 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1419 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
1420 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1421 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1422 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1423 [D loss: 0.999979] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1424 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1425 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1426 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1427 [D loss: 0.999975] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1428 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1429 [D loss: 0.999975] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1430 [D loss: 0.999975] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1431 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1432 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1433 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1434 [D loss: 0.999976] [G loss: 1.000090] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1435 [D loss: 0.999988] [G loss: 1.000076] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1436 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1437 [D loss: 0.999974] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1438 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1439 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1440 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1441 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1442 [D loss: 0.999980] [G loss: 1.000084] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1443 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1444 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1445 [D loss: 0.999973] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1446 [D loss: 0.999975] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1447 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1448 [D loss: 0.999975] [G loss: 1.000093] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1449 [D loss: 0.999975] [G loss: 1.000090] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1450 [D loss: 0.999974] [G loss: 1.000097] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 75ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1451 [D loss: 0.999975] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1452 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1453 [D loss: 0.999974] [G loss: 1.000100] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1454 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1455 [D loss: 0.999974] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1456 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1457 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1458 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1459 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1460 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1461 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1462 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1463 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1464 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1465 [D loss: 0.999974] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1466 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1467 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1468 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1469 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1470 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1471 [D loss: 0.999973] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1472 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1473 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1474 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1475 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1476 [D loss: 0.999974] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1477 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1478 [D loss: 0.999983] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1479 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1480 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1481 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1482 [D loss: 0.999984] [G loss: 1.000088] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1483 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1484 [D loss: 0.999981] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1485 [D loss: 0.999975] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1486 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1487 [D loss: 0.999978] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1488 [D loss: 0.999980] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
1489 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1490 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1491 [D loss: 0.999975] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1492 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1493 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1494 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1495 [D loss: 0.999981] [G loss: 1.000087] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1496 [D loss: 0.999983] [G loss: 1.000085] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1497 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1498 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1499 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1500 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 78ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1501 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1502 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 12ms/step
1503 [D loss: 0.999972] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1504 [D loss: 0.999974] [G loss: 1.000098] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1505 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1506 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1507 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1508 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1509 [D loss: 0.999979] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1510 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1511 [D loss: 0.999975] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1512 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1513 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1514 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1515 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1516 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1517 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1518 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1519 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1520 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1521 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1522 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1523 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1524 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1525 [D loss: 0.999973] [G loss: 1.000099] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1526 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1527 [D loss: 0.999981] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1528 [D loss: 0.999986] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1529 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1530 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1531 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1532 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1533 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1534 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1535 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1536 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1537 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1538 [D loss: 0.999975] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1539 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1540 [D loss: 0.999971] [G loss: 1.000098] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1541 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1542 [D loss: 0.999976] [G loss: 1.000091] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1543 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1544 [D loss: 0.999983] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1545 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1546 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1547 [D loss: 0.999974] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1548 [D loss: 0.999975] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1549 [D loss: 0.999974] [G loss: 1.000100] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1550 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 78ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1551 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1552 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1553 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1554 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1555 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1556 [D loss: 0.999978] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1557 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1558 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1559 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1560 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1561 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1562 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1563 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1564 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1565 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1566 [D loss: 0.999972] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1567 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1568 [D loss: 0.999982] [G loss: 1.000085] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1569 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1570 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1571 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1572 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1573 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
1574 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1575 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1576 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1577 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1578 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1579 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1580 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1581 [D loss: 0.999974] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1582 [D loss: 0.999972] [G loss: 1.000100] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1583 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
1584 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1585 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1586 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1587 [D loss: 0.999985] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1588 [D loss: 0.999983] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1589 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1590 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1591 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1592 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1593 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1594 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1595 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1596 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1597 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1598 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1599 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1600 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 88ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1601 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1602 [D loss: 0.999984] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1603 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1604 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1605 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1606 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1607 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1608 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1609 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1610 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1611 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1612 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1613 [D loss: 0.999974] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1614 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1615 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1616 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1617 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1618 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1619 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1620 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1621 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1622 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1623 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1624 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1625 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1626 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1627 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1628 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1629 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1630 [D loss: 0.999975] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1631 [D loss: 0.999975] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1632 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1633 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1634 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1635 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1636 [D loss: 0.999974] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1637 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1638 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1639 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1640 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1641 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1642 [D loss: 0.999982] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1643 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1644 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1645 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
1646 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1647 [D loss: 0.999975] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1648 [D loss: 0.999975] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1649 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1650 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 71ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1651 [D loss: 0.999973] [G loss: 1.000098] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1652 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1653 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1654 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
1655 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1656 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
1657 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1658 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1659 [D loss: 0.999974] [G loss: 1.000102] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1660 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1661 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1662 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1663 [D loss: 0.999974] [G loss: 1.000099] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1664 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1665 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
1666 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1667 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1668 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1669 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1670 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1671 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1672 [D loss: 0.999971] [G loss: 1.000102] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1673 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1674 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 16ms/step
1675 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1676 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1677 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1678 [D loss: 0.999974] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1679 [D loss: 0.999979] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1680 [D loss: 0.999976] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1681 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1682 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1683 [D loss: 0.999974] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1684 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1685 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1686 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1687 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1688 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1689 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1690 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1691 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1692 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1693 [D loss: 0.999975] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1694 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1695 [D loss: 0.999975] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1696 [D loss: 0.999974] [G loss: 1.000102] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1697 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1698 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1699 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1700 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000024]
1/1 [==============================] - 0s 69ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1701 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1702 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1703 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1704 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1705 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1706 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1707 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1708 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1709 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1710 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1711 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1712 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1713 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1714 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1715 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1716 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
1717 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1718 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1719 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
1720 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1721 [D loss: 0.999981] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1722 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1723 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1724 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1725 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1726 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1727 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1728 [D loss: 0.999977] [G loss: 1.000107] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1729 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1730 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1731 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1732 [D loss: 0.999975] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1733 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1734 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1735 [D loss: 0.999981] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1736 [D loss: 0.999983] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1737 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1738 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1739 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1740 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1741 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1742 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1743 [D loss: 0.999985] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1744 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1745 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
1746 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1747 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1748 [D loss: 0.999972] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1749 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1750 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000025]
1/1 [==============================] - 0s 71ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
1751 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1752 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1753 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1754 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1755 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1756 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1757 [D loss: 0.999971] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1758 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1759 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1760 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1761 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1762 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1763 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1764 [D loss: 0.999975] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1765 [D loss: 0.999980] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1766 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1767 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1768 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1769 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1770 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1771 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1772 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1773 [D loss: 0.999980] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1774 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1775 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1776 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1777 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1778 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1779 [D loss: 0.999984] [G loss: 1.000085] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1780 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1781 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1782 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1783 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1784 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1785 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1786 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1787 [D loss: 0.999985] [G loss: 1.000086] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1788 [D loss: 0.999981] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1789 [D loss: 0.999973] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1790 [D loss: 0.999973] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1791 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1792 [D loss: 0.999975] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1793 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1794 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1795 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1796 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1797 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1798 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 15ms/step
1799 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1800 [D loss: 0.999981] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 68ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1801 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1802 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1803 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1804 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1805 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1806 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1807 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1808 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1809 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1810 [D loss: 0.999982] [G loss: 1.000088] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1811 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1812 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1813 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1814 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1815 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1816 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1817 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1818 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1819 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1820 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1821 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1822 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1823 [D loss: 0.999982] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1824 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1825 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1826 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1827 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1828 [D loss: 0.999979] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1829 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1830 [D loss: 0.999983] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1831 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1832 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1833 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1834 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1835 [D loss: 0.999973] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1836 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1837 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1838 [D loss: 0.999979] [G loss: 1.000088] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1839 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1840 [D loss: 0.999973] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1841 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1842 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1843 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1844 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1845 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
1846 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1847 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
1848 [D loss: 0.999974] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1849 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1850 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 76ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1851 [D loss: 0.999977] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1852 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1853 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1854 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1855 [D loss: 0.999981] [G loss: 1.000091] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1856 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1857 [D loss: 0.999982] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1858 [D loss: 0.999977] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1859 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1860 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1861 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1862 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1863 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 19ms/step
1864 [D loss: 0.999975] [G loss: 1.000097] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1865 [D loss: 0.999985] [G loss: 1.000074] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1866 [D loss: 0.999982] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1867 [D loss: 0.999974] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1868 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1869 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1870 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1871 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1872 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1873 [D loss: 0.999983] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1874 [D loss: 0.999984] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1875 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1876 [D loss: 0.999977] [G loss: 1.000090] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1877 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
1878 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
1879 [D loss: 0.999982] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1880 [D loss: 0.999981] [G loss: 1.000084] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1881 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1882 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1883 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1884 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1885 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1886 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1887 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
1888 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1889 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1890 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1891 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1892 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1893 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1894 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1895 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1896 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1897 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1898 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1899 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1900 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 84ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1901 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1902 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1903 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
1904 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1905 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1906 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1907 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1908 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
1909 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1910 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1911 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1912 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1913 [D loss: 0.999984] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1914 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1915 [D loss: 0.999992] [G loss: 1.000083] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1916 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000016]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1917 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1918 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1919 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
1920 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1921 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1922 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1923 [D loss: 0.999975] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1924 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1925 [D loss: 0.999982] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
1926 [D loss: 0.999975] [G loss: 1.000108] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1927 [D loss: 0.999976] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1928 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1929 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1930 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1931 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1932 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1933 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
1934 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1935 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1936 [D loss: 0.999973] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1937 [D loss: 0.999983] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1938 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
1939 [D loss: 0.999986] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1940 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1941 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1942 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1943 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1944 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1945 [D loss: 0.999980] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1946 [D loss: 0.999983] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1947 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
1948 [D loss: 0.999974] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1949 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1950 [D loss: 0.999979] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 77ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1951 [D loss: 0.999976] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1952 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1953 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
1954 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1955 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1956 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
1957 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1958 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1959 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1960 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1961 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
1962 [D loss: 0.999981] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1963 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
1964 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1965 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1966 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1967 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
1968 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1969 [D loss: 0.999978] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1970 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1971 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1972 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1973 [D loss: 0.999977] [G loss: 1.000107] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
1974 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1975 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1976 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1977 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
1978 [D loss: 0.999983] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1979 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
1980 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
1981 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
1982 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
1983 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
1984 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
1985 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
1986 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1987 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1988 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1989 [D loss: 0.999976] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1990 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1991 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1992 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1993 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
1994 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1995 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
1996 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
1997 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
1998 [D loss: 0.999973] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
1999 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2000 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 75ms/step
8/8 [==============================] - 0s 25ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 24ms/step
8/8 [==============================] - 0s 12ms/step
2001 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2002 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2003 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2004 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2005 [D loss: 0.999984] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2006 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2007 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2008 [D loss: 0.999982] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2009 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2010 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2011 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2012 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2013 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2014 [D loss: 0.999982] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2015 [D loss: 0.999981] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2016 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2017 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2018 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2019 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2020 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2021 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2022 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2023 [D loss: 0.999975] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2024 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2025 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2026 [D loss: 0.999974] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2027 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2028 [D loss: 0.999985] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2029 [D loss: 0.999980] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2030 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2031 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2032 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2033 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2034 [D loss: 0.999978] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2035 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2036 [D loss: 0.999982] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2037 [D loss: 0.999983] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2038 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2039 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2040 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2041 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2042 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2043 [D loss: 0.999985] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2044 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2045 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2046 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2047 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2048 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2049 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2050 [D loss: 0.999987] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 69ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2051 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2052 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2053 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2054 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2055 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2056 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2057 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2058 [D loss: 0.999974] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2059 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
2060 [D loss: 0.999982] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2061 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2062 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2063 [D loss: 0.999978] [G loss: 1.000108] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2064 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2065 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2066 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
2067 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2068 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2069 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2070 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2071 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2072 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2073 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2074 [D loss: 0.999981] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2075 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2076 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2077 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2078 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2079 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2080 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
2081 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 18ms/step
2082 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2083 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
2084 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2085 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2086 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2087 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2088 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2089 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
2090 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2091 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2092 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2093 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2094 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2095 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2096 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2097 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2098 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2099 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2100 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 82ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2101 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2102 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2103 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2104 [D loss: 0.999981] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2105 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2106 [D loss: 0.999971] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2107 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2108 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2109 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2110 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2111 [D loss: 0.999977] [G loss: 1.000107] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2112 [D loss: 0.999982] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2113 [D loss: 0.999981] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2114 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2115 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2116 [D loss: 0.999973] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2117 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2118 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2119 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2120 [D loss: 0.999981] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2121 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2122 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2123 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2124 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2125 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2126 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2127 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2128 [D loss: 0.999983] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2129 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2130 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2131 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2132 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2133 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2134 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2135 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2136 [D loss: 0.999983] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2137 [D loss: 0.999982] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2138 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2139 [D loss: 0.999981] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2140 [D loss: 0.999981] [G loss: 1.000093] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 16ms/step
2141 [D loss: 0.999987] [G loss: 1.000080] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2142 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2143 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2144 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2145 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2146 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2147 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2148 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2149 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2150 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 72ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2151 [D loss: 0.999979] [G loss: 1.000106] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2152 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2153 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2154 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2155 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2156 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2157 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2158 [D loss: 0.999982] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2159 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2160 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2161 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2162 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2163 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2164 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2165 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2166 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2167 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2168 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2169 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2170 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2171 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
2172 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2173 [D loss: 0.999981] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
2174 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2175 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2176 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2177 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2178 [D loss: 0.999984] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2179 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2180 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2181 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2182 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2183 [D loss: 0.999984] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2184 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2185 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2186 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2187 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2188 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2189 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2190 [D loss: 0.999984] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2191 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2192 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2193 [D loss: 0.999976] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2194 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2195 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2196 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2197 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2198 [D loss: 0.999973] [G loss: 1.000107] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2199 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2200 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 79ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 19ms/step
2201 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2202 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2203 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2204 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2205 [D loss: 0.999972] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2206 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2207 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2208 [D loss: 0.999991] [G loss: 1.000078] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2209 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2210 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2211 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2212 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2213 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2214 [D loss: 0.999973] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2215 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2216 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2217 [D loss: 0.999983] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2218 [D loss: 0.999988] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2219 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2220 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2221 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2222 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2223 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2224 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2225 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2226 [D loss: 0.999975] [G loss: 1.000107] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2227 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2228 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2229 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2230 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2231 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2232 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2233 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2234 [D loss: 0.999973] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2235 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2236 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2237 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2238 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2239 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2240 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2241 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2242 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2243 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2244 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2245 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2246 [D loss: 0.999979] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2247 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2248 [D loss: 0.999982] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2249 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2250 [D loss: 0.999970] [G loss: 1.000110] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 78ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2251 [D loss: 0.999981] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2252 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2253 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2254 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2255 [D loss: 0.999975] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2256 [D loss: 0.999982] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2257 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2258 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2259 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2260 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2261 [D loss: 0.999975] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2262 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2263 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2264 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2265 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2266 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2267 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2268 [D loss: 0.999976] [G loss: 1.000107] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2269 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2270 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2271 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 17ms/step
2272 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2273 [D loss: 0.999981] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2274 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2275 [D loss: 0.999974] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
2276 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 19ms/step
2277 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2278 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2279 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2280 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2281 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2282 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2283 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2284 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2285 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2286 [D loss: 0.999977] [G loss: 1.000108] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2287 [D loss: 0.999975] [G loss: 1.000106] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2288 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2289 [D loss: 0.999976] [G loss: 1.000107] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2290 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2291 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 14ms/step
2292 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2293 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2294 [D loss: 0.999983] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2295 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2296 [D loss: 0.999984] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2297 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2298 [D loss: 0.999985] [G loss: 1.000087] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2299 [D loss: 0.999983] [G loss: 1.000088] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2300 [D loss: 0.999977] [G loss: 1.000092] [Wasserstein Distance: -0.000019]
1/1 [==============================] - 0s 65ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2301 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2302 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2303 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2304 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2305 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
2306 [D loss: 0.999975] [G loss: 1.000109] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2307 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2308 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2309 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2310 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2311 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2312 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2313 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2314 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2315 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2316 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2317 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2318 [D loss: 0.999982] [G loss: 1.000087] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2319 [D loss: 0.999983] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2320 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2321 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2322 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2323 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2324 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2325 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 13ms/step
2326 [D loss: 0.999983] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 14ms/step
2327 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2328 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2329 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2330 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2331 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2332 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2333 [D loss: 0.999981] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2334 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2335 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2336 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2337 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2338 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2339 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2340 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 17ms/step
2341 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2342 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2343 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2344 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2345 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2346 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2347 [D loss: 0.999979] [G loss: 1.000089] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2348 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2349 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2350 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 98ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2351 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2352 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2353 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2354 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2355 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2356 [D loss: 0.999984] [G loss: 1.000090] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2357 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2358 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2359 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2360 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
2361 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 18ms/step
2362 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
2363 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2364 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2365 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2366 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2367 [D loss: 0.999980] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 13ms/step
2368 [D loss: 0.999983] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2369 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2370 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2371 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2372 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2373 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2374 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2375 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2376 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2377 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2378 [D loss: 0.999978] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2379 [D loss: 0.999978] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2380 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2381 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
2382 [D loss: 0.999979] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2383 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2384 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2385 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2386 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2387 [D loss: 0.999973] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2388 [D loss: 0.999982] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 13ms/step
2389 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2390 [D loss: 0.999975] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2391 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2392 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2393 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2394 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2395 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2396 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2397 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2398 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2399 [D loss: 0.999973] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2400 [D loss: 0.999984] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 79ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2401 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2402 [D loss: 0.999982] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2403 [D loss: 0.999981] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 17ms/step
2404 [D loss: 0.999981] [G loss: 1.000101] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 18ms/step
2405 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2406 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2407 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2408 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2409 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2410 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2411 [D loss: 0.999982] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 8ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2412 [D loss: 0.999991] [G loss: 1.000095] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2413 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2414 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2415 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2416 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2417 [D loss: 0.999977] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2418 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2419 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 25ms/step
8/8 [==============================] - 0s 22ms/step
2420 [D loss: 0.999984] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2421 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2422 [D loss: 0.999980] [G loss: 1.000107] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2423 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2424 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2425 [D loss: 0.999980] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2426 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2427 [D loss: 0.999974] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2428 [D loss: 0.999978] [G loss: 1.000106] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2429 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
2430 [D loss: 0.999984] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2431 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2432 [D loss: 0.999979] [G loss: 1.000105] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2433 [D loss: 0.999978] [G loss: 1.000105] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2434 [D loss: 0.999984] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
2435 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
2436 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2437 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2438 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2439 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2440 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2441 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2442 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2443 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2444 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2445 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2446 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2447 [D loss: 0.999983] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2448 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2449 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2450 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 79ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2451 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2452 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2453 [D loss: 0.999982] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2454 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2455 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2456 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2457 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2458 [D loss: 0.999987] [G loss: 1.000083] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2459 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2460 [D loss: 0.999983] [G loss: 1.000095] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2461 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2462 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2463 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 16ms/step
2464 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 12ms/step
2465 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2466 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2467 [D loss: 0.999988] [G loss: 1.000091] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2468 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2469 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2470 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2471 [D loss: 0.999982] [G loss: 1.000092] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2472 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2473 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2474 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2475 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2476 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2477 [D loss: 0.999975] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 12ms/step
2478 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 14ms/step
2479 [D loss: 0.999981] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2480 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2481 [D loss: 0.999971] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2482 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2483 [D loss: 0.999988] [G loss: 1.000088] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2484 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2485 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2486 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2487 [D loss: 0.999984] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2488 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2489 [D loss: 0.999982] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2490 [D loss: 0.999980] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2491 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2492 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2493 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2494 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2495 [D loss: 0.999976] [G loss: 1.000107] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2496 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
2497 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2498 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2499 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2500 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 104ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2501 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2502 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2503 [D loss: 0.999979] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2504 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2505 [D loss: 0.999978] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2506 [D loss: 0.999981] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2507 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2508 [D loss: 0.999976] [G loss: 1.000109] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2509 [D loss: 0.999976] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2510 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2511 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2512 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2513 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2514 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2515 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2516 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2517 [D loss: 0.999979] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
2518 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2519 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2520 [D loss: 0.999974] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2521 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2522 [D loss: 0.999982] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2523 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2524 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 16ms/step
2525 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2526 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2527 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2528 [D loss: 0.999986] [G loss: 1.000086] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2529 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2530 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2531 [D loss: 0.999982] [G loss: 1.000101] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2532 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2533 [D loss: 0.999976] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2534 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2535 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2536 [D loss: 0.999978] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2537 [D loss: 0.999973] [G loss: 1.000107] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2538 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2539 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2540 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2541 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2542 [D loss: 0.999981] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2543 [D loss: 0.999980] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2544 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2545 [D loss: 0.999986] [G loss: 1.000097] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2546 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2547 [D loss: 0.999975] [G loss: 1.000105] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2548 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2549 [D loss: 0.999985] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2550 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 80ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2551 [D loss: 0.999973] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2552 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2553 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2554 [D loss: 0.999983] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2555 [D loss: 0.999985] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
2556 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2557 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2558 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2559 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2560 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 15ms/step
2561 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2562 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2563 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2564 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2565 [D loss: 0.999977] [G loss: 1.000106] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2566 [D loss: 0.999977] [G loss: 1.000107] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 17ms/step
2567 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2568 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2569 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2570 [D loss: 0.999981] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2571 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2572 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2573 [D loss: 0.999981] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2574 [D loss: 0.999983] [G loss: 1.000088] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2575 [D loss: 0.999975] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2576 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2577 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2578 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2579 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2580 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2581 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2582 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2583 [D loss: 0.999971] [G loss: 1.000104] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2584 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2585 [D loss: 0.999975] [G loss: 1.000107] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2586 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2587 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2588 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
2589 [D loss: 0.999974] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 13ms/step
2590 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2591 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2592 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2593 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2594 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2595 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2596 [D loss: 0.999974] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2597 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 17ms/step
2598 [D loss: 0.999974] [G loss: 1.000100] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2599 [D loss: 0.999983] [G loss: 1.000086] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2600 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 90ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2601 [D loss: 0.999974] [G loss: 1.000094] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 16ms/step
2602 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2603 [D loss: 0.999983] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2604 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2605 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2606 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2607 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2608 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2609 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 17ms/step
2610 [D loss: 0.999974] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 16ms/step
2611 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2612 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2613 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2614 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2615 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2616 [D loss: 0.999975] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2617 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2618 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2619 [D loss: 0.999975] [G loss: 1.000105] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2620 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2621 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2622 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2623 [D loss: 0.999985] [G loss: 1.000084] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 17ms/step
2624 [D loss: 0.999985] [G loss: 1.000087] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2625 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2626 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000018]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2627 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2628 [D loss: 0.999982] [G loss: 1.000092] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2629 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2630 [D loss: 0.999982] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2631 [D loss: 0.999978] [G loss: 1.000108] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2632 [D loss: 0.999984] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 18ms/step
2633 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 16ms/step
2634 [D loss: 0.999982] [G loss: 1.000099] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 18ms/step
2635 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2636 [D loss: 0.999986] [G loss: 1.000091] [Wasserstein Distance: -0.000017]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 16ms/step
2637 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2638 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2639 [D loss: 0.999978] [G loss: 1.000106] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2640 [D loss: 0.999978] [G loss: 1.000106] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2641 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2642 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2643 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 15ms/step
2644 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2645 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2646 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2647 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2648 [D loss: 0.999975] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2649 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2650 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
1/1 [==============================] - 0s 94ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2651 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2652 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2653 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 15ms/step
2654 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2655 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
2656 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2657 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2658 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2659 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2660 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 15ms/step
2661 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2662 [D loss: 0.999981] [G loss: 1.000090] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2663 [D loss: 0.999981] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2664 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2665 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2666 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2667 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2668 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 19ms/step
2669 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2670 [D loss: 0.999979] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2671 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2672 [D loss: 0.999981] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2673 [D loss: 0.999983] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2674 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2675 [D loss: 0.999981] [G loss: 1.000100] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2676 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2677 [D loss: 0.999974] [G loss: 1.000106] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2678 [D loss: 0.999979] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2679 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 12ms/step
2680 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2681 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2682 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2683 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2684 [D loss: 0.999982] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2685 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2686 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2687 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2688 [D loss: 0.999974] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2689 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2690 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2691 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2692 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2693 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2694 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
2695 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2696 [D loss: 0.999980] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2697 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2698 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 17ms/step
2699 [D loss: 0.999982] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2700 [D loss: 0.999982] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 71ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2701 [D loss: 0.999974] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2702 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2703 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2704 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2705 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2706 [D loss: 0.999982] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2707 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2708 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2709 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2710 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2711 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2712 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2713 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2714 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2715 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2716 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
2717 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2718 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2719 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2720 [D loss: 0.999975] [G loss: 1.000107] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2721 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 17ms/step
2722 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2723 [D loss: 0.999975] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2724 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2725 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2726 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2727 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2728 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2729 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 24ms/step
2730 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2731 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 17ms/step
2732 [D loss: 0.999980] [G loss: 1.000086] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2733 [D loss: 0.999983] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2734 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2735 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2736 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2737 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2738 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 14ms/step
2739 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2740 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2741 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2742 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2743 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
2744 [D loss: 0.999976] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2745 [D loss: 0.999982] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 17ms/step
2746 [D loss: 0.999982] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2747 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2748 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2749 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2750 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 104ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2751 [D loss: 0.999981] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2752 [D loss: 0.999979] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2753 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2754 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2755 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2756 [D loss: 0.999974] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2757 [D loss: 0.999972] [G loss: 1.000096] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2758 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2759 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000025]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2760 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2761 [D loss: 0.999976] [G loss: 1.000098] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2762 [D loss: 0.999977] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2763 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2764 [D loss: 0.999974] [G loss: 1.000101] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2765 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 18ms/step
2766 [D loss: 0.999975] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2767 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2768 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2769 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2770 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2771 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2772 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2773 [D loss: 0.999975] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 17ms/step
2774 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 18ms/step
2775 [D loss: 0.999983] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2776 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2777 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2778 [D loss: 0.999979] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 16ms/step
2779 [D loss: 0.999984] [G loss: 1.000089] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2780 [D loss: 0.999984] [G loss: 1.000093] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2781 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2782 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2783 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2784 [D loss: 0.999979] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2785 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2786 [D loss: 0.999983] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2787 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2788 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2789 [D loss: 0.999974] [G loss: 1.000107] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2790 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2791 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2792 [D loss: 0.999978] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2793 [D loss: 0.999983] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2794 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2795 [D loss: 0.999976] [G loss: 1.000107] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2796 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2797 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2798 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2799 [D loss: 0.999976] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2800 [D loss: 0.999982] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 89ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 12ms/step
2801 [D loss: 0.999991] [G loss: 1.000078] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2802 [D loss: 0.999974] [G loss: 1.000104] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2803 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2804 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 19ms/step
2805 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2806 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 19ms/step
2807 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2808 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2809 [D loss: 0.999984] [G loss: 1.000082] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
2810 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2811 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2812 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2813 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2814 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 18ms/step
2815 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 18ms/step
2816 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2817 [D loss: 0.999970] [G loss: 1.000104] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2818 [D loss: 0.999979] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2819 [D loss: 0.999985] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 14ms/step
2820 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2821 [D loss: 0.999982] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2822 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2823 [D loss: 0.999978] [G loss: 1.000094] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2824 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2825 [D loss: 0.999981] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2826 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2827 [D loss: 0.999982] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2828 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2829 [D loss: 0.999974] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2830 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2831 [D loss: 0.999981] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
2832 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2833 [D loss: 0.999981] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2834 [D loss: 0.999982] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2835 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
2836 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2837 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2838 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2839 [D loss: 0.999977] [G loss: 1.000106] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2840 [D loss: 0.999981] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2841 [D loss: 0.999978] [G loss: 1.000106] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2842 [D loss: 0.999975] [G loss: 1.000109] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2843 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 17ms/step
2844 [D loss: 0.999972] [G loss: 1.000108] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 17ms/step
2845 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2846 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2847 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2848 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2849 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2850 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
1/1 [==============================] - 0s 78ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2851 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2852 [D loss: 0.999973] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 14ms/step
2853 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
2854 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2855 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2856 [D loss: 0.999977] [G loss: 1.000105] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2857 [D loss: 0.999985] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2858 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2859 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2860 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2861 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2862 [D loss: 0.999976] [G loss: 1.000106] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2863 [D loss: 0.999975] [G loss: 1.000108] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2864 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2865 [D loss: 0.999975] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2866 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2867 [D loss: 0.999982] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2868 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2869 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 17ms/step
2870 [D loss: 0.999981] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2871 [D loss: 0.999980] [G loss: 1.000104] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2872 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 19ms/step
2873 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 18ms/step
2874 [D loss: 0.999976] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2875 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2876 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 18ms/step
2877 [D loss: 0.999980] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2878 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2879 [D loss: 0.999981] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 19ms/step
2880 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2881 [D loss: 0.999980] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 19ms/step
2882 [D loss: 0.999982] [G loss: 1.000090] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2883 [D loss: 0.999978] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 17ms/step
2884 [D loss: 0.999981] [G loss: 1.000092] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2885 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 19ms/step
2886 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
2887 [D loss: 0.999982] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2888 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2889 [D loss: 0.999981] [G loss: 1.000094] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 15ms/step
2890 [D loss: 0.999980] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2891 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2892 [D loss: 0.999981] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2893 [D loss: 0.999976] [G loss: 1.000105] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2894 [D loss: 0.999982] [G loss: 1.000091] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2895 [D loss: 0.999982] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2896 [D loss: 0.999978] [G loss: 1.000101] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2897 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2898 [D loss: 0.999979] [G loss: 1.000098] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2899 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2900 [D loss: 0.999986] [G loss: 1.000093] [Wasserstein Distance: -0.000020]
1/1 [==============================] - 0s 86ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 26ms/step
2901 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 15ms/step
2902 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2903 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000019]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2904 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2905 [D loss: 0.999975] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2906 [D loss: 0.999977] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2907 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2908 [D loss: 0.999984] [G loss: 1.000092] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2909 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2910 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2911 [D loss: 0.999981] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2912 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 12ms/step
2913 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2914 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 29ms/step
8/8 [==============================] - 0s 23ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
2915 [D loss: 0.999978] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2916 [D loss: 0.999980] [G loss: 1.000090] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2917 [D loss: 0.999976] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2918 [D loss: 0.999981] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2919 [D loss: 0.999976] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2920 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2921 [D loss: 0.999974] [G loss: 1.000101] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2922 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2923 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 16ms/step
2924 [D loss: 0.999979] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2925 [D loss: 0.999978] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2926 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2927 [D loss: 0.999980] [G loss: 1.000091] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2928 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 18ms/step
2929 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2930 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2931 [D loss: 0.999977] [G loss: 1.000095] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2932 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2933 [D loss: 0.999981] [G loss: 1.000093] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 19ms/step
2934 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2935 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2936 [D loss: 0.999973] [G loss: 1.000105] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2937 [D loss: 0.999978] [G loss: 1.000097] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2938 [D loss: 0.999983] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2939 [D loss: 0.999974] [G loss: 1.000107] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 14ms/step
2940 [D loss: 0.999980] [G loss: 1.000089] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2941 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2942 [D loss: 0.999977] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 7ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
2943 [D loss: 0.999980] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 13ms/step
2944 [D loss: 0.999979] [G loss: 1.000097] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2945 [D loss: 0.999977] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2946 [D loss: 0.999975] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2947 [D loss: 0.999978] [G loss: 1.000099] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2948 [D loss: 0.999978] [G loss: 1.000091] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 13ms/step
2949 [D loss: 0.999977] [G loss: 1.000096] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2950 [D loss: 0.999980] [G loss: 1.000094] [Wasserstein Distance: -0.000022]
1/1 [==============================] - 0s 83ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 19ms/step
8/8 [==============================] - 0s 18ms/step
2951 [D loss: 0.999983] [G loss: 1.000090] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2952 [D loss: 0.999977] [G loss: 1.000107] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2953 [D loss: 0.999983] [G loss: 1.000089] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2954 [D loss: 0.999979] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2955 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2956 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2957 [D loss: 0.999980] [G loss: 1.000093] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 18ms/step
2958 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 12ms/step
2959 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2960 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2961 [D loss: 0.999978] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2962 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2963 [D loss: 0.999974] [G loss: 1.000098] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2964 [D loss: 0.999980] [G loss: 1.000095] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2965 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 15ms/step
2966 [D loss: 0.999979] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2967 [D loss: 0.999983] [G loss: 1.000095] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2968 [D loss: 0.999976] [G loss: 1.000095] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
2969 [D loss: 0.999981] [G loss: 1.000102] [Wasserstein Distance: -0.000020]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 19ms/step
2970 [D loss: 0.999977] [G loss: 1.000101] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 15ms/step
8/8 [==============================] - 0s 13ms/step
2971 [D loss: 0.999978] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 16ms/step
2972 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2973 [D loss: 0.999982] [G loss: 1.000094] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2974 [D loss: 0.999978] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2975 [D loss: 0.999979] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2976 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 20ms/step
8/8 [==============================] - 0s 17ms/step
2977 [D loss: 0.999977] [G loss: 1.000104] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2978 [D loss: 0.999976] [G loss: 1.000101] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 17ms/step
2979 [D loss: 0.999976] [G loss: 1.000102] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2980 [D loss: 0.999978] [G loss: 1.000104] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2981 [D loss: 0.999976] [G loss: 1.000103] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 13ms/step
2982 [D loss: 0.999981] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2983 [D loss: 0.999980] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2984 [D loss: 0.999977] [G loss: 1.000098] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 13ms/step
2985 [D loss: 0.999980] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 18ms/step
2986 [D loss: 0.999974] [G loss: 1.000103] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2987 [D loss: 0.999976] [G loss: 1.000099] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2988 [D loss: 0.999975] [G loss: 1.000100] [Wasserstein Distance: -0.000024]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 15ms/step
2989 [D loss: 0.999981] [G loss: 1.000097] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2990 [D loss: 0.999978] [G loss: 1.000090] [Wasserstein Distance: -0.000023]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2991 [D loss: 0.999980] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 14ms/step
2992 [D loss: 0.999979] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 12ms/step
2993 [D loss: 0.999979] [G loss: 1.000099] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 14ms/step
2994 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 13ms/step
2995 [D loss: 0.999977] [G loss: 1.000102] [Wasserstein Distance: -0.000021]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 13ms/step
8/8 [==============================] - 0s 12ms/step
2996 [D loss: 0.999974] [G loss: 1.000100] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 9ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 11ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 11ms/step
2997 [D loss: 0.999980] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 12ms/step
8/8 [==============================] - 0s 12ms/step
2998 [D loss: 0.999981] [G loss: 1.000096] [Wasserstein Distance: -0.000022]
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 10ms/step
8/8 [==============================] - 0s 14ms/step
8/8 [==============================] - 0s 14ms/step
2999 [D loss: 0.999981] [G loss: 1.000095] [Wasserstein Distance: -0.000022]

Plot Loss

plot_losses(wgan.d_losses, wgan.g_losses)

Plot Wasserstein Distance

plot_wasserstein_distance(wgan.wasserstein_distances)

Generated Images at Different Epochs (Tanh)

At 100 Epochs

At 1000 Epochs

At 2950 Epochs

Results

Training losses The graph shows significant improvements as compared to the previous 2 graphs. The discriminator loss can be seen to be very close to 0 which means that the discriminator is effectively distinguishing between real and generated images. The generator loss can be seen to always be close to 0 but not as close as the discriminator’s loss, this means that while the generator is performing well and producing high-quality images, it has not yet fully achieved the level of success of the discriminator.

Wasserstein Distance The Wasserstein distance’s behavior indicates periods of instability followed by improved performance. The initial spike to reach positive values means that the generator's initial attempts to produce realistic samples were met with significant challenges, causing the distance to temporarily increase. However, was the epoch increases, the Wasserstein distance drop back down to the negative values and is stable with negative values close to 0, which means that the generator has managed to improve over time and reduce the gap between the generated samples and the real data distribution. The negative values suggest that the training is progressing well, as a negative Wasserstein distance is a sign of effective learning and convergence towards the true data distribution.

Generated Images The current model demonstrates significant improvements over the previous one, with better detail and more accurate representations of the handwritten digits. These advancements reflect the model’s enhanced performance and effective learning capabilities in generating realistic samples from the EMNIST dataset.

In summary, the combination of low training losses, stabilized Wasserstein distance, and high-quality generated images demonstrates that the current model represents a significant advancement over previous iterations. The model’s performance improvements across these metrics reflect its enhanced ability to generate realistic samples and its effective convergence towards the true data distribution. To further attempt to improve and trying something new for the generation of quality of the generated images, we plan to experiment using the current model and adding gradient penalty to it.

Final Model

class CGAN():
    def __init__(self):
        # Input shape
        self.img_rows = 28
        self.img_cols = 28
        self.channels = 1
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.num_classes = 26
        self.latent_dim = 100

        optimizer = Adam(0.001, 0.5)

        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss=['binary_crossentropy'],
            optimizer=optimizer,
            metrics=['accuracy'])

        # Build the generator
        self.generator = self.build_generator()

        # The generator takes noise and the target label as input
        # and generates the corresponding digit of that label
        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,))
        img = self.generator([noise, label])

        # For the combined model we will only train the generator
        self.discriminator.trainable = False

        # The discriminator takes generated image as input and determines validity
        # and the label of that image
        valid = self.discriminator([img, label])

        # The combined model  (stacked generator and discriminator)
        # Trains generator to fool discriminator
        self.combined = Model([noise, label], valid)
        self.combined.compile(loss=['binary_crossentropy'],
            optimizer=optimizer)

        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []

    def build_generator(self):

        model = Sequential()

        model.add(Dense(512 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 512)))
        
        model.add(Conv2DTranspose(128, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2DTranspose(64, kernel_size=4,  strides=(2,2), padding='same'))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(self.channels, kernel_size=4, strides=(2,2), padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        label = Input(shape=(1,), dtype='int32')
        label_embedding = Flatten()(Embedding(self.num_classes, self.latent_dim)(label))

        model_input = multiply([noise, label_embedding])
        img = model(model_input)

        return Model([noise, label], img)

    def build_discriminator(self):
        model = Sequential()

        model.add(Conv2D(64, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))

        
        model.add(Flatten())
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        # Image input and label input
        img = Input(shape=self.img_shape)
        label = Input(shape=(1,), dtype='int32')

        # Embedding for label
        label_embedding = Flatten()(Embedding(self.num_classes, np.prod(self.img_shape))(label))
        label_embedding = Dense(np.prod(self.img_shape))(label_embedding)
        label_embedding = Reshape(self.img_shape)(label_embedding)

        # Multiply image and label embeddings
        combined = multiply([img, label_embedding])

        # Validity prediction
        validity = model(combined)

        return Model([img, label], validity)

    def train(self, epochs, batch_size=128, sample_interval=50):


        # Extract image data and convert to numpy array
        X_train = preprocessed_df.iloc[:, 1:].values
        y_train = preprocessed_df.iloc[:, 0].values
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)

        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))

        for epoch in range(epochs):

            # ---------------------
            #  Train Discriminator
            # ---------------------

            # Select a random half batch of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs, labels = X_train[idx], y_train[idx]
            # Sample noise as generator input
            noise = np.random.normal(0, 1, (batch_size, 100))

            # Generate a half batch of new images
            gen_imgs = self.generator.predict([noise, labels])

            # Train the discriminator
            d_loss_real = self.discriminator.train_on_batch([imgs, labels], valid)
            d_loss_fake = self.discriminator.train_on_batch([gen_imgs, labels], fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)

            # ---------------------
            #  Train Generator
            # ---------------------

            # Condition on labels (Generate random samples)
            sampled_labels = np.random.randint(1, 27, batch_size).reshape(-1, 1)

            # Train the generator
            g_loss = self.combined.train_on_batch([noise, sampled_labels], valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            
            # Plot the progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100*d_loss[1], g_loss))

            # If at save interval => save generated image samples
            if epoch % sample_interval == 0:
                self.sample_images(epoch)

    def sample_images(self, epoch):
        r, c = 5, 6
        num_samples = 26
        # Generate noise based on the number of samples
        noise = np.random.normal(0, 1, (num_samples, 100))
        sampled_labels = np.arange(1, 27).reshape(-1, 1)

        gen_imgs = self.generator.predict([noise, sampled_labels])

        # Rescale images 0 - 1
        gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0  # Counter for the images
        for i in range(r):
            for j in range(c):
                if cnt < num_samples:  # Ensure we don't go out of bounds
                    axs[i,j].imshow(gen_imgs[cnt,:,:,0], cmap='gray')  # Display image

                    mapped_label = map_labels(sampled_labels[cnt][0])  # Map label to its corresponding class name
                    axs[i,j].set_title("Class: %s" % mapped_label)  # Set title of the subplot
                    axs[i,j].axis('off')  # Turn off axis
                    cnt += 1  # Increment counter
                else:
                    axs[i,j].axis('off')  # Turn off axis if there's no image to display
                    
        # Adjust the spacing between subplots
        plt.subplots_adjust(wspace=0.2, hspace=0.6)
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/final', exist_ok=True)
        fig.savefig("generated_images/final/cgan_{:d}.png".format(epoch))
        plt.close()

cgan = CGAN()
cgan.train(epochs=10000, batch_size=256, sample_interval=50)

Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d (Conv2D)             (None, 14, 14, 64)        640       
                                                                 
 leaky_re_lu (LeakyReLU)     (None, 14, 14, 64)        0         
                                                                 
 conv2d_1 (Conv2D)           (None, 7, 7, 128)         73856     
                                                                 
 leaky_re_lu_1 (LeakyReLU)   (None, 7, 7, 128)         0         
                                                                 
 conv2d_2 (Conv2D)           (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_2 (LeakyReLU)   (None, 4, 4, 256)         0         
                                                                 
 flatten (Flatten)           (None, 4096)              0         
                                                                 
 dense (Dense)               (None, 1)                 4097      
                                                                 
=================================================================
Total params: 373,761
Trainable params: 373,761
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_1"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_2 (Dense)             (None, 25088)             2533888   
                                                                 
 reshape_1 (Reshape)         (None, 7, 7, 512)         0         
                                                                 
 conv2d_transpose (Conv2DTra  (None, 14, 14, 128)      1048704   
 nspose)                                                         
                                                                 
 leaky_re_lu_3 (LeakyReLU)   (None, 14, 14, 128)       0         
                                                                 
 conv2d_transpose_1 (Conv2DT  (None, 28, 28, 64)       131136    
 ranspose)                                                       
                                                                 
 leaky_re_lu_4 (LeakyReLU)   (None, 28, 28, 64)        0         
                                                                 
 conv2d_transpose_2 (Conv2DT  (None, 56, 56, 64)       65600     
 ranspose)                                                       
                                                                 
 leaky_re_lu_5 (LeakyReLU)   (None, 56, 56, 64)        0         
                                                                 
 conv2d_3 (Conv2D)           (None, 28, 28, 1)         1025      
                                                                 
 activation (Activation)     (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 3,780,353
Trainable params: 3,780,353
Non-trainable params: 0
_________________________________________________________________
8/8 [==============================] - 10s 18ms/step
0 [D loss: 0.698377, acc.: 26.17%] [G loss: 0.691314]
1/1 [==============================] - 0s 306ms/step
8/8 [==============================] - 0s 7ms/step
1 [D loss: 0.693956, acc.: 50.00%] [G loss: 0.692133]
8/8 [==============================] - 0s 5ms/step
2 [D loss: 0.693342, acc.: 50.00%] [G loss: 0.693115]
8/8 [==============================] - 0s 5ms/step
3 [D loss: 0.692808, acc.: 51.76%] [G loss: 0.695517]
8/8 [==============================] - 0s 5ms/step
4 [D loss: 0.691756, acc.: 91.02%] [G loss: 0.703551]
8/8 [==============================] - 0s 5ms/step
5 [D loss: 0.688034, acc.: 94.92%] [G loss: 0.735055]
8/8 [==============================] - 0s 5ms/step
6 [D loss: 0.671662, acc.: 86.72%] [G loss: 0.856822]
8/8 [==============================] - 0s 5ms/step
7 [D loss: 0.614169, acc.: 89.26%] [G loss: 1.308590]
8/8 [==============================] - 0s 5ms/step
8 [D loss: 0.508267, acc.: 89.06%] [G loss: 2.172501]
8/8 [==============================] - 0s 5ms/step
9 [D loss: 0.451413, acc.: 93.95%] [G loss: 2.497743]
8/8 [==============================] - 0s 4ms/step
10 [D loss: 0.775613, acc.: 35.94%] [G loss: 0.621190]
8/8 [==============================] - 0s 5ms/step
11 [D loss: 0.521797, acc.: 49.41%] [G loss: 0.675552]
8/8 [==============================] - 0s 5ms/step
12 [D loss: 0.383304, acc.: 51.76%] [G loss: 0.733251]
8/8 [==============================] - 0s 4ms/step
13 [D loss: 0.348801, acc.: 96.88%] [G loss: 0.809898]
8/8 [==============================] - 0s 5ms/step
14 [D loss: 0.296910, acc.: 98.44%] [G loss: 0.959499]
8/8 [==============================] - 0s 5ms/step
15 [D loss: 0.243892, acc.: 98.24%] [G loss: 1.269197]
8/8 [==============================] - 0s 8ms/step
16 [D loss: 0.171828, acc.: 98.24%] [G loss: 1.851927]
8/8 [==============================] - 0s 5ms/step
17 [D loss: 0.131533, acc.: 97.27%] [G loss: 2.571984]
8/8 [==============================] - 0s 5ms/step
18 [D loss: 0.162220, acc.: 96.29%] [G loss: 3.484830]
8/8 [==============================] - 0s 5ms/step
19 [D loss: 1.093874, acc.: 59.96%] [G loss: 4.459144]
8/8 [==============================] - 0s 5ms/step
20 [D loss: 1.916050, acc.: 36.52%] [G loss: 3.608317]
8/8 [==============================] - 0s 6ms/step
21 [D loss: 4.649335, acc.: 12.89%] [G loss: 1.236190]
8/8 [==============================] - 0s 6ms/step
22 [D loss: 1.174573, acc.: 50.00%] [G loss: 2.863718]
8/8 [==============================] - 0s 5ms/step
23 [D loss: 0.838477, acc.: 50.00%] [G loss: 1.588565]
8/8 [==============================] - 0s 6ms/step
24 [D loss: 0.702386, acc.: 50.00%] [G loss: 1.154814]
8/8 [==============================] - 0s 5ms/step
25 [D loss: 0.655476, acc.: 50.00%] [G loss: 1.103935]
8/8 [==============================] - 0s 5ms/step
26 [D loss: 0.636994, acc.: 49.22%] [G loss: 1.084928]
8/8 [==============================] - 0s 5ms/step
27 [D loss: 0.627714, acc.: 52.15%] [G loss: 1.099943]
8/8 [==============================] - 0s 6ms/step
28 [D loss: 0.637558, acc.: 55.47%] [G loss: 1.105922]
8/8 [==============================] - 0s 5ms/step
29 [D loss: 0.633441, acc.: 58.20%] [G loss: 1.141252]
8/8 [==============================] - 0s 6ms/step
30 [D loss: 0.631935, acc.: 58.98%] [G loss: 1.203510]
8/8 [==============================] - 0s 6ms/step
31 [D loss: 0.626272, acc.: 62.50%] [G loss: 1.269265]
8/8 [==============================] - 0s 6ms/step
32 [D loss: 0.610862, acc.: 61.52%] [G loss: 1.459757]
8/8 [==============================] - 0s 5ms/step
33 [D loss: 0.588867, acc.: 64.45%] [G loss: 1.599183]
8/8 [==============================] - 0s 5ms/step
34 [D loss: 0.585645, acc.: 67.19%] [G loss: 1.639875]
8/8 [==============================] - 0s 5ms/step
35 [D loss: 0.582162, acc.: 69.73%] [G loss: 1.670318]
8/8 [==============================] - 0s 5ms/step
36 [D loss: 0.596148, acc.: 70.90%] [G loss: 1.655398]
8/8 [==============================] - 0s 5ms/step
37 [D loss: 0.627977, acc.: 66.41%] [G loss: 1.283276]
8/8 [==============================] - 0s 5ms/step
38 [D loss: 0.874189, acc.: 25.00%] [G loss: 0.517955]
8/8 [==============================] - 0s 14ms/step
39 [D loss: 0.789387, acc.: 41.02%] [G loss: 0.503097]
8/8 [==============================] - 0s 5ms/step
40 [D loss: 0.757264, acc.: 43.16%] [G loss: 0.519898]
8/8 [==============================] - 0s 5ms/step
41 [D loss: 0.724591, acc.: 48.44%] [G loss: 0.537957]
8/8 [==============================] - 0s 5ms/step
42 [D loss: 0.710341, acc.: 49.80%] [G loss: 0.555167]
8/8 [==============================] - 0s 6ms/step
43 [D loss: 0.702907, acc.: 49.41%] [G loss: 0.572130]
8/8 [==============================] - 0s 5ms/step
44 [D loss: 0.693670, acc.: 49.61%] [G loss: 0.589633]
8/8 [==============================] - 0s 5ms/step
45 [D loss: 0.687360, acc.: 49.61%] [G loss: 0.607214]
8/8 [==============================] - 0s 19ms/step
46 [D loss: 0.680160, acc.: 50.00%] [G loss: 0.625349]
8/8 [==============================] - 0s 5ms/step
47 [D loss: 0.673114, acc.: 49.80%] [G loss: 0.643881]
8/8 [==============================] - 0s 5ms/step
48 [D loss: 0.663086, acc.: 49.80%] [G loss: 0.664424]
8/8 [==============================] - 0s 5ms/step
49 [D loss: 0.653931, acc.: 49.41%] [G loss: 0.687171]
8/8 [==============================] - 0s 5ms/step
50 [D loss: 0.639814, acc.: 49.80%] [G loss: 0.713303]
1/1 [==============================] - 0s 21ms/step
8/8 [==============================] - 0s 8ms/step
51 [D loss: 0.630681, acc.: 96.09%] [G loss: 0.740932]
8/8 [==============================] - 0s 5ms/step
52 [D loss: 0.619288, acc.: 91.99%] [G loss: 0.771522]
8/8 [==============================] - 0s 5ms/step
53 [D loss: 0.600911, acc.: 91.02%] [G loss: 0.806361]
8/8 [==============================] - 0s 5ms/step
54 [D loss: 0.586911, acc.: 88.48%] [G loss: 0.843960]
8/8 [==============================] - 0s 5ms/step
55 [D loss: 0.555286, acc.: 87.89%] [G loss: 0.890821]
8/8 [==============================] - 0s 5ms/step
56 [D loss: 0.536112, acc.: 85.35%] [G loss: 0.944097]
8/8 [==============================] - 0s 5ms/step
57 [D loss: 0.519529, acc.: 85.55%] [G loss: 0.998920]
8/8 [==============================] - 0s 5ms/step
58 [D loss: 0.481743, acc.: 88.28%] [G loss: 1.067155]
8/8 [==============================] - 0s 4ms/step
59 [D loss: 0.454903, acc.: 86.91%] [G loss: 1.143516]
8/8 [==============================] - 0s 5ms/step
60 [D loss: 0.425556, acc.: 89.26%] [G loss: 1.225960]
8/8 [==============================] - 0s 5ms/step
61 [D loss: 0.385402, acc.: 90.23%] [G loss: 1.323323]
8/8 [==============================] - 0s 5ms/step
62 [D loss: 0.349519, acc.: 91.41%] [G loss: 1.435864]
8/8 [==============================] - 0s 5ms/step
63 [D loss: 0.321940, acc.: 92.58%] [G loss: 1.549517]
8/8 [==============================] - 0s 5ms/step
64 [D loss: 0.285940, acc.: 93.75%] [G loss: 1.666787]
8/8 [==============================] - 0s 5ms/step
65 [D loss: 0.254042, acc.: 95.12%] [G loss: 1.792326]
8/8 [==============================] - 0s 5ms/step
66 [D loss: 0.224035, acc.: 95.51%] [G loss: 1.921930]
8/8 [==============================] - 0s 5ms/step
67 [D loss: 0.212368, acc.: 95.51%] [G loss: 2.031311]
8/8 [==============================] - 0s 4ms/step
68 [D loss: 0.196254, acc.: 95.90%] [G loss: 2.127039]
8/8 [==============================] - 0s 5ms/step
69 [D loss: 0.161986, acc.: 96.68%] [G loss: 2.250783]
8/8 [==============================] - 0s 5ms/step
70 [D loss: 0.123964, acc.: 98.44%] [G loss: 2.410772]
8/8 [==============================] - 0s 5ms/step
71 [D loss: 0.139175, acc.: 97.27%] [G loss: 2.505313]
8/8 [==============================] - 0s 5ms/step
72 [D loss: 0.110024, acc.: 97.85%] [G loss: 2.623029]
8/8 [==============================] - 0s 5ms/step
73 [D loss: 0.110602, acc.: 97.46%] [G loss: 2.715196]
8/8 [==============================] - 0s 5ms/step
74 [D loss: 0.102117, acc.: 98.05%] [G loss: 2.799596]
8/8 [==============================] - 0s 5ms/step
75 [D loss: 0.102887, acc.: 97.85%] [G loss: 2.857367]
8/8 [==============================] - 0s 5ms/step
76 [D loss: 0.099524, acc.: 97.66%] [G loss: 2.906861]
8/8 [==============================] - 0s 5ms/step
77 [D loss: 0.101791, acc.: 97.27%] [G loss: 2.934799]
8/8 [==============================] - 0s 5ms/step
78 [D loss: 0.091326, acc.: 98.05%] [G loss: 2.985956]
8/8 [==============================] - 0s 5ms/step
79 [D loss: 0.112716, acc.: 97.07%] [G loss: 2.973809]
8/8 [==============================] - 0s 5ms/step
80 [D loss: 0.085947, acc.: 97.85%] [G loss: 3.012878]
8/8 [==============================] - 0s 5ms/step
81 [D loss: 0.070986, acc.: 98.24%] [G loss: 3.087992]
8/8 [==============================] - 0s 5ms/step
82 [D loss: 0.089792, acc.: 97.85%] [G loss: 3.101709]
8/8 [==============================] - 0s 5ms/step
83 [D loss: 0.096023, acc.: 97.27%] [G loss: 3.094916]
8/8 [==============================] - 0s 5ms/step
84 [D loss: 0.078366, acc.: 97.85%] [G loss: 3.103786]
8/8 [==============================] - 0s 5ms/step
85 [D loss: 0.049806, acc.: 99.22%] [G loss: 3.203753]
8/8 [==============================] - 0s 5ms/step
86 [D loss: 0.096893, acc.: 97.27%] [G loss: 3.144793]
8/8 [==============================] - 0s 5ms/step
87 [D loss: 0.096804, acc.: 97.46%] [G loss: 3.024979]
8/8 [==============================] - 0s 5ms/step
88 [D loss: 0.114438, acc.: 97.46%] [G loss: 2.825798]
8/8 [==============================] - 0s 5ms/step
89 [D loss: 0.322068, acc.: 87.30%] [G loss: 2.571004]
8/8 [==============================] - 0s 5ms/step
90 [D loss: 2.110336, acc.: 53.91%] [G loss: 3.246073]
8/8 [==============================] - 0s 5ms/step
91 [D loss: 0.824711, acc.: 64.26%] [G loss: 3.592859]
8/8 [==============================] - 0s 5ms/step
92 [D loss: 1.609798, acc.: 38.48%] [G loss: 5.078979]
8/8 [==============================] - 0s 5ms/step
93 [D loss: 2.283161, acc.: 32.23%] [G loss: 20.986206]
8/8 [==============================] - 0s 5ms/step
94 [D loss: 1.652693, acc.: 50.00%] [G loss: 5.622614]
8/8 [==============================] - 0s 4ms/step
95 [D loss: 1.026636, acc.: 33.40%] [G loss: 1.121786]
8/8 [==============================] - 0s 5ms/step
96 [D loss: 0.678731, acc.: 49.22%] [G loss: 1.503433]
8/8 [==============================] - 0s 5ms/step
97 [D loss: 0.546978, acc.: 68.55%] [G loss: 2.327609]
8/8 [==============================] - 0s 5ms/step
98 [D loss: 0.503890, acc.: 72.46%] [G loss: 2.468967]
8/8 [==============================] - 0s 5ms/step
99 [D loss: 0.490544, acc.: 75.98%] [G loss: 2.412451]
8/8 [==============================] - 0s 5ms/step
100 [D loss: 0.475678, acc.: 76.95%] [G loss: 2.643099]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 5ms/step
101 [D loss: 0.432880, acc.: 79.10%] [G loss: 2.773262]
8/8 [==============================] - 0s 5ms/step
102 [D loss: 0.483801, acc.: 76.95%] [G loss: 2.601105]
8/8 [==============================] - 0s 5ms/step
103 [D loss: 0.658470, acc.: 59.57%] [G loss: 1.330121]
8/8 [==============================] - 0s 5ms/step
104 [D loss: 0.744316, acc.: 45.90%] [G loss: 0.615500]
8/8 [==============================] - 0s 5ms/step
105 [D loss: 0.665447, acc.: 45.31%] [G loss: 0.735931]
8/8 [==============================] - 0s 5ms/step
106 [D loss: 0.605944, acc.: 82.03%] [G loss: 0.877824]
8/8 [==============================] - 0s 5ms/step
107 [D loss: 0.584498, acc.: 82.42%] [G loss: 0.985355]
8/8 [==============================] - 0s 5ms/step
108 [D loss: 0.576873, acc.: 79.88%] [G loss: 1.034856]
8/8 [==============================] - 0s 5ms/step
109 [D loss: 0.565899, acc.: 80.66%] [G loss: 1.063692]
8/8 [==============================] - 0s 5ms/step
110 [D loss: 0.531015, acc.: 85.16%] [G loss: 1.122054]
8/8 [==============================] - 0s 4ms/step
111 [D loss: 0.503213, acc.: 84.38%] [G loss: 1.141596]
8/8 [==============================] - 0s 5ms/step
112 [D loss: 0.514047, acc.: 79.69%] [G loss: 1.152234]
8/8 [==============================] - 0s 4ms/step
113 [D loss: 0.526094, acc.: 76.95%] [G loss: 1.159749]
8/8 [==============================] - 0s 5ms/step
114 [D loss: 0.509391, acc.: 77.93%] [G loss: 1.186864]
8/8 [==============================] - 0s 5ms/step
115 [D loss: 0.510901, acc.: 78.71%] [G loss: 1.346849]
8/8 [==============================] - 0s 4ms/step
116 [D loss: 0.449786, acc.: 83.59%] [G loss: 1.570093]
8/8 [==============================] - 0s 5ms/step
117 [D loss: 0.402822, acc.: 85.35%] [G loss: 1.828438]
8/8 [==============================] - 0s 5ms/step
118 [D loss: 0.445773, acc.: 81.25%] [G loss: 1.832080]
8/8 [==============================] - 0s 5ms/step
119 [D loss: 0.494221, acc.: 77.93%] [G loss: 1.797419]
8/8 [==============================] - 0s 4ms/step
120 [D loss: 0.504160, acc.: 79.88%] [G loss: 1.793967]
8/8 [==============================] - 0s 5ms/step
121 [D loss: 0.556121, acc.: 74.41%] [G loss: 1.478423]
8/8 [==============================] - 0s 5ms/step
122 [D loss: 0.542174, acc.: 75.59%] [G loss: 1.633729]
8/8 [==============================] - 0s 5ms/step
123 [D loss: 0.548984, acc.: 73.83%] [G loss: 1.647868]
8/8 [==============================] - 0s 5ms/step
124 [D loss: 0.560823, acc.: 72.27%] [G loss: 1.502543]
8/8 [==============================] - 0s 4ms/step
125 [D loss: 0.552343, acc.: 70.51%] [G loss: 1.459369]
8/8 [==============================] - 0s 4ms/step
126 [D loss: 0.529429, acc.: 72.85%] [G loss: 1.445223]
8/8 [==============================] - 0s 4ms/step
127 [D loss: 0.452676, acc.: 86.13%] [G loss: 1.503015]
8/8 [==============================] - 0s 5ms/step
128 [D loss: 0.414209, acc.: 88.67%] [G loss: 1.704827]
8/8 [==============================] - 0s 5ms/step
129 [D loss: 0.403890, acc.: 86.91%] [G loss: 1.711817]
8/8 [==============================] - 0s 5ms/step
130 [D loss: 0.341096, acc.: 91.99%] [G loss: 1.675172]
8/8 [==============================] - 0s 5ms/step
131 [D loss: 0.311809, acc.: 93.16%] [G loss: 1.746720]
8/8 [==============================] - 0s 5ms/step
132 [D loss: 0.300340, acc.: 91.60%] [G loss: 1.845856]
8/8 [==============================] - 0s 5ms/step
133 [D loss: 0.281741, acc.: 94.34%] [G loss: 1.900974]
8/8 [==============================] - 0s 5ms/step
134 [D loss: 0.284053, acc.: 92.58%] [G loss: 2.003007]
8/8 [==============================] - 0s 5ms/step
135 [D loss: 0.295733, acc.: 93.95%] [G loss: 2.020007]
8/8 [==============================] - 0s 5ms/step
136 [D loss: 0.266122, acc.: 94.34%] [G loss: 2.173761]
8/8 [==============================] - 0s 5ms/step
137 [D loss: 0.261632, acc.: 94.92%] [G loss: 2.140345]
8/8 [==============================] - 0s 5ms/step
138 [D loss: 0.260361, acc.: 94.14%] [G loss: 2.130860]
8/8 [==============================] - 0s 5ms/step
139 [D loss: 0.290828, acc.: 91.80%] [G loss: 2.119727]
8/8 [==============================] - 0s 5ms/step
140 [D loss: 0.396351, acc.: 84.57%] [G loss: 1.939495]
8/8 [==============================] - 0s 5ms/step
141 [D loss: 0.495106, acc.: 75.59%] [G loss: 1.866684]
8/8 [==============================] - 0s 5ms/step
142 [D loss: 0.533902, acc.: 76.95%] [G loss: 2.926730]
8/8 [==============================] - 0s 5ms/step
143 [D loss: 0.566631, acc.: 74.02%] [G loss: 3.812837]
8/8 [==============================] - 0s 5ms/step
144 [D loss: 0.832333, acc.: 53.91%] [G loss: 2.540532]
8/8 [==============================] - 0s 5ms/step
145 [D loss: 0.491377, acc.: 77.34%] [G loss: 3.046237]
8/8 [==============================] - 0s 5ms/step
146 [D loss: 0.581401, acc.: 73.24%] [G loss: 2.328939]
8/8 [==============================] - 0s 5ms/step
147 [D loss: 0.493260, acc.: 76.95%] [G loss: 2.232923]
8/8 [==============================] - 0s 5ms/step
148 [D loss: 0.474216, acc.: 82.62%] [G loss: 2.422593]
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149 [D loss: 0.476555, acc.: 84.18%] [G loss: 2.419968]
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150 [D loss: 0.355991, acc.: 90.62%] [G loss: 3.045541]
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151 [D loss: 0.465344, acc.: 79.30%] [G loss: 2.043758]
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152 [D loss: 0.366679, acc.: 89.45%] [G loss: 2.466649]
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153 [D loss: 0.254629, acc.: 94.53%] [G loss: 2.978457]
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154 [D loss: 0.262296, acc.: 94.14%] [G loss: 2.833214]
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155 [D loss: 0.224669, acc.: 94.53%] [G loss: 2.675633]
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156 [D loss: 0.204111, acc.: 95.90%] [G loss: 2.938314]
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157 [D loss: 0.670999, acc.: 67.58%] [G loss: 3.159714]
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158 [D loss: 1.008841, acc.: 53.91%] [G loss: 4.074263]
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159 [D loss: 0.343566, acc.: 88.48%] [G loss: 3.330620]
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160 [D loss: 0.331610, acc.: 89.65%] [G loss: 2.415855]
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161 [D loss: 0.204801, acc.: 94.14%] [G loss: 2.354643]
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162 [D loss: 0.256722, acc.: 94.53%] [G loss: 2.046955]
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163 [D loss: 0.402548, acc.: 80.27%] [G loss: 2.005107]
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164 [D loss: 0.334518, acc.: 86.91%] [G loss: 2.828143]
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165 [D loss: 0.309328, acc.: 90.82%] [G loss: 3.180063]
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166 [D loss: 0.366984, acc.: 86.72%] [G loss: 3.234635]
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167 [D loss: 0.260816, acc.: 93.55%] [G loss: 3.526954]
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168 [D loss: 0.250910, acc.: 92.58%] [G loss: 3.229489]
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169 [D loss: 0.478007, acc.: 77.73%] [G loss: 1.838213]
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170 [D loss: 2.208913, acc.: 45.90%] [G loss: 2.565123]
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171 [D loss: 0.576657, acc.: 74.80%] [G loss: 3.067012]
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172 [D loss: 0.629891, acc.: 73.24%] [G loss: 1.851677]
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173 [D loss: 0.533998, acc.: 75.20%] [G loss: 1.550171]
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174 [D loss: 0.422550, acc.: 85.35%] [G loss: 1.527926]
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175 [D loss: 0.388706, acc.: 86.33%] [G loss: 1.581719]
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176 [D loss: 0.372706, acc.: 87.50%] [G loss: 1.806108]
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177 [D loss: 0.385015, acc.: 85.35%] [G loss: 1.830049]
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178 [D loss: 0.443265, acc.: 83.01%] [G loss: 1.672297]
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179 [D loss: 0.465934, acc.: 78.91%] [G loss: 1.783277]
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180 [D loss: 0.469112, acc.: 78.12%] [G loss: 1.844014]
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181 [D loss: 0.527079, acc.: 74.41%] [G loss: 1.837997]
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182 [D loss: 0.504037, acc.: 72.46%] [G loss: 2.338544]
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183 [D loss: 0.444614, acc.: 82.42%] [G loss: 2.216784]
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184 [D loss: 0.454229, acc.: 84.77%] [G loss: 2.193986]
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185 [D loss: 0.374866, acc.: 89.06%] [G loss: 2.123595]
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186 [D loss: 0.366335, acc.: 87.89%] [G loss: 2.260980]
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187 [D loss: 0.405112, acc.: 83.20%] [G loss: 2.603157]
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188 [D loss: 0.404485, acc.: 83.79%] [G loss: 2.742943]
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189 [D loss: 0.336636, acc.: 86.72%] [G loss: 3.237873]
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190 [D loss: 0.283098, acc.: 91.60%] [G loss: 3.490590]
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191 [D loss: 0.258875, acc.: 92.97%] [G loss: 2.966718]
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192 [D loss: 0.308936, acc.: 91.41%] [G loss: 2.478255]
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193 [D loss: 0.540233, acc.: 72.27%] [G loss: 1.474999]
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194 [D loss: 0.517459, acc.: 74.02%] [G loss: 1.569079]
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195 [D loss: 0.448020, acc.: 79.30%] [G loss: 1.915938]
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196 [D loss: 0.995076, acc.: 62.89%] [G loss: 2.528757]
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197 [D loss: 0.422406, acc.: 84.38%] [G loss: 3.281474]
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198 [D loss: 0.365842, acc.: 86.52%] [G loss: 2.353403]
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199 [D loss: 0.315522, acc.: 88.87%] [G loss: 2.166324]
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200 [D loss: 0.258998, acc.: 94.92%] [G loss: 1.848624]
1/1 [==============================] - 0s 18ms/step
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201 [D loss: 0.283583, acc.: 94.53%] [G loss: 2.029243]
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202 [D loss: 0.187299, acc.: 95.90%] [G loss: 2.487841]
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203 [D loss: 0.150171, acc.: 97.27%] [G loss: 2.768008]
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204 [D loss: 0.148388, acc.: 95.90%] [G loss: 2.939623]
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205 [D loss: 0.127735, acc.: 97.66%] [G loss: 2.898901]
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206 [D loss: 0.175671, acc.: 96.29%] [G loss: 2.491917]
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207 [D loss: 0.159397, acc.: 95.31%] [G loss: 2.488749]
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208 [D loss: 0.128930, acc.: 96.48%] [G loss: 2.540766]
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209 [D loss: 0.107912, acc.: 97.27%] [G loss: 2.602739]
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210 [D loss: 0.102787, acc.: 98.05%] [G loss: 2.672112]
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211 [D loss: 0.132267, acc.: 95.70%] [G loss: 2.637096]
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212 [D loss: 0.128162, acc.: 96.09%] [G loss: 2.631754]
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213 [D loss: 0.111571, acc.: 97.46%] [G loss: 2.654927]
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214 [D loss: 0.111489, acc.: 97.85%] [G loss: 2.645017]
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215 [D loss: 0.136416, acc.: 96.88%] [G loss: 2.713352]
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216 [D loss: 0.111571, acc.: 97.07%] [G loss: 2.739812]
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217 [D loss: 0.152871, acc.: 96.29%] [G loss: 2.695341]
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218 [D loss: 0.179243, acc.: 96.48%] [G loss: 2.545278]
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219 [D loss: 0.150592, acc.: 97.07%] [G loss: 2.764495]
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220 [D loss: 0.201443, acc.: 93.16%] [G loss: 3.030016]
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221 [D loss: 0.313130, acc.: 86.91%] [G loss: 3.148907]
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222 [D loss: 0.215276, acc.: 93.95%] [G loss: 3.786922]
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223 [D loss: 0.213784, acc.: 93.95%] [G loss: 3.671268]
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224 [D loss: 0.214143, acc.: 93.55%] [G loss: 3.941904]
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225 [D loss: 0.341067, acc.: 85.55%] [G loss: 4.728559]
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226 [D loss: 0.329732, acc.: 89.65%] [G loss: 3.650962]
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227 [D loss: 0.294138, acc.: 89.45%] [G loss: 2.816218]
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228 [D loss: 0.300591, acc.: 89.26%] [G loss: 2.696507]
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229 [D loss: 0.258607, acc.: 89.65%] [G loss: 2.637126]
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230 [D loss: 0.206300, acc.: 93.55%] [G loss: 3.128527]
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231 [D loss: 0.156969, acc.: 96.29%] [G loss: 3.183184]
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232 [D loss: 0.206041, acc.: 92.97%] [G loss: 3.049964]
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233 [D loss: 0.162520, acc.: 96.09%] [G loss: 3.271912]
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234 [D loss: 0.126921, acc.: 96.88%] [G loss: 3.450347]
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235 [D loss: 0.143515, acc.: 95.90%] [G loss: 3.547741]
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236 [D loss: 0.149522, acc.: 94.92%] [G loss: 3.411452]
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237 [D loss: 0.153928, acc.: 96.09%] [G loss: 3.401739]
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238 [D loss: 0.216922, acc.: 92.58%] [G loss: 2.814449]
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239 [D loss: 0.241296, acc.: 89.45%] [G loss: 3.319827]
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240 [D loss: 0.342642, acc.: 86.91%] [G loss: 3.736113]
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241 [D loss: 0.315200, acc.: 87.89%] [G loss: 4.693123]
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242 [D loss: 0.461265, acc.: 81.84%] [G loss: 4.329004]
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243 [D loss: 0.317369, acc.: 89.26%] [G loss: 3.735707]
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244 [D loss: 0.217107, acc.: 93.75%] [G loss: 3.603086]
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245 [D loss: 0.260586, acc.: 91.60%] [G loss: 3.298671]
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246 [D loss: 0.221106, acc.: 93.36%] [G loss: 3.106891]
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247 [D loss: 0.196580, acc.: 94.92%] [G loss: 3.200370]
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248 [D loss: 0.223073, acc.: 92.38%] [G loss: 3.287097]
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249 [D loss: 0.290778, acc.: 88.87%] [G loss: 3.224873]
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250 [D loss: 0.213918, acc.: 94.53%] [G loss: 3.327000]
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251 [D loss: 0.142919, acc.: 94.92%] [G loss: 3.636870]
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252 [D loss: 0.205621, acc.: 93.95%] [G loss: 2.984307]
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253 [D loss: 0.216485, acc.: 92.19%] [G loss: 3.461152]
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254 [D loss: 0.382419, acc.: 80.47%] [G loss: 4.816573]
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255 [D loss: 0.187123, acc.: 92.97%] [G loss: 6.099920]
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256 [D loss: 0.244641, acc.: 91.60%] [G loss: 6.055943]
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257 [D loss: 0.239974, acc.: 88.87%] [G loss: 14.141499]
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258 [D loss: 0.145491, acc.: 93.75%] [G loss: 16.653141]
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259 [D loss: 0.200604, acc.: 92.77%] [G loss: 7.898787]
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260 [D loss: 0.265423, acc.: 85.74%] [G loss: 8.202050]
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261 [D loss: 0.226328, acc.: 91.80%] [G loss: 6.370125]
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262 [D loss: 0.164851, acc.: 94.34%] [G loss: 3.791579]
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263 [D loss: 0.066618, acc.: 97.66%] [G loss: 3.439670]
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264 [D loss: 0.045633, acc.: 99.22%] [G loss: 3.517971]
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265 [D loss: 0.082181, acc.: 98.24%] [G loss: 3.549877]
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266 [D loss: 0.079907, acc.: 97.07%] [G loss: 3.514217]
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267 [D loss: 0.066677, acc.: 97.46%] [G loss: 3.437327]
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268 [D loss: 0.058972, acc.: 98.05%] [G loss: 3.432081]
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269 [D loss: 0.057263, acc.: 98.24%] [G loss: 3.423942]
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270 [D loss: 0.034737, acc.: 99.02%] [G loss: 3.502928]
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271 [D loss: 0.061817, acc.: 98.24%] [G loss: 3.494148]
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272 [D loss: 0.036690, acc.: 99.22%] [G loss: 3.515239]
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273 [D loss: 0.052403, acc.: 97.66%] [G loss: 3.531169]
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274 [D loss: 0.074491, acc.: 97.66%] [G loss: 3.409271]
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275 [D loss: 0.054349, acc.: 98.24%] [G loss: 3.364315]
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276 [D loss: 0.049770, acc.: 98.44%] [G loss: 3.322339]
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277 [D loss: 0.086437, acc.: 97.66%] [G loss: 3.180749]
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278 [D loss: 0.123145, acc.: 96.48%] [G loss: 3.174781]
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279 [D loss: 0.141038, acc.: 96.68%] [G loss: 3.578085]
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280 [D loss: 0.086282, acc.: 97.46%] [G loss: 4.252727]
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281 [D loss: 0.165869, acc.: 94.14%] [G loss: 4.216654]
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282 [D loss: 0.220212, acc.: 91.02%] [G loss: 4.493444]
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283 [D loss: 0.456352, acc.: 80.86%] [G loss: 6.456324]
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284 [D loss: 0.388960, acc.: 85.74%] [G loss: 5.776811]
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285 [D loss: 0.424963, acc.: 81.84%] [G loss: 5.670080]
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286 [D loss: 0.294219, acc.: 91.41%] [G loss: 4.967835]
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287 [D loss: 0.355518, acc.: 83.79%] [G loss: 4.206514]
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288 [D loss: 0.192006, acc.: 93.95%] [G loss: 3.942553]
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289 [D loss: 0.153643, acc.: 95.31%] [G loss: 3.416472]
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290 [D loss: 0.176267, acc.: 94.34%] [G loss: 3.398949]
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291 [D loss: 0.208389, acc.: 91.80%] [G loss: 4.635968]
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292 [D loss: 0.215995, acc.: 91.80%] [G loss: 4.679379]
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293 [D loss: 0.211158, acc.: 93.55%] [G loss: 3.931307]
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294 [D loss: 0.159247, acc.: 94.53%] [G loss: 4.026942]
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295 [D loss: 0.125588, acc.: 96.88%] [G loss: 3.619452]
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296 [D loss: 0.216991, acc.: 93.95%] [G loss: 3.081940]
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297 [D loss: 0.168680, acc.: 94.92%] [G loss: 2.767585]
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298 [D loss: 0.133554, acc.: 96.48%] [G loss: 2.946536]
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299 [D loss: 0.152502, acc.: 95.51%] [G loss: 3.166268]
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301 [D loss: 0.164278, acc.: 94.14%] [G loss: 3.533592]
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302 [D loss: 0.161939, acc.: 94.92%] [G loss: 3.871307]
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303 [D loss: 0.135557, acc.: 95.31%] [G loss: 3.808631]
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304 [D loss: 0.142479, acc.: 96.29%] [G loss: 3.723544]
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305 [D loss: 0.135084, acc.: 95.90%] [G loss: 3.819617]
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306 [D loss: 0.132610, acc.: 95.31%] [G loss: 3.798402]
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307 [D loss: 0.105952, acc.: 96.88%] [G loss: 4.243762]
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308 [D loss: 0.155651, acc.: 94.53%] [G loss: 4.280488]
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309 [D loss: 0.138493, acc.: 94.92%] [G loss: 4.785243]
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310 [D loss: 0.111369, acc.: 97.27%] [G loss: 5.152536]
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311 [D loss: 0.265779, acc.: 90.43%] [G loss: 5.122048]
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312 [D loss: 0.320609, acc.: 86.72%] [G loss: 6.575543]
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313 [D loss: 0.406441, acc.: 83.79%] [G loss: 6.377954]
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314 [D loss: 0.436137, acc.: 81.64%] [G loss: 6.341930]
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315 [D loss: 0.302915, acc.: 89.26%] [G loss: 5.821026]
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316 [D loss: 0.372413, acc.: 87.89%] [G loss: 3.991342]
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317 [D loss: 0.325941, acc.: 86.52%] [G loss: 3.099840]
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318 [D loss: 0.530674, acc.: 79.69%] [G loss: 2.784709]
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319 [D loss: 0.419433, acc.: 84.77%] [G loss: 3.752144]
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320 [D loss: 0.376003, acc.: 84.77%] [G loss: 2.991901]
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321 [D loss: 0.349063, acc.: 87.30%] [G loss: 2.710129]
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322 [D loss: 0.416153, acc.: 82.42%] [G loss: 3.226338]
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323 [D loss: 0.367968, acc.: 84.57%] [G loss: 4.526352]
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324 [D loss: 0.563074, acc.: 76.17%] [G loss: 3.772185]
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325 [D loss: 0.432228, acc.: 80.47%] [G loss: 4.050941]
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326 [D loss: 0.341920, acc.: 87.11%] [G loss: 3.573910]
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327 [D loss: 0.413815, acc.: 84.38%] [G loss: 4.104517]
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328 [D loss: 0.242145, acc.: 90.82%] [G loss: 3.557014]
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329 [D loss: 0.302422, acc.: 87.89%] [G loss: 3.155449]
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330 [D loss: 0.258865, acc.: 89.84%] [G loss: 3.137812]
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331 [D loss: 0.302219, acc.: 87.30%] [G loss: 3.194998]
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332 [D loss: 0.270797, acc.: 89.65%] [G loss: 3.799415]
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333 [D loss: 0.316027, acc.: 88.09%] [G loss: 3.353724]
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334 [D loss: 0.303835, acc.: 86.72%] [G loss: 3.706626]
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335 [D loss: 0.374050, acc.: 86.33%] [G loss: 3.784050]
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336 [D loss: 0.402173, acc.: 83.01%] [G loss: 3.460054]
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337 [D loss: 0.439767, acc.: 80.27%] [G loss: 4.148049]
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338 [D loss: 0.314904, acc.: 88.48%] [G loss: 3.280554]
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339 [D loss: 0.372491, acc.: 84.77%] [G loss: 2.628843]
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340 [D loss: 0.256260, acc.: 92.77%] [G loss: 2.633666]
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341 [D loss: 0.252787, acc.: 88.48%] [G loss: 3.081141]
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342 [D loss: 0.213325, acc.: 92.38%] [G loss: 2.864527]
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343 [D loss: 0.251466, acc.: 91.80%] [G loss: 2.655672]
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344 [D loss: 0.311988, acc.: 86.13%] [G loss: 3.157257]
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345 [D loss: 0.327741, acc.: 86.91%] [G loss: 2.999231]
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346 [D loss: 0.353932, acc.: 87.11%] [G loss: 3.027057]
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347 [D loss: 0.264812, acc.: 90.23%] [G loss: 2.813392]
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348 [D loss: 0.306260, acc.: 87.11%] [G loss: 3.117558]
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349 [D loss: 0.442249, acc.: 81.45%] [G loss: 3.563870]
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350 [D loss: 0.382415, acc.: 84.18%] [G loss: 2.763137]
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351 [D loss: 0.418416, acc.: 80.86%] [G loss: 2.672452]
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352 [D loss: 0.385739, acc.: 83.98%] [G loss: 2.927007]
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353 [D loss: 0.399725, acc.: 82.62%] [G loss: 2.928272]
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354 [D loss: 0.356396, acc.: 83.98%] [G loss: 3.163015]
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355 [D loss: 0.403006, acc.: 83.20%] [G loss: 3.602180]
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356 [D loss: 0.368971, acc.: 84.57%] [G loss: 3.162817]
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357 [D loss: 0.365436, acc.: 83.20%] [G loss: 3.027038]
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358 [D loss: 0.238285, acc.: 91.41%] [G loss: 2.900435]
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359 [D loss: 0.267843, acc.: 89.06%] [G loss: 2.734248]
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360 [D loss: 0.275827, acc.: 89.45%] [G loss: 2.795209]
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361 [D loss: 0.301144, acc.: 88.09%] [G loss: 3.495988]
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362 [D loss: 0.325218, acc.: 86.91%] [G loss: 3.873104]
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363 [D loss: 0.322536, acc.: 86.72%] [G loss: 2.668129]
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364 [D loss: 0.398479, acc.: 83.98%] [G loss: 2.585574]
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365 [D loss: 0.422468, acc.: 82.03%] [G loss: 3.074506]
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366 [D loss: 0.382411, acc.: 83.59%] [G loss: 2.928823]
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367 [D loss: 0.487124, acc.: 77.73%] [G loss: 2.247442]
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368 [D loss: 0.454734, acc.: 78.52%] [G loss: 2.728902]
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369 [D loss: 0.499992, acc.: 77.34%] [G loss: 3.139692]
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370 [D loss: 0.462017, acc.: 83.79%] [G loss: 2.561788]
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371 [D loss: 0.519361, acc.: 75.98%] [G loss: 2.722302]
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372 [D loss: 0.464949, acc.: 79.49%] [G loss: 2.490958]
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373 [D loss: 0.485800, acc.: 77.15%] [G loss: 2.503463]
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374 [D loss: 0.435380, acc.: 80.86%] [G loss: 2.376297]
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375 [D loss: 0.496143, acc.: 77.34%] [G loss: 2.205397]
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376 [D loss: 0.517390, acc.: 75.78%] [G loss: 2.720968]
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377 [D loss: 0.464102, acc.: 81.25%] [G loss: 2.056279]
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378 [D loss: 0.515736, acc.: 77.54%] [G loss: 2.125847]
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379 [D loss: 0.592504, acc.: 74.80%] [G loss: 2.044627]
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380 [D loss: 0.477048, acc.: 79.88%] [G loss: 2.027748]
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381 [D loss: 0.561944, acc.: 71.88%] [G loss: 3.945045]
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382 [D loss: 0.526473, acc.: 75.98%] [G loss: 2.544950]
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383 [D loss: 0.477362, acc.: 80.47%] [G loss: 2.462009]
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384 [D loss: 0.421041, acc.: 81.84%] [G loss: 2.015506]
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385 [D loss: 0.570612, acc.: 73.05%] [G loss: 2.039401]
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386 [D loss: 0.457617, acc.: 81.45%] [G loss: 3.320365]
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387 [D loss: 0.508342, acc.: 79.49%] [G loss: 2.398207]
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388 [D loss: 0.506383, acc.: 76.95%] [G loss: 1.900939]
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389 [D loss: 0.446534, acc.: 80.47%] [G loss: 1.930166]
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390 [D loss: 0.536030, acc.: 71.29%] [G loss: 1.871975]
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391 [D loss: 0.555506, acc.: 71.68%] [G loss: 2.242187]
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392 [D loss: 0.469479, acc.: 79.88%] [G loss: 1.990285]
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393 [D loss: 0.528414, acc.: 74.61%] [G loss: 1.777891]
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394 [D loss: 0.602711, acc.: 68.95%] [G loss: 1.770425]
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395 [D loss: 0.544532, acc.: 74.41%] [G loss: 2.062869]
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396 [D loss: 0.550775, acc.: 75.59%] [G loss: 1.750496]
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397 [D loss: 0.616568, acc.: 69.14%] [G loss: 1.614065]
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398 [D loss: 0.606520, acc.: 69.92%] [G loss: 2.039229]
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399 [D loss: 0.524444, acc.: 75.59%] [G loss: 1.752932]
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400 [D loss: 0.502056, acc.: 77.15%] [G loss: 1.710200]
1/1 [==============================] - 0s 19ms/step
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401 [D loss: 0.604466, acc.: 70.31%] [G loss: 1.536551]
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402 [D loss: 0.593444, acc.: 72.66%] [G loss: 1.971291]
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403 [D loss: 0.555083, acc.: 75.20%] [G loss: 1.826298]
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404 [D loss: 0.536872, acc.: 75.39%] [G loss: 1.673610]
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405 [D loss: 0.549741, acc.: 74.22%] [G loss: 1.565812]
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406 [D loss: 0.613466, acc.: 67.97%] [G loss: 1.680873]
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407 [D loss: 0.596504, acc.: 68.75%] [G loss: 1.808858]
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408 [D loss: 0.538669, acc.: 76.95%] [G loss: 1.713984]
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409 [D loss: 0.563414, acc.: 73.24%] [G loss: 1.583919]
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410 [D loss: 0.649183, acc.: 66.02%] [G loss: 1.501238]
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411 [D loss: 0.587340, acc.: 70.90%] [G loss: 1.532490]
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412 [D loss: 0.626811, acc.: 69.34%] [G loss: 1.592460]
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413 [D loss: 0.631008, acc.: 69.53%] [G loss: 1.459028]
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414 [D loss: 0.578274, acc.: 69.92%] [G loss: 1.450555]
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415 [D loss: 0.664316, acc.: 66.41%] [G loss: 1.308031]
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416 [D loss: 0.605379, acc.: 65.82%] [G loss: 1.621707]
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417 [D loss: 0.666867, acc.: 66.80%] [G loss: 1.358178]
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418 [D loss: 0.587231, acc.: 72.46%] [G loss: 1.363807]
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419 [D loss: 0.582465, acc.: 73.44%] [G loss: 1.362599]
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420 [D loss: 0.612289, acc.: 66.02%] [G loss: 1.429118]
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421 [D loss: 0.640946, acc.: 67.58%] [G loss: 1.400600]
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422 [D loss: 0.600106, acc.: 71.68%] [G loss: 1.530754]
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423 [D loss: 0.649280, acc.: 67.38%] [G loss: 1.363156]
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424 [D loss: 0.630414, acc.: 69.14%] [G loss: 1.323670]
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425 [D loss: 0.673419, acc.: 65.62%] [G loss: 1.234297]
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426 [D loss: 0.621839, acc.: 67.77%] [G loss: 1.256136]
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427 [D loss: 0.609938, acc.: 70.70%] [G loss: 1.448981]
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428 [D loss: 0.645981, acc.: 66.41%] [G loss: 1.244864]
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429 [D loss: 0.619957, acc.: 69.73%] [G loss: 1.293595]
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430 [D loss: 0.613150, acc.: 67.97%] [G loss: 1.234951]
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431 [D loss: 0.639652, acc.: 67.58%] [G loss: 1.272908]
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432 [D loss: 0.609889, acc.: 69.73%] [G loss: 1.269039]
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433 [D loss: 0.639066, acc.: 67.38%] [G loss: 1.220704]
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434 [D loss: 0.699778, acc.: 66.02%] [G loss: 1.146303]
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435 [D loss: 0.653589, acc.: 64.45%] [G loss: 1.108058]
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436 [D loss: 0.665877, acc.: 62.11%] [G loss: 1.221570]
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437 [D loss: 0.629998, acc.: 67.38%] [G loss: 1.188693]
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438 [D loss: 0.668543, acc.: 63.48%] [G loss: 1.139774]
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439 [D loss: 0.670968, acc.: 61.13%] [G loss: 1.101386]
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440 [D loss: 0.673974, acc.: 59.96%] [G loss: 1.126630]
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441 [D loss: 0.668437, acc.: 63.09%] [G loss: 1.110543]
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442 [D loss: 0.668456, acc.: 61.72%] [G loss: 1.141251]
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443 [D loss: 0.648989, acc.: 66.41%] [G loss: 1.067177]
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444 [D loss: 0.697862, acc.: 58.40%] [G loss: 1.121216]
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445 [D loss: 0.651935, acc.: 62.89%] [G loss: 1.143549]
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446 [D loss: 0.647342, acc.: 60.74%] [G loss: 1.128213]
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447 [D loss: 0.663837, acc.: 63.87%] [G loss: 1.108482]
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448 [D loss: 0.627128, acc.: 65.82%] [G loss: 1.031674]
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449 [D loss: 0.689928, acc.: 57.81%] [G loss: 1.027139]
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450 [D loss: 0.694476, acc.: 57.81%] [G loss: 1.096748]
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451 [D loss: 0.662591, acc.: 62.11%] [G loss: 1.047637]
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452 [D loss: 0.660900, acc.: 58.98%] [G loss: 0.997600]
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453 [D loss: 0.673996, acc.: 56.45%] [G loss: 0.959514]
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454 [D loss: 0.671599, acc.: 58.40%] [G loss: 0.994609]
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455 [D loss: 0.667203, acc.: 60.74%] [G loss: 0.949545]
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456 [D loss: 0.637108, acc.: 63.48%] [G loss: 1.025811]
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457 [D loss: 0.632118, acc.: 65.62%] [G loss: 1.039813]
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458 [D loss: 0.659756, acc.: 63.87%] [G loss: 0.987073]
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459 [D loss: 0.679630, acc.: 57.62%] [G loss: 1.021440]
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460 [D loss: 0.632214, acc.: 67.58%] [G loss: 1.029030]
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461 [D loss: 0.634039, acc.: 66.21%] [G loss: 1.039771]
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462 [D loss: 0.663637, acc.: 60.94%] [G loss: 1.004846]
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463 [D loss: 0.659373, acc.: 60.94%] [G loss: 1.044495]
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464 [D loss: 0.672430, acc.: 60.94%] [G loss: 1.008952]
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465 [D loss: 0.644497, acc.: 64.06%] [G loss: 0.971069]
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466 [D loss: 0.630430, acc.: 65.62%] [G loss: 1.012250]
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467 [D loss: 0.670808, acc.: 59.77%] [G loss: 1.013078]
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468 [D loss: 0.642916, acc.: 63.67%] [G loss: 1.023276]
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469 [D loss: 0.649252, acc.: 63.28%] [G loss: 1.009651]
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470 [D loss: 0.651448, acc.: 61.33%] [G loss: 1.003346]
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471 [D loss: 0.637468, acc.: 62.50%] [G loss: 0.969439]
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472 [D loss: 0.692614, acc.: 56.64%] [G loss: 0.966106]
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473 [D loss: 0.659054, acc.: 59.77%] [G loss: 1.014527]
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474 [D loss: 0.650438, acc.: 62.50%] [G loss: 0.950860]
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475 [D loss: 0.637752, acc.: 66.60%] [G loss: 0.943350]
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476 [D loss: 0.678575, acc.: 57.42%] [G loss: 0.954616]
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477 [D loss: 0.647171, acc.: 60.16%] [G loss: 0.956589]
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478 [D loss: 0.656506, acc.: 63.67%] [G loss: 0.972721]
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479 [D loss: 0.667244, acc.: 60.94%] [G loss: 0.964258]
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480 [D loss: 0.666346, acc.: 60.16%] [G loss: 1.000193]
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481 [D loss: 0.654861, acc.: 58.98%] [G loss: 0.913862]
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482 [D loss: 0.611659, acc.: 69.53%] [G loss: 0.988050]
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483 [D loss: 0.667445, acc.: 59.38%] [G loss: 0.920541]
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484 [D loss: 0.654047, acc.: 61.33%] [G loss: 1.006642]
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485 [D loss: 0.629800, acc.: 65.04%] [G loss: 0.973825]
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486 [D loss: 0.670903, acc.: 58.40%] [G loss: 0.944390]
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487 [D loss: 0.690887, acc.: 54.10%] [G loss: 0.926283]
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488 [D loss: 0.661242, acc.: 59.96%] [G loss: 0.971831]
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489 [D loss: 0.655982, acc.: 60.55%] [G loss: 0.920897]
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490 [D loss: 0.646659, acc.: 63.67%] [G loss: 0.972917]
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491 [D loss: 0.672317, acc.: 59.57%] [G loss: 0.896703]
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492 [D loss: 0.702506, acc.: 54.49%] [G loss: 0.919636]
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493 [D loss: 0.666355, acc.: 59.57%] [G loss: 0.970342]
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494 [D loss: 0.642547, acc.: 63.87%] [G loss: 0.939543]
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495 [D loss: 0.664860, acc.: 60.55%] [G loss: 0.913644]
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496 [D loss: 0.668084, acc.: 56.25%] [G loss: 0.935829]
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497 [D loss: 0.673995, acc.: 59.38%] [G loss: 0.950057]
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498 [D loss: 0.676706, acc.: 60.16%] [G loss: 0.909520]
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499 [D loss: 0.676575, acc.: 61.72%] [G loss: 0.958089]
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500 [D loss: 0.678260, acc.: 58.59%] [G loss: 0.898975]
1/1 [==============================] - 0s 19ms/step
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501 [D loss: 0.648473, acc.: 61.33%] [G loss: 0.942842]
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502 [D loss: 0.660215, acc.: 60.16%] [G loss: 0.946389]
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503 [D loss: 0.661658, acc.: 62.89%] [G loss: 0.933893]
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504 [D loss: 0.694103, acc.: 54.88%] [G loss: 0.876985]
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505 [D loss: 0.665887, acc.: 59.77%] [G loss: 0.869025]
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506 [D loss: 0.682405, acc.: 56.05%] [G loss: 0.862128]
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507 [D loss: 0.680131, acc.: 58.20%] [G loss: 0.893127]
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508 [D loss: 0.700256, acc.: 52.73%] [G loss: 0.897048]
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509 [D loss: 0.660883, acc.: 62.50%] [G loss: 0.906583]
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510 [D loss: 0.673774, acc.: 56.64%] [G loss: 0.915249]
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511 [D loss: 0.674844, acc.: 55.66%] [G loss: 0.932941]
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512 [D loss: 0.676157, acc.: 57.81%] [G loss: 0.895944]
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513 [D loss: 0.662227, acc.: 62.50%] [G loss: 0.939584]
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514 [D loss: 0.653714, acc.: 60.55%] [G loss: 0.875828]
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515 [D loss: 0.692062, acc.: 52.73%] [G loss: 0.923389]
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516 [D loss: 0.664707, acc.: 55.86%] [G loss: 0.886446]
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517 [D loss: 0.691523, acc.: 54.69%] [G loss: 0.873976]
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518 [D loss: 0.683621, acc.: 58.20%] [G loss: 0.861526]
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519 [D loss: 0.676354, acc.: 55.66%] [G loss: 0.883061]
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520 [D loss: 0.670752, acc.: 58.59%] [G loss: 0.873290]
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521 [D loss: 0.648751, acc.: 61.52%] [G loss: 0.895576]
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522 [D loss: 0.668007, acc.: 60.16%] [G loss: 0.863176]
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523 [D loss: 0.679997, acc.: 55.08%] [G loss: 0.868264]
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524 [D loss: 0.674048, acc.: 57.03%] [G loss: 0.885646]
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525 [D loss: 0.670355, acc.: 57.62%] [G loss: 0.865030]
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526 [D loss: 0.664893, acc.: 58.79%] [G loss: 0.876583]
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527 [D loss: 0.665370, acc.: 58.79%] [G loss: 0.869796]
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528 [D loss: 0.659382, acc.: 60.74%] [G loss: 0.855754]
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529 [D loss: 0.682781, acc.: 56.45%] [G loss: 0.894781]
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530 [D loss: 0.671519, acc.: 58.59%] [G loss: 0.857211]
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531 [D loss: 0.664969, acc.: 56.25%] [G loss: 0.887735]
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532 [D loss: 0.670249, acc.: 57.81%] [G loss: 0.857981]
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533 [D loss: 0.649952, acc.: 62.30%] [G loss: 0.894547]
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534 [D loss: 0.658062, acc.: 61.91%] [G loss: 0.855819]
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535 [D loss: 0.674872, acc.: 60.74%] [G loss: 0.899357]
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536 [D loss: 0.686475, acc.: 54.88%] [G loss: 0.846834]
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537 [D loss: 0.687449, acc.: 54.88%] [G loss: 0.879879]
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538 [D loss: 0.687108, acc.: 54.88%] [G loss: 0.873559]
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539 [D loss: 0.666232, acc.: 60.94%] [G loss: 0.882829]
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540 [D loss: 0.671126, acc.: 57.42%] [G loss: 0.893618]
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541 [D loss: 0.676110, acc.: 57.81%] [G loss: 0.898143]
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542 [D loss: 0.663215, acc.: 59.38%] [G loss: 0.957494]
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543 [D loss: 0.675608, acc.: 56.05%] [G loss: 0.867152]
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544 [D loss: 0.641155, acc.: 63.48%] [G loss: 0.935902]
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545 [D loss: 0.685759, acc.: 53.91%] [G loss: 0.874789]
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546 [D loss: 0.666788, acc.: 60.16%] [G loss: 0.961846]
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547 [D loss: 0.646243, acc.: 64.65%] [G loss: 0.950718]
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548 [D loss: 0.652440, acc.: 61.33%] [G loss: 0.891463]
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549 [D loss: 0.631342, acc.: 63.09%] [G loss: 0.952600]
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550 [D loss: 0.677537, acc.: 56.64%] [G loss: 0.785009]
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551 [D loss: 0.672794, acc.: 55.08%] [G loss: 0.908197]
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552 [D loss: 0.665276, acc.: 57.81%] [G loss: 0.855955]
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553 [D loss: 0.677793, acc.: 57.03%] [G loss: 0.869482]
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554 [D loss: 0.654305, acc.: 63.67%] [G loss: 0.952374]
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555 [D loss: 0.694320, acc.: 53.12%] [G loss: 0.817258]
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556 [D loss: 0.672032, acc.: 56.25%] [G loss: 0.956967]
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557 [D loss: 0.649385, acc.: 60.74%] [G loss: 0.868015]
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558 [D loss: 0.653878, acc.: 61.72%] [G loss: 0.953628]
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559 [D loss: 0.640195, acc.: 65.62%] [G loss: 0.960120]
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560 [D loss: 0.679810, acc.: 56.84%] [G loss: 0.818742]
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561 [D loss: 0.651121, acc.: 61.72%] [G loss: 1.080613]
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562 [D loss: 0.672933, acc.: 58.20%] [G loss: 0.875002]
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563 [D loss: 0.644395, acc.: 63.48%] [G loss: 0.942440]
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564 [D loss: 0.677002, acc.: 57.03%] [G loss: 0.883298]
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565 [D loss: 0.687781, acc.: 54.88%] [G loss: 0.838056]
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566 [D loss: 0.648277, acc.: 60.35%] [G loss: 0.965185]
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567 [D loss: 0.684856, acc.: 54.69%] [G loss: 0.843863]
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568 [D loss: 0.655566, acc.: 60.55%] [G loss: 0.940151]
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569 [D loss: 0.668442, acc.: 60.16%] [G loss: 0.858687]
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570 [D loss: 0.674918, acc.: 57.23%] [G loss: 0.838981]
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571 [D loss: 0.664071, acc.: 58.98%] [G loss: 0.888700]
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572 [D loss: 0.664957, acc.: 61.13%] [G loss: 0.851162]
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573 [D loss: 0.647421, acc.: 65.23%] [G loss: 0.925571]
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574 [D loss: 0.669890, acc.: 58.40%] [G loss: 0.836619]
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575 [D loss: 0.644713, acc.: 62.70%] [G loss: 0.970442]
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576 [D loss: 0.663969, acc.: 61.91%] [G loss: 0.885538]
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577 [D loss: 0.665097, acc.: 58.98%] [G loss: 0.905732]
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578 [D loss: 0.640180, acc.: 64.26%] [G loss: 0.927189]
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579 [D loss: 0.713417, acc.: 49.80%] [G loss: 0.813692]
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580 [D loss: 0.667264, acc.: 59.38%] [G loss: 0.993719]
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581 [D loss: 0.642132, acc.: 65.23%] [G loss: 0.860681]
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582 [D loss: 0.637789, acc.: 66.80%] [G loss: 0.965034]
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583 [D loss: 0.641002, acc.: 64.26%] [G loss: 0.978062]
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584 [D loss: 0.697710, acc.: 53.32%] [G loss: 0.868089]
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585 [D loss: 0.641350, acc.: 66.80%] [G loss: 1.114914]
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586 [D loss: 0.677824, acc.: 59.38%] [G loss: 0.833951]
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587 [D loss: 0.632577, acc.: 67.19%] [G loss: 1.031590]
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588 [D loss: 0.651686, acc.: 64.26%] [G loss: 0.907087]
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589 [D loss: 0.692242, acc.: 57.62%] [G loss: 0.853619]
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590 [D loss: 0.633924, acc.: 67.77%] [G loss: 1.132874]
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591 [D loss: 0.682665, acc.: 59.18%] [G loss: 0.854031]
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592 [D loss: 0.633909, acc.: 69.34%] [G loss: 1.011712]
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593 [D loss: 0.627889, acc.: 66.02%] [G loss: 1.027561]
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594 [D loss: 0.727085, acc.: 49.41%] [G loss: 0.854913]
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595 [D loss: 0.622319, acc.: 67.38%] [G loss: 1.125644]
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596 [D loss: 0.681760, acc.: 58.59%] [G loss: 0.853799]
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597 [D loss: 0.655987, acc.: 64.06%] [G loss: 0.955906]
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598 [D loss: 0.610832, acc.: 72.46%] [G loss: 1.061915]
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599 [D loss: 0.684525, acc.: 54.88%] [G loss: 0.837213]
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600 [D loss: 0.686785, acc.: 55.08%] [G loss: 0.930139]
1/1 [==============================] - 0s 16ms/step
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601 [D loss: 0.628457, acc.: 67.38%] [G loss: 1.156304]
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602 [D loss: 0.689836, acc.: 57.81%] [G loss: 0.859896]
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603 [D loss: 0.634899, acc.: 67.58%] [G loss: 1.020524]
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604 [D loss: 0.615887, acc.: 67.97%] [G loss: 1.001420]
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605 [D loss: 0.723764, acc.: 50.39%] [G loss: 0.803978]
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606 [D loss: 0.638903, acc.: 65.82%] [G loss: 1.137028]
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607 [D loss: 0.664756, acc.: 60.74%] [G loss: 0.897021]
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608 [D loss: 0.670859, acc.: 62.70%] [G loss: 0.935167]
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609 [D loss: 0.624115, acc.: 67.19%] [G loss: 1.085520]
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610 [D loss: 0.665555, acc.: 57.42%] [G loss: 0.871643]
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611 [D loss: 0.700969, acc.: 55.66%] [G loss: 0.885837]
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612 [D loss: 0.614091, acc.: 70.51%] [G loss: 1.195599]
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613 [D loss: 0.670925, acc.: 61.13%] [G loss: 0.808027]
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614 [D loss: 0.644927, acc.: 63.67%] [G loss: 1.042579]
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615 [D loss: 0.634673, acc.: 64.84%] [G loss: 1.026143]
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616 [D loss: 0.704582, acc.: 52.73%] [G loss: 0.781518]
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617 [D loss: 0.647699, acc.: 64.65%] [G loss: 1.107003]
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618 [D loss: 0.653290, acc.: 61.33%] [G loss: 1.014464]
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619 [D loss: 0.680230, acc.: 59.18%] [G loss: 0.903339]
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620 [D loss: 0.618052, acc.: 70.70%] [G loss: 1.059634]
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621 [D loss: 0.668616, acc.: 58.98%] [G loss: 0.937954]
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622 [D loss: 0.678608, acc.: 59.18%] [G loss: 0.814645]
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623 [D loss: 0.636305, acc.: 65.82%] [G loss: 1.087991]
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624 [D loss: 0.663030, acc.: 58.59%] [G loss: 0.918247]
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625 [D loss: 0.680710, acc.: 58.20%] [G loss: 0.949001]
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626 [D loss: 0.594003, acc.: 73.63%] [G loss: 1.084037]
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627 [D loss: 0.676166, acc.: 56.45%] [G loss: 0.890964]
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628 [D loss: 0.712577, acc.: 53.32%] [G loss: 0.809395]
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629 [D loss: 0.628847, acc.: 64.06%] [G loss: 1.239251]
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630 [D loss: 0.674259, acc.: 58.40%] [G loss: 0.858858]
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631 [D loss: 0.652445, acc.: 64.26%] [G loss: 0.965036]
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632 [D loss: 0.593524, acc.: 72.46%] [G loss: 1.116706]
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633 [D loss: 0.672016, acc.: 60.35%] [G loss: 0.872605]
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634 [D loss: 0.688366, acc.: 56.84%] [G loss: 0.865181]
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635 [D loss: 0.611920, acc.: 70.90%] [G loss: 1.222426]
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636 [D loss: 0.657901, acc.: 58.01%] [G loss: 0.863133]
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637 [D loss: 0.684767, acc.: 59.77%] [G loss: 0.902270]
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638 [D loss: 0.624094, acc.: 66.99%] [G loss: 1.032676]
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639 [D loss: 0.654687, acc.: 60.55%] [G loss: 0.909740]
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640 [D loss: 0.710949, acc.: 52.93%] [G loss: 0.829504]
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641 [D loss: 0.643969, acc.: 62.30%] [G loss: 1.134459]
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642 [D loss: 0.666112, acc.: 60.94%] [G loss: 0.874903]
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643 [D loss: 0.665619, acc.: 60.35%] [G loss: 0.883056]
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644 [D loss: 0.622130, acc.: 67.97%] [G loss: 1.027265]
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645 [D loss: 0.654627, acc.: 60.55%] [G loss: 0.949205]
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646 [D loss: 0.689118, acc.: 54.10%] [G loss: 0.794788]
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647 [D loss: 0.621817, acc.: 66.21%] [G loss: 1.093153]
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648 [D loss: 0.648305, acc.: 63.48%] [G loss: 0.957242]
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649 [D loss: 0.713799, acc.: 54.88%] [G loss: 0.878739]
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650 [D loss: 0.622897, acc.: 65.62%] [G loss: 1.031174]
1/1 [==============================] - 0s 16ms/step
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651 [D loss: 0.631555, acc.: 65.82%] [G loss: 0.983791]
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652 [D loss: 0.697192, acc.: 53.52%] [G loss: 0.794230]
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653 [D loss: 0.679764, acc.: 59.38%] [G loss: 0.919022]
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654 [D loss: 0.627044, acc.: 67.38%] [G loss: 1.035533]
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655 [D loss: 0.682810, acc.: 57.42%] [G loss: 0.832323]
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656 [D loss: 0.657757, acc.: 62.89%] [G loss: 0.922788]
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657 [D loss: 0.642510, acc.: 64.45%] [G loss: 0.943715]
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658 [D loss: 0.686578, acc.: 57.42%] [G loss: 0.835940]
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659 [D loss: 0.702477, acc.: 56.64%] [G loss: 0.837683]
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660 [D loss: 0.648347, acc.: 62.30%] [G loss: 0.916710]
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661 [D loss: 0.673702, acc.: 59.18%] [G loss: 0.907284]
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662 [D loss: 0.674930, acc.: 58.98%] [G loss: 0.861563]
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663 [D loss: 0.649790, acc.: 63.87%] [G loss: 0.945805]
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664 [D loss: 0.659753, acc.: 63.87%] [G loss: 0.903962]
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665 [D loss: 0.695000, acc.: 55.86%] [G loss: 0.795000]
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666 [D loss: 0.658885, acc.: 61.33%] [G loss: 0.873538]
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667 [D loss: 0.651257, acc.: 61.33%] [G loss: 0.925670]
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668 [D loss: 0.664902, acc.: 59.18%] [G loss: 0.846661]
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669 [D loss: 0.660437, acc.: 61.91%] [G loss: 0.850439]
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670 [D loss: 0.664574, acc.: 61.13%] [G loss: 0.891403]
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671 [D loss: 0.675951, acc.: 55.47%] [G loss: 0.807294]
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672 [D loss: 0.701060, acc.: 55.27%] [G loss: 0.814931]
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673 [D loss: 0.683181, acc.: 59.57%] [G loss: 0.887996]
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674 [D loss: 0.642552, acc.: 61.13%] [G loss: 0.858634]
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675 [D loss: 0.696978, acc.: 56.84%] [G loss: 0.832543]
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676 [D loss: 0.651798, acc.: 62.89%] [G loss: 0.850457]
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677 [D loss: 0.669294, acc.: 58.01%] [G loss: 0.849223]
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678 [D loss: 0.686242, acc.: 58.01%] [G loss: 0.790933]
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679 [D loss: 0.661988, acc.: 60.35%] [G loss: 0.855318]
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680 [D loss: 0.651143, acc.: 61.91%] [G loss: 0.882419]
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681 [D loss: 0.667681, acc.: 58.79%] [G loss: 0.844736]
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682 [D loss: 0.673533, acc.: 58.20%] [G loss: 0.839990]
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683 [D loss: 0.667792, acc.: 57.23%] [G loss: 0.869143]
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684 [D loss: 0.680428, acc.: 57.81%] [G loss: 0.816903]
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685 [D loss: 0.670384, acc.: 60.35%] [G loss: 0.832223]
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686 [D loss: 0.661952, acc.: 63.09%] [G loss: 0.870362]
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687 [D loss: 0.680003, acc.: 56.25%] [G loss: 0.848065]
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688 [D loss: 0.657341, acc.: 60.55%] [G loss: 0.820645]
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689 [D loss: 0.665872, acc.: 60.16%] [G loss: 0.881055]
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690 [D loss: 0.667258, acc.: 60.35%] [G loss: 0.849575]
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691 [D loss: 0.675302, acc.: 58.98%] [G loss: 0.867659]
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692 [D loss: 0.678325, acc.: 57.42%] [G loss: 0.842611]
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693 [D loss: 0.652162, acc.: 64.65%] [G loss: 0.883985]
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694 [D loss: 0.653000, acc.: 63.09%] [G loss: 0.871290]
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695 [D loss: 0.668570, acc.: 57.62%] [G loss: 0.833604]
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696 [D loss: 0.667078, acc.: 58.79%] [G loss: 0.889115]
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697 [D loss: 0.666033, acc.: 59.57%] [G loss: 0.819202]
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698 [D loss: 0.667418, acc.: 59.96%] [G loss: 0.803322]
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699 [D loss: 0.670465, acc.: 61.33%] [G loss: 0.837446]
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700 [D loss: 0.659021, acc.: 61.33%] [G loss: 0.867654]
1/1 [==============================] - 0s 17ms/step
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701 [D loss: 0.660208, acc.: 59.18%] [G loss: 0.859342]
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702 [D loss: 0.671080, acc.: 60.16%] [G loss: 0.842899]
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703 [D loss: 0.666863, acc.: 60.55%] [G loss: 0.854821]
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704 [D loss: 0.672518, acc.: 59.96%] [G loss: 0.851155]
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705 [D loss: 0.660367, acc.: 59.57%] [G loss: 0.825815]
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706 [D loss: 0.674375, acc.: 58.01%] [G loss: 0.860081]
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707 [D loss: 0.648010, acc.: 62.50%] [G loss: 0.909509]
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708 [D loss: 0.679319, acc.: 57.81%] [G loss: 0.842162]
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709 [D loss: 0.668293, acc.: 56.84%] [G loss: 0.853102]
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710 [D loss: 0.646424, acc.: 63.48%] [G loss: 0.876746]
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711 [D loss: 0.660687, acc.: 62.11%] [G loss: 0.846932]
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712 [D loss: 0.679772, acc.: 54.69%] [G loss: 0.822984]
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713 [D loss: 0.687090, acc.: 56.05%] [G loss: 0.890600]
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714 [D loss: 0.666179, acc.: 59.96%] [G loss: 0.900681]
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715 [D loss: 0.693567, acc.: 53.52%] [G loss: 0.851958]
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716 [D loss: 0.647903, acc.: 61.13%] [G loss: 0.874099]
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717 [D loss: 0.661832, acc.: 60.16%] [G loss: 0.878082]
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718 [D loss: 0.679635, acc.: 56.64%] [G loss: 0.804382]
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719 [D loss: 0.690881, acc.: 54.69%] [G loss: 0.784187]
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720 [D loss: 0.657616, acc.: 61.52%] [G loss: 0.897322]
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721 [D loss: 0.663711, acc.: 58.98%] [G loss: 0.970936]
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722 [D loss: 0.671578, acc.: 57.62%] [G loss: 0.828253]
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723 [D loss: 0.667355, acc.: 58.40%] [G loss: 0.866049]
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724 [D loss: 0.646540, acc.: 64.06%] [G loss: 0.944801]
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725 [D loss: 0.662363, acc.: 59.38%] [G loss: 0.867082]
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726 [D loss: 0.698579, acc.: 55.86%] [G loss: 0.809156]
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727 [D loss: 0.671482, acc.: 56.84%] [G loss: 0.924144]
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728 [D loss: 0.642062, acc.: 66.99%] [G loss: 0.971178]
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729 [D loss: 0.682657, acc.: 57.81%] [G loss: 0.829363]
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730 [D loss: 0.672488, acc.: 57.42%] [G loss: 0.864619]
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731 [D loss: 0.647168, acc.: 64.45%] [G loss: 0.895613]
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732 [D loss: 0.671908, acc.: 57.62%] [G loss: 0.834004]
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733 [D loss: 0.720143, acc.: 50.39%] [G loss: 0.751780]
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734 [D loss: 0.675108, acc.: 58.40%] [G loss: 0.848827]
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735 [D loss: 0.653625, acc.: 62.89%] [G loss: 0.993594]
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736 [D loss: 0.670755, acc.: 59.77%] [G loss: 0.855927]
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737 [D loss: 0.670654, acc.: 59.57%] [G loss: 0.830062]
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738 [D loss: 0.648516, acc.: 63.87%] [G loss: 0.908338]
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739 [D loss: 0.655739, acc.: 62.70%] [G loss: 0.907333]
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740 [D loss: 0.683723, acc.: 55.66%] [G loss: 0.825890]
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741 [D loss: 0.696015, acc.: 54.49%] [G loss: 0.823291]
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742 [D loss: 0.646230, acc.: 64.45%] [G loss: 0.964646]
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743 [D loss: 0.679769, acc.: 55.47%] [G loss: 0.892672]
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744 [D loss: 0.690577, acc.: 55.47%] [G loss: 0.821035]
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745 [D loss: 0.646285, acc.: 66.21%] [G loss: 0.898679]
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746 [D loss: 0.652687, acc.: 62.89%] [G loss: 0.874582]
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747 [D loss: 0.698122, acc.: 53.32%] [G loss: 0.797833]
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748 [D loss: 0.681175, acc.: 54.10%] [G loss: 0.795059]
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749 [D loss: 0.649746, acc.: 64.65%] [G loss: 0.885428]
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750 [D loss: 0.652038, acc.: 62.11%] [G loss: 0.900035]
1/1 [==============================] - 0s 19ms/step
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751 [D loss: 0.705458, acc.: 52.34%] [G loss: 0.826545]
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752 [D loss: 0.675244, acc.: 56.25%] [G loss: 0.826838]
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753 [D loss: 0.640760, acc.: 65.23%] [G loss: 0.907101]
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754 [D loss: 0.669996, acc.: 59.18%] [G loss: 0.859655]
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755 [D loss: 0.704098, acc.: 52.73%] [G loss: 0.768447]
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756 [D loss: 0.682350, acc.: 56.25%] [G loss: 0.827204]
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757 [D loss: 0.638660, acc.: 67.19%] [G loss: 0.927143]
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758 [D loss: 0.676065, acc.: 57.62%] [G loss: 0.819472]
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759 [D loss: 0.679330, acc.: 56.64%] [G loss: 0.831209]
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760 [D loss: 0.648833, acc.: 63.28%] [G loss: 0.841552]
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761 [D loss: 0.655907, acc.: 63.09%] [G loss: 0.830418]
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762 [D loss: 0.680015, acc.: 56.64%] [G loss: 0.770096]
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763 [D loss: 0.676919, acc.: 58.79%] [G loss: 0.843648]
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764 [D loss: 0.661956, acc.: 60.35%] [G loss: 0.872544]
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765 [D loss: 0.652603, acc.: 64.65%] [G loss: 0.838803]
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766 [D loss: 0.668266, acc.: 59.18%] [G loss: 0.862752]
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767 [D loss: 0.630361, acc.: 65.82%] [G loss: 0.894295]
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768 [D loss: 0.654696, acc.: 60.94%] [G loss: 0.892579]
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769 [D loss: 0.698951, acc.: 54.49%] [G loss: 0.803390]
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770 [D loss: 0.671054, acc.: 55.86%] [G loss: 0.839155]
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771 [D loss: 0.658068, acc.: 61.72%] [G loss: 0.948840]
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772 [D loss: 0.653313, acc.: 62.50%] [G loss: 0.903250]
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773 [D loss: 0.675770, acc.: 58.20%] [G loss: 0.837866]
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774 [D loss: 0.651993, acc.: 63.87%] [G loss: 0.906509]
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775 [D loss: 0.660469, acc.: 61.91%] [G loss: 0.856067]
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776 [D loss: 0.674297, acc.: 58.20%] [G loss: 0.796419]
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777 [D loss: 0.675551, acc.: 56.84%] [G loss: 0.852237]
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778 [D loss: 0.656654, acc.: 61.13%] [G loss: 1.017076]
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779 [D loss: 0.661264, acc.: 61.13%] [G loss: 0.891703]
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780 [D loss: 0.688036, acc.: 53.12%] [G loss: 0.838987]
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781 [D loss: 0.662189, acc.: 62.30%] [G loss: 0.905631]
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782 [D loss: 0.644513, acc.: 66.02%] [G loss: 0.919174]
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783 [D loss: 0.673939, acc.: 56.64%] [G loss: 0.793409]
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784 [D loss: 0.695852, acc.: 54.69%] [G loss: 0.800199]
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785 [D loss: 0.643849, acc.: 66.02%] [G loss: 1.046662]
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786 [D loss: 0.656616, acc.: 62.50%] [G loss: 1.005428]
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787 [D loss: 0.699667, acc.: 51.95%] [G loss: 0.817581]
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788 [D loss: 0.651347, acc.: 64.65%] [G loss: 0.894289]
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789 [D loss: 0.644556, acc.: 63.09%] [G loss: 1.002130]
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790 [D loss: 0.651265, acc.: 63.28%] [G loss: 0.821183]
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791 [D loss: 0.706434, acc.: 54.30%] [G loss: 0.750054]
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792 [D loss: 0.678889, acc.: 57.42%] [G loss: 0.939167]
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793 [D loss: 0.649170, acc.: 61.52%] [G loss: 0.993446]
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794 [D loss: 0.667353, acc.: 58.40%] [G loss: 0.872076]
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795 [D loss: 0.678546, acc.: 57.42%] [G loss: 0.850187]
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796 [D loss: 0.654064, acc.: 63.09%] [G loss: 0.956020]
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797 [D loss: 0.634489, acc.: 66.02%] [G loss: 0.936215]
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798 [D loss: 0.689417, acc.: 52.93%] [G loss: 0.725652]
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799 [D loss: 0.707175, acc.: 52.73%] [G loss: 0.806058]
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800 [D loss: 0.638433, acc.: 66.60%] [G loss: 1.068229]
1/1 [==============================] - 0s 17ms/step
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801 [D loss: 0.646639, acc.: 61.91%] [G loss: 0.935681]
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802 [D loss: 0.689177, acc.: 52.54%] [G loss: 0.804461]
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803 [D loss: 0.654042, acc.: 60.55%] [G loss: 0.875421]
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804 [D loss: 0.632763, acc.: 66.02%] [G loss: 0.952416]
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805 [D loss: 0.675487, acc.: 56.84%] [G loss: 0.826202]
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806 [D loss: 0.687379, acc.: 55.08%] [G loss: 0.763533]
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807 [D loss: 0.660674, acc.: 56.05%] [G loss: 0.869432]
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808 [D loss: 0.637681, acc.: 64.45%] [G loss: 1.017541]
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809 [D loss: 0.676754, acc.: 62.11%] [G loss: 0.863069]
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810 [D loss: 0.664868, acc.: 63.67%] [G loss: 0.870794]
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811 [D loss: 0.646293, acc.: 63.09%] [G loss: 0.934165]
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812 [D loss: 0.672210, acc.: 58.20%] [G loss: 0.841294]
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813 [D loss: 0.684073, acc.: 56.25%] [G loss: 0.773054]
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814 [D loss: 0.682797, acc.: 56.45%] [G loss: 0.845170]
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815 [D loss: 0.629507, acc.: 67.97%] [G loss: 0.945121]
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816 [D loss: 0.655542, acc.: 61.52%] [G loss: 0.855988]
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817 [D loss: 0.688806, acc.: 54.49%] [G loss: 0.832694]
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818 [D loss: 0.654215, acc.: 60.74%] [G loss: 0.922464]
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819 [D loss: 0.657329, acc.: 61.13%] [G loss: 0.862658]
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820 [D loss: 0.707296, acc.: 51.37%] [G loss: 0.782523]
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821 [D loss: 0.670110, acc.: 58.40%] [G loss: 0.855891]
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822 [D loss: 0.654952, acc.: 60.55%] [G loss: 1.009816]
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823 [D loss: 0.670108, acc.: 60.35%] [G loss: 0.918214]
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824 [D loss: 0.672548, acc.: 57.81%] [G loss: 0.835723]
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825 [D loss: 0.652687, acc.: 62.89%] [G loss: 0.906195]
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826 [D loss: 0.651350, acc.: 64.06%] [G loss: 0.914980]
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827 [D loss: 0.686575, acc.: 56.64%] [G loss: 0.821619]
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828 [D loss: 0.697308, acc.: 53.71%] [G loss: 0.796862]
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829 [D loss: 0.669427, acc.: 57.62%] [G loss: 0.962793]
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830 [D loss: 0.648933, acc.: 62.11%] [G loss: 0.991227]
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831 [D loss: 0.686202, acc.: 55.27%] [G loss: 0.843064]
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832 [D loss: 0.663901, acc.: 61.91%] [G loss: 0.864133]
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833 [D loss: 0.652849, acc.: 63.87%] [G loss: 0.952442]
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834 [D loss: 0.665558, acc.: 58.98%] [G loss: 0.864334]
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835 [D loss: 0.713606, acc.: 50.00%] [G loss: 0.768537]
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836 [D loss: 0.676138, acc.: 58.20%] [G loss: 0.860468]
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837 [D loss: 0.636110, acc.: 68.95%] [G loss: 1.036626]
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838 [D loss: 0.674517, acc.: 60.35%] [G loss: 0.841420]
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839 [D loss: 0.681751, acc.: 57.62%] [G loss: 0.829668]
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840 [D loss: 0.618962, acc.: 68.36%] [G loss: 0.945292]
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841 [D loss: 0.662104, acc.: 61.52%] [G loss: 0.882639]
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842 [D loss: 0.678896, acc.: 58.01%] [G loss: 0.805215]
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843 [D loss: 0.701933, acc.: 53.12%] [G loss: 0.784948]
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844 [D loss: 0.643746, acc.: 62.30%] [G loss: 0.959923]
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845 [D loss: 0.643333, acc.: 60.16%] [G loss: 1.001497]
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846 [D loss: 0.690793, acc.: 55.86%] [G loss: 0.830355]
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847 [D loss: 0.672647, acc.: 58.20%] [G loss: 0.863110]
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848 [D loss: 0.632384, acc.: 66.41%] [G loss: 0.913457]
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849 [D loss: 0.653167, acc.: 62.70%] [G loss: 0.857653]
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850 [D loss: 0.694546, acc.: 54.88%] [G loss: 0.790312]
1/1 [==============================] - 0s 19ms/step
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851 [D loss: 0.712873, acc.: 50.00%] [G loss: 0.816787]
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852 [D loss: 0.664731, acc.: 61.33%] [G loss: 0.988478]
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853 [D loss: 0.662216, acc.: 58.98%] [G loss: 0.941324]
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854 [D loss: 0.701917, acc.: 52.93%] [G loss: 0.797328]
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855 [D loss: 0.676088, acc.: 54.69%] [G loss: 0.853373]
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856 [D loss: 0.647715, acc.: 65.04%] [G loss: 0.884651]
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857 [D loss: 0.665801, acc.: 60.94%] [G loss: 0.810271]
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858 [D loss: 0.690706, acc.: 52.93%] [G loss: 0.773557]
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859 [D loss: 0.688313, acc.: 54.69%] [G loss: 0.829265]
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860 [D loss: 0.657705, acc.: 59.38%] [G loss: 0.981419]
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861 [D loss: 0.657446, acc.: 59.38%] [G loss: 0.904277]
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862 [D loss: 0.686908, acc.: 54.30%] [G loss: 0.818688]
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863 [D loss: 0.675178, acc.: 57.42%] [G loss: 0.831996]
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864 [D loss: 0.649772, acc.: 63.09%] [G loss: 0.912591]
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865 [D loss: 0.670977, acc.: 58.40%] [G loss: 0.846334]
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866 [D loss: 0.690360, acc.: 54.49%] [G loss: 0.794512]
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867 [D loss: 0.673123, acc.: 59.38%] [G loss: 0.799639]
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868 [D loss: 0.668132, acc.: 58.98%] [G loss: 0.936548]
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869 [D loss: 0.660957, acc.: 60.16%] [G loss: 0.925202]
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870 [D loss: 0.688612, acc.: 56.45%] [G loss: 0.828222]
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871 [D loss: 0.663324, acc.: 57.81%] [G loss: 0.861782]
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872 [D loss: 0.649093, acc.: 63.48%] [G loss: 0.908249]
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873 [D loss: 0.666682, acc.: 59.96%] [G loss: 0.861851]
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874 [D loss: 0.703017, acc.: 52.54%] [G loss: 0.775599]
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875 [D loss: 0.695239, acc.: 55.47%] [G loss: 0.831300]
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876 [D loss: 0.673183, acc.: 57.81%] [G loss: 0.938018]
8/8 [==============================] - 0s 5ms/step
877 [D loss: 0.656322, acc.: 61.52%] [G loss: 0.941312]
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878 [D loss: 0.681386, acc.: 52.93%] [G loss: 0.825765]
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879 [D loss: 0.686089, acc.: 53.32%] [G loss: 0.822284]
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880 [D loss: 0.649500, acc.: 63.67%] [G loss: 0.873663]
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881 [D loss: 0.640759, acc.: 65.82%] [G loss: 0.878602]
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882 [D loss: 0.708472, acc.: 54.49%] [G loss: 0.794885]
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883 [D loss: 0.680882, acc.: 55.08%] [G loss: 0.769391]
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884 [D loss: 0.664211, acc.: 58.59%] [G loss: 0.893999]
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885 [D loss: 0.646389, acc.: 65.62%] [G loss: 0.969081]
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886 [D loss: 0.699176, acc.: 51.56%] [G loss: 0.805166]
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887 [D loss: 0.675611, acc.: 56.05%] [G loss: 0.828017]
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888 [D loss: 0.634468, acc.: 68.16%] [G loss: 0.936247]
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889 [D loss: 0.660341, acc.: 62.70%] [G loss: 0.924540]
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890 [D loss: 0.662182, acc.: 62.30%] [G loss: 0.821056]
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891 [D loss: 0.717124, acc.: 48.83%] [G loss: 0.755057]
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892 [D loss: 0.709004, acc.: 51.76%] [G loss: 0.830474]
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893 [D loss: 0.651402, acc.: 61.52%] [G loss: 1.036796]
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894 [D loss: 0.666481, acc.: 58.59%] [G loss: 0.889935]
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895 [D loss: 0.693195, acc.: 54.30%] [G loss: 0.808499]
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896 [D loss: 0.662273, acc.: 60.35%] [G loss: 0.853225]
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897 [D loss: 0.637960, acc.: 65.23%] [G loss: 0.912446]
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898 [D loss: 0.658078, acc.: 61.52%] [G loss: 0.896476]
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899 [D loss: 0.695833, acc.: 54.69%] [G loss: 0.771649]
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900 [D loss: 0.711321, acc.: 50.00%] [G loss: 0.774358]
1/1 [==============================] - 0s 16ms/step
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901 [D loss: 0.637484, acc.: 65.23%] [G loss: 0.977867]
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902 [D loss: 0.646447, acc.: 63.87%] [G loss: 1.025573]
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903 [D loss: 0.682380, acc.: 61.33%] [G loss: 0.868605]
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904 [D loss: 0.673531, acc.: 57.23%] [G loss: 0.825498]
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905 [D loss: 0.656312, acc.: 63.09%] [G loss: 0.895019]
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906 [D loss: 0.667353, acc.: 63.87%] [G loss: 0.892767]
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907 [D loss: 0.688673, acc.: 56.05%] [G loss: 0.787774]
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908 [D loss: 0.694327, acc.: 54.88%] [G loss: 0.782785]
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909 [D loss: 0.658474, acc.: 60.74%] [G loss: 0.887663]
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910 [D loss: 0.638695, acc.: 65.04%] [G loss: 1.028647]
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911 [D loss: 0.688759, acc.: 54.69%] [G loss: 0.896690]
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912 [D loss: 0.671510, acc.: 56.45%] [G loss: 0.843488]
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913 [D loss: 0.652754, acc.: 63.87%] [G loss: 0.896498]
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914 [D loss: 0.635092, acc.: 67.97%] [G loss: 0.886215]
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915 [D loss: 0.664005, acc.: 59.96%] [G loss: 0.830030]
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916 [D loss: 0.684346, acc.: 57.03%] [G loss: 0.765923]
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917 [D loss: 0.692941, acc.: 56.05%] [G loss: 0.878611]
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918 [D loss: 0.659881, acc.: 60.35%] [G loss: 0.949587]
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919 [D loss: 0.682124, acc.: 56.84%] [G loss: 0.865650]
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920 [D loss: 0.678227, acc.: 60.55%] [G loss: 0.804785]
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921 [D loss: 0.664375, acc.: 59.77%] [G loss: 0.817509]
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922 [D loss: 0.646580, acc.: 66.21%] [G loss: 0.882574]
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923 [D loss: 0.662938, acc.: 62.70%] [G loss: 0.879053]
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924 [D loss: 0.698244, acc.: 52.54%] [G loss: 0.765172]
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925 [D loss: 0.700240, acc.: 51.56%] [G loss: 0.774887]
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926 [D loss: 0.655179, acc.: 62.50%] [G loss: 0.868550]
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927 [D loss: 0.640990, acc.: 65.62%] [G loss: 0.958113]
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928 [D loss: 0.677867, acc.: 60.55%] [G loss: 0.834308]
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929 [D loss: 0.688069, acc.: 54.30%] [G loss: 0.831171]
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930 [D loss: 0.657670, acc.: 61.52%] [G loss: 0.873401]
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931 [D loss: 0.656630, acc.: 62.11%] [G loss: 0.873410]
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932 [D loss: 0.680218, acc.: 56.84%] [G loss: 0.796555]
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933 [D loss: 0.679997, acc.: 54.88%] [G loss: 0.789900]
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934 [D loss: 0.679111, acc.: 57.62%] [G loss: 0.819577]
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935 [D loss: 0.675483, acc.: 61.13%] [G loss: 0.855687]
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936 [D loss: 0.649249, acc.: 63.09%] [G loss: 0.873167]
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937 [D loss: 0.671741, acc.: 56.64%] [G loss: 0.871358]
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938 [D loss: 0.660991, acc.: 62.11%] [G loss: 0.823014]
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939 [D loss: 0.662261, acc.: 59.77%] [G loss: 0.865624]
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940 [D loss: 0.663688, acc.: 61.52%] [G loss: 0.840409]
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941 [D loss: 0.683130, acc.: 56.45%] [G loss: 0.807871]
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942 [D loss: 0.679534, acc.: 55.47%] [G loss: 0.799529]
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943 [D loss: 0.697152, acc.: 50.78%] [G loss: 0.790486]
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944 [D loss: 0.647882, acc.: 63.67%] [G loss: 0.821279]
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945 [D loss: 0.668394, acc.: 57.81%] [G loss: 0.887173]
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946 [D loss: 0.679742, acc.: 56.64%] [G loss: 0.872194]
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947 [D loss: 0.684062, acc.: 56.05%] [G loss: 0.800520]
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948 [D loss: 0.689887, acc.: 53.12%] [G loss: 0.792951]
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949 [D loss: 0.676536, acc.: 57.81%] [G loss: 0.837345]
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950 [D loss: 0.659224, acc.: 60.94%] [G loss: 0.814761]
1/1 [==============================] - 0s 18ms/step
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951 [D loss: 0.670759, acc.: 58.59%] [G loss: 0.784681]
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952 [D loss: 0.687089, acc.: 53.32%] [G loss: 0.771350]
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953 [D loss: 0.692150, acc.: 54.69%] [G loss: 0.827772]
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954 [D loss: 0.660177, acc.: 59.57%] [G loss: 0.893806]
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955 [D loss: 0.685663, acc.: 56.64%] [G loss: 0.873201]
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956 [D loss: 0.670389, acc.: 55.86%] [G loss: 0.809022]
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957 [D loss: 0.684356, acc.: 54.49%] [G loss: 0.801814]
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958 [D loss: 0.685555, acc.: 53.52%] [G loss: 0.841830]
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959 [D loss: 0.674112, acc.: 57.03%] [G loss: 0.847323]
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960 [D loss: 0.669953, acc.: 58.40%] [G loss: 0.797770]
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961 [D loss: 0.689654, acc.: 55.66%] [G loss: 0.794933]
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962 [D loss: 0.675941, acc.: 57.81%] [G loss: 0.854823]
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963 [D loss: 0.666054, acc.: 59.57%] [G loss: 0.884252]
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964 [D loss: 0.685777, acc.: 53.12%] [G loss: 0.846587]
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965 [D loss: 0.686534, acc.: 56.45%] [G loss: 0.814946]
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966 [D loss: 0.673288, acc.: 56.84%] [G loss: 0.824392]
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967 [D loss: 0.675299, acc.: 58.20%] [G loss: 0.800367]
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968 [D loss: 0.672525, acc.: 57.62%] [G loss: 0.800299]
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969 [D loss: 0.684901, acc.: 54.10%] [G loss: 0.780440]
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970 [D loss: 0.697343, acc.: 51.76%] [G loss: 0.792983]
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971 [D loss: 0.671040, acc.: 59.77%] [G loss: 0.844168]
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972 [D loss: 0.656622, acc.: 61.13%] [G loss: 0.850606]
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973 [D loss: 0.665569, acc.: 58.01%] [G loss: 0.873282]
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974 [D loss: 0.681967, acc.: 57.03%] [G loss: 0.781789]
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975 [D loss: 0.660477, acc.: 59.96%] [G loss: 0.797716]
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976 [D loss: 0.664869, acc.: 57.81%] [G loss: 0.836267]
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977 [D loss: 0.687205, acc.: 58.40%] [G loss: 0.823572]
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978 [D loss: 0.682361, acc.: 55.08%] [G loss: 0.759556]
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979 [D loss: 0.705128, acc.: 50.20%] [G loss: 0.775684]
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980 [D loss: 0.677877, acc.: 58.79%] [G loss: 0.864018]
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981 [D loss: 0.657484, acc.: 59.77%] [G loss: 0.891578]
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982 [D loss: 0.687004, acc.: 54.10%] [G loss: 0.827972]
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983 [D loss: 0.689438, acc.: 55.66%] [G loss: 0.819515]
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984 [D loss: 0.667457, acc.: 61.13%] [G loss: 0.812017]
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985 [D loss: 0.681854, acc.: 57.03%] [G loss: 0.797749]
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986 [D loss: 0.659440, acc.: 61.72%] [G loss: 0.798806]
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987 [D loss: 0.679933, acc.: 57.42%] [G loss: 0.767588]
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988 [D loss: 0.686565, acc.: 54.49%] [G loss: 0.761296]
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989 [D loss: 0.677656, acc.: 57.81%] [G loss: 0.784187]
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990 [D loss: 0.675544, acc.: 58.01%] [G loss: 0.806722]
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991 [D loss: 0.663142, acc.: 62.70%] [G loss: 0.810899]
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992 [D loss: 0.672051, acc.: 53.91%] [G loss: 0.829185]
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993 [D loss: 0.687436, acc.: 54.69%] [G loss: 0.814331]
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994 [D loss: 0.658421, acc.: 58.59%] [G loss: 0.828419]
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995 [D loss: 0.652720, acc.: 62.50%] [G loss: 0.795024]
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996 [D loss: 0.676762, acc.: 57.03%] [G loss: 0.791182]
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997 [D loss: 0.691748, acc.: 51.56%] [G loss: 0.773559]
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998 [D loss: 0.683637, acc.: 57.23%] [G loss: 0.790182]
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999 [D loss: 0.662845, acc.: 62.30%] [G loss: 0.856853]
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1000 [D loss: 0.667910, acc.: 57.62%] [G loss: 0.841972]
1/1 [==============================] - 0s 16ms/step
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1001 [D loss: 0.671808, acc.: 57.62%] [G loss: 0.838326]
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1002 [D loss: 0.677615, acc.: 55.86%] [G loss: 0.796496]
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1003 [D loss: 0.671332, acc.: 57.23%] [G loss: 0.806669]
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1004 [D loss: 0.670648, acc.: 58.79%] [G loss: 0.798977]
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1005 [D loss: 0.662105, acc.: 60.16%] [G loss: 0.783124]
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1006 [D loss: 0.684638, acc.: 55.66%] [G loss: 0.769637]
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1007 [D loss: 0.671259, acc.: 56.84%] [G loss: 0.796801]
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1008 [D loss: 0.680766, acc.: 54.30%] [G loss: 0.847742]
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1009 [D loss: 0.668677, acc.: 56.84%] [G loss: 0.895642]
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1010 [D loss: 0.671041, acc.: 61.13%] [G loss: 0.854983]
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1011 [D loss: 0.693218, acc.: 54.10%] [G loss: 0.841908]
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1012 [D loss: 0.687997, acc.: 54.88%] [G loss: 0.828251]
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1013 [D loss: 0.672588, acc.: 58.20%] [G loss: 0.823883]
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1014 [D loss: 0.663679, acc.: 59.77%] [G loss: 0.787587]
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1015 [D loss: 0.681132, acc.: 54.30%] [G loss: 0.770397]
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1016 [D loss: 0.697427, acc.: 51.56%] [G loss: 0.769579]
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1017 [D loss: 0.671970, acc.: 58.79%] [G loss: 0.872848]
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1018 [D loss: 0.667820, acc.: 59.77%] [G loss: 0.867719]
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1019 [D loss: 0.670272, acc.: 57.42%] [G loss: 0.832965]
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1020 [D loss: 0.677799, acc.: 57.81%] [G loss: 0.803372]
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1021 [D loss: 0.686609, acc.: 57.81%] [G loss: 0.816563]
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1022 [D loss: 0.667229, acc.: 57.03%] [G loss: 0.816115]
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1023 [D loss: 0.657605, acc.: 60.55%] [G loss: 0.815835]
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1024 [D loss: 0.668702, acc.: 60.16%] [G loss: 0.808584]
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1025 [D loss: 0.707358, acc.: 51.37%] [G loss: 0.788594]
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1026 [D loss: 0.703455, acc.: 50.59%] [G loss: 0.869226]
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1027 [D loss: 0.661312, acc.: 61.72%] [G loss: 0.896678]
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1028 [D loss: 0.670196, acc.: 57.42%] [G loss: 0.851476]
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1029 [D loss: 0.693978, acc.: 54.69%] [G loss: 0.808933]
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1030 [D loss: 0.681462, acc.: 56.45%] [G loss: 0.801284]
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1031 [D loss: 0.657315, acc.: 61.72%] [G loss: 0.844443]
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1032 [D loss: 0.654798, acc.: 58.98%] [G loss: 0.857320]
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1033 [D loss: 0.678966, acc.: 56.64%] [G loss: 0.760053]
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1034 [D loss: 0.705940, acc.: 51.95%] [G loss: 0.746413]
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1035 [D loss: 0.685687, acc.: 54.69%] [G loss: 0.845368]
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1036 [D loss: 0.643383, acc.: 65.23%] [G loss: 0.948049]
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1037 [D loss: 0.677867, acc.: 57.42%] [G loss: 0.880487]
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1038 [D loss: 0.680227, acc.: 57.81%] [G loss: 0.805840]
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1039 [D loss: 0.681633, acc.: 55.86%] [G loss: 0.799897]
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1040 [D loss: 0.661555, acc.: 60.16%] [G loss: 0.832893]
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1041 [D loss: 0.665663, acc.: 61.33%] [G loss: 0.831770]
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1042 [D loss: 0.675150, acc.: 57.42%] [G loss: 0.771349]
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1043 [D loss: 0.703960, acc.: 54.30%] [G loss: 0.759344]
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1044 [D loss: 0.685841, acc.: 56.05%] [G loss: 0.856817]
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1045 [D loss: 0.651233, acc.: 64.84%] [G loss: 0.963609]
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1046 [D loss: 0.667909, acc.: 59.18%] [G loss: 0.912880]
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1047 [D loss: 0.685677, acc.: 55.08%] [G loss: 0.810323]
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1048 [D loss: 0.679849, acc.: 54.10%] [G loss: 0.802777]
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1049 [D loss: 0.655457, acc.: 59.18%] [G loss: 0.844258]
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1050 [D loss: 0.668046, acc.: 59.38%] [G loss: 0.835723]
1/1 [==============================] - 0s 16ms/step
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1051 [D loss: 0.667727, acc.: 57.23%] [G loss: 0.822781]
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1052 [D loss: 0.726878, acc.: 46.68%] [G loss: 0.775472]
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1053 [D loss: 0.689038, acc.: 55.66%] [G loss: 0.811035]
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1054 [D loss: 0.652106, acc.: 65.43%] [G loss: 0.923672]
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1055 [D loss: 0.651817, acc.: 60.74%] [G loss: 0.936561]
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1056 [D loss: 0.689899, acc.: 54.88%] [G loss: 0.824386]
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1057 [D loss: 0.692681, acc.: 55.66%] [G loss: 0.786143]
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1058 [D loss: 0.670691, acc.: 57.81%] [G loss: 0.850654]
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1059 [D loss: 0.651757, acc.: 61.52%] [G loss: 0.860261]
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1060 [D loss: 0.668061, acc.: 60.35%] [G loss: 0.839736]
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1061 [D loss: 0.700697, acc.: 51.76%] [G loss: 0.756173]
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1062 [D loss: 0.696347, acc.: 52.15%] [G loss: 0.782038]
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1063 [D loss: 0.673615, acc.: 56.64%] [G loss: 0.916505]
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1064 [D loss: 0.650630, acc.: 63.48%] [G loss: 0.971337]
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1065 [D loss: 0.679341, acc.: 58.98%] [G loss: 0.856192]
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1066 [D loss: 0.689434, acc.: 52.54%] [G loss: 0.808699]
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1067 [D loss: 0.675404, acc.: 54.88%] [G loss: 0.825856]
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1068 [D loss: 0.648576, acc.: 62.70%] [G loss: 0.848432]
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1069 [D loss: 0.652651, acc.: 60.55%] [G loss: 0.815357]
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1070 [D loss: 0.700216, acc.: 48.05%] [G loss: 0.747949]
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1071 [D loss: 0.691306, acc.: 54.88%] [G loss: 0.747124]
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1072 [D loss: 0.692114, acc.: 54.30%] [G loss: 0.875650]
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1073 [D loss: 0.656325, acc.: 64.26%] [G loss: 0.963981]
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1074 [D loss: 0.686991, acc.: 55.47%] [G loss: 0.885936]
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1075 [D loss: 0.684617, acc.: 56.64%] [G loss: 0.817589]
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1076 [D loss: 0.688978, acc.: 54.88%] [G loss: 0.784544]
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1077 [D loss: 0.662337, acc.: 59.57%] [G loss: 0.823656]
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1078 [D loss: 0.635887, acc.: 66.02%] [G loss: 0.859141]
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1079 [D loss: 0.654740, acc.: 60.35%] [G loss: 0.820903]
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1080 [D loss: 0.693757, acc.: 51.95%] [G loss: 0.746448]
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1081 [D loss: 0.706152, acc.: 51.37%] [G loss: 0.805140]
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1082 [D loss: 0.662620, acc.: 61.91%] [G loss: 0.895446]
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1083 [D loss: 0.665915, acc.: 56.84%] [G loss: 0.951979]
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1084 [D loss: 0.670263, acc.: 60.94%] [G loss: 0.871101]
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1085 [D loss: 0.685595, acc.: 55.86%] [G loss: 0.819612]
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1086 [D loss: 0.669747, acc.: 60.74%] [G loss: 0.828530]
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1087 [D loss: 0.656063, acc.: 62.50%] [G loss: 0.830609]
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1088 [D loss: 0.649514, acc.: 61.91%] [G loss: 0.805674]
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1089 [D loss: 0.693502, acc.: 54.49%] [G loss: 0.781139]
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1090 [D loss: 0.708984, acc.: 51.56%] [G loss: 0.739410]
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1091 [D loss: 0.680180, acc.: 54.30%] [G loss: 0.804507]
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1092 [D loss: 0.671172, acc.: 55.86%] [G loss: 0.871816]
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1093 [D loss: 0.659640, acc.: 60.94%] [G loss: 0.946767]
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1094 [D loss: 0.704359, acc.: 50.20%] [G loss: 0.817452]
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1095 [D loss: 0.685615, acc.: 56.45%] [G loss: 0.786578]
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1096 [D loss: 0.666209, acc.: 61.33%] [G loss: 0.820704]
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1097 [D loss: 0.661335, acc.: 61.52%] [G loss: 0.811158]
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1098 [D loss: 0.680286, acc.: 57.42%] [G loss: 0.812364]
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1099 [D loss: 0.668026, acc.: 59.57%] [G loss: 0.762756]
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1100 [D loss: 0.685698, acc.: 55.86%] [G loss: 0.755549]
1/1 [==============================] - 0s 17ms/step
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1101 [D loss: 0.701622, acc.: 53.52%] [G loss: 0.794999]
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1102 [D loss: 0.679587, acc.: 56.25%] [G loss: 0.881307]
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1103 [D loss: 0.667568, acc.: 61.52%] [G loss: 0.890040]
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1104 [D loss: 0.672015, acc.: 58.79%] [G loss: 0.838955]
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1105 [D loss: 0.674489, acc.: 58.59%] [G loss: 0.790625]
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1106 [D loss: 0.685575, acc.: 54.49%] [G loss: 0.803061]
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1107 [D loss: 0.670904, acc.: 58.20%] [G loss: 0.820883]
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1108 [D loss: 0.661137, acc.: 61.91%] [G loss: 0.816408]
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1109 [D loss: 0.670131, acc.: 58.59%] [G loss: 0.815245]
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1110 [D loss: 0.683869, acc.: 55.86%] [G loss: 0.801675]
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1111 [D loss: 0.688112, acc.: 54.30%] [G loss: 0.815616]
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1112 [D loss: 0.667729, acc.: 62.70%] [G loss: 0.890638]
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1113 [D loss: 0.657755, acc.: 61.91%] [G loss: 0.868357]
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1114 [D loss: 0.697499, acc.: 54.49%] [G loss: 0.837087]
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1115 [D loss: 0.695874, acc.: 54.49%] [G loss: 0.820891]
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1116 [D loss: 0.672938, acc.: 59.96%] [G loss: 0.798176]
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1117 [D loss: 0.678020, acc.: 59.96%] [G loss: 0.814059]
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1118 [D loss: 0.668005, acc.: 59.77%] [G loss: 0.806925]
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1119 [D loss: 0.675879, acc.: 57.03%] [G loss: 0.779346]
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1120 [D loss: 0.663527, acc.: 58.98%] [G loss: 0.771884]
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1121 [D loss: 0.698607, acc.: 49.22%] [G loss: 0.784387]
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1122 [D loss: 0.662841, acc.: 58.40%] [G loss: 0.862447]
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1123 [D loss: 0.664952, acc.: 56.64%] [G loss: 0.864590]
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1124 [D loss: 0.680637, acc.: 56.64%] [G loss: 0.859192]
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1125 [D loss: 0.682786, acc.: 58.01%] [G loss: 0.811725]
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1126 [D loss: 0.667854, acc.: 58.40%] [G loss: 0.800187]
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1127 [D loss: 0.668533, acc.: 59.77%] [G loss: 0.806693]
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1128 [D loss: 0.669013, acc.: 60.55%] [G loss: 0.806917]
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1129 [D loss: 0.675957, acc.: 55.66%] [G loss: 0.790005]
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1130 [D loss: 0.683645, acc.: 54.10%] [G loss: 0.750729]
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1131 [D loss: 0.691886, acc.: 56.45%] [G loss: 0.753340]
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1132 [D loss: 0.672356, acc.: 60.16%] [G loss: 0.843738]
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1133 [D loss: 0.669680, acc.: 57.42%] [G loss: 0.836288]
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1134 [D loss: 0.672954, acc.: 58.98%] [G loss: 0.833200]
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1135 [D loss: 0.676183, acc.: 57.62%] [G loss: 0.806209]
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1136 [D loss: 0.679161, acc.: 56.25%] [G loss: 0.804871]
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1137 [D loss: 0.667370, acc.: 59.96%] [G loss: 0.816515]
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1138 [D loss: 0.658496, acc.: 62.89%] [G loss: 0.805543]
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1139 [D loss: 0.678003, acc.: 52.93%] [G loss: 0.791951]
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1140 [D loss: 0.676981, acc.: 54.69%] [G loss: 0.753340]
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1141 [D loss: 0.696127, acc.: 51.95%] [G loss: 0.791825]
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1142 [D loss: 0.672576, acc.: 59.57%] [G loss: 0.876655]
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1143 [D loss: 0.654406, acc.: 59.38%] [G loss: 0.886271]
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1144 [D loss: 0.674179, acc.: 56.84%] [G loss: 0.848385]
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1145 [D loss: 0.690453, acc.: 52.15%] [G loss: 0.800184]
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1146 [D loss: 0.669715, acc.: 57.23%] [G loss: 0.788446]
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1147 [D loss: 0.674475, acc.: 57.23%] [G loss: 0.786564]
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1148 [D loss: 0.668956, acc.: 58.20%] [G loss: 0.778415]
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1149 [D loss: 0.670429, acc.: 56.05%] [G loss: 0.765305]
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1150 [D loss: 0.683905, acc.: 52.15%] [G loss: 0.738227]
1/1 [==============================] - 0s 19ms/step
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1151 [D loss: 0.695390, acc.: 50.78%] [G loss: 0.741053]
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1152 [D loss: 0.676457, acc.: 57.23%] [G loss: 0.812895]
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1153 [D loss: 0.685742, acc.: 56.25%] [G loss: 0.867055]
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1154 [D loss: 0.664109, acc.: 61.33%] [G loss: 0.863891]
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1155 [D loss: 0.687650, acc.: 53.32%] [G loss: 0.831813]
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1156 [D loss: 0.687741, acc.: 53.12%] [G loss: 0.774265]
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1157 [D loss: 0.667804, acc.: 58.59%] [G loss: 0.789325]
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1158 [D loss: 0.664084, acc.: 57.62%] [G loss: 0.788521]
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1159 [D loss: 0.678360, acc.: 57.03%] [G loss: 0.794664]
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1160 [D loss: 0.683992, acc.: 58.20%] [G loss: 0.750176]
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1161 [D loss: 0.684587, acc.: 54.88%] [G loss: 0.766477]
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1162 [D loss: 0.684139, acc.: 55.27%] [G loss: 0.795179]
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1163 [D loss: 0.665407, acc.: 61.52%] [G loss: 0.854616]
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1164 [D loss: 0.665989, acc.: 60.16%] [G loss: 0.849363]
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1165 [D loss: 0.675618, acc.: 53.71%] [G loss: 0.838838]
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1166 [D loss: 0.681248, acc.: 55.27%] [G loss: 0.790811]
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1167 [D loss: 0.669462, acc.: 58.79%] [G loss: 0.794398]
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1168 [D loss: 0.665818, acc.: 62.89%] [G loss: 0.813692]
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1169 [D loss: 0.665614, acc.: 59.57%] [G loss: 0.819881]
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1170 [D loss: 0.686310, acc.: 55.08%] [G loss: 0.788369]
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1171 [D loss: 0.679853, acc.: 57.42%] [G loss: 0.769452]
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1172 [D loss: 0.695346, acc.: 52.34%] [G loss: 0.794651]
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1173 [D loss: 0.650523, acc.: 65.04%] [G loss: 0.871710]
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1174 [D loss: 0.670499, acc.: 55.86%] [G loss: 0.872508]
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1175 [D loss: 0.675223, acc.: 58.98%] [G loss: 0.840525]
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1176 [D loss: 0.693716, acc.: 50.59%] [G loss: 0.819417]
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1177 [D loss: 0.676232, acc.: 55.47%] [G loss: 0.785999]
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1178 [D loss: 0.662566, acc.: 62.89%] [G loss: 0.811430]
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1179 [D loss: 0.654933, acc.: 63.87%] [G loss: 0.796239]
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1180 [D loss: 0.668299, acc.: 57.81%] [G loss: 0.769845]
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1181 [D loss: 0.683720, acc.: 55.66%] [G loss: 0.747806]
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1182 [D loss: 0.695392, acc.: 53.71%] [G loss: 0.762105]
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1183 [D loss: 0.685960, acc.: 52.93%] [G loss: 0.815830]
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1184 [D loss: 0.670677, acc.: 56.05%] [G loss: 0.866943]
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1185 [D loss: 0.678748, acc.: 57.03%] [G loss: 0.861346]
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1186 [D loss: 0.685440, acc.: 55.66%] [G loss: 0.820916]
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1187 [D loss: 0.683551, acc.: 56.64%] [G loss: 0.789108]
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1188 [D loss: 0.657834, acc.: 61.72%] [G loss: 0.820325]
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1189 [D loss: 0.656295, acc.: 62.89%] [G loss: 0.823790]
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1190 [D loss: 0.675663, acc.: 58.01%] [G loss: 0.786217]
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1191 [D loss: 0.693833, acc.: 52.54%] [G loss: 0.749862]
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1192 [D loss: 0.701296, acc.: 50.39%] [G loss: 0.766489]
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1193 [D loss: 0.691059, acc.: 56.05%] [G loss: 0.825710]
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1194 [D loss: 0.666164, acc.: 58.79%] [G loss: 0.883360]
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1195 [D loss: 0.671308, acc.: 56.45%] [G loss: 0.870037]
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1196 [D loss: 0.690328, acc.: 54.30%] [G loss: 0.779410]
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1197 [D loss: 0.693778, acc.: 52.73%] [G loss: 0.781384]
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1198 [D loss: 0.659538, acc.: 61.13%] [G loss: 0.786427]
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1199 [D loss: 0.652572, acc.: 62.50%] [G loss: 0.813830]
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1200 [D loss: 0.671811, acc.: 57.23%] [G loss: 0.793468]
1/1 [==============================] - 0s 19ms/step
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1201 [D loss: 0.681708, acc.: 54.69%] [G loss: 0.755748]
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1202 [D loss: 0.683968, acc.: 56.05%] [G loss: 0.773455]
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1203 [D loss: 0.702969, acc.: 51.17%] [G loss: 0.788083]
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1204 [D loss: 0.671453, acc.: 59.96%] [G loss: 0.854439]
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1205 [D loss: 0.668088, acc.: 60.16%] [G loss: 0.885089]
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1206 [D loss: 0.671137, acc.: 60.16%] [G loss: 0.829469]
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1207 [D loss: 0.681204, acc.: 57.23%] [G loss: 0.784824]
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1208 [D loss: 0.673031, acc.: 57.23%] [G loss: 0.785322]
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1209 [D loss: 0.667653, acc.: 58.79%] [G loss: 0.807473]
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1210 [D loss: 0.652885, acc.: 62.70%] [G loss: 0.781343]
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1211 [D loss: 0.684570, acc.: 55.86%] [G loss: 0.776751]
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1212 [D loss: 0.698194, acc.: 51.37%] [G loss: 0.757944]
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1213 [D loss: 0.685915, acc.: 53.12%] [G loss: 0.797660]
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1214 [D loss: 0.669495, acc.: 58.59%] [G loss: 0.867844]
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1215 [D loss: 0.666199, acc.: 59.77%] [G loss: 0.867819]
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1216 [D loss: 0.680962, acc.: 58.20%] [G loss: 0.847382]
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1217 [D loss: 0.685350, acc.: 54.10%] [G loss: 0.809594]
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1218 [D loss: 0.687043, acc.: 56.64%] [G loss: 0.780318]
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1219 [D loss: 0.668442, acc.: 57.81%] [G loss: 0.792005]
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1220 [D loss: 0.667309, acc.: 58.20%] [G loss: 0.818789]
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1221 [D loss: 0.671135, acc.: 59.57%] [G loss: 0.806793]
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1222 [D loss: 0.690914, acc.: 52.34%] [G loss: 0.787278]
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1223 [D loss: 0.681782, acc.: 57.23%] [G loss: 0.726788]
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1224 [D loss: 0.682928, acc.: 55.27%] [G loss: 0.760216]
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1225 [D loss: 0.673708, acc.: 55.66%] [G loss: 0.810252]
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1226 [D loss: 0.653946, acc.: 61.33%] [G loss: 0.858215]
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1227 [D loss: 0.673634, acc.: 56.05%] [G loss: 0.858300]
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1228 [D loss: 0.698754, acc.: 53.12%] [G loss: 0.797462]
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1229 [D loss: 0.699041, acc.: 52.54%] [G loss: 0.799348]
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1230 [D loss: 0.662595, acc.: 62.11%] [G loss: 0.799540]
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1231 [D loss: 0.672620, acc.: 57.62%] [G loss: 0.806975]
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1232 [D loss: 0.663465, acc.: 58.79%] [G loss: 0.794437]
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1233 [D loss: 0.679920, acc.: 52.34%] [G loss: 0.780872]
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1234 [D loss: 0.684780, acc.: 56.25%] [G loss: 0.791366]
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1235 [D loss: 0.688200, acc.: 54.10%] [G loss: 0.813246]
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1236 [D loss: 0.665853, acc.: 60.16%] [G loss: 0.868273]
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1237 [D loss: 0.681805, acc.: 53.32%] [G loss: 0.841487]
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1238 [D loss: 0.675553, acc.: 53.91%] [G loss: 0.843876]
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1239 [D loss: 0.693998, acc.: 50.98%] [G loss: 0.791229]
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1240 [D loss: 0.682612, acc.: 55.27%] [G loss: 0.796862]
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1241 [D loss: 0.670862, acc.: 60.16%] [G loss: 0.792055]
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1242 [D loss: 0.663639, acc.: 59.77%] [G loss: 0.778535]
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1243 [D loss: 0.671872, acc.: 56.45%] [G loss: 0.761396]
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1244 [D loss: 0.679515, acc.: 56.05%] [G loss: 0.751722]
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1245 [D loss: 0.708705, acc.: 48.63%] [G loss: 0.750162]
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1246 [D loss: 0.685984, acc.: 55.66%] [G loss: 0.779661]
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1247 [D loss: 0.666377, acc.: 62.50%] [G loss: 0.835889]
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1248 [D loss: 0.685943, acc.: 52.34%] [G loss: 0.857686]
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1249 [D loss: 0.677794, acc.: 57.62%] [G loss: 0.803540]
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1250 [D loss: 0.677857, acc.: 56.05%] [G loss: 0.779982]
1/1 [==============================] - 0s 17ms/step
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1251 [D loss: 0.676664, acc.: 54.88%] [G loss: 0.775979]
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1252 [D loss: 0.687179, acc.: 55.47%] [G loss: 0.784261]
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1253 [D loss: 0.678552, acc.: 57.42%] [G loss: 0.776542]
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1254 [D loss: 0.671671, acc.: 57.03%] [G loss: 0.757152]
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1255 [D loss: 0.686978, acc.: 54.88%] [G loss: 0.759766]
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1256 [D loss: 0.684467, acc.: 53.71%] [G loss: 0.782502]
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1257 [D loss: 0.676669, acc.: 56.45%] [G loss: 0.823629]
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1258 [D loss: 0.668378, acc.: 60.55%] [G loss: 0.859725]
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1259 [D loss: 0.665044, acc.: 57.03%] [G loss: 0.833481]
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1260 [D loss: 0.685048, acc.: 54.30%] [G loss: 0.824901]
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1261 [D loss: 0.679026, acc.: 56.25%] [G loss: 0.800358]
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1262 [D loss: 0.671671, acc.: 59.77%] [G loss: 0.805440]
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1263 [D loss: 0.666045, acc.: 57.42%] [G loss: 0.820221]
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1264 [D loss: 0.666344, acc.: 60.35%] [G loss: 0.773851]
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1265 [D loss: 0.668426, acc.: 60.74%] [G loss: 0.784546]
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1266 [D loss: 0.693379, acc.: 53.71%] [G loss: 0.770976]
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1267 [D loss: 0.696370, acc.: 52.73%] [G loss: 0.761735]
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1268 [D loss: 0.679928, acc.: 54.30%] [G loss: 0.801260]
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1269 [D loss: 0.685990, acc.: 54.30%] [G loss: 0.826321]
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1270 [D loss: 0.679675, acc.: 55.27%] [G loss: 0.824915]
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1271 [D loss: 0.684253, acc.: 57.42%] [G loss: 0.781509]
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1272 [D loss: 0.676559, acc.: 57.03%] [G loss: 0.768787]
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1273 [D loss: 0.686070, acc.: 56.84%] [G loss: 0.770843]
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1274 [D loss: 0.683378, acc.: 54.88%] [G loss: 0.758756]
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1275 [D loss: 0.688075, acc.: 53.32%] [G loss: 0.766883]
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1276 [D loss: 0.675593, acc.: 55.08%] [G loss: 0.757671]
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1277 [D loss: 0.676318, acc.: 55.47%] [G loss: 0.759807]
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1278 [D loss: 0.703174, acc.: 51.37%] [G loss: 0.771213]
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1279 [D loss: 0.676192, acc.: 55.47%] [G loss: 0.781760]
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1280 [D loss: 0.673866, acc.: 59.18%] [G loss: 0.803336]
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1281 [D loss: 0.676206, acc.: 54.10%] [G loss: 0.799996]
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1282 [D loss: 0.693940, acc.: 51.76%] [G loss: 0.795800]
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1283 [D loss: 0.694362, acc.: 53.91%] [G loss: 0.778868]
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1284 [D loss: 0.678385, acc.: 55.08%] [G loss: 0.775714]
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1285 [D loss: 0.676740, acc.: 57.62%] [G loss: 0.753675]
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1286 [D loss: 0.670182, acc.: 56.05%] [G loss: 0.783937]
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1287 [D loss: 0.669348, acc.: 57.81%] [G loss: 0.760951]
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1288 [D loss: 0.686176, acc.: 54.49%] [G loss: 0.762074]
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1289 [D loss: 0.677764, acc.: 54.69%] [G loss: 0.786278]
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1290 [D loss: 0.674971, acc.: 56.45%] [G loss: 0.797403]
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1291 [D loss: 0.680996, acc.: 54.49%] [G loss: 0.797911]
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1292 [D loss: 0.669331, acc.: 56.64%] [G loss: 0.832847]
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1293 [D loss: 0.687227, acc.: 56.05%] [G loss: 0.823989]
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1294 [D loss: 0.673462, acc.: 59.38%] [G loss: 0.812764]
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1295 [D loss: 0.681091, acc.: 57.81%] [G loss: 0.793912]
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1296 [D loss: 0.675237, acc.: 56.05%] [G loss: 0.806199]
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1297 [D loss: 0.678899, acc.: 55.47%] [G loss: 0.821866]
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1298 [D loss: 0.680097, acc.: 53.12%] [G loss: 0.787648]
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1299 [D loss: 0.687764, acc.: 55.86%] [G loss: 0.776435]
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1300 [D loss: 0.682164, acc.: 54.88%] [G loss: 0.777861]
1/1 [==============================] - 0s 16ms/step
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1301 [D loss: 0.687327, acc.: 54.88%] [G loss: 0.771063]
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1302 [D loss: 0.677369, acc.: 58.98%] [G loss: 0.792677]
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1303 [D loss: 0.674039, acc.: 59.38%] [G loss: 0.790107]
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1304 [D loss: 0.683952, acc.: 53.91%] [G loss: 0.808440]
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1305 [D loss: 0.663482, acc.: 60.55%] [G loss: 0.786077]
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1306 [D loss: 0.672075, acc.: 60.35%] [G loss: 0.798438]
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1307 [D loss: 0.680582, acc.: 55.27%] [G loss: 0.787527]
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1308 [D loss: 0.669207, acc.: 61.52%] [G loss: 0.783029]
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1309 [D loss: 0.683769, acc.: 54.88%] [G loss: 0.759672]
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1310 [D loss: 0.679127, acc.: 57.42%] [G loss: 0.777560]
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1311 [D loss: 0.695337, acc.: 50.39%] [G loss: 0.756723]
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1312 [D loss: 0.695750, acc.: 54.88%] [G loss: 0.774486]
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1313 [D loss: 0.678110, acc.: 54.69%] [G loss: 0.802521]
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1314 [D loss: 0.678957, acc.: 56.45%] [G loss: 0.804335]
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1315 [D loss: 0.673595, acc.: 61.33%] [G loss: 0.791832]
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1316 [D loss: 0.690033, acc.: 54.69%] [G loss: 0.785171]
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1317 [D loss: 0.663760, acc.: 58.98%] [G loss: 0.779373]
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1318 [D loss: 0.678903, acc.: 53.91%] [G loss: 0.781180]
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1319 [D loss: 0.663540, acc.: 63.28%] [G loss: 0.781043]
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1320 [D loss: 0.672339, acc.: 56.45%] [G loss: 0.754180]
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1321 [D loss: 0.681574, acc.: 54.49%] [G loss: 0.754523]
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1322 [D loss: 0.676201, acc.: 58.40%] [G loss: 0.772694]
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1323 [D loss: 0.682049, acc.: 54.69%] [G loss: 0.790692]
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1324 [D loss: 0.669665, acc.: 60.74%] [G loss: 0.802401]
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1325 [D loss: 0.676028, acc.: 58.20%] [G loss: 0.793811]
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1326 [D loss: 0.683208, acc.: 54.30%] [G loss: 0.786120]
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1327 [D loss: 0.676350, acc.: 57.62%] [G loss: 0.773082]
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1328 [D loss: 0.683248, acc.: 56.45%] [G loss: 0.796680]
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1329 [D loss: 0.670867, acc.: 60.74%] [G loss: 0.801187]
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1330 [D loss: 0.673322, acc.: 56.25%] [G loss: 0.796894]
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1331 [D loss: 0.677588, acc.: 56.05%] [G loss: 0.754893]
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1332 [D loss: 0.679956, acc.: 57.81%] [G loss: 0.755733]
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1333 [D loss: 0.673988, acc.: 57.03%] [G loss: 0.755406]
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1334 [D loss: 0.679172, acc.: 57.03%] [G loss: 0.773290]
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1335 [D loss: 0.682556, acc.: 56.05%] [G loss: 0.793544]
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1336 [D loss: 0.674317, acc.: 58.40%] [G loss: 0.806797]
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1337 [D loss: 0.667093, acc.: 60.16%] [G loss: 0.813294]
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1338 [D loss: 0.671411, acc.: 60.55%] [G loss: 0.802002]
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1339 [D loss: 0.685489, acc.: 54.88%] [G loss: 0.774930]
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1340 [D loss: 0.668833, acc.: 61.91%] [G loss: 0.777907]
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1341 [D loss: 0.674184, acc.: 58.79%] [G loss: 0.775737]
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1342 [D loss: 0.663649, acc.: 59.38%] [G loss: 0.766591]
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1343 [D loss: 0.698983, acc.: 52.54%] [G loss: 0.750911]
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1344 [D loss: 0.681526, acc.: 56.05%] [G loss: 0.756357]
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1345 [D loss: 0.681913, acc.: 55.86%] [G loss: 0.809615]
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1346 [D loss: 0.680681, acc.: 55.47%] [G loss: 0.823999]
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1347 [D loss: 0.682962, acc.: 53.12%] [G loss: 0.837196]
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1348 [D loss: 0.685021, acc.: 55.08%] [G loss: 0.844093]
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1349 [D loss: 0.702347, acc.: 50.98%] [G loss: 0.790894]
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1350 [D loss: 0.697852, acc.: 53.71%] [G loss: 0.778771]
1/1 [==============================] - 0s 17ms/step
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1351 [D loss: 0.680109, acc.: 55.47%] [G loss: 0.776014]
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1352 [D loss: 0.674979, acc.: 61.72%] [G loss: 0.781322]
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1353 [D loss: 0.670962, acc.: 60.55%] [G loss: 0.760988]
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1354 [D loss: 0.683352, acc.: 55.27%] [G loss: 0.756707]
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1355 [D loss: 0.692440, acc.: 52.73%] [G loss: 0.766140]
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1356 [D loss: 0.680094, acc.: 54.69%] [G loss: 0.762834]
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1357 [D loss: 0.683281, acc.: 54.10%] [G loss: 0.788425]
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1358 [D loss: 0.673118, acc.: 60.35%] [G loss: 0.804083]
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1359 [D loss: 0.669734, acc.: 60.35%] [G loss: 0.800289]
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1360 [D loss: 0.679070, acc.: 57.23%] [G loss: 0.798466]
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1361 [D loss: 0.677857, acc.: 57.42%] [G loss: 0.784522]
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1362 [D loss: 0.677745, acc.: 58.20%] [G loss: 0.786251]
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1363 [D loss: 0.681930, acc.: 55.86%] [G loss: 0.791191]
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1364 [D loss: 0.671626, acc.: 55.66%] [G loss: 0.775556]
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1365 [D loss: 0.679010, acc.: 54.30%] [G loss: 0.771628]
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1366 [D loss: 0.685952, acc.: 55.08%] [G loss: 0.768963]
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1367 [D loss: 0.690711, acc.: 53.12%] [G loss: 0.749607]
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1368 [D loss: 0.684710, acc.: 55.08%] [G loss: 0.771933]
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1369 [D loss: 0.690425, acc.: 54.10%] [G loss: 0.825329]
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1370 [D loss: 0.668277, acc.: 60.55%] [G loss: 0.827561]
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1371 [D loss: 0.674368, acc.: 60.94%] [G loss: 0.839080]
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1372 [D loss: 0.686418, acc.: 55.08%] [G loss: 0.829866]
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1373 [D loss: 0.697484, acc.: 53.12%] [G loss: 0.779316]
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1374 [D loss: 0.682837, acc.: 56.64%] [G loss: 0.790058]
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1375 [D loss: 0.670506, acc.: 59.77%] [G loss: 0.773785]
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1376 [D loss: 0.685079, acc.: 54.69%] [G loss: 0.762818]
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1377 [D loss: 0.668556, acc.: 59.18%] [G loss: 0.763598]
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1378 [D loss: 0.685958, acc.: 55.66%] [G loss: 0.742423]
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1379 [D loss: 0.682479, acc.: 55.86%] [G loss: 0.770706]
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1380 [D loss: 0.678249, acc.: 56.05%] [G loss: 0.824596]
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1381 [D loss: 0.652892, acc.: 62.11%] [G loss: 0.872937]
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1382 [D loss: 0.663035, acc.: 60.55%] [G loss: 0.899320]
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1383 [D loss: 0.689041, acc.: 52.34%] [G loss: 0.836786]
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1384 [D loss: 0.679848, acc.: 57.42%] [G loss: 0.799259]
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1385 [D loss: 0.682536, acc.: 53.71%] [G loss: 0.772039]
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1386 [D loss: 0.675577, acc.: 59.57%] [G loss: 0.790733]
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1387 [D loss: 0.668578, acc.: 57.81%] [G loss: 0.778940]
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1388 [D loss: 0.680995, acc.: 52.54%] [G loss: 0.761057]
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1389 [D loss: 0.693135, acc.: 51.17%] [G loss: 0.741788]
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1390 [D loss: 0.717287, acc.: 46.09%] [G loss: 0.730927]
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1391 [D loss: 0.707392, acc.: 47.85%] [G loss: 0.777639]
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1392 [D loss: 0.669104, acc.: 57.81%] [G loss: 0.863773]
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1393 [D loss: 0.662111, acc.: 58.40%] [G loss: 0.915875]
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1394 [D loss: 0.679491, acc.: 54.30%] [G loss: 0.886175]
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1395 [D loss: 0.674875, acc.: 57.62%] [G loss: 0.825247]
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1396 [D loss: 0.689785, acc.: 58.01%] [G loss: 0.784321]
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1397 [D loss: 0.675151, acc.: 62.50%] [G loss: 0.778856]
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1398 [D loss: 0.658828, acc.: 62.11%] [G loss: 0.784104]
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1399 [D loss: 0.645748, acc.: 63.87%] [G loss: 0.804961]
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1400 [D loss: 0.666048, acc.: 60.74%] [G loss: 0.753932]
1/1 [==============================] - 0s 17ms/step
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1401 [D loss: 0.692968, acc.: 52.15%] [G loss: 0.731149]
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1402 [D loss: 0.708158, acc.: 50.39%] [G loss: 0.738069]
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1403 [D loss: 0.712545, acc.: 48.05%] [G loss: 0.793363]
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1404 [D loss: 0.655267, acc.: 62.30%] [G loss: 0.857938]
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1405 [D loss: 0.663251, acc.: 59.38%] [G loss: 0.896981]
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1406 [D loss: 0.667984, acc.: 58.40%] [G loss: 0.857509]
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1407 [D loss: 0.695581, acc.: 53.52%] [G loss: 0.779521]
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1408 [D loss: 0.696024, acc.: 51.76%] [G loss: 0.787671]
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1409 [D loss: 0.689762, acc.: 50.78%] [G loss: 0.765957]
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1410 [D loss: 0.669232, acc.: 58.79%] [G loss: 0.783668]
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1411 [D loss: 0.664892, acc.: 60.74%] [G loss: 0.782887]
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1412 [D loss: 0.680331, acc.: 55.08%] [G loss: 0.760590]
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1413 [D loss: 0.673164, acc.: 56.84%] [G loss: 0.734270]
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1414 [D loss: 0.698933, acc.: 50.00%] [G loss: 0.768102]
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1415 [D loss: 0.687242, acc.: 56.45%] [G loss: 0.768997]
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1416 [D loss: 0.688471, acc.: 52.93%] [G loss: 0.827291]
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1417 [D loss: 0.671989, acc.: 57.42%] [G loss: 0.822172]
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1418 [D loss: 0.686312, acc.: 54.49%] [G loss: 0.834834]
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1419 [D loss: 0.679878, acc.: 55.47%] [G loss: 0.813162]
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1420 [D loss: 0.662286, acc.: 62.70%] [G loss: 0.815269]
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1421 [D loss: 0.677671, acc.: 55.66%] [G loss: 0.811431]
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1422 [D loss: 0.653708, acc.: 66.41%] [G loss: 0.798170]
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1423 [D loss: 0.662735, acc.: 62.11%] [G loss: 0.790638]
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1424 [D loss: 0.675454, acc.: 55.66%] [G loss: 0.789093]
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1425 [D loss: 0.676617, acc.: 56.25%] [G loss: 0.757284]
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1426 [D loss: 0.682804, acc.: 55.08%] [G loss: 0.749567]
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1427 [D loss: 0.704076, acc.: 50.00%] [G loss: 0.743931]
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1428 [D loss: 0.692175, acc.: 54.10%] [G loss: 0.790139]
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1429 [D loss: 0.688386, acc.: 53.12%] [G loss: 0.837449]
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1430 [D loss: 0.685375, acc.: 55.08%] [G loss: 0.840623]
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1431 [D loss: 0.684005, acc.: 54.88%] [G loss: 0.837409]
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1432 [D loss: 0.669296, acc.: 59.77%] [G loss: 0.800371]
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1433 [D loss: 0.672563, acc.: 60.94%] [G loss: 0.800443]
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1434 [D loss: 0.677708, acc.: 57.23%] [G loss: 0.807386]
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1435 [D loss: 0.677638, acc.: 58.20%] [G loss: 0.778341]
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1436 [D loss: 0.674346, acc.: 55.86%] [G loss: 0.763447]
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1437 [D loss: 0.675202, acc.: 55.47%] [G loss: 0.781207]
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1438 [D loss: 0.685248, acc.: 53.52%] [G loss: 0.770097]
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1439 [D loss: 0.687959, acc.: 54.10%] [G loss: 0.773457]
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1440 [D loss: 0.678983, acc.: 54.69%] [G loss: 0.800821]
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1441 [D loss: 0.664718, acc.: 60.35%] [G loss: 0.812379]
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1442 [D loss: 0.669477, acc.: 61.33%] [G loss: 0.851624]
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1443 [D loss: 0.691337, acc.: 54.49%] [G loss: 0.804972]
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1444 [D loss: 0.693228, acc.: 51.76%] [G loss: 0.799588]
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1445 [D loss: 0.689195, acc.: 52.34%] [G loss: 0.781892]
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1446 [D loss: 0.694289, acc.: 53.91%] [G loss: 0.750337]
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1447 [D loss: 0.679906, acc.: 53.12%] [G loss: 0.775053]
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1448 [D loss: 0.669088, acc.: 58.98%] [G loss: 0.793800]
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1449 [D loss: 0.660174, acc.: 60.35%] [G loss: 0.781258]
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1450 [D loss: 0.661965, acc.: 59.38%] [G loss: 0.775356]
1/1 [==============================] - 0s 17ms/step
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1451 [D loss: 0.671564, acc.: 58.79%] [G loss: 0.786663]
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1452 [D loss: 0.679202, acc.: 55.08%] [G loss: 0.785608]
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1453 [D loss: 0.691960, acc.: 53.12%] [G loss: 0.799526]
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1454 [D loss: 0.677350, acc.: 57.23%] [G loss: 0.795829]
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1455 [D loss: 0.686225, acc.: 53.71%] [G loss: 0.795148]
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1456 [D loss: 0.678086, acc.: 56.84%] [G loss: 0.803436]
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1457 [D loss: 0.684182, acc.: 56.84%] [G loss: 0.795647]
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1458 [D loss: 0.674144, acc.: 59.38%] [G loss: 0.807779]
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1459 [D loss: 0.680765, acc.: 56.64%] [G loss: 0.786305]
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1460 [D loss: 0.676810, acc.: 59.57%] [G loss: 0.794491]
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1461 [D loss: 0.678154, acc.: 54.88%] [G loss: 0.783481]
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1462 [D loss: 0.675981, acc.: 57.23%] [G loss: 0.784464]
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1463 [D loss: 0.681843, acc.: 58.01%] [G loss: 0.792019]
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1464 [D loss: 0.661174, acc.: 59.57%] [G loss: 0.783454]
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1465 [D loss: 0.675708, acc.: 55.27%] [G loss: 0.776623]
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1466 [D loss: 0.679703, acc.: 55.47%] [G loss: 0.765916]
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1467 [D loss: 0.688051, acc.: 53.12%] [G loss: 0.775616]
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1468 [D loss: 0.678115, acc.: 58.01%] [G loss: 0.793750]
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1469 [D loss: 0.683704, acc.: 54.49%] [G loss: 0.822658]
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1470 [D loss: 0.672095, acc.: 58.79%] [G loss: 0.836161]
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1471 [D loss: 0.674276, acc.: 58.20%] [G loss: 0.839057]
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1472 [D loss: 0.682729, acc.: 58.79%] [G loss: 0.824771]
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1473 [D loss: 0.682781, acc.: 54.30%] [G loss: 0.794440]
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1474 [D loss: 0.681964, acc.: 54.30%] [G loss: 0.790457]
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1475 [D loss: 0.679934, acc.: 58.20%] [G loss: 0.757437]
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1476 [D loss: 0.693249, acc.: 53.71%] [G loss: 0.779579]
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1477 [D loss: 0.687578, acc.: 54.10%] [G loss: 0.770661]
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1478 [D loss: 0.690015, acc.: 55.27%] [G loss: 0.780108]
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1479 [D loss: 0.668765, acc.: 57.42%] [G loss: 0.779454]
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1480 [D loss: 0.672849, acc.: 56.05%] [G loss: 0.784737]
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1481 [D loss: 0.671313, acc.: 57.42%] [G loss: 0.782984]
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1482 [D loss: 0.693325, acc.: 52.93%] [G loss: 0.742848]
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1483 [D loss: 0.700096, acc.: 51.95%] [G loss: 0.768585]
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1484 [D loss: 0.681507, acc.: 54.10%] [G loss: 0.778022]
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1485 [D loss: 0.693543, acc.: 51.95%] [G loss: 0.784033]
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1486 [D loss: 0.690081, acc.: 52.93%] [G loss: 0.785057]
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1487 [D loss: 0.675571, acc.: 54.49%] [G loss: 0.800082]
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1488 [D loss: 0.678337, acc.: 57.81%] [G loss: 0.800516]
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1489 [D loss: 0.668815, acc.: 58.59%] [G loss: 0.814014]
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1490 [D loss: 0.669044, acc.: 56.84%] [G loss: 0.816229]
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1491 [D loss: 0.662478, acc.: 62.30%] [G loss: 0.811723]
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1492 [D loss: 0.670025, acc.: 58.40%] [G loss: 0.784932]
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1493 [D loss: 0.671667, acc.: 58.79%] [G loss: 0.779353]
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1494 [D loss: 0.682719, acc.: 56.84%] [G loss: 0.780037]
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1495 [D loss: 0.686225, acc.: 52.54%] [G loss: 0.782873]
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1496 [D loss: 0.681046, acc.: 54.69%] [G loss: 0.779646]
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1497 [D loss: 0.691017, acc.: 54.10%] [G loss: 0.787167]
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1498 [D loss: 0.683277, acc.: 57.81%] [G loss: 0.809228]
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1499 [D loss: 0.666573, acc.: 61.91%] [G loss: 0.806337]
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1500 [D loss: 0.692385, acc.: 54.30%] [G loss: 0.787675]
1/1 [==============================] - 0s 16ms/step
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1501 [D loss: 0.673621, acc.: 58.98%] [G loss: 0.777773]
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1502 [D loss: 0.681442, acc.: 56.64%] [G loss: 0.768980]
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1503 [D loss: 0.667643, acc.: 57.81%] [G loss: 0.779408]
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1504 [D loss: 0.673059, acc.: 56.25%] [G loss: 0.757983]
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1505 [D loss: 0.673770, acc.: 56.45%] [G loss: 0.767490]
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1506 [D loss: 0.684061, acc.: 53.71%] [G loss: 0.779950]
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1507 [D loss: 0.690357, acc.: 53.91%] [G loss: 0.775025]
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1508 [D loss: 0.684314, acc.: 57.03%] [G loss: 0.799283]
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1509 [D loss: 0.678638, acc.: 58.20%] [G loss: 0.809880]
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1510 [D loss: 0.674294, acc.: 58.20%] [G loss: 0.808581]
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1511 [D loss: 0.668005, acc.: 59.57%] [G loss: 0.812102]
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1512 [D loss: 0.674300, acc.: 58.40%] [G loss: 0.787955]
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1513 [D loss: 0.672348, acc.: 58.01%] [G loss: 0.788262]
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1514 [D loss: 0.668290, acc.: 59.18%] [G loss: 0.799607]
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1515 [D loss: 0.680328, acc.: 55.47%] [G loss: 0.783511]
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1516 [D loss: 0.678280, acc.: 57.42%] [G loss: 0.774350]
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1517 [D loss: 0.681271, acc.: 56.64%] [G loss: 0.782783]
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1518 [D loss: 0.682588, acc.: 57.42%] [G loss: 0.762486]
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1519 [D loss: 0.688354, acc.: 54.10%] [G loss: 0.777161]
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1520 [D loss: 0.674186, acc.: 57.81%] [G loss: 0.787366]
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1521 [D loss: 0.668088, acc.: 58.98%] [G loss: 0.792334]
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1522 [D loss: 0.674342, acc.: 59.18%] [G loss: 0.822577]
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1523 [D loss: 0.687367, acc.: 52.93%] [G loss: 0.804897]
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1524 [D loss: 0.689063, acc.: 53.91%] [G loss: 0.768500]
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1525 [D loss: 0.670700, acc.: 57.81%] [G loss: 0.772666]
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1526 [D loss: 0.672079, acc.: 58.01%] [G loss: 0.773302]
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1527 [D loss: 0.685084, acc.: 53.71%] [G loss: 0.757223]
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1528 [D loss: 0.689235, acc.: 54.88%] [G loss: 0.751637]
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1529 [D loss: 0.695995, acc.: 51.95%] [G loss: 0.761476]
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1530 [D loss: 0.668250, acc.: 57.81%] [G loss: 0.775465]
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1531 [D loss: 0.671098, acc.: 57.03%] [G loss: 0.790341]
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1532 [D loss: 0.685345, acc.: 55.66%] [G loss: 0.813402]
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1533 [D loss: 0.688326, acc.: 54.10%] [G loss: 0.805119]
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1534 [D loss: 0.677200, acc.: 58.01%] [G loss: 0.775866]
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1535 [D loss: 0.686166, acc.: 55.66%] [G loss: 0.804059]
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1536 [D loss: 0.685389, acc.: 55.27%] [G loss: 0.783919]
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1537 [D loss: 0.673894, acc.: 59.38%] [G loss: 0.787005]
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1538 [D loss: 0.680280, acc.: 52.93%] [G loss: 0.764579]
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1539 [D loss: 0.670774, acc.: 59.38%] [G loss: 0.769279]
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1540 [D loss: 0.679923, acc.: 54.49%] [G loss: 0.761528]
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1541 [D loss: 0.687716, acc.: 54.88%] [G loss: 0.781825]
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1542 [D loss: 0.689152, acc.: 53.71%] [G loss: 0.781814]
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1543 [D loss: 0.682299, acc.: 53.12%] [G loss: 0.810803]
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1544 [D loss: 0.680941, acc.: 54.30%] [G loss: 0.819175]
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1545 [D loss: 0.671395, acc.: 59.18%] [G loss: 0.828179]
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1546 [D loss: 0.673595, acc.: 59.38%] [G loss: 0.824415]
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1547 [D loss: 0.672904, acc.: 61.52%] [G loss: 0.813325]
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1548 [D loss: 0.680025, acc.: 58.98%] [G loss: 0.785404]
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1549 [D loss: 0.685017, acc.: 56.05%] [G loss: 0.762566]
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1550 [D loss: 0.671874, acc.: 60.35%] [G loss: 0.785972]
1/1 [==============================] - 0s 17ms/step
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1551 [D loss: 0.670967, acc.: 58.59%] [G loss: 0.775890]
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1552 [D loss: 0.678948, acc.: 55.27%] [G loss: 0.742483]
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1553 [D loss: 0.680355, acc.: 53.71%] [G loss: 0.735127]
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1554 [D loss: 0.694592, acc.: 52.73%] [G loss: 0.753191]
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1555 [D loss: 0.689607, acc.: 54.10%] [G loss: 0.767196]
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1556 [D loss: 0.686358, acc.: 52.34%] [G loss: 0.814002]
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1557 [D loss: 0.670369, acc.: 61.72%] [G loss: 0.845791]
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1558 [D loss: 0.677298, acc.: 56.45%] [G loss: 0.834745]
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1559 [D loss: 0.686550, acc.: 55.66%] [G loss: 0.797395]
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1560 [D loss: 0.689515, acc.: 54.49%] [G loss: 0.747507]
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1561 [D loss: 0.685751, acc.: 55.47%] [G loss: 0.763074]
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1562 [D loss: 0.688916, acc.: 53.52%] [G loss: 0.764029]
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1563 [D loss: 0.677329, acc.: 57.23%] [G loss: 0.778079]
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1564 [D loss: 0.666241, acc.: 60.16%] [G loss: 0.754722]
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1565 [D loss: 0.686550, acc.: 53.71%] [G loss: 0.752248]
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1566 [D loss: 0.700943, acc.: 53.32%] [G loss: 0.746031]
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1567 [D loss: 0.682446, acc.: 56.45%] [G loss: 0.771701]
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1568 [D loss: 0.682848, acc.: 55.47%] [G loss: 0.852463]
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1569 [D loss: 0.658528, acc.: 62.50%] [G loss: 0.906790]
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1570 [D loss: 0.678864, acc.: 58.20%] [G loss: 0.866270]
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1571 [D loss: 0.682720, acc.: 58.98%] [G loss: 0.812082]
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1572 [D loss: 0.686287, acc.: 57.62%] [G loss: 0.784543]
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1573 [D loss: 0.683329, acc.: 55.47%] [G loss: 0.766281]
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1574 [D loss: 0.680991, acc.: 58.40%] [G loss: 0.791440]
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1575 [D loss: 0.655776, acc.: 62.70%] [G loss: 0.778783]
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1576 [D loss: 0.651299, acc.: 60.94%] [G loss: 0.779275]
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1577 [D loss: 0.677635, acc.: 55.66%] [G loss: 0.735564]
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1578 [D loss: 0.680860, acc.: 54.49%] [G loss: 0.744603]
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1579 [D loss: 0.706067, acc.: 50.59%] [G loss: 0.742799]
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1580 [D loss: 0.695217, acc.: 54.88%] [G loss: 0.828099]
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1581 [D loss: 0.680839, acc.: 54.69%] [G loss: 0.895925]
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1582 [D loss: 0.694987, acc.: 52.54%] [G loss: 0.887995]
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1583 [D loss: 0.698796, acc.: 51.95%] [G loss: 0.823967]
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1584 [D loss: 0.698437, acc.: 51.56%] [G loss: 0.792597]
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1585 [D loss: 0.702492, acc.: 53.12%] [G loss: 0.779483]
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1586 [D loss: 0.672717, acc.: 58.98%] [G loss: 0.786469]
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1587 [D loss: 0.668328, acc.: 59.57%] [G loss: 0.796075]
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1588 [D loss: 0.660907, acc.: 64.06%] [G loss: 0.788621]
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1589 [D loss: 0.689060, acc.: 52.73%] [G loss: 0.771544]
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1590 [D loss: 0.689691, acc.: 54.49%] [G loss: 0.767095]
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1591 [D loss: 0.669560, acc.: 58.79%] [G loss: 0.805814]
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1592 [D loss: 0.682053, acc.: 55.27%] [G loss: 0.834241]
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1593 [D loss: 0.680918, acc.: 56.64%] [G loss: 0.842687]
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1594 [D loss: 0.681328, acc.: 56.05%] [G loss: 0.850074]
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1595 [D loss: 0.682038, acc.: 56.45%] [G loss: 0.813381]
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1596 [D loss: 0.695113, acc.: 51.56%] [G loss: 0.795443]
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1597 [D loss: 0.676741, acc.: 59.18%] [G loss: 0.794562]
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1598 [D loss: 0.688692, acc.: 53.32%] [G loss: 0.773107]
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1599 [D loss: 0.691619, acc.: 51.95%] [G loss: 0.785546]
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1600 [D loss: 0.689907, acc.: 52.73%] [G loss: 0.758237]
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1601 [D loss: 0.673511, acc.: 58.20%] [G loss: 0.758970]
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1602 [D loss: 0.684549, acc.: 54.69%] [G loss: 0.801455]
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1603 [D loss: 0.666618, acc.: 59.96%] [G loss: 0.817127]
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1604 [D loss: 0.678323, acc.: 57.03%] [G loss: 0.818991]
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1605 [D loss: 0.675227, acc.: 56.84%] [G loss: 0.823861]
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1606 [D loss: 0.679595, acc.: 55.86%] [G loss: 0.812622]
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1607 [D loss: 0.689312, acc.: 53.71%] [G loss: 0.782484]
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1608 [D loss: 0.707300, acc.: 49.80%] [G loss: 0.778478]
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1609 [D loss: 0.701551, acc.: 48.83%] [G loss: 0.746800]
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1610 [D loss: 0.691332, acc.: 53.71%] [G loss: 0.771718]
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1611 [D loss: 0.686932, acc.: 54.49%] [G loss: 0.760100]
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1612 [D loss: 0.684162, acc.: 53.91%] [G loss: 0.794332]
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1613 [D loss: 0.674087, acc.: 58.59%] [G loss: 0.767235]
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1614 [D loss: 0.679577, acc.: 55.27%] [G loss: 0.796742]
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1615 [D loss: 0.683747, acc.: 54.30%] [G loss: 0.799984]
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1616 [D loss: 0.665270, acc.: 59.96%] [G loss: 0.791807]
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1617 [D loss: 0.675512, acc.: 56.45%] [G loss: 0.781680]
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1618 [D loss: 0.685599, acc.: 57.42%] [G loss: 0.783455]
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1619 [D loss: 0.677844, acc.: 59.38%] [G loss: 0.777409]
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1620 [D loss: 0.700566, acc.: 52.54%] [G loss: 0.784649]
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1621 [D loss: 0.685146, acc.: 55.27%] [G loss: 0.787761]
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1622 [D loss: 0.693710, acc.: 53.12%] [G loss: 0.781147]
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1623 [D loss: 0.688219, acc.: 55.27%] [G loss: 0.792188]
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1624 [D loss: 0.693245, acc.: 53.12%] [G loss: 0.807120]
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1625 [D loss: 0.683065, acc.: 56.05%] [G loss: 0.783616]
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1626 [D loss: 0.683461, acc.: 55.27%] [G loss: 0.778868]
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1627 [D loss: 0.680700, acc.: 57.81%] [G loss: 0.776626]
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1628 [D loss: 0.679733, acc.: 58.01%] [G loss: 0.766211]
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1629 [D loss: 0.685086, acc.: 53.91%] [G loss: 0.775000]
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1630 [D loss: 0.680358, acc.: 57.42%] [G loss: 0.761100]
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1631 [D loss: 0.675228, acc.: 56.64%] [G loss: 0.775480]
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1632 [D loss: 0.677547, acc.: 56.25%] [G loss: 0.786920]
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1633 [D loss: 0.686866, acc.: 54.69%] [G loss: 0.770236]
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1634 [D loss: 0.673677, acc.: 57.03%] [G loss: 0.775073]
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1635 [D loss: 0.688017, acc.: 53.52%] [G loss: 0.783929]
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1636 [D loss: 0.685164, acc.: 53.52%] [G loss: 0.769813]
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1637 [D loss: 0.688971, acc.: 55.86%] [G loss: 0.773122]
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1638 [D loss: 0.694701, acc.: 52.34%] [G loss: 0.761978]
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1639 [D loss: 0.687503, acc.: 57.03%] [G loss: 0.767950]
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1640 [D loss: 0.687522, acc.: 56.05%] [G loss: 0.793932]
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1641 [D loss: 0.683154, acc.: 55.27%] [G loss: 0.772984]
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1642 [D loss: 0.673632, acc.: 58.59%] [G loss: 0.788868]
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1643 [D loss: 0.666341, acc.: 61.33%] [G loss: 0.800590]
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1644 [D loss: 0.677432, acc.: 58.79%] [G loss: 0.770677]
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1645 [D loss: 0.674157, acc.: 58.20%] [G loss: 0.775676]
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1646 [D loss: 0.681138, acc.: 58.01%] [G loss: 0.775863]
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1647 [D loss: 0.677238, acc.: 57.23%] [G loss: 0.802400]
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1648 [D loss: 0.693158, acc.: 53.12%] [G loss: 0.761780]
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1649 [D loss: 0.685495, acc.: 51.76%] [G loss: 0.766530]
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1650 [D loss: 0.688911, acc.: 53.71%] [G loss: 0.761379]
1/1 [==============================] - 0s 16ms/step
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1651 [D loss: 0.678190, acc.: 57.42%] [G loss: 0.785012]
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1652 [D loss: 0.685558, acc.: 52.54%] [G loss: 0.785293]
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1653 [D loss: 0.674654, acc.: 56.64%] [G loss: 0.797696]
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1654 [D loss: 0.665642, acc.: 62.11%] [G loss: 0.791502]
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1655 [D loss: 0.673221, acc.: 62.11%] [G loss: 0.779644]
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1656 [D loss: 0.681035, acc.: 57.03%] [G loss: 0.752022]
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1657 [D loss: 0.679427, acc.: 57.23%] [G loss: 0.762441]
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1658 [D loss: 0.663352, acc.: 61.72%] [G loss: 0.752965]
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1659 [D loss: 0.681249, acc.: 54.49%] [G loss: 0.771103]
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1660 [D loss: 0.675092, acc.: 57.42%] [G loss: 0.767293]
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1661 [D loss: 0.692406, acc.: 54.10%] [G loss: 0.778730]
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1662 [D loss: 0.682392, acc.: 56.84%] [G loss: 0.803204]
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1663 [D loss: 0.689868, acc.: 55.66%] [G loss: 0.802336]
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1664 [D loss: 0.693216, acc.: 55.47%] [G loss: 0.779141]
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1665 [D loss: 0.692642, acc.: 56.05%] [G loss: 0.797552]
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1666 [D loss: 0.678434, acc.: 59.57%] [G loss: 0.794451]
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1667 [D loss: 0.693155, acc.: 55.66%] [G loss: 0.795646]
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1668 [D loss: 0.676309, acc.: 58.59%] [G loss: 0.801125]
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1669 [D loss: 0.682921, acc.: 55.66%] [G loss: 0.796082]
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1670 [D loss: 0.681251, acc.: 57.81%] [G loss: 0.786909]
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1671 [D loss: 0.673112, acc.: 56.05%] [G loss: 0.788514]
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1672 [D loss: 0.680313, acc.: 57.23%] [G loss: 0.757997]
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1673 [D loss: 0.675582, acc.: 58.79%] [G loss: 0.773402]
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1674 [D loss: 0.686706, acc.: 53.91%] [G loss: 0.782375]
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1675 [D loss: 0.680009, acc.: 57.62%] [G loss: 0.778795]
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1676 [D loss: 0.690847, acc.: 52.93%] [G loss: 0.796251]
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1677 [D loss: 0.701899, acc.: 49.22%] [G loss: 0.782298]
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1678 [D loss: 0.688776, acc.: 52.73%] [G loss: 0.787124]
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1679 [D loss: 0.691115, acc.: 53.32%] [G loss: 0.762894]
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1680 [D loss: 0.686988, acc.: 54.88%] [G loss: 0.761064]
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1681 [D loss: 0.690467, acc.: 54.49%] [G loss: 0.766056]
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1682 [D loss: 0.672451, acc.: 58.20%] [G loss: 0.756879]
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1683 [D loss: 0.675827, acc.: 61.72%] [G loss: 0.765444]
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1684 [D loss: 0.678651, acc.: 56.25%] [G loss: 0.766791]
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1685 [D loss: 0.683397, acc.: 54.49%] [G loss: 0.765656]
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1686 [D loss: 0.690013, acc.: 55.08%] [G loss: 0.762592]
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1687 [D loss: 0.698921, acc.: 54.69%] [G loss: 0.768962]
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1688 [D loss: 0.680393, acc.: 57.03%] [G loss: 0.786639]
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1689 [D loss: 0.689823, acc.: 55.08%] [G loss: 0.822856]
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1690 [D loss: 0.688020, acc.: 54.30%] [G loss: 0.845901]
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1691 [D loss: 0.691237, acc.: 53.91%] [G loss: 0.834519]
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1692 [D loss: 0.692179, acc.: 53.52%] [G loss: 0.779474]
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1693 [D loss: 0.688493, acc.: 56.05%] [G loss: 0.784281]
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1694 [D loss: 0.671207, acc.: 60.94%] [G loss: 0.781888]
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1695 [D loss: 0.673277, acc.: 58.59%] [G loss: 0.768311]
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1696 [D loss: 0.657279, acc.: 62.11%] [G loss: 0.776312]
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1697 [D loss: 0.672346, acc.: 56.45%] [G loss: 0.750425]
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1698 [D loss: 0.689822, acc.: 53.52%] [G loss: 0.725572]
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1699 [D loss: 0.718208, acc.: 48.44%] [G loss: 0.720655]
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1700 [D loss: 0.699315, acc.: 53.91%] [G loss: 0.755781]
1/1 [==============================] - 0s 17ms/step
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1701 [D loss: 0.688935, acc.: 51.56%] [G loss: 0.840521]
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1702 [D loss: 0.672004, acc.: 54.88%] [G loss: 0.877540]
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1703 [D loss: 0.675963, acc.: 56.64%] [G loss: 0.867598]
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1704 [D loss: 0.674135, acc.: 58.40%] [G loss: 0.830470]
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1705 [D loss: 0.688445, acc.: 59.96%] [G loss: 0.802276]
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1706 [D loss: 0.679503, acc.: 57.81%] [G loss: 0.784125]
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1707 [D loss: 0.678458, acc.: 61.13%] [G loss: 0.797018]
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1708 [D loss: 0.680347, acc.: 55.66%] [G loss: 0.768638]
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1709 [D loss: 0.676330, acc.: 54.49%] [G loss: 0.739908]
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1710 [D loss: 0.694268, acc.: 53.12%] [G loss: 0.703307]
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1711 [D loss: 0.690668, acc.: 51.56%] [G loss: 0.710732]
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1712 [D loss: 0.710051, acc.: 47.46%] [G loss: 0.716008]
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1713 [D loss: 0.699285, acc.: 52.93%] [G loss: 0.757368]
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1714 [D loss: 0.684781, acc.: 52.93%] [G loss: 0.813608]
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1715 [D loss: 0.666631, acc.: 61.13%] [G loss: 0.831888]
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1716 [D loss: 0.681389, acc.: 56.25%] [G loss: 0.823699]
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1717 [D loss: 0.682290, acc.: 56.84%] [G loss: 0.782100]
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1718 [D loss: 0.695114, acc.: 52.54%] [G loss: 0.785791]
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1719 [D loss: 0.685919, acc.: 56.64%] [G loss: 0.758264]
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1720 [D loss: 0.681252, acc.: 57.62%] [G loss: 0.762810]
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1721 [D loss: 0.665400, acc.: 60.94%] [G loss: 0.760138]
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1722 [D loss: 0.664442, acc.: 60.55%] [G loss: 0.751900]
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1723 [D loss: 0.676560, acc.: 56.64%] [G loss: 0.736798]
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1724 [D loss: 0.684797, acc.: 55.08%] [G loss: 0.730714]
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1725 [D loss: 0.696309, acc.: 52.73%] [G loss: 0.738342]
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1726 [D loss: 0.690268, acc.: 52.93%] [G loss: 0.773135]
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1727 [D loss: 0.679771, acc.: 57.81%] [G loss: 0.824372]
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1728 [D loss: 0.681696, acc.: 54.69%] [G loss: 0.838207]
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1729 [D loss: 0.685589, acc.: 56.05%] [G loss: 0.833499]
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1730 [D loss: 0.696468, acc.: 52.54%] [G loss: 0.813595]
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1731 [D loss: 0.692189, acc.: 52.93%] [G loss: 0.793329]
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1732 [D loss: 0.682493, acc.: 57.81%] [G loss: 0.777201]
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1733 [D loss: 0.684295, acc.: 55.08%] [G loss: 0.779503]
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1734 [D loss: 0.676444, acc.: 59.77%] [G loss: 0.765292]
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1735 [D loss: 0.671372, acc.: 59.77%] [G loss: 0.772523]
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1736 [D loss: 0.657271, acc.: 63.87%] [G loss: 0.781623]
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1737 [D loss: 0.667938, acc.: 58.79%] [G loss: 0.746750]
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1738 [D loss: 0.683104, acc.: 55.66%] [G loss: 0.730976]
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1739 [D loss: 0.701370, acc.: 50.20%] [G loss: 0.721392]
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1740 [D loss: 0.688717, acc.: 51.95%] [G loss: 0.735486]
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1741 [D loss: 0.697831, acc.: 51.95%] [G loss: 0.773014]
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1742 [D loss: 0.692419, acc.: 52.93%] [G loss: 0.792933]
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1743 [D loss: 0.685024, acc.: 57.03%] [G loss: 0.793602]
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1744 [D loss: 0.685506, acc.: 54.30%] [G loss: 0.813624]
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1745 [D loss: 0.679988, acc.: 53.91%] [G loss: 0.798890]
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1746 [D loss: 0.675409, acc.: 58.40%] [G loss: 0.786198]
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1747 [D loss: 0.674487, acc.: 61.13%] [G loss: 0.781890]
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1748 [D loss: 0.667882, acc.: 61.72%] [G loss: 0.767358]
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1749 [D loss: 0.679736, acc.: 55.86%] [G loss: 0.760191]
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1750 [D loss: 0.679443, acc.: 57.23%] [G loss: 0.725886]
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1751 [D loss: 0.687669, acc.: 53.52%] [G loss: 0.740092]
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1752 [D loss: 0.689798, acc.: 52.15%] [G loss: 0.740985]
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1753 [D loss: 0.703303, acc.: 50.00%] [G loss: 0.754598]
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1754 [D loss: 0.671681, acc.: 56.25%] [G loss: 0.842873]
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1755 [D loss: 0.664084, acc.: 59.18%] [G loss: 0.889025]
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1756 [D loss: 0.669460, acc.: 57.03%] [G loss: 0.873860]
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1757 [D loss: 0.685692, acc.: 54.10%] [G loss: 0.837792]
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1758 [D loss: 0.689567, acc.: 51.17%] [G loss: 0.798272]
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1759 [D loss: 0.681648, acc.: 55.08%] [G loss: 0.760875]
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1760 [D loss: 0.701759, acc.: 48.63%] [G loss: 0.747525]
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1761 [D loss: 0.685158, acc.: 57.03%] [G loss: 0.728459]
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1762 [D loss: 0.679736, acc.: 56.05%] [G loss: 0.730632]
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1763 [D loss: 0.680063, acc.: 54.30%] [G loss: 0.731148]
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1764 [D loss: 0.688668, acc.: 53.91%] [G loss: 0.739458]
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1765 [D loss: 0.687624, acc.: 53.32%] [G loss: 0.752916]
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1766 [D loss: 0.682951, acc.: 56.05%] [G loss: 0.799634]
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1767 [D loss: 0.668012, acc.: 58.59%] [G loss: 0.826265]
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1768 [D loss: 0.677400, acc.: 57.03%] [G loss: 0.863237]
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1769 [D loss: 0.680369, acc.: 56.05%] [G loss: 0.826916]
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1770 [D loss: 0.692396, acc.: 53.91%] [G loss: 0.793579]
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1771 [D loss: 0.690574, acc.: 53.12%] [G loss: 0.787682]
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1772 [D loss: 0.698960, acc.: 49.41%] [G loss: 0.760914]
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1773 [D loss: 0.687230, acc.: 52.73%] [G loss: 0.745651]
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1774 [D loss: 0.683011, acc.: 57.03%] [G loss: 0.755074]
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1775 [D loss: 0.679778, acc.: 59.77%] [G loss: 0.742006]
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1776 [D loss: 0.680156, acc.: 55.66%] [G loss: 0.755915]
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1777 [D loss: 0.672421, acc.: 57.42%] [G loss: 0.758523]
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1778 [D loss: 0.665699, acc.: 60.55%] [G loss: 0.764455]
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1779 [D loss: 0.674589, acc.: 58.01%] [G loss: 0.768663]
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1780 [D loss: 0.679744, acc.: 57.03%] [G loss: 0.771495]
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1781 [D loss: 0.679976, acc.: 55.86%] [G loss: 0.785010]
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1782 [D loss: 0.699434, acc.: 52.73%] [G loss: 0.799404]
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1783 [D loss: 0.682345, acc.: 54.69%] [G loss: 0.806418]
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1784 [D loss: 0.674043, acc.: 58.20%] [G loss: 0.793682]
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1785 [D loss: 0.687066, acc.: 55.47%] [G loss: 0.797399]
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1786 [D loss: 0.688592, acc.: 57.03%] [G loss: 0.796489]
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1787 [D loss: 0.677240, acc.: 57.81%] [G loss: 0.789130]
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1788 [D loss: 0.672995, acc.: 58.40%] [G loss: 0.767717]
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1789 [D loss: 0.671991, acc.: 61.13%] [G loss: 0.769083]
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1790 [D loss: 0.670486, acc.: 58.40%] [G loss: 0.768713]
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1791 [D loss: 0.689476, acc.: 55.27%] [G loss: 0.755269]
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1792 [D loss: 0.691863, acc.: 53.12%] [G loss: 0.767926]
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1793 [D loss: 0.695096, acc.: 52.93%] [G loss: 0.776153]
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1794 [D loss: 0.694571, acc.: 52.93%] [G loss: 0.775206]
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1795 [D loss: 0.690203, acc.: 52.73%] [G loss: 0.778459]
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1796 [D loss: 0.688809, acc.: 55.66%] [G loss: 0.790878]
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1797 [D loss: 0.691638, acc.: 52.54%] [G loss: 0.797265]
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1798 [D loss: 0.698318, acc.: 54.69%] [G loss: 0.770076]
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1799 [D loss: 0.686816, acc.: 55.66%] [G loss: 0.773958]
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1800 [D loss: 0.682568, acc.: 55.47%] [G loss: 0.752587]
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1801 [D loss: 0.677983, acc.: 59.18%] [G loss: 0.755881]
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1802 [D loss: 0.680283, acc.: 56.64%] [G loss: 0.761383]
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1803 [D loss: 0.662963, acc.: 61.72%] [G loss: 0.755887]
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1804 [D loss: 0.686493, acc.: 54.88%] [G loss: 0.756368]
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1805 [D loss: 0.681529, acc.: 57.42%] [G loss: 0.742428]
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1806 [D loss: 0.671905, acc.: 58.01%] [G loss: 0.759503]
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1807 [D loss: 0.685517, acc.: 55.86%] [G loss: 0.779861]
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1808 [D loss: 0.677313, acc.: 57.03%] [G loss: 0.772218]
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1809 [D loss: 0.681773, acc.: 56.25%] [G loss: 0.754731]
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1810 [D loss: 0.691580, acc.: 53.12%] [G loss: 0.797898]
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1811 [D loss: 0.685960, acc.: 52.15%] [G loss: 0.793841]
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1812 [D loss: 0.692659, acc.: 54.88%] [G loss: 0.800437]
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1813 [D loss: 0.683041, acc.: 55.86%] [G loss: 0.800062]
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1814 [D loss: 0.687952, acc.: 56.05%] [G loss: 0.778543]
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1815 [D loss: 0.696663, acc.: 52.15%] [G loss: 0.763060]
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1816 [D loss: 0.686192, acc.: 54.69%] [G loss: 0.764624]
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1817 [D loss: 0.689299, acc.: 50.59%] [G loss: 0.760303]
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1818 [D loss: 0.682691, acc.: 59.96%] [G loss: 0.751025]
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1819 [D loss: 0.674977, acc.: 60.16%] [G loss: 0.753706]
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1820 [D loss: 0.682388, acc.: 57.03%] [G loss: 0.744698]
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1821 [D loss: 0.683452, acc.: 56.05%] [G loss: 0.761496]
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1822 [D loss: 0.696026, acc.: 52.34%] [G loss: 0.782463]
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1823 [D loss: 0.680176, acc.: 56.64%] [G loss: 0.796222]
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1824 [D loss: 0.676618, acc.: 56.05%] [G loss: 0.815174]
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1825 [D loss: 0.669790, acc.: 59.96%] [G loss: 0.792894]
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1826 [D loss: 0.683468, acc.: 58.40%] [G loss: 0.808409]
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1827 [D loss: 0.689160, acc.: 52.15%] [G loss: 0.763792]
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1828 [D loss: 0.698241, acc.: 50.59%] [G loss: 0.731058]
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1829 [D loss: 0.698528, acc.: 50.98%] [G loss: 0.726499]
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1830 [D loss: 0.687673, acc.: 54.88%] [G loss: 0.736552]
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1831 [D loss: 0.703017, acc.: 49.22%] [G loss: 0.733815]
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1832 [D loss: 0.684469, acc.: 56.45%] [G loss: 0.732370]
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1833 [D loss: 0.687566, acc.: 54.30%] [G loss: 0.751560]
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1834 [D loss: 0.686354, acc.: 53.91%] [G loss: 0.776372]
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1835 [D loss: 0.677846, acc.: 57.81%] [G loss: 0.803784]
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1836 [D loss: 0.670892, acc.: 60.55%] [G loss: 0.827289]
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1837 [D loss: 0.669840, acc.: 55.08%] [G loss: 0.839481]
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1838 [D loss: 0.673739, acc.: 56.84%] [G loss: 0.825006]
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1839 [D loss: 0.689826, acc.: 56.05%] [G loss: 0.795843]
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1840 [D loss: 0.694158, acc.: 51.56%] [G loss: 0.770282]
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1841 [D loss: 0.703131, acc.: 51.37%] [G loss: 0.753630]
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1842 [D loss: 0.695864, acc.: 48.83%] [G loss: 0.750160]
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1843 [D loss: 0.684634, acc.: 53.32%] [G loss: 0.741324]
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1844 [D loss: 0.674845, acc.: 58.98%] [G loss: 0.742689]
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1845 [D loss: 0.664305, acc.: 59.77%] [G loss: 0.778024]
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1846 [D loss: 0.684514, acc.: 55.86%] [G loss: 0.753486]
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1847 [D loss: 0.687777, acc.: 50.59%] [G loss: 0.738339]
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1848 [D loss: 0.680616, acc.: 55.08%] [G loss: 0.772938]
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1849 [D loss: 0.679464, acc.: 55.27%] [G loss: 0.775067]
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1850 [D loss: 0.690218, acc.: 54.10%] [G loss: 0.781666]
1/1 [==============================] - 0s 18ms/step
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1851 [D loss: 0.692100, acc.: 52.73%] [G loss: 0.812408]
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1852 [D loss: 0.677544, acc.: 56.25%] [G loss: 0.800314]
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1853 [D loss: 0.695914, acc.: 53.12%] [G loss: 0.804975]
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1854 [D loss: 0.680827, acc.: 54.49%] [G loss: 0.773994]
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1855 [D loss: 0.685509, acc.: 56.05%] [G loss: 0.782273]
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1856 [D loss: 0.668231, acc.: 61.91%] [G loss: 0.771841]
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1857 [D loss: 0.671582, acc.: 59.18%] [G loss: 0.795995]
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1858 [D loss: 0.663653, acc.: 61.13%] [G loss: 0.778404]
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1859 [D loss: 0.693647, acc.: 56.45%] [G loss: 0.767092]
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1860 [D loss: 0.681556, acc.: 54.88%] [G loss: 0.751559]
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1861 [D loss: 0.691973, acc.: 52.15%] [G loss: 0.783331]
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1862 [D loss: 0.691034, acc.: 55.47%] [G loss: 0.793209]
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1863 [D loss: 0.679841, acc.: 56.25%] [G loss: 0.831945]
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1864 [D loss: 0.702230, acc.: 50.39%] [G loss: 0.851302]
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1865 [D loss: 0.700203, acc.: 51.37%] [G loss: 0.810623]
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1866 [D loss: 0.698297, acc.: 51.95%] [G loss: 0.838660]
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1867 [D loss: 0.697019, acc.: 51.37%] [G loss: 0.806882]
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1868 [D loss: 0.688657, acc.: 51.37%] [G loss: 0.788165]
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1869 [D loss: 0.670544, acc.: 57.81%] [G loss: 0.768623]
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1870 [D loss: 0.647082, acc.: 67.58%] [G loss: 0.799164]
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1871 [D loss: 0.660221, acc.: 63.67%] [G loss: 0.803355]
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1872 [D loss: 0.659200, acc.: 56.45%] [G loss: 0.754682]
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1873 [D loss: 0.669082, acc.: 58.79%] [G loss: 0.732849]
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1874 [D loss: 0.682153, acc.: 54.69%] [G loss: 0.716280]
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1875 [D loss: 0.719713, acc.: 50.20%] [G loss: 0.694159]
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1876 [D loss: 0.722045, acc.: 47.85%] [G loss: 0.727784]
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1877 [D loss: 0.705885, acc.: 50.39%] [G loss: 0.805095]
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1878 [D loss: 0.683299, acc.: 53.71%] [G loss: 0.850204]
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1879 [D loss: 0.681577, acc.: 53.32%] [G loss: 0.875675]
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1880 [D loss: 0.674370, acc.: 60.74%] [G loss: 0.868739]
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1881 [D loss: 0.673691, acc.: 57.81%] [G loss: 0.807293]
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1882 [D loss: 0.672295, acc.: 59.38%] [G loss: 0.836308]
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1883 [D loss: 0.666403, acc.: 63.09%] [G loss: 0.818102]
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1884 [D loss: 0.649552, acc.: 67.19%] [G loss: 0.814482]
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1885 [D loss: 0.671423, acc.: 59.57%] [G loss: 0.773266]
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1886 [D loss: 0.688969, acc.: 53.91%] [G loss: 0.737086]
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1887 [D loss: 0.708713, acc.: 51.56%] [G loss: 0.720898]
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1888 [D loss: 0.715634, acc.: 50.00%] [G loss: 0.721832]
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1889 [D loss: 0.724232, acc.: 47.27%] [G loss: 0.788203]
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1890 [D loss: 0.685109, acc.: 54.30%] [G loss: 0.848368]
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1891 [D loss: 0.664958, acc.: 60.35%] [G loss: 0.918194]
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1892 [D loss: 0.674903, acc.: 58.40%] [G loss: 0.880275]
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1893 [D loss: 0.686858, acc.: 55.47%] [G loss: 0.836509]
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1894 [D loss: 0.693065, acc.: 55.08%] [G loss: 0.789881]
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1895 [D loss: 0.687168, acc.: 56.25%] [G loss: 0.776920]
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1896 [D loss: 0.683135, acc.: 56.25%] [G loss: 0.763182]
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1897 [D loss: 0.664950, acc.: 59.57%] [G loss: 0.744852]
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1898 [D loss: 0.676999, acc.: 57.81%] [G loss: 0.747242]
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1899 [D loss: 0.687950, acc.: 51.17%] [G loss: 0.737679]
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1900 [D loss: 0.690687, acc.: 51.95%] [G loss: 0.730852]
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1901 [D loss: 0.704836, acc.: 50.20%] [G loss: 0.725455]
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1902 [D loss: 0.703996, acc.: 49.61%] [G loss: 0.741970]
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1903 [D loss: 0.683028, acc.: 55.08%] [G loss: 0.800265]
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1904 [D loss: 0.665256, acc.: 62.50%] [G loss: 0.857671]
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1905 [D loss: 0.681749, acc.: 55.66%] [G loss: 0.904995]
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1906 [D loss: 0.685809, acc.: 54.69%] [G loss: 0.872328]
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1907 [D loss: 0.689775, acc.: 54.30%] [G loss: 0.815448]
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1908 [D loss: 0.705181, acc.: 50.00%] [G loss: 0.779351]
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1909 [D loss: 0.696815, acc.: 51.56%] [G loss: 0.776636]
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1910 [D loss: 0.669489, acc.: 61.91%] [G loss: 0.785859]
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1911 [D loss: 0.656136, acc.: 61.52%] [G loss: 0.810106]
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1912 [D loss: 0.644068, acc.: 67.77%] [G loss: 0.784543]
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1913 [D loss: 0.676689, acc.: 56.84%] [G loss: 0.767964]
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1914 [D loss: 0.701155, acc.: 51.56%] [G loss: 0.735483]
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1915 [D loss: 0.704360, acc.: 53.52%] [G loss: 0.736219]
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1916 [D loss: 0.712245, acc.: 47.66%] [G loss: 0.787952]
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1917 [D loss: 0.701234, acc.: 50.20%] [G loss: 0.833655]
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1918 [D loss: 0.667577, acc.: 58.98%] [G loss: 0.882607]
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1919 [D loss: 0.666933, acc.: 58.98%] [G loss: 0.870220]
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1920 [D loss: 0.681323, acc.: 56.25%] [G loss: 0.832581]
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1921 [D loss: 0.683591, acc.: 57.03%] [G loss: 0.795937]
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1922 [D loss: 0.689274, acc.: 54.10%] [G loss: 0.770083]
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1923 [D loss: 0.680837, acc.: 59.77%] [G loss: 0.775294]
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1924 [D loss: 0.684452, acc.: 55.66%] [G loss: 0.774126]
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1925 [D loss: 0.669177, acc.: 56.64%] [G loss: 0.749787]
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1926 [D loss: 0.674446, acc.: 57.62%] [G loss: 0.752037]
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1927 [D loss: 0.691018, acc.: 52.54%] [G loss: 0.737734]
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1928 [D loss: 0.702032, acc.: 54.30%] [G loss: 0.727689]
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1929 [D loss: 0.694239, acc.: 50.78%] [G loss: 0.732560]
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1930 [D loss: 0.699751, acc.: 51.56%] [G loss: 0.783656]
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1931 [D loss: 0.679830, acc.: 56.05%] [G loss: 0.826824]
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1932 [D loss: 0.672044, acc.: 59.38%] [G loss: 0.882898]
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1933 [D loss: 0.676729, acc.: 59.96%] [G loss: 0.832196]
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1934 [D loss: 0.676817, acc.: 60.35%] [G loss: 0.833348]
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1935 [D loss: 0.683689, acc.: 57.42%] [G loss: 0.791918]
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1936 [D loss: 0.683105, acc.: 58.20%] [G loss: 0.791710]
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1937 [D loss: 0.672271, acc.: 59.57%] [G loss: 0.767830]
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1938 [D loss: 0.675341, acc.: 59.18%] [G loss: 0.801672]
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1939 [D loss: 0.663373, acc.: 60.94%] [G loss: 0.790686]
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1940 [D loss: 0.670342, acc.: 58.98%] [G loss: 0.767309]
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1941 [D loss: 0.686290, acc.: 54.88%] [G loss: 0.761598]
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1942 [D loss: 0.695488, acc.: 52.73%] [G loss: 0.786575]
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1943 [D loss: 0.689830, acc.: 54.10%] [G loss: 0.823417]
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1944 [D loss: 0.696942, acc.: 53.12%] [G loss: 0.838391]
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1945 [D loss: 0.694485, acc.: 50.59%] [G loss: 0.832038]
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1946 [D loss: 0.696778, acc.: 53.52%] [G loss: 0.809833]
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1947 [D loss: 0.695392, acc.: 50.78%] [G loss: 0.768333]
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1948 [D loss: 0.694007, acc.: 53.91%] [G loss: 0.777918]
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1949 [D loss: 0.679253, acc.: 55.27%] [G loss: 0.759779]
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1950 [D loss: 0.666040, acc.: 61.13%] [G loss: 0.775258]
1/1 [==============================] - 0s 23ms/step
8/8 [==============================] - 0s 5ms/step
1951 [D loss: 0.676383, acc.: 56.25%] [G loss: 0.757865]
8/8 [==============================] - 0s 7ms/step
1952 [D loss: 0.671165, acc.: 58.01%] [G loss: 0.754066]
8/8 [==============================] - 0s 5ms/step
1953 [D loss: 0.685300, acc.: 54.10%] [G loss: 0.765563]
8/8 [==============================] - 0s 5ms/step
1954 [D loss: 0.675037, acc.: 56.25%] [G loss: 0.763469]
8/8 [==============================] - 0s 5ms/step
1955 [D loss: 0.678597, acc.: 55.47%] [G loss: 0.783082]
8/8 [==============================] - 0s 5ms/step
1956 [D loss: 0.681465, acc.: 56.25%] [G loss: 0.787770]
8/8 [==============================] - 0s 5ms/step
1957 [D loss: 0.681440, acc.: 55.27%] [G loss: 0.814869]
8/8 [==============================] - 0s 5ms/step
1958 [D loss: 0.685745, acc.: 54.69%] [G loss: 0.786171]
8/8 [==============================] - 0s 5ms/step
1959 [D loss: 0.708605, acc.: 50.98%] [G loss: 0.786865]
8/8 [==============================] - 0s 4ms/step
1960 [D loss: 0.705803, acc.: 50.98%] [G loss: 0.770876]
8/8 [==============================] - 0s 5ms/step
1961 [D loss: 0.696007, acc.: 52.73%] [G loss: 0.766015]
8/8 [==============================] - 0s 5ms/step
1962 [D loss: 0.702651, acc.: 50.39%] [G loss: 0.764557]
8/8 [==============================] - 0s 4ms/step
1963 [D loss: 0.678434, acc.: 58.79%] [G loss: 0.773608]
8/8 [==============================] - 0s 5ms/step
1964 [D loss: 0.698554, acc.: 50.98%] [G loss: 0.785919]
8/8 [==============================] - 0s 5ms/step
1965 [D loss: 0.667887, acc.: 58.59%] [G loss: 0.786259]
8/8 [==============================] - 0s 5ms/step
1966 [D loss: 0.682937, acc.: 54.10%] [G loss: 0.793874]
8/8 [==============================] - 0s 5ms/step
1967 [D loss: 0.663203, acc.: 61.33%] [G loss: 0.811814]
8/8 [==============================] - 0s 7ms/step
1968 [D loss: 0.670139, acc.: 58.40%] [G loss: 0.793952]
8/8 [==============================] - 0s 5ms/step
1969 [D loss: 0.674478, acc.: 58.40%] [G loss: 0.798615]
8/8 [==============================] - 0s 4ms/step
1970 [D loss: 0.678815, acc.: 56.05%] [G loss: 0.790223]
8/8 [==============================] - 0s 5ms/step
1971 [D loss: 0.695249, acc.: 51.56%] [G loss: 0.787436]
8/8 [==============================] - 0s 6ms/step
1972 [D loss: 0.674863, acc.: 58.01%] [G loss: 0.762889]
8/8 [==============================] - 0s 5ms/step
1973 [D loss: 0.689571, acc.: 53.71%] [G loss: 0.789640]
8/8 [==============================] - 0s 5ms/step
1974 [D loss: 0.707522, acc.: 49.61%] [G loss: 0.758381]
8/8 [==============================] - 0s 5ms/step
1975 [D loss: 0.702216, acc.: 51.95%] [G loss: 0.764635]
8/8 [==============================] - 0s 4ms/step
1976 [D loss: 0.699153, acc.: 50.00%] [G loss: 0.767582]
8/8 [==============================] - 0s 5ms/step
1977 [D loss: 0.683694, acc.: 54.88%] [G loss: 0.780222]
8/8 [==============================] - 0s 5ms/step
1978 [D loss: 0.683715, acc.: 56.25%] [G loss: 0.774511]
8/8 [==============================] - 0s 5ms/step
1979 [D loss: 0.669817, acc.: 59.18%] [G loss: 0.770704]
8/8 [==============================] - 0s 5ms/step
1980 [D loss: 0.669971, acc.: 59.18%] [G loss: 0.792755]
8/8 [==============================] - 0s 5ms/step
1981 [D loss: 0.664307, acc.: 62.70%] [G loss: 0.773882]
8/8 [==============================] - 0s 5ms/step
1982 [D loss: 0.682917, acc.: 54.49%] [G loss: 0.785983]
8/8 [==============================] - 0s 5ms/step
1983 [D loss: 0.672354, acc.: 58.40%] [G loss: 0.779946]
8/8 [==============================] - 0s 5ms/step
1984 [D loss: 0.679566, acc.: 57.23%] [G loss: 0.757079]
8/8 [==============================] - 0s 5ms/step
1985 [D loss: 0.676954, acc.: 56.05%] [G loss: 0.764449]
8/8 [==============================] - 0s 5ms/step
1986 [D loss: 0.698273, acc.: 51.76%] [G loss: 0.752564]
8/8 [==============================] - 0s 5ms/step
1987 [D loss: 0.684889, acc.: 54.88%] [G loss: 0.771453]
8/8 [==============================] - 0s 4ms/step
1988 [D loss: 0.695964, acc.: 52.34%] [G loss: 0.776901]
8/8 [==============================] - 0s 5ms/step
1989 [D loss: 0.683891, acc.: 53.71%] [G loss: 0.771535]
8/8 [==============================] - 0s 5ms/step
1990 [D loss: 0.705542, acc.: 47.27%] [G loss: 0.784584]
8/8 [==============================] - 0s 5ms/step
1991 [D loss: 0.678022, acc.: 56.45%] [G loss: 0.799222]
8/8 [==============================] - 0s 5ms/step
1992 [D loss: 0.680693, acc.: 56.84%] [G loss: 0.793734]
8/8 [==============================] - 0s 5ms/step
1993 [D loss: 0.680950, acc.: 54.49%] [G loss: 0.797225]
8/8 [==============================] - 0s 5ms/step
1994 [D loss: 0.675482, acc.: 55.86%] [G loss: 0.784030]
8/8 [==============================] - 0s 4ms/step
1995 [D loss: 0.672679, acc.: 57.23%] [G loss: 0.808930]
8/8 [==============================] - 0s 5ms/step
1996 [D loss: 0.675564, acc.: 54.88%] [G loss: 0.805547]
8/8 [==============================] - 0s 5ms/step
1997 [D loss: 0.671259, acc.: 57.81%] [G loss: 0.798410]
8/8 [==============================] - 0s 5ms/step
1998 [D loss: 0.677815, acc.: 59.96%] [G loss: 0.759315]
8/8 [==============================] - 0s 5ms/step
1999 [D loss: 0.684413, acc.: 55.66%] [G loss: 0.791694]
8/8 [==============================] - 0s 5ms/step
2000 [D loss: 0.703786, acc.: 52.34%] [G loss: 0.763074]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 5ms/step
2001 [D loss: 0.706750, acc.: 53.71%] [G loss: 0.766502]
8/8 [==============================] - 0s 5ms/step
2002 [D loss: 0.694830, acc.: 51.95%] [G loss: 0.763944]
8/8 [==============================] - 0s 5ms/step
2003 [D loss: 0.704916, acc.: 52.93%] [G loss: 0.773874]
8/8 [==============================] - 0s 4ms/step
2004 [D loss: 0.697995, acc.: 50.98%] [G loss: 0.785462]
8/8 [==============================] - 0s 5ms/step
2005 [D loss: 0.684283, acc.: 54.49%] [G loss: 0.789079]
8/8 [==============================] - 0s 7ms/step
2006 [D loss: 0.678319, acc.: 56.64%] [G loss: 0.797223]
8/8 [==============================] - 0s 5ms/step
2007 [D loss: 0.679598, acc.: 55.27%] [G loss: 0.819895]
8/8 [==============================] - 0s 5ms/step
2008 [D loss: 0.675535, acc.: 57.62%] [G loss: 0.787456]
8/8 [==============================] - 0s 5ms/step
2009 [D loss: 0.657431, acc.: 64.06%] [G loss: 0.804435]
8/8 [==============================] - 0s 5ms/step
2010 [D loss: 0.659280, acc.: 61.33%] [G loss: 0.794301]
8/8 [==============================] - 0s 5ms/step
2011 [D loss: 0.680377, acc.: 58.20%] [G loss: 0.746370]
8/8 [==============================] - 0s 5ms/step
2012 [D loss: 0.685700, acc.: 54.30%] [G loss: 0.758884]
8/8 [==============================] - 0s 5ms/step
2013 [D loss: 0.699855, acc.: 53.71%] [G loss: 0.729489]
8/8 [==============================] - 0s 7ms/step
2014 [D loss: 0.714230, acc.: 49.41%] [G loss: 0.723527]
8/8 [==============================] - 0s 5ms/step
2015 [D loss: 0.714890, acc.: 47.27%] [G loss: 0.757504]
8/8 [==============================] - 0s 5ms/step
2016 [D loss: 0.693799, acc.: 49.02%] [G loss: 0.781645]
8/8 [==============================] - 0s 5ms/step
2017 [D loss: 0.697235, acc.: 51.95%] [G loss: 0.813764]
8/8 [==============================] - 0s 6ms/step
2018 [D loss: 0.696701, acc.: 50.39%] [G loss: 0.813600]
8/8 [==============================] - 0s 5ms/step
2019 [D loss: 0.684294, acc.: 58.20%] [G loss: 0.820285]
8/8 [==============================] - 0s 5ms/step
2020 [D loss: 0.677270, acc.: 57.23%] [G loss: 0.828792]
8/8 [==============================] - 0s 5ms/step
2021 [D loss: 0.670586, acc.: 60.94%] [G loss: 0.792253]
8/8 [==============================] - 0s 5ms/step
2022 [D loss: 0.679422, acc.: 57.42%] [G loss: 0.805138]
8/8 [==============================] - 0s 5ms/step
2023 [D loss: 0.663883, acc.: 63.67%] [G loss: 0.799860]
8/8 [==============================] - 0s 5ms/step
2024 [D loss: 0.652343, acc.: 64.45%] [G loss: 0.789937]
8/8 [==============================] - 0s 5ms/step
2025 [D loss: 0.658983, acc.: 59.57%] [G loss: 0.772986]
8/8 [==============================] - 0s 5ms/step
2026 [D loss: 0.682086, acc.: 56.45%] [G loss: 0.768264]
8/8 [==============================] - 0s 5ms/step
2027 [D loss: 0.705691, acc.: 50.78%] [G loss: 0.728098]
8/8 [==============================] - 0s 5ms/step
2028 [D loss: 0.703169, acc.: 51.17%] [G loss: 0.725912]
8/8 [==============================] - 0s 5ms/step
2029 [D loss: 0.707246, acc.: 48.63%] [G loss: 0.764065]
8/8 [==============================] - 0s 5ms/step
2030 [D loss: 0.699218, acc.: 51.17%] [G loss: 0.787357]
8/8 [==============================] - 0s 5ms/step
2031 [D loss: 0.697734, acc.: 53.91%] [G loss: 0.851217]
8/8 [==============================] - 0s 5ms/step
2032 [D loss: 0.680738, acc.: 53.52%] [G loss: 0.859935]
8/8 [==============================] - 0s 5ms/step
2033 [D loss: 0.688829, acc.: 52.34%] [G loss: 0.832798]
8/8 [==============================] - 0s 5ms/step
2034 [D loss: 0.685200, acc.: 52.54%] [G loss: 0.808630]
8/8 [==============================] - 0s 5ms/step
2035 [D loss: 0.683947, acc.: 57.42%] [G loss: 0.802211]
8/8 [==============================] - 0s 5ms/step
2036 [D loss: 0.667188, acc.: 61.13%] [G loss: 0.820970]
8/8 [==============================] - 0s 5ms/step
2037 [D loss: 0.669866, acc.: 60.55%] [G loss: 0.800604]
8/8 [==============================] - 0s 5ms/step
2038 [D loss: 0.663062, acc.: 60.35%] [G loss: 0.806894]
8/8 [==============================] - 0s 5ms/step
2039 [D loss: 0.658422, acc.: 64.84%] [G loss: 0.772880]
8/8 [==============================] - 0s 5ms/step
2040 [D loss: 0.676503, acc.: 54.49%] [G loss: 0.754228]
8/8 [==============================] - 0s 5ms/step
2041 [D loss: 0.671248, acc.: 58.40%] [G loss: 0.721974]
8/8 [==============================] - 0s 5ms/step
2042 [D loss: 0.696891, acc.: 51.76%] [G loss: 0.732609]
8/8 [==============================] - 0s 5ms/step
2043 [D loss: 0.710464, acc.: 47.66%] [G loss: 0.727236]
8/8 [==============================] - 0s 5ms/step
2044 [D loss: 0.691707, acc.: 54.88%] [G loss: 0.741563]
8/8 [==============================] - 0s 5ms/step
2045 [D loss: 0.684969, acc.: 56.25%] [G loss: 0.849825]
8/8 [==============================] - 0s 5ms/step
2046 [D loss: 0.683547, acc.: 57.23%] [G loss: 0.840501]
8/8 [==============================] - 0s 6ms/step
2047 [D loss: 0.685147, acc.: 55.27%] [G loss: 0.857425]
8/8 [==============================] - 0s 5ms/step
2048 [D loss: 0.691966, acc.: 55.27%] [G loss: 0.841278]
8/8 [==============================] - 0s 5ms/step
2049 [D loss: 0.690555, acc.: 51.95%] [G loss: 0.783139]
8/8 [==============================] - 0s 5ms/step
2050 [D loss: 0.692378, acc.: 54.30%] [G loss: 0.759310]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 5ms/step
2051 [D loss: 0.682835, acc.: 56.45%] [G loss: 0.772609]
8/8 [==============================] - 0s 5ms/step
2052 [D loss: 0.675898, acc.: 59.38%] [G loss: 0.769357]
8/8 [==============================] - 0s 5ms/step
2053 [D loss: 0.679062, acc.: 56.64%] [G loss: 0.773324]
8/8 [==============================] - 0s 5ms/step
2054 [D loss: 0.671015, acc.: 55.66%] [G loss: 0.785443]
8/8 [==============================] - 0s 5ms/step
2055 [D loss: 0.677388, acc.: 57.03%] [G loss: 0.749221]
8/8 [==============================] - 0s 4ms/step
2056 [D loss: 0.690756, acc.: 53.52%] [G loss: 0.723001]
8/8 [==============================] - 0s 5ms/step
2057 [D loss: 0.693104, acc.: 53.32%] [G loss: 0.716877]
8/8 [==============================] - 0s 5ms/step
2058 [D loss: 0.706079, acc.: 50.59%] [G loss: 0.724399]
8/8 [==============================] - 0s 5ms/step
2059 [D loss: 0.690625, acc.: 51.95%] [G loss: 0.787032]
8/8 [==============================] - 0s 5ms/step
2060 [D loss: 0.688759, acc.: 56.25%] [G loss: 0.811019]
8/8 [==============================] - 0s 5ms/step
2061 [D loss: 0.679435, acc.: 52.34%] [G loss: 0.837376]
8/8 [==============================] - 0s 5ms/step
2062 [D loss: 0.681656, acc.: 56.45%] [G loss: 0.841033]
8/8 [==============================] - 0s 5ms/step
2063 [D loss: 0.685603, acc.: 55.47%] [G loss: 0.798873]
8/8 [==============================] - 0s 5ms/step
2064 [D loss: 0.687487, acc.: 56.64%] [G loss: 0.771768]
8/8 [==============================] - 0s 5ms/step
2065 [D loss: 0.675500, acc.: 58.59%] [G loss: 0.768791]
8/8 [==============================] - 0s 5ms/step
2066 [D loss: 0.667907, acc.: 62.70%] [G loss: 0.766511]
8/8 [==============================] - 0s 5ms/step
2067 [D loss: 0.670455, acc.: 58.59%] [G loss: 0.740062]
8/8 [==============================] - 0s 4ms/step
2068 [D loss: 0.669637, acc.: 58.40%] [G loss: 0.751370]
8/8 [==============================] - 0s 4ms/step
2069 [D loss: 0.663460, acc.: 61.13%] [G loss: 0.734266]
8/8 [==============================] - 0s 4ms/step
2070 [D loss: 0.695246, acc.: 54.88%] [G loss: 0.738464]
8/8 [==============================] - 0s 5ms/step
2071 [D loss: 0.700111, acc.: 52.54%] [G loss: 0.725385]
8/8 [==============================] - 0s 5ms/step
2072 [D loss: 0.698520, acc.: 50.98%] [G loss: 0.748369]
8/8 [==============================] - 0s 5ms/step
2073 [D loss: 0.707381, acc.: 48.05%] [G loss: 0.748215]
8/8 [==============================] - 0s 5ms/step
2074 [D loss: 0.702766, acc.: 50.78%] [G loss: 0.790467]
8/8 [==============================] - 0s 5ms/step
2075 [D loss: 0.690487, acc.: 52.73%] [G loss: 0.807579]
8/8 [==============================] - 0s 5ms/step
2076 [D loss: 0.674955, acc.: 60.94%] [G loss: 0.823602]
8/8 [==============================] - 0s 5ms/step
2077 [D loss: 0.673467, acc.: 56.05%] [G loss: 0.817677]
8/8 [==============================] - 0s 5ms/step
2078 [D loss: 0.683345, acc.: 53.91%] [G loss: 0.823339]
8/8 [==============================] - 0s 5ms/step
2079 [D loss: 0.671698, acc.: 63.28%] [G loss: 0.788563]
8/8 [==============================] - 0s 4ms/step
2080 [D loss: 0.679961, acc.: 57.81%] [G loss: 0.766683]
8/8 [==============================] - 0s 5ms/step
2081 [D loss: 0.681418, acc.: 58.40%] [G loss: 0.785713]
8/8 [==============================] - 0s 5ms/step
2082 [D loss: 0.667886, acc.: 58.01%] [G loss: 0.748461]
8/8 [==============================] - 0s 5ms/step
2083 [D loss: 0.679431, acc.: 58.59%] [G loss: 0.766369]
8/8 [==============================] - 0s 5ms/step
2084 [D loss: 0.692489, acc.: 54.30%] [G loss: 0.732405]
8/8 [==============================] - 0s 5ms/step
2085 [D loss: 0.690341, acc.: 55.47%] [G loss: 0.730871]
8/8 [==============================] - 0s 4ms/step
2086 [D loss: 0.695342, acc.: 52.15%] [G loss: 0.745935]
8/8 [==============================] - 0s 5ms/step
2087 [D loss: 0.696328, acc.: 50.39%] [G loss: 0.771208]
8/8 [==============================] - 0s 5ms/step
2088 [D loss: 0.689851, acc.: 53.71%] [G loss: 0.787590]
8/8 [==============================] - 0s 5ms/step
2089 [D loss: 0.686914, acc.: 52.54%] [G loss: 0.815059]
8/8 [==============================] - 0s 5ms/step
2090 [D loss: 0.677840, acc.: 54.30%] [G loss: 0.822409]
8/8 [==============================] - 0s 5ms/step
2091 [D loss: 0.685169, acc.: 53.71%] [G loss: 0.801245]
8/8 [==============================] - 0s 5ms/step
2092 [D loss: 0.691123, acc.: 50.78%] [G loss: 0.814996]
8/8 [==============================] - 0s 6ms/step
2093 [D loss: 0.693539, acc.: 54.49%] [G loss: 0.773717]
8/8 [==============================] - 0s 5ms/step
2094 [D loss: 0.677862, acc.: 58.79%] [G loss: 0.756782]
8/8 [==============================] - 0s 5ms/step
2095 [D loss: 0.687342, acc.: 55.08%] [G loss: 0.755588]
8/8 [==============================] - 0s 5ms/step
2096 [D loss: 0.685081, acc.: 55.27%] [G loss: 0.732438]
8/8 [==============================] - 0s 5ms/step
2097 [D loss: 0.675406, acc.: 58.98%] [G loss: 0.737938]
8/8 [==============================] - 0s 5ms/step
2098 [D loss: 0.681507, acc.: 57.62%] [G loss: 0.744229]
8/8 [==============================] - 0s 4ms/step
2099 [D loss: 0.681930, acc.: 55.08%] [G loss: 0.742452]
8/8 [==============================] - 0s 4ms/step
2100 [D loss: 0.683177, acc.: 57.23%] [G loss: 0.741222]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 5ms/step
2101 [D loss: 0.678672, acc.: 55.66%] [G loss: 0.738664]
8/8 [==============================] - 0s 5ms/step
2102 [D loss: 0.675051, acc.: 58.98%] [G loss: 0.770612]
8/8 [==============================] - 0s 5ms/step
2103 [D loss: 0.678124, acc.: 58.40%] [G loss: 0.786331]
8/8 [==============================] - 0s 5ms/step
2104 [D loss: 0.689518, acc.: 54.69%] [G loss: 0.775158]
8/8 [==============================] - 0s 5ms/step
2105 [D loss: 0.698429, acc.: 49.80%] [G loss: 0.771106]
8/8 [==============================] - 0s 5ms/step
2106 [D loss: 0.686283, acc.: 57.03%] [G loss: 0.767059]
8/8 [==============================] - 0s 5ms/step
2107 [D loss: 0.695349, acc.: 52.54%] [G loss: 0.743970]
8/8 [==============================] - 0s 5ms/step
2108 [D loss: 0.692955, acc.: 55.08%] [G loss: 0.763706]
8/8 [==============================] - 0s 5ms/step
2109 [D loss: 0.686236, acc.: 54.88%] [G loss: 0.765553]
8/8 [==============================] - 0s 5ms/step
2110 [D loss: 0.679603, acc.: 56.84%] [G loss: 0.766017]
8/8 [==============================] - 0s 5ms/step
2111 [D loss: 0.683452, acc.: 56.25%] [G loss: 0.761445]
8/8 [==============================] - 0s 5ms/step
2112 [D loss: 0.675509, acc.: 57.42%] [G loss: 0.753147]
8/8 [==============================] - 0s 5ms/step
2113 [D loss: 0.680030, acc.: 55.27%] [G loss: 0.747181]
8/8 [==============================] - 0s 5ms/step
2114 [D loss: 0.677147, acc.: 56.25%] [G loss: 0.748473]
8/8 [==============================] - 0s 5ms/step
2115 [D loss: 0.686853, acc.: 52.54%] [G loss: 0.768843]
8/8 [==============================] - 0s 5ms/step
2116 [D loss: 0.679357, acc.: 59.18%] [G loss: 0.772902]
8/8 [==============================] - 0s 4ms/step
2117 [D loss: 0.683901, acc.: 53.52%] [G loss: 0.796154]
8/8 [==============================] - 0s 5ms/step
2118 [D loss: 0.687917, acc.: 52.15%] [G loss: 0.814364]
8/8 [==============================] - 0s 5ms/step
2119 [D loss: 0.694623, acc.: 52.54%] [G loss: 0.793911]
8/8 [==============================] - 0s 5ms/step
2120 [D loss: 0.701756, acc.: 51.17%] [G loss: 0.787538]
8/8 [==============================] - 0s 5ms/step
2121 [D loss: 0.699407, acc.: 51.17%] [G loss: 0.764572]
8/8 [==============================] - 0s 5ms/step
2122 [D loss: 0.699172, acc.: 50.98%] [G loss: 0.757663]
8/8 [==============================] - 0s 5ms/step
2123 [D loss: 0.684963, acc.: 57.62%] [G loss: 0.767300]
8/8 [==============================] - 0s 5ms/step
2124 [D loss: 0.681415, acc.: 58.20%] [G loss: 0.753964]
8/8 [==============================] - 0s 5ms/step
2125 [D loss: 0.676464, acc.: 58.20%] [G loss: 0.776469]
8/8 [==============================] - 0s 5ms/step
2126 [D loss: 0.678826, acc.: 57.62%] [G loss: 0.773258]
8/8 [==============================] - 0s 5ms/step
2127 [D loss: 0.671270, acc.: 59.77%] [G loss: 0.756776]
8/8 [==============================] - 0s 5ms/step
2128 [D loss: 0.674781, acc.: 58.59%] [G loss: 0.745066]
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2129 [D loss: 0.670195, acc.: 57.81%] [G loss: 0.759196]
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2130 [D loss: 0.679655, acc.: 57.23%] [G loss: 0.718893]
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2131 [D loss: 0.690432, acc.: 49.80%] [G loss: 0.761379]
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2132 [D loss: 0.696205, acc.: 51.17%] [G loss: 0.751411]
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2133 [D loss: 0.694855, acc.: 52.34%] [G loss: 0.763585]
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2134 [D loss: 0.700653, acc.: 50.20%] [G loss: 0.766794]
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2135 [D loss: 0.689820, acc.: 55.27%] [G loss: 0.772677]
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2136 [D loss: 0.706379, acc.: 48.83%] [G loss: 0.767780]
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2137 [D loss: 0.694308, acc.: 52.93%] [G loss: 0.776518]
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2138 [D loss: 0.699854, acc.: 49.02%] [G loss: 0.772392]
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2139 [D loss: 0.688810, acc.: 56.05%] [G loss: 0.780875]
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2140 [D loss: 0.671136, acc.: 60.74%] [G loss: 0.765499]
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2141 [D loss: 0.672773, acc.: 57.81%] [G loss: 0.765800]
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2142 [D loss: 0.676079, acc.: 57.62%] [G loss: 0.770926]
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2143 [D loss: 0.669169, acc.: 60.16%] [G loss: 0.762147]
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2144 [D loss: 0.685436, acc.: 53.52%] [G loss: 0.755311]
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2145 [D loss: 0.689634, acc.: 52.73%] [G loss: 0.759551]
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2146 [D loss: 0.689142, acc.: 55.66%] [G loss: 0.782181]
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2147 [D loss: 0.692297, acc.: 52.15%] [G loss: 0.797920]
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2148 [D loss: 0.688915, acc.: 53.52%] [G loss: 0.784520]
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2149 [D loss: 0.692768, acc.: 55.08%] [G loss: 0.796948]
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2150 [D loss: 0.702297, acc.: 53.71%] [G loss: 0.782236]
1/1 [==============================] - 0s 17ms/step
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2151 [D loss: 0.690077, acc.: 55.08%] [G loss: 0.793558]
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2152 [D loss: 0.675684, acc.: 61.13%] [G loss: 0.766548]
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2153 [D loss: 0.670643, acc.: 60.94%] [G loss: 0.783356]
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2154 [D loss: 0.669255, acc.: 61.52%] [G loss: 0.765609]
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2155 [D loss: 0.673243, acc.: 62.50%] [G loss: 0.782143]
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2156 [D loss: 0.676902, acc.: 59.96%] [G loss: 0.756696]
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2157 [D loss: 0.683506, acc.: 54.30%] [G loss: 0.761482]
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2158 [D loss: 0.678909, acc.: 54.88%] [G loss: 0.753724]
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2159 [D loss: 0.678407, acc.: 54.88%] [G loss: 0.757549]
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2160 [D loss: 0.689210, acc.: 54.88%] [G loss: 0.772001]
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2161 [D loss: 0.678986, acc.: 58.98%] [G loss: 0.789915]
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2162 [D loss: 0.679913, acc.: 60.55%] [G loss: 0.818433]
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2163 [D loss: 0.704408, acc.: 51.95%] [G loss: 0.802971]
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2164 [D loss: 0.701244, acc.: 51.95%] [G loss: 0.773306]
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2165 [D loss: 0.694684, acc.: 55.08%] [G loss: 0.766789]
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2166 [D loss: 0.691881, acc.: 51.37%] [G loss: 0.764961]
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2167 [D loss: 0.693734, acc.: 50.39%] [G loss: 0.750903]
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2168 [D loss: 0.679098, acc.: 56.45%] [G loss: 0.767798]
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2169 [D loss: 0.668331, acc.: 60.55%] [G loss: 0.758458]
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2170 [D loss: 0.664907, acc.: 59.77%] [G loss: 0.764267]
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2171 [D loss: 0.670551, acc.: 56.45%] [G loss: 0.757973]
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2172 [D loss: 0.676233, acc.: 58.98%] [G loss: 0.765004]
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2173 [D loss: 0.677296, acc.: 57.62%] [G loss: 0.775127]
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2174 [D loss: 0.683898, acc.: 55.86%] [G loss: 0.782370]
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2175 [D loss: 0.693920, acc.: 51.17%] [G loss: 0.801513]
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2176 [D loss: 0.671304, acc.: 58.40%] [G loss: 0.791087]
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2177 [D loss: 0.688207, acc.: 56.25%] [G loss: 0.822193]
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2178 [D loss: 0.687498, acc.: 53.12%] [G loss: 0.789245]
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2179 [D loss: 0.703144, acc.: 50.59%] [G loss: 0.762738]
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2180 [D loss: 0.692737, acc.: 55.27%] [G loss: 0.759470]
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2181 [D loss: 0.691094, acc.: 54.30%] [G loss: 0.760572]
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2182 [D loss: 0.684956, acc.: 54.88%] [G loss: 0.754468]
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2183 [D loss: 0.687564, acc.: 54.10%] [G loss: 0.753378]
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2184 [D loss: 0.669865, acc.: 57.81%] [G loss: 0.760653]
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2185 [D loss: 0.664549, acc.: 59.77%] [G loss: 0.757419]
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2186 [D loss: 0.669120, acc.: 58.01%] [G loss: 0.781169]
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2187 [D loss: 0.683761, acc.: 55.47%] [G loss: 0.798701]
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2188 [D loss: 0.675269, acc.: 57.62%] [G loss: 0.806241]
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2189 [D loss: 0.689467, acc.: 52.93%] [G loss: 0.794137]
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2190 [D loss: 0.690339, acc.: 50.78%] [G loss: 0.764583]
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2191 [D loss: 0.689611, acc.: 53.32%] [G loss: 0.770334]
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2192 [D loss: 0.700974, acc.: 48.83%] [G loss: 0.750616]
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2193 [D loss: 0.704085, acc.: 48.63%] [G loss: 0.744015]
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2194 [D loss: 0.700417, acc.: 51.56%] [G loss: 0.747345]
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2195 [D loss: 0.694503, acc.: 52.54%] [G loss: 0.764759]
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2196 [D loss: 0.698515, acc.: 51.95%] [G loss: 0.773967]
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2197 [D loss: 0.674063, acc.: 57.42%] [G loss: 0.774323]
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2198 [D loss: 0.665793, acc.: 58.01%] [G loss: 0.770732]
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2199 [D loss: 0.663242, acc.: 60.55%] [G loss: 0.807328]
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2200 [D loss: 0.662487, acc.: 61.72%] [G loss: 0.791003]
1/1 [==============================] - 0s 17ms/step
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2201 [D loss: 0.672594, acc.: 57.42%] [G loss: 0.813800]
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2202 [D loss: 0.678842, acc.: 56.45%] [G loss: 0.813453]
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2203 [D loss: 0.658509, acc.: 61.91%] [G loss: 0.800787]
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2204 [D loss: 0.668419, acc.: 59.77%] [G loss: 0.784818]
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2205 [D loss: 0.676952, acc.: 56.25%] [G loss: 0.787130]
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2206 [D loss: 0.691943, acc.: 53.32%] [G loss: 0.761813]
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2207 [D loss: 0.715249, acc.: 48.63%] [G loss: 0.779057]
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2208 [D loss: 0.698726, acc.: 53.32%] [G loss: 0.754060]
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2209 [D loss: 0.715512, acc.: 46.09%] [G loss: 0.778395]
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2210 [D loss: 0.695808, acc.: 48.24%] [G loss: 0.777614]
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2211 [D loss: 0.696003, acc.: 51.56%] [G loss: 0.785379]
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2212 [D loss: 0.695386, acc.: 49.61%] [G loss: 0.798851]
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2213 [D loss: 0.683758, acc.: 58.59%] [G loss: 0.790210]
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2214 [D loss: 0.678343, acc.: 58.59%] [G loss: 0.768899]
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2215 [D loss: 0.675858, acc.: 60.16%] [G loss: 0.769538]
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2216 [D loss: 0.664226, acc.: 62.89%] [G loss: 0.783366]
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2217 [D loss: 0.668390, acc.: 61.52%] [G loss: 0.774447]
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2218 [D loss: 0.680193, acc.: 57.23%] [G loss: 0.743572]
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2219 [D loss: 0.676187, acc.: 57.23%] [G loss: 0.758549]
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2220 [D loss: 0.680207, acc.: 54.88%] [G loss: 0.751637]
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2221 [D loss: 0.682197, acc.: 55.08%] [G loss: 0.758390]
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2222 [D loss: 0.679714, acc.: 57.62%] [G loss: 0.772232]
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2223 [D loss: 0.690817, acc.: 54.30%] [G loss: 0.810777]
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2224 [D loss: 0.687043, acc.: 51.37%] [G loss: 0.818483]
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2225 [D loss: 0.695182, acc.: 49.22%] [G loss: 0.792110]
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2226 [D loss: 0.704711, acc.: 48.63%] [G loss: 0.797075]
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2227 [D loss: 0.693329, acc.: 53.52%] [G loss: 0.778917]
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2228 [D loss: 0.699142, acc.: 51.56%] [G loss: 0.751437]
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2229 [D loss: 0.682280, acc.: 54.69%] [G loss: 0.771777]
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2230 [D loss: 0.673768, acc.: 58.40%] [G loss: 0.753954]
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2231 [D loss: 0.684421, acc.: 56.05%] [G loss: 0.766965]
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2232 [D loss: 0.683171, acc.: 56.45%] [G loss: 0.767305]
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2233 [D loss: 0.675623, acc.: 54.30%] [G loss: 0.799275]
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2234 [D loss: 0.681675, acc.: 57.03%] [G loss: 0.812392]
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2235 [D loss: 0.668603, acc.: 58.59%] [G loss: 0.815359]
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2236 [D loss: 0.675427, acc.: 56.64%] [G loss: 0.812696]
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2237 [D loss: 0.698611, acc.: 51.37%] [G loss: 0.800971]
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2238 [D loss: 0.705165, acc.: 49.61%] [G loss: 0.774206]
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2239 [D loss: 0.696240, acc.: 51.37%] [G loss: 0.762020]
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2240 [D loss: 0.708288, acc.: 50.20%] [G loss: 0.755969]
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2241 [D loss: 0.696824, acc.: 50.78%] [G loss: 0.758887]
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2242 [D loss: 0.690861, acc.: 53.32%] [G loss: 0.744790]
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2243 [D loss: 0.678877, acc.: 56.45%] [G loss: 0.759789]
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2244 [D loss: 0.679879, acc.: 58.79%] [G loss: 0.761296]
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2245 [D loss: 0.680203, acc.: 56.05%] [G loss: 0.772030]
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2246 [D loss: 0.682142, acc.: 55.08%] [G loss: 0.762245]
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2247 [D loss: 0.671344, acc.: 58.79%] [G loss: 0.771767]
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2248 [D loss: 0.673657, acc.: 58.20%] [G loss: 0.773259]
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2249 [D loss: 0.673424, acc.: 58.20%] [G loss: 0.772771]
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2250 [D loss: 0.683017, acc.: 55.27%] [G loss: 0.763733]
1/1 [==============================] - 0s 18ms/step
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2251 [D loss: 0.684458, acc.: 53.91%] [G loss: 0.753616]
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2252 [D loss: 0.689853, acc.: 51.76%] [G loss: 0.746782]
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2253 [D loss: 0.692858, acc.: 53.91%] [G loss: 0.750225]
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2254 [D loss: 0.684796, acc.: 55.86%] [G loss: 0.764890]
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2255 [D loss: 0.694164, acc.: 52.34%] [G loss: 0.775710]
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2256 [D loss: 0.693181, acc.: 50.20%] [G loss: 0.779538]
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2257 [D loss: 0.684857, acc.: 54.69%] [G loss: 0.778502]
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2258 [D loss: 0.671471, acc.: 60.74%] [G loss: 0.812835]
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2259 [D loss: 0.671041, acc.: 58.40%] [G loss: 0.807982]
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2260 [D loss: 0.668998, acc.: 60.94%] [G loss: 0.794530]
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2261 [D loss: 0.681436, acc.: 56.64%] [G loss: 0.813862]
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2262 [D loss: 0.681981, acc.: 53.71%] [G loss: 0.808482]
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2263 [D loss: 0.682038, acc.: 58.20%] [G loss: 0.795151]
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2264 [D loss: 0.682862, acc.: 55.27%] [G loss: 0.790705]
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2265 [D loss: 0.712425, acc.: 48.24%] [G loss: 0.763530]
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2266 [D loss: 0.701778, acc.: 49.61%] [G loss: 0.749697]
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2267 [D loss: 0.693650, acc.: 52.73%] [G loss: 0.768016]
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2268 [D loss: 0.701678, acc.: 47.66%] [G loss: 0.772677]
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2269 [D loss: 0.691522, acc.: 53.52%] [G loss: 0.774756]
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2270 [D loss: 0.683838, acc.: 53.52%] [G loss: 0.781631]
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2271 [D loss: 0.683239, acc.: 54.88%] [G loss: 0.787737]
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2272 [D loss: 0.667502, acc.: 63.28%] [G loss: 0.792778]
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2273 [D loss: 0.682749, acc.: 56.64%] [G loss: 0.770634]
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2274 [D loss: 0.683813, acc.: 58.79%] [G loss: 0.745212]
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2275 [D loss: 0.679170, acc.: 56.84%] [G loss: 0.751745]
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2276 [D loss: 0.684029, acc.: 57.23%] [G loss: 0.734164]
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2277 [D loss: 0.687120, acc.: 53.12%] [G loss: 0.749798]
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2278 [D loss: 0.691682, acc.: 52.93%] [G loss: 0.739351]
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2279 [D loss: 0.691325, acc.: 53.32%] [G loss: 0.744161]
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2280 [D loss: 0.710811, acc.: 48.63%] [G loss: 0.750343]
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2281 [D loss: 0.698167, acc.: 53.52%] [G loss: 0.783023]
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2282 [D loss: 0.688673, acc.: 51.76%] [G loss: 0.772572]
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2283 [D loss: 0.683183, acc.: 56.05%] [G loss: 0.806615]
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2284 [D loss: 0.685745, acc.: 54.30%] [G loss: 0.800853]
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2285 [D loss: 0.682878, acc.: 58.20%] [G loss: 0.788708]
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2286 [D loss: 0.678643, acc.: 58.59%] [G loss: 0.790264]
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2287 [D loss: 0.676832, acc.: 60.94%] [G loss: 0.785227]
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2288 [D loss: 0.699745, acc.: 52.54%] [G loss: 0.770486]
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2289 [D loss: 0.663980, acc.: 63.48%] [G loss: 0.756229]
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2290 [D loss: 0.672615, acc.: 58.98%] [G loss: 0.763817]
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2291 [D loss: 0.668088, acc.: 61.13%] [G loss: 0.742015]
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2292 [D loss: 0.665232, acc.: 58.59%] [G loss: 0.735534]
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2293 [D loss: 0.680587, acc.: 55.27%] [G loss: 0.732326]
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2294 [D loss: 0.713311, acc.: 47.07%] [G loss: 0.746197]
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2295 [D loss: 0.710144, acc.: 44.14%] [G loss: 0.774810]
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2296 [D loss: 0.685845, acc.: 52.54%] [G loss: 0.821455]
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2297 [D loss: 0.690966, acc.: 52.15%] [G loss: 0.855914]
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2298 [D loss: 0.696432, acc.: 52.34%] [G loss: 0.826825]
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2299 [D loss: 0.690172, acc.: 52.15%] [G loss: 0.793581]
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2300 [D loss: 0.686394, acc.: 56.64%] [G loss: 0.776956]
1/1 [==============================] - 0s 21ms/step
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2301 [D loss: 0.671627, acc.: 60.55%] [G loss: 0.786549]
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2302 [D loss: 0.679060, acc.: 58.59%] [G loss: 0.798116]
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2303 [D loss: 0.671122, acc.: 59.38%] [G loss: 0.787166]
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2304 [D loss: 0.661510, acc.: 59.77%] [G loss: 0.761262]
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2305 [D loss: 0.669925, acc.: 58.79%] [G loss: 0.730550]
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2306 [D loss: 0.690782, acc.: 51.76%] [G loss: 0.724253]
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2307 [D loss: 0.699123, acc.: 50.59%] [G loss: 0.722303]
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2308 [D loss: 0.688655, acc.: 52.73%] [G loss: 0.743532]
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2309 [D loss: 0.694175, acc.: 51.17%] [G loss: 0.779424]
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2310 [D loss: 0.686386, acc.: 53.52%] [G loss: 0.787149]
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2311 [D loss: 0.684406, acc.: 58.20%] [G loss: 0.813794]
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2312 [D loss: 0.693783, acc.: 54.88%] [G loss: 0.818041]
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2313 [D loss: 0.692839, acc.: 56.84%] [G loss: 0.825074]
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2314 [D loss: 0.707823, acc.: 47.66%] [G loss: 0.806046]
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2315 [D loss: 0.691083, acc.: 54.30%] [G loss: 0.792945]
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2316 [D loss: 0.681077, acc.: 60.16%] [G loss: 0.792571]
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2317 [D loss: 0.672017, acc.: 59.38%] [G loss: 0.796469]
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2318 [D loss: 0.659431, acc.: 60.16%] [G loss: 0.790137]
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2319 [D loss: 0.659998, acc.: 60.74%] [G loss: 0.796136]
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2320 [D loss: 0.655072, acc.: 61.72%] [G loss: 0.792455]
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2321 [D loss: 0.654252, acc.: 63.48%] [G loss: 0.755004]
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2322 [D loss: 0.687099, acc.: 54.88%] [G loss: 0.741327]
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2323 [D loss: 0.700141, acc.: 53.32%] [G loss: 0.706873]
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2324 [D loss: 0.702768, acc.: 53.12%] [G loss: 0.741217]
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2325 [D loss: 0.687554, acc.: 55.27%] [G loss: 0.774377]
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2326 [D loss: 0.685626, acc.: 50.00%] [G loss: 0.832808]
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2327 [D loss: 0.701232, acc.: 51.37%] [G loss: 0.836372]
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2328 [D loss: 0.697080, acc.: 51.95%] [G loss: 0.804938]
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2329 [D loss: 0.699762, acc.: 50.00%] [G loss: 0.790035]
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2330 [D loss: 0.710556, acc.: 51.37%] [G loss: 0.783238]
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2331 [D loss: 0.690796, acc.: 53.91%] [G loss: 0.773090]
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2332 [D loss: 0.679915, acc.: 57.03%] [G loss: 0.754936]
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2333 [D loss: 0.669661, acc.: 61.72%] [G loss: 0.767775]
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2334 [D loss: 0.682358, acc.: 55.66%] [G loss: 0.759524]
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2335 [D loss: 0.669952, acc.: 59.96%] [G loss: 0.767841]
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2336 [D loss: 0.674831, acc.: 57.42%] [G loss: 0.760546]
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2337 [D loss: 0.666594, acc.: 56.84%] [G loss: 0.772526]
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2338 [D loss: 0.695955, acc.: 51.95%] [G loss: 0.759381]
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2339 [D loss: 0.683480, acc.: 53.91%] [G loss: 0.749242]
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2340 [D loss: 0.684633, acc.: 55.27%] [G loss: 0.762427]
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2341 [D loss: 0.698979, acc.: 53.71%] [G loss: 0.782858]
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2342 [D loss: 0.693250, acc.: 53.52%] [G loss: 0.760890]
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2343 [D loss: 0.705135, acc.: 49.61%] [G loss: 0.743564]
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2344 [D loss: 0.706292, acc.: 48.63%] [G loss: 0.746596]
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2345 [D loss: 0.702336, acc.: 48.24%] [G loss: 0.757763]
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2346 [D loss: 0.688005, acc.: 54.69%] [G loss: 0.781901]
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2347 [D loss: 0.681560, acc.: 55.66%] [G loss: 0.787381]
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2348 [D loss: 0.668076, acc.: 58.79%] [G loss: 0.800362]
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2349 [D loss: 0.667668, acc.: 60.74%] [G loss: 0.823396]
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2350 [D loss: 0.674695, acc.: 56.64%] [G loss: 0.797294]
1/1 [==============================] - 0s 17ms/step
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2351 [D loss: 0.675541, acc.: 56.84%] [G loss: 0.816698]
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2352 [D loss: 0.680247, acc.: 54.49%] [G loss: 0.813790]
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2353 [D loss: 0.694600, acc.: 54.10%] [G loss: 0.790463]
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2354 [D loss: 0.702726, acc.: 50.78%] [G loss: 0.808291]
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2355 [D loss: 0.701921, acc.: 51.17%] [G loss: 0.765377]
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2356 [D loss: 0.699560, acc.: 50.00%] [G loss: 0.774348]
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2357 [D loss: 0.685317, acc.: 55.86%] [G loss: 0.774664]
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2358 [D loss: 0.702375, acc.: 51.76%] [G loss: 0.771443]
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2359 [D loss: 0.687369, acc.: 53.12%] [G loss: 0.765090]
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2360 [D loss: 0.688271, acc.: 54.88%] [G loss: 0.751601]
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2361 [D loss: 0.688652, acc.: 54.69%] [G loss: 0.741927]
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2362 [D loss: 0.670917, acc.: 59.96%] [G loss: 0.743983]
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2363 [D loss: 0.680552, acc.: 55.08%] [G loss: 0.755044]
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2364 [D loss: 0.666328, acc.: 59.57%] [G loss: 0.758461]
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2365 [D loss: 0.679177, acc.: 58.59%] [G loss: 0.766945]
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2366 [D loss: 0.679536, acc.: 58.59%] [G loss: 0.746310]
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2367 [D loss: 0.668847, acc.: 59.38%] [G loss: 0.760167]
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2368 [D loss: 0.682039, acc.: 55.08%] [G loss: 0.752990]
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2369 [D loss: 0.685813, acc.: 52.73%] [G loss: 0.738778]
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2370 [D loss: 0.696901, acc.: 51.37%] [G loss: 0.745654]
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2371 [D loss: 0.694952, acc.: 48.63%] [G loss: 0.757784]
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2372 [D loss: 0.702666, acc.: 50.39%] [G loss: 0.758067]
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2373 [D loss: 0.698991, acc.: 51.17%] [G loss: 0.761275]
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2374 [D loss: 0.694165, acc.: 53.12%] [G loss: 0.761834]
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2375 [D loss: 0.689077, acc.: 53.32%] [G loss: 0.755839]
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2376 [D loss: 0.691294, acc.: 50.78%] [G loss: 0.762188]
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2377 [D loss: 0.689878, acc.: 51.95%] [G loss: 0.768391]
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2378 [D loss: 0.681738, acc.: 56.45%] [G loss: 0.772576]
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2379 [D loss: 0.678372, acc.: 57.23%] [G loss: 0.775491]
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2380 [D loss: 0.663733, acc.: 59.57%] [G loss: 0.811310]
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2381 [D loss: 0.666116, acc.: 57.81%] [G loss: 0.804831]
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2382 [D loss: 0.679266, acc.: 55.66%] [G loss: 0.796772]
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2383 [D loss: 0.665083, acc.: 59.77%] [G loss: 0.791043]
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2384 [D loss: 0.678452, acc.: 56.45%] [G loss: 0.812843]
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2385 [D loss: 0.683902, acc.: 55.86%] [G loss: 0.785731]
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2386 [D loss: 0.697799, acc.: 52.73%] [G loss: 0.765642]
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2387 [D loss: 0.708832, acc.: 50.20%] [G loss: 0.764359]
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2388 [D loss: 0.700289, acc.: 49.61%] [G loss: 0.773486]
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2389 [D loss: 0.694799, acc.: 52.34%] [G loss: 0.765397]
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2390 [D loss: 0.702334, acc.: 48.83%] [G loss: 0.792436]
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2391 [D loss: 0.696537, acc.: 52.54%] [G loss: 0.793598]
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2392 [D loss: 0.685027, acc.: 57.62%] [G loss: 0.788354]
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2393 [D loss: 0.678388, acc.: 56.25%] [G loss: 0.800341]
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2394 [D loss: 0.663339, acc.: 63.09%] [G loss: 0.801812]
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2395 [D loss: 0.670111, acc.: 60.55%] [G loss: 0.793440]
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2396 [D loss: 0.674996, acc.: 57.42%] [G loss: 0.787657]
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2397 [D loss: 0.658696, acc.: 63.09%] [G loss: 0.781849]
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2398 [D loss: 0.655937, acc.: 62.70%] [G loss: 0.753700]
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2399 [D loss: 0.670556, acc.: 57.42%] [G loss: 0.732485]
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2400 [D loss: 0.678877, acc.: 56.84%] [G loss: 0.752785]
1/1 [==============================] - 0s 18ms/step
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2401 [D loss: 0.690812, acc.: 53.91%] [G loss: 0.717294]
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2402 [D loss: 0.702903, acc.: 50.98%] [G loss: 0.712704]
8/8 [==============================] - 0s 5ms/step
2403 [D loss: 0.725441, acc.: 46.09%] [G loss: 0.768001]
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2404 [D loss: 0.706513, acc.: 47.07%] [G loss: 0.795773]
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2405 [D loss: 0.693889, acc.: 52.15%] [G loss: 0.800557]
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2406 [D loss: 0.695267, acc.: 52.54%] [G loss: 0.834220]
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2407 [D loss: 0.692314, acc.: 57.03%] [G loss: 0.822584]
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2408 [D loss: 0.704918, acc.: 51.56%] [G loss: 0.813620]
8/8 [==============================] - 0s 5ms/step
2409 [D loss: 0.690996, acc.: 55.47%] [G loss: 0.806710]
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2410 [D loss: 0.680706, acc.: 55.66%] [G loss: 0.789635]
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2411 [D loss: 0.672991, acc.: 62.70%] [G loss: 0.778319]
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2412 [D loss: 0.668857, acc.: 59.96%] [G loss: 0.779703]
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2413 [D loss: 0.657147, acc.: 63.87%] [G loss: 0.762865]
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2414 [D loss: 0.663029, acc.: 59.38%] [G loss: 0.748286]
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2415 [D loss: 0.689689, acc.: 53.91%] [G loss: 0.741917]
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2416 [D loss: 0.705966, acc.: 49.22%] [G loss: 0.695435]
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2417 [D loss: 0.729385, acc.: 43.75%] [G loss: 0.709538]
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2418 [D loss: 0.726361, acc.: 43.95%] [G loss: 0.759351]
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2419 [D loss: 0.686660, acc.: 54.30%] [G loss: 0.839909]
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2420 [D loss: 0.666366, acc.: 58.40%] [G loss: 0.879695]
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2421 [D loss: 0.691040, acc.: 52.34%] [G loss: 0.821473]
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2422 [D loss: 0.685086, acc.: 54.69%] [G loss: 0.801828]
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2423 [D loss: 0.693199, acc.: 52.34%] [G loss: 0.759532]
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2424 [D loss: 0.688260, acc.: 55.86%] [G loss: 0.775836]
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2425 [D loss: 0.678689, acc.: 57.81%] [G loss: 0.769194]
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2426 [D loss: 0.667685, acc.: 58.20%] [G loss: 0.760034]
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2427 [D loss: 0.665961, acc.: 60.94%] [G loss: 0.763785]
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2428 [D loss: 0.679750, acc.: 55.66%] [G loss: 0.757207]
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2429 [D loss: 0.672622, acc.: 57.23%] [G loss: 0.726348]
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2430 [D loss: 0.688436, acc.: 55.27%] [G loss: 0.730346]
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2431 [D loss: 0.704114, acc.: 48.63%] [G loss: 0.719917]
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2432 [D loss: 0.690354, acc.: 55.86%] [G loss: 0.731121]
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2433 [D loss: 0.685862, acc.: 56.45%] [G loss: 0.789767]
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2434 [D loss: 0.686172, acc.: 55.27%] [G loss: 0.825350]
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2435 [D loss: 0.686111, acc.: 53.91%] [G loss: 0.820123]
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2436 [D loss: 0.713690, acc.: 44.14%] [G loss: 0.810954]
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2437 [D loss: 0.699563, acc.: 52.34%] [G loss: 0.784084]
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2438 [D loss: 0.703543, acc.: 50.59%] [G loss: 0.776622]
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2439 [D loss: 0.685634, acc.: 59.96%] [G loss: 0.764945]
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2440 [D loss: 0.682658, acc.: 55.47%] [G loss: 0.768503]
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2441 [D loss: 0.669762, acc.: 61.33%] [G loss: 0.771012]
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2442 [D loss: 0.664896, acc.: 59.57%] [G loss: 0.769168]
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2443 [D loss: 0.679441, acc.: 56.25%] [G loss: 0.750259]
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2444 [D loss: 0.673733, acc.: 58.20%] [G loss: 0.754212]
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2445 [D loss: 0.681851, acc.: 56.45%] [G loss: 0.750314]
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2446 [D loss: 0.676010, acc.: 58.20%] [G loss: 0.768436]
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2447 [D loss: 0.681621, acc.: 58.79%] [G loss: 0.774108]
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2448 [D loss: 0.689888, acc.: 57.23%] [G loss: 0.797695]
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2449 [D loss: 0.698795, acc.: 52.34%] [G loss: 0.803118]
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2450 [D loss: 0.695052, acc.: 50.78%] [G loss: 0.794830]
1/1 [==============================] - 0s 16ms/step
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2451 [D loss: 0.705270, acc.: 49.41%] [G loss: 0.769257]
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2452 [D loss: 0.697733, acc.: 50.98%] [G loss: 0.762922]
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2453 [D loss: 0.698790, acc.: 53.52%] [G loss: 0.764475]
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2454 [D loss: 0.675843, acc.: 57.62%] [G loss: 0.768355]
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2455 [D loss: 0.680684, acc.: 55.08%] [G loss: 0.767322]
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2456 [D loss: 0.675687, acc.: 59.96%] [G loss: 0.754934]
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2457 [D loss: 0.668499, acc.: 60.94%] [G loss: 0.758134]
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2458 [D loss: 0.673764, acc.: 56.64%] [G loss: 0.755895]
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2459 [D loss: 0.681150, acc.: 56.45%] [G loss: 0.743540]
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2460 [D loss: 0.689131, acc.: 54.10%] [G loss: 0.748349]
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2461 [D loss: 0.693849, acc.: 52.93%] [G loss: 0.754220]
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2462 [D loss: 0.702892, acc.: 51.37%] [G loss: 0.761890]
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2463 [D loss: 0.690009, acc.: 51.37%] [G loss: 0.774435]
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2464 [D loss: 0.690376, acc.: 50.59%] [G loss: 0.792872]
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2465 [D loss: 0.694326, acc.: 50.20%] [G loss: 0.785101]
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2466 [D loss: 0.701050, acc.: 47.66%] [G loss: 0.785352]
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2467 [D loss: 0.709070, acc.: 50.98%] [G loss: 0.761158]
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2468 [D loss: 0.679443, acc.: 58.79%] [G loss: 0.784997]
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2469 [D loss: 0.695037, acc.: 51.76%] [G loss: 0.758473]
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2470 [D loss: 0.690988, acc.: 52.15%] [G loss: 0.761805]
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2471 [D loss: 0.672868, acc.: 57.42%] [G loss: 0.760086]
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2472 [D loss: 0.678191, acc.: 57.23%] [G loss: 0.750061]
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2473 [D loss: 0.680659, acc.: 55.66%] [G loss: 0.766787]
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2474 [D loss: 0.675877, acc.: 58.59%] [G loss: 0.769181]
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2475 [D loss: 0.691806, acc.: 57.23%] [G loss: 0.766261]
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2476 [D loss: 0.691683, acc.: 52.15%] [G loss: 0.794335]
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2477 [D loss: 0.681079, acc.: 54.69%] [G loss: 0.812819]
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2478 [D loss: 0.691281, acc.: 53.71%] [G loss: 0.828504]
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2479 [D loss: 0.686902, acc.: 54.49%] [G loss: 0.791750]
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2480 [D loss: 0.697092, acc.: 52.73%] [G loss: 0.783941]
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2481 [D loss: 0.694135, acc.: 53.91%] [G loss: 0.776752]
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2482 [D loss: 0.697110, acc.: 50.78%] [G loss: 0.745687]
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2483 [D loss: 0.695254, acc.: 52.34%] [G loss: 0.746716]
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2484 [D loss: 0.695185, acc.: 51.37%] [G loss: 0.745333]
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2485 [D loss: 0.695524, acc.: 52.54%] [G loss: 0.738574]
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2486 [D loss: 0.683237, acc.: 55.08%] [G loss: 0.737672]
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2487 [D loss: 0.670945, acc.: 59.38%] [G loss: 0.756156]
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2488 [D loss: 0.677124, acc.: 58.01%] [G loss: 0.774873]
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2489 [D loss: 0.667278, acc.: 59.38%] [G loss: 0.776804]
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2490 [D loss: 0.676377, acc.: 57.03%] [G loss: 0.774314]
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2491 [D loss: 0.686465, acc.: 56.64%] [G loss: 0.765306]
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2492 [D loss: 0.691829, acc.: 53.71%] [G loss: 0.789604]
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2493 [D loss: 0.691109, acc.: 55.86%] [G loss: 0.758118]
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2494 [D loss: 0.688275, acc.: 51.17%] [G loss: 0.738582]
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2495 [D loss: 0.695078, acc.: 53.91%] [G loss: 0.749273]
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2496 [D loss: 0.698718, acc.: 53.52%] [G loss: 0.749192]
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2497 [D loss: 0.697943, acc.: 51.37%] [G loss: 0.735922]
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2498 [D loss: 0.707091, acc.: 49.41%] [G loss: 0.758244]
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2499 [D loss: 0.703912, acc.: 45.31%] [G loss: 0.748333]
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2500 [D loss: 0.696104, acc.: 48.63%] [G loss: 0.743866]
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2501 [D loss: 0.694027, acc.: 50.98%] [G loss: 0.761767]
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2502 [D loss: 0.686162, acc.: 51.95%] [G loss: 0.762252]
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2503 [D loss: 0.679199, acc.: 56.64%] [G loss: 0.755403]
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2504 [D loss: 0.683632, acc.: 56.25%] [G loss: 0.768814]
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2505 [D loss: 0.679612, acc.: 56.25%] [G loss: 0.768504]
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2506 [D loss: 0.672914, acc.: 61.91%] [G loss: 0.779730]
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2507 [D loss: 0.678615, acc.: 56.45%] [G loss: 0.786888]
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2508 [D loss: 0.693082, acc.: 53.91%] [G loss: 0.765579]
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2509 [D loss: 0.681330, acc.: 54.88%] [G loss: 0.760383]
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2510 [D loss: 0.685871, acc.: 55.86%] [G loss: 0.746381]
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2511 [D loss: 0.695148, acc.: 52.93%] [G loss: 0.753036]
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2512 [D loss: 0.696806, acc.: 52.34%] [G loss: 0.762458]
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2513 [D loss: 0.687951, acc.: 56.45%] [G loss: 0.770009]
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2514 [D loss: 0.690781, acc.: 53.32%] [G loss: 0.776467]
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2515 [D loss: 0.692098, acc.: 52.54%] [G loss: 0.772275]
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2516 [D loss: 0.698775, acc.: 50.59%] [G loss: 0.766557]
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2517 [D loss: 0.691425, acc.: 51.37%] [G loss: 0.756784]
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2518 [D loss: 0.681260, acc.: 56.05%] [G loss: 0.746088]
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2519 [D loss: 0.676278, acc.: 60.55%] [G loss: 0.768456]
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2520 [D loss: 0.687031, acc.: 51.56%] [G loss: 0.755231]
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2521 [D loss: 0.680198, acc.: 58.59%] [G loss: 0.747133]
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2522 [D loss: 0.682743, acc.: 59.18%] [G loss: 0.749534]
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2523 [D loss: 0.672950, acc.: 59.38%] [G loss: 0.763056]
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2524 [D loss: 0.688075, acc.: 52.15%] [G loss: 0.739955]
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2525 [D loss: 0.683679, acc.: 55.86%] [G loss: 0.742488]
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2526 [D loss: 0.691486, acc.: 54.10%] [G loss: 0.747599]
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2527 [D loss: 0.685007, acc.: 52.73%] [G loss: 0.771947]
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2528 [D loss: 0.694361, acc.: 53.32%] [G loss: 0.761319]
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2529 [D loss: 0.689884, acc.: 55.47%] [G loss: 0.763913]
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2530 [D loss: 0.676669, acc.: 56.25%] [G loss: 0.791874]
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2531 [D loss: 0.686604, acc.: 56.05%] [G loss: 0.769925]
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2532 [D loss: 0.702880, acc.: 53.12%] [G loss: 0.749354]
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2533 [D loss: 0.692238, acc.: 52.73%] [G loss: 0.734579]
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2534 [D loss: 0.699500, acc.: 49.02%] [G loss: 0.748060]
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2535 [D loss: 0.693894, acc.: 53.12%] [G loss: 0.736451]
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2536 [D loss: 0.687728, acc.: 51.95%] [G loss: 0.747812]
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2537 [D loss: 0.679130, acc.: 56.05%] [G loss: 0.756511]
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2538 [D loss: 0.688702, acc.: 54.30%] [G loss: 0.746035]
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2539 [D loss: 0.680736, acc.: 57.23%] [G loss: 0.772178]
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2540 [D loss: 0.688506, acc.: 53.91%] [G loss: 0.786959]
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2541 [D loss: 0.684242, acc.: 56.25%] [G loss: 0.798501]
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2542 [D loss: 0.684925, acc.: 55.47%] [G loss: 0.799614]
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2543 [D loss: 0.697878, acc.: 52.15%] [G loss: 0.794433]
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2544 [D loss: 0.689756, acc.: 56.84%] [G loss: 0.788056]
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2545 [D loss: 0.698563, acc.: 50.78%] [G loss: 0.776326]
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2546 [D loss: 0.699053, acc.: 51.56%] [G loss: 0.737281]
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2547 [D loss: 0.700426, acc.: 48.44%] [G loss: 0.729211]
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2548 [D loss: 0.691118, acc.: 54.69%] [G loss: 0.745826]
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2549 [D loss: 0.691635, acc.: 51.56%] [G loss: 0.734388]
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2550 [D loss: 0.694720, acc.: 52.34%] [G loss: 0.735636]
1/1 [==============================] - 0s 20ms/step
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2551 [D loss: 0.690686, acc.: 53.91%] [G loss: 0.750110]
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2552 [D loss: 0.701515, acc.: 51.17%] [G loss: 0.753596]
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2553 [D loss: 0.682825, acc.: 56.64%] [G loss: 0.761317]
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2554 [D loss: 0.683952, acc.: 54.49%] [G loss: 0.769281]
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2555 [D loss: 0.682876, acc.: 56.64%] [G loss: 0.754471]
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2556 [D loss: 0.694437, acc.: 53.71%] [G loss: 0.771694]
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2557 [D loss: 0.683845, acc.: 57.81%] [G loss: 0.757550]
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2558 [D loss: 0.685662, acc.: 54.49%] [G loss: 0.754806]
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2559 [D loss: 0.685011, acc.: 55.86%] [G loss: 0.758673]
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2560 [D loss: 0.692706, acc.: 54.30%] [G loss: 0.756301]
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2561 [D loss: 0.685859, acc.: 53.91%] [G loss: 0.751365]
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2562 [D loss: 0.690738, acc.: 51.17%] [G loss: 0.746257]
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2563 [D loss: 0.688394, acc.: 54.10%] [G loss: 0.745726]
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2564 [D loss: 0.679048, acc.: 54.88%] [G loss: 0.736251]
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2565 [D loss: 0.671819, acc.: 59.57%] [G loss: 0.751357]
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2566 [D loss: 0.686597, acc.: 55.86%] [G loss: 0.749283]
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2567 [D loss: 0.676554, acc.: 59.57%] [G loss: 0.741777]
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2568 [D loss: 0.702352, acc.: 50.98%] [G loss: 0.763114]
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2569 [D loss: 0.690425, acc.: 53.32%] [G loss: 0.803522]
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2570 [D loss: 0.683696, acc.: 56.05%] [G loss: 0.811042]
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2571 [D loss: 0.679281, acc.: 57.23%] [G loss: 0.802742]
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2572 [D loss: 0.685157, acc.: 55.08%] [G loss: 0.791394]
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2573 [D loss: 0.676037, acc.: 58.98%] [G loss: 0.764738]
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2574 [D loss: 0.698675, acc.: 49.61%] [G loss: 0.773262]
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2575 [D loss: 0.702075, acc.: 49.02%] [G loss: 0.760899]
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2576 [D loss: 0.699403, acc.: 51.76%] [G loss: 0.733054]
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2577 [D loss: 0.695755, acc.: 54.10%] [G loss: 0.729103]
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2578 [D loss: 0.685648, acc.: 54.88%] [G loss: 0.727722]
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2579 [D loss: 0.697194, acc.: 49.22%] [G loss: 0.728562]
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2580 [D loss: 0.691960, acc.: 50.59%] [G loss: 0.724015]
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2581 [D loss: 0.689321, acc.: 51.95%] [G loss: 0.717071]
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2582 [D loss: 0.694634, acc.: 49.61%] [G loss: 0.742688]
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2583 [D loss: 0.686265, acc.: 54.49%] [G loss: 0.779333]
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2584 [D loss: 0.671966, acc.: 58.20%] [G loss: 0.792171]
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2585 [D loss: 0.677759, acc.: 57.42%] [G loss: 0.802302]
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2586 [D loss: 0.667639, acc.: 61.13%] [G loss: 0.823709]
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2587 [D loss: 0.677345, acc.: 59.57%] [G loss: 0.803183]
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2588 [D loss: 0.678594, acc.: 58.20%] [G loss: 0.787182]
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2589 [D loss: 0.692360, acc.: 52.54%] [G loss: 0.756488]
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2590 [D loss: 0.685533, acc.: 54.49%] [G loss: 0.746210]
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2591 [D loss: 0.703205, acc.: 48.44%] [G loss: 0.739285]
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2592 [D loss: 0.702516, acc.: 50.39%] [G loss: 0.713370]
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2593 [D loss: 0.704183, acc.: 47.66%] [G loss: 0.715394]
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2594 [D loss: 0.704633, acc.: 48.83%] [G loss: 0.734604]
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2595 [D loss: 0.705359, acc.: 46.09%] [G loss: 0.737433]
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2596 [D loss: 0.693112, acc.: 50.98%] [G loss: 0.746774]
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2597 [D loss: 0.684991, acc.: 55.47%] [G loss: 0.778837]
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2598 [D loss: 0.678888, acc.: 58.20%] [G loss: 0.772844]
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2599 [D loss: 0.685499, acc.: 54.49%] [G loss: 0.780362]
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2600 [D loss: 0.676704, acc.: 59.57%] [G loss: 0.795754]
1/1 [==============================] - 0s 17ms/step
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2601 [D loss: 0.680270, acc.: 58.79%] [G loss: 0.776473]
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2602 [D loss: 0.679692, acc.: 56.64%] [G loss: 0.773463]
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2603 [D loss: 0.681537, acc.: 57.62%] [G loss: 0.764284]
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2604 [D loss: 0.685522, acc.: 55.47%] [G loss: 0.742430]
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2605 [D loss: 0.673158, acc.: 58.79%] [G loss: 0.739953]
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2606 [D loss: 0.687113, acc.: 53.52%] [G loss: 0.755006]
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2607 [D loss: 0.691709, acc.: 51.56%] [G loss: 0.758565]
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2608 [D loss: 0.695843, acc.: 52.54%] [G loss: 0.758061]
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2609 [D loss: 0.678512, acc.: 57.23%] [G loss: 0.780991]
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2610 [D loss: 0.688129, acc.: 54.88%] [G loss: 0.797577]
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2611 [D loss: 0.689632, acc.: 54.49%] [G loss: 0.804297]
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2612 [D loss: 0.688403, acc.: 56.25%] [G loss: 0.791197]
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2613 [D loss: 0.692310, acc.: 50.98%] [G loss: 0.780489]
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2614 [D loss: 0.696033, acc.: 52.93%] [G loss: 0.754989]
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2615 [D loss: 0.694464, acc.: 50.78%] [G loss: 0.756041]
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2616 [D loss: 0.689367, acc.: 54.69%] [G loss: 0.751612]
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2617 [D loss: 0.692857, acc.: 52.93%] [G loss: 0.743401]
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2618 [D loss: 0.677106, acc.: 57.81%] [G loss: 0.738040]
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2619 [D loss: 0.682608, acc.: 54.30%] [G loss: 0.753870]
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2620 [D loss: 0.674929, acc.: 59.96%] [G loss: 0.738307]
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2621 [D loss: 0.676615, acc.: 58.98%] [G loss: 0.740526]
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2622 [D loss: 0.674510, acc.: 56.05%] [G loss: 0.754388]
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2623 [D loss: 0.682717, acc.: 58.20%] [G loss: 0.749346]
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2624 [D loss: 0.690644, acc.: 54.49%] [G loss: 0.782770]
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2625 [D loss: 0.678180, acc.: 59.77%] [G loss: 0.790652]
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2626 [D loss: 0.687001, acc.: 51.95%] [G loss: 0.771892]
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2627 [D loss: 0.709411, acc.: 47.27%] [G loss: 0.729847]
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2628 [D loss: 0.708537, acc.: 47.07%] [G loss: 0.747659]
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2629 [D loss: 0.701519, acc.: 48.83%] [G loss: 0.746403]
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2630 [D loss: 0.690987, acc.: 52.54%] [G loss: 0.772245]
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2631 [D loss: 0.682408, acc.: 57.03%] [G loss: 0.755642]
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2632 [D loss: 0.671438, acc.: 59.18%] [G loss: 0.767235]
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2633 [D loss: 0.669493, acc.: 60.94%] [G loss: 0.766461]
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2634 [D loss: 0.674288, acc.: 60.55%] [G loss: 0.780710]
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2635 [D loss: 0.686878, acc.: 54.69%] [G loss: 0.780996]
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2636 [D loss: 0.679101, acc.: 57.23%] [G loss: 0.753530]
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2637 [D loss: 0.685050, acc.: 56.45%] [G loss: 0.762687]
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2638 [D loss: 0.689534, acc.: 55.66%] [G loss: 0.771516]
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2639 [D loss: 0.681583, acc.: 55.27%] [G loss: 0.736096]
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2640 [D loss: 0.687986, acc.: 53.91%] [G loss: 0.745026]
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2641 [D loss: 0.682129, acc.: 58.79%] [G loss: 0.751155]
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2642 [D loss: 0.687756, acc.: 56.25%] [G loss: 0.738130]
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2643 [D loss: 0.706702, acc.: 50.78%] [G loss: 0.735537]
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2644 [D loss: 0.677994, acc.: 57.42%] [G loss: 0.763069]
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2645 [D loss: 0.681992, acc.: 57.62%] [G loss: 0.747813]
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2646 [D loss: 0.684675, acc.: 57.42%] [G loss: 0.751642]
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2647 [D loss: 0.680874, acc.: 57.03%] [G loss: 0.781088]
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2648 [D loss: 0.706376, acc.: 50.59%] [G loss: 0.774088]
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2649 [D loss: 0.700749, acc.: 51.95%] [G loss: 0.771973]
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2650 [D loss: 0.697848, acc.: 50.59%] [G loss: 0.769788]
1/1 [==============================] - 0s 16ms/step
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2651 [D loss: 0.688229, acc.: 54.69%] [G loss: 0.767053]
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2652 [D loss: 0.700185, acc.: 50.98%] [G loss: 0.776491]
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2653 [D loss: 0.681164, acc.: 58.01%] [G loss: 0.781574]
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2654 [D loss: 0.681622, acc.: 57.03%] [G loss: 0.760126]
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2655 [D loss: 0.682807, acc.: 56.64%] [G loss: 0.763714]
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2656 [D loss: 0.684545, acc.: 54.49%] [G loss: 0.764550]
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2657 [D loss: 0.676313, acc.: 58.98%] [G loss: 0.761998]
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2658 [D loss: 0.692531, acc.: 53.32%] [G loss: 0.760578]
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2659 [D loss: 0.695755, acc.: 48.83%] [G loss: 0.750717]
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2660 [D loss: 0.687065, acc.: 55.86%] [G loss: 0.747200]
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2661 [D loss: 0.686991, acc.: 56.05%] [G loss: 0.751018]
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2662 [D loss: 0.680340, acc.: 56.45%] [G loss: 0.777685]
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2663 [D loss: 0.669887, acc.: 59.57%] [G loss: 0.787683]
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2664 [D loss: 0.687950, acc.: 53.32%] [G loss: 0.783874]
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2665 [D loss: 0.681145, acc.: 59.96%] [G loss: 0.786295]
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2666 [D loss: 0.687894, acc.: 54.69%] [G loss: 0.772221]
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2667 [D loss: 0.680068, acc.: 58.59%] [G loss: 0.758299]
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2668 [D loss: 0.688760, acc.: 54.10%] [G loss: 0.754497]
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2669 [D loss: 0.701337, acc.: 55.27%] [G loss: 0.738226]
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2670 [D loss: 0.687301, acc.: 52.93%] [G loss: 0.752864]
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2671 [D loss: 0.693982, acc.: 52.93%] [G loss: 0.751852]
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2672 [D loss: 0.696429, acc.: 51.76%] [G loss: 0.757716]
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2673 [D loss: 0.699051, acc.: 50.39%] [G loss: 0.749359]
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2674 [D loss: 0.701565, acc.: 48.83%] [G loss: 0.761297]
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2675 [D loss: 0.685352, acc.: 55.66%] [G loss: 0.791638]
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2676 [D loss: 0.685248, acc.: 56.45%] [G loss: 0.782778]
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2677 [D loss: 0.687313, acc.: 55.47%] [G loss: 0.765352]
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2678 [D loss: 0.674417, acc.: 58.01%] [G loss: 0.778924]
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2679 [D loss: 0.669934, acc.: 59.96%] [G loss: 0.755767]
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2680 [D loss: 0.682683, acc.: 58.40%] [G loss: 0.762414]
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2681 [D loss: 0.673485, acc.: 56.25%] [G loss: 0.750366]
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2682 [D loss: 0.682834, acc.: 57.03%] [G loss: 0.741879]
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2683 [D loss: 0.691251, acc.: 52.54%] [G loss: 0.715519]
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2684 [D loss: 0.682471, acc.: 54.30%] [G loss: 0.733124]
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2685 [D loss: 0.710402, acc.: 42.77%] [G loss: 0.736030]
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2686 [D loss: 0.689322, acc.: 52.15%] [G loss: 0.721633]
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2687 [D loss: 0.691232, acc.: 54.30%] [G loss: 0.735586]
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2688 [D loss: 0.695901, acc.: 51.95%] [G loss: 0.747069]
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2689 [D loss: 0.701124, acc.: 51.56%] [G loss: 0.753801]
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2690 [D loss: 0.692947, acc.: 55.27%] [G loss: 0.758992]
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2691 [D loss: 0.696898, acc.: 50.78%] [G loss: 0.769523]
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2692 [D loss: 0.704461, acc.: 46.88%] [G loss: 0.764990]
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2693 [D loss: 0.695802, acc.: 52.73%] [G loss: 0.772281]
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2694 [D loss: 0.685533, acc.: 57.42%] [G loss: 0.768875]
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2695 [D loss: 0.696333, acc.: 51.56%] [G loss: 0.761993]
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2696 [D loss: 0.699326, acc.: 49.02%] [G loss: 0.766828]
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2697 [D loss: 0.682256, acc.: 54.49%] [G loss: 0.763452]
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2698 [D loss: 0.695159, acc.: 50.78%] [G loss: 0.754432]
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2699 [D loss: 0.684710, acc.: 51.17%] [G loss: 0.741183]
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2700 [D loss: 0.685466, acc.: 51.76%] [G loss: 0.750998]
1/1 [==============================] - 0s 16ms/step
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2701 [D loss: 0.677473, acc.: 60.74%] [G loss: 0.761551]
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2702 [D loss: 0.682154, acc.: 57.42%] [G loss: 0.756424]
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2703 [D loss: 0.675015, acc.: 57.62%] [G loss: 0.770427]
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2704 [D loss: 0.683026, acc.: 57.42%] [G loss: 0.768932]
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2705 [D loss: 0.696543, acc.: 55.66%] [G loss: 0.768376]
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2706 [D loss: 0.694035, acc.: 52.93%] [G loss: 0.748590]
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2707 [D loss: 0.683579, acc.: 56.64%] [G loss: 0.747374]
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2708 [D loss: 0.692021, acc.: 53.52%] [G loss: 0.758161]
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2709 [D loss: 0.693628, acc.: 53.12%] [G loss: 0.758547]
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2710 [D loss: 0.700382, acc.: 50.00%] [G loss: 0.753423]
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2711 [D loss: 0.687373, acc.: 52.54%] [G loss: 0.751194]
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2712 [D loss: 0.693023, acc.: 52.15%] [G loss: 0.729961]
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2713 [D loss: 0.686758, acc.: 51.37%] [G loss: 0.743464]
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2714 [D loss: 0.677764, acc.: 58.59%] [G loss: 0.742284]
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2715 [D loss: 0.686359, acc.: 56.45%] [G loss: 0.760025]
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2716 [D loss: 0.685003, acc.: 53.52%] [G loss: 0.750299]
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2717 [D loss: 0.688051, acc.: 53.91%] [G loss: 0.749899]
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2718 [D loss: 0.692348, acc.: 47.85%] [G loss: 0.724547]
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2719 [D loss: 0.696507, acc.: 53.32%] [G loss: 0.743167]
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2720 [D loss: 0.693097, acc.: 51.17%] [G loss: 0.762734]
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2721 [D loss: 0.687892, acc.: 54.88%] [G loss: 0.768013]
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2722 [D loss: 0.697216, acc.: 51.76%] [G loss: 0.753528]
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2723 [D loss: 0.697948, acc.: 48.83%] [G loss: 0.764425]
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2724 [D loss: 0.690635, acc.: 51.17%] [G loss: 0.759766]
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2725 [D loss: 0.689213, acc.: 54.10%] [G loss: 0.760015]
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2726 [D loss: 0.682844, acc.: 58.01%] [G loss: 0.768500]
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2727 [D loss: 0.689914, acc.: 52.73%] [G loss: 0.753418]
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2728 [D loss: 0.692370, acc.: 51.17%] [G loss: 0.747034]
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2729 [D loss: 0.688808, acc.: 54.30%] [G loss: 0.743555]
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2730 [D loss: 0.694288, acc.: 52.15%] [G loss: 0.746807]
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2731 [D loss: 0.688803, acc.: 54.10%] [G loss: 0.740802]
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2732 [D loss: 0.693628, acc.: 52.34%] [G loss: 0.767641]
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2733 [D loss: 0.681596, acc.: 57.03%] [G loss: 0.767936]
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2734 [D loss: 0.687802, acc.: 52.73%] [G loss: 0.790634]
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2735 [D loss: 0.686173, acc.: 53.52%] [G loss: 0.783167]
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2736 [D loss: 0.683890, acc.: 57.42%] [G loss: 0.775456]
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2737 [D loss: 0.692079, acc.: 53.91%] [G loss: 0.772974]
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2738 [D loss: 0.684145, acc.: 55.47%] [G loss: 0.741814]
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2739 [D loss: 0.696963, acc.: 50.20%] [G loss: 0.752133]
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2740 [D loss: 0.692486, acc.: 54.30%] [G loss: 0.738882]
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2741 [D loss: 0.688099, acc.: 55.27%] [G loss: 0.722119]
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2742 [D loss: 0.690408, acc.: 53.32%] [G loss: 0.734174]
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2743 [D loss: 0.696934, acc.: 51.95%] [G loss: 0.736630]
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2744 [D loss: 0.692013, acc.: 51.17%] [G loss: 0.726026]
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2745 [D loss: 0.699687, acc.: 49.22%] [G loss: 0.753873]
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2746 [D loss: 0.685754, acc.: 56.64%] [G loss: 0.776616]
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2747 [D loss: 0.679724, acc.: 58.20%] [G loss: 0.771037]
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2748 [D loss: 0.689455, acc.: 51.56%] [G loss: 0.769514]
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2749 [D loss: 0.693445, acc.: 53.32%] [G loss: 0.761892]
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2750 [D loss: 0.690989, acc.: 55.27%] [G loss: 0.744628]
1/1 [==============================] - 0s 19ms/step
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2751 [D loss: 0.689135, acc.: 54.10%] [G loss: 0.755671]
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2752 [D loss: 0.680489, acc.: 59.96%] [G loss: 0.734412]
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2753 [D loss: 0.684092, acc.: 55.27%] [G loss: 0.715960]
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2754 [D loss: 0.684091, acc.: 54.49%] [G loss: 0.723985]
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2755 [D loss: 0.688804, acc.: 51.95%] [G loss: 0.708209]
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2756 [D loss: 0.690568, acc.: 52.93%] [G loss: 0.708109]
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2757 [D loss: 0.690137, acc.: 53.91%] [G loss: 0.710864]
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2758 [D loss: 0.692273, acc.: 51.37%] [G loss: 0.738178]
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2759 [D loss: 0.679421, acc.: 53.71%] [G loss: 0.757259]
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2760 [D loss: 0.679949, acc.: 56.45%] [G loss: 0.777902]
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2761 [D loss: 0.682019, acc.: 54.30%] [G loss: 0.791517]
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2762 [D loss: 0.685556, acc.: 53.52%] [G loss: 0.787548]
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2763 [D loss: 0.690671, acc.: 51.76%] [G loss: 0.768819]
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2764 [D loss: 0.692772, acc.: 54.88%] [G loss: 0.765557]
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2765 [D loss: 0.692475, acc.: 54.49%] [G loss: 0.750831]
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2766 [D loss: 0.689774, acc.: 54.10%] [G loss: 0.739275]
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2767 [D loss: 0.701493, acc.: 50.98%] [G loss: 0.731353]
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2768 [D loss: 0.694414, acc.: 52.93%] [G loss: 0.729256]
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2769 [D loss: 0.692117, acc.: 53.12%] [G loss: 0.713118]
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2770 [D loss: 0.694980, acc.: 50.39%] [G loss: 0.733104]
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2771 [D loss: 0.682200, acc.: 56.45%] [G loss: 0.733475]
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2772 [D loss: 0.688528, acc.: 54.88%] [G loss: 0.748985]
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2773 [D loss: 0.696815, acc.: 50.78%] [G loss: 0.776929]
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2774 [D loss: 0.682173, acc.: 55.27%] [G loss: 0.794312]
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2775 [D loss: 0.675140, acc.: 57.03%] [G loss: 0.798786]
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2776 [D loss: 0.690821, acc.: 53.32%] [G loss: 0.805456]
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2777 [D loss: 0.686756, acc.: 54.49%] [G loss: 0.770787]
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2778 [D loss: 0.691447, acc.: 53.12%] [G loss: 0.775395]
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2779 [D loss: 0.682802, acc.: 59.18%] [G loss: 0.758630]
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2780 [D loss: 0.694054, acc.: 52.73%] [G loss: 0.762487]
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2781 [D loss: 0.677754, acc.: 58.01%] [G loss: 0.751406]
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2782 [D loss: 0.677016, acc.: 57.23%] [G loss: 0.759848]
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2783 [D loss: 0.674347, acc.: 58.59%] [G loss: 0.748861]
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2784 [D loss: 0.690588, acc.: 53.91%] [G loss: 0.745210]
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2785 [D loss: 0.683840, acc.: 53.32%] [G loss: 0.726645]
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2786 [D loss: 0.688571, acc.: 57.03%] [G loss: 0.751443]
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2787 [D loss: 0.688790, acc.: 56.64%] [G loss: 0.737211]
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2788 [D loss: 0.698546, acc.: 52.93%] [G loss: 0.771721]
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2789 [D loss: 0.700831, acc.: 49.80%] [G loss: 0.769588]
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2790 [D loss: 0.702678, acc.: 51.37%] [G loss: 0.771269]
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2791 [D loss: 0.699587, acc.: 51.56%] [G loss: 0.775859]
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2792 [D loss: 0.692727, acc.: 53.32%] [G loss: 0.742370]
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2793 [D loss: 0.676125, acc.: 59.77%] [G loss: 0.753100]
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2794 [D loss: 0.683223, acc.: 56.64%] [G loss: 0.751036]
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2795 [D loss: 0.681105, acc.: 58.20%] [G loss: 0.758889]
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2796 [D loss: 0.680883, acc.: 54.88%] [G loss: 0.736684]
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2797 [D loss: 0.675716, acc.: 58.20%] [G loss: 0.735279]
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2798 [D loss: 0.688833, acc.: 54.30%] [G loss: 0.733910]
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2799 [D loss: 0.704623, acc.: 50.59%] [G loss: 0.728674]
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2800 [D loss: 0.715795, acc.: 47.66%] [G loss: 0.718788]
1/1 [==============================] - 0s 19ms/step
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2801 [D loss: 0.693661, acc.: 50.39%] [G loss: 0.752488]
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2802 [D loss: 0.696230, acc.: 49.41%] [G loss: 0.757862]
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2803 [D loss: 0.692375, acc.: 50.59%] [G loss: 0.783976]
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2804 [D loss: 0.694528, acc.: 46.88%] [G loss: 0.785186]
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2805 [D loss: 0.687167, acc.: 53.52%] [G loss: 0.783449]
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2806 [D loss: 0.688421, acc.: 55.47%] [G loss: 0.759966]
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2807 [D loss: 0.687760, acc.: 50.00%] [G loss: 0.768948]
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2808 [D loss: 0.691440, acc.: 51.76%] [G loss: 0.755925]
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2809 [D loss: 0.685655, acc.: 55.86%] [G loss: 0.754551]
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2810 [D loss: 0.683158, acc.: 57.23%] [G loss: 0.747964]
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2811 [D loss: 0.677934, acc.: 56.84%] [G loss: 0.734910]
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2812 [D loss: 0.686145, acc.: 53.52%] [G loss: 0.745542]
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2813 [D loss: 0.688368, acc.: 55.47%] [G loss: 0.720791]
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2814 [D loss: 0.690777, acc.: 51.56%] [G loss: 0.746575]
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2815 [D loss: 0.683534, acc.: 56.84%] [G loss: 0.731149]
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2816 [D loss: 0.683818, acc.: 56.84%] [G loss: 0.769579]
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2817 [D loss: 0.676651, acc.: 58.40%] [G loss: 0.773217]
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2818 [D loss: 0.679860, acc.: 58.01%] [G loss: 0.802379]
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2819 [D loss: 0.684255, acc.: 56.45%] [G loss: 0.762472]
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2820 [D loss: 0.700017, acc.: 47.85%] [G loss: 0.777200]
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2821 [D loss: 0.709568, acc.: 45.31%] [G loss: 0.747607]
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2822 [D loss: 0.700291, acc.: 52.15%] [G loss: 0.747292]
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2823 [D loss: 0.697071, acc.: 52.15%] [G loss: 0.728500]
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2824 [D loss: 0.694981, acc.: 52.34%] [G loss: 0.716718]
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2825 [D loss: 0.693893, acc.: 48.63%] [G loss: 0.720627]
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2826 [D loss: 0.690228, acc.: 53.91%] [G loss: 0.714864]
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2827 [D loss: 0.682243, acc.: 57.62%] [G loss: 0.724950]
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2828 [D loss: 0.690319, acc.: 50.98%] [G loss: 0.743588]
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2829 [D loss: 0.676329, acc.: 56.64%] [G loss: 0.775952]
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2830 [D loss: 0.679668, acc.: 58.59%] [G loss: 0.805316]
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2831 [D loss: 0.666346, acc.: 56.64%] [G loss: 0.830181]
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2832 [D loss: 0.679494, acc.: 54.10%] [G loss: 0.815175]
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2833 [D loss: 0.672043, acc.: 56.64%] [G loss: 0.798384]
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2834 [D loss: 0.699854, acc.: 51.56%] [G loss: 0.770313]
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2835 [D loss: 0.691034, acc.: 50.78%] [G loss: 0.753731]
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2836 [D loss: 0.687111, acc.: 52.34%] [G loss: 0.746070]
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2837 [D loss: 0.687396, acc.: 55.86%] [G loss: 0.742572]
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2838 [D loss: 0.680841, acc.: 53.12%] [G loss: 0.732694]
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2839 [D loss: 0.681608, acc.: 54.88%] [G loss: 0.713712]
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2840 [D loss: 0.692818, acc.: 49.61%] [G loss: 0.701236]
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2841 [D loss: 0.693014, acc.: 54.30%] [G loss: 0.724913]
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2842 [D loss: 0.701599, acc.: 49.61%] [G loss: 0.740469]
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2843 [D loss: 0.695658, acc.: 53.71%] [G loss: 0.773400]
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2844 [D loss: 0.697898, acc.: 51.76%] [G loss: 0.804943]
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2845 [D loss: 0.687863, acc.: 54.30%] [G loss: 0.785660]
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2846 [D loss: 0.698976, acc.: 47.07%] [G loss: 0.778451]
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2847 [D loss: 0.689914, acc.: 53.52%] [G loss: 0.756984]
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2848 [D loss: 0.690866, acc.: 52.15%] [G loss: 0.754360]
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2849 [D loss: 0.681819, acc.: 56.05%] [G loss: 0.759434]
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2850 [D loss: 0.679391, acc.: 60.16%] [G loss: 0.750262]
1/1 [==============================] - 0s 16ms/step
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2851 [D loss: 0.684440, acc.: 54.10%] [G loss: 0.719384]
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2852 [D loss: 0.703025, acc.: 51.76%] [G loss: 0.701365]
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2853 [D loss: 0.711239, acc.: 48.44%] [G loss: 0.727376]
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2854 [D loss: 0.701794, acc.: 51.76%] [G loss: 0.746112]
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2855 [D loss: 0.697792, acc.: 51.56%] [G loss: 0.765599]
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2856 [D loss: 0.696381, acc.: 51.56%] [G loss: 0.785650]
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2857 [D loss: 0.691990, acc.: 52.54%] [G loss: 0.769380]
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2858 [D loss: 0.696384, acc.: 51.56%] [G loss: 0.777906]
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2859 [D loss: 0.695729, acc.: 48.44%] [G loss: 0.759402]
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2860 [D loss: 0.693009, acc.: 54.30%] [G loss: 0.745881]
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2861 [D loss: 0.689332, acc.: 52.34%] [G loss: 0.743075]
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2862 [D loss: 0.684836, acc.: 52.34%] [G loss: 0.753741]
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2863 [D loss: 0.684436, acc.: 51.95%] [G loss: 0.735309]
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2864 [D loss: 0.684706, acc.: 54.88%] [G loss: 0.720346]
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2865 [D loss: 0.685449, acc.: 54.10%] [G loss: 0.723282]
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2866 [D loss: 0.694586, acc.: 51.17%] [G loss: 0.746868]
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2867 [D loss: 0.696130, acc.: 52.73%] [G loss: 0.732749]
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2868 [D loss: 0.687272, acc.: 56.05%] [G loss: 0.763314]
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2869 [D loss: 0.686504, acc.: 54.10%] [G loss: 0.772727]
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2870 [D loss: 0.681167, acc.: 56.64%] [G loss: 0.792606]
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2871 [D loss: 0.706631, acc.: 48.44%] [G loss: 0.777611]
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2872 [D loss: 0.687894, acc.: 54.88%] [G loss: 0.746412]
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2873 [D loss: 0.700112, acc.: 49.02%] [G loss: 0.740377]
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2874 [D loss: 0.703180, acc.: 47.46%] [G loss: 0.757005]
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2875 [D loss: 0.692270, acc.: 53.52%] [G loss: 0.741758]
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2876 [D loss: 0.698664, acc.: 50.00%] [G loss: 0.730365]
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2877 [D loss: 0.685701, acc.: 54.69%] [G loss: 0.721332]
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2878 [D loss: 0.693503, acc.: 50.00%] [G loss: 0.714782]
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2879 [D loss: 0.695573, acc.: 51.76%] [G loss: 0.707423]
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2880 [D loss: 0.693708, acc.: 50.98%] [G loss: 0.715555]
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2881 [D loss: 0.693753, acc.: 52.73%] [G loss: 0.734255]
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2882 [D loss: 0.696626, acc.: 52.34%] [G loss: 0.748217]
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2883 [D loss: 0.694609, acc.: 50.00%] [G loss: 0.791941]
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2884 [D loss: 0.686177, acc.: 50.78%] [G loss: 0.786927]
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2885 [D loss: 0.681534, acc.: 56.64%] [G loss: 0.783097]
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2886 [D loss: 0.687837, acc.: 54.30%] [G loss: 0.782462]
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2887 [D loss: 0.688215, acc.: 51.76%] [G loss: 0.763844]
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2888 [D loss: 0.687849, acc.: 57.23%] [G loss: 0.762463]
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2889 [D loss: 0.694996, acc.: 52.34%] [G loss: 0.761946]
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2890 [D loss: 0.695855, acc.: 50.20%] [G loss: 0.736016]
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2891 [D loss: 0.687860, acc.: 52.73%] [G loss: 0.738148]
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2892 [D loss: 0.681461, acc.: 55.47%] [G loss: 0.715577]
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2893 [D loss: 0.693304, acc.: 51.56%] [G loss: 0.718044]
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2894 [D loss: 0.698571, acc.: 50.78%] [G loss: 0.715407]
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2895 [D loss: 0.692419, acc.: 52.93%] [G loss: 0.724227]
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2896 [D loss: 0.694219, acc.: 51.95%] [G loss: 0.738668]
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2897 [D loss: 0.688641, acc.: 51.95%] [G loss: 0.746641]
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2898 [D loss: 0.688337, acc.: 55.27%] [G loss: 0.774117]
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2899 [D loss: 0.686282, acc.: 56.05%] [G loss: 0.787257]
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2900 [D loss: 0.682241, acc.: 56.25%] [G loss: 0.783704]
1/1 [==============================] - 0s 17ms/step
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2901 [D loss: 0.687087, acc.: 52.54%] [G loss: 0.787687]
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2902 [D loss: 0.684046, acc.: 57.42%] [G loss: 0.773011]
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2903 [D loss: 0.683706, acc.: 54.10%] [G loss: 0.772030]
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2904 [D loss: 0.690076, acc.: 55.47%] [G loss: 0.764695]
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2905 [D loss: 0.683771, acc.: 55.27%] [G loss: 0.750226]
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2906 [D loss: 0.691484, acc.: 53.52%] [G loss: 0.729136]
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2907 [D loss: 0.676745, acc.: 54.69%] [G loss: 0.705503]
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2908 [D loss: 0.686304, acc.: 53.52%] [G loss: 0.694865]
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2909 [D loss: 0.695363, acc.: 50.78%] [G loss: 0.698056]
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2910 [D loss: 0.702632, acc.: 50.00%] [G loss: 0.699421]
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2911 [D loss: 0.699420, acc.: 48.63%] [G loss: 0.718136]
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2912 [D loss: 0.696982, acc.: 52.54%] [G loss: 0.765266]
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2913 [D loss: 0.677922, acc.: 59.77%] [G loss: 0.780642]
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2914 [D loss: 0.672942, acc.: 57.62%] [G loss: 0.794654]
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2915 [D loss: 0.667834, acc.: 60.35%] [G loss: 0.788440]
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2916 [D loss: 0.688154, acc.: 54.69%] [G loss: 0.774628]
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2917 [D loss: 0.685142, acc.: 52.93%] [G loss: 0.759470]
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2918 [D loss: 0.685408, acc.: 55.86%] [G loss: 0.742870]
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2919 [D loss: 0.693155, acc.: 53.12%] [G loss: 0.735293]
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2920 [D loss: 0.689055, acc.: 54.69%] [G loss: 0.719696]
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2921 [D loss: 0.695701, acc.: 50.78%] [G loss: 0.714159]
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2922 [D loss: 0.710409, acc.: 47.07%] [G loss: 0.709308]
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2923 [D loss: 0.708871, acc.: 47.46%] [G loss: 0.719804]
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2924 [D loss: 0.704922, acc.: 49.61%] [G loss: 0.729478]
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2925 [D loss: 0.692768, acc.: 50.20%] [G loss: 0.776047]
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2926 [D loss: 0.682556, acc.: 56.25%] [G loss: 0.811004]
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2927 [D loss: 0.666406, acc.: 60.55%] [G loss: 0.809768]
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2928 [D loss: 0.675842, acc.: 56.05%] [G loss: 0.822081]
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2929 [D loss: 0.673509, acc.: 55.08%] [G loss: 0.809936]
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2930 [D loss: 0.682867, acc.: 53.91%] [G loss: 0.790647]
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2931 [D loss: 0.685956, acc.: 54.69%] [G loss: 0.761981]
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2932 [D loss: 0.691923, acc.: 52.93%] [G loss: 0.736441]
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2933 [D loss: 0.700254, acc.: 49.61%] [G loss: 0.712939]
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2934 [D loss: 0.697394, acc.: 48.83%] [G loss: 0.714960]
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2935 [D loss: 0.706946, acc.: 46.88%] [G loss: 0.708327]
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2936 [D loss: 0.716052, acc.: 47.46%] [G loss: 0.702814]
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2937 [D loss: 0.692357, acc.: 50.20%] [G loss: 0.728613]
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2938 [D loss: 0.705164, acc.: 47.66%] [G loss: 0.759937]
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2939 [D loss: 0.689269, acc.: 53.52%] [G loss: 0.781134]
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2940 [D loss: 0.693235, acc.: 52.93%] [G loss: 0.816168]
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2941 [D loss: 0.694807, acc.: 51.76%] [G loss: 0.799235]
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2942 [D loss: 0.679117, acc.: 57.03%] [G loss: 0.793815]
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2943 [D loss: 0.681852, acc.: 54.49%] [G loss: 0.770577]
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2944 [D loss: 0.685194, acc.: 55.08%] [G loss: 0.759600]
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2945 [D loss: 0.689446, acc.: 54.30%] [G loss: 0.739221]
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2946 [D loss: 0.686917, acc.: 51.76%] [G loss: 0.725568]
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2947 [D loss: 0.689895, acc.: 52.34%] [G loss: 0.718602]
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2948 [D loss: 0.695992, acc.: 52.73%] [G loss: 0.710311]
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2949 [D loss: 0.700154, acc.: 48.83%] [G loss: 0.710792]
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2950 [D loss: 0.687529, acc.: 54.30%] [G loss: 0.712631]
1/1 [==============================] - 0s 18ms/step
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2951 [D loss: 0.705414, acc.: 46.48%] [G loss: 0.748477]
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2952 [D loss: 0.683397, acc.: 51.17%] [G loss: 0.763496]
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2953 [D loss: 0.679601, acc.: 55.86%] [G loss: 0.794799]
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2954 [D loss: 0.688327, acc.: 53.32%] [G loss: 0.789438]
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2955 [D loss: 0.687422, acc.: 54.69%] [G loss: 0.768482]
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2956 [D loss: 0.687553, acc.: 54.69%] [G loss: 0.769728]
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2957 [D loss: 0.693028, acc.: 48.24%] [G loss: 0.739735]
8/8 [==============================] - 0s 7ms/step
2958 [D loss: 0.699549, acc.: 50.59%] [G loss: 0.749898]
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2959 [D loss: 0.687873, acc.: 54.10%] [G loss: 0.731129]
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2960 [D loss: 0.695853, acc.: 49.22%] [G loss: 0.736191]
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2961 [D loss: 0.690041, acc.: 51.95%] [G loss: 0.741133]
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2962 [D loss: 0.680416, acc.: 56.45%] [G loss: 0.719518]
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2963 [D loss: 0.692383, acc.: 52.93%] [G loss: 0.701186]
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2964 [D loss: 0.688400, acc.: 57.03%] [G loss: 0.731388]
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2965 [D loss: 0.693685, acc.: 53.32%] [G loss: 0.751006]
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2966 [D loss: 0.685759, acc.: 55.86%] [G loss: 0.753570]
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2967 [D loss: 0.681612, acc.: 55.08%] [G loss: 0.766678]
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2968 [D loss: 0.691735, acc.: 54.49%] [G loss: 0.759864]
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2969 [D loss: 0.688627, acc.: 53.32%] [G loss: 0.781313]
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2970 [D loss: 0.684482, acc.: 58.20%] [G loss: 0.756315]
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2971 [D loss: 0.696204, acc.: 53.71%] [G loss: 0.759659]
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2972 [D loss: 0.695373, acc.: 53.12%] [G loss: 0.743658]
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2973 [D loss: 0.697146, acc.: 49.41%] [G loss: 0.745199]
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2974 [D loss: 0.688805, acc.: 52.93%] [G loss: 0.754043]
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2975 [D loss: 0.687364, acc.: 54.69%] [G loss: 0.741769]
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2976 [D loss: 0.679426, acc.: 55.08%] [G loss: 0.745434]
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2977 [D loss: 0.692452, acc.: 53.12%] [G loss: 0.743500]
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2978 [D loss: 0.696518, acc.: 51.37%] [G loss: 0.736161]
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2979 [D loss: 0.687813, acc.: 55.08%] [G loss: 0.752727]
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2980 [D loss: 0.697114, acc.: 53.12%] [G loss: 0.765957]
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2981 [D loss: 0.687756, acc.: 54.88%] [G loss: 0.772710]
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2982 [D loss: 0.692092, acc.: 51.17%] [G loss: 0.756162]
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2983 [D loss: 0.687567, acc.: 53.91%] [G loss: 0.755152]
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2984 [D loss: 0.689705, acc.: 56.25%] [G loss: 0.757897]
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2985 [D loss: 0.706762, acc.: 47.27%] [G loss: 0.751699]
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2986 [D loss: 0.694268, acc.: 52.54%] [G loss: 0.746989]
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2987 [D loss: 0.682054, acc.: 58.40%] [G loss: 0.759462]
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2988 [D loss: 0.681331, acc.: 56.84%] [G loss: 0.744579]
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2989 [D loss: 0.674288, acc.: 59.38%] [G loss: 0.735006]
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2990 [D loss: 0.679305, acc.: 55.66%] [G loss: 0.724519]
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2991 [D loss: 0.683002, acc.: 54.69%] [G loss: 0.708003]
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2992 [D loss: 0.694263, acc.: 52.93%] [G loss: 0.690803]
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2993 [D loss: 0.709398, acc.: 45.90%] [G loss: 0.729425]
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2994 [D loss: 0.705317, acc.: 49.22%] [G loss: 0.749653]
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2995 [D loss: 0.694021, acc.: 53.91%] [G loss: 0.793384]
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2996 [D loss: 0.694602, acc.: 51.76%] [G loss: 0.785973]
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2997 [D loss: 0.695757, acc.: 51.56%] [G loss: 0.798380]
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2998 [D loss: 0.696947, acc.: 50.39%] [G loss: 0.770353]
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2999 [D loss: 0.697054, acc.: 55.66%] [G loss: 0.754444]
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3000 [D loss: 0.683893, acc.: 57.62%] [G loss: 0.767043]
1/1 [==============================] - 0s 18ms/step
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3001 [D loss: 0.682479, acc.: 57.03%] [G loss: 0.771668]
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3002 [D loss: 0.683344, acc.: 56.45%] [G loss: 0.755475]
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3003 [D loss: 0.675601, acc.: 59.38%] [G loss: 0.750918]
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3004 [D loss: 0.681385, acc.: 57.03%] [G loss: 0.721966]
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3005 [D loss: 0.693100, acc.: 53.32%] [G loss: 0.717126]
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3006 [D loss: 0.694287, acc.: 51.95%] [G loss: 0.717597]
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3007 [D loss: 0.695609, acc.: 51.76%] [G loss: 0.749524]
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3008 [D loss: 0.677930, acc.: 56.64%] [G loss: 0.772316]
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3009 [D loss: 0.686881, acc.: 53.71%] [G loss: 0.779012]
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3010 [D loss: 0.700475, acc.: 48.44%] [G loss: 0.771433]
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3011 [D loss: 0.697259, acc.: 49.80%] [G loss: 0.778285]
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3012 [D loss: 0.705978, acc.: 49.80%] [G loss: 0.745339]
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3013 [D loss: 0.700415, acc.: 50.20%] [G loss: 0.755506]
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3014 [D loss: 0.688837, acc.: 55.27%] [G loss: 0.750858]
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3015 [D loss: 0.688029, acc.: 52.54%] [G loss: 0.746257]
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3016 [D loss: 0.678896, acc.: 56.64%] [G loss: 0.748777]
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3017 [D loss: 0.670289, acc.: 60.74%] [G loss: 0.744286]
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3018 [D loss: 0.673436, acc.: 59.18%] [G loss: 0.733610]
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3019 [D loss: 0.691722, acc.: 51.76%] [G loss: 0.725551]
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3020 [D loss: 0.692098, acc.: 50.78%] [G loss: 0.722915]
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3021 [D loss: 0.696231, acc.: 51.56%] [G loss: 0.733771]
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3022 [D loss: 0.695719, acc.: 52.34%] [G loss: 0.729481]
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3023 [D loss: 0.687542, acc.: 54.69%] [G loss: 0.769338]
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3024 [D loss: 0.673503, acc.: 58.59%] [G loss: 0.782406]
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3025 [D loss: 0.694361, acc.: 52.73%] [G loss: 0.792435]
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3026 [D loss: 0.687822, acc.: 55.08%] [G loss: 0.779903]
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3027 [D loss: 0.695094, acc.: 54.69%] [G loss: 0.754600]
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3028 [D loss: 0.696232, acc.: 51.37%] [G loss: 0.763167]
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3029 [D loss: 0.694093, acc.: 52.34%] [G loss: 0.759382]
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3030 [D loss: 0.696021, acc.: 52.73%] [G loss: 0.749437]
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3031 [D loss: 0.688155, acc.: 53.12%] [G loss: 0.743711]
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3032 [D loss: 0.693560, acc.: 51.76%] [G loss: 0.747010]
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3033 [D loss: 0.700309, acc.: 47.66%] [G loss: 0.718320]
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3034 [D loss: 0.697115, acc.: 50.00%] [G loss: 0.708399]
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3035 [D loss: 0.704798, acc.: 46.48%] [G loss: 0.722323]
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3036 [D loss: 0.702491, acc.: 49.41%] [G loss: 0.750087]
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3037 [D loss: 0.698061, acc.: 51.17%] [G loss: 0.777874]
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3038 [D loss: 0.679506, acc.: 58.40%] [G loss: 0.807409]
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3039 [D loss: 0.672513, acc.: 58.20%] [G loss: 0.820935]
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3040 [D loss: 0.683435, acc.: 56.64%] [G loss: 0.820798]
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3041 [D loss: 0.671845, acc.: 59.18%] [G loss: 0.810466]
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3042 [D loss: 0.678796, acc.: 56.84%] [G loss: 0.783008]
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3043 [D loss: 0.691420, acc.: 55.66%] [G loss: 0.761911]
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3044 [D loss: 0.691580, acc.: 53.32%] [G loss: 0.743616]
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3045 [D loss: 0.684498, acc.: 55.27%] [G loss: 0.747876]
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3046 [D loss: 0.690638, acc.: 51.95%] [G loss: 0.725029]
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3047 [D loss: 0.693347, acc.: 51.56%] [G loss: 0.706582]
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3048 [D loss: 0.700183, acc.: 49.41%] [G loss: 0.714810]
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3049 [D loss: 0.695221, acc.: 52.73%] [G loss: 0.716228]
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3050 [D loss: 0.695588, acc.: 48.63%] [G loss: 0.733335]
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3051 [D loss: 0.682340, acc.: 54.69%] [G loss: 0.740368]
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3052 [D loss: 0.675170, acc.: 58.40%] [G loss: 0.770209]
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3053 [D loss: 0.683315, acc.: 53.52%] [G loss: 0.790061]
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3054 [D loss: 0.695171, acc.: 54.30%] [G loss: 0.776471]
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3055 [D loss: 0.688911, acc.: 54.88%] [G loss: 0.765954]
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3056 [D loss: 0.692927, acc.: 50.59%] [G loss: 0.763521]
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3057 [D loss: 0.695170, acc.: 52.73%] [G loss: 0.743040]
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3058 [D loss: 0.698949, acc.: 51.17%] [G loss: 0.749639]
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3059 [D loss: 0.691664, acc.: 52.34%] [G loss: 0.734624]
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3060 [D loss: 0.691018, acc.: 53.91%] [G loss: 0.736734]
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3061 [D loss: 0.698999, acc.: 50.59%] [G loss: 0.726544]
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3062 [D loss: 0.688787, acc.: 54.10%] [G loss: 0.714517]
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3063 [D loss: 0.693870, acc.: 48.44%] [G loss: 0.721538]
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3064 [D loss: 0.689560, acc.: 53.32%] [G loss: 0.738776]
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3065 [D loss: 0.693539, acc.: 51.95%] [G loss: 0.749456]
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3066 [D loss: 0.699691, acc.: 52.15%] [G loss: 0.761115]
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3067 [D loss: 0.684801, acc.: 53.52%] [G loss: 0.791984]
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3068 [D loss: 0.677332, acc.: 57.03%] [G loss: 0.800634]
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3069 [D loss: 0.693808, acc.: 52.15%] [G loss: 0.790289]
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3070 [D loss: 0.688540, acc.: 54.69%] [G loss: 0.768997]
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3071 [D loss: 0.705276, acc.: 50.78%] [G loss: 0.758824]
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3072 [D loss: 0.706147, acc.: 47.07%] [G loss: 0.748213]
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3073 [D loss: 0.703723, acc.: 49.61%] [G loss: 0.751945]
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3074 [D loss: 0.695572, acc.: 49.80%] [G loss: 0.739336]
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3075 [D loss: 0.696230, acc.: 51.76%] [G loss: 0.738109]
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3076 [D loss: 0.672604, acc.: 59.96%] [G loss: 0.749114]
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3077 [D loss: 0.692353, acc.: 51.95%] [G loss: 0.739039]
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3078 [D loss: 0.692683, acc.: 50.00%] [G loss: 0.736405]
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3079 [D loss: 0.682882, acc.: 55.27%] [G loss: 0.734802]
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3080 [D loss: 0.685091, acc.: 55.66%] [G loss: 0.740314]
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3081 [D loss: 0.682630, acc.: 56.25%] [G loss: 0.772454]
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3082 [D loss: 0.676967, acc.: 58.20%] [G loss: 0.785909]
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3083 [D loss: 0.682714, acc.: 58.98%] [G loss: 0.773569]
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3084 [D loss: 0.692269, acc.: 52.73%] [G loss: 0.760143]
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3085 [D loss: 0.699313, acc.: 50.78%] [G loss: 0.761869]
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3086 [D loss: 0.693139, acc.: 52.34%] [G loss: 0.748390]
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3087 [D loss: 0.697956, acc.: 49.22%] [G loss: 0.742126]
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3088 [D loss: 0.686169, acc.: 53.12%] [G loss: 0.734665]
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3089 [D loss: 0.694448, acc.: 52.34%] [G loss: 0.726213]
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3090 [D loss: 0.691094, acc.: 51.56%] [G loss: 0.717721]
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3091 [D loss: 0.699057, acc.: 49.80%] [G loss: 0.709744]
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3092 [D loss: 0.683449, acc.: 54.30%] [G loss: 0.709873]
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3093 [D loss: 0.689693, acc.: 55.66%] [G loss: 0.718117]
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3094 [D loss: 0.691204, acc.: 52.34%] [G loss: 0.712163]
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3095 [D loss: 0.687648, acc.: 53.71%] [G loss: 0.721621]
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3096 [D loss: 0.697396, acc.: 47.85%] [G loss: 0.747845]
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3097 [D loss: 0.701541, acc.: 47.27%] [G loss: 0.757765]
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3098 [D loss: 0.691872, acc.: 53.71%] [G loss: 0.768939]
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3099 [D loss: 0.677888, acc.: 55.86%] [G loss: 0.789376]
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3100 [D loss: 0.685746, acc.: 54.88%] [G loss: 0.782159]
1/1 [==============================] - 0s 17ms/step
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3101 [D loss: 0.688243, acc.: 54.10%] [G loss: 0.786862]
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3102 [D loss: 0.684626, acc.: 54.69%] [G loss: 0.771555]
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3103 [D loss: 0.695993, acc.: 49.41%] [G loss: 0.770385]
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3104 [D loss: 0.691351, acc.: 52.34%] [G loss: 0.762873]
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3105 [D loss: 0.690565, acc.: 52.73%] [G loss: 0.728151]
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3106 [D loss: 0.687151, acc.: 55.08%] [G loss: 0.741779]
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3107 [D loss: 0.694095, acc.: 54.88%] [G loss: 0.721074]
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3108 [D loss: 0.692468, acc.: 54.30%] [G loss: 0.720519]
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3109 [D loss: 0.692956, acc.: 51.95%] [G loss: 0.703830]
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3110 [D loss: 0.694751, acc.: 54.69%] [G loss: 0.733907]
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3111 [D loss: 0.694507, acc.: 50.78%] [G loss: 0.739356]
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3112 [D loss: 0.685814, acc.: 55.66%] [G loss: 0.754274]
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3113 [D loss: 0.688137, acc.: 50.78%] [G loss: 0.761308]
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3114 [D loss: 0.685675, acc.: 51.76%] [G loss: 0.785632]
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3115 [D loss: 0.681949, acc.: 57.81%] [G loss: 0.777381]
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3116 [D loss: 0.688573, acc.: 54.88%] [G loss: 0.766271]
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3117 [D loss: 0.689783, acc.: 54.69%] [G loss: 0.773233]
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3118 [D loss: 0.694047, acc.: 52.73%] [G loss: 0.751171]
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3119 [D loss: 0.678887, acc.: 57.42%] [G loss: 0.763865]
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3120 [D loss: 0.686264, acc.: 54.49%] [G loss: 0.755432]
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3121 [D loss: 0.683843, acc.: 56.45%] [G loss: 0.743740]
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3122 [D loss: 0.683236, acc.: 54.10%] [G loss: 0.741064]
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3123 [D loss: 0.700347, acc.: 49.02%] [G loss: 0.729651]
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3124 [D loss: 0.695673, acc.: 51.76%] [G loss: 0.713946]
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3125 [D loss: 0.694622, acc.: 50.78%] [G loss: 0.734332]
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3126 [D loss: 0.693845, acc.: 51.17%] [G loss: 0.714863]
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3127 [D loss: 0.698349, acc.: 48.63%] [G loss: 0.732453]
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3128 [D loss: 0.702652, acc.: 51.95%] [G loss: 0.741145]
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3129 [D loss: 0.687179, acc.: 55.47%] [G loss: 0.736646]
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3130 [D loss: 0.688758, acc.: 55.86%] [G loss: 0.762491]
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3131 [D loss: 0.697018, acc.: 50.20%] [G loss: 0.750985]
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3132 [D loss: 0.689559, acc.: 52.73%] [G loss: 0.744638]
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3133 [D loss: 0.690956, acc.: 49.41%] [G loss: 0.761003]
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3134 [D loss: 0.683365, acc.: 58.40%] [G loss: 0.740604]
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3135 [D loss: 0.685257, acc.: 56.05%] [G loss: 0.733291]
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3136 [D loss: 0.688097, acc.: 56.25%] [G loss: 0.731426]
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3137 [D loss: 0.694328, acc.: 51.17%] [G loss: 0.741706]
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3138 [D loss: 0.693560, acc.: 52.15%] [G loss: 0.740760]
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3139 [D loss: 0.689350, acc.: 53.91%] [G loss: 0.730700]
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3140 [D loss: 0.682398, acc.: 53.32%] [G loss: 0.749459]
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3141 [D loss: 0.688864, acc.: 56.05%] [G loss: 0.751375]
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3142 [D loss: 0.683987, acc.: 55.86%] [G loss: 0.751405]
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3143 [D loss: 0.690973, acc.: 55.66%] [G loss: 0.759386]
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3144 [D loss: 0.680933, acc.: 54.69%] [G loss: 0.774923]
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3145 [D loss: 0.690835, acc.: 51.76%] [G loss: 0.758084]
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3146 [D loss: 0.678836, acc.: 55.47%] [G loss: 0.763814]
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3147 [D loss: 0.682133, acc.: 58.59%] [G loss: 0.748751]
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3148 [D loss: 0.691097, acc.: 53.12%] [G loss: 0.765160]
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3149 [D loss: 0.692119, acc.: 50.20%] [G loss: 0.744861]
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3150 [D loss: 0.683317, acc.: 53.32%] [G loss: 0.740524]
1/1 [==============================] - 0s 17ms/step
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3151 [D loss: 0.689750, acc.: 55.66%] [G loss: 0.733649]
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3152 [D loss: 0.689085, acc.: 53.52%] [G loss: 0.720184]
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3153 [D loss: 0.698397, acc.: 49.80%] [G loss: 0.726425]
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3154 [D loss: 0.694840, acc.: 52.15%] [G loss: 0.728815]
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3155 [D loss: 0.683824, acc.: 56.84%] [G loss: 0.744414]
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3156 [D loss: 0.690702, acc.: 55.86%] [G loss: 0.754830]
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3157 [D loss: 0.691792, acc.: 55.27%] [G loss: 0.771775]
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3158 [D loss: 0.682478, acc.: 55.66%] [G loss: 0.762960]
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3159 [D loss: 0.691167, acc.: 52.54%] [G loss: 0.752495]
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3160 [D loss: 0.688043, acc.: 55.86%] [G loss: 0.756987]
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3161 [D loss: 0.695189, acc.: 52.54%] [G loss: 0.756500]
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3162 [D loss: 0.691218, acc.: 55.47%] [G loss: 0.736615]
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3163 [D loss: 0.698405, acc.: 53.71%] [G loss: 0.746547]
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3164 [D loss: 0.680090, acc.: 58.79%] [G loss: 0.740326]
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3165 [D loss: 0.692413, acc.: 54.30%] [G loss: 0.720321]
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3166 [D loss: 0.682075, acc.: 56.45%] [G loss: 0.723283]
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3167 [D loss: 0.703260, acc.: 48.83%] [G loss: 0.727017]
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3168 [D loss: 0.691746, acc.: 54.30%] [G loss: 0.730553]
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3169 [D loss: 0.685035, acc.: 55.86%] [G loss: 0.730346]
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3170 [D loss: 0.693870, acc.: 51.17%] [G loss: 0.746592]
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3171 [D loss: 0.685491, acc.: 54.88%] [G loss: 0.746768]
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3172 [D loss: 0.688465, acc.: 55.66%] [G loss: 0.771063]
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3173 [D loss: 0.682808, acc.: 58.98%] [G loss: 0.755955]
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3174 [D loss: 0.692942, acc.: 51.37%] [G loss: 0.770960]
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3175 [D loss: 0.688216, acc.: 55.86%] [G loss: 0.755599]
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3176 [D loss: 0.679980, acc.: 58.79%] [G loss: 0.738143]
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3177 [D loss: 0.682591, acc.: 55.08%] [G loss: 0.751312]
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3178 [D loss: 0.690344, acc.: 51.95%] [G loss: 0.747927]
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3179 [D loss: 0.695266, acc.: 52.93%] [G loss: 0.737877]
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3180 [D loss: 0.687308, acc.: 53.12%] [G loss: 0.731137]
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3181 [D loss: 0.699590, acc.: 51.17%] [G loss: 0.729615]
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3182 [D loss: 0.691615, acc.: 51.76%] [G loss: 0.731282]
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3183 [D loss: 0.684575, acc.: 52.34%] [G loss: 0.746577]
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3184 [D loss: 0.687672, acc.: 51.17%] [G loss: 0.736159]
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3185 [D loss: 0.701877, acc.: 51.17%] [G loss: 0.757722]
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3186 [D loss: 0.690070, acc.: 52.54%] [G loss: 0.767693]
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3187 [D loss: 0.681132, acc.: 56.05%] [G loss: 0.748669]
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3188 [D loss: 0.691559, acc.: 54.49%] [G loss: 0.755580]
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3189 [D loss: 0.684278, acc.: 54.88%] [G loss: 0.748201]
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3190 [D loss: 0.696393, acc.: 53.52%] [G loss: 0.746723]
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3191 [D loss: 0.695211, acc.: 50.59%] [G loss: 0.742187]
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3192 [D loss: 0.684771, acc.: 56.05%] [G loss: 0.741677]
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3193 [D loss: 0.688489, acc.: 54.30%] [G loss: 0.730729]
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3194 [D loss: 0.692394, acc.: 54.10%] [G loss: 0.731255]
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3195 [D loss: 0.695143, acc.: 54.49%] [G loss: 0.725443]
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3196 [D loss: 0.695762, acc.: 50.00%] [G loss: 0.731375]
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3197 [D loss: 0.686736, acc.: 53.32%] [G loss: 0.748649]
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3198 [D loss: 0.694226, acc.: 50.98%] [G loss: 0.736046]
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3199 [D loss: 0.687087, acc.: 56.05%] [G loss: 0.758945]
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3200 [D loss: 0.697535, acc.: 48.83%] [G loss: 0.765445]
1/1 [==============================] - 0s 18ms/step
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3201 [D loss: 0.687400, acc.: 54.30%] [G loss: 0.763345]
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3202 [D loss: 0.688100, acc.: 52.15%] [G loss: 0.768459]
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3203 [D loss: 0.695500, acc.: 50.20%] [G loss: 0.759147]
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3204 [D loss: 0.688625, acc.: 55.27%] [G loss: 0.749122]
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3205 [D loss: 0.698821, acc.: 50.00%] [G loss: 0.744246]
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3206 [D loss: 0.682912, acc.: 54.49%] [G loss: 0.740818]
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3207 [D loss: 0.684320, acc.: 54.30%] [G loss: 0.747393]
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3208 [D loss: 0.692427, acc.: 54.30%] [G loss: 0.731486]
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3209 [D loss: 0.693050, acc.: 52.34%] [G loss: 0.741836]
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3210 [D loss: 0.686319, acc.: 54.10%] [G loss: 0.741036]
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3211 [D loss: 0.691761, acc.: 51.56%] [G loss: 0.737193]
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3212 [D loss: 0.692202, acc.: 52.34%] [G loss: 0.754391]
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3213 [D loss: 0.693191, acc.: 53.52%] [G loss: 0.743900]
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3214 [D loss: 0.681595, acc.: 55.86%] [G loss: 0.760131]
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3215 [D loss: 0.691400, acc.: 52.34%] [G loss: 0.765107]
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3216 [D loss: 0.682919, acc.: 57.23%] [G loss: 0.760184]
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3217 [D loss: 0.686408, acc.: 54.88%] [G loss: 0.756357]
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3218 [D loss: 0.697349, acc.: 53.32%] [G loss: 0.759158]
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3219 [D loss: 0.684492, acc.: 56.84%] [G loss: 0.747647]
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3220 [D loss: 0.696063, acc.: 52.15%] [G loss: 0.733876]
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3221 [D loss: 0.692407, acc.: 55.27%] [G loss: 0.738555]
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3222 [D loss: 0.689039, acc.: 51.95%] [G loss: 0.726989]
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3223 [D loss: 0.691292, acc.: 52.73%] [G loss: 0.724193]
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3224 [D loss: 0.690765, acc.: 54.10%] [G loss: 0.711036]
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3225 [D loss: 0.700624, acc.: 48.83%] [G loss: 0.707876]
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3226 [D loss: 0.700566, acc.: 51.56%] [G loss: 0.729356]
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3227 [D loss: 0.696939, acc.: 50.00%] [G loss: 0.740736]
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3228 [D loss: 0.694215, acc.: 51.76%] [G loss: 0.743461]
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3229 [D loss: 0.688491, acc.: 53.12%] [G loss: 0.766866]
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3230 [D loss: 0.684427, acc.: 53.71%] [G loss: 0.773209]
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3231 [D loss: 0.690035, acc.: 51.17%] [G loss: 0.776480]
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3232 [D loss: 0.693303, acc.: 52.34%] [G loss: 0.757529]
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3233 [D loss: 0.691083, acc.: 53.12%] [G loss: 0.747918]
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3234 [D loss: 0.683889, acc.: 55.08%] [G loss: 0.754144]
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3235 [D loss: 0.688634, acc.: 53.71%] [G loss: 0.736634]
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3236 [D loss: 0.685376, acc.: 56.84%] [G loss: 0.731914]
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3237 [D loss: 0.685122, acc.: 54.69%] [G loss: 0.723166]
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3238 [D loss: 0.687717, acc.: 50.78%] [G loss: 0.717011]
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3239 [D loss: 0.688905, acc.: 51.17%] [G loss: 0.727832]
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3240 [D loss: 0.691946, acc.: 49.80%] [G loss: 0.724283]
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3241 [D loss: 0.689837, acc.: 52.93%] [G loss: 0.723538]
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3242 [D loss: 0.689086, acc.: 51.95%] [G loss: 0.727951]
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3243 [D loss: 0.690345, acc.: 52.34%] [G loss: 0.746940]
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3244 [D loss: 0.684364, acc.: 52.93%] [G loss: 0.761345]
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3245 [D loss: 0.678884, acc.: 55.47%] [G loss: 0.748842]
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3246 [D loss: 0.691336, acc.: 55.27%] [G loss: 0.749136]
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3247 [D loss: 0.692056, acc.: 52.73%] [G loss: 0.740473]
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3248 [D loss: 0.692749, acc.: 52.54%] [G loss: 0.738984]
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3249 [D loss: 0.702393, acc.: 51.17%] [G loss: 0.739406]
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3250 [D loss: 0.702675, acc.: 46.68%] [G loss: 0.734319]
1/1 [==============================] - 0s 17ms/step
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3251 [D loss: 0.690986, acc.: 52.34%] [G loss: 0.729955]
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3252 [D loss: 0.689353, acc.: 55.27%] [G loss: 0.727772]
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3253 [D loss: 0.693838, acc.: 51.37%] [G loss: 0.729952]
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3254 [D loss: 0.695034, acc.: 52.93%] [G loss: 0.743515]
8/8 [==============================] - 0s 7ms/step
3255 [D loss: 0.686713, acc.: 55.27%] [G loss: 0.746079]
8/8 [==============================] - 0s 5ms/step
3256 [D loss: 0.696527, acc.: 49.22%] [G loss: 0.738021]
8/8 [==============================] - 0s 5ms/step
3257 [D loss: 0.699444, acc.: 52.15%] [G loss: 0.748544]
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3258 [D loss: 0.690380, acc.: 53.52%] [G loss: 0.753434]
8/8 [==============================] - 0s 7ms/step
3259 [D loss: 0.695217, acc.: 53.91%] [G loss: 0.762672]
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3260 [D loss: 0.692278, acc.: 53.91%] [G loss: 0.754625]
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3261 [D loss: 0.683586, acc.: 54.88%] [G loss: 0.757055]
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3262 [D loss: 0.693690, acc.: 53.52%] [G loss: 0.756088]
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3263 [D loss: 0.684243, acc.: 54.30%] [G loss: 0.762493]
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3264 [D loss: 0.687535, acc.: 53.12%] [G loss: 0.744199]
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3265 [D loss: 0.687146, acc.: 55.27%] [G loss: 0.738634]
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3266 [D loss: 0.680966, acc.: 55.47%] [G loss: 0.739078]
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3267 [D loss: 0.677932, acc.: 55.66%] [G loss: 0.726713]
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3268 [D loss: 0.682287, acc.: 56.64%] [G loss: 0.731172]
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3269 [D loss: 0.694266, acc.: 53.32%] [G loss: 0.715535]
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3270 [D loss: 0.696964, acc.: 51.95%] [G loss: 0.714490]
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3271 [D loss: 0.696585, acc.: 53.12%] [G loss: 0.709847]
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3272 [D loss: 0.694308, acc.: 54.30%] [G loss: 0.726294]
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3273 [D loss: 0.693103, acc.: 54.49%] [G loss: 0.734837]
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3274 [D loss: 0.695794, acc.: 49.80%] [G loss: 0.737286]
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3275 [D loss: 0.700723, acc.: 49.80%] [G loss: 0.742715]
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3276 [D loss: 0.696742, acc.: 50.78%] [G loss: 0.740126]
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3277 [D loss: 0.682576, acc.: 57.23%] [G loss: 0.738739]
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3278 [D loss: 0.686029, acc.: 53.91%] [G loss: 0.751514]
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3279 [D loss: 0.678715, acc.: 56.05%] [G loss: 0.740484]
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3280 [D loss: 0.673886, acc.: 58.98%] [G loss: 0.739691]
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3281 [D loss: 0.676130, acc.: 57.42%] [G loss: 0.739084]
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3282 [D loss: 0.690323, acc.: 50.00%] [G loss: 0.729173]
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3283 [D loss: 0.700668, acc.: 48.05%] [G loss: 0.722427]
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3284 [D loss: 0.687798, acc.: 52.34%] [G loss: 0.729434]
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3285 [D loss: 0.693648, acc.: 49.22%] [G loss: 0.725952]
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3286 [D loss: 0.692339, acc.: 48.63%] [G loss: 0.732775]
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3287 [D loss: 0.706388, acc.: 50.98%] [G loss: 0.757565]
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3288 [D loss: 0.695267, acc.: 53.12%] [G loss: 0.764877]
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3289 [D loss: 0.702822, acc.: 48.83%] [G loss: 0.758304]
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3290 [D loss: 0.699681, acc.: 49.02%] [G loss: 0.759259]
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3291 [D loss: 0.699404, acc.: 50.78%] [G loss: 0.735291]
8/8 [==============================] - 0s 5ms/step
3292 [D loss: 0.693640, acc.: 51.37%] [G loss: 0.738318]
8/8 [==============================] - 0s 5ms/step
3293 [D loss: 0.689647, acc.: 55.27%] [G loss: 0.751187]
8/8 [==============================] - 0s 5ms/step
3294 [D loss: 0.690739, acc.: 52.15%] [G loss: 0.741446]
8/8 [==============================] - 0s 5ms/step
3295 [D loss: 0.676244, acc.: 57.62%] [G loss: 0.743019]
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3296 [D loss: 0.682173, acc.: 55.86%] [G loss: 0.750575]
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3297 [D loss: 0.674841, acc.: 57.62%] [G loss: 0.730446]
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3298 [D loss: 0.689867, acc.: 53.12%] [G loss: 0.732078]
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3299 [D loss: 0.694778, acc.: 50.20%] [G loss: 0.730500]
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3300 [D loss: 0.698527, acc.: 51.76%] [G loss: 0.743119]
1/1 [==============================] - 0s 17ms/step
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3301 [D loss: 0.687912, acc.: 52.15%] [G loss: 0.757572]
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3302 [D loss: 0.691452, acc.: 51.76%] [G loss: 0.783443]
8/8 [==============================] - 0s 4ms/step
3303 [D loss: 0.694178, acc.: 53.12%] [G loss: 0.797784]
8/8 [==============================] - 0s 5ms/step
3304 [D loss: 0.706486, acc.: 47.07%] [G loss: 0.777424]
8/8 [==============================] - 0s 5ms/step
3305 [D loss: 0.695532, acc.: 53.32%] [G loss: 0.765700]
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3306 [D loss: 0.695597, acc.: 53.12%] [G loss: 0.758162]
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3307 [D loss: 0.689705, acc.: 54.49%] [G loss: 0.763942]
8/8 [==============================] - 0s 6ms/step
3308 [D loss: 0.687300, acc.: 51.76%] [G loss: 0.751926]
8/8 [==============================] - 0s 5ms/step
3309 [D loss: 0.681996, acc.: 56.25%] [G loss: 0.739371]
8/8 [==============================] - 0s 5ms/step
3310 [D loss: 0.692725, acc.: 52.93%] [G loss: 0.725564]
8/8 [==============================] - 0s 5ms/step
3311 [D loss: 0.688269, acc.: 51.56%] [G loss: 0.714448]
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3312 [D loss: 0.691638, acc.: 52.93%] [G loss: 0.705085]
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3313 [D loss: 0.697547, acc.: 52.34%] [G loss: 0.728537]
8/8 [==============================] - 0s 5ms/step
3314 [D loss: 0.693275, acc.: 53.32%] [G loss: 0.774000]
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3315 [D loss: 0.693704, acc.: 53.32%] [G loss: 0.798481]
8/8 [==============================] - 0s 6ms/step
3316 [D loss: 0.683873, acc.: 55.47%] [G loss: 0.802259]
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3317 [D loss: 0.689447, acc.: 51.76%] [G loss: 0.772541]
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3318 [D loss: 0.701911, acc.: 50.00%] [G loss: 0.758131]
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3319 [D loss: 0.689591, acc.: 53.91%] [G loss: 0.743688]
8/8 [==============================] - 0s 5ms/step
3320 [D loss: 0.700977, acc.: 47.85%] [G loss: 0.736866]
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3321 [D loss: 0.692080, acc.: 52.54%] [G loss: 0.744974]
8/8 [==============================] - 0s 5ms/step
3322 [D loss: 0.694618, acc.: 48.44%] [G loss: 0.724207]
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3323 [D loss: 0.707682, acc.: 48.63%] [G loss: 0.707939]
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3324 [D loss: 0.702418, acc.: 47.46%] [G loss: 0.702477]
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3325 [D loss: 0.697993, acc.: 48.44%] [G loss: 0.718810]
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3326 [D loss: 0.694116, acc.: 52.93%] [G loss: 0.742722]
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3327 [D loss: 0.690462, acc.: 51.95%] [G loss: 0.762143]
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3328 [D loss: 0.681453, acc.: 55.86%] [G loss: 0.780926]
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3329 [D loss: 0.679372, acc.: 56.25%] [G loss: 0.797479]
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3330 [D loss: 0.684729, acc.: 54.30%] [G loss: 0.794574]
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3331 [D loss: 0.685310, acc.: 55.47%] [G loss: 0.770472]
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3332 [D loss: 0.691551, acc.: 53.12%] [G loss: 0.766480]
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3333 [D loss: 0.694426, acc.: 51.76%] [G loss: 0.743103]
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3334 [D loss: 0.696813, acc.: 50.39%] [G loss: 0.733547]
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3335 [D loss: 0.691818, acc.: 53.71%] [G loss: 0.730070]
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3336 [D loss: 0.692572, acc.: 51.95%] [G loss: 0.729350]
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3337 [D loss: 0.693166, acc.: 51.37%] [G loss: 0.718191]
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3338 [D loss: 0.693902, acc.: 49.61%] [G loss: 0.722208]
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3339 [D loss: 0.686666, acc.: 55.27%] [G loss: 0.728579]
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3340 [D loss: 0.688634, acc.: 49.80%] [G loss: 0.723963]
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3341 [D loss: 0.690271, acc.: 51.76%] [G loss: 0.741522]
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3342 [D loss: 0.682361, acc.: 57.23%] [G loss: 0.758361]
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3343 [D loss: 0.684021, acc.: 56.64%] [G loss: 0.766852]
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3344 [D loss: 0.689740, acc.: 53.12%] [G loss: 0.768323]
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3345 [D loss: 0.702500, acc.: 50.98%] [G loss: 0.738173]
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3346 [D loss: 0.703576, acc.: 45.90%] [G loss: 0.732749]
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3347 [D loss: 0.702567, acc.: 48.24%] [G loss: 0.727997]
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3348 [D loss: 0.706528, acc.: 47.27%] [G loss: 0.730894]
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3349 [D loss: 0.694926, acc.: 50.78%] [G loss: 0.746928]
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3350 [D loss: 0.686569, acc.: 54.88%] [G loss: 0.749697]
1/1 [==============================] - 0s 17ms/step
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3351 [D loss: 0.689245, acc.: 54.30%] [G loss: 0.742858]
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3352 [D loss: 0.686236, acc.: 54.69%] [G loss: 0.733235]
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3353 [D loss: 0.687335, acc.: 54.10%] [G loss: 0.745736]
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3354 [D loss: 0.685724, acc.: 55.47%] [G loss: 0.748399]
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3355 [D loss: 0.684839, acc.: 55.08%] [G loss: 0.746793]
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3356 [D loss: 0.688038, acc.: 52.54%] [G loss: 0.738993]
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3357 [D loss: 0.701625, acc.: 50.39%] [G loss: 0.744189]
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3358 [D loss: 0.700684, acc.: 52.54%] [G loss: 0.737987]
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3359 [D loss: 0.700374, acc.: 52.54%] [G loss: 0.721935]
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3360 [D loss: 0.702320, acc.: 49.80%] [G loss: 0.724376]
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3361 [D loss: 0.704894, acc.: 45.90%] [G loss: 0.718043]
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3362 [D loss: 0.696821, acc.: 51.37%] [G loss: 0.718613]
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3363 [D loss: 0.691371, acc.: 52.73%] [G loss: 0.720516]
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3364 [D loss: 0.681253, acc.: 55.47%] [G loss: 0.741526]
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3365 [D loss: 0.681762, acc.: 54.88%] [G loss: 0.734743]
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3366 [D loss: 0.688181, acc.: 53.32%] [G loss: 0.735364]
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3367 [D loss: 0.690806, acc.: 50.98%] [G loss: 0.745858]
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3368 [D loss: 0.691977, acc.: 51.37%] [G loss: 0.736573]
8/8 [==============================] - 0s 7ms/step
3369 [D loss: 0.687196, acc.: 53.32%] [G loss: 0.735828]
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3370 [D loss: 0.684457, acc.: 55.27%] [G loss: 0.736852]
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3371 [D loss: 0.697805, acc.: 49.41%] [G loss: 0.743360]
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3372 [D loss: 0.708229, acc.: 46.09%] [G loss: 0.752641]
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3373 [D loss: 0.695411, acc.: 47.07%] [G loss: 0.746495]
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3374 [D loss: 0.690650, acc.: 52.34%] [G loss: 0.785396]
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3375 [D loss: 0.681497, acc.: 57.42%] [G loss: 0.784623]
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3376 [D loss: 0.674976, acc.: 56.25%] [G loss: 0.792492]
8/8 [==============================] - 0s 7ms/step
3377 [D loss: 0.685622, acc.: 57.42%] [G loss: 0.777695]
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3378 [D loss: 0.682903, acc.: 56.64%] [G loss: 0.757152]
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3379 [D loss: 0.684100, acc.: 58.98%] [G loss: 0.752012]
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3380 [D loss: 0.692432, acc.: 55.86%] [G loss: 0.725356]
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3381 [D loss: 0.700200, acc.: 49.22%] [G loss: 0.721172]
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3382 [D loss: 0.697792, acc.: 48.63%] [G loss: 0.711441]
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3383 [D loss: 0.709274, acc.: 45.90%] [G loss: 0.694309]
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3384 [D loss: 0.698526, acc.: 50.59%] [G loss: 0.726191]
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3385 [D loss: 0.698961, acc.: 48.44%] [G loss: 0.736246]
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3386 [D loss: 0.682150, acc.: 54.49%] [G loss: 0.741448]
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3387 [D loss: 0.676867, acc.: 59.77%] [G loss: 0.761538]
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3388 [D loss: 0.682286, acc.: 52.54%] [G loss: 0.743599]
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3389 [D loss: 0.681232, acc.: 57.62%] [G loss: 0.755851]
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3390 [D loss: 0.679457, acc.: 58.98%] [G loss: 0.745672]
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3391 [D loss: 0.693315, acc.: 50.78%] [G loss: 0.759376]
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3392 [D loss: 0.689739, acc.: 55.08%] [G loss: 0.735040]
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3393 [D loss: 0.687219, acc.: 54.30%] [G loss: 0.728331]
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3394 [D loss: 0.697778, acc.: 47.46%] [G loss: 0.719371]
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3395 [D loss: 0.702620, acc.: 50.98%] [G loss: 0.712126]
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3396 [D loss: 0.702800, acc.: 48.83%] [G loss: 0.726997]
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3397 [D loss: 0.685458, acc.: 55.86%] [G loss: 0.738540]
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3398 [D loss: 0.686773, acc.: 53.52%] [G loss: 0.784137]
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3399 [D loss: 0.685672, acc.: 54.69%] [G loss: 0.779286]
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3400 [D loss: 0.684054, acc.: 52.73%] [G loss: 0.796107]
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3401 [D loss: 0.686926, acc.: 53.91%] [G loss: 0.776323]
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3402 [D loss: 0.687267, acc.: 53.12%] [G loss: 0.775077]
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3403 [D loss: 0.696974, acc.: 53.32%] [G loss: 0.740804]
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3404 [D loss: 0.688949, acc.: 56.84%] [G loss: 0.740045]
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3405 [D loss: 0.702196, acc.: 48.05%] [G loss: 0.722298]
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3406 [D loss: 0.693715, acc.: 51.56%] [G loss: 0.717261]
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3407 [D loss: 0.692489, acc.: 51.56%] [G loss: 0.714552]
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3408 [D loss: 0.686028, acc.: 53.52%] [G loss: 0.704250]
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3409 [D loss: 0.686739, acc.: 54.10%] [G loss: 0.703377]
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3410 [D loss: 0.683566, acc.: 52.15%] [G loss: 0.711528]
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3411 [D loss: 0.689313, acc.: 53.12%] [G loss: 0.712481]
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3412 [D loss: 0.696094, acc.: 50.78%] [G loss: 0.726110]
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3413 [D loss: 0.700944, acc.: 51.76%] [G loss: 0.746950]
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3414 [D loss: 0.690253, acc.: 53.52%] [G loss: 0.766095]
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3415 [D loss: 0.679796, acc.: 57.03%] [G loss: 0.798647]
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3416 [D loss: 0.680565, acc.: 59.18%] [G loss: 0.785241]
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3417 [D loss: 0.691688, acc.: 51.95%] [G loss: 0.776834]
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3418 [D loss: 0.697269, acc.: 49.41%] [G loss: 0.738209]
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3419 [D loss: 0.694206, acc.: 52.93%] [G loss: 0.741190]
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3420 [D loss: 0.701347, acc.: 51.37%] [G loss: 0.731270]
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3421 [D loss: 0.695352, acc.: 52.15%] [G loss: 0.735861]
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3422 [D loss: 0.686219, acc.: 52.54%] [G loss: 0.726460]
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3423 [D loss: 0.690572, acc.: 51.17%] [G loss: 0.727672]
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3424 [D loss: 0.700886, acc.: 49.02%] [G loss: 0.718217]
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3425 [D loss: 0.689321, acc.: 55.08%] [G loss: 0.721538]
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3426 [D loss: 0.698554, acc.: 51.37%] [G loss: 0.717737]
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3427 [D loss: 0.685714, acc.: 53.52%] [G loss: 0.743979]
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3428 [D loss: 0.689254, acc.: 54.30%] [G loss: 0.735314]
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3429 [D loss: 0.688578, acc.: 53.71%] [G loss: 0.753225]
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3430 [D loss: 0.691225, acc.: 50.39%] [G loss: 0.753355]
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3431 [D loss: 0.692124, acc.: 51.17%] [G loss: 0.753973]
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3432 [D loss: 0.695960, acc.: 53.52%] [G loss: 0.743523]
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3433 [D loss: 0.700963, acc.: 52.15%] [G loss: 0.736579]
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3434 [D loss: 0.692392, acc.: 50.78%] [G loss: 0.748474]
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3435 [D loss: 0.695035, acc.: 54.30%] [G loss: 0.725633]
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3436 [D loss: 0.699221, acc.: 52.15%] [G loss: 0.736794]
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3437 [D loss: 0.695019, acc.: 55.08%] [G loss: 0.749583]
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3438 [D loss: 0.690079, acc.: 52.34%] [G loss: 0.751864]
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3439 [D loss: 0.686480, acc.: 55.08%] [G loss: 0.746680]
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3440 [D loss: 0.685106, acc.: 52.73%] [G loss: 0.738243]
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3441 [D loss: 0.686916, acc.: 54.88%] [G loss: 0.754566]
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3442 [D loss: 0.697065, acc.: 48.83%] [G loss: 0.759147]
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3443 [D loss: 0.684121, acc.: 54.30%] [G loss: 0.771832]
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3444 [D loss: 0.693978, acc.: 51.95%] [G loss: 0.747311]
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3445 [D loss: 0.684642, acc.: 53.12%] [G loss: 0.756869]
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3446 [D loss: 0.687873, acc.: 52.93%] [G loss: 0.755248]
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3447 [D loss: 0.683015, acc.: 55.47%] [G loss: 0.745749]
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3448 [D loss: 0.684571, acc.: 55.08%] [G loss: 0.743768]
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3449 [D loss: 0.699167, acc.: 51.17%] [G loss: 0.725362]
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3450 [D loss: 0.691705, acc.: 50.59%] [G loss: 0.736647]
1/1 [==============================] - 0s 16ms/step
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3451 [D loss: 0.684179, acc.: 54.30%] [G loss: 0.744196]
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3452 [D loss: 0.699277, acc.: 49.61%] [G loss: 0.730551]
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3453 [D loss: 0.682038, acc.: 55.08%] [G loss: 0.735055]
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3454 [D loss: 0.690402, acc.: 51.76%] [G loss: 0.742833]
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3455 [D loss: 0.695266, acc.: 50.39%] [G loss: 0.746490]
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3456 [D loss: 0.699640, acc.: 51.95%] [G loss: 0.720486]
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3457 [D loss: 0.700471, acc.: 50.20%] [G loss: 0.720758]
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3458 [D loss: 0.695946, acc.: 53.12%] [G loss: 0.726791]
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3459 [D loss: 0.691873, acc.: 51.95%] [G loss: 0.733094]
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3460 [D loss: 0.689469, acc.: 51.37%] [G loss: 0.736756]
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3461 [D loss: 0.695112, acc.: 51.95%] [G loss: 0.735987]
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3462 [D loss: 0.689530, acc.: 54.88%] [G loss: 0.741894]
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3463 [D loss: 0.695173, acc.: 50.39%] [G loss: 0.761825]
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3464 [D loss: 0.680686, acc.: 56.05%] [G loss: 0.738243]
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3465 [D loss: 0.685859, acc.: 57.62%] [G loss: 0.750014]
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3466 [D loss: 0.685041, acc.: 53.71%] [G loss: 0.737939]
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3467 [D loss: 0.685937, acc.: 53.71%] [G loss: 0.729082]
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3468 [D loss: 0.688868, acc.: 51.95%] [G loss: 0.716476]
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3469 [D loss: 0.695852, acc.: 51.17%] [G loss: 0.722899]
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3470 [D loss: 0.698177, acc.: 49.02%] [G loss: 0.713558]
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3471 [D loss: 0.690823, acc.: 52.93%] [G loss: 0.722227]
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3472 [D loss: 0.701643, acc.: 48.44%] [G loss: 0.730655]
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3473 [D loss: 0.695218, acc.: 49.22%] [G loss: 0.724591]
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3474 [D loss: 0.696384, acc.: 51.17%] [G loss: 0.743247]
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3475 [D loss: 0.690834, acc.: 52.34%] [G loss: 0.746989]
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3476 [D loss: 0.677023, acc.: 57.03%] [G loss: 0.758345]
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3477 [D loss: 0.679819, acc.: 56.84%] [G loss: 0.739827]
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3478 [D loss: 0.678998, acc.: 56.64%] [G loss: 0.753297]
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3479 [D loss: 0.682475, acc.: 58.01%] [G loss: 0.748661]
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3480 [D loss: 0.689487, acc.: 54.69%] [G loss: 0.728599]
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3481 [D loss: 0.681798, acc.: 57.42%] [G loss: 0.711070]
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3482 [D loss: 0.686840, acc.: 56.45%] [G loss: 0.724903]
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3483 [D loss: 0.691851, acc.: 53.52%] [G loss: 0.729988]
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3484 [D loss: 0.696735, acc.: 52.15%] [G loss: 0.719278]
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3485 [D loss: 0.698060, acc.: 50.59%] [G loss: 0.726379]
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3486 [D loss: 0.686911, acc.: 54.30%] [G loss: 0.720016]
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3487 [D loss: 0.694044, acc.: 52.93%] [G loss: 0.740659]
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3488 [D loss: 0.698142, acc.: 51.17%] [G loss: 0.764366]
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3489 [D loss: 0.687568, acc.: 52.54%] [G loss: 0.774590]
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3490 [D loss: 0.684340, acc.: 55.47%] [G loss: 0.771770]
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3491 [D loss: 0.685270, acc.: 54.88%] [G loss: 0.759606]
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3492 [D loss: 0.696729, acc.: 53.12%] [G loss: 0.753168]
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3493 [D loss: 0.683673, acc.: 54.69%] [G loss: 0.726911]
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3494 [D loss: 0.703556, acc.: 52.34%] [G loss: 0.697017]
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3495 [D loss: 0.711056, acc.: 46.68%] [G loss: 0.699735]
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3496 [D loss: 0.704376, acc.: 49.22%] [G loss: 0.708036]
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3497 [D loss: 0.700343, acc.: 47.27%] [G loss: 0.711851]
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3498 [D loss: 0.696967, acc.: 50.00%] [G loss: 0.726071]
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3499 [D loss: 0.687594, acc.: 53.91%] [G loss: 0.732801]
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3500 [D loss: 0.692763, acc.: 52.73%] [G loss: 0.760983]
1/1 [==============================] - 0s 17ms/step
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3501 [D loss: 0.683378, acc.: 55.47%] [G loss: 0.759598]
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3502 [D loss: 0.686491, acc.: 55.86%] [G loss: 0.753430]
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3503 [D loss: 0.681011, acc.: 59.96%] [G loss: 0.755114]
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3504 [D loss: 0.694465, acc.: 52.15%] [G loss: 0.752046]
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3505 [D loss: 0.688601, acc.: 53.91%] [G loss: 0.733188]
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3506 [D loss: 0.690847, acc.: 54.69%] [G loss: 0.720539]
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3507 [D loss: 0.696366, acc.: 50.39%] [G loss: 0.709023]
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3508 [D loss: 0.707973, acc.: 46.48%] [G loss: 0.706586]
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3509 [D loss: 0.693552, acc.: 53.12%] [G loss: 0.707276]
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3510 [D loss: 0.691648, acc.: 53.32%] [G loss: 0.706514]
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3511 [D loss: 0.706042, acc.: 48.24%] [G loss: 0.715298]
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3512 [D loss: 0.688877, acc.: 54.49%] [G loss: 0.718428]
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3513 [D loss: 0.689131, acc.: 55.08%] [G loss: 0.749814]
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3514 [D loss: 0.679461, acc.: 59.96%] [G loss: 0.771359]
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3515 [D loss: 0.687462, acc.: 57.42%] [G loss: 0.784098]
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3516 [D loss: 0.677488, acc.: 57.62%] [G loss: 0.787058]
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3517 [D loss: 0.695823, acc.: 52.34%] [G loss: 0.764962]
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3518 [D loss: 0.698637, acc.: 51.56%] [G loss: 0.739677]
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3519 [D loss: 0.697939, acc.: 50.00%] [G loss: 0.735930]
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3520 [D loss: 0.695669, acc.: 51.37%] [G loss: 0.734127]
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3521 [D loss: 0.695212, acc.: 49.61%] [G loss: 0.730334]
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3522 [D loss: 0.686317, acc.: 56.25%] [G loss: 0.720550]
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3523 [D loss: 0.689287, acc.: 52.73%] [G loss: 0.721223]
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3524 [D loss: 0.697164, acc.: 50.59%] [G loss: 0.720204]
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3525 [D loss: 0.691452, acc.: 50.39%] [G loss: 0.731371]
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3526 [D loss: 0.688027, acc.: 51.76%] [G loss: 0.749200]
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3527 [D loss: 0.686930, acc.: 51.95%] [G loss: 0.764746]
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3528 [D loss: 0.685208, acc.: 51.95%] [G loss: 0.743800]
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3529 [D loss: 0.686074, acc.: 55.27%] [G loss: 0.767961]
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3530 [D loss: 0.693512, acc.: 52.15%] [G loss: 0.747506]
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3531 [D loss: 0.700863, acc.: 48.05%] [G loss: 0.723382]
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3532 [D loss: 0.693359, acc.: 52.34%] [G loss: 0.728846]
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3533 [D loss: 0.703881, acc.: 47.66%] [G loss: 0.705222]
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3534 [D loss: 0.697849, acc.: 50.78%] [G loss: 0.711689]
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3535 [D loss: 0.698695, acc.: 49.61%] [G loss: 0.712039]
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3536 [D loss: 0.696519, acc.: 52.73%] [G loss: 0.707960]
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3537 [D loss: 0.701229, acc.: 46.68%] [G loss: 0.697247]
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3538 [D loss: 0.696428, acc.: 48.24%] [G loss: 0.706495]
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3539 [D loss: 0.696353, acc.: 50.78%] [G loss: 0.726645]
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3540 [D loss: 0.685615, acc.: 53.71%] [G loss: 0.724868]
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3541 [D loss: 0.691275, acc.: 53.91%] [G loss: 0.746406]
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3542 [D loss: 0.682160, acc.: 55.86%] [G loss: 0.753395]
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3543 [D loss: 0.687074, acc.: 52.93%] [G loss: 0.760473]
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3544 [D loss: 0.686871, acc.: 53.12%] [G loss: 0.768395]
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3545 [D loss: 0.692225, acc.: 50.00%] [G loss: 0.771415]
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3546 [D loss: 0.698836, acc.: 52.15%] [G loss: 0.744992]
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3547 [D loss: 0.696077, acc.: 48.05%] [G loss: 0.745029]
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3548 [D loss: 0.687409, acc.: 52.73%] [G loss: 0.742448]
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3549 [D loss: 0.684883, acc.: 57.23%] [G loss: 0.743744]
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3550 [D loss: 0.690942, acc.: 55.08%] [G loss: 0.722142]
1/1 [==============================] - 0s 17ms/step
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3551 [D loss: 0.693493, acc.: 51.37%] [G loss: 0.728406]
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3552 [D loss: 0.697697, acc.: 51.76%] [G loss: 0.716138]
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3553 [D loss: 0.696154, acc.: 50.59%] [G loss: 0.712787]
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3554 [D loss: 0.695227, acc.: 50.00%] [G loss: 0.725764]
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3555 [D loss: 0.700117, acc.: 48.24%] [G loss: 0.730969]
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3556 [D loss: 0.700838, acc.: 48.24%] [G loss: 0.731629]
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3557 [D loss: 0.692884, acc.: 49.22%] [G loss: 0.736320]
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3558 [D loss: 0.692174, acc.: 53.12%] [G loss: 0.738193]
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3559 [D loss: 0.688628, acc.: 52.73%] [G loss: 0.753800]
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3560 [D loss: 0.691291, acc.: 50.98%] [G loss: 0.740956]
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3561 [D loss: 0.684869, acc.: 56.84%] [G loss: 0.744889]
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3562 [D loss: 0.684475, acc.: 54.49%] [G loss: 0.758220]
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3563 [D loss: 0.677823, acc.: 57.23%] [G loss: 0.766839]
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3564 [D loss: 0.680268, acc.: 58.20%] [G loss: 0.743689]
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3565 [D loss: 0.683555, acc.: 52.93%] [G loss: 0.743200]
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3566 [D loss: 0.685845, acc.: 55.27%] [G loss: 0.738214]
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3567 [D loss: 0.686365, acc.: 57.03%] [G loss: 0.727393]
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3568 [D loss: 0.679139, acc.: 55.47%] [G loss: 0.736038]
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3569 [D loss: 0.709253, acc.: 46.29%] [G loss: 0.713208]
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3570 [D loss: 0.712159, acc.: 45.31%] [G loss: 0.725720]
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3571 [D loss: 0.700955, acc.: 49.41%] [G loss: 0.721646]
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3572 [D loss: 0.698872, acc.: 49.41%] [G loss: 0.735845]
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3573 [D loss: 0.695204, acc.: 49.61%] [G loss: 0.757217]
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3574 [D loss: 0.701366, acc.: 47.66%] [G loss: 0.765686]
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3575 [D loss: 0.680791, acc.: 57.81%] [G loss: 0.764102]
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3576 [D loss: 0.686898, acc.: 53.52%] [G loss: 0.783254]
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3577 [D loss: 0.691585, acc.: 51.37%] [G loss: 0.763597]
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3578 [D loss: 0.695852, acc.: 51.17%] [G loss: 0.747924]
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3579 [D loss: 0.685984, acc.: 56.05%] [G loss: 0.742071]
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3580 [D loss: 0.692737, acc.: 50.00%] [G loss: 0.743472]
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3581 [D loss: 0.689581, acc.: 53.91%] [G loss: 0.725160]
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3582 [D loss: 0.689900, acc.: 55.47%] [G loss: 0.718377]
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3583 [D loss: 0.697284, acc.: 51.37%] [G loss: 0.703748]
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3584 [D loss: 0.699411, acc.: 50.20%] [G loss: 0.705680]
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3585 [D loss: 0.704480, acc.: 47.27%] [G loss: 0.716234]
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3586 [D loss: 0.695765, acc.: 52.15%] [G loss: 0.732890]
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3587 [D loss: 0.686234, acc.: 53.91%] [G loss: 0.756036]
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3588 [D loss: 0.690621, acc.: 52.34%] [G loss: 0.768231]
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3589 [D loss: 0.682770, acc.: 55.66%] [G loss: 0.778290]
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3590 [D loss: 0.690567, acc.: 53.12%] [G loss: 0.765978]
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3591 [D loss: 0.688466, acc.: 54.88%] [G loss: 0.748518]
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3592 [D loss: 0.680165, acc.: 57.03%] [G loss: 0.737125]
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3593 [D loss: 0.698584, acc.: 48.44%] [G loss: 0.735448]
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3594 [D loss: 0.693182, acc.: 51.76%] [G loss: 0.716628]
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3595 [D loss: 0.696213, acc.: 49.80%] [G loss: 0.715480]
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3596 [D loss: 0.695657, acc.: 48.44%] [G loss: 0.702027]
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3597 [D loss: 0.692071, acc.: 50.39%] [G loss: 0.712530]
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3598 [D loss: 0.694246, acc.: 51.76%] [G loss: 0.704843]
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3599 [D loss: 0.690336, acc.: 53.52%] [G loss: 0.709244]
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3600 [D loss: 0.691448, acc.: 51.95%] [G loss: 0.730405]
1/1 [==============================] - 0s 17ms/step
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3601 [D loss: 0.693826, acc.: 51.76%] [G loss: 0.729773]
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3602 [D loss: 0.694083, acc.: 50.20%] [G loss: 0.748470]
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3603 [D loss: 0.701875, acc.: 47.27%] [G loss: 0.771175]
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3604 [D loss: 0.701619, acc.: 50.39%] [G loss: 0.753224]
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3605 [D loss: 0.694483, acc.: 49.41%] [G loss: 0.744942]
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3606 [D loss: 0.698213, acc.: 49.80%] [G loss: 0.742537]
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3607 [D loss: 0.693945, acc.: 49.41%] [G loss: 0.734381]
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3608 [D loss: 0.685743, acc.: 55.86%] [G loss: 0.744463]
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3609 [D loss: 0.682707, acc.: 56.64%] [G loss: 0.749466]
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3610 [D loss: 0.684003, acc.: 52.73%] [G loss: 0.750204]
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3611 [D loss: 0.685607, acc.: 54.88%] [G loss: 0.723798]
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3612 [D loss: 0.684848, acc.: 53.71%] [G loss: 0.728133]
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3613 [D loss: 0.690838, acc.: 53.71%] [G loss: 0.740313]
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3614 [D loss: 0.688771, acc.: 51.37%] [G loss: 0.734163]
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3615 [D loss: 0.690602, acc.: 51.56%] [G loss: 0.737341]
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3616 [D loss: 0.695250, acc.: 52.15%] [G loss: 0.727441]
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3617 [D loss: 0.694171, acc.: 51.95%] [G loss: 0.740472]
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3618 [D loss: 0.703502, acc.: 49.41%] [G loss: 0.755888]
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3619 [D loss: 0.692718, acc.: 52.73%] [G loss: 0.750051]
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3620 [D loss: 0.685247, acc.: 56.84%] [G loss: 0.760998]
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3621 [D loss: 0.698674, acc.: 50.39%] [G loss: 0.761429]
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3622 [D loss: 0.692230, acc.: 52.73%] [G loss: 0.758899]
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3623 [D loss: 0.688470, acc.: 54.88%] [G loss: 0.742064]
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3624 [D loss: 0.685073, acc.: 57.62%] [G loss: 0.747465]
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3625 [D loss: 0.686125, acc.: 56.45%] [G loss: 0.741788]
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3626 [D loss: 0.686822, acc.: 56.05%] [G loss: 0.709558]
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3627 [D loss: 0.694081, acc.: 52.73%] [G loss: 0.717350]
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3628 [D loss: 0.695266, acc.: 52.73%] [G loss: 0.706233]
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3629 [D loss: 0.697345, acc.: 51.56%] [G loss: 0.702488]
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3630 [D loss: 0.699181, acc.: 49.61%] [G loss: 0.706302]
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3631 [D loss: 0.696133, acc.: 54.49%] [G loss: 0.723506]
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3632 [D loss: 0.694497, acc.: 52.93%] [G loss: 0.729645]
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3633 [D loss: 0.686901, acc.: 55.08%] [G loss: 0.760661]
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3634 [D loss: 0.682454, acc.: 58.40%] [G loss: 0.768045]
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3635 [D loss: 0.685300, acc.: 53.32%] [G loss: 0.781467]
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3636 [D loss: 0.691652, acc.: 52.54%] [G loss: 0.754230]
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3637 [D loss: 0.679253, acc.: 58.79%] [G loss: 0.749493]
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3638 [D loss: 0.691706, acc.: 51.76%] [G loss: 0.738908]
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3639 [D loss: 0.694188, acc.: 51.95%] [G loss: 0.753740]
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3640 [D loss: 0.690483, acc.: 53.52%] [G loss: 0.730794]
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3641 [D loss: 0.695359, acc.: 50.59%] [G loss: 0.727846]
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3642 [D loss: 0.693813, acc.: 50.98%] [G loss: 0.726796]
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3643 [D loss: 0.690923, acc.: 51.95%] [G loss: 0.735666]
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3644 [D loss: 0.698069, acc.: 54.30%] [G loss: 0.738351]
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3645 [D loss: 0.694676, acc.: 52.54%] [G loss: 0.730770]
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3646 [D loss: 0.694613, acc.: 47.27%] [G loss: 0.733159]
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3647 [D loss: 0.695542, acc.: 51.95%] [G loss: 0.743018]
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3648 [D loss: 0.701657, acc.: 49.02%] [G loss: 0.755113]
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3649 [D loss: 0.694297, acc.: 51.56%] [G loss: 0.762905]
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3650 [D loss: 0.683483, acc.: 57.03%] [G loss: 0.759049]
1/1 [==============================] - 0s 19ms/step
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3651 [D loss: 0.683087, acc.: 55.86%] [G loss: 0.756551]
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3652 [D loss: 0.682674, acc.: 56.84%] [G loss: 0.757773]
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3653 [D loss: 0.674348, acc.: 59.96%] [G loss: 0.750269]
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3654 [D loss: 0.672008, acc.: 59.96%] [G loss: 0.730442]
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3655 [D loss: 0.679978, acc.: 58.01%] [G loss: 0.739852]
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3656 [D loss: 0.689317, acc.: 55.08%] [G loss: 0.722794]
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3657 [D loss: 0.692251, acc.: 53.32%] [G loss: 0.709601]
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3658 [D loss: 0.701732, acc.: 50.98%] [G loss: 0.715298]
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3659 [D loss: 0.693620, acc.: 53.32%] [G loss: 0.684386]
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3660 [D loss: 0.698112, acc.: 54.10%] [G loss: 0.700671]
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3661 [D loss: 0.704507, acc.: 45.12%] [G loss: 0.714849]
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3662 [D loss: 0.704713, acc.: 45.12%] [G loss: 0.715629]
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3663 [D loss: 0.704354, acc.: 46.48%] [G loss: 0.726213]
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3664 [D loss: 0.698949, acc.: 50.00%] [G loss: 0.727042]
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3665 [D loss: 0.692875, acc.: 52.73%] [G loss: 0.744780]
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3666 [D loss: 0.690230, acc.: 56.25%] [G loss: 0.754971]
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3667 [D loss: 0.682322, acc.: 59.18%] [G loss: 0.756487]
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3668 [D loss: 0.680001, acc.: 57.62%] [G loss: 0.753842]
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3669 [D loss: 0.684294, acc.: 53.52%] [G loss: 0.758079]
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3670 [D loss: 0.682441, acc.: 59.38%] [G loss: 0.761619]
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3671 [D loss: 0.687437, acc.: 54.88%] [G loss: 0.750332]
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3672 [D loss: 0.690496, acc.: 53.71%] [G loss: 0.743738]
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3673 [D loss: 0.692403, acc.: 50.59%] [G loss: 0.735128]
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3674 [D loss: 0.687569, acc.: 51.17%] [G loss: 0.741123]
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3675 [D loss: 0.703952, acc.: 49.80%] [G loss: 0.754486]
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3676 [D loss: 0.693769, acc.: 51.56%] [G loss: 0.740725]
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3677 [D loss: 0.695202, acc.: 51.95%] [G loss: 0.753592]
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3678 [D loss: 0.697173, acc.: 49.22%] [G loss: 0.748622]
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3679 [D loss: 0.702419, acc.: 48.63%] [G loss: 0.742845]
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3680 [D loss: 0.692785, acc.: 50.00%] [G loss: 0.735972]
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3681 [D loss: 0.685475, acc.: 55.47%] [G loss: 0.742903]
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3682 [D loss: 0.695881, acc.: 51.17%] [G loss: 0.745758]
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3683 [D loss: 0.693410, acc.: 50.39%] [G loss: 0.725880]
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3684 [D loss: 0.684342, acc.: 53.52%] [G loss: 0.720045]
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3685 [D loss: 0.705681, acc.: 48.24%] [G loss: 0.723084]
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3686 [D loss: 0.686645, acc.: 55.08%] [G loss: 0.709092]
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3687 [D loss: 0.690284, acc.: 51.37%] [G loss: 0.726166]
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3688 [D loss: 0.699068, acc.: 50.39%] [G loss: 0.721310]
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3689 [D loss: 0.698342, acc.: 47.46%] [G loss: 0.729116]
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3690 [D loss: 0.695847, acc.: 49.02%] [G loss: 0.731572]
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3691 [D loss: 0.703779, acc.: 48.05%] [G loss: 0.725674]
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3692 [D loss: 0.687597, acc.: 53.12%] [G loss: 0.749012]
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3693 [D loss: 0.698070, acc.: 50.59%] [G loss: 0.750584]
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3694 [D loss: 0.687385, acc.: 55.27%] [G loss: 0.757015]
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3695 [D loss: 0.686356, acc.: 54.69%] [G loss: 0.751917]
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3696 [D loss: 0.679339, acc.: 57.42%] [G loss: 0.757949]
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3697 [D loss: 0.689105, acc.: 53.91%] [G loss: 0.767076]
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3698 [D loss: 0.686473, acc.: 53.12%] [G loss: 0.751164]
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3699 [D loss: 0.679167, acc.: 57.62%] [G loss: 0.744551]
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3700 [D loss: 0.671385, acc.: 60.16%] [G loss: 0.742386]
1/1 [==============================] - 0s 18ms/step
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3701 [D loss: 0.697981, acc.: 49.22%] [G loss: 0.734608]
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3702 [D loss: 0.701264, acc.: 50.98%] [G loss: 0.724557]
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3703 [D loss: 0.704050, acc.: 47.66%] [G loss: 0.727045]
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3704 [D loss: 0.696623, acc.: 49.41%] [G loss: 0.734657]
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3705 [D loss: 0.702375, acc.: 50.20%] [G loss: 0.732440]
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3706 [D loss: 0.695865, acc.: 52.73%] [G loss: 0.732601]
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3707 [D loss: 0.697121, acc.: 49.80%] [G loss: 0.746945]
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3708 [D loss: 0.687878, acc.: 54.10%] [G loss: 0.759397]
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3709 [D loss: 0.695517, acc.: 50.39%] [G loss: 0.745144]
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3710 [D loss: 0.694649, acc.: 51.95%] [G loss: 0.737371]
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3711 [D loss: 0.689464, acc.: 53.32%] [G loss: 0.749001]
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3712 [D loss: 0.684523, acc.: 54.69%] [G loss: 0.727147]
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3713 [D loss: 0.682293, acc.: 56.05%] [G loss: 0.733785]
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3714 [D loss: 0.686809, acc.: 55.47%] [G loss: 0.727529]
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3715 [D loss: 0.693098, acc.: 52.73%] [G loss: 0.706237]
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3716 [D loss: 0.697342, acc.: 48.83%] [G loss: 0.698561]
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3717 [D loss: 0.690675, acc.: 52.54%] [G loss: 0.702255]
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3718 [D loss: 0.695895, acc.: 48.24%] [G loss: 0.722881]
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3719 [D loss: 0.696120, acc.: 50.00%] [G loss: 0.726630]
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3720 [D loss: 0.696207, acc.: 51.37%] [G loss: 0.745043]
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3721 [D loss: 0.691128, acc.: 54.10%] [G loss: 0.745018]
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3722 [D loss: 0.690707, acc.: 52.15%] [G loss: 0.753641]
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3723 [D loss: 0.699021, acc.: 54.69%] [G loss: 0.747111]
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3724 [D loss: 0.696612, acc.: 47.85%] [G loss: 0.740603]
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3725 [D loss: 0.696110, acc.: 48.44%] [G loss: 0.740809]
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3726 [D loss: 0.697850, acc.: 50.20%] [G loss: 0.729195]
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3727 [D loss: 0.698562, acc.: 49.80%] [G loss: 0.721131]
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3728 [D loss: 0.690785, acc.: 51.76%] [G loss: 0.715906]
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3729 [D loss: 0.685872, acc.: 57.62%] [G loss: 0.738019]
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3730 [D loss: 0.691007, acc.: 55.66%] [G loss: 0.737179]
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3731 [D loss: 0.686582, acc.: 53.91%] [G loss: 0.741218]
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3732 [D loss: 0.679673, acc.: 56.84%] [G loss: 0.749003]
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3733 [D loss: 0.689129, acc.: 53.91%] [G loss: 0.742711]
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3734 [D loss: 0.678363, acc.: 59.77%] [G loss: 0.767344]
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3735 [D loss: 0.690736, acc.: 53.71%] [G loss: 0.749168]
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3736 [D loss: 0.696164, acc.: 50.78%] [G loss: 0.750977]
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3737 [D loss: 0.699952, acc.: 51.56%] [G loss: 0.732839]
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3738 [D loss: 0.706491, acc.: 46.88%] [G loss: 0.719828]
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3739 [D loss: 0.702892, acc.: 49.80%] [G loss: 0.728214]
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3740 [D loss: 0.706853, acc.: 46.88%] [G loss: 0.737402]
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3741 [D loss: 0.696752, acc.: 49.41%] [G loss: 0.753251]
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3742 [D loss: 0.691244, acc.: 51.17%] [G loss: 0.731645]
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3743 [D loss: 0.688774, acc.: 54.69%] [G loss: 0.729652]
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3744 [D loss: 0.689819, acc.: 50.39%] [G loss: 0.733662]
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3745 [D loss: 0.693983, acc.: 51.95%] [G loss: 0.724023]
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3746 [D loss: 0.685120, acc.: 52.54%] [G loss: 0.734739]
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3747 [D loss: 0.684665, acc.: 54.10%] [G loss: 0.731185]
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3748 [D loss: 0.694539, acc.: 50.20%] [G loss: 0.729342]
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3749 [D loss: 0.688102, acc.: 51.37%] [G loss: 0.731309]
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3750 [D loss: 0.691614, acc.: 51.56%] [G loss: 0.720399]
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3751 [D loss: 0.695473, acc.: 51.37%] [G loss: 0.736104]
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3752 [D loss: 0.688682, acc.: 55.27%] [G loss: 0.723984]
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3753 [D loss: 0.687405, acc.: 55.66%] [G loss: 0.750901]
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3754 [D loss: 0.690156, acc.: 55.86%] [G loss: 0.745428]
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3755 [D loss: 0.685445, acc.: 55.86%] [G loss: 0.756255]
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3756 [D loss: 0.694523, acc.: 53.52%] [G loss: 0.759129]
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3757 [D loss: 0.683675, acc.: 54.88%] [G loss: 0.754355]
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3758 [D loss: 0.686687, acc.: 56.05%] [G loss: 0.750077]
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3759 [D loss: 0.690870, acc.: 52.34%] [G loss: 0.746397]
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3760 [D loss: 0.688364, acc.: 56.25%] [G loss: 0.746558]
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3761 [D loss: 0.685094, acc.: 56.84%] [G loss: 0.726442]
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3762 [D loss: 0.685478, acc.: 56.64%] [G loss: 0.726268]
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3763 [D loss: 0.680742, acc.: 57.42%] [G loss: 0.730267]
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3764 [D loss: 0.691918, acc.: 50.59%] [G loss: 0.729116]
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3765 [D loss: 0.706900, acc.: 46.88%] [G loss: 0.707075]
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3766 [D loss: 0.698631, acc.: 49.61%] [G loss: 0.703814]
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3767 [D loss: 0.698445, acc.: 50.00%] [G loss: 0.713037]
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3768 [D loss: 0.707203, acc.: 45.70%] [G loss: 0.722855]
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3769 [D loss: 0.691800, acc.: 51.95%] [G loss: 0.751568]
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3770 [D loss: 0.699546, acc.: 50.59%] [G loss: 0.755470]
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3771 [D loss: 0.677748, acc.: 57.81%] [G loss: 0.783118]
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3772 [D loss: 0.679481, acc.: 58.59%] [G loss: 0.766316]
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3773 [D loss: 0.674368, acc.: 61.13%] [G loss: 0.768966]
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3774 [D loss: 0.695509, acc.: 52.93%] [G loss: 0.753367]
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3775 [D loss: 0.690648, acc.: 53.32%] [G loss: 0.727917]
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3776 [D loss: 0.696423, acc.: 49.41%] [G loss: 0.730864]
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3777 [D loss: 0.692252, acc.: 53.32%] [G loss: 0.714866]
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3778 [D loss: 0.696320, acc.: 51.37%] [G loss: 0.713689]
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3779 [D loss: 0.697464, acc.: 47.46%] [G loss: 0.691671]
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3780 [D loss: 0.703871, acc.: 44.73%] [G loss: 0.688977]
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3781 [D loss: 0.698908, acc.: 47.27%] [G loss: 0.696594]
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3782 [D loss: 0.709333, acc.: 47.66%] [G loss: 0.713125]
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3783 [D loss: 0.696153, acc.: 53.32%] [G loss: 0.742612]
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3784 [D loss: 0.695383, acc.: 50.98%] [G loss: 0.783098]
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3785 [D loss: 0.687179, acc.: 54.49%] [G loss: 0.769962]
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3786 [D loss: 0.694763, acc.: 51.56%] [G loss: 0.767259]
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3787 [D loss: 0.696626, acc.: 50.78%] [G loss: 0.738297]
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3788 [D loss: 0.693397, acc.: 54.88%] [G loss: 0.741587]
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3789 [D loss: 0.689761, acc.: 54.69%] [G loss: 0.727368]
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3790 [D loss: 0.692250, acc.: 51.56%] [G loss: 0.743748]
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3791 [D loss: 0.676355, acc.: 57.03%] [G loss: 0.725378]
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3792 [D loss: 0.684124, acc.: 54.30%] [G loss: 0.723016]
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3793 [D loss: 0.689208, acc.: 52.54%] [G loss: 0.704242]
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3794 [D loss: 0.701837, acc.: 46.68%] [G loss: 0.687065]
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3795 [D loss: 0.701498, acc.: 48.63%] [G loss: 0.692972]
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3796 [D loss: 0.707697, acc.: 47.27%] [G loss: 0.719808]
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3797 [D loss: 0.696908, acc.: 47.27%] [G loss: 0.751060]
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3798 [D loss: 0.687653, acc.: 55.86%] [G loss: 0.778238]
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3799 [D loss: 0.693143, acc.: 51.76%] [G loss: 0.770011]
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3800 [D loss: 0.692696, acc.: 49.22%] [G loss: 0.765979]
1/1 [==============================] - 0s 18ms/step
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3801 [D loss: 0.690303, acc.: 53.91%] [G loss: 0.756036]
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3802 [D loss: 0.690118, acc.: 54.10%] [G loss: 0.761510]
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3803 [D loss: 0.691468, acc.: 54.88%] [G loss: 0.746131]
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3804 [D loss: 0.689401, acc.: 54.30%] [G loss: 0.744821]
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3805 [D loss: 0.684426, acc.: 55.27%] [G loss: 0.723376]
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3806 [D loss: 0.695760, acc.: 49.80%] [G loss: 0.718822]
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3807 [D loss: 0.693298, acc.: 52.34%] [G loss: 0.710303]
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3808 [D loss: 0.690501, acc.: 51.17%] [G loss: 0.696857]
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3809 [D loss: 0.697073, acc.: 51.17%] [G loss: 0.717301]
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3810 [D loss: 0.688619, acc.: 51.37%] [G loss: 0.753864]
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3811 [D loss: 0.693402, acc.: 51.17%] [G loss: 0.753433]
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3812 [D loss: 0.692102, acc.: 53.71%] [G loss: 0.755383]
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3813 [D loss: 0.686823, acc.: 54.49%] [G loss: 0.763116]
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3814 [D loss: 0.700166, acc.: 51.76%] [G loss: 0.741131]
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3815 [D loss: 0.684494, acc.: 57.62%] [G loss: 0.746046]
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3816 [D loss: 0.692800, acc.: 53.91%] [G loss: 0.737815]
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3817 [D loss: 0.698738, acc.: 51.95%] [G loss: 0.734987]
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3818 [D loss: 0.692657, acc.: 51.76%] [G loss: 0.716165]
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3819 [D loss: 0.692978, acc.: 52.15%] [G loss: 0.718099]
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3820 [D loss: 0.692533, acc.: 50.98%] [G loss: 0.695747]
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3821 [D loss: 0.712619, acc.: 44.73%] [G loss: 0.716387]
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3822 [D loss: 0.697747, acc.: 48.24%] [G loss: 0.723765]
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3823 [D loss: 0.689114, acc.: 51.76%] [G loss: 0.739435]
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3824 [D loss: 0.695045, acc.: 49.80%] [G loss: 0.748744]
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3825 [D loss: 0.686792, acc.: 51.95%] [G loss: 0.762596]
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3826 [D loss: 0.690409, acc.: 49.22%] [G loss: 0.759201]
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3827 [D loss: 0.684296, acc.: 56.05%] [G loss: 0.755272]
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3828 [D loss: 0.692862, acc.: 54.30%] [G loss: 0.744606]
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3829 [D loss: 0.688398, acc.: 54.49%] [G loss: 0.740697]
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3830 [D loss: 0.690555, acc.: 52.15%] [G loss: 0.745653]
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3831 [D loss: 0.693981, acc.: 50.20%] [G loss: 0.735148]
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3832 [D loss: 0.684825, acc.: 53.71%] [G loss: 0.716116]
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3833 [D loss: 0.685170, acc.: 54.10%] [G loss: 0.714310]
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3834 [D loss: 0.692089, acc.: 51.17%] [G loss: 0.715799]
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3835 [D loss: 0.700015, acc.: 48.24%] [G loss: 0.716718]
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3836 [D loss: 0.693585, acc.: 52.54%] [G loss: 0.720338]
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3837 [D loss: 0.698827, acc.: 51.37%] [G loss: 0.745839]
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3838 [D loss: 0.688890, acc.: 53.32%] [G loss: 0.739967]
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3839 [D loss: 0.688449, acc.: 52.73%] [G loss: 0.770353]
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3840 [D loss: 0.685072, acc.: 55.27%] [G loss: 0.768682]
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3841 [D loss: 0.688542, acc.: 53.91%] [G loss: 0.751984]
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3842 [D loss: 0.697675, acc.: 52.54%] [G loss: 0.751574]
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3843 [D loss: 0.688404, acc.: 52.93%] [G loss: 0.751228]
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3844 [D loss: 0.695416, acc.: 51.76%] [G loss: 0.738592]
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3845 [D loss: 0.689104, acc.: 53.71%] [G loss: 0.733424]
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3846 [D loss: 0.694420, acc.: 52.73%] [G loss: 0.719315]
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3847 [D loss: 0.692907, acc.: 52.93%] [G loss: 0.706849]
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3848 [D loss: 0.696161, acc.: 50.78%] [G loss: 0.693066]
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3849 [D loss: 0.703493, acc.: 46.29%] [G loss: 0.698182]
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3850 [D loss: 0.700699, acc.: 48.83%] [G loss: 0.704155]
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3851 [D loss: 0.694576, acc.: 51.37%] [G loss: 0.724181]
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3852 [D loss: 0.701151, acc.: 49.22%] [G loss: 0.739921]
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3853 [D loss: 0.688061, acc.: 53.12%] [G loss: 0.763141]
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3854 [D loss: 0.688484, acc.: 50.78%] [G loss: 0.777350]
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3855 [D loss: 0.684496, acc.: 54.30%] [G loss: 0.778396]
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3856 [D loss: 0.690877, acc.: 52.93%] [G loss: 0.762685]
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3857 [D loss: 0.690242, acc.: 51.76%] [G loss: 0.747016]
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3858 [D loss: 0.690624, acc.: 50.59%] [G loss: 0.746626]
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3859 [D loss: 0.689965, acc.: 54.10%] [G loss: 0.733153]
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3860 [D loss: 0.680692, acc.: 58.40%] [G loss: 0.735764]
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3861 [D loss: 0.689044, acc.: 53.32%] [G loss: 0.706571]
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3862 [D loss: 0.703183, acc.: 46.09%] [G loss: 0.707251]
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3863 [D loss: 0.700029, acc.: 49.61%] [G loss: 0.710097]
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3864 [D loss: 0.694707, acc.: 51.17%] [G loss: 0.701517]
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3865 [D loss: 0.701140, acc.: 47.46%] [G loss: 0.713811]
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3866 [D loss: 0.705345, acc.: 49.61%] [G loss: 0.736899]
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3867 [D loss: 0.691066, acc.: 52.93%] [G loss: 0.734040]
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3868 [D loss: 0.690614, acc.: 52.93%] [G loss: 0.753452]
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3869 [D loss: 0.694800, acc.: 51.17%] [G loss: 0.744695]
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3870 [D loss: 0.688308, acc.: 50.00%] [G loss: 0.738291]
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3871 [D loss: 0.691924, acc.: 51.56%] [G loss: 0.729382]
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3872 [D loss: 0.695843, acc.: 49.61%] [G loss: 0.721379]
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3873 [D loss: 0.696797, acc.: 46.88%] [G loss: 0.705395]
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3874 [D loss: 0.703102, acc.: 47.07%] [G loss: 0.713891]
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3875 [D loss: 0.693351, acc.: 49.80%] [G loss: 0.709814]
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3876 [D loss: 0.688742, acc.: 53.12%] [G loss: 0.710977]
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3877 [D loss: 0.695007, acc.: 49.41%] [G loss: 0.719565]
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3878 [D loss: 0.689042, acc.: 53.12%] [G loss: 0.721424]
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3879 [D loss: 0.699731, acc.: 50.20%] [G loss: 0.736742]
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3880 [D loss: 0.692172, acc.: 50.59%] [G loss: 0.742349]
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3881 [D loss: 0.693524, acc.: 50.59%] [G loss: 0.759541]
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3882 [D loss: 0.689665, acc.: 53.91%] [G loss: 0.757995]
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3883 [D loss: 0.681165, acc.: 58.59%] [G loss: 0.780799]
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3884 [D loss: 0.679874, acc.: 55.08%] [G loss: 0.776997]
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3885 [D loss: 0.691787, acc.: 51.37%] [G loss: 0.756620]
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3886 [D loss: 0.686807, acc.: 54.88%] [G loss: 0.759260]
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3887 [D loss: 0.695426, acc.: 50.98%] [G loss: 0.743030]
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3888 [D loss: 0.694321, acc.: 53.52%] [G loss: 0.734122]
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3889 [D loss: 0.696376, acc.: 51.76%] [G loss: 0.724719]
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3890 [D loss: 0.703166, acc.: 46.48%] [G loss: 0.720744]
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3891 [D loss: 0.700940, acc.: 48.63%] [G loss: 0.727320]
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3892 [D loss: 0.690398, acc.: 52.54%] [G loss: 0.718605]
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3893 [D loss: 0.695519, acc.: 50.20%] [G loss: 0.705559]
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3894 [D loss: 0.692772, acc.: 53.91%] [G loss: 0.721102]
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3895 [D loss: 0.689518, acc.: 54.49%] [G loss: 0.731673]
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3896 [D loss: 0.696092, acc.: 50.78%] [G loss: 0.737233]
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3897 [D loss: 0.686667, acc.: 54.10%] [G loss: 0.737646]
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3898 [D loss: 0.689376, acc.: 50.39%] [G loss: 0.745540]
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3899 [D loss: 0.690313, acc.: 52.93%] [G loss: 0.732620]
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3900 [D loss: 0.687849, acc.: 51.37%] [G loss: 0.735813]
1/1 [==============================] - 0s 17ms/step
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3901 [D loss: 0.691821, acc.: 53.91%] [G loss: 0.744688]
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3902 [D loss: 0.690796, acc.: 53.91%] [G loss: 0.734393]
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3903 [D loss: 0.688586, acc.: 54.49%] [G loss: 0.725366]
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3904 [D loss: 0.690028, acc.: 50.59%] [G loss: 0.719669]
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3905 [D loss: 0.697435, acc.: 50.78%] [G loss: 0.715287]
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3906 [D loss: 0.694722, acc.: 49.61%] [G loss: 0.707510]
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3907 [D loss: 0.698346, acc.: 49.22%] [G loss: 0.718742]
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3908 [D loss: 0.702144, acc.: 45.12%] [G loss: 0.713536]
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3909 [D loss: 0.697181, acc.: 49.41%] [G loss: 0.729953]
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3910 [D loss: 0.699002, acc.: 46.48%] [G loss: 0.723069]
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3911 [D loss: 0.694839, acc.: 48.05%] [G loss: 0.724675]
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3912 [D loss: 0.691491, acc.: 51.95%] [G loss: 0.730029]
8/8 [==============================] - 0s 7ms/step
3913 [D loss: 0.691292, acc.: 51.37%] [G loss: 0.732288]
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3914 [D loss: 0.689044, acc.: 53.32%] [G loss: 0.736231]
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3915 [D loss: 0.685855, acc.: 56.64%] [G loss: 0.730038]
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3916 [D loss: 0.689999, acc.: 52.34%] [G loss: 0.725212]
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3917 [D loss: 0.692515, acc.: 51.76%] [G loss: 0.724980]
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3918 [D loss: 0.687704, acc.: 54.69%] [G loss: 0.723491]
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3919 [D loss: 0.690421, acc.: 53.91%] [G loss: 0.713878]
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3920 [D loss: 0.693465, acc.: 49.80%] [G loss: 0.732333]
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3921 [D loss: 0.690549, acc.: 53.52%] [G loss: 0.736619]
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3922 [D loss: 0.693735, acc.: 50.59%] [G loss: 0.739914]
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3923 [D loss: 0.681783, acc.: 54.49%] [G loss: 0.743863]
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3924 [D loss: 0.689515, acc.: 51.76%] [G loss: 0.751756]
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3925 [D loss: 0.688815, acc.: 54.88%] [G loss: 0.746156]
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3926 [D loss: 0.694250, acc.: 50.20%] [G loss: 0.751410]
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3927 [D loss: 0.689660, acc.: 50.98%] [G loss: 0.728868]
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3928 [D loss: 0.697510, acc.: 48.44%] [G loss: 0.734335]
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3929 [D loss: 0.697816, acc.: 47.85%] [G loss: 0.724044]
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3930 [D loss: 0.692520, acc.: 50.39%] [G loss: 0.716528]
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3931 [D loss: 0.694502, acc.: 49.02%] [G loss: 0.712691]
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3932 [D loss: 0.697425, acc.: 48.63%] [G loss: 0.705215]
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3933 [D loss: 0.701427, acc.: 45.90%] [G loss: 0.696962]
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3934 [D loss: 0.701193, acc.: 48.05%] [G loss: 0.717049]
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3935 [D loss: 0.697745, acc.: 47.27%] [G loss: 0.741122]
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3936 [D loss: 0.694106, acc.: 50.59%] [G loss: 0.736341]
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3937 [D loss: 0.696819, acc.: 47.66%] [G loss: 0.753509]
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3938 [D loss: 0.698436, acc.: 50.20%] [G loss: 0.745493]
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3939 [D loss: 0.694595, acc.: 52.73%] [G loss: 0.750449]
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3940 [D loss: 0.686222, acc.: 56.45%] [G loss: 0.755391]
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3941 [D loss: 0.686966, acc.: 53.52%] [G loss: 0.739176]
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3942 [D loss: 0.686385, acc.: 56.05%] [G loss: 0.734924]
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3943 [D loss: 0.696815, acc.: 51.17%] [G loss: 0.728875]
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3944 [D loss: 0.684887, acc.: 54.49%] [G loss: 0.732098]
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3945 [D loss: 0.682481, acc.: 56.84%] [G loss: 0.708476]
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3946 [D loss: 0.680907, acc.: 58.59%] [G loss: 0.709841]
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3947 [D loss: 0.693418, acc.: 53.12%] [G loss: 0.713619]
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3948 [D loss: 0.690171, acc.: 52.73%] [G loss: 0.704643]
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3949 [D loss: 0.688807, acc.: 54.30%] [G loss: 0.717143]
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3950 [D loss: 0.692556, acc.: 55.27%] [G loss: 0.720498]
1/1 [==============================] - 0s 28ms/step
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3951 [D loss: 0.693582, acc.: 52.54%] [G loss: 0.729939]
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3952 [D loss: 0.692237, acc.: 50.78%] [G loss: 0.737081]
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3953 [D loss: 0.694058, acc.: 50.20%] [G loss: 0.729235]
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3954 [D loss: 0.686033, acc.: 54.10%] [G loss: 0.738934]
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3955 [D loss: 0.691288, acc.: 54.10%] [G loss: 0.743647]
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3956 [D loss: 0.699551, acc.: 49.41%] [G loss: 0.729825]
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3957 [D loss: 0.694313, acc.: 49.61%] [G loss: 0.741592]
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3958 [D loss: 0.701409, acc.: 46.48%] [G loss: 0.729681]
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3959 [D loss: 0.692303, acc.: 52.34%] [G loss: 0.736074]
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3960 [D loss: 0.691485, acc.: 50.39%] [G loss: 0.728797]
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3961 [D loss: 0.688785, acc.: 54.49%] [G loss: 0.724871]
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3962 [D loss: 0.689577, acc.: 51.17%] [G loss: 0.718518]
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3963 [D loss: 0.697571, acc.: 48.83%] [G loss: 0.732548]
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3964 [D loss: 0.692803, acc.: 49.80%] [G loss: 0.728849]
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3965 [D loss: 0.690385, acc.: 51.56%] [G loss: 0.736429]
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3966 [D loss: 0.692039, acc.: 50.59%] [G loss: 0.732908]
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3967 [D loss: 0.690376, acc.: 51.95%] [G loss: 0.737262]
8/8 [==============================] - 0s 7ms/step
3968 [D loss: 0.693550, acc.: 51.76%] [G loss: 0.746943]
8/8 [==============================] - 0s 5ms/step
3969 [D loss: 0.699625, acc.: 51.76%] [G loss: 0.733743]
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3970 [D loss: 0.682988, acc.: 59.18%] [G loss: 0.730415]
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3971 [D loss: 0.690033, acc.: 54.69%] [G loss: 0.729316]
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3972 [D loss: 0.689943, acc.: 54.88%] [G loss: 0.722087]
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3973 [D loss: 0.690159, acc.: 51.37%] [G loss: 0.716908]
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3974 [D loss: 0.696341, acc.: 51.17%] [G loss: 0.714708]
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3975 [D loss: 0.691891, acc.: 50.00%] [G loss: 0.710967]
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3976 [D loss: 0.693596, acc.: 51.76%] [G loss: 0.725034]
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3977 [D loss: 0.700761, acc.: 47.66%] [G loss: 0.728485]
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3978 [D loss: 0.692909, acc.: 50.78%] [G loss: 0.725081]
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3979 [D loss: 0.692532, acc.: 52.34%] [G loss: 0.717950]
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3980 [D loss: 0.700590, acc.: 49.22%] [G loss: 0.716967]
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3981 [D loss: 0.701497, acc.: 48.24%] [G loss: 0.726963]
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3982 [D loss: 0.708314, acc.: 47.27%] [G loss: 0.728773]
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3983 [D loss: 0.687439, acc.: 52.93%] [G loss: 0.730117]
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3984 [D loss: 0.691886, acc.: 50.20%] [G loss: 0.730078]
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3985 [D loss: 0.689991, acc.: 48.63%] [G loss: 0.733191]
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3986 [D loss: 0.687875, acc.: 56.45%] [G loss: 0.744480]
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3987 [D loss: 0.691294, acc.: 53.12%] [G loss: 0.736459]
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3988 [D loss: 0.687800, acc.: 54.10%] [G loss: 0.733558]
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3989 [D loss: 0.680926, acc.: 57.23%] [G loss: 0.736832]
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3990 [D loss: 0.687389, acc.: 53.12%] [G loss: 0.741631]
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3991 [D loss: 0.684961, acc.: 52.73%] [G loss: 0.731555]
8/8 [==============================] - 0s 5ms/step
3992 [D loss: 0.687212, acc.: 56.64%] [G loss: 0.736628]
8/8 [==============================] - 0s 5ms/step
3993 [D loss: 0.690059, acc.: 54.69%] [G loss: 0.725527]
8/8 [==============================] - 0s 7ms/step
3994 [D loss: 0.697085, acc.: 53.32%] [G loss: 0.735151]
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3995 [D loss: 0.692946, acc.: 51.17%] [G loss: 0.738452]
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3996 [D loss: 0.701094, acc.: 44.92%] [G loss: 0.738040]
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3997 [D loss: 0.700609, acc.: 49.22%] [G loss: 0.729714]
8/8 [==============================] - 0s 5ms/step
3998 [D loss: 0.697896, acc.: 49.80%] [G loss: 0.733570]
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3999 [D loss: 0.692267, acc.: 50.59%] [G loss: 0.733507]
8/8 [==============================] - 0s 6ms/step
4000 [D loss: 0.695991, acc.: 49.41%] [G loss: 0.731366]
1/1 [==============================] - 0s 27ms/step
8/8 [==============================] - 0s 5ms/step
4001 [D loss: 0.693693, acc.: 49.02%] [G loss: 0.734397]
8/8 [==============================] - 0s 4ms/step
4002 [D loss: 0.688281, acc.: 55.08%] [G loss: 0.722865]
8/8 [==============================] - 0s 6ms/step
4003 [D loss: 0.691893, acc.: 51.17%] [G loss: 0.730884]
8/8 [==============================] - 0s 5ms/step
4004 [D loss: 0.689684, acc.: 51.76%] [G loss: 0.720182]
8/8 [==============================] - 0s 5ms/step
4005 [D loss: 0.679845, acc.: 58.40%] [G loss: 0.736433]
8/8 [==============================] - 0s 4ms/step
4006 [D loss: 0.690012, acc.: 51.95%] [G loss: 0.730201]
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4007 [D loss: 0.690760, acc.: 51.95%] [G loss: 0.729911]
8/8 [==============================] - 0s 5ms/step
4008 [D loss: 0.692081, acc.: 50.59%] [G loss: 0.721836]
8/8 [==============================] - 0s 6ms/step
4009 [D loss: 0.683615, acc.: 55.27%] [G loss: 0.727998]
8/8 [==============================] - 0s 5ms/step
4010 [D loss: 0.692961, acc.: 51.37%] [G loss: 0.729184]
8/8 [==============================] - 0s 5ms/step
4011 [D loss: 0.693235, acc.: 50.00%] [G loss: 0.727925]
8/8 [==============================] - 0s 5ms/step
4012 [D loss: 0.685482, acc.: 53.71%] [G loss: 0.725222]
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4013 [D loss: 0.690153, acc.: 49.80%] [G loss: 0.726538]
8/8 [==============================] - 0s 5ms/step
4014 [D loss: 0.689341, acc.: 53.71%] [G loss: 0.726954]
8/8 [==============================] - 0s 5ms/step
4015 [D loss: 0.697293, acc.: 50.98%] [G loss: 0.726092]
8/8 [==============================] - 0s 5ms/step
4016 [D loss: 0.686067, acc.: 53.12%] [G loss: 0.732820]
8/8 [==============================] - 0s 5ms/step
4017 [D loss: 0.685790, acc.: 53.52%] [G loss: 0.720912]
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4018 [D loss: 0.691763, acc.: 50.59%] [G loss: 0.719355]
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4019 [D loss: 0.682885, acc.: 53.52%] [G loss: 0.719865]
8/8 [==============================] - 0s 7ms/step
4020 [D loss: 0.698220, acc.: 46.48%] [G loss: 0.722097]
8/8 [==============================] - 0s 5ms/step
4021 [D loss: 0.683263, acc.: 56.05%] [G loss: 0.722099]
8/8 [==============================] - 0s 5ms/step
4022 [D loss: 0.697394, acc.: 52.15%] [G loss: 0.717862]
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4023 [D loss: 0.690235, acc.: 53.91%] [G loss: 0.728259]
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4024 [D loss: 0.692802, acc.: 46.88%] [G loss: 0.735411]
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4025 [D loss: 0.694314, acc.: 50.20%] [G loss: 0.726932]
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4026 [D loss: 0.693067, acc.: 52.34%] [G loss: 0.739399]
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4027 [D loss: 0.698613, acc.: 50.00%] [G loss: 0.738725]
8/8 [==============================] - 0s 5ms/step
4028 [D loss: 0.686085, acc.: 54.69%] [G loss: 0.753849]
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4029 [D loss: 0.695936, acc.: 53.12%] [G loss: 0.753620]
8/8 [==============================] - 0s 5ms/step
4030 [D loss: 0.692851, acc.: 51.37%] [G loss: 0.744859]
8/8 [==============================] - 0s 5ms/step
4031 [D loss: 0.695924, acc.: 51.95%] [G loss: 0.743065]
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4032 [D loss: 0.694027, acc.: 49.80%] [G loss: 0.730560]
8/8 [==============================] - 0s 5ms/step
4033 [D loss: 0.693094, acc.: 54.30%] [G loss: 0.719806]
8/8 [==============================] - 0s 7ms/step
4034 [D loss: 0.686165, acc.: 54.10%] [G loss: 0.726474]
8/8 [==============================] - 0s 6ms/step
4035 [D loss: 0.692021, acc.: 53.12%] [G loss: 0.715124]
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4036 [D loss: 0.694659, acc.: 50.39%] [G loss: 0.706528]
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4037 [D loss: 0.691515, acc.: 51.95%] [G loss: 0.706308]
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4038 [D loss: 0.687540, acc.: 53.91%] [G loss: 0.717289]
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4039 [D loss: 0.697732, acc.: 51.37%] [G loss: 0.710719]
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4040 [D loss: 0.696777, acc.: 48.44%] [G loss: 0.730676]
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4041 [D loss: 0.696409, acc.: 48.05%] [G loss: 0.743879]
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4042 [D loss: 0.692918, acc.: 48.05%] [G loss: 0.753114]
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4043 [D loss: 0.696637, acc.: 50.78%] [G loss: 0.740914]
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4044 [D loss: 0.696972, acc.: 47.66%] [G loss: 0.736333]
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4045 [D loss: 0.695343, acc.: 51.37%] [G loss: 0.730679]
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4046 [D loss: 0.689929, acc.: 53.71%] [G loss: 0.735309]
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4047 [D loss: 0.689382, acc.: 54.30%] [G loss: 0.728178]
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4048 [D loss: 0.688684, acc.: 54.10%] [G loss: 0.732021]
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4049 [D loss: 0.685144, acc.: 54.88%] [G loss: 0.725255]
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4050 [D loss: 0.696334, acc.: 52.93%] [G loss: 0.710812]
1/1 [==============================] - 0s 21ms/step
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4051 [D loss: 0.687471, acc.: 56.25%] [G loss: 0.711878]
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4052 [D loss: 0.698479, acc.: 48.63%] [G loss: 0.710054]
8/8 [==============================] - 0s 5ms/step
4053 [D loss: 0.698576, acc.: 49.41%] [G loss: 0.712936]
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4054 [D loss: 0.693443, acc.: 48.05%] [G loss: 0.718151]
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4055 [D loss: 0.684907, acc.: 53.52%] [G loss: 0.735136]
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4056 [D loss: 0.683091, acc.: 58.20%] [G loss: 0.747695]
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4057 [D loss: 0.690183, acc.: 53.52%] [G loss: 0.764073]
8/8 [==============================] - 0s 5ms/step
4058 [D loss: 0.687266, acc.: 52.54%] [G loss: 0.756570]
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4059 [D loss: 0.697800, acc.: 51.56%] [G loss: 0.737023]
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4060 [D loss: 0.693160, acc.: 50.20%] [G loss: 0.730640]
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4061 [D loss: 0.698719, acc.: 47.85%] [G loss: 0.727697]
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4062 [D loss: 0.698662, acc.: 45.90%] [G loss: 0.728685]
8/8 [==============================] - 0s 7ms/step
4063 [D loss: 0.697204, acc.: 50.59%] [G loss: 0.713558]
8/8 [==============================] - 0s 5ms/step
4064 [D loss: 0.696974, acc.: 45.90%] [G loss: 0.716456]
8/8 [==============================] - 0s 5ms/step
4065 [D loss: 0.693966, acc.: 51.56%] [G loss: 0.709497]
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4066 [D loss: 0.694426, acc.: 50.59%] [G loss: 0.712467]
8/8 [==============================] - 0s 5ms/step
4067 [D loss: 0.703177, acc.: 49.02%] [G loss: 0.718472]
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4068 [D loss: 0.695719, acc.: 49.02%] [G loss: 0.708909]
8/8 [==============================] - 0s 5ms/step
4069 [D loss: 0.690487, acc.: 52.73%] [G loss: 0.721413]
8/8 [==============================] - 0s 4ms/step
4070 [D loss: 0.694091, acc.: 48.44%] [G loss: 0.729345]
8/8 [==============================] - 0s 5ms/step
4071 [D loss: 0.691073, acc.: 51.37%] [G loss: 0.742325]
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4072 [D loss: 0.695418, acc.: 51.56%] [G loss: 0.747548]
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4073 [D loss: 0.687560, acc.: 54.30%] [G loss: 0.745788]
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4074 [D loss: 0.699668, acc.: 49.61%] [G loss: 0.733127]
8/8 [==============================] - 0s 5ms/step
4075 [D loss: 0.685117, acc.: 57.81%] [G loss: 0.731205]
8/8 [==============================] - 0s 5ms/step
4076 [D loss: 0.691707, acc.: 51.56%] [G loss: 0.720229]
8/8 [==============================] - 0s 5ms/step
4077 [D loss: 0.698198, acc.: 50.78%] [G loss: 0.720096]
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4078 [D loss: 0.696110, acc.: 50.78%] [G loss: 0.718016]
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4079 [D loss: 0.692738, acc.: 54.10%] [G loss: 0.717218]
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4080 [D loss: 0.692937, acc.: 52.15%] [G loss: 0.722476]
8/8 [==============================] - 0s 5ms/step
4081 [D loss: 0.700961, acc.: 46.29%] [G loss: 0.729557]
8/8 [==============================] - 0s 5ms/step
4082 [D loss: 0.685409, acc.: 56.84%] [G loss: 0.729914]
8/8 [==============================] - 0s 5ms/step
4083 [D loss: 0.691464, acc.: 51.95%] [G loss: 0.745628]
8/8 [==============================] - 0s 5ms/step
4084 [D loss: 0.691217, acc.: 50.59%] [G loss: 0.746020]
8/8 [==============================] - 0s 5ms/step
4085 [D loss: 0.681570, acc.: 56.45%] [G loss: 0.753675]
8/8 [==============================] - 0s 5ms/step
4086 [D loss: 0.694429, acc.: 52.54%] [G loss: 0.740750]
8/8 [==============================] - 0s 5ms/step
4087 [D loss: 0.692666, acc.: 54.10%] [G loss: 0.734432]
8/8 [==============================] - 0s 5ms/step
4088 [D loss: 0.692457, acc.: 50.98%] [G loss: 0.718103]
8/8 [==============================] - 0s 5ms/step
4089 [D loss: 0.694360, acc.: 51.37%] [G loss: 0.727550]
8/8 [==============================] - 0s 5ms/step
4090 [D loss: 0.687881, acc.: 53.71%] [G loss: 0.725423]
8/8 [==============================] - 0s 5ms/step
4091 [D loss: 0.696192, acc.: 47.85%] [G loss: 0.713653]
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4092 [D loss: 0.693997, acc.: 51.17%] [G loss: 0.704500]
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4093 [D loss: 0.702472, acc.: 47.46%] [G loss: 0.707415]
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4094 [D loss: 0.688815, acc.: 54.88%] [G loss: 0.714852]
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4095 [D loss: 0.687953, acc.: 53.71%] [G loss: 0.711735]
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4096 [D loss: 0.699815, acc.: 51.17%] [G loss: 0.725204]
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4097 [D loss: 0.699681, acc.: 48.63%] [G loss: 0.724815]
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4098 [D loss: 0.697734, acc.: 50.59%] [G loss: 0.733357]
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4099 [D loss: 0.696242, acc.: 49.41%] [G loss: 0.736687]
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4100 [D loss: 0.695971, acc.: 50.00%] [G loss: 0.728957]
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4101 [D loss: 0.695574, acc.: 50.78%] [G loss: 0.722488]
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4102 [D loss: 0.695148, acc.: 51.76%] [G loss: 0.727924]
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4103 [D loss: 0.692424, acc.: 52.54%] [G loss: 0.723170]
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4104 [D loss: 0.693811, acc.: 49.80%] [G loss: 0.720511]
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4105 [D loss: 0.692981, acc.: 51.76%] [G loss: 0.725935]
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4106 [D loss: 0.690985, acc.: 54.49%] [G loss: 0.735489]
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4107 [D loss: 0.685271, acc.: 51.37%] [G loss: 0.727155]
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4108 [D loss: 0.688886, acc.: 52.93%] [G loss: 0.733381]
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4109 [D loss: 0.689697, acc.: 49.61%] [G loss: 0.738045]
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4110 [D loss: 0.690075, acc.: 50.98%] [G loss: 0.722815]
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4111 [D loss: 0.694017, acc.: 51.76%] [G loss: 0.743521]
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4112 [D loss: 0.693262, acc.: 54.10%] [G loss: 0.733073]
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4113 [D loss: 0.697157, acc.: 47.27%] [G loss: 0.735985]
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4114 [D loss: 0.691452, acc.: 50.20%] [G loss: 0.747385]
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4115 [D loss: 0.698683, acc.: 48.63%] [G loss: 0.732827]
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4116 [D loss: 0.694249, acc.: 54.49%] [G loss: 0.742424]
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4117 [D loss: 0.691930, acc.: 51.17%] [G loss: 0.733899]
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4118 [D loss: 0.684507, acc.: 53.52%] [G loss: 0.739086]
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4119 [D loss: 0.681901, acc.: 57.62%] [G loss: 0.737568]
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4120 [D loss: 0.688609, acc.: 54.49%] [G loss: 0.723412]
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4121 [D loss: 0.697370, acc.: 50.98%] [G loss: 0.698224]
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4122 [D loss: 0.694751, acc.: 48.05%] [G loss: 0.702570]
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4123 [D loss: 0.695560, acc.: 49.22%] [G loss: 0.706210]
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4124 [D loss: 0.688730, acc.: 53.32%] [G loss: 0.709332]
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4125 [D loss: 0.705616, acc.: 43.16%] [G loss: 0.705495]
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4126 [D loss: 0.695829, acc.: 49.22%] [G loss: 0.717247]
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4127 [D loss: 0.704741, acc.: 44.73%] [G loss: 0.718416]
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4128 [D loss: 0.705883, acc.: 45.31%] [G loss: 0.721208]
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4129 [D loss: 0.691976, acc.: 50.20%] [G loss: 0.717322]
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4130 [D loss: 0.696958, acc.: 51.17%] [G loss: 0.725366]
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4131 [D loss: 0.692944, acc.: 53.71%] [G loss: 0.724637]
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4132 [D loss: 0.687191, acc.: 53.32%] [G loss: 0.726981]
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4133 [D loss: 0.688788, acc.: 50.98%] [G loss: 0.727931]
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4134 [D loss: 0.690464, acc.: 52.34%] [G loss: 0.729305]
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4135 [D loss: 0.685119, acc.: 52.93%] [G loss: 0.738263]
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4136 [D loss: 0.691826, acc.: 55.47%] [G loss: 0.721701]
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4137 [D loss: 0.690468, acc.: 52.73%] [G loss: 0.720799]
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4138 [D loss: 0.691180, acc.: 55.27%] [G loss: 0.723158]
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4139 [D loss: 0.702351, acc.: 47.66%] [G loss: 0.729135]
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4140 [D loss: 0.694648, acc.: 51.37%] [G loss: 0.725514]
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4141 [D loss: 0.700083, acc.: 47.66%] [G loss: 0.715948]
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4142 [D loss: 0.702523, acc.: 46.88%] [G loss: 0.720955]
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4143 [D loss: 0.694647, acc.: 52.34%] [G loss: 0.727733]
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4144 [D loss: 0.691537, acc.: 50.59%] [G loss: 0.716726]
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4145 [D loss: 0.695810, acc.: 50.59%] [G loss: 0.728346]
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4146 [D loss: 0.692961, acc.: 51.17%] [G loss: 0.731933]
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4147 [D loss: 0.694631, acc.: 52.73%] [G loss: 0.719398]
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4148 [D loss: 0.693172, acc.: 50.78%] [G loss: 0.718880]
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4149 [D loss: 0.689543, acc.: 50.59%] [G loss: 0.724118]
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4150 [D loss: 0.683768, acc.: 57.03%] [G loss: 0.724315]
1/1 [==============================] - 0s 18ms/step
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4151 [D loss: 0.688900, acc.: 55.08%] [G loss: 0.715375]
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4152 [D loss: 0.697612, acc.: 49.61%] [G loss: 0.717402]
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4153 [D loss: 0.686221, acc.: 56.84%] [G loss: 0.713852]
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4154 [D loss: 0.693841, acc.: 51.37%] [G loss: 0.714575]
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4155 [D loss: 0.689910, acc.: 51.56%] [G loss: 0.729791]
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4156 [D loss: 0.693817, acc.: 51.37%] [G loss: 0.729073]
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4157 [D loss: 0.695396, acc.: 49.61%] [G loss: 0.741958]
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4158 [D loss: 0.694204, acc.: 50.78%] [G loss: 0.746502]
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4159 [D loss: 0.699911, acc.: 49.80%] [G loss: 0.741229]
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4160 [D loss: 0.691458, acc.: 51.95%] [G loss: 0.736423]
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4161 [D loss: 0.698531, acc.: 48.83%] [G loss: 0.739198]
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4162 [D loss: 0.686331, acc.: 54.49%] [G loss: 0.726412]
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4163 [D loss: 0.691033, acc.: 52.15%] [G loss: 0.722179]
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4164 [D loss: 0.693004, acc.: 52.73%] [G loss: 0.722252]
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4165 [D loss: 0.689966, acc.: 51.95%] [G loss: 0.722833]
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4166 [D loss: 0.698636, acc.: 49.61%] [G loss: 0.716854]
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4167 [D loss: 0.690002, acc.: 51.56%] [G loss: 0.719320]
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4168 [D loss: 0.694161, acc.: 53.12%] [G loss: 0.725587]
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4169 [D loss: 0.691336, acc.: 53.71%] [G loss: 0.745064]
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4170 [D loss: 0.693706, acc.: 51.37%] [G loss: 0.757357]
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4171 [D loss: 0.684593, acc.: 54.10%] [G loss: 0.746742]
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4172 [D loss: 0.686055, acc.: 54.30%] [G loss: 0.762999]
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4173 [D loss: 0.688884, acc.: 51.56%] [G loss: 0.740477]
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4174 [D loss: 0.694030, acc.: 52.54%] [G loss: 0.739892]
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4175 [D loss: 0.694953, acc.: 51.37%] [G loss: 0.735547]
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4176 [D loss: 0.696426, acc.: 51.17%] [G loss: 0.730284]
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4177 [D loss: 0.699201, acc.: 49.80%] [G loss: 0.732350]
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4178 [D loss: 0.693317, acc.: 50.59%] [G loss: 0.706496]
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4179 [D loss: 0.700965, acc.: 47.66%] [G loss: 0.717770]
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4180 [D loss: 0.703165, acc.: 45.90%] [G loss: 0.706997]
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4181 [D loss: 0.698677, acc.: 49.41%] [G loss: 0.715008]
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4182 [D loss: 0.692144, acc.: 54.30%] [G loss: 0.739416]
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4183 [D loss: 0.696963, acc.: 51.17%] [G loss: 0.735043]
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4184 [D loss: 0.686640, acc.: 54.30%] [G loss: 0.739097]
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4185 [D loss: 0.685109, acc.: 52.93%] [G loss: 0.742676]
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4186 [D loss: 0.688679, acc.: 52.93%] [G loss: 0.738726]
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4187 [D loss: 0.684172, acc.: 54.69%] [G loss: 0.732809]
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4188 [D loss: 0.690890, acc.: 51.37%] [G loss: 0.728648]
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4189 [D loss: 0.688820, acc.: 55.47%] [G loss: 0.728624]
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4190 [D loss: 0.693103, acc.: 53.71%] [G loss: 0.715914]
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4191 [D loss: 0.694562, acc.: 52.54%] [G loss: 0.701807]
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4192 [D loss: 0.701598, acc.: 47.66%] [G loss: 0.698458]
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4193 [D loss: 0.698819, acc.: 48.05%] [G loss: 0.705752]
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4194 [D loss: 0.700295, acc.: 47.27%] [G loss: 0.720851]
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4195 [D loss: 0.697980, acc.: 48.05%] [G loss: 0.733520]
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4196 [D loss: 0.695596, acc.: 49.41%] [G loss: 0.768470]
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4197 [D loss: 0.682604, acc.: 57.42%] [G loss: 0.748514]
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4198 [D loss: 0.680424, acc.: 57.42%] [G loss: 0.779629]
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4199 [D loss: 0.682803, acc.: 55.47%] [G loss: 0.766237]
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4200 [D loss: 0.685651, acc.: 53.52%] [G loss: 0.771318]
1/1 [==============================] - 0s 18ms/step
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4201 [D loss: 0.688213, acc.: 56.64%] [G loss: 0.742100]
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4202 [D loss: 0.681075, acc.: 58.01%] [G loss: 0.749527]
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4203 [D loss: 0.677683, acc.: 61.33%] [G loss: 0.751303]
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4204 [D loss: 0.679669, acc.: 59.38%] [G loss: 0.725772]
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4205 [D loss: 0.685734, acc.: 53.12%] [G loss: 0.712072]
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4206 [D loss: 0.698634, acc.: 47.07%] [G loss: 0.683980]
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4207 [D loss: 0.711555, acc.: 44.92%] [G loss: 0.678497]
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4208 [D loss: 0.718320, acc.: 45.70%] [G loss: 0.689230]
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4209 [D loss: 0.714516, acc.: 44.14%] [G loss: 0.738463]
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4210 [D loss: 0.695344, acc.: 46.09%] [G loss: 0.776889]
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4211 [D loss: 0.701909, acc.: 42.58%] [G loss: 0.778985]
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4212 [D loss: 0.697541, acc.: 50.00%] [G loss: 0.778354]
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4213 [D loss: 0.692308, acc.: 55.08%] [G loss: 0.768957]
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4214 [D loss: 0.694686, acc.: 53.91%] [G loss: 0.752113]
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4215 [D loss: 0.692924, acc.: 54.88%] [G loss: 0.735193]
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4216 [D loss: 0.690598, acc.: 55.66%] [G loss: 0.717330]
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4217 [D loss: 0.690167, acc.: 55.27%] [G loss: 0.695545]
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4218 [D loss: 0.700640, acc.: 50.59%] [G loss: 0.702249]
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4219 [D loss: 0.698749, acc.: 49.22%] [G loss: 0.709789]
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4220 [D loss: 0.692250, acc.: 54.49%] [G loss: 0.730660]
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4221 [D loss: 0.690611, acc.: 53.71%] [G loss: 0.739555]
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4222 [D loss: 0.692174, acc.: 53.52%] [G loss: 0.751219]
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4223 [D loss: 0.701295, acc.: 49.02%] [G loss: 0.753069]
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4224 [D loss: 0.689976, acc.: 53.12%] [G loss: 0.745142]
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4225 [D loss: 0.694380, acc.: 53.71%] [G loss: 0.752214]
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4226 [D loss: 0.694892, acc.: 52.34%] [G loss: 0.748753]
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4227 [D loss: 0.687242, acc.: 53.52%] [G loss: 0.730480]
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4228 [D loss: 0.684811, acc.: 58.40%] [G loss: 0.744414]
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4229 [D loss: 0.683686, acc.: 56.05%] [G loss: 0.738102]
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4230 [D loss: 0.688281, acc.: 55.66%] [G loss: 0.727343]
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4231 [D loss: 0.690103, acc.: 51.95%] [G loss: 0.726423]
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4232 [D loss: 0.682752, acc.: 54.69%] [G loss: 0.718127]
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4233 [D loss: 0.686866, acc.: 53.32%] [G loss: 0.708628]
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4234 [D loss: 0.689204, acc.: 52.73%] [G loss: 0.708783]
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4235 [D loss: 0.694811, acc.: 51.76%] [G loss: 0.711010]
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4236 [D loss: 0.698013, acc.: 49.02%] [G loss: 0.720817]
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4237 [D loss: 0.692688, acc.: 50.98%] [G loss: 0.729050]
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4238 [D loss: 0.689553, acc.: 53.71%] [G loss: 0.740240]
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4239 [D loss: 0.696592, acc.: 51.95%] [G loss: 0.731822]
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4240 [D loss: 0.688224, acc.: 51.37%] [G loss: 0.755315]
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4241 [D loss: 0.697386, acc.: 49.22%] [G loss: 0.739450]
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4242 [D loss: 0.696125, acc.: 51.17%] [G loss: 0.726977]
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4243 [D loss: 0.704044, acc.: 46.09%] [G loss: 0.730257]
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4244 [D loss: 0.699534, acc.: 48.05%] [G loss: 0.716515]
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4245 [D loss: 0.695909, acc.: 53.32%] [G loss: 0.722791]
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4246 [D loss: 0.690028, acc.: 55.86%] [G loss: 0.717372]
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4247 [D loss: 0.691635, acc.: 53.12%] [G loss: 0.708557]
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4248 [D loss: 0.690211, acc.: 54.30%] [G loss: 0.695661]
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4249 [D loss: 0.695233, acc.: 51.56%] [G loss: 0.699872]
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4250 [D loss: 0.689791, acc.: 54.69%] [G loss: 0.697504]
1/1 [==============================] - 0s 19ms/step
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4251 [D loss: 0.690638, acc.: 54.69%] [G loss: 0.722468]
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4252 [D loss: 0.691471, acc.: 53.71%] [G loss: 0.740307]
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4253 [D loss: 0.688154, acc.: 54.30%] [G loss: 0.741721]
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4254 [D loss: 0.692887, acc.: 53.12%] [G loss: 0.744001]
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4255 [D loss: 0.700007, acc.: 52.15%] [G loss: 0.732836]
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4256 [D loss: 0.694097, acc.: 50.59%] [G loss: 0.728028]
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4257 [D loss: 0.693074, acc.: 52.54%] [G loss: 0.712506]
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4258 [D loss: 0.693713, acc.: 51.17%] [G loss: 0.716009]
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4259 [D loss: 0.697379, acc.: 51.17%] [G loss: 0.708499]
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4260 [D loss: 0.698150, acc.: 51.95%] [G loss: 0.696180]
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4261 [D loss: 0.696025, acc.: 49.80%] [G loss: 0.703982]
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4262 [D loss: 0.708947, acc.: 46.88%] [G loss: 0.707089]
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4263 [D loss: 0.692012, acc.: 50.20%] [G loss: 0.704638]
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4264 [D loss: 0.688401, acc.: 56.84%] [G loss: 0.729013]
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4265 [D loss: 0.689879, acc.: 53.52%] [G loss: 0.739441]
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4266 [D loss: 0.687604, acc.: 54.49%] [G loss: 0.751525]
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4267 [D loss: 0.686796, acc.: 51.95%] [G loss: 0.764668]
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4268 [D loss: 0.687213, acc.: 55.66%] [G loss: 0.760055]
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4269 [D loss: 0.688210, acc.: 53.32%] [G loss: 0.745429]
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4270 [D loss: 0.693215, acc.: 50.78%] [G loss: 0.746847]
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4271 [D loss: 0.692350, acc.: 51.76%] [G loss: 0.731093]
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4272 [D loss: 0.689004, acc.: 51.95%] [G loss: 0.716421]
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4273 [D loss: 0.692762, acc.: 52.34%] [G loss: 0.719668]
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4274 [D loss: 0.687867, acc.: 53.12%] [G loss: 0.725356]
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4275 [D loss: 0.690323, acc.: 49.41%] [G loss: 0.713662]
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4276 [D loss: 0.698842, acc.: 49.80%] [G loss: 0.714619]
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4277 [D loss: 0.702593, acc.: 51.76%] [G loss: 0.709762]
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4278 [D loss: 0.693932, acc.: 51.56%] [G loss: 0.717580]
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4279 [D loss: 0.684548, acc.: 59.18%] [G loss: 0.736156]
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4280 [D loss: 0.695160, acc.: 52.34%] [G loss: 0.744747]
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4281 [D loss: 0.680718, acc.: 56.64%] [G loss: 0.740059]
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4282 [D loss: 0.698223, acc.: 51.17%] [G loss: 0.743675]
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4283 [D loss: 0.696277, acc.: 49.41%] [G loss: 0.746271]
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4284 [D loss: 0.691266, acc.: 52.54%] [G loss: 0.743834]
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4285 [D loss: 0.693143, acc.: 51.37%] [G loss: 0.740939]
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4286 [D loss: 0.693800, acc.: 50.98%] [G loss: 0.738367]
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4287 [D loss: 0.679266, acc.: 58.79%] [G loss: 0.742470]
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4288 [D loss: 0.686876, acc.: 52.93%] [G loss: 0.729305]
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4289 [D loss: 0.684401, acc.: 55.47%] [G loss: 0.732007]
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4290 [D loss: 0.692509, acc.: 52.93%] [G loss: 0.718401]
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4291 [D loss: 0.688553, acc.: 56.05%] [G loss: 0.708992]
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4292 [D loss: 0.694881, acc.: 50.98%] [G loss: 0.709184]
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4293 [D loss: 0.698277, acc.: 50.00%] [G loss: 0.703489]
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4294 [D loss: 0.699955, acc.: 49.02%] [G loss: 0.713565]
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4295 [D loss: 0.703447, acc.: 47.07%] [G loss: 0.728426]
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4296 [D loss: 0.696528, acc.: 48.83%] [G loss: 0.753823]
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4297 [D loss: 0.695876, acc.: 50.00%] [G loss: 0.739929]
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4298 [D loss: 0.693149, acc.: 51.95%] [G loss: 0.742738]
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4299 [D loss: 0.694006, acc.: 51.56%] [G loss: 0.749802]
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4300 [D loss: 0.695997, acc.: 50.98%] [G loss: 0.745649]
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4301 [D loss: 0.687094, acc.: 54.69%] [G loss: 0.734570]
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4302 [D loss: 0.692690, acc.: 52.93%] [G loss: 0.738206]
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4303 [D loss: 0.697118, acc.: 48.44%] [G loss: 0.732210]
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4304 [D loss: 0.691393, acc.: 53.12%] [G loss: 0.728503]
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4305 [D loss: 0.689931, acc.: 54.88%] [G loss: 0.724090]
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4306 [D loss: 0.689155, acc.: 51.76%] [G loss: 0.711581]
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4307 [D loss: 0.691437, acc.: 52.34%] [G loss: 0.713698]
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4308 [D loss: 0.698666, acc.: 47.85%] [G loss: 0.702113]
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4309 [D loss: 0.699336, acc.: 46.88%] [G loss: 0.709389]
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4310 [D loss: 0.697251, acc.: 49.02%] [G loss: 0.728754]
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4311 [D loss: 0.693088, acc.: 49.80%] [G loss: 0.731825]
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4312 [D loss: 0.699379, acc.: 47.46%] [G loss: 0.741955]
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4313 [D loss: 0.699662, acc.: 47.66%] [G loss: 0.727177]
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4314 [D loss: 0.697557, acc.: 50.20%] [G loss: 0.734286]
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4315 [D loss: 0.683670, acc.: 56.84%] [G loss: 0.741357]
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4316 [D loss: 0.693162, acc.: 51.56%] [G loss: 0.734051]
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4317 [D loss: 0.689033, acc.: 52.15%] [G loss: 0.729795]
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4318 [D loss: 0.687809, acc.: 52.73%] [G loss: 0.722717]
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4319 [D loss: 0.681635, acc.: 55.86%] [G loss: 0.726581]
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4320 [D loss: 0.687849, acc.: 57.23%] [G loss: 0.722187]
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4321 [D loss: 0.681111, acc.: 57.23%] [G loss: 0.718354]
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4322 [D loss: 0.692807, acc.: 50.39%] [G loss: 0.713054]
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4323 [D loss: 0.694046, acc.: 49.61%] [G loss: 0.704341]
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4324 [D loss: 0.695917, acc.: 51.37%] [G loss: 0.710675]
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4325 [D loss: 0.692208, acc.: 53.12%] [G loss: 0.709678]
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4326 [D loss: 0.699710, acc.: 50.00%] [G loss: 0.717174]
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4327 [D loss: 0.693295, acc.: 52.93%] [G loss: 0.725745]
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4328 [D loss: 0.695126, acc.: 52.93%] [G loss: 0.729504]
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4329 [D loss: 0.704375, acc.: 48.05%] [G loss: 0.722843]
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4330 [D loss: 0.697450, acc.: 50.59%] [G loss: 0.736447]
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4331 [D loss: 0.687431, acc.: 53.71%] [G loss: 0.736248]
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4332 [D loss: 0.688822, acc.: 55.27%] [G loss: 0.735137]
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4333 [D loss: 0.684883, acc.: 56.25%] [G loss: 0.731015]
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4334 [D loss: 0.680670, acc.: 59.18%] [G loss: 0.752649]
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4335 [D loss: 0.680458, acc.: 57.81%] [G loss: 0.738151]
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4336 [D loss: 0.679272, acc.: 57.62%] [G loss: 0.737632]
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4337 [D loss: 0.684910, acc.: 56.05%] [G loss: 0.741302]
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4338 [D loss: 0.691000, acc.: 54.88%] [G loss: 0.719604]
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4339 [D loss: 0.697900, acc.: 51.17%] [G loss: 0.709444]
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4340 [D loss: 0.701330, acc.: 49.02%] [G loss: 0.701305]
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4341 [D loss: 0.700531, acc.: 50.59%] [G loss: 0.702693]
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4342 [D loss: 0.697949, acc.: 49.22%] [G loss: 0.700309]
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4343 [D loss: 0.710268, acc.: 43.75%] [G loss: 0.702709]
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4344 [D loss: 0.701850, acc.: 47.27%] [G loss: 0.721555]
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4345 [D loss: 0.693175, acc.: 49.41%] [G loss: 0.740614]
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4346 [D loss: 0.691174, acc.: 49.02%] [G loss: 0.757237]
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4347 [D loss: 0.692513, acc.: 46.48%] [G loss: 0.757081]
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4348 [D loss: 0.684264, acc.: 54.69%] [G loss: 0.748633]
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4349 [D loss: 0.687629, acc.: 51.17%] [G loss: 0.740045]
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4350 [D loss: 0.691336, acc.: 52.73%] [G loss: 0.731999]
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4351 [D loss: 0.689789, acc.: 55.27%] [G loss: 0.733216]
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4352 [D loss: 0.686552, acc.: 55.47%] [G loss: 0.722101]
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4353 [D loss: 0.687279, acc.: 58.01%] [G loss: 0.710514]
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4354 [D loss: 0.689730, acc.: 54.88%] [G loss: 0.702156]
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4355 [D loss: 0.688991, acc.: 52.15%] [G loss: 0.697106]
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4356 [D loss: 0.694265, acc.: 50.98%] [G loss: 0.691895]
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4357 [D loss: 0.696255, acc.: 51.95%] [G loss: 0.703591]
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4358 [D loss: 0.695120, acc.: 49.22%] [G loss: 0.710997]
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4359 [D loss: 0.701188, acc.: 44.53%] [G loss: 0.718600]
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4360 [D loss: 0.699517, acc.: 46.48%] [G loss: 0.739123]
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4361 [D loss: 0.696141, acc.: 49.22%] [G loss: 0.735762]
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4362 [D loss: 0.693839, acc.: 51.37%] [G loss: 0.746125]
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4363 [D loss: 0.703893, acc.: 48.24%] [G loss: 0.732239]
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4364 [D loss: 0.689426, acc.: 51.56%] [G loss: 0.733396]
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4365 [D loss: 0.689372, acc.: 53.12%] [G loss: 0.743239]
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4366 [D loss: 0.682697, acc.: 57.81%] [G loss: 0.728667]
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4367 [D loss: 0.677659, acc.: 61.13%] [G loss: 0.738467]
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4368 [D loss: 0.692552, acc.: 51.17%] [G loss: 0.723454]
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4369 [D loss: 0.699368, acc.: 48.05%] [G loss: 0.723718]
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4370 [D loss: 0.695259, acc.: 49.61%] [G loss: 0.713777]
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4371 [D loss: 0.694115, acc.: 51.95%] [G loss: 0.719583]
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4372 [D loss: 0.692315, acc.: 54.69%] [G loss: 0.716309]
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4373 [D loss: 0.689219, acc.: 52.73%] [G loss: 0.736489]
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4374 [D loss: 0.691375, acc.: 52.54%] [G loss: 0.744739]
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4375 [D loss: 0.697587, acc.: 52.15%] [G loss: 0.732469]
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4376 [D loss: 0.700644, acc.: 49.22%] [G loss: 0.729769]
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4377 [D loss: 0.701807, acc.: 47.85%] [G loss: 0.734456]
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4378 [D loss: 0.697782, acc.: 50.00%] [G loss: 0.731168]
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4379 [D loss: 0.692626, acc.: 50.20%] [G loss: 0.721041]
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4380 [D loss: 0.691467, acc.: 52.54%] [G loss: 0.725049]
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4381 [D loss: 0.690923, acc.: 53.32%] [G loss: 0.726804]
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4382 [D loss: 0.691741, acc.: 48.63%] [G loss: 0.724399]
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4383 [D loss: 0.689931, acc.: 51.95%] [G loss: 0.717266]
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4384 [D loss: 0.687019, acc.: 52.34%] [G loss: 0.710071]
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4385 [D loss: 0.691766, acc.: 50.98%] [G loss: 0.711946]
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4386 [D loss: 0.691631, acc.: 49.61%] [G loss: 0.708992]
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4387 [D loss: 0.691070, acc.: 51.56%] [G loss: 0.707068]
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4388 [D loss: 0.693447, acc.: 50.78%] [G loss: 0.703072]
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4389 [D loss: 0.701639, acc.: 48.63%] [G loss: 0.709408]
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4390 [D loss: 0.693845, acc.: 51.17%] [G loss: 0.727166]
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4391 [D loss: 0.698146, acc.: 53.52%] [G loss: 0.729098]
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4392 [D loss: 0.699734, acc.: 50.78%] [G loss: 0.733558]
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4393 [D loss: 0.686597, acc.: 57.23%] [G loss: 0.742835]
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4394 [D loss: 0.695094, acc.: 52.54%] [G loss: 0.729013]
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4395 [D loss: 0.694543, acc.: 50.20%] [G loss: 0.720930]
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4396 [D loss: 0.694270, acc.: 51.76%] [G loss: 0.733090]
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4397 [D loss: 0.691140, acc.: 50.98%] [G loss: 0.734269]
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4398 [D loss: 0.692552, acc.: 52.93%] [G loss: 0.726363]
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4399 [D loss: 0.678982, acc.: 59.57%] [G loss: 0.721499]
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4400 [D loss: 0.682779, acc.: 55.47%] [G loss: 0.735510]
1/1 [==============================] - 0s 19ms/step
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4401 [D loss: 0.684099, acc.: 54.88%] [G loss: 0.725177]
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4402 [D loss: 0.686684, acc.: 51.17%] [G loss: 0.721820]
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4403 [D loss: 0.695233, acc.: 45.70%] [G loss: 0.722538]
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4404 [D loss: 0.691708, acc.: 51.37%] [G loss: 0.715139]
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4405 [D loss: 0.686828, acc.: 53.32%] [G loss: 0.723400]
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4406 [D loss: 0.696000, acc.: 52.34%] [G loss: 0.725025]
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4407 [D loss: 0.700368, acc.: 47.66%] [G loss: 0.731108]
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4408 [D loss: 0.696962, acc.: 51.17%] [G loss: 0.736857]
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4409 [D loss: 0.699497, acc.: 50.39%] [G loss: 0.735383]
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4410 [D loss: 0.708613, acc.: 43.16%] [G loss: 0.722249]
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4411 [D loss: 0.695389, acc.: 52.73%] [G loss: 0.717176]
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4412 [D loss: 0.697554, acc.: 48.24%] [G loss: 0.716604]
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4413 [D loss: 0.698243, acc.: 50.39%] [G loss: 0.733992]
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4414 [D loss: 0.690191, acc.: 54.69%] [G loss: 0.727908]
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4415 [D loss: 0.694181, acc.: 51.17%] [G loss: 0.728293]
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4416 [D loss: 0.692821, acc.: 51.17%] [G loss: 0.721749]
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4417 [D loss: 0.691287, acc.: 51.76%] [G loss: 0.718871]
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4418 [D loss: 0.692938, acc.: 50.78%] [G loss: 0.732140]
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4419 [D loss: 0.687961, acc.: 53.12%] [G loss: 0.726711]
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4420 [D loss: 0.689367, acc.: 55.08%] [G loss: 0.721548]
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4421 [D loss: 0.691361, acc.: 54.10%] [G loss: 0.728890]
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4422 [D loss: 0.696124, acc.: 48.24%] [G loss: 0.722208]
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4423 [D loss: 0.695954, acc.: 49.41%] [G loss: 0.708722]
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4424 [D loss: 0.691038, acc.: 52.93%] [G loss: 0.713946]
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4425 [D loss: 0.693532, acc.: 51.56%] [G loss: 0.710522]
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4426 [D loss: 0.700295, acc.: 46.88%] [G loss: 0.709945]
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4427 [D loss: 0.692579, acc.: 51.95%] [G loss: 0.717725]
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4428 [D loss: 0.699415, acc.: 49.22%] [G loss: 0.708622]
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4429 [D loss: 0.690886, acc.: 54.30%] [G loss: 0.715940]
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4430 [D loss: 0.693121, acc.: 50.78%] [G loss: 0.716819]
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4431 [D loss: 0.693470, acc.: 52.93%] [G loss: 0.726727]
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4432 [D loss: 0.684800, acc.: 54.88%] [G loss: 0.721568]
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4433 [D loss: 0.694493, acc.: 49.80%] [G loss: 0.735653]
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4434 [D loss: 0.680796, acc.: 55.08%] [G loss: 0.737057]
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4435 [D loss: 0.692457, acc.: 51.37%] [G loss: 0.731184]
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4436 [D loss: 0.684880, acc.: 58.79%] [G loss: 0.735280]
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4437 [D loss: 0.692350, acc.: 51.95%] [G loss: 0.720250]
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4438 [D loss: 0.696092, acc.: 51.76%] [G loss: 0.730357]
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4439 [D loss: 0.707232, acc.: 43.55%] [G loss: 0.723547]
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4440 [D loss: 0.695465, acc.: 50.00%] [G loss: 0.717134]
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4441 [D loss: 0.703439, acc.: 47.27%] [G loss: 0.713066]
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4442 [D loss: 0.703560, acc.: 47.27%] [G loss: 0.729927]
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4443 [D loss: 0.696991, acc.: 48.44%] [G loss: 0.730437]
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4444 [D loss: 0.694478, acc.: 50.98%] [G loss: 0.737848]
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4445 [D loss: 0.687494, acc.: 53.91%] [G loss: 0.743805]
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4446 [D loss: 0.697567, acc.: 50.59%] [G loss: 0.736365]
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4447 [D loss: 0.692936, acc.: 53.71%] [G loss: 0.739344]
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4448 [D loss: 0.682668, acc.: 57.42%] [G loss: 0.737945]
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4449 [D loss: 0.690130, acc.: 49.22%] [G loss: 0.735124]
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4450 [D loss: 0.688713, acc.: 53.12%] [G loss: 0.731858]
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4451 [D loss: 0.691773, acc.: 53.52%] [G loss: 0.720083]
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4452 [D loss: 0.694215, acc.: 49.80%] [G loss: 0.728712]
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4453 [D loss: 0.689994, acc.: 51.76%] [G loss: 0.711058]
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4454 [D loss: 0.694936, acc.: 48.83%] [G loss: 0.720606]
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4455 [D loss: 0.700696, acc.: 47.85%] [G loss: 0.722922]
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4456 [D loss: 0.693050, acc.: 50.39%] [G loss: 0.724163]
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4457 [D loss: 0.696503, acc.: 50.20%] [G loss: 0.727173]
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4458 [D loss: 0.690052, acc.: 50.39%] [G loss: 0.735778]
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4459 [D loss: 0.698828, acc.: 48.05%] [G loss: 0.738418]
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4460 [D loss: 0.691998, acc.: 51.95%] [G loss: 0.740485]
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4461 [D loss: 0.693906, acc.: 50.59%] [G loss: 0.740271]
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4462 [D loss: 0.697270, acc.: 50.98%] [G loss: 0.740442]
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4463 [D loss: 0.688914, acc.: 52.54%] [G loss: 0.725529]
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4464 [D loss: 0.692834, acc.: 51.37%] [G loss: 0.732917]
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4465 [D loss: 0.699089, acc.: 46.09%] [G loss: 0.725439]
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4466 [D loss: 0.681728, acc.: 56.25%] [G loss: 0.734503]
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4467 [D loss: 0.682034, acc.: 55.08%] [G loss: 0.727139]
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4468 [D loss: 0.682177, acc.: 58.59%] [G loss: 0.721115]
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4469 [D loss: 0.686238, acc.: 53.32%] [G loss: 0.721003]
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4470 [D loss: 0.688330, acc.: 53.91%] [G loss: 0.726050]
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4471 [D loss: 0.684802, acc.: 56.05%] [G loss: 0.714082]
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4472 [D loss: 0.696981, acc.: 50.39%] [G loss: 0.714064]
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4473 [D loss: 0.700780, acc.: 48.24%] [G loss: 0.704466]
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4474 [D loss: 0.710513, acc.: 44.14%] [G loss: 0.719775]
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4475 [D loss: 0.698939, acc.: 49.61%] [G loss: 0.718653]
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4476 [D loss: 0.704010, acc.: 46.09%] [G loss: 0.708629]
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4477 [D loss: 0.697476, acc.: 49.02%] [G loss: 0.711443]
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4478 [D loss: 0.703158, acc.: 44.53%] [G loss: 0.725072]
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4479 [D loss: 0.694760, acc.: 48.24%] [G loss: 0.734721]
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4480 [D loss: 0.692161, acc.: 51.95%] [G loss: 0.731301]
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4481 [D loss: 0.691609, acc.: 50.59%] [G loss: 0.733269]
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4482 [D loss: 0.687620, acc.: 53.71%] [G loss: 0.728848]
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4483 [D loss: 0.687559, acc.: 54.49%] [G loss: 0.726276]
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4484 [D loss: 0.681999, acc.: 57.42%] [G loss: 0.726601]
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4485 [D loss: 0.686207, acc.: 53.12%] [G loss: 0.729005]
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4486 [D loss: 0.690097, acc.: 52.93%] [G loss: 0.713067]
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4487 [D loss: 0.693770, acc.: 50.39%] [G loss: 0.713517]
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4488 [D loss: 0.697396, acc.: 50.39%] [G loss: 0.713742]
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4489 [D loss: 0.697926, acc.: 50.20%] [G loss: 0.716832]
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4490 [D loss: 0.698058, acc.: 51.17%] [G loss: 0.717387]
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4491 [D loss: 0.700375, acc.: 49.41%] [G loss: 0.723070]
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4492 [D loss: 0.691551, acc.: 52.73%] [G loss: 0.726752]
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4493 [D loss: 0.699407, acc.: 50.59%] [G loss: 0.725911]
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4494 [D loss: 0.692799, acc.: 53.52%] [G loss: 0.723577]
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4495 [D loss: 0.697256, acc.: 50.78%] [G loss: 0.716706]
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4496 [D loss: 0.696814, acc.: 49.22%] [G loss: 0.732012]
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4497 [D loss: 0.687669, acc.: 55.66%] [G loss: 0.725803]
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4498 [D loss: 0.692270, acc.: 53.52%] [G loss: 0.731330]
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4499 [D loss: 0.691333, acc.: 50.98%] [G loss: 0.723504]
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4500 [D loss: 0.685618, acc.: 55.66%] [G loss: 0.719688]
1/1 [==============================] - 0s 19ms/step
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4501 [D loss: 0.688835, acc.: 54.49%] [G loss: 0.712061]
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4502 [D loss: 0.688774, acc.: 52.93%] [G loss: 0.709657]
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4503 [D loss: 0.693928, acc.: 50.20%] [G loss: 0.714112]
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4504 [D loss: 0.689215, acc.: 53.71%] [G loss: 0.709578]
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4505 [D loss: 0.695601, acc.: 52.34%] [G loss: 0.717287]
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4506 [D loss: 0.694159, acc.: 49.61%] [G loss: 0.735050]
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4507 [D loss: 0.690475, acc.: 53.91%] [G loss: 0.740559]
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4508 [D loss: 0.692977, acc.: 49.02%] [G loss: 0.744593]
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4509 [D loss: 0.688877, acc.: 50.98%] [G loss: 0.741428]
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4510 [D loss: 0.698866, acc.: 47.46%] [G loss: 0.733224]
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4511 [D loss: 0.699686, acc.: 47.46%] [G loss: 0.724052]
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4512 [D loss: 0.693945, acc.: 50.98%] [G loss: 0.721876]
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4513 [D loss: 0.694462, acc.: 49.61%] [G loss: 0.714066]
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4514 [D loss: 0.692061, acc.: 51.17%] [G loss: 0.722633]
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4515 [D loss: 0.697353, acc.: 44.73%] [G loss: 0.710055]
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4516 [D loss: 0.689630, acc.: 53.91%] [G loss: 0.710063]
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4517 [D loss: 0.696376, acc.: 53.12%] [G loss: 0.718122]
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4518 [D loss: 0.698187, acc.: 52.54%] [G loss: 0.714344]
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4519 [D loss: 0.693355, acc.: 51.56%] [G loss: 0.716751]
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4520 [D loss: 0.695790, acc.: 51.37%] [G loss: 0.716675]
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4521 [D loss: 0.694513, acc.: 53.52%] [G loss: 0.731300]
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4522 [D loss: 0.683780, acc.: 58.20%] [G loss: 0.746033]
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4523 [D loss: 0.687565, acc.: 53.32%] [G loss: 0.727597]
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4524 [D loss: 0.685823, acc.: 55.86%] [G loss: 0.749283]
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4525 [D loss: 0.703719, acc.: 47.66%] [G loss: 0.740081]
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4526 [D loss: 0.693011, acc.: 51.95%] [G loss: 0.734678]
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4527 [D loss: 0.703312, acc.: 48.44%] [G loss: 0.726743]
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4528 [D loss: 0.697304, acc.: 48.44%] [G loss: 0.722148]
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4529 [D loss: 0.694421, acc.: 50.78%] [G loss: 0.708303]
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4530 [D loss: 0.698077, acc.: 48.63%] [G loss: 0.705744]
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4531 [D loss: 0.694828, acc.: 47.27%] [G loss: 0.700431]
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4532 [D loss: 0.695919, acc.: 49.02%] [G loss: 0.704279]
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4533 [D loss: 0.697264, acc.: 48.44%] [G loss: 0.712512]
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4534 [D loss: 0.692027, acc.: 51.56%] [G loss: 0.723899]
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4535 [D loss: 0.690029, acc.: 52.93%] [G loss: 0.732877]
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4536 [D loss: 0.691430, acc.: 53.32%] [G loss: 0.738042]
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4537 [D loss: 0.690975, acc.: 50.20%] [G loss: 0.748356]
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4538 [D loss: 0.686081, acc.: 56.64%] [G loss: 0.752644]
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4539 [D loss: 0.694618, acc.: 50.98%] [G loss: 0.744387]
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4540 [D loss: 0.686274, acc.: 57.81%] [G loss: 0.744615]
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4541 [D loss: 0.691151, acc.: 51.95%] [G loss: 0.727124]
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4542 [D loss: 0.692776, acc.: 53.91%] [G loss: 0.736858]
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4543 [D loss: 0.691650, acc.: 54.10%] [G loss: 0.721434]
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4544 [D loss: 0.698544, acc.: 48.83%] [G loss: 0.704254]
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4545 [D loss: 0.693871, acc.: 50.39%] [G loss: 0.703299]
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4546 [D loss: 0.700108, acc.: 44.73%] [G loss: 0.696832]
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4547 [D loss: 0.698532, acc.: 48.63%] [G loss: 0.698311]
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4548 [D loss: 0.696100, acc.: 51.37%] [G loss: 0.712825]
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4549 [D loss: 0.694412, acc.: 51.95%] [G loss: 0.722667]
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4550 [D loss: 0.690094, acc.: 50.20%] [G loss: 0.736503]
1/1 [==============================] - 0s 19ms/step
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4551 [D loss: 0.689409, acc.: 49.02%] [G loss: 0.749884]
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4552 [D loss: 0.686612, acc.: 52.73%] [G loss: 0.744960]
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4553 [D loss: 0.691408, acc.: 48.83%] [G loss: 0.743640]
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4554 [D loss: 0.696197, acc.: 46.88%] [G loss: 0.737481]
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4555 [D loss: 0.693417, acc.: 52.73%] [G loss: 0.732380]
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4556 [D loss: 0.685560, acc.: 56.25%] [G loss: 0.735016]
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4557 [D loss: 0.688788, acc.: 52.34%] [G loss: 0.717839]
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4558 [D loss: 0.697337, acc.: 47.46%] [G loss: 0.723109]
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4559 [D loss: 0.694064, acc.: 52.15%] [G loss: 0.703614]
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4560 [D loss: 0.690074, acc.: 53.12%] [G loss: 0.703538]
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4561 [D loss: 0.695014, acc.: 51.37%] [G loss: 0.695952]
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4562 [D loss: 0.693226, acc.: 52.73%] [G loss: 0.690030]
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4563 [D loss: 0.698739, acc.: 47.85%] [G loss: 0.687306]
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4564 [D loss: 0.694663, acc.: 48.24%] [G loss: 0.699317]
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4565 [D loss: 0.696115, acc.: 46.29%] [G loss: 0.724683]
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4566 [D loss: 0.687868, acc.: 52.15%] [G loss: 0.731007]
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4567 [D loss: 0.693260, acc.: 50.78%] [G loss: 0.755992]
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4568 [D loss: 0.688470, acc.: 55.08%] [G loss: 0.752269]
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4569 [D loss: 0.686573, acc.: 55.47%] [G loss: 0.743757]
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4570 [D loss: 0.692039, acc.: 52.34%] [G loss: 0.741611]
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4571 [D loss: 0.697783, acc.: 49.02%] [G loss: 0.740820]
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4572 [D loss: 0.703592, acc.: 47.46%] [G loss: 0.729509]
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4573 [D loss: 0.693513, acc.: 52.54%] [G loss: 0.722144]
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4574 [D loss: 0.689800, acc.: 50.98%] [G loss: 0.732055]
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4575 [D loss: 0.699415, acc.: 50.39%] [G loss: 0.720927]
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4576 [D loss: 0.691303, acc.: 52.54%] [G loss: 0.716692]
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4577 [D loss: 0.688877, acc.: 52.34%] [G loss: 0.710763]
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4578 [D loss: 0.685107, acc.: 56.64%] [G loss: 0.707723]
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4579 [D loss: 0.693610, acc.: 53.91%] [G loss: 0.707068]
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4580 [D loss: 0.688040, acc.: 52.93%] [G loss: 0.708505]
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4581 [D loss: 0.695312, acc.: 50.98%] [G loss: 0.706240]
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4582 [D loss: 0.695132, acc.: 49.41%] [G loss: 0.719503]
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4583 [D loss: 0.702206, acc.: 48.05%] [G loss: 0.720814]
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4584 [D loss: 0.695467, acc.: 50.98%] [G loss: 0.739333]
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4585 [D loss: 0.689475, acc.: 54.49%] [G loss: 0.738397]
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4586 [D loss: 0.695641, acc.: 51.95%] [G loss: 0.734097]
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4587 [D loss: 0.694450, acc.: 51.76%] [G loss: 0.728978]
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4588 [D loss: 0.695676, acc.: 52.93%] [G loss: 0.727542]
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4589 [D loss: 0.691417, acc.: 54.69%] [G loss: 0.738914]
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4590 [D loss: 0.692566, acc.: 52.73%] [G loss: 0.732843]
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4591 [D loss: 0.687566, acc.: 56.05%] [G loss: 0.729747]
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4592 [D loss: 0.687149, acc.: 56.25%] [G loss: 0.719232]
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4593 [D loss: 0.689215, acc.: 53.12%] [G loss: 0.712507]
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4594 [D loss: 0.692414, acc.: 52.54%] [G loss: 0.709128]
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4595 [D loss: 0.694863, acc.: 51.76%] [G loss: 0.700523]
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4596 [D loss: 0.699682, acc.: 48.44%] [G loss: 0.702210]
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4597 [D loss: 0.700576, acc.: 48.24%] [G loss: 0.708006]
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4598 [D loss: 0.689565, acc.: 53.12%] [G loss: 0.708706]
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4599 [D loss: 0.698086, acc.: 52.54%] [G loss: 0.725089]
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4600 [D loss: 0.693784, acc.: 53.32%] [G loss: 0.734940]
1/1 [==============================] - 0s 17ms/step
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4601 [D loss: 0.690897, acc.: 50.20%] [G loss: 0.733515]
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4602 [D loss: 0.686985, acc.: 56.05%] [G loss: 0.735398]
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4603 [D loss: 0.694404, acc.: 50.59%] [G loss: 0.741058]
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4604 [D loss: 0.687867, acc.: 57.23%] [G loss: 0.733106]
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4605 [D loss: 0.687723, acc.: 54.88%] [G loss: 0.741554]
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4606 [D loss: 0.686791, acc.: 54.30%] [G loss: 0.730998]
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4607 [D loss: 0.680947, acc.: 59.57%] [G loss: 0.738659]
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4608 [D loss: 0.691522, acc.: 51.17%] [G loss: 0.729110]
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4609 [D loss: 0.682971, acc.: 55.86%] [G loss: 0.728927]
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4610 [D loss: 0.693740, acc.: 50.78%] [G loss: 0.722917]
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4611 [D loss: 0.682977, acc.: 57.81%] [G loss: 0.710467]
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4612 [D loss: 0.694654, acc.: 51.56%] [G loss: 0.718676]
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4613 [D loss: 0.697627, acc.: 50.39%] [G loss: 0.713769]
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4614 [D loss: 0.697515, acc.: 47.66%] [G loss: 0.732035]
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4615 [D loss: 0.694323, acc.: 50.78%] [G loss: 0.740292]
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4616 [D loss: 0.693262, acc.: 50.20%] [G loss: 0.752479]
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4617 [D loss: 0.692236, acc.: 51.37%] [G loss: 0.739985]
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4618 [D loss: 0.697602, acc.: 51.76%] [G loss: 0.729867]
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4619 [D loss: 0.695966, acc.: 48.63%] [G loss: 0.726939]
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4620 [D loss: 0.700486, acc.: 51.37%] [G loss: 0.707592]
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4621 [D loss: 0.695221, acc.: 50.59%] [G loss: 0.714198]
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4622 [D loss: 0.695868, acc.: 48.24%] [G loss: 0.712070]
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4623 [D loss: 0.696210, acc.: 49.41%] [G loss: 0.706784]
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4624 [D loss: 0.691259, acc.: 50.78%] [G loss: 0.715584]
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4625 [D loss: 0.691581, acc.: 52.15%] [G loss: 0.720620]
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4626 [D loss: 0.690499, acc.: 50.78%] [G loss: 0.723026]
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4627 [D loss: 0.687329, acc.: 55.27%] [G loss: 0.726180]
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4628 [D loss: 0.689941, acc.: 54.30%] [G loss: 0.738114]
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4629 [D loss: 0.693722, acc.: 50.98%] [G loss: 0.736609]
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4630 [D loss: 0.687342, acc.: 51.76%] [G loss: 0.730705]
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4631 [D loss: 0.692996, acc.: 50.78%] [G loss: 0.738594]
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4632 [D loss: 0.688281, acc.: 53.12%] [G loss: 0.729537]
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4633 [D loss: 0.690722, acc.: 52.15%] [G loss: 0.723801]
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4634 [D loss: 0.693709, acc.: 51.76%] [G loss: 0.722015]
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4635 [D loss: 0.694284, acc.: 48.44%] [G loss: 0.717716]
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4636 [D loss: 0.694007, acc.: 50.39%] [G loss: 0.694756]
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4637 [D loss: 0.699541, acc.: 46.48%] [G loss: 0.697756]
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4638 [D loss: 0.699160, acc.: 47.27%] [G loss: 0.694108]
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4639 [D loss: 0.702164, acc.: 44.34%] [G loss: 0.694195]
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4640 [D loss: 0.702687, acc.: 47.46%] [G loss: 0.692072]
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4641 [D loss: 0.697521, acc.: 47.07%] [G loss: 0.712898]
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4642 [D loss: 0.695022, acc.: 47.85%] [G loss: 0.730404]
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4643 [D loss: 0.686272, acc.: 53.91%] [G loss: 0.746019]
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4644 [D loss: 0.688682, acc.: 51.37%] [G loss: 0.750482]
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4645 [D loss: 0.689695, acc.: 51.17%] [G loss: 0.732993]
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4646 [D loss: 0.685323, acc.: 56.45%] [G loss: 0.749713]
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4647 [D loss: 0.684081, acc.: 55.47%] [G loss: 0.741176]
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4648 [D loss: 0.688920, acc.: 53.71%] [G loss: 0.727377]
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4649 [D loss: 0.691932, acc.: 54.49%] [G loss: 0.731302]
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4650 [D loss: 0.694885, acc.: 53.52%] [G loss: 0.709283]
1/1 [==============================] - 0s 17ms/step
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4651 [D loss: 0.691214, acc.: 51.95%] [G loss: 0.709997]
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4652 [D loss: 0.691368, acc.: 51.95%] [G loss: 0.702439]
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4653 [D loss: 0.693381, acc.: 49.22%] [G loss: 0.699075]
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4654 [D loss: 0.697935, acc.: 47.07%] [G loss: 0.702362]
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4655 [D loss: 0.691946, acc.: 51.76%] [G loss: 0.707151]
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4656 [D loss: 0.690150, acc.: 51.37%] [G loss: 0.733169]
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4657 [D loss: 0.683161, acc.: 52.15%] [G loss: 0.732645]
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4658 [D loss: 0.687414, acc.: 52.15%] [G loss: 0.727661]
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4659 [D loss: 0.692700, acc.: 51.56%] [G loss: 0.729216]
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4660 [D loss: 0.699382, acc.: 47.46%] [G loss: 0.731585]
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4661 [D loss: 0.699176, acc.: 46.88%] [G loss: 0.708914]
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4662 [D loss: 0.700904, acc.: 45.51%] [G loss: 0.703419]
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4663 [D loss: 0.706848, acc.: 45.90%] [G loss: 0.700502]
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4664 [D loss: 0.702329, acc.: 44.53%] [G loss: 0.708475]
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4665 [D loss: 0.700331, acc.: 46.48%] [G loss: 0.706685]
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4666 [D loss: 0.696335, acc.: 50.78%] [G loss: 0.705901]
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4667 [D loss: 0.695264, acc.: 53.12%] [G loss: 0.721478]
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4668 [D loss: 0.692871, acc.: 52.54%] [G loss: 0.715221]
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4669 [D loss: 0.693174, acc.: 50.98%] [G loss: 0.734124]
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4670 [D loss: 0.689208, acc.: 50.59%] [G loss: 0.739889]
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4671 [D loss: 0.687933, acc.: 53.91%] [G loss: 0.742760]
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4672 [D loss: 0.688297, acc.: 51.37%] [G loss: 0.735906]
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4673 [D loss: 0.688229, acc.: 55.08%] [G loss: 0.732389]
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4674 [D loss: 0.688079, acc.: 52.54%] [G loss: 0.739112]
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4675 [D loss: 0.687834, acc.: 52.73%] [G loss: 0.732639]
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4676 [D loss: 0.692531, acc.: 50.00%] [G loss: 0.733977]
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4677 [D loss: 0.694880, acc.: 50.98%] [G loss: 0.721870]
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4678 [D loss: 0.689157, acc.: 53.12%] [G loss: 0.720988]
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4679 [D loss: 0.688430, acc.: 53.91%] [G loss: 0.709011]
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4680 [D loss: 0.684680, acc.: 55.08%] [G loss: 0.709052]
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4681 [D loss: 0.696995, acc.: 51.95%] [G loss: 0.719761]
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4682 [D loss: 0.697191, acc.: 50.00%] [G loss: 0.714974]
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4683 [D loss: 0.700949, acc.: 48.83%] [G loss: 0.728915]
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4684 [D loss: 0.696599, acc.: 50.59%] [G loss: 0.732144]
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4685 [D loss: 0.693764, acc.: 51.37%] [G loss: 0.722361]
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4686 [D loss: 0.693431, acc.: 53.12%] [G loss: 0.717982]
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4687 [D loss: 0.700005, acc.: 49.41%] [G loss: 0.710102]
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4688 [D loss: 0.698056, acc.: 49.22%] [G loss: 0.718166]
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4689 [D loss: 0.702766, acc.: 44.92%] [G loss: 0.704627]
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4690 [D loss: 0.696974, acc.: 49.41%] [G loss: 0.720038]
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4691 [D loss: 0.697324, acc.: 47.07%] [G loss: 0.712022]
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4692 [D loss: 0.702104, acc.: 45.31%] [G loss: 0.716008]
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4693 [D loss: 0.697827, acc.: 49.02%] [G loss: 0.715537]
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4694 [D loss: 0.699858, acc.: 48.44%] [G loss: 0.717758]
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4695 [D loss: 0.695644, acc.: 49.61%] [G loss: 0.720132]
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4696 [D loss: 0.694423, acc.: 49.80%] [G loss: 0.724145]
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4697 [D loss: 0.686129, acc.: 56.05%] [G loss: 0.727958]
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4698 [D loss: 0.692964, acc.: 51.37%] [G loss: 0.753098]
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4699 [D loss: 0.691860, acc.: 52.34%] [G loss: 0.737447]
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4700 [D loss: 0.692631, acc.: 53.71%] [G loss: 0.730647]
1/1 [==============================] - 0s 21ms/step
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4701 [D loss: 0.686751, acc.: 55.86%] [G loss: 0.724803]
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4702 [D loss: 0.695245, acc.: 51.17%] [G loss: 0.722321]
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4703 [D loss: 0.692955, acc.: 51.17%] [G loss: 0.728415]
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4704 [D loss: 0.693698, acc.: 52.54%] [G loss: 0.703879]
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4705 [D loss: 0.694882, acc.: 51.37%] [G loss: 0.713939]
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4706 [D loss: 0.690940, acc.: 52.15%] [G loss: 0.707198]
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4707 [D loss: 0.694544, acc.: 50.78%] [G loss: 0.704635]
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4708 [D loss: 0.690296, acc.: 49.22%] [G loss: 0.709444]
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4709 [D loss: 0.691459, acc.: 54.69%] [G loss: 0.712418]
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4710 [D loss: 0.694370, acc.: 50.78%] [G loss: 0.719258]
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4711 [D loss: 0.693706, acc.: 50.20%] [G loss: 0.714226]
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4712 [D loss: 0.694391, acc.: 48.83%] [G loss: 0.720987]
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4713 [D loss: 0.695333, acc.: 49.80%] [G loss: 0.721188]
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4714 [D loss: 0.691410, acc.: 51.56%] [G loss: 0.725558]
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4715 [D loss: 0.691061, acc.: 48.83%] [G loss: 0.727179]
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4716 [D loss: 0.693807, acc.: 49.41%] [G loss: 0.727609]
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4717 [D loss: 0.692867, acc.: 48.05%] [G loss: 0.727906]
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4718 [D loss: 0.689449, acc.: 52.93%] [G loss: 0.718804]
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4719 [D loss: 0.695901, acc.: 50.59%] [G loss: 0.714383]
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4720 [D loss: 0.695203, acc.: 47.66%] [G loss: 0.727053]
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4721 [D loss: 0.697561, acc.: 52.15%] [G loss: 0.718648]
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4722 [D loss: 0.696592, acc.: 49.61%] [G loss: 0.719499]
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4723 [D loss: 0.688850, acc.: 51.76%] [G loss: 0.721821]
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4724 [D loss: 0.692743, acc.: 53.32%] [G loss: 0.715533]
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4725 [D loss: 0.695734, acc.: 46.48%] [G loss: 0.721534]
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4726 [D loss: 0.694925, acc.: 51.37%] [G loss: 0.722594]
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4727 [D loss: 0.694702, acc.: 51.95%] [G loss: 0.727929]
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4728 [D loss: 0.693865, acc.: 53.71%] [G loss: 0.723222]
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4729 [D loss: 0.690405, acc.: 53.91%] [G loss: 0.723489]
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4730 [D loss: 0.693535, acc.: 51.17%] [G loss: 0.728874]
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4731 [D loss: 0.685478, acc.: 54.69%] [G loss: 0.718541]
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4732 [D loss: 0.691876, acc.: 50.00%] [G loss: 0.715538]
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4733 [D loss: 0.686684, acc.: 53.91%] [G loss: 0.712658]
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4734 [D loss: 0.685764, acc.: 55.86%] [G loss: 0.713516]
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4735 [D loss: 0.692297, acc.: 51.95%] [G loss: 0.724391]
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4736 [D loss: 0.687456, acc.: 51.37%] [G loss: 0.718946]
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4737 [D loss: 0.684982, acc.: 57.03%] [G loss: 0.721926]
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4738 [D loss: 0.691602, acc.: 51.56%] [G loss: 0.718813]
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4739 [D loss: 0.689132, acc.: 55.27%] [G loss: 0.718581]
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4740 [D loss: 0.697204, acc.: 50.20%] [G loss: 0.711930]
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4741 [D loss: 0.695803, acc.: 48.24%] [G loss: 0.713392]
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4742 [D loss: 0.696590, acc.: 49.02%] [G loss: 0.708950]
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4743 [D loss: 0.700616, acc.: 45.70%] [G loss: 0.701868]
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4744 [D loss: 0.695177, acc.: 47.27%] [G loss: 0.710286]
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4745 [D loss: 0.691235, acc.: 52.15%] [G loss: 0.720307]
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4746 [D loss: 0.690369, acc.: 50.98%] [G loss: 0.730004]
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4747 [D loss: 0.691413, acc.: 55.08%] [G loss: 0.741037]
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4748 [D loss: 0.687611, acc.: 53.71%] [G loss: 0.752204]
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4749 [D loss: 0.688531, acc.: 55.47%] [G loss: 0.743639]
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4750 [D loss: 0.692709, acc.: 53.71%] [G loss: 0.735566]
1/1 [==============================] - 0s 16ms/step
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4751 [D loss: 0.686711, acc.: 54.69%] [G loss: 0.734319]
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4752 [D loss: 0.684619, acc.: 54.69%] [G loss: 0.724436]
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4753 [D loss: 0.686137, acc.: 55.47%] [G loss: 0.718909]
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4754 [D loss: 0.692571, acc.: 50.59%] [G loss: 0.709764]
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4755 [D loss: 0.691260, acc.: 52.15%] [G loss: 0.716549]
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4756 [D loss: 0.701579, acc.: 46.68%] [G loss: 0.706318]
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4757 [D loss: 0.697673, acc.: 47.66%] [G loss: 0.698611]
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4758 [D loss: 0.695307, acc.: 49.22%] [G loss: 0.717050]
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4759 [D loss: 0.694572, acc.: 50.78%] [G loss: 0.726863]
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4760 [D loss: 0.692570, acc.: 52.93%] [G loss: 0.738847]
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4761 [D loss: 0.697344, acc.: 50.39%] [G loss: 0.732021]
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4762 [D loss: 0.699047, acc.: 46.48%] [G loss: 0.724019]
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4763 [D loss: 0.690798, acc.: 51.56%] [G loss: 0.728702]
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4764 [D loss: 0.691961, acc.: 52.34%] [G loss: 0.726122]
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4765 [D loss: 0.693056, acc.: 52.73%] [G loss: 0.714040]
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4766 [D loss: 0.692117, acc.: 50.78%] [G loss: 0.717347]
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4767 [D loss: 0.701837, acc.: 44.73%] [G loss: 0.698672]
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4768 [D loss: 0.699991, acc.: 48.63%] [G loss: 0.701675]
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4769 [D loss: 0.703990, acc.: 43.36%] [G loss: 0.702249]
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4770 [D loss: 0.703789, acc.: 45.31%] [G loss: 0.714246]
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4771 [D loss: 0.701870, acc.: 49.80%] [G loss: 0.720055]
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4772 [D loss: 0.697727, acc.: 49.61%] [G loss: 0.728346]
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4773 [D loss: 0.689187, acc.: 53.32%] [G loss: 0.735421]
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4774 [D loss: 0.690294, acc.: 54.10%] [G loss: 0.747910]
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4775 [D loss: 0.684653, acc.: 53.52%] [G loss: 0.750480]
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4776 [D loss: 0.690636, acc.: 54.49%] [G loss: 0.738872]
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4777 [D loss: 0.687513, acc.: 53.12%] [G loss: 0.748235]
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4778 [D loss: 0.690659, acc.: 52.93%] [G loss: 0.742198]
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4779 [D loss: 0.690376, acc.: 52.34%] [G loss: 0.726290]
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4780 [D loss: 0.694146, acc.: 50.20%] [G loss: 0.725238]
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4781 [D loss: 0.695267, acc.: 50.39%] [G loss: 0.710328]
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4782 [D loss: 0.697563, acc.: 50.00%] [G loss: 0.706211]
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4783 [D loss: 0.693015, acc.: 52.93%] [G loss: 0.694613]
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4784 [D loss: 0.700658, acc.: 49.02%] [G loss: 0.704668]
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4785 [D loss: 0.697556, acc.: 46.68%] [G loss: 0.699761]
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4786 [D loss: 0.693369, acc.: 51.76%] [G loss: 0.712555]
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4787 [D loss: 0.690043, acc.: 51.76%] [G loss: 0.732486]
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4788 [D loss: 0.689998, acc.: 51.37%] [G loss: 0.750818]
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4789 [D loss: 0.687170, acc.: 52.34%] [G loss: 0.754591]
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4790 [D loss: 0.687263, acc.: 53.12%] [G loss: 0.742682]
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4791 [D loss: 0.694636, acc.: 50.39%] [G loss: 0.732764]
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4792 [D loss: 0.688887, acc.: 52.54%] [G loss: 0.719936]
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4793 [D loss: 0.699147, acc.: 48.44%] [G loss: 0.724317]
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4794 [D loss: 0.695826, acc.: 51.37%] [G loss: 0.711208]
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4795 [D loss: 0.695488, acc.: 51.95%] [G loss: 0.708476]
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4796 [D loss: 0.695867, acc.: 52.73%] [G loss: 0.703356]
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4797 [D loss: 0.697674, acc.: 47.07%] [G loss: 0.695755]
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4798 [D loss: 0.700453, acc.: 48.24%] [G loss: 0.685154]
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4799 [D loss: 0.696410, acc.: 49.61%] [G loss: 0.706828]
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4800 [D loss: 0.695598, acc.: 52.54%] [G loss: 0.717605]
1/1 [==============================] - 0s 26ms/step
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4801 [D loss: 0.700750, acc.: 46.29%] [G loss: 0.737298]
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4802 [D loss: 0.694801, acc.: 50.00%] [G loss: 0.741947]
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4803 [D loss: 0.687787, acc.: 53.32%] [G loss: 0.748514]
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4804 [D loss: 0.689507, acc.: 52.54%] [G loss: 0.740130]
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4805 [D loss: 0.693519, acc.: 53.91%] [G loss: 0.739335]
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4806 [D loss: 0.701896, acc.: 43.16%] [G loss: 0.726438]
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4807 [D loss: 0.696379, acc.: 48.83%] [G loss: 0.723598]
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4808 [D loss: 0.691934, acc.: 51.95%] [G loss: 0.727593]
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4809 [D loss: 0.690389, acc.: 52.93%] [G loss: 0.722351]
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4810 [D loss: 0.689326, acc.: 52.73%] [G loss: 0.715940]
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4811 [D loss: 0.691389, acc.: 51.56%] [G loss: 0.702911]
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4812 [D loss: 0.703028, acc.: 44.34%] [G loss: 0.702666]
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4813 [D loss: 0.703916, acc.: 45.70%] [G loss: 0.698962]
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4814 [D loss: 0.705088, acc.: 47.66%] [G loss: 0.711801]
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4815 [D loss: 0.697069, acc.: 50.39%] [G loss: 0.758235]
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4816 [D loss: 0.687905, acc.: 51.76%] [G loss: 0.769656]
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4817 [D loss: 0.689745, acc.: 52.34%] [G loss: 0.765781]
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4818 [D loss: 0.691786, acc.: 52.15%] [G loss: 0.752308]
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4819 [D loss: 0.699678, acc.: 49.02%] [G loss: 0.738479]
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4820 [D loss: 0.695448, acc.: 48.63%] [G loss: 0.738697]
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4821 [D loss: 0.693790, acc.: 54.10%] [G loss: 0.747461]
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4822 [D loss: 0.682722, acc.: 60.35%] [G loss: 0.733641]
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4823 [D loss: 0.687241, acc.: 53.71%] [G loss: 0.719994]
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4824 [D loss: 0.689349, acc.: 52.73%] [G loss: 0.705238]
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4825 [D loss: 0.689704, acc.: 50.39%] [G loss: 0.704493]
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4826 [D loss: 0.696138, acc.: 48.63%] [G loss: 0.699556]
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4827 [D loss: 0.698583, acc.: 51.56%] [G loss: 0.711320]
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4828 [D loss: 0.695007, acc.: 49.22%] [G loss: 0.719576]
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4829 [D loss: 0.697002, acc.: 48.24%] [G loss: 0.720947]
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4830 [D loss: 0.692831, acc.: 50.98%] [G loss: 0.725131]
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4831 [D loss: 0.694404, acc.: 50.39%] [G loss: 0.732602]
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4832 [D loss: 0.694551, acc.: 48.83%] [G loss: 0.728213]
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4833 [D loss: 0.693348, acc.: 52.73%] [G loss: 0.722086]
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4834 [D loss: 0.696370, acc.: 53.52%] [G loss: 0.722224]
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4835 [D loss: 0.696535, acc.: 48.83%] [G loss: 0.726032]
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4836 [D loss: 0.695004, acc.: 48.44%] [G loss: 0.719512]
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4837 [D loss: 0.694609, acc.: 49.22%] [G loss: 0.717847]
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4838 [D loss: 0.689862, acc.: 53.52%] [G loss: 0.721534]
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4839 [D loss: 0.687720, acc.: 54.49%] [G loss: 0.717023]
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4840 [D loss: 0.692616, acc.: 49.80%] [G loss: 0.714870]
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4841 [D loss: 0.691781, acc.: 54.69%] [G loss: 0.720556]
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4842 [D loss: 0.693758, acc.: 50.98%] [G loss: 0.718131]
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4843 [D loss: 0.692552, acc.: 53.52%] [G loss: 0.714015]
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4844 [D loss: 0.695639, acc.: 49.41%] [G loss: 0.717595]
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4845 [D loss: 0.693968, acc.: 50.39%] [G loss: 0.714185]
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4846 [D loss: 0.695292, acc.: 47.66%] [G loss: 0.731248]
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4847 [D loss: 0.689237, acc.: 53.12%] [G loss: 0.730351]
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4848 [D loss: 0.685543, acc.: 55.08%] [G loss: 0.731630]
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4849 [D loss: 0.683473, acc.: 56.05%] [G loss: 0.733889]
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4850 [D loss: 0.696102, acc.: 48.24%] [G loss: 0.732039]
1/1 [==============================] - 0s 19ms/step
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4851 [D loss: 0.687825, acc.: 55.47%] [G loss: 0.724327]
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4852 [D loss: 0.686431, acc.: 51.95%] [G loss: 0.727033]
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4853 [D loss: 0.684666, acc.: 55.47%] [G loss: 0.718106]
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4854 [D loss: 0.680634, acc.: 57.23%] [G loss: 0.720223]
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4855 [D loss: 0.688781, acc.: 53.32%] [G loss: 0.710335]
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4856 [D loss: 0.693676, acc.: 51.56%] [G loss: 0.703318]
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4857 [D loss: 0.693903, acc.: 50.59%] [G loss: 0.703905]
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4858 [D loss: 0.700141, acc.: 48.83%] [G loss: 0.701969]
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4859 [D loss: 0.693165, acc.: 49.02%] [G loss: 0.704273]
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4860 [D loss: 0.698523, acc.: 46.29%] [G loss: 0.716203]
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4861 [D loss: 0.701751, acc.: 49.22%] [G loss: 0.731491]
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4862 [D loss: 0.694522, acc.: 49.02%] [G loss: 0.721907]
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4863 [D loss: 0.690216, acc.: 50.98%] [G loss: 0.741724]
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4864 [D loss: 0.690517, acc.: 52.54%] [G loss: 0.727760]
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4865 [D loss: 0.693573, acc.: 51.95%] [G loss: 0.732818]
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4866 [D loss: 0.689069, acc.: 55.66%] [G loss: 0.730561]
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4867 [D loss: 0.691572, acc.: 52.54%] [G loss: 0.725434]
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4868 [D loss: 0.687583, acc.: 52.73%] [G loss: 0.719289]
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4869 [D loss: 0.692821, acc.: 52.34%] [G loss: 0.707057]
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4870 [D loss: 0.694833, acc.: 48.63%] [G loss: 0.697924]
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4871 [D loss: 0.693167, acc.: 51.76%] [G loss: 0.694456]
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4872 [D loss: 0.703834, acc.: 44.34%] [G loss: 0.705704]
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4873 [D loss: 0.692230, acc.: 50.98%] [G loss: 0.698153]
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4874 [D loss: 0.697874, acc.: 46.48%] [G loss: 0.718765]
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4875 [D loss: 0.696927, acc.: 49.80%] [G loss: 0.725270]
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4876 [D loss: 0.686334, acc.: 53.71%] [G loss: 0.721342]
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4877 [D loss: 0.690283, acc.: 54.30%] [G loss: 0.721881]
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4878 [D loss: 0.686642, acc.: 58.20%] [G loss: 0.720288]
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4879 [D loss: 0.690238, acc.: 55.27%] [G loss: 0.715411]
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4880 [D loss: 0.694814, acc.: 52.73%] [G loss: 0.715383]
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4881 [D loss: 0.692499, acc.: 50.59%] [G loss: 0.704609]
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4882 [D loss: 0.694885, acc.: 50.39%] [G loss: 0.710771]
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4883 [D loss: 0.690233, acc.: 55.08%] [G loss: 0.713510]
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4884 [D loss: 0.692759, acc.: 50.98%] [G loss: 0.711466]
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4885 [D loss: 0.701332, acc.: 45.31%] [G loss: 0.704795]
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4886 [D loss: 0.697720, acc.: 48.83%] [G loss: 0.712333]
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4887 [D loss: 0.693951, acc.: 46.29%] [G loss: 0.725485]
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4888 [D loss: 0.692885, acc.: 55.27%] [G loss: 0.726435]
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4889 [D loss: 0.694597, acc.: 50.78%] [G loss: 0.730751]
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4890 [D loss: 0.694589, acc.: 51.37%] [G loss: 0.721391]
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4891 [D loss: 0.689661, acc.: 53.91%] [G loss: 0.730824]
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4892 [D loss: 0.689514, acc.: 53.32%] [G loss: 0.724433]
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4893 [D loss: 0.692903, acc.: 51.76%] [G loss: 0.723800]
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4894 [D loss: 0.695050, acc.: 51.76%] [G loss: 0.716245]
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4895 [D loss: 0.694971, acc.: 48.44%] [G loss: 0.714206]
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4896 [D loss: 0.690469, acc.: 51.56%] [G loss: 0.713735]
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4897 [D loss: 0.690654, acc.: 50.59%] [G loss: 0.712938]
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4898 [D loss: 0.692421, acc.: 51.17%] [G loss: 0.694018]
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4899 [D loss: 0.704576, acc.: 44.53%] [G loss: 0.688966]
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4900 [D loss: 0.699855, acc.: 47.27%] [G loss: 0.703649]
1/1 [==============================] - 0s 20ms/step
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4901 [D loss: 0.698406, acc.: 47.66%] [G loss: 0.714016]
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4902 [D loss: 0.693402, acc.: 51.56%] [G loss: 0.729589]
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4903 [D loss: 0.689841, acc.: 53.12%] [G loss: 0.738941]
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4904 [D loss: 0.693880, acc.: 51.37%] [G loss: 0.742283]
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4905 [D loss: 0.693998, acc.: 49.80%] [G loss: 0.743550]
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4906 [D loss: 0.691361, acc.: 52.15%] [G loss: 0.734851]
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4907 [D loss: 0.696172, acc.: 48.05%] [G loss: 0.732021]
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4908 [D loss: 0.687524, acc.: 53.91%] [G loss: 0.736461]
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4909 [D loss: 0.688158, acc.: 55.08%] [G loss: 0.731215]
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4910 [D loss: 0.688230, acc.: 53.12%] [G loss: 0.723338]
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4911 [D loss: 0.689933, acc.: 51.17%] [G loss: 0.708533]
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4912 [D loss: 0.701466, acc.: 49.02%] [G loss: 0.710770]
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4913 [D loss: 0.702751, acc.: 43.95%] [G loss: 0.706943]
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4914 [D loss: 0.689139, acc.: 53.32%] [G loss: 0.712243]
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4915 [D loss: 0.688260, acc.: 50.98%] [G loss: 0.713095]
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4916 [D loss: 0.696095, acc.: 50.20%] [G loss: 0.716895]
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4917 [D loss: 0.691134, acc.: 54.49%] [G loss: 0.720499]
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4918 [D loss: 0.693337, acc.: 51.95%] [G loss: 0.725347]
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4919 [D loss: 0.697294, acc.: 52.34%] [G loss: 0.732825]
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4920 [D loss: 0.692340, acc.: 52.54%] [G loss: 0.733902]
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4921 [D loss: 0.689934, acc.: 55.47%] [G loss: 0.727071]
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4922 [D loss: 0.695308, acc.: 49.80%] [G loss: 0.725907]
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4923 [D loss: 0.698700, acc.: 48.63%] [G loss: 0.712182]
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4924 [D loss: 0.698000, acc.: 46.48%] [G loss: 0.705032]
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4925 [D loss: 0.699569, acc.: 46.68%] [G loss: 0.707902]
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4926 [D loss: 0.697992, acc.: 45.90%] [G loss: 0.697093]
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4927 [D loss: 0.699351, acc.: 48.44%] [G loss: 0.705752]
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4928 [D loss: 0.701937, acc.: 45.51%] [G loss: 0.697396]
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4929 [D loss: 0.700687, acc.: 45.70%] [G loss: 0.709370]
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4930 [D loss: 0.695978, acc.: 47.66%] [G loss: 0.717757]
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4931 [D loss: 0.694064, acc.: 50.78%] [G loss: 0.725541]
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4932 [D loss: 0.689482, acc.: 54.30%] [G loss: 0.730698]
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4933 [D loss: 0.691255, acc.: 50.98%] [G loss: 0.745658]
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4934 [D loss: 0.690256, acc.: 50.78%] [G loss: 0.750564]
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4935 [D loss: 0.692822, acc.: 50.59%] [G loss: 0.747603]
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4936 [D loss: 0.691789, acc.: 51.56%] [G loss: 0.733004]
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4937 [D loss: 0.688174, acc.: 53.52%] [G loss: 0.732601]
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4938 [D loss: 0.693967, acc.: 52.93%] [G loss: 0.725981]
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4939 [D loss: 0.689517, acc.: 52.73%] [G loss: 0.729129]
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4940 [D loss: 0.689934, acc.: 52.34%] [G loss: 0.713389]
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4941 [D loss: 0.691967, acc.: 51.56%] [G loss: 0.712084]
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4942 [D loss: 0.694861, acc.: 51.56%] [G loss: 0.704657]
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4943 [D loss: 0.693876, acc.: 52.15%] [G loss: 0.699407]
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4944 [D loss: 0.701922, acc.: 47.07%] [G loss: 0.707706]
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4945 [D loss: 0.700469, acc.: 46.68%] [G loss: 0.714269]
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4946 [D loss: 0.689996, acc.: 54.49%] [G loss: 0.718707]
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4947 [D loss: 0.695203, acc.: 49.22%] [G loss: 0.729138]
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4948 [D loss: 0.691485, acc.: 51.76%] [G loss: 0.728075]
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4949 [D loss: 0.694573, acc.: 52.73%] [G loss: 0.725447]
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4950 [D loss: 0.704640, acc.: 47.46%] [G loss: 0.723130]
1/1 [==============================] - 0s 17ms/step
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4951 [D loss: 0.701155, acc.: 47.27%] [G loss: 0.721320]
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4952 [D loss: 0.691058, acc.: 51.37%] [G loss: 0.713880]
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4953 [D loss: 0.695053, acc.: 50.00%] [G loss: 0.720132]
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4954 [D loss: 0.690622, acc.: 53.91%] [G loss: 0.710022]
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4955 [D loss: 0.691295, acc.: 50.98%] [G loss: 0.708303]
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4956 [D loss: 0.688093, acc.: 53.12%] [G loss: 0.709597]
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4957 [D loss: 0.689232, acc.: 53.12%] [G loss: 0.714548]
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4958 [D loss: 0.687628, acc.: 53.32%] [G loss: 0.707900]
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4959 [D loss: 0.692145, acc.: 52.73%] [G loss: 0.711449]
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4960 [D loss: 0.690570, acc.: 51.37%] [G loss: 0.709597]
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4961 [D loss: 0.690301, acc.: 54.10%] [G loss: 0.718956]
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4962 [D loss: 0.701870, acc.: 47.46%] [G loss: 0.718254]
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4963 [D loss: 0.695506, acc.: 45.90%] [G loss: 0.716875]
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4964 [D loss: 0.693696, acc.: 48.63%] [G loss: 0.723546]
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4965 [D loss: 0.693364, acc.: 51.17%] [G loss: 0.718769]
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4966 [D loss: 0.691817, acc.: 47.66%] [G loss: 0.708585]
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4967 [D loss: 0.695134, acc.: 49.22%] [G loss: 0.711846]
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4968 [D loss: 0.697484, acc.: 45.51%] [G loss: 0.716505]
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4969 [D loss: 0.695283, acc.: 50.59%] [G loss: 0.711584]
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4970 [D loss: 0.696104, acc.: 49.61%] [G loss: 0.719721]
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4971 [D loss: 0.692998, acc.: 54.49%] [G loss: 0.717833]
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4972 [D loss: 0.693304, acc.: 50.98%] [G loss: 0.726058]
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4973 [D loss: 0.688880, acc.: 50.78%] [G loss: 0.732821]
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4974 [D loss: 0.690683, acc.: 49.80%] [G loss: 0.727503]
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4975 [D loss: 0.692428, acc.: 51.37%] [G loss: 0.722934]
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4976 [D loss: 0.697672, acc.: 47.66%] [G loss: 0.722653]
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4977 [D loss: 0.696148, acc.: 52.34%] [G loss: 0.719633]
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4978 [D loss: 0.701490, acc.: 47.27%] [G loss: 0.717926]
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4979 [D loss: 0.697997, acc.: 44.14%] [G loss: 0.708187]
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4980 [D loss: 0.700910, acc.: 45.70%] [G loss: 0.709325]
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4981 [D loss: 0.693030, acc.: 50.39%] [G loss: 0.708050]
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4982 [D loss: 0.695896, acc.: 51.37%] [G loss: 0.712356]
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4983 [D loss: 0.696405, acc.: 50.59%] [G loss: 0.710380]
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4984 [D loss: 0.690322, acc.: 54.30%] [G loss: 0.709957]
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4985 [D loss: 0.700346, acc.: 46.48%] [G loss: 0.709342]
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4986 [D loss: 0.690615, acc.: 54.30%] [G loss: 0.702819]
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4987 [D loss: 0.695815, acc.: 50.78%] [G loss: 0.696639]
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4988 [D loss: 0.689350, acc.: 53.52%] [G loss: 0.713414]
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4989 [D loss: 0.693157, acc.: 52.34%] [G loss: 0.717921]
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4990 [D loss: 0.697945, acc.: 47.66%] [G loss: 0.710896]
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4991 [D loss: 0.697398, acc.: 50.39%] [G loss: 0.711068]
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4992 [D loss: 0.693365, acc.: 48.24%] [G loss: 0.717566]
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4993 [D loss: 0.694127, acc.: 50.00%] [G loss: 0.719283]
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4994 [D loss: 0.690305, acc.: 50.78%] [G loss: 0.722792]
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4995 [D loss: 0.699946, acc.: 44.34%] [G loss: 0.716552]
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4996 [D loss: 0.691875, acc.: 53.71%] [G loss: 0.719958]
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4997 [D loss: 0.693843, acc.: 51.17%] [G loss: 0.715735]
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4998 [D loss: 0.696719, acc.: 49.02%] [G loss: 0.718427]
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4999 [D loss: 0.694740, acc.: 51.56%] [G loss: 0.718721]
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5000 [D loss: 0.692202, acc.: 52.34%] [G loss: 0.711406]
1/1 [==============================] - 0s 19ms/step
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5001 [D loss: 0.691201, acc.: 49.02%] [G loss: 0.725297]
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5002 [D loss: 0.691112, acc.: 49.61%] [G loss: 0.725011]
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5003 [D loss: 0.687284, acc.: 55.86%] [G loss: 0.717226]
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5004 [D loss: 0.694886, acc.: 50.20%] [G loss: 0.718223]
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5005 [D loss: 0.695792, acc.: 45.31%] [G loss: 0.728522]
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5006 [D loss: 0.694897, acc.: 50.78%] [G loss: 0.721671]
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5007 [D loss: 0.694842, acc.: 50.59%] [G loss: 0.715241]
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5008 [D loss: 0.689426, acc.: 50.59%] [G loss: 0.724719]
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5009 [D loss: 0.692442, acc.: 52.54%] [G loss: 0.720271]
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5010 [D loss: 0.697271, acc.: 50.59%] [G loss: 0.718886]
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5011 [D loss: 0.693378, acc.: 49.02%] [G loss: 0.715032]
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5012 [D loss: 0.697139, acc.: 47.66%] [G loss: 0.708722]
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5013 [D loss: 0.693015, acc.: 51.37%] [G loss: 0.709957]
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5014 [D loss: 0.693894, acc.: 50.39%] [G loss: 0.710614]
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5015 [D loss: 0.696457, acc.: 48.63%] [G loss: 0.711600]
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5016 [D loss: 0.696545, acc.: 46.09%] [G loss: 0.709928]
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5017 [D loss: 0.698034, acc.: 46.48%] [G loss: 0.707953]
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5018 [D loss: 0.697241, acc.: 48.63%] [G loss: 0.715282]
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5019 [D loss: 0.696514, acc.: 47.85%] [G loss: 0.715718]
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5020 [D loss: 0.689793, acc.: 53.12%] [G loss: 0.718839]
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5021 [D loss: 0.690140, acc.: 51.76%] [G loss: 0.727113]
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5022 [D loss: 0.696749, acc.: 52.15%] [G loss: 0.724036]
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5023 [D loss: 0.688790, acc.: 52.73%] [G loss: 0.731567]
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5024 [D loss: 0.684583, acc.: 57.23%] [G loss: 0.727718]
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5025 [D loss: 0.689709, acc.: 49.41%] [G loss: 0.717510]
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5026 [D loss: 0.692473, acc.: 50.39%] [G loss: 0.712580]
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5027 [D loss: 0.692308, acc.: 50.39%] [G loss: 0.718069]
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5028 [D loss: 0.695372, acc.: 51.17%] [G loss: 0.712823]
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5029 [D loss: 0.693082, acc.: 50.98%] [G loss: 0.714945]
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5030 [D loss: 0.696912, acc.: 46.09%] [G loss: 0.715553]
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5031 [D loss: 0.698267, acc.: 49.41%] [G loss: 0.709553]
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5032 [D loss: 0.697773, acc.: 50.00%] [G loss: 0.720140]
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5033 [D loss: 0.700876, acc.: 49.61%] [G loss: 0.722025]
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5034 [D loss: 0.697052, acc.: 48.44%] [G loss: 0.735637]
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5035 [D loss: 0.696896, acc.: 49.02%] [G loss: 0.733643]
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5036 [D loss: 0.692989, acc.: 53.32%] [G loss: 0.736583]
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5037 [D loss: 0.690945, acc.: 56.84%] [G loss: 0.727672]
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5038 [D loss: 0.694578, acc.: 50.20%] [G loss: 0.732646]
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5039 [D loss: 0.689938, acc.: 54.69%] [G loss: 0.730036]
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5040 [D loss: 0.686977, acc.: 58.20%] [G loss: 0.720854]
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5041 [D loss: 0.684635, acc.: 59.57%] [G loss: 0.721163]
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5042 [D loss: 0.689003, acc.: 54.10%] [G loss: 0.722441]
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5043 [D loss: 0.690641, acc.: 52.54%] [G loss: 0.710077]
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5044 [D loss: 0.696863, acc.: 48.83%] [G loss: 0.706250]
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5045 [D loss: 0.696888, acc.: 50.00%] [G loss: 0.703407]
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5046 [D loss: 0.694805, acc.: 48.24%] [G loss: 0.705681]
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5047 [D loss: 0.696825, acc.: 47.46%] [G loss: 0.710183]
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5048 [D loss: 0.704405, acc.: 41.41%] [G loss: 0.723132]
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5049 [D loss: 0.693631, acc.: 50.20%] [G loss: 0.728589]
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5050 [D loss: 0.688573, acc.: 52.15%] [G loss: 0.730108]
1/1 [==============================] - 0s 18ms/step
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5051 [D loss: 0.690506, acc.: 51.37%] [G loss: 0.743372]
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5052 [D loss: 0.686697, acc.: 55.08%] [G loss: 0.733700]
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5053 [D loss: 0.692166, acc.: 50.59%] [G loss: 0.734339]
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5054 [D loss: 0.685598, acc.: 54.69%] [G loss: 0.733314]
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5055 [D loss: 0.691350, acc.: 52.73%] [G loss: 0.726135]
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5056 [D loss: 0.687005, acc.: 53.12%] [G loss: 0.726242]
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5057 [D loss: 0.683619, acc.: 55.86%] [G loss: 0.719242]
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5058 [D loss: 0.687136, acc.: 54.49%] [G loss: 0.711770]
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5059 [D loss: 0.693233, acc.: 50.00%] [G loss: 0.702194]
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5060 [D loss: 0.699254, acc.: 50.78%] [G loss: 0.708851]
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5061 [D loss: 0.699411, acc.: 49.80%] [G loss: 0.697280]
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5062 [D loss: 0.699373, acc.: 51.37%] [G loss: 0.694870]
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5063 [D loss: 0.700141, acc.: 50.00%] [G loss: 0.704069]
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5064 [D loss: 0.705068, acc.: 46.88%] [G loss: 0.715849]
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5065 [D loss: 0.700491, acc.: 44.53%] [G loss: 0.735997]
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5066 [D loss: 0.693916, acc.: 49.22%] [G loss: 0.746793]
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5067 [D loss: 0.695132, acc.: 48.05%] [G loss: 0.742704]
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5068 [D loss: 0.693803, acc.: 49.80%] [G loss: 0.744762]
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5069 [D loss: 0.689963, acc.: 52.73%] [G loss: 0.732751]
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5070 [D loss: 0.689118, acc.: 49.41%] [G loss: 0.738298]
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5071 [D loss: 0.692751, acc.: 53.12%] [G loss: 0.728728]
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5072 [D loss: 0.692929, acc.: 51.56%] [G loss: 0.733804]
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5073 [D loss: 0.682784, acc.: 59.96%] [G loss: 0.726951]
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5074 [D loss: 0.684327, acc.: 55.27%] [G loss: 0.724551]
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5075 [D loss: 0.689393, acc.: 53.32%] [G loss: 0.707474]
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5076 [D loss: 0.695968, acc.: 48.44%] [G loss: 0.696583]
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5077 [D loss: 0.701340, acc.: 47.07%] [G loss: 0.694974]
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5078 [D loss: 0.701016, acc.: 45.90%] [G loss: 0.704708]
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5079 [D loss: 0.693894, acc.: 50.00%] [G loss: 0.725719]
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5080 [D loss: 0.699211, acc.: 48.83%] [G loss: 0.745210]
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5081 [D loss: 0.693323, acc.: 51.17%] [G loss: 0.733291]
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5082 [D loss: 0.700659, acc.: 49.22%] [G loss: 0.742643]
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5083 [D loss: 0.706589, acc.: 41.21%] [G loss: 0.728881]
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5084 [D loss: 0.700751, acc.: 46.48%] [G loss: 0.729161]
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5085 [D loss: 0.695125, acc.: 50.98%] [G loss: 0.723689]
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5086 [D loss: 0.693870, acc.: 50.39%] [G loss: 0.718713]
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5087 [D loss: 0.693533, acc.: 49.41%] [G loss: 0.708626]
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5088 [D loss: 0.697126, acc.: 49.61%] [G loss: 0.707375]
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5089 [D loss: 0.693204, acc.: 50.00%] [G loss: 0.699910]
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5090 [D loss: 0.696577, acc.: 46.09%] [G loss: 0.697958]
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5091 [D loss: 0.693083, acc.: 51.76%] [G loss: 0.703366]
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5092 [D loss: 0.690982, acc.: 52.54%] [G loss: 0.711930]
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5093 [D loss: 0.695148, acc.: 48.63%] [G loss: 0.715713]
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5094 [D loss: 0.692883, acc.: 50.78%] [G loss: 0.723679]
8/8 [==============================] - 0s 5ms/step
5095 [D loss: 0.691701, acc.: 53.12%] [G loss: 0.734259]
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5096 [D loss: 0.692553, acc.: 53.71%] [G loss: 0.729443]
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5097 [D loss: 0.692940, acc.: 52.34%] [G loss: 0.723760]
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5098 [D loss: 0.691501, acc.: 49.80%] [G loss: 0.725619]
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5099 [D loss: 0.690082, acc.: 51.95%] [G loss: 0.714936]
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5100 [D loss: 0.693621, acc.: 50.78%] [G loss: 0.712653]
1/1 [==============================] - 0s 17ms/step
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5101 [D loss: 0.691177, acc.: 50.00%] [G loss: 0.712375]
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5102 [D loss: 0.690990, acc.: 54.10%] [G loss: 0.702940]
8/8 [==============================] - 0s 5ms/step
5103 [D loss: 0.694235, acc.: 50.20%] [G loss: 0.698945]
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5104 [D loss: 0.697579, acc.: 47.46%] [G loss: 0.700187]
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5105 [D loss: 0.693249, acc.: 51.17%] [G loss: 0.715126]
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5106 [D loss: 0.699378, acc.: 49.61%] [G loss: 0.718878]
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5107 [D loss: 0.693277, acc.: 50.59%] [G loss: 0.724520]
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5108 [D loss: 0.689588, acc.: 50.59%] [G loss: 0.727968]
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5109 [D loss: 0.695782, acc.: 48.44%] [G loss: 0.737523]
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5110 [D loss: 0.693726, acc.: 50.98%] [G loss: 0.734740]
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5111 [D loss: 0.690047, acc.: 55.47%] [G loss: 0.727363]
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5112 [D loss: 0.694400, acc.: 50.98%] [G loss: 0.727811]
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5113 [D loss: 0.693487, acc.: 50.39%] [G loss: 0.720179]
8/8 [==============================] - 0s 5ms/step
5114 [D loss: 0.689122, acc.: 52.93%] [G loss: 0.724416]
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5115 [D loss: 0.695316, acc.: 48.05%] [G loss: 0.714289]
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5116 [D loss: 0.691117, acc.: 51.95%] [G loss: 0.707558]
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5117 [D loss: 0.697411, acc.: 47.27%] [G loss: 0.702146]
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5118 [D loss: 0.695054, acc.: 49.41%] [G loss: 0.700532]
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5119 [D loss: 0.695861, acc.: 51.95%] [G loss: 0.716549]
8/8 [==============================] - 0s 5ms/step
5120 [D loss: 0.695803, acc.: 49.22%] [G loss: 0.715552]
8/8 [==============================] - 0s 5ms/step
5121 [D loss: 0.696532, acc.: 50.39%] [G loss: 0.724711]
8/8 [==============================] - 0s 5ms/step
5122 [D loss: 0.691971, acc.: 51.17%] [G loss: 0.728951]
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5123 [D loss: 0.691662, acc.: 52.73%] [G loss: 0.731825]
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5124 [D loss: 0.689025, acc.: 55.08%] [G loss: 0.728317]
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5125 [D loss: 0.689294, acc.: 55.08%] [G loss: 0.734557]
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5126 [D loss: 0.691873, acc.: 52.34%] [G loss: 0.719066]
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5127 [D loss: 0.697509, acc.: 46.88%] [G loss: 0.719705]
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5128 [D loss: 0.691465, acc.: 53.32%] [G loss: 0.719567]
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5129 [D loss: 0.692962, acc.: 52.73%] [G loss: 0.716631]
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5130 [D loss: 0.697638, acc.: 47.66%] [G loss: 0.710615]
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5131 [D loss: 0.691499, acc.: 55.08%] [G loss: 0.712707]
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5132 [D loss: 0.688056, acc.: 55.47%] [G loss: 0.705950]
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5133 [D loss: 0.694617, acc.: 49.02%] [G loss: 0.701981]
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5134 [D loss: 0.697089, acc.: 47.85%] [G loss: 0.703791]
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5135 [D loss: 0.694304, acc.: 50.39%] [G loss: 0.705907]
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5136 [D loss: 0.697482, acc.: 47.27%] [G loss: 0.712986]
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5137 [D loss: 0.687809, acc.: 52.34%] [G loss: 0.717493]
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5138 [D loss: 0.689958, acc.: 50.39%] [G loss: 0.727106]
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5139 [D loss: 0.693205, acc.: 50.59%] [G loss: 0.724217]
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5140 [D loss: 0.694756, acc.: 49.80%] [G loss: 0.718174]
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5141 [D loss: 0.692269, acc.: 51.17%] [G loss: 0.725067]
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5142 [D loss: 0.686624, acc.: 54.88%] [G loss: 0.721882]
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5143 [D loss: 0.697253, acc.: 51.17%] [G loss: 0.716146]
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5144 [D loss: 0.692082, acc.: 53.32%] [G loss: 0.715033]
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5145 [D loss: 0.686954, acc.: 55.47%] [G loss: 0.724890]
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5146 [D loss: 0.689414, acc.: 54.10%] [G loss: 0.716252]
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5147 [D loss: 0.685668, acc.: 55.27%] [G loss: 0.715878]
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5148 [D loss: 0.688013, acc.: 53.12%] [G loss: 0.714548]
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5149 [D loss: 0.697579, acc.: 49.41%] [G loss: 0.712692]
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5150 [D loss: 0.693795, acc.: 50.59%] [G loss: 0.704057]
1/1 [==============================] - 0s 20ms/step
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5151 [D loss: 0.685219, acc.: 55.47%] [G loss: 0.707988]
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5152 [D loss: 0.693744, acc.: 49.61%] [G loss: 0.716044]
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5153 [D loss: 0.693462, acc.: 49.02%] [G loss: 0.714592]
8/8 [==============================] - 0s 7ms/step
5154 [D loss: 0.688320, acc.: 54.49%] [G loss: 0.714682]
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5155 [D loss: 0.693587, acc.: 52.54%] [G loss: 0.717896]
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5156 [D loss: 0.687477, acc.: 51.17%] [G loss: 0.710079]
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5157 [D loss: 0.692734, acc.: 51.37%] [G loss: 0.715434]
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5158 [D loss: 0.693881, acc.: 51.17%] [G loss: 0.716900]
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5159 [D loss: 0.692929, acc.: 53.71%] [G loss: 0.714754]
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5160 [D loss: 0.699485, acc.: 49.61%] [G loss: 0.715986]
8/8 [==============================] - 0s 5ms/step
5161 [D loss: 0.693487, acc.: 49.61%] [G loss: 0.708375]
8/8 [==============================] - 0s 5ms/step
5162 [D loss: 0.692705, acc.: 53.12%] [G loss: 0.721401]
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5163 [D loss: 0.690415, acc.: 53.32%] [G loss: 0.716329]
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5164 [D loss: 0.696802, acc.: 49.41%] [G loss: 0.718387]
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5165 [D loss: 0.695307, acc.: 48.05%] [G loss: 0.712426]
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5166 [D loss: 0.692862, acc.: 53.52%] [G loss: 0.731534]
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5167 [D loss: 0.690870, acc.: 52.34%] [G loss: 0.728142]
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5168 [D loss: 0.690843, acc.: 51.56%] [G loss: 0.731672]
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5169 [D loss: 0.695452, acc.: 48.05%] [G loss: 0.733631]
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5170 [D loss: 0.687604, acc.: 52.34%] [G loss: 0.740584]
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5171 [D loss: 0.693098, acc.: 51.56%] [G loss: 0.730118]
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5172 [D loss: 0.689995, acc.: 51.37%] [G loss: 0.733034]
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5173 [D loss: 0.693433, acc.: 50.59%] [G loss: 0.721852]
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5174 [D loss: 0.683657, acc.: 57.42%] [G loss: 0.723874]
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5175 [D loss: 0.689709, acc.: 51.76%] [G loss: 0.712630]
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5176 [D loss: 0.693564, acc.: 50.98%] [G loss: 0.707517]
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5177 [D loss: 0.695721, acc.: 49.61%] [G loss: 0.704600]
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5178 [D loss: 0.695170, acc.: 51.95%] [G loss: 0.707177]
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5179 [D loss: 0.695295, acc.: 51.37%] [G loss: 0.702552]
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5180 [D loss: 0.697302, acc.: 47.46%] [G loss: 0.702117]
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5181 [D loss: 0.690083, acc.: 52.73%] [G loss: 0.716500]
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5182 [D loss: 0.688926, acc.: 51.76%] [G loss: 0.726439]
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5183 [D loss: 0.692935, acc.: 51.37%] [G loss: 0.724419]
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5184 [D loss: 0.693771, acc.: 49.80%] [G loss: 0.725951]
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5185 [D loss: 0.691768, acc.: 50.98%] [G loss: 0.715566]
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5186 [D loss: 0.696509, acc.: 47.85%] [G loss: 0.720548]
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5187 [D loss: 0.693924, acc.: 52.54%] [G loss: 0.714511]
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5188 [D loss: 0.687671, acc.: 53.71%] [G loss: 0.716770]
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5189 [D loss: 0.687661, acc.: 49.80%] [G loss: 0.712436]
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5190 [D loss: 0.693368, acc.: 49.61%] [G loss: 0.706569]
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5191 [D loss: 0.694958, acc.: 47.46%] [G loss: 0.712528]
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5192 [D loss: 0.694245, acc.: 51.56%] [G loss: 0.717800]
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5193 [D loss: 0.694635, acc.: 46.68%] [G loss: 0.723055]
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5194 [D loss: 0.692027, acc.: 50.59%] [G loss: 0.732533]
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5195 [D loss: 0.687011, acc.: 54.69%] [G loss: 0.733048]
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5196 [D loss: 0.689081, acc.: 52.93%] [G loss: 0.744785]
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5197 [D loss: 0.691512, acc.: 50.20%] [G loss: 0.746470]
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5198 [D loss: 0.693985, acc.: 49.80%] [G loss: 0.734486]
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5199 [D loss: 0.688166, acc.: 52.54%] [G loss: 0.728483]
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5200 [D loss: 0.691227, acc.: 52.54%] [G loss: 0.723588]
1/1 [==============================] - 0s 23ms/step
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5201 [D loss: 0.691637, acc.: 54.30%] [G loss: 0.723104]
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5202 [D loss: 0.691669, acc.: 52.34%] [G loss: 0.705513]
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5203 [D loss: 0.696747, acc.: 49.22%] [G loss: 0.703968]
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5204 [D loss: 0.694333, acc.: 50.78%] [G loss: 0.705068]
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5205 [D loss: 0.697789, acc.: 50.20%] [G loss: 0.708702]
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5206 [D loss: 0.697448, acc.: 51.37%] [G loss: 0.721595]
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5207 [D loss: 0.696242, acc.: 46.88%] [G loss: 0.725740]
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5208 [D loss: 0.691571, acc.: 50.59%] [G loss: 0.728437]
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5209 [D loss: 0.695625, acc.: 49.22%] [G loss: 0.746745]
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5210 [D loss: 0.687048, acc.: 53.32%] [G loss: 0.739632]
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5211 [D loss: 0.693766, acc.: 49.02%] [G loss: 0.739343]
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5212 [D loss: 0.692597, acc.: 50.00%] [G loss: 0.736868]
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5213 [D loss: 0.698025, acc.: 49.02%] [G loss: 0.730167]
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5214 [D loss: 0.693145, acc.: 49.22%] [G loss: 0.717648]
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5215 [D loss: 0.693829, acc.: 50.39%] [G loss: 0.711672]
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5216 [D loss: 0.694781, acc.: 49.02%] [G loss: 0.710471]
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5217 [D loss: 0.694194, acc.: 50.59%] [G loss: 0.705765]
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5218 [D loss: 0.694028, acc.: 49.22%] [G loss: 0.710334]
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5219 [D loss: 0.693820, acc.: 52.93%] [G loss: 0.703188]
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5220 [D loss: 0.696654, acc.: 48.83%] [G loss: 0.700610]
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5221 [D loss: 0.694385, acc.: 49.61%] [G loss: 0.712139]
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5222 [D loss: 0.693094, acc.: 50.20%] [G loss: 0.712613]
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5223 [D loss: 0.697393, acc.: 50.78%] [G loss: 0.720067]
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5224 [D loss: 0.698335, acc.: 46.29%] [G loss: 0.723343]
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5225 [D loss: 0.695975, acc.: 46.88%] [G loss: 0.725900]
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5226 [D loss: 0.698720, acc.: 45.70%] [G loss: 0.722740]
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5227 [D loss: 0.694014, acc.: 48.24%] [G loss: 0.725078]
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5228 [D loss: 0.690178, acc.: 52.93%] [G loss: 0.724821]
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5229 [D loss: 0.687598, acc.: 55.66%] [G loss: 0.723382]
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5230 [D loss: 0.684916, acc.: 57.81%] [G loss: 0.716173]
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5231 [D loss: 0.693012, acc.: 52.93%] [G loss: 0.719907]
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5232 [D loss: 0.690329, acc.: 53.32%] [G loss: 0.717719]
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5233 [D loss: 0.686403, acc.: 55.47%] [G loss: 0.717312]
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5234 [D loss: 0.692335, acc.: 50.59%] [G loss: 0.708562]
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5235 [D loss: 0.698158, acc.: 49.80%] [G loss: 0.710270]
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5236 [D loss: 0.693725, acc.: 50.00%] [G loss: 0.713635]
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5237 [D loss: 0.697013, acc.: 49.02%] [G loss: 0.717561]
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5238 [D loss: 0.692848, acc.: 52.34%] [G loss: 0.712188]
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5239 [D loss: 0.688445, acc.: 55.86%] [G loss: 0.728371]
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5240 [D loss: 0.690913, acc.: 50.39%] [G loss: 0.729973]
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5241 [D loss: 0.695349, acc.: 50.20%] [G loss: 0.730577]
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5242 [D loss: 0.690775, acc.: 50.98%] [G loss: 0.728028]
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5243 [D loss: 0.698282, acc.: 47.27%] [G loss: 0.725126]
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5244 [D loss: 0.682342, acc.: 52.73%] [G loss: 0.730163]
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5245 [D loss: 0.684549, acc.: 54.30%] [G loss: 0.732531]
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5246 [D loss: 0.688333, acc.: 54.49%] [G loss: 0.723082]
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5247 [D loss: 0.682961, acc.: 55.86%] [G loss: 0.725149]
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5248 [D loss: 0.689203, acc.: 54.49%] [G loss: 0.713312]
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5249 [D loss: 0.683233, acc.: 56.64%] [G loss: 0.712897]
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5250 [D loss: 0.692769, acc.: 51.17%] [G loss: 0.715145]
1/1 [==============================] - 0s 17ms/step
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5251 [D loss: 0.691326, acc.: 51.17%] [G loss: 0.726272]
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5252 [D loss: 0.687797, acc.: 54.10%] [G loss: 0.717444]
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5253 [D loss: 0.695316, acc.: 51.76%] [G loss: 0.710061]
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5254 [D loss: 0.696639, acc.: 46.09%] [G loss: 0.724395]
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5255 [D loss: 0.691921, acc.: 52.34%] [G loss: 0.728066]
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5256 [D loss: 0.691348, acc.: 50.98%] [G loss: 0.723857]
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5257 [D loss: 0.701176, acc.: 44.92%] [G loss: 0.725678]
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5258 [D loss: 0.693107, acc.: 48.24%] [G loss: 0.724948]
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5259 [D loss: 0.696500, acc.: 47.85%] [G loss: 0.725903]
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5260 [D loss: 0.690960, acc.: 50.78%] [G loss: 0.722273]
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5261 [D loss: 0.691697, acc.: 50.78%] [G loss: 0.724586]
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5262 [D loss: 0.690206, acc.: 49.41%] [G loss: 0.713836]
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5263 [D loss: 0.695719, acc.: 47.66%] [G loss: 0.712533]
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5264 [D loss: 0.688982, acc.: 50.59%] [G loss: 0.719810]
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5265 [D loss: 0.686726, acc.: 51.76%] [G loss: 0.724430]
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5266 [D loss: 0.688807, acc.: 51.76%] [G loss: 0.722606]
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5267 [D loss: 0.687549, acc.: 50.78%] [G loss: 0.726130]
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5268 [D loss: 0.683054, acc.: 54.69%] [G loss: 0.731212]
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5269 [D loss: 0.682307, acc.: 56.05%] [G loss: 0.729038]
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5270 [D loss: 0.686999, acc.: 50.98%] [G loss: 0.737415]
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5271 [D loss: 0.692091, acc.: 51.37%] [G loss: 0.721044]
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5272 [D loss: 0.692558, acc.: 51.76%] [G loss: 0.733209]
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5273 [D loss: 0.697018, acc.: 46.29%] [G loss: 0.719607]
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5274 [D loss: 0.695941, acc.: 47.66%] [G loss: 0.705573]
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5275 [D loss: 0.698159, acc.: 50.20%] [G loss: 0.711085]
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5276 [D loss: 0.701245, acc.: 49.41%] [G loss: 0.698451]
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5277 [D loss: 0.701431, acc.: 48.24%] [G loss: 0.700072]
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5278 [D loss: 0.702313, acc.: 45.51%] [G loss: 0.700588]
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5279 [D loss: 0.696527, acc.: 51.17%] [G loss: 0.705591]
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5280 [D loss: 0.693080, acc.: 50.20%] [G loss: 0.709408]
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5281 [D loss: 0.692621, acc.: 50.00%] [G loss: 0.718650]
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5282 [D loss: 0.693343, acc.: 50.00%] [G loss: 0.730104]
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5283 [D loss: 0.694247, acc.: 50.59%] [G loss: 0.730479]
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5284 [D loss: 0.687161, acc.: 53.91%] [G loss: 0.729592]
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5285 [D loss: 0.686772, acc.: 55.27%] [G loss: 0.737415]
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5286 [D loss: 0.693463, acc.: 54.49%] [G loss: 0.733872]
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5287 [D loss: 0.693622, acc.: 52.34%] [G loss: 0.719209]
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5288 [D loss: 0.694307, acc.: 50.00%] [G loss: 0.724657]
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5289 [D loss: 0.690553, acc.: 49.41%] [G loss: 0.715977]
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5290 [D loss: 0.684965, acc.: 55.86%] [G loss: 0.708187]
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5291 [D loss: 0.698787, acc.: 45.70%] [G loss: 0.698766]
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5292 [D loss: 0.695511, acc.: 49.02%] [G loss: 0.692482]
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5293 [D loss: 0.699578, acc.: 46.88%] [G loss: 0.710762]
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5294 [D loss: 0.696784, acc.: 48.24%] [G loss: 0.714684]
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5295 [D loss: 0.701678, acc.: 46.09%] [G loss: 0.729352]
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5296 [D loss: 0.691598, acc.: 48.83%] [G loss: 0.726690]
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5297 [D loss: 0.693000, acc.: 53.32%] [G loss: 0.736168]
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5298 [D loss: 0.689846, acc.: 48.44%] [G loss: 0.731951]
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5299 [D loss: 0.684090, acc.: 57.03%] [G loss: 0.731386]
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5300 [D loss: 0.694963, acc.: 51.17%] [G loss: 0.725741]
1/1 [==============================] - 0s 19ms/step
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5301 [D loss: 0.690203, acc.: 53.32%] [G loss: 0.726568]
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5302 [D loss: 0.697245, acc.: 51.56%] [G loss: 0.721784]
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5303 [D loss: 0.694019, acc.: 51.37%] [G loss: 0.725822]
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5304 [D loss: 0.690587, acc.: 52.34%] [G loss: 0.712012]
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5305 [D loss: 0.690088, acc.: 52.54%] [G loss: 0.715262]
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5306 [D loss: 0.700389, acc.: 45.90%] [G loss: 0.702579]
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5307 [D loss: 0.689915, acc.: 52.54%] [G loss: 0.703826]
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5308 [D loss: 0.693644, acc.: 48.63%] [G loss: 0.704735]
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5309 [D loss: 0.697457, acc.: 49.41%] [G loss: 0.705399]
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5310 [D loss: 0.696193, acc.: 49.22%] [G loss: 0.711877]
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5311 [D loss: 0.693806, acc.: 53.12%] [G loss: 0.723985]
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5312 [D loss: 0.691149, acc.: 52.34%] [G loss: 0.731863]
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5313 [D loss: 0.694662, acc.: 53.12%] [G loss: 0.744889]
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5314 [D loss: 0.689340, acc.: 55.47%] [G loss: 0.747143]
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5315 [D loss: 0.689199, acc.: 51.76%] [G loss: 0.748186]
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5316 [D loss: 0.695260, acc.: 47.07%] [G loss: 0.737111]
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5317 [D loss: 0.694638, acc.: 49.22%] [G loss: 0.728235]
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5318 [D loss: 0.691139, acc.: 52.34%] [G loss: 0.722584]
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5319 [D loss: 0.700710, acc.: 49.02%] [G loss: 0.712186]
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5320 [D loss: 0.694270, acc.: 52.93%] [G loss: 0.701511]
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5321 [D loss: 0.697856, acc.: 48.05%] [G loss: 0.687305]
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5322 [D loss: 0.703540, acc.: 44.92%] [G loss: 0.687733]
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5323 [D loss: 0.698840, acc.: 49.61%] [G loss: 0.695256]
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5324 [D loss: 0.700900, acc.: 44.53%] [G loss: 0.719895]
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5325 [D loss: 0.692112, acc.: 50.00%] [G loss: 0.738196]
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5326 [D loss: 0.693623, acc.: 48.83%] [G loss: 0.745970]
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5327 [D loss: 0.687871, acc.: 52.15%] [G loss: 0.745833]
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5328 [D loss: 0.691565, acc.: 51.76%] [G loss: 0.740043]
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5329 [D loss: 0.696331, acc.: 48.63%] [G loss: 0.727162]
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5330 [D loss: 0.697563, acc.: 47.66%] [G loss: 0.721080]
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5331 [D loss: 0.687851, acc.: 55.47%] [G loss: 0.719068]
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5332 [D loss: 0.698931, acc.: 45.31%] [G loss: 0.705273]
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5333 [D loss: 0.688932, acc.: 52.73%] [G loss: 0.700200]
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5334 [D loss: 0.699489, acc.: 44.92%] [G loss: 0.700064]
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5335 [D loss: 0.697572, acc.: 47.07%] [G loss: 0.702095]
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5336 [D loss: 0.703074, acc.: 45.12%] [G loss: 0.699307]
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5337 [D loss: 0.703000, acc.: 44.34%] [G loss: 0.711261]
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5338 [D loss: 0.694851, acc.: 46.48%] [G loss: 0.723751]
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5339 [D loss: 0.691979, acc.: 50.39%] [G loss: 0.746224]
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5340 [D loss: 0.688737, acc.: 54.10%] [G loss: 0.743826]
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5341 [D loss: 0.688120, acc.: 51.17%] [G loss: 0.735973]
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5342 [D loss: 0.688053, acc.: 50.59%] [G loss: 0.739207]
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5343 [D loss: 0.691730, acc.: 47.07%] [G loss: 0.730442]
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5344 [D loss: 0.692725, acc.: 51.76%] [G loss: 0.725786]
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5345 [D loss: 0.688499, acc.: 52.34%] [G loss: 0.717488]
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5346 [D loss: 0.693271, acc.: 50.20%] [G loss: 0.716045]
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5347 [D loss: 0.692135, acc.: 49.22%] [G loss: 0.712933]
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5348 [D loss: 0.693775, acc.: 49.61%] [G loss: 0.710618]
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5349 [D loss: 0.692625, acc.: 50.00%] [G loss: 0.716530]
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5350 [D loss: 0.694487, acc.: 50.78%] [G loss: 0.704049]
1/1 [==============================] - 0s 19ms/step
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5351 [D loss: 0.693495, acc.: 49.80%] [G loss: 0.704588]
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5352 [D loss: 0.693635, acc.: 48.63%] [G loss: 0.708975]
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5353 [D loss: 0.700321, acc.: 46.68%] [G loss: 0.731198]
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5354 [D loss: 0.693985, acc.: 49.80%] [G loss: 0.730594]
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5355 [D loss: 0.695662, acc.: 47.27%] [G loss: 0.745135]
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5356 [D loss: 0.688726, acc.: 50.59%] [G loss: 0.750963]
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5357 [D loss: 0.690337, acc.: 53.12%] [G loss: 0.759795]
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5358 [D loss: 0.689209, acc.: 51.56%] [G loss: 0.743807]
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5359 [D loss: 0.694940, acc.: 50.39%] [G loss: 0.740264]
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5360 [D loss: 0.692248, acc.: 53.71%] [G loss: 0.736877]
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5361 [D loss: 0.690578, acc.: 48.63%] [G loss: 0.719199]
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5362 [D loss: 0.695190, acc.: 50.00%] [G loss: 0.728943]
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5363 [D loss: 0.690754, acc.: 51.37%] [G loss: 0.724567]
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5364 [D loss: 0.685808, acc.: 53.91%] [G loss: 0.717935]
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5365 [D loss: 0.701559, acc.: 46.09%] [G loss: 0.706487]
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5366 [D loss: 0.701439, acc.: 40.82%] [G loss: 0.699501]
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5367 [D loss: 0.698627, acc.: 48.05%] [G loss: 0.707099]
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5368 [D loss: 0.698661, acc.: 48.05%] [G loss: 0.726544]
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5369 [D loss: 0.689688, acc.: 51.76%] [G loss: 0.738246]
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5370 [D loss: 0.686329, acc.: 53.12%] [G loss: 0.741830]
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5371 [D loss: 0.689184, acc.: 47.85%] [G loss: 0.730523]
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5372 [D loss: 0.700366, acc.: 44.34%] [G loss: 0.721614]
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5373 [D loss: 0.702556, acc.: 47.66%] [G loss: 0.720815]
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5374 [D loss: 0.697047, acc.: 49.41%] [G loss: 0.722668]
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5375 [D loss: 0.694307, acc.: 51.37%] [G loss: 0.712986]
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5376 [D loss: 0.694813, acc.: 50.00%] [G loss: 0.711397]
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5377 [D loss: 0.695072, acc.: 49.02%] [G loss: 0.710014]
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5378 [D loss: 0.686906, acc.: 54.88%] [G loss: 0.719214]
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5379 [D loss: 0.691989, acc.: 50.39%] [G loss: 0.725282]
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5380 [D loss: 0.691660, acc.: 51.56%] [G loss: 0.723183]
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5381 [D loss: 0.690368, acc.: 53.32%] [G loss: 0.724810]
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5382 [D loss: 0.692192, acc.: 56.05%] [G loss: 0.713820]
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5383 [D loss: 0.688876, acc.: 55.08%] [G loss: 0.718551]
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5384 [D loss: 0.694673, acc.: 50.78%] [G loss: 0.721343]
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5385 [D loss: 0.691418, acc.: 54.30%] [G loss: 0.718658]
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5386 [D loss: 0.693378, acc.: 52.15%] [G loss: 0.710831]
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5387 [D loss: 0.697304, acc.: 49.80%] [G loss: 0.711541]
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5388 [D loss: 0.693027, acc.: 48.63%] [G loss: 0.699773]
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5389 [D loss: 0.699856, acc.: 47.46%] [G loss: 0.707302]
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5390 [D loss: 0.697149, acc.: 50.39%] [G loss: 0.704744]
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5391 [D loss: 0.697063, acc.: 46.48%] [G loss: 0.720140]
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5392 [D loss: 0.693049, acc.: 48.44%] [G loss: 0.727696]
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5393 [D loss: 0.688090, acc.: 54.30%] [G loss: 0.744756]
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5394 [D loss: 0.682015, acc.: 56.84%] [G loss: 0.745385]
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5395 [D loss: 0.686470, acc.: 52.93%] [G loss: 0.751803]
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5396 [D loss: 0.686793, acc.: 53.12%] [G loss: 0.748237]
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5397 [D loss: 0.697564, acc.: 46.68%] [G loss: 0.732836]
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5398 [D loss: 0.692340, acc.: 48.05%] [G loss: 0.722907]
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5399 [D loss: 0.696597, acc.: 50.20%] [G loss: 0.712375]
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5400 [D loss: 0.693482, acc.: 48.24%] [G loss: 0.702817]
1/1 [==============================] - 0s 18ms/step
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5401 [D loss: 0.699097, acc.: 47.66%] [G loss: 0.700065]
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5402 [D loss: 0.695868, acc.: 51.37%] [G loss: 0.704773]
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5403 [D loss: 0.692926, acc.: 49.22%] [G loss: 0.701206]
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5404 [D loss: 0.699326, acc.: 46.68%] [G loss: 0.709291]
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5405 [D loss: 0.690711, acc.: 50.98%] [G loss: 0.726910]
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5406 [D loss: 0.688770, acc.: 54.10%] [G loss: 0.727293]
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5407 [D loss: 0.693035, acc.: 50.59%] [G loss: 0.736663]
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5408 [D loss: 0.691882, acc.: 52.34%] [G loss: 0.740249]
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5409 [D loss: 0.695644, acc.: 47.27%] [G loss: 0.732904]
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5410 [D loss: 0.696793, acc.: 49.61%] [G loss: 0.730224]
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5411 [D loss: 0.696641, acc.: 48.63%] [G loss: 0.721166]
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5412 [D loss: 0.697921, acc.: 46.48%] [G loss: 0.719468]
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5413 [D loss: 0.697982, acc.: 48.83%] [G loss: 0.711084]
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5414 [D loss: 0.697374, acc.: 46.68%] [G loss: 0.709663]
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5415 [D loss: 0.692726, acc.: 51.56%] [G loss: 0.715360]
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5416 [D loss: 0.690869, acc.: 52.34%] [G loss: 0.706206]
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5417 [D loss: 0.692553, acc.: 52.54%] [G loss: 0.706632]
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5418 [D loss: 0.699220, acc.: 45.51%] [G loss: 0.703551]
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5419 [D loss: 0.688091, acc.: 51.56%] [G loss: 0.704935]
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5420 [D loss: 0.687895, acc.: 53.91%] [G loss: 0.720536]
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5421 [D loss: 0.691187, acc.: 54.49%] [G loss: 0.715220]
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5422 [D loss: 0.686065, acc.: 55.86%] [G loss: 0.722476]
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5423 [D loss: 0.688330, acc.: 52.73%] [G loss: 0.734826]
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5424 [D loss: 0.690140, acc.: 50.78%] [G loss: 0.727211]
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5425 [D loss: 0.685904, acc.: 53.52%] [G loss: 0.737292]
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5426 [D loss: 0.699336, acc.: 45.12%] [G loss: 0.728787]
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5427 [D loss: 0.699281, acc.: 47.46%] [G loss: 0.722552]
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5428 [D loss: 0.697892, acc.: 49.80%] [G loss: 0.711450]
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5429 [D loss: 0.690930, acc.: 52.73%] [G loss: 0.714907]
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5430 [D loss: 0.693792, acc.: 49.61%] [G loss: 0.707998]
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5431 [D loss: 0.692644, acc.: 50.00%] [G loss: 0.709552]
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5432 [D loss: 0.693581, acc.: 49.41%] [G loss: 0.704930]
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5433 [D loss: 0.693949, acc.: 50.59%] [G loss: 0.701972]
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5434 [D loss: 0.694953, acc.: 51.37%] [G loss: 0.715095]
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5435 [D loss: 0.690160, acc.: 50.78%] [G loss: 0.718272]
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5436 [D loss: 0.695212, acc.: 48.63%] [G loss: 0.716463]
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5437 [D loss: 0.689953, acc.: 51.76%] [G loss: 0.723177]
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5438 [D loss: 0.692928, acc.: 49.22%] [G loss: 0.721934]
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5439 [D loss: 0.694219, acc.: 52.15%] [G loss: 0.722956]
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5440 [D loss: 0.695385, acc.: 47.66%] [G loss: 0.718580]
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5441 [D loss: 0.696762, acc.: 49.02%] [G loss: 0.714508]
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5442 [D loss: 0.696564, acc.: 49.61%] [G loss: 0.712746]
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5443 [D loss: 0.692820, acc.: 49.80%] [G loss: 0.716777]
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5444 [D loss: 0.696800, acc.: 48.44%] [G loss: 0.715812]
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5445 [D loss: 0.694108, acc.: 49.41%] [G loss: 0.715977]
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5446 [D loss: 0.697477, acc.: 51.17%] [G loss: 0.713014]
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5447 [D loss: 0.692833, acc.: 52.15%] [G loss: 0.710124]
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5448 [D loss: 0.688764, acc.: 53.52%] [G loss: 0.714319]
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5449 [D loss: 0.691967, acc.: 53.32%] [G loss: 0.719824]
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5450 [D loss: 0.690494, acc.: 52.34%] [G loss: 0.729415]
1/1 [==============================] - 0s 24ms/step
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5451 [D loss: 0.690615, acc.: 53.71%] [G loss: 0.725168]
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5452 [D loss: 0.693027, acc.: 48.83%] [G loss: 0.725822]
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5453 [D loss: 0.693043, acc.: 50.59%] [G loss: 0.718140]
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5454 [D loss: 0.694114, acc.: 49.22%] [G loss: 0.717556]
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5455 [D loss: 0.693126, acc.: 50.00%] [G loss: 0.716090]
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5456 [D loss: 0.693405, acc.: 47.66%] [G loss: 0.714375]
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5457 [D loss: 0.691743, acc.: 51.17%] [G loss: 0.717102]
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5458 [D loss: 0.694824, acc.: 47.46%] [G loss: 0.715554]
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5459 [D loss: 0.693244, acc.: 49.80%] [G loss: 0.721828]
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5460 [D loss: 0.693953, acc.: 48.83%] [G loss: 0.720633]
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5461 [D loss: 0.692736, acc.: 49.41%] [G loss: 0.725179]
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5462 [D loss: 0.690502, acc.: 54.49%] [G loss: 0.725535]
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5463 [D loss: 0.684961, acc.: 54.49%] [G loss: 0.730453]
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5464 [D loss: 0.689115, acc.: 51.56%] [G loss: 0.726576]
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5465 [D loss: 0.681318, acc.: 54.88%] [G loss: 0.735603]
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5466 [D loss: 0.687245, acc.: 54.30%] [G loss: 0.730643]
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5467 [D loss: 0.688318, acc.: 50.00%] [G loss: 0.732564]
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5468 [D loss: 0.688194, acc.: 51.56%] [G loss: 0.727386]
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5469 [D loss: 0.688494, acc.: 51.37%] [G loss: 0.722750]
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5470 [D loss: 0.692671, acc.: 47.85%] [G loss: 0.729712]
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5471 [D loss: 0.688679, acc.: 53.32%] [G loss: 0.728043]
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5472 [D loss: 0.689064, acc.: 50.39%] [G loss: 0.729582]
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5473 [D loss: 0.690365, acc.: 50.98%] [G loss: 0.734911]
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5474 [D loss: 0.685760, acc.: 52.15%] [G loss: 0.726109]
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5475 [D loss: 0.687495, acc.: 53.52%] [G loss: 0.725288]
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5476 [D loss: 0.686596, acc.: 52.15%] [G loss: 0.719469]
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5477 [D loss: 0.693576, acc.: 50.00%] [G loss: 0.726922]
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5478 [D loss: 0.693482, acc.: 48.24%] [G loss: 0.721272]
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5479 [D loss: 0.698338, acc.: 46.88%] [G loss: 0.721417]
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5480 [D loss: 0.695068, acc.: 46.48%] [G loss: 0.717909]
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5481 [D loss: 0.692382, acc.: 49.02%] [G loss: 0.718687]
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5482 [D loss: 0.697360, acc.: 42.19%] [G loss: 0.711549]
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5483 [D loss: 0.689988, acc.: 50.20%] [G loss: 0.715504]
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5484 [D loss: 0.687290, acc.: 51.95%] [G loss: 0.714997]
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5485 [D loss: 0.690969, acc.: 52.15%] [G loss: 0.709386]
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5486 [D loss: 0.693534, acc.: 47.66%] [G loss: 0.719442]
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5487 [D loss: 0.693515, acc.: 48.83%] [G loss: 0.716520]
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5488 [D loss: 0.697144, acc.: 47.46%] [G loss: 0.719058]
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5489 [D loss: 0.692336, acc.: 50.00%] [G loss: 0.712382]
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5490 [D loss: 0.692073, acc.: 50.98%] [G loss: 0.709800]
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5491 [D loss: 0.699441, acc.: 45.12%] [G loss: 0.708453]
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5492 [D loss: 0.701724, acc.: 45.12%] [G loss: 0.702771]
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5493 [D loss: 0.693621, acc.: 49.61%] [G loss: 0.713582]
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5494 [D loss: 0.690350, acc.: 54.30%] [G loss: 0.697115]
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5495 [D loss: 0.699820, acc.: 45.51%] [G loss: 0.698845]
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5496 [D loss: 0.698874, acc.: 45.31%] [G loss: 0.709433]
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5497 [D loss: 0.693900, acc.: 50.39%] [G loss: 0.707163]
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5498 [D loss: 0.689493, acc.: 53.32%] [G loss: 0.709463]
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5499 [D loss: 0.693289, acc.: 49.41%] [G loss: 0.710867]
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5500 [D loss: 0.694450, acc.: 48.83%] [G loss: 0.712591]
1/1 [==============================] - 0s 16ms/step
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5501 [D loss: 0.689823, acc.: 51.76%] [G loss: 0.709167]
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5502 [D loss: 0.695746, acc.: 50.00%] [G loss: 0.720346]
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5503 [D loss: 0.694806, acc.: 48.05%] [G loss: 0.728647]
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5504 [D loss: 0.692396, acc.: 52.34%] [G loss: 0.718140]
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5505 [D loss: 0.691903, acc.: 49.41%] [G loss: 0.728412]
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5506 [D loss: 0.695628, acc.: 50.59%] [G loss: 0.735039]
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5507 [D loss: 0.693225, acc.: 51.37%] [G loss: 0.719890]
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5508 [D loss: 0.694174, acc.: 49.80%] [G loss: 0.734757]
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5509 [D loss: 0.688865, acc.: 53.52%] [G loss: 0.736672]
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5510 [D loss: 0.693905, acc.: 47.66%] [G loss: 0.721293]
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5511 [D loss: 0.692743, acc.: 51.76%] [G loss: 0.713842]
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5512 [D loss: 0.691140, acc.: 52.34%] [G loss: 0.710106]
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5513 [D loss: 0.695843, acc.: 49.02%] [G loss: 0.708165]
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5514 [D loss: 0.692085, acc.: 50.20%] [G loss: 0.704633]
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5515 [D loss: 0.691351, acc.: 51.56%] [G loss: 0.702857]
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5516 [D loss: 0.691321, acc.: 51.95%] [G loss: 0.704278]
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5517 [D loss: 0.695061, acc.: 51.76%] [G loss: 0.726240]
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5518 [D loss: 0.696191, acc.: 49.61%] [G loss: 0.736309]
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5519 [D loss: 0.695453, acc.: 49.22%] [G loss: 0.735603]
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5520 [D loss: 0.693673, acc.: 50.39%] [G loss: 0.726416]
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5521 [D loss: 0.692989, acc.: 51.17%] [G loss: 0.738939]
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5522 [D loss: 0.688083, acc.: 55.08%] [G loss: 0.738618]
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5523 [D loss: 0.685901, acc.: 58.20%] [G loss: 0.741064]
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5524 [D loss: 0.686858, acc.: 52.34%] [G loss: 0.728603]
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5525 [D loss: 0.687520, acc.: 54.88%] [G loss: 0.729356]
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5526 [D loss: 0.688820, acc.: 54.10%] [G loss: 0.724185]
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5527 [D loss: 0.690449, acc.: 51.95%] [G loss: 0.713012]
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5528 [D loss: 0.694451, acc.: 53.52%] [G loss: 0.698256]
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5529 [D loss: 0.698637, acc.: 48.83%] [G loss: 0.697592]
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5530 [D loss: 0.693034, acc.: 51.17%] [G loss: 0.697459]
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5531 [D loss: 0.697954, acc.: 48.44%] [G loss: 0.705919]
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5532 [D loss: 0.701293, acc.: 45.70%] [G loss: 0.716063]
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5533 [D loss: 0.690589, acc.: 52.54%] [G loss: 0.722137]
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5534 [D loss: 0.688792, acc.: 52.73%] [G loss: 0.748429]
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5535 [D loss: 0.692899, acc.: 50.20%] [G loss: 0.736639]
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5536 [D loss: 0.689570, acc.: 51.76%] [G loss: 0.730147]
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5537 [D loss: 0.684791, acc.: 54.10%] [G loss: 0.736108]
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5538 [D loss: 0.691049, acc.: 51.76%] [G loss: 0.726230]
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5539 [D loss: 0.687055, acc.: 55.08%] [G loss: 0.730885]
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5540 [D loss: 0.681636, acc.: 59.57%] [G loss: 0.728275]
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5541 [D loss: 0.686758, acc.: 52.54%] [G loss: 0.721721]
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5542 [D loss: 0.691493, acc.: 48.83%] [G loss: 0.711942]
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5543 [D loss: 0.693580, acc.: 47.27%] [G loss: 0.708251]
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5544 [D loss: 0.691221, acc.: 48.63%] [G loss: 0.697743]
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5545 [D loss: 0.697480, acc.: 43.55%] [G loss: 0.701358]
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5546 [D loss: 0.695533, acc.: 51.17%] [G loss: 0.708079]
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5547 [D loss: 0.702544, acc.: 42.19%] [G loss: 0.719236]
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5548 [D loss: 0.690139, acc.: 53.52%] [G loss: 0.740277]
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5549 [D loss: 0.689531, acc.: 52.73%] [G loss: 0.739377]
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5550 [D loss: 0.688474, acc.: 55.66%] [G loss: 0.747208]
1/1 [==============================] - 0s 17ms/step
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5551 [D loss: 0.692308, acc.: 52.15%] [G loss: 0.741716]
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5552 [D loss: 0.696072, acc.: 50.78%] [G loss: 0.735117]
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5553 [D loss: 0.695657, acc.: 49.02%] [G loss: 0.728945]
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5554 [D loss: 0.696202, acc.: 46.29%] [G loss: 0.709217]
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5555 [D loss: 0.696883, acc.: 49.02%] [G loss: 0.716811]
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5556 [D loss: 0.697961, acc.: 50.78%] [G loss: 0.693797]
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5557 [D loss: 0.695168, acc.: 46.09%] [G loss: 0.695204]
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5558 [D loss: 0.698277, acc.: 48.05%] [G loss: 0.704068]
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5559 [D loss: 0.694277, acc.: 49.02%] [G loss: 0.697859]
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5560 [D loss: 0.684797, acc.: 56.84%] [G loss: 0.720125]
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5561 [D loss: 0.691743, acc.: 51.56%] [G loss: 0.711971]
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5562 [D loss: 0.690326, acc.: 51.37%] [G loss: 0.715546]
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5563 [D loss: 0.697341, acc.: 50.39%] [G loss: 0.709656]
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5564 [D loss: 0.700882, acc.: 45.12%] [G loss: 0.708796]
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5565 [D loss: 0.687797, acc.: 52.73%] [G loss: 0.715186]
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5566 [D loss: 0.693870, acc.: 50.59%] [G loss: 0.713658]
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5567 [D loss: 0.690332, acc.: 52.15%] [G loss: 0.718497]
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5568 [D loss: 0.695643, acc.: 47.66%] [G loss: 0.714115]
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5569 [D loss: 0.698237, acc.: 49.41%] [G loss: 0.722492]
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5570 [D loss: 0.696058, acc.: 49.61%] [G loss: 0.712659]
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5571 [D loss: 0.695601, acc.: 48.63%] [G loss: 0.724466]
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5572 [D loss: 0.687116, acc.: 54.69%] [G loss: 0.724819]
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5573 [D loss: 0.690282, acc.: 52.93%] [G loss: 0.736798]
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5574 [D loss: 0.694789, acc.: 49.61%] [G loss: 0.732775]
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5575 [D loss: 0.688307, acc.: 54.88%] [G loss: 0.716126]
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5576 [D loss: 0.698801, acc.: 45.12%] [G loss: 0.723280]
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5577 [D loss: 0.693838, acc.: 49.22%] [G loss: 0.711656]
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5578 [D loss: 0.696138, acc.: 47.85%] [G loss: 0.718728]
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5579 [D loss: 0.692782, acc.: 51.56%] [G loss: 0.715920]
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5580 [D loss: 0.696770, acc.: 50.39%] [G loss: 0.712602]
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5581 [D loss: 0.696374, acc.: 49.41%] [G loss: 0.722777]
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5582 [D loss: 0.694225, acc.: 52.15%] [G loss: 0.707855]
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5583 [D loss: 0.686646, acc.: 52.34%] [G loss: 0.725150]
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5584 [D loss: 0.693856, acc.: 49.02%] [G loss: 0.719276]
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5585 [D loss: 0.684881, acc.: 53.52%] [G loss: 0.727998]
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5586 [D loss: 0.693866, acc.: 50.00%] [G loss: 0.714452]
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5587 [D loss: 0.691784, acc.: 49.61%] [G loss: 0.720692]
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5588 [D loss: 0.684654, acc.: 56.25%] [G loss: 0.715055]
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5589 [D loss: 0.695470, acc.: 48.24%] [G loss: 0.715132]
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5590 [D loss: 0.695388, acc.: 50.78%] [G loss: 0.712757]
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5591 [D loss: 0.693794, acc.: 51.56%] [G loss: 0.725234]
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5592 [D loss: 0.684945, acc.: 55.08%] [G loss: 0.714776]
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5593 [D loss: 0.696400, acc.: 47.27%] [G loss: 0.724398]
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5594 [D loss: 0.693470, acc.: 50.98%] [G loss: 0.729610]
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5595 [D loss: 0.694032, acc.: 50.39%] [G loss: 0.725040]
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5596 [D loss: 0.696914, acc.: 52.15%] [G loss: 0.722239]
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5597 [D loss: 0.687036, acc.: 53.12%] [G loss: 0.725181]
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5598 [D loss: 0.690492, acc.: 51.37%] [G loss: 0.735470]
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5599 [D loss: 0.699241, acc.: 46.48%] [G loss: 0.725630]
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5600 [D loss: 0.695912, acc.: 49.61%] [G loss: 0.728532]
1/1 [==============================] - 0s 27ms/step
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5601 [D loss: 0.695267, acc.: 48.63%] [G loss: 0.723089]
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5602 [D loss: 0.698576, acc.: 46.29%] [G loss: 0.720906]
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5603 [D loss: 0.692547, acc.: 50.59%] [G loss: 0.724193]
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5604 [D loss: 0.690939, acc.: 50.98%] [G loss: 0.714890]
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5605 [D loss: 0.695204, acc.: 48.44%] [G loss: 0.724451]
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5606 [D loss: 0.692935, acc.: 50.59%] [G loss: 0.715939]
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5607 [D loss: 0.691319, acc.: 53.32%] [G loss: 0.724259]
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5608 [D loss: 0.693184, acc.: 54.30%] [G loss: 0.717444]
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5609 [D loss: 0.697361, acc.: 49.41%] [G loss: 0.712741]
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5610 [D loss: 0.693400, acc.: 53.91%] [G loss: 0.710036]
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5611 [D loss: 0.700618, acc.: 48.24%] [G loss: 0.713376]
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5612 [D loss: 0.699181, acc.: 49.41%] [G loss: 0.702058]
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5613 [D loss: 0.699193, acc.: 48.44%] [G loss: 0.705933]
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5614 [D loss: 0.698114, acc.: 45.51%] [G loss: 0.714581]
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5615 [D loss: 0.697335, acc.: 48.44%] [G loss: 0.708446]
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5616 [D loss: 0.696217, acc.: 46.48%] [G loss: 0.721495]
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5617 [D loss: 0.695067, acc.: 49.61%] [G loss: 0.727064]
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5618 [D loss: 0.692251, acc.: 49.22%] [G loss: 0.729165]
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5619 [D loss: 0.696083, acc.: 50.00%] [G loss: 0.724976]
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5620 [D loss: 0.691056, acc.: 53.12%] [G loss: 0.729324]
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5621 [D loss: 0.690610, acc.: 52.93%] [G loss: 0.721953]
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5622 [D loss: 0.695682, acc.: 49.61%] [G loss: 0.719241]
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5623 [D loss: 0.694893, acc.: 51.37%] [G loss: 0.720346]
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5624 [D loss: 0.693760, acc.: 50.39%] [G loss: 0.713097]
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5625 [D loss: 0.694548, acc.: 50.98%] [G loss: 0.715370]
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5626 [D loss: 0.690832, acc.: 50.59%] [G loss: 0.713675]
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5627 [D loss: 0.695010, acc.: 47.46%] [G loss: 0.719614]
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5628 [D loss: 0.692505, acc.: 48.83%] [G loss: 0.723968]
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5629 [D loss: 0.698672, acc.: 45.51%] [G loss: 0.721124]
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5630 [D loss: 0.691150, acc.: 51.37%] [G loss: 0.720321]
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5631 [D loss: 0.692429, acc.: 50.78%] [G loss: 0.724002]
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5632 [D loss: 0.687861, acc.: 55.66%] [G loss: 0.731147]
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5633 [D loss: 0.683034, acc.: 58.40%] [G loss: 0.719910]
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5634 [D loss: 0.683897, acc.: 55.47%] [G loss: 0.714401]
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5635 [D loss: 0.688741, acc.: 55.47%] [G loss: 0.716574]
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5636 [D loss: 0.689045, acc.: 51.17%] [G loss: 0.730673]
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5637 [D loss: 0.693793, acc.: 49.41%] [G loss: 0.705160]
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5638 [D loss: 0.691000, acc.: 48.83%] [G loss: 0.707340]
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5639 [D loss: 0.690918, acc.: 51.76%] [G loss: 0.711771]
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5640 [D loss: 0.693594, acc.: 52.93%] [G loss: 0.713995]
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5641 [D loss: 0.692218, acc.: 51.17%] [G loss: 0.720229]
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5642 [D loss: 0.691304, acc.: 50.00%] [G loss: 0.718023]
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5643 [D loss: 0.695795, acc.: 48.63%] [G loss: 0.717272]
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5644 [D loss: 0.697963, acc.: 49.80%] [G loss: 0.720237]
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5645 [D loss: 0.696649, acc.: 47.27%] [G loss: 0.720571]
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5646 [D loss: 0.699303, acc.: 45.31%] [G loss: 0.725618]
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5647 [D loss: 0.699729, acc.: 43.55%] [G loss: 0.728907]
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5648 [D loss: 0.692245, acc.: 50.59%] [G loss: 0.731931]
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5649 [D loss: 0.696052, acc.: 47.07%] [G loss: 0.733579]
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5650 [D loss: 0.695235, acc.: 49.22%] [G loss: 0.731944]
1/1 [==============================] - 0s 18ms/step
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5651 [D loss: 0.695449, acc.: 47.85%] [G loss: 0.732820]
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5652 [D loss: 0.692450, acc.: 49.22%] [G loss: 0.739372]
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5653 [D loss: 0.689042, acc.: 53.91%] [G loss: 0.731258]
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5654 [D loss: 0.689359, acc.: 53.71%] [G loss: 0.738009]
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5655 [D loss: 0.684643, acc.: 55.66%] [G loss: 0.738903]
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5656 [D loss: 0.693816, acc.: 49.02%] [G loss: 0.727978]
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5657 [D loss: 0.691662, acc.: 52.34%] [G loss: 0.713685]
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5658 [D loss: 0.694174, acc.: 51.17%] [G loss: 0.717604]
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5659 [D loss: 0.693624, acc.: 46.88%] [G loss: 0.713495]
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5660 [D loss: 0.702419, acc.: 42.77%] [G loss: 0.701411]
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5661 [D loss: 0.704598, acc.: 42.19%] [G loss: 0.698530]
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5662 [D loss: 0.706144, acc.: 43.16%] [G loss: 0.696948]
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5663 [D loss: 0.698954, acc.: 45.31%] [G loss: 0.708445]
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5664 [D loss: 0.703277, acc.: 46.29%] [G loss: 0.713915]
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5665 [D loss: 0.694930, acc.: 49.02%] [G loss: 0.722326]
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5666 [D loss: 0.687736, acc.: 51.76%] [G loss: 0.730903]
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5667 [D loss: 0.691590, acc.: 55.47%] [G loss: 0.739426]
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5668 [D loss: 0.688718, acc.: 54.10%] [G loss: 0.746153]
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5669 [D loss: 0.694541, acc.: 51.37%] [G loss: 0.738568]
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5670 [D loss: 0.692402, acc.: 51.37%] [G loss: 0.732139]
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5671 [D loss: 0.690921, acc.: 52.34%] [G loss: 0.728068]
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5672 [D loss: 0.689198, acc.: 54.49%] [G loss: 0.723230]
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5673 [D loss: 0.688300, acc.: 52.54%] [G loss: 0.719861]
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5674 [D loss: 0.689843, acc.: 52.54%] [G loss: 0.710661]
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5675 [D loss: 0.697345, acc.: 47.27%] [G loss: 0.708648]
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5676 [D loss: 0.689618, acc.: 50.59%] [G loss: 0.711540]
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5677 [D loss: 0.695983, acc.: 47.27%] [G loss: 0.705893]
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5678 [D loss: 0.694384, acc.: 49.41%] [G loss: 0.711739]
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5679 [D loss: 0.697119, acc.: 47.27%] [G loss: 0.718696]
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5680 [D loss: 0.692797, acc.: 50.20%] [G loss: 0.728295]
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5681 [D loss: 0.699339, acc.: 44.53%] [G loss: 0.730800]
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5682 [D loss: 0.692768, acc.: 51.76%] [G loss: 0.736706]
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5683 [D loss: 0.694247, acc.: 50.59%] [G loss: 0.730225]
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5684 [D loss: 0.694211, acc.: 49.41%] [G loss: 0.732212]
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5685 [D loss: 0.693687, acc.: 50.20%] [G loss: 0.731392]
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5686 [D loss: 0.687855, acc.: 50.00%] [G loss: 0.730229]
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5687 [D loss: 0.689244, acc.: 50.98%] [G loss: 0.736982]
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5688 [D loss: 0.680890, acc.: 52.73%] [G loss: 0.730620]
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5689 [D loss: 0.688340, acc.: 50.20%] [G loss: 0.729346]
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5690 [D loss: 0.693179, acc.: 50.00%] [G loss: 0.727007]
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5691 [D loss: 0.693172, acc.: 51.37%] [G loss: 0.725761]
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5692 [D loss: 0.690598, acc.: 52.73%] [G loss: 0.727433]
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5693 [D loss: 0.691306, acc.: 51.76%] [G loss: 0.712426]
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5694 [D loss: 0.692060, acc.: 52.73%] [G loss: 0.710641]
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5695 [D loss: 0.696799, acc.: 47.85%] [G loss: 0.712225]
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5696 [D loss: 0.694482, acc.: 51.76%] [G loss: 0.709726]
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5697 [D loss: 0.701850, acc.: 45.12%] [G loss: 0.706982]
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5698 [D loss: 0.701088, acc.: 43.95%] [G loss: 0.705260]
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5699 [D loss: 0.699740, acc.: 46.29%] [G loss: 0.704781]
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5700 [D loss: 0.701940, acc.: 46.29%] [G loss: 0.707171]
1/1 [==============================] - 0s 20ms/step
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5701 [D loss: 0.697458, acc.: 45.90%] [G loss: 0.709792]
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5702 [D loss: 0.699372, acc.: 49.22%] [G loss: 0.723603]
8/8 [==============================] - 0s 5ms/step
5703 [D loss: 0.697223, acc.: 47.66%] [G loss: 0.721514]
8/8 [==============================] - 0s 7ms/step
5704 [D loss: 0.694484, acc.: 50.39%] [G loss: 0.714202]
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5705 [D loss: 0.690337, acc.: 52.34%] [G loss: 0.721748]
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5706 [D loss: 0.691202, acc.: 50.39%] [G loss: 0.718036]
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5707 [D loss: 0.691374, acc.: 51.95%] [G loss: 0.720169]
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5708 [D loss: 0.695029, acc.: 49.80%] [G loss: 0.712978]
8/8 [==============================] - 0s 5ms/step
5709 [D loss: 0.689338, acc.: 53.91%] [G loss: 0.709323]
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5710 [D loss: 0.695404, acc.: 49.02%] [G loss: 0.703831]
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5711 [D loss: 0.695588, acc.: 49.41%] [G loss: 0.708888]
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5712 [D loss: 0.695793, acc.: 46.48%] [G loss: 0.705782]
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5713 [D loss: 0.690396, acc.: 52.34%] [G loss: 0.707000]
8/8 [==============================] - 0s 5ms/step
5714 [D loss: 0.694069, acc.: 50.00%] [G loss: 0.706728]
8/8 [==============================] - 0s 7ms/step
5715 [D loss: 0.695533, acc.: 50.20%] [G loss: 0.711802]
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5716 [D loss: 0.698100, acc.: 48.63%] [G loss: 0.716822]
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5717 [D loss: 0.692357, acc.: 52.15%] [G loss: 0.722867]
8/8 [==============================] - 0s 5ms/step
5718 [D loss: 0.689625, acc.: 52.93%] [G loss: 0.720736]
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5719 [D loss: 0.695856, acc.: 48.05%] [G loss: 0.725999]
8/8 [==============================] - 0s 5ms/step
5720 [D loss: 0.695182, acc.: 50.39%] [G loss: 0.724953]
8/8 [==============================] - 0s 5ms/step
5721 [D loss: 0.694455, acc.: 51.37%] [G loss: 0.716829]
8/8 [==============================] - 0s 5ms/step
5722 [D loss: 0.686406, acc.: 55.27%] [G loss: 0.717954]
8/8 [==============================] - 0s 5ms/step
5723 [D loss: 0.688953, acc.: 54.69%] [G loss: 0.727952]
8/8 [==============================] - 0s 5ms/step
5724 [D loss: 0.691649, acc.: 50.98%] [G loss: 0.720817]
8/8 [==============================] - 0s 5ms/step
5725 [D loss: 0.687167, acc.: 52.73%] [G loss: 0.712354]
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5726 [D loss: 0.690656, acc.: 52.15%] [G loss: 0.718883]
8/8 [==============================] - 0s 5ms/step
5727 [D loss: 0.691856, acc.: 49.22%] [G loss: 0.719153]
8/8 [==============================] - 0s 5ms/step
5728 [D loss: 0.692807, acc.: 49.80%] [G loss: 0.710282]
8/8 [==============================] - 0s 5ms/step
5729 [D loss: 0.693121, acc.: 51.56%] [G loss: 0.714413]
8/8 [==============================] - 0s 5ms/step
5730 [D loss: 0.693393, acc.: 48.24%] [G loss: 0.729698]
8/8 [==============================] - 0s 5ms/step
5731 [D loss: 0.693078, acc.: 51.17%] [G loss: 0.730183]
8/8 [==============================] - 0s 5ms/step
5732 [D loss: 0.687446, acc.: 51.56%] [G loss: 0.732278]
8/8 [==============================] - 0s 5ms/step
5733 [D loss: 0.693581, acc.: 49.41%] [G loss: 0.741367]
8/8 [==============================] - 0s 5ms/step
5734 [D loss: 0.696954, acc.: 48.24%] [G loss: 0.724644]
8/8 [==============================] - 0s 5ms/step
5735 [D loss: 0.691578, acc.: 50.98%] [G loss: 0.722203]
8/8 [==============================] - 0s 5ms/step
5736 [D loss: 0.693383, acc.: 51.17%] [G loss: 0.718501]
8/8 [==============================] - 0s 7ms/step
5737 [D loss: 0.691831, acc.: 51.17%] [G loss: 0.702184]
8/8 [==============================] - 0s 5ms/step
5738 [D loss: 0.698475, acc.: 50.20%] [G loss: 0.696337]
8/8 [==============================] - 0s 5ms/step
5739 [D loss: 0.699802, acc.: 47.85%] [G loss: 0.696290]
8/8 [==============================] - 0s 5ms/step
5740 [D loss: 0.696792, acc.: 50.00%] [G loss: 0.696355]
8/8 [==============================] - 0s 5ms/step
5741 [D loss: 0.693708, acc.: 52.34%] [G loss: 0.709486]
8/8 [==============================] - 0s 5ms/step
5742 [D loss: 0.697534, acc.: 49.22%] [G loss: 0.718265]
8/8 [==============================] - 0s 5ms/step
5743 [D loss: 0.692104, acc.: 49.22%] [G loss: 0.741270]
8/8 [==============================] - 0s 7ms/step
5744 [D loss: 0.696175, acc.: 49.41%] [G loss: 0.734579]
8/8 [==============================] - 0s 5ms/step
5745 [D loss: 0.702953, acc.: 47.07%] [G loss: 0.718881]
8/8 [==============================] - 0s 5ms/step
5746 [D loss: 0.696764, acc.: 51.76%] [G loss: 0.723169]
8/8 [==============================] - 0s 5ms/step
5747 [D loss: 0.698329, acc.: 48.05%] [G loss: 0.709062]
8/8 [==============================] - 0s 5ms/step
5748 [D loss: 0.698349, acc.: 48.83%] [G loss: 0.716774]
8/8 [==============================] - 0s 5ms/step
5749 [D loss: 0.694348, acc.: 50.20%] [G loss: 0.710523]
8/8 [==============================] - 0s 5ms/step
5750 [D loss: 0.691335, acc.: 52.93%] [G loss: 0.707460]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 6ms/step
5751 [D loss: 0.695972, acc.: 53.12%] [G loss: 0.705325]
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5752 [D loss: 0.692207, acc.: 50.78%] [G loss: 0.712969]
8/8 [==============================] - 0s 5ms/step
5753 [D loss: 0.699676, acc.: 47.46%] [G loss: 0.716094]
8/8 [==============================] - 0s 5ms/step
5754 [D loss: 0.691670, acc.: 48.63%] [G loss: 0.719761]
8/8 [==============================] - 0s 5ms/step
5755 [D loss: 0.701848, acc.: 48.44%] [G loss: 0.712658]
8/8 [==============================] - 0s 5ms/step
5756 [D loss: 0.698918, acc.: 50.39%] [G loss: 0.725911]
8/8 [==============================] - 0s 5ms/step
5757 [D loss: 0.692315, acc.: 47.46%] [G loss: 0.744304]
8/8 [==============================] - 0s 5ms/step
5758 [D loss: 0.694076, acc.: 50.39%] [G loss: 0.734384]
8/8 [==============================] - 0s 5ms/step
5759 [D loss: 0.694061, acc.: 48.24%] [G loss: 0.736971]
8/8 [==============================] - 0s 5ms/step
5760 [D loss: 0.691821, acc.: 52.15%] [G loss: 0.731826]
8/8 [==============================] - 0s 5ms/step
5761 [D loss: 0.689409, acc.: 53.71%] [G loss: 0.733047]
8/8 [==============================] - 0s 5ms/step
5762 [D loss: 0.692200, acc.: 51.95%] [G loss: 0.722576]
8/8 [==============================] - 0s 5ms/step
5763 [D loss: 0.694390, acc.: 50.78%] [G loss: 0.722016]
8/8 [==============================] - 0s 5ms/step
5764 [D loss: 0.690571, acc.: 53.91%] [G loss: 0.722492]
8/8 [==============================] - 0s 5ms/step
5765 [D loss: 0.695283, acc.: 49.41%] [G loss: 0.711309]
8/8 [==============================] - 0s 5ms/step
5766 [D loss: 0.696337, acc.: 47.85%] [G loss: 0.706888]
8/8 [==============================] - 0s 5ms/step
5767 [D loss: 0.696209, acc.: 48.44%] [G loss: 0.703418]
8/8 [==============================] - 0s 5ms/step
5768 [D loss: 0.695207, acc.: 51.37%] [G loss: 0.692656]
8/8 [==============================] - 0s 5ms/step
5769 [D loss: 0.693189, acc.: 50.20%] [G loss: 0.704928]
8/8 [==============================] - 0s 5ms/step
5770 [D loss: 0.694157, acc.: 50.39%] [G loss: 0.719544]
8/8 [==============================] - 0s 5ms/step
5771 [D loss: 0.693762, acc.: 51.37%] [G loss: 0.722027]
8/8 [==============================] - 0s 5ms/step
5772 [D loss: 0.695647, acc.: 50.59%] [G loss: 0.722700]
8/8 [==============================] - 0s 5ms/step
5773 [D loss: 0.691300, acc.: 51.76%] [G loss: 0.715327]
8/8 [==============================] - 0s 5ms/step
5774 [D loss: 0.696801, acc.: 46.09%] [G loss: 0.710866]
8/8 [==============================] - 0s 5ms/step
5775 [D loss: 0.695887, acc.: 47.27%] [G loss: 0.712575]
8/8 [==============================] - 0s 5ms/step
5776 [D loss: 0.694017, acc.: 50.20%] [G loss: 0.711054]
8/8 [==============================] - 0s 5ms/step
5777 [D loss: 0.691027, acc.: 53.91%] [G loss: 0.706680]
8/8 [==============================] - 0s 5ms/step
5778 [D loss: 0.693921, acc.: 50.00%] [G loss: 0.698934]
8/8 [==============================] - 0s 5ms/step
5779 [D loss: 0.695848, acc.: 46.29%] [G loss: 0.694874]
8/8 [==============================] - 0s 5ms/step
5780 [D loss: 0.696389, acc.: 44.34%] [G loss: 0.686593]
8/8 [==============================] - 0s 5ms/step
5781 [D loss: 0.699046, acc.: 46.48%] [G loss: 0.697363]
8/8 [==============================] - 0s 5ms/step
5782 [D loss: 0.700189, acc.: 45.12%] [G loss: 0.706285]
8/8 [==============================] - 0s 5ms/step
5783 [D loss: 0.692427, acc.: 49.61%] [G loss: 0.733116]
8/8 [==============================] - 0s 5ms/step
5784 [D loss: 0.697464, acc.: 49.22%] [G loss: 0.735971]
8/8 [==============================] - 0s 5ms/step
5785 [D loss: 0.693730, acc.: 46.48%] [G loss: 0.735781]
8/8 [==============================] - 0s 5ms/step
5786 [D loss: 0.690791, acc.: 48.44%] [G loss: 0.733231]
8/8 [==============================] - 0s 5ms/step
5787 [D loss: 0.693770, acc.: 48.63%] [G loss: 0.730576]
8/8 [==============================] - 0s 5ms/step
5788 [D loss: 0.695205, acc.: 48.05%] [G loss: 0.722555]
8/8 [==============================] - 0s 5ms/step
5789 [D loss: 0.696222, acc.: 49.80%] [G loss: 0.720582]
8/8 [==============================] - 0s 5ms/step
5790 [D loss: 0.688206, acc.: 53.71%] [G loss: 0.721227]
8/8 [==============================] - 0s 5ms/step
5791 [D loss: 0.693076, acc.: 52.73%] [G loss: 0.717083]
8/8 [==============================] - 0s 5ms/step
5792 [D loss: 0.690739, acc.: 52.15%] [G loss: 0.711250]
8/8 [==============================] - 0s 5ms/step
5793 [D loss: 0.692653, acc.: 49.02%] [G loss: 0.708832]
8/8 [==============================] - 0s 5ms/step
5794 [D loss: 0.685280, acc.: 52.34%] [G loss: 0.702784]
8/8 [==============================] - 0s 5ms/step
5795 [D loss: 0.694119, acc.: 45.51%] [G loss: 0.699554]
8/8 [==============================] - 0s 5ms/step
5796 [D loss: 0.700160, acc.: 45.90%] [G loss: 0.699303]
8/8 [==============================] - 0s 5ms/step
5797 [D loss: 0.690803, acc.: 52.34%] [G loss: 0.704535]
8/8 [==============================] - 0s 5ms/step
5798 [D loss: 0.693931, acc.: 49.22%] [G loss: 0.714227]
8/8 [==============================] - 0s 5ms/step
5799 [D loss: 0.689336, acc.: 52.54%] [G loss: 0.731942]
8/8 [==============================] - 0s 5ms/step
5800 [D loss: 0.687995, acc.: 52.15%] [G loss: 0.739914]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 5ms/step
5801 [D loss: 0.686368, acc.: 52.34%] [G loss: 0.739580]
8/8 [==============================] - 0s 5ms/step
5802 [D loss: 0.694131, acc.: 49.22%] [G loss: 0.725400]
8/8 [==============================] - 0s 5ms/step
5803 [D loss: 0.695271, acc.: 50.98%] [G loss: 0.724361]
8/8 [==============================] - 0s 5ms/step
5804 [D loss: 0.692654, acc.: 47.66%] [G loss: 0.724389]
8/8 [==============================] - 0s 5ms/step
5805 [D loss: 0.689151, acc.: 57.23%] [G loss: 0.722199]
8/8 [==============================] - 0s 5ms/step
5806 [D loss: 0.688575, acc.: 52.73%] [G loss: 0.713788]
8/8 [==============================] - 0s 5ms/step
5807 [D loss: 0.690682, acc.: 50.00%] [G loss: 0.708452]
8/8 [==============================] - 0s 5ms/step
5808 [D loss: 0.688342, acc.: 52.73%] [G loss: 0.708827]
8/8 [==============================] - 0s 5ms/step
5809 [D loss: 0.692847, acc.: 51.56%] [G loss: 0.699893]
8/8 [==============================] - 0s 5ms/step
5810 [D loss: 0.685036, acc.: 51.76%] [G loss: 0.706369]
8/8 [==============================] - 0s 5ms/step
5811 [D loss: 0.692806, acc.: 50.59%] [G loss: 0.701168]
8/8 [==============================] - 0s 5ms/step
5812 [D loss: 0.694033, acc.: 48.63%] [G loss: 0.712341]
8/8 [==============================] - 0s 5ms/step
5813 [D loss: 0.694037, acc.: 47.85%] [G loss: 0.721767]
8/8 [==============================] - 0s 5ms/step
5814 [D loss: 0.688342, acc.: 52.34%] [G loss: 0.723371]
8/8 [==============================] - 0s 5ms/step
5815 [D loss: 0.696307, acc.: 49.22%] [G loss: 0.731610]
8/8 [==============================] - 0s 5ms/step
5816 [D loss: 0.696062, acc.: 44.34%] [G loss: 0.721746]
8/8 [==============================] - 0s 5ms/step
5817 [D loss: 0.690654, acc.: 51.37%] [G loss: 0.727171]
8/8 [==============================] - 0s 5ms/step
5818 [D loss: 0.693816, acc.: 49.41%] [G loss: 0.722901]
8/8 [==============================] - 0s 5ms/step
5819 [D loss: 0.697730, acc.: 49.02%] [G loss: 0.715307]
8/8 [==============================] - 0s 5ms/step
5820 [D loss: 0.705130, acc.: 47.27%] [G loss: 0.704177]
8/8 [==============================] - 0s 5ms/step
5821 [D loss: 0.693783, acc.: 51.76%] [G loss: 0.697819]
8/8 [==============================] - 0s 5ms/step
5822 [D loss: 0.690708, acc.: 50.59%] [G loss: 0.713691]
8/8 [==============================] - 0s 5ms/step
5823 [D loss: 0.692484, acc.: 45.31%] [G loss: 0.713397]
8/8 [==============================] - 0s 5ms/step
5824 [D loss: 0.691215, acc.: 49.02%] [G loss: 0.727575]
8/8 [==============================] - 0s 5ms/step
5825 [D loss: 0.684964, acc.: 53.71%] [G loss: 0.731682]
8/8 [==============================] - 0s 5ms/step
5826 [D loss: 0.692668, acc.: 48.83%] [G loss: 0.726139]
8/8 [==============================] - 0s 6ms/step
5827 [D loss: 0.694415, acc.: 50.00%] [G loss: 0.715594]
8/8 [==============================] - 0s 5ms/step
5828 [D loss: 0.696822, acc.: 48.05%] [G loss: 0.713706]
8/8 [==============================] - 0s 5ms/step
5829 [D loss: 0.697390, acc.: 45.31%] [G loss: 0.711183]
8/8 [==============================] - 0s 5ms/step
5830 [D loss: 0.690701, acc.: 50.39%] [G loss: 0.715014]
8/8 [==============================] - 0s 5ms/step
5831 [D loss: 0.694318, acc.: 47.07%] [G loss: 0.703325]
8/8 [==============================] - 0s 5ms/step
5832 [D loss: 0.698605, acc.: 45.90%] [G loss: 0.704808]
8/8 [==============================] - 0s 5ms/step
5833 [D loss: 0.693078, acc.: 51.95%] [G loss: 0.702374]
8/8 [==============================] - 0s 5ms/step
5834 [D loss: 0.693412, acc.: 53.91%] [G loss: 0.701832]
8/8 [==============================] - 0s 5ms/step
5835 [D loss: 0.695765, acc.: 50.59%] [G loss: 0.695637]
8/8 [==============================] - 0s 5ms/step
5836 [D loss: 0.696426, acc.: 48.44%] [G loss: 0.701791]
8/8 [==============================] - 0s 5ms/step
5837 [D loss: 0.700018, acc.: 44.73%] [G loss: 0.697134]
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5838 [D loss: 0.699119, acc.: 48.24%] [G loss: 0.702310]
8/8 [==============================] - 0s 5ms/step
5839 [D loss: 0.694634, acc.: 50.39%] [G loss: 0.713790]
8/8 [==============================] - 0s 5ms/step
5840 [D loss: 0.692178, acc.: 50.39%] [G loss: 0.726955]
8/8 [==============================] - 0s 5ms/step
5841 [D loss: 0.690522, acc.: 53.32%] [G loss: 0.725426]
8/8 [==============================] - 0s 5ms/step
5842 [D loss: 0.695178, acc.: 49.02%] [G loss: 0.728437]
8/8 [==============================] - 0s 5ms/step
5843 [D loss: 0.691041, acc.: 54.30%] [G loss: 0.720750]
8/8 [==============================] - 0s 5ms/step
5844 [D loss: 0.698163, acc.: 44.34%] [G loss: 0.721154]
8/8 [==============================] - 0s 5ms/step
5845 [D loss: 0.692040, acc.: 50.98%] [G loss: 0.716630]
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5846 [D loss: 0.691773, acc.: 51.56%] [G loss: 0.717160]
8/8 [==============================] - 0s 5ms/step
5847 [D loss: 0.689864, acc.: 52.93%] [G loss: 0.720215]
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5848 [D loss: 0.692406, acc.: 52.15%] [G loss: 0.717709]
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5849 [D loss: 0.690111, acc.: 53.32%] [G loss: 0.719995]
8/8 [==============================] - 0s 5ms/step
5850 [D loss: 0.686596, acc.: 53.52%] [G loss: 0.713190]
1/1 [==============================] - 0s 18ms/step
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5851 [D loss: 0.692032, acc.: 50.98%] [G loss: 0.717442]
8/8 [==============================] - 0s 5ms/step
5852 [D loss: 0.693369, acc.: 51.17%] [G loss: 0.712590]
8/8 [==============================] - 0s 5ms/step
5853 [D loss: 0.691378, acc.: 50.59%] [G loss: 0.709854]
8/8 [==============================] - 0s 5ms/step
5854 [D loss: 0.692554, acc.: 52.54%] [G loss: 0.722061]
8/8 [==============================] - 0s 5ms/step
5855 [D loss: 0.691029, acc.: 51.56%] [G loss: 0.717689]
8/8 [==============================] - 0s 5ms/step
5856 [D loss: 0.686024, acc.: 54.49%] [G loss: 0.725504]
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5857 [D loss: 0.681309, acc.: 56.25%] [G loss: 0.734926]
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5858 [D loss: 0.686929, acc.: 52.15%] [G loss: 0.737566]
8/8 [==============================] - 0s 5ms/step
5859 [D loss: 0.685200, acc.: 56.25%] [G loss: 0.737990]
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5860 [D loss: 0.688026, acc.: 52.15%] [G loss: 0.732777]
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5861 [D loss: 0.694523, acc.: 50.59%] [G loss: 0.729784]
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5862 [D loss: 0.691757, acc.: 51.37%] [G loss: 0.723467]
8/8 [==============================] - 0s 5ms/step
5863 [D loss: 0.685012, acc.: 53.71%] [G loss: 0.729389]
8/8 [==============================] - 0s 5ms/step
5864 [D loss: 0.685312, acc.: 52.93%] [G loss: 0.720009]
8/8 [==============================] - 0s 5ms/step
5865 [D loss: 0.690776, acc.: 51.76%] [G loss: 0.715997]
8/8 [==============================] - 0s 5ms/step
5866 [D loss: 0.698413, acc.: 50.20%] [G loss: 0.706377]
8/8 [==============================] - 0s 5ms/step
5867 [D loss: 0.702417, acc.: 47.66%] [G loss: 0.699083]
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5868 [D loss: 0.702569, acc.: 48.63%] [G loss: 0.699579]
8/8 [==============================] - 0s 5ms/step
5869 [D loss: 0.699633, acc.: 47.27%] [G loss: 0.713601]
8/8 [==============================] - 0s 5ms/step
5870 [D loss: 0.697441, acc.: 49.41%] [G loss: 0.717389]
8/8 [==============================] - 0s 5ms/step
5871 [D loss: 0.697957, acc.: 45.90%] [G loss: 0.725529]
8/8 [==============================] - 0s 5ms/step
5872 [D loss: 0.694740, acc.: 49.80%] [G loss: 0.728941]
8/8 [==============================] - 0s 5ms/step
5873 [D loss: 0.694939, acc.: 46.48%] [G loss: 0.717292]
8/8 [==============================] - 0s 5ms/step
5874 [D loss: 0.692101, acc.: 50.78%] [G loss: 0.722686]
8/8 [==============================] - 0s 5ms/step
5875 [D loss: 0.687814, acc.: 53.32%] [G loss: 0.724982]
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5876 [D loss: 0.686914, acc.: 53.71%] [G loss: 0.724667]
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5877 [D loss: 0.693788, acc.: 47.85%] [G loss: 0.716351]
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5878 [D loss: 0.692978, acc.: 48.63%] [G loss: 0.710757]
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5879 [D loss: 0.695415, acc.: 49.22%] [G loss: 0.700651]
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5880 [D loss: 0.695710, acc.: 50.39%] [G loss: 0.717417]
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5881 [D loss: 0.698628, acc.: 46.29%] [G loss: 0.712677]
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5882 [D loss: 0.691235, acc.: 50.00%] [G loss: 0.717848]
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5883 [D loss: 0.690124, acc.: 52.54%] [G loss: 0.707331]
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5884 [D loss: 0.691748, acc.: 50.98%] [G loss: 0.720169]
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5885 [D loss: 0.696655, acc.: 50.20%] [G loss: 0.716820]
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5886 [D loss: 0.701056, acc.: 44.92%] [G loss: 0.710382]
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5887 [D loss: 0.690864, acc.: 51.95%] [G loss: 0.714296]
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5888 [D loss: 0.695032, acc.: 48.63%] [G loss: 0.699282]
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5889 [D loss: 0.691751, acc.: 52.93%] [G loss: 0.711102]
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5890 [D loss: 0.692617, acc.: 50.00%] [G loss: 0.710502]
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5891 [D loss: 0.697902, acc.: 48.24%] [G loss: 0.708145]
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5892 [D loss: 0.691356, acc.: 53.91%] [G loss: 0.714465]
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5893 [D loss: 0.696971, acc.: 53.32%] [G loss: 0.712410]
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5894 [D loss: 0.692707, acc.: 51.95%] [G loss: 0.723481]
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5895 [D loss: 0.693407, acc.: 52.15%] [G loss: 0.711442]
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5896 [D loss: 0.695450, acc.: 50.39%] [G loss: 0.718034]
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5897 [D loss: 0.687237, acc.: 55.27%] [G loss: 0.726302]
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5898 [D loss: 0.691783, acc.: 48.83%] [G loss: 0.717391]
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5899 [D loss: 0.694131, acc.: 48.63%] [G loss: 0.721433]
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5900 [D loss: 0.687096, acc.: 52.54%] [G loss: 0.720707]
1/1 [==============================] - 0s 18ms/step
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5901 [D loss: 0.688889, acc.: 52.34%] [G loss: 0.715978]
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5902 [D loss: 0.692686, acc.: 50.78%] [G loss: 0.714679]
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5903 [D loss: 0.691858, acc.: 51.37%] [G loss: 0.708627]
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5904 [D loss: 0.696471, acc.: 48.05%] [G loss: 0.706198]
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5905 [D loss: 0.695540, acc.: 49.61%] [G loss: 0.706742]
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5906 [D loss: 0.694372, acc.: 49.41%] [G loss: 0.712954]
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5907 [D loss: 0.690280, acc.: 52.54%] [G loss: 0.712441]
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5908 [D loss: 0.692819, acc.: 48.83%] [G loss: 0.719572]
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5909 [D loss: 0.690602, acc.: 48.83%] [G loss: 0.714490]
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5910 [D loss: 0.689667, acc.: 51.56%] [G loss: 0.723790]
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5911 [D loss: 0.687968, acc.: 52.34%] [G loss: 0.721647]
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5912 [D loss: 0.690972, acc.: 49.02%] [G loss: 0.712805]
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5913 [D loss: 0.692826, acc.: 49.22%] [G loss: 0.719987]
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5914 [D loss: 0.696052, acc.: 48.83%] [G loss: 0.726636]
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5915 [D loss: 0.680911, acc.: 54.88%] [G loss: 0.723154]
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5916 [D loss: 0.691798, acc.: 51.17%] [G loss: 0.708978]
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5917 [D loss: 0.688619, acc.: 51.17%] [G loss: 0.714100]
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5918 [D loss: 0.694295, acc.: 49.41%] [G loss: 0.706704]
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5919 [D loss: 0.686871, acc.: 53.52%] [G loss: 0.712255]
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5920 [D loss: 0.690807, acc.: 50.78%] [G loss: 0.709746]
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5921 [D loss: 0.695439, acc.: 48.83%] [G loss: 0.701882]
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5922 [D loss: 0.694831, acc.: 48.63%] [G loss: 0.709126]
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5923 [D loss: 0.698126, acc.: 44.14%] [G loss: 0.724865]
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5924 [D loss: 0.691427, acc.: 48.83%] [G loss: 0.720411]
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5925 [D loss: 0.694757, acc.: 47.46%] [G loss: 0.726576]
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5926 [D loss: 0.695061, acc.: 48.24%] [G loss: 0.723052]
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5927 [D loss: 0.694133, acc.: 49.41%] [G loss: 0.735503]
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5928 [D loss: 0.697524, acc.: 48.24%] [G loss: 0.733056]
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5929 [D loss: 0.692580, acc.: 51.95%] [G loss: 0.732287]
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5930 [D loss: 0.695208, acc.: 47.46%] [G loss: 0.733650]
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5931 [D loss: 0.691631, acc.: 49.80%] [G loss: 0.726556]
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5932 [D loss: 0.693390, acc.: 51.17%] [G loss: 0.718719]
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5933 [D loss: 0.688350, acc.: 52.34%] [G loss: 0.715178]
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5934 [D loss: 0.697052, acc.: 46.68%] [G loss: 0.710308]
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5935 [D loss: 0.691514, acc.: 49.80%] [G loss: 0.703769]
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5936 [D loss: 0.687559, acc.: 51.37%] [G loss: 0.714856]
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5937 [D loss: 0.693301, acc.: 50.00%] [G loss: 0.719465]
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5938 [D loss: 0.687622, acc.: 53.32%] [G loss: 0.724980]
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5939 [D loss: 0.689593, acc.: 51.37%] [G loss: 0.736681]
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5940 [D loss: 0.687323, acc.: 50.20%] [G loss: 0.736072]
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5941 [D loss: 0.695015, acc.: 46.88%] [G loss: 0.733637]
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5942 [D loss: 0.692297, acc.: 50.00%] [G loss: 0.732572]
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5943 [D loss: 0.694768, acc.: 50.78%] [G loss: 0.726223]
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5944 [D loss: 0.696580, acc.: 48.44%] [G loss: 0.719403]
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5945 [D loss: 0.684861, acc.: 54.10%] [G loss: 0.720364]
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5946 [D loss: 0.686954, acc.: 54.49%] [G loss: 0.715784]
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5947 [D loss: 0.686298, acc.: 53.12%] [G loss: 0.711291]
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5948 [D loss: 0.691082, acc.: 49.80%] [G loss: 0.705068]
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5949 [D loss: 0.690797, acc.: 51.76%] [G loss: 0.702121]
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5950 [D loss: 0.693184, acc.: 45.70%] [G loss: 0.702298]
1/1 [==============================] - 0s 18ms/step
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5951 [D loss: 0.691476, acc.: 50.98%] [G loss: 0.719591]
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5952 [D loss: 0.687839, acc.: 51.95%] [G loss: 0.719509]
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5953 [D loss: 0.681995, acc.: 56.25%] [G loss: 0.720017]
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5954 [D loss: 0.678873, acc.: 53.91%] [G loss: 0.744456]
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5955 [D loss: 0.693585, acc.: 48.24%] [G loss: 0.729240]
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5956 [D loss: 0.694621, acc.: 46.88%] [G loss: 0.734834]
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5957 [D loss: 0.697229, acc.: 46.48%] [G loss: 0.716811]
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5958 [D loss: 0.699805, acc.: 47.07%] [G loss: 0.705795]
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5959 [D loss: 0.691953, acc.: 49.61%] [G loss: 0.706143]
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5960 [D loss: 0.693425, acc.: 48.44%] [G loss: 0.711713]
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5961 [D loss: 0.693983, acc.: 47.85%] [G loss: 0.712495]
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5962 [D loss: 0.690612, acc.: 53.52%] [G loss: 0.716529]
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5963 [D loss: 0.693366, acc.: 49.41%] [G loss: 0.719251]
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5964 [D loss: 0.687223, acc.: 51.56%] [G loss: 0.720284]
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5965 [D loss: 0.692389, acc.: 48.24%] [G loss: 0.726132]
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5966 [D loss: 0.693273, acc.: 50.98%] [G loss: 0.722957]
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5967 [D loss: 0.692282, acc.: 50.39%] [G loss: 0.722952]
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5968 [D loss: 0.695868, acc.: 50.39%] [G loss: 0.716348]
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5969 [D loss: 0.697024, acc.: 47.85%] [G loss: 0.719233]
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5970 [D loss: 0.697040, acc.: 47.07%] [G loss: 0.713385]
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5971 [D loss: 0.698565, acc.: 50.78%] [G loss: 0.708918]
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5972 [D loss: 0.689444, acc.: 54.69%] [G loss: 0.719912]
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5973 [D loss: 0.696618, acc.: 49.61%] [G loss: 0.710908]
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5974 [D loss: 0.693190, acc.: 50.20%] [G loss: 0.709568]
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5975 [D loss: 0.689957, acc.: 52.73%] [G loss: 0.712952]
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5976 [D loss: 0.700705, acc.: 47.27%] [G loss: 0.705472]
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5977 [D loss: 0.691212, acc.: 51.37%] [G loss: 0.714045]
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5978 [D loss: 0.692535, acc.: 48.63%] [G loss: 0.710199]
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5979 [D loss: 0.706932, acc.: 46.48%] [G loss: 0.703959]
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5980 [D loss: 0.709071, acc.: 48.63%] [G loss: 0.722813]
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5981 [D loss: 0.700048, acc.: 43.16%] [G loss: 0.728625]
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5982 [D loss: 0.696923, acc.: 50.78%] [G loss: 0.736456]
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5983 [D loss: 0.693838, acc.: 48.63%] [G loss: 0.743098]
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5984 [D loss: 0.695862, acc.: 46.09%] [G loss: 0.744953]
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5985 [D loss: 0.688860, acc.: 51.95%] [G loss: 0.728394]
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5986 [D loss: 0.692240, acc.: 50.78%] [G loss: 0.732245]
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5987 [D loss: 0.691560, acc.: 51.95%] [G loss: 0.725589]
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5988 [D loss: 0.687890, acc.: 53.52%] [G loss: 0.730815]
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5989 [D loss: 0.692512, acc.: 52.34%] [G loss: 0.708673]
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5990 [D loss: 0.693750, acc.: 50.00%] [G loss: 0.709339]
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5991 [D loss: 0.696771, acc.: 48.24%] [G loss: 0.702990]
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5992 [D loss: 0.696061, acc.: 47.46%] [G loss: 0.702029]
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5993 [D loss: 0.700568, acc.: 45.51%] [G loss: 0.701240]
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5994 [D loss: 0.696345, acc.: 48.05%] [G loss: 0.719324]
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5995 [D loss: 0.695298, acc.: 49.80%] [G loss: 0.722140]
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5996 [D loss: 0.698654, acc.: 48.44%] [G loss: 0.718283]
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5997 [D loss: 0.694601, acc.: 48.63%] [G loss: 0.720300]
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5998 [D loss: 0.696198, acc.: 49.02%] [G loss: 0.712339]
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5999 [D loss: 0.692109, acc.: 51.37%] [G loss: 0.721528]
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6000 [D loss: 0.695643, acc.: 49.02%] [G loss: 0.716029]
1/1 [==============================] - 0s 22ms/step
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6001 [D loss: 0.692004, acc.: 50.39%] [G loss: 0.708935]
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6002 [D loss: 0.692689, acc.: 51.37%] [G loss: 0.715887]
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6003 [D loss: 0.692812, acc.: 52.15%] [G loss: 0.711810]
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6004 [D loss: 0.689208, acc.: 49.61%] [G loss: 0.719377]
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6005 [D loss: 0.699822, acc.: 46.29%] [G loss: 0.716025]
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6006 [D loss: 0.694314, acc.: 46.29%] [G loss: 0.727595]
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6007 [D loss: 0.691865, acc.: 51.17%] [G loss: 0.725206]
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6008 [D loss: 0.689632, acc.: 51.17%] [G loss: 0.742940]
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6009 [D loss: 0.688012, acc.: 52.34%] [G loss: 0.741524]
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6010 [D loss: 0.686335, acc.: 54.30%] [G loss: 0.744372]
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6011 [D loss: 0.690070, acc.: 51.37%] [G loss: 0.740556]
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6012 [D loss: 0.692585, acc.: 47.46%] [G loss: 0.739824]
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6013 [D loss: 0.692742, acc.: 49.02%] [G loss: 0.733613]
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6014 [D loss: 0.690034, acc.: 52.54%] [G loss: 0.725848]
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6015 [D loss: 0.698642, acc.: 46.09%] [G loss: 0.705201]
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6016 [D loss: 0.699238, acc.: 49.02%] [G loss: 0.703000]
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6017 [D loss: 0.694523, acc.: 51.56%] [G loss: 0.703545]
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6018 [D loss: 0.701511, acc.: 47.66%] [G loss: 0.700047]
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6019 [D loss: 0.698150, acc.: 48.05%] [G loss: 0.710497]
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6020 [D loss: 0.695659, acc.: 49.80%] [G loss: 0.720962]
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6021 [D loss: 0.690517, acc.: 51.76%] [G loss: 0.717264]
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6022 [D loss: 0.697987, acc.: 46.48%] [G loss: 0.724800]
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6023 [D loss: 0.690940, acc.: 55.08%] [G loss: 0.730212]
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6024 [D loss: 0.690479, acc.: 53.71%] [G loss: 0.720109]
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6025 [D loss: 0.695455, acc.: 50.39%] [G loss: 0.719884]
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6026 [D loss: 0.700179, acc.: 47.07%] [G loss: 0.714351]
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6027 [D loss: 0.698615, acc.: 46.48%] [G loss: 0.709705]
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6028 [D loss: 0.699225, acc.: 42.97%] [G loss: 0.707645]
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6029 [D loss: 0.693731, acc.: 49.02%] [G loss: 0.706656]
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6030 [D loss: 0.698147, acc.: 42.77%] [G loss: 0.707632]
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6031 [D loss: 0.693094, acc.: 49.80%] [G loss: 0.705027]
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6032 [D loss: 0.693786, acc.: 50.98%] [G loss: 0.707113]
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6033 [D loss: 0.695184, acc.: 50.00%] [G loss: 0.715030]
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6034 [D loss: 0.689001, acc.: 53.91%] [G loss: 0.723063]
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6035 [D loss: 0.699213, acc.: 47.85%] [G loss: 0.725980]
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6036 [D loss: 0.689776, acc.: 54.30%] [G loss: 0.725813]
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6037 [D loss: 0.693084, acc.: 49.02%] [G loss: 0.730209]
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6038 [D loss: 0.691758, acc.: 52.34%] [G loss: 0.729365]
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6039 [D loss: 0.690290, acc.: 49.61%] [G loss: 0.730120]
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6040 [D loss: 0.692711, acc.: 50.78%] [G loss: 0.726228]
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6041 [D loss: 0.694799, acc.: 50.00%] [G loss: 0.713974]
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6042 [D loss: 0.692589, acc.: 53.32%] [G loss: 0.711237]
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6043 [D loss: 0.691184, acc.: 51.95%] [G loss: 0.708950]
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6044 [D loss: 0.688432, acc.: 54.88%] [G loss: 0.715733]
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6045 [D loss: 0.695091, acc.: 49.61%] [G loss: 0.704642]
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6046 [D loss: 0.690285, acc.: 52.15%] [G loss: 0.715662]
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6047 [D loss: 0.692545, acc.: 53.32%] [G loss: 0.723261]
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6048 [D loss: 0.680503, acc.: 58.59%] [G loss: 0.726879]
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6049 [D loss: 0.687146, acc.: 51.76%] [G loss: 0.719997]
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6050 [D loss: 0.692096, acc.: 51.37%] [G loss: 0.728802]
1/1 [==============================] - 0s 17ms/step
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6051 [D loss: 0.697056, acc.: 48.83%] [G loss: 0.726839]
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6052 [D loss: 0.697087, acc.: 48.24%] [G loss: 0.715289]
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6053 [D loss: 0.695662, acc.: 48.44%] [G loss: 0.707204]
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6054 [D loss: 0.700672, acc.: 47.07%] [G loss: 0.706852]
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6055 [D loss: 0.698443, acc.: 50.59%] [G loss: 0.714595]
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6056 [D loss: 0.696323, acc.: 47.46%] [G loss: 0.722461]
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6057 [D loss: 0.689202, acc.: 53.32%] [G loss: 0.711939]
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6058 [D loss: 0.692035, acc.: 50.98%] [G loss: 0.726685]
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6059 [D loss: 0.685798, acc.: 54.49%] [G loss: 0.720603]
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6060 [D loss: 0.694098, acc.: 51.17%] [G loss: 0.722664]
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6061 [D loss: 0.691837, acc.: 49.61%] [G loss: 0.723260]
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6062 [D loss: 0.697786, acc.: 46.48%] [G loss: 0.731417]
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6063 [D loss: 0.691335, acc.: 48.83%] [G loss: 0.735041]
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6064 [D loss: 0.689894, acc.: 49.61%] [G loss: 0.725730]
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6065 [D loss: 0.693869, acc.: 48.63%] [G loss: 0.736227]
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6066 [D loss: 0.691296, acc.: 52.34%] [G loss: 0.724024]
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6067 [D loss: 0.692255, acc.: 48.83%] [G loss: 0.727399]
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6068 [D loss: 0.694937, acc.: 48.05%] [G loss: 0.725008]
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6069 [D loss: 0.698282, acc.: 45.51%] [G loss: 0.717418]
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6070 [D loss: 0.696342, acc.: 46.88%] [G loss: 0.718594]
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6071 [D loss: 0.698768, acc.: 46.68%] [G loss: 0.721580]
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6072 [D loss: 0.694604, acc.: 50.39%] [G loss: 0.717680]
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6073 [D loss: 0.690798, acc.: 49.41%] [G loss: 0.717653]
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6074 [D loss: 0.693063, acc.: 50.78%] [G loss: 0.716317]
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6075 [D loss: 0.694243, acc.: 47.85%] [G loss: 0.713320]
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6076 [D loss: 0.693117, acc.: 49.02%] [G loss: 0.710877]
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6077 [D loss: 0.698152, acc.: 44.14%] [G loss: 0.716557]
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6078 [D loss: 0.700467, acc.: 46.88%] [G loss: 0.709332]
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6079 [D loss: 0.695480, acc.: 50.20%] [G loss: 0.709141]
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6080 [D loss: 0.693825, acc.: 50.39%] [G loss: 0.707899]
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6081 [D loss: 0.698992, acc.: 45.51%] [G loss: 0.710843]
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6082 [D loss: 0.696582, acc.: 50.59%] [G loss: 0.709868]
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6083 [D loss: 0.694936, acc.: 49.02%] [G loss: 0.715073]
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6084 [D loss: 0.688846, acc.: 51.95%] [G loss: 0.710040]
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6085 [D loss: 0.689596, acc.: 50.98%] [G loss: 0.718835]
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6086 [D loss: 0.693245, acc.: 52.73%] [G loss: 0.723637]
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6087 [D loss: 0.690929, acc.: 50.78%] [G loss: 0.724858]
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6088 [D loss: 0.694915, acc.: 48.63%] [G loss: 0.721363]
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6089 [D loss: 0.687391, acc.: 53.32%] [G loss: 0.723029]
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6090 [D loss: 0.692651, acc.: 55.66%] [G loss: 0.721628]
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6091 [D loss: 0.694224, acc.: 48.83%] [G loss: 0.720144]
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6092 [D loss: 0.692424, acc.: 51.76%] [G loss: 0.719300]
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6093 [D loss: 0.697413, acc.: 46.88%] [G loss: 0.707898]
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6094 [D loss: 0.700161, acc.: 45.51%] [G loss: 0.711346]
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6095 [D loss: 0.693654, acc.: 50.00%] [G loss: 0.711969]
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6096 [D loss: 0.696482, acc.: 50.59%] [G loss: 0.711481]
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6097 [D loss: 0.694297, acc.: 52.15%] [G loss: 0.708558]
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6098 [D loss: 0.693877, acc.: 50.59%] [G loss: 0.714596]
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6099 [D loss: 0.693213, acc.: 52.34%] [G loss: 0.710324]
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6100 [D loss: 0.691747, acc.: 54.10%] [G loss: 0.708267]
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6101 [D loss: 0.690045, acc.: 52.54%] [G loss: 0.708288]
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6102 [D loss: 0.693628, acc.: 50.98%] [G loss: 0.702765]
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6103 [D loss: 0.690897, acc.: 51.37%] [G loss: 0.708408]
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6104 [D loss: 0.695433, acc.: 50.39%] [G loss: 0.718865]
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6105 [D loss: 0.697992, acc.: 48.63%] [G loss: 0.706830]
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6106 [D loss: 0.703254, acc.: 44.73%] [G loss: 0.705163]
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6107 [D loss: 0.700413, acc.: 45.51%] [G loss: 0.705603]
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6108 [D loss: 0.693695, acc.: 49.61%] [G loss: 0.714494]
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6109 [D loss: 0.691242, acc.: 52.93%] [G loss: 0.718340]
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6110 [D loss: 0.696021, acc.: 50.00%] [G loss: 0.728842]
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6111 [D loss: 0.692461, acc.: 55.47%] [G loss: 0.738716]
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6112 [D loss: 0.688695, acc.: 52.54%] [G loss: 0.731851]
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6113 [D loss: 0.693978, acc.: 50.78%] [G loss: 0.730905]
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6114 [D loss: 0.692591, acc.: 49.80%] [G loss: 0.734914]
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6115 [D loss: 0.688420, acc.: 52.34%] [G loss: 0.731721]
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6116 [D loss: 0.695635, acc.: 49.22%] [G loss: 0.717913]
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6117 [D loss: 0.693848, acc.: 50.20%] [G loss: 0.711862]
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6118 [D loss: 0.691850, acc.: 50.78%] [G loss: 0.719049]
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6119 [D loss: 0.695268, acc.: 48.63%] [G loss: 0.708617]
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6120 [D loss: 0.694837, acc.: 48.24%] [G loss: 0.703941]
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6121 [D loss: 0.698614, acc.: 44.34%] [G loss: 0.707919]
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6122 [D loss: 0.697587, acc.: 47.27%] [G loss: 0.718894]
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6123 [D loss: 0.695199, acc.: 47.27%] [G loss: 0.726214]
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6124 [D loss: 0.686894, acc.: 52.34%] [G loss: 0.728915]
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6125 [D loss: 0.694725, acc.: 50.59%] [G loss: 0.739483]
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6126 [D loss: 0.689346, acc.: 54.10%] [G loss: 0.730787]
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6127 [D loss: 0.696644, acc.: 51.17%] [G loss: 0.735938]
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6128 [D loss: 0.687477, acc.: 56.25%] [G loss: 0.732678]
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6129 [D loss: 0.692260, acc.: 51.95%] [G loss: 0.723241]
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6130 [D loss: 0.696647, acc.: 49.41%] [G loss: 0.717422]
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6131 [D loss: 0.697528, acc.: 44.92%] [G loss: 0.709844]
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6132 [D loss: 0.690117, acc.: 51.95%] [G loss: 0.706914]
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6133 [D loss: 0.699064, acc.: 47.07%] [G loss: 0.699857]
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6134 [D loss: 0.698122, acc.: 46.29%] [G loss: 0.701369]
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6135 [D loss: 0.694263, acc.: 47.85%] [G loss: 0.705972]
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6136 [D loss: 0.692608, acc.: 50.59%] [G loss: 0.715410]
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6137 [D loss: 0.689802, acc.: 48.83%] [G loss: 0.727725]
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6138 [D loss: 0.694400, acc.: 48.44%] [G loss: 0.735382]
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6139 [D loss: 0.687354, acc.: 50.59%] [G loss: 0.740460]
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6140 [D loss: 0.689586, acc.: 50.78%] [G loss: 0.749447]
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6141 [D loss: 0.686455, acc.: 56.25%] [G loss: 0.732637]
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6142 [D loss: 0.692146, acc.: 50.39%] [G loss: 0.735258]
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6143 [D loss: 0.687769, acc.: 51.56%] [G loss: 0.720721]
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6144 [D loss: 0.691058, acc.: 49.80%] [G loss: 0.722621]
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6145 [D loss: 0.692818, acc.: 50.98%] [G loss: 0.711158]
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6146 [D loss: 0.693134, acc.: 51.76%] [G loss: 0.705416]
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6147 [D loss: 0.694645, acc.: 52.54%] [G loss: 0.689163]
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6148 [D loss: 0.700498, acc.: 45.31%] [G loss: 0.692661]
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6149 [D loss: 0.696682, acc.: 51.37%] [G loss: 0.698081]
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6150 [D loss: 0.698705, acc.: 45.51%] [G loss: 0.715783]
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6151 [D loss: 0.693727, acc.: 50.78%] [G loss: 0.715404]
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6152 [D loss: 0.694852, acc.: 49.80%] [G loss: 0.714052]
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6153 [D loss: 0.695556, acc.: 49.41%] [G loss: 0.719960]
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6154 [D loss: 0.692486, acc.: 52.93%] [G loss: 0.723037]
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6155 [D loss: 0.694867, acc.: 47.85%] [G loss: 0.714662]
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6156 [D loss: 0.692735, acc.: 48.83%] [G loss: 0.713118]
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6157 [D loss: 0.692986, acc.: 47.46%] [G loss: 0.716557]
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6158 [D loss: 0.692677, acc.: 49.80%] [G loss: 0.711278]
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6159 [D loss: 0.693231, acc.: 50.39%] [G loss: 0.716172]
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6160 [D loss: 0.690699, acc.: 54.88%] [G loss: 0.713752]
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6161 [D loss: 0.695067, acc.: 53.71%] [G loss: 0.718064]
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6162 [D loss: 0.692601, acc.: 50.98%] [G loss: 0.717568]
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6163 [D loss: 0.684701, acc.: 58.40%] [G loss: 0.713037]
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6164 [D loss: 0.685878, acc.: 55.08%] [G loss: 0.738500]
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6165 [D loss: 0.693642, acc.: 51.17%] [G loss: 0.724078]
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6166 [D loss: 0.694219, acc.: 47.46%] [G loss: 0.717281]
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6167 [D loss: 0.702057, acc.: 45.70%] [G loss: 0.707763]
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6168 [D loss: 0.694959, acc.: 49.02%] [G loss: 0.704640]
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6169 [D loss: 0.699438, acc.: 45.70%] [G loss: 0.705521]
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6170 [D loss: 0.703017, acc.: 43.55%] [G loss: 0.705313]
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6171 [D loss: 0.697132, acc.: 45.70%] [G loss: 0.708745]
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6172 [D loss: 0.695609, acc.: 48.44%] [G loss: 0.705251]
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6173 [D loss: 0.699699, acc.: 46.48%] [G loss: 0.716340]
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6174 [D loss: 0.696195, acc.: 48.24%] [G loss: 0.707932]
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6175 [D loss: 0.696704, acc.: 46.88%] [G loss: 0.717839]
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6176 [D loss: 0.694242, acc.: 48.24%] [G loss: 0.719421]
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6177 [D loss: 0.692559, acc.: 52.15%] [G loss: 0.716545]
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6178 [D loss: 0.696169, acc.: 46.88%] [G loss: 0.722954]
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6179 [D loss: 0.693600, acc.: 51.17%] [G loss: 0.715136]
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6180 [D loss: 0.693670, acc.: 49.22%] [G loss: 0.714164]
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6181 [D loss: 0.691886, acc.: 52.73%] [G loss: 0.709997]
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6182 [D loss: 0.694381, acc.: 49.80%] [G loss: 0.712401]
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6183 [D loss: 0.693612, acc.: 49.22%] [G loss: 0.702609]
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6184 [D loss: 0.693349, acc.: 50.98%] [G loss: 0.704423]
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6185 [D loss: 0.690822, acc.: 51.95%] [G loss: 0.697436]
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6186 [D loss: 0.696717, acc.: 48.63%] [G loss: 0.714135]
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6187 [D loss: 0.694623, acc.: 47.66%] [G loss: 0.717626]
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6188 [D loss: 0.691395, acc.: 49.61%] [G loss: 0.721175]
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6189 [D loss: 0.695359, acc.: 45.31%] [G loss: 0.721781]
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6190 [D loss: 0.689184, acc.: 50.59%] [G loss: 0.725133]
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6191 [D loss: 0.687374, acc.: 52.73%] [G loss: 0.729493]
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6192 [D loss: 0.690748, acc.: 50.98%] [G loss: 0.727890]
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6193 [D loss: 0.687827, acc.: 51.37%] [G loss: 0.729528]
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6194 [D loss: 0.694097, acc.: 50.39%] [G loss: 0.724267]
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6195 [D loss: 0.693499, acc.: 52.34%] [G loss: 0.724174]
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6196 [D loss: 0.696142, acc.: 46.09%] [G loss: 0.720777]
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6197 [D loss: 0.689857, acc.: 48.83%] [G loss: 0.718745]
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6198 [D loss: 0.695065, acc.: 48.24%] [G loss: 0.714163]
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6199 [D loss: 0.696930, acc.: 46.68%] [G loss: 0.710050]
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6200 [D loss: 0.697414, acc.: 49.80%] [G loss: 0.702931]
1/1 [==============================] - 0s 19ms/step
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6201 [D loss: 0.695273, acc.: 45.70%] [G loss: 0.702384]
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6202 [D loss: 0.701791, acc.: 43.95%] [G loss: 0.699668]
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6203 [D loss: 0.693559, acc.: 51.17%] [G loss: 0.706139]
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6204 [D loss: 0.699842, acc.: 44.34%] [G loss: 0.707211]
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6205 [D loss: 0.691804, acc.: 50.78%] [G loss: 0.723312]
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6206 [D loss: 0.691568, acc.: 51.17%] [G loss: 0.730216]
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6207 [D loss: 0.689649, acc.: 53.52%] [G loss: 0.735283]
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6208 [D loss: 0.693159, acc.: 50.00%] [G loss: 0.732328]
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6209 [D loss: 0.691018, acc.: 54.30%] [G loss: 0.726156]
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6210 [D loss: 0.691011, acc.: 51.76%] [G loss: 0.720440]
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6211 [D loss: 0.692624, acc.: 52.73%] [G loss: 0.712814]
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6212 [D loss: 0.693502, acc.: 50.39%] [G loss: 0.710925]
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6213 [D loss: 0.694934, acc.: 47.85%] [G loss: 0.708499]
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6214 [D loss: 0.687810, acc.: 53.32%] [G loss: 0.703995]
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6215 [D loss: 0.695926, acc.: 48.63%] [G loss: 0.699447]
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6216 [D loss: 0.693852, acc.: 47.85%] [G loss: 0.690684]
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6217 [D loss: 0.700173, acc.: 46.09%] [G loss: 0.701056]
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6218 [D loss: 0.698238, acc.: 46.88%] [G loss: 0.707420]
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6219 [D loss: 0.693531, acc.: 51.56%] [G loss: 0.724503]
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6220 [D loss: 0.692369, acc.: 49.80%] [G loss: 0.736132]
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6221 [D loss: 0.688334, acc.: 54.49%] [G loss: 0.741260]
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6222 [D loss: 0.694571, acc.: 47.46%] [G loss: 0.736912]
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6223 [D loss: 0.695823, acc.: 49.80%] [G loss: 0.730118]
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6224 [D loss: 0.698782, acc.: 48.05%] [G loss: 0.724066]
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6225 [D loss: 0.692576, acc.: 53.12%] [G loss: 0.713847]
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6226 [D loss: 0.692489, acc.: 52.93%] [G loss: 0.721056]
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6227 [D loss: 0.691637, acc.: 53.52%] [G loss: 0.709071]
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6228 [D loss: 0.687171, acc.: 53.52%] [G loss: 0.712858]
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6229 [D loss: 0.699939, acc.: 44.73%] [G loss: 0.688974]
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6230 [D loss: 0.692693, acc.: 46.68%] [G loss: 0.689509]
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6231 [D loss: 0.698187, acc.: 46.48%] [G loss: 0.698162]
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6232 [D loss: 0.693441, acc.: 49.41%] [G loss: 0.706652]
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6233 [D loss: 0.694140, acc.: 50.98%] [G loss: 0.727128]
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6234 [D loss: 0.693069, acc.: 50.20%] [G loss: 0.729519]
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6235 [D loss: 0.687059, acc.: 51.95%] [G loss: 0.735317]
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6236 [D loss: 0.692901, acc.: 48.24%] [G loss: 0.734481]
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6237 [D loss: 0.690540, acc.: 54.10%] [G loss: 0.735386]
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6238 [D loss: 0.692107, acc.: 48.05%] [G loss: 0.730224]
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6239 [D loss: 0.690696, acc.: 50.78%] [G loss: 0.726911]
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6240 [D loss: 0.691651, acc.: 54.49%] [G loss: 0.718635]
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6241 [D loss: 0.693576, acc.: 48.83%] [G loss: 0.708462]
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6242 [D loss: 0.699693, acc.: 46.48%] [G loss: 0.703731]
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6243 [D loss: 0.702524, acc.: 43.55%] [G loss: 0.694879]
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6244 [D loss: 0.696190, acc.: 47.66%] [G loss: 0.697419]
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6245 [D loss: 0.701385, acc.: 45.12%] [G loss: 0.705093]
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6246 [D loss: 0.698044, acc.: 47.07%] [G loss: 0.709616]
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6247 [D loss: 0.697427, acc.: 43.95%] [G loss: 0.721086]
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6248 [D loss: 0.694916, acc.: 47.85%] [G loss: 0.726339]
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6249 [D loss: 0.690770, acc.: 50.59%] [G loss: 0.723244]
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6250 [D loss: 0.693991, acc.: 51.56%] [G loss: 0.720454]
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6251 [D loss: 0.695087, acc.: 47.07%] [G loss: 0.718153]
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6252 [D loss: 0.693315, acc.: 51.76%] [G loss: 0.710325]
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6253 [D loss: 0.688821, acc.: 53.32%] [G loss: 0.717728]
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6254 [D loss: 0.689389, acc.: 52.54%] [G loss: 0.720277]
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6255 [D loss: 0.691637, acc.: 52.15%] [G loss: 0.710171]
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6256 [D loss: 0.688772, acc.: 55.27%] [G loss: 0.710406]
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6257 [D loss: 0.693694, acc.: 50.39%] [G loss: 0.708180]
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6258 [D loss: 0.692204, acc.: 49.02%] [G loss: 0.720657]
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6259 [D loss: 0.688956, acc.: 51.95%] [G loss: 0.716916]
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6260 [D loss: 0.693353, acc.: 48.44%] [G loss: 0.728803]
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6261 [D loss: 0.692764, acc.: 47.85%] [G loss: 0.729085]
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6262 [D loss: 0.685921, acc.: 52.15%] [G loss: 0.733023]
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6263 [D loss: 0.695016, acc.: 46.09%] [G loss: 0.741117]
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6264 [D loss: 0.688752, acc.: 54.49%] [G loss: 0.733586]
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6265 [D loss: 0.697593, acc.: 48.24%] [G loss: 0.728789]
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6266 [D loss: 0.689935, acc.: 51.76%] [G loss: 0.732896]
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6267 [D loss: 0.692070, acc.: 51.37%] [G loss: 0.727284]
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6268 [D loss: 0.693273, acc.: 50.78%] [G loss: 0.721074]
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6269 [D loss: 0.693791, acc.: 48.83%] [G loss: 0.720055]
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6270 [D loss: 0.696781, acc.: 48.63%] [G loss: 0.712566]
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6271 [D loss: 0.700875, acc.: 45.31%] [G loss: 0.705859]
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6272 [D loss: 0.694165, acc.: 47.85%] [G loss: 0.705402]
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6273 [D loss: 0.690517, acc.: 47.07%] [G loss: 0.718941]
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6274 [D loss: 0.689712, acc.: 53.52%] [G loss: 0.730066]
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6275 [D loss: 0.689788, acc.: 55.47%] [G loss: 0.728285]
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6276 [D loss: 0.683621, acc.: 56.45%] [G loss: 0.735209]
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6277 [D loss: 0.694506, acc.: 51.17%] [G loss: 0.721482]
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6278 [D loss: 0.693800, acc.: 48.44%] [G loss: 0.725968]
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6279 [D loss: 0.684980, acc.: 55.27%] [G loss: 0.727743]
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6280 [D loss: 0.691176, acc.: 50.39%] [G loss: 0.715042]
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6281 [D loss: 0.689324, acc.: 52.93%] [G loss: 0.702253]
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6282 [D loss: 0.694969, acc.: 47.07%] [G loss: 0.694019]
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6283 [D loss: 0.696147, acc.: 49.80%] [G loss: 0.692131]
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6284 [D loss: 0.696313, acc.: 48.63%] [G loss: 0.689189]
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6285 [D loss: 0.700637, acc.: 46.29%] [G loss: 0.694324]
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6286 [D loss: 0.698764, acc.: 46.68%] [G loss: 0.700739]
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6287 [D loss: 0.696669, acc.: 50.59%] [G loss: 0.725290]
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6288 [D loss: 0.698900, acc.: 47.27%] [G loss: 0.732029]
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6289 [D loss: 0.700955, acc.: 43.95%] [G loss: 0.742095]
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6290 [D loss: 0.697258, acc.: 47.07%] [G loss: 0.732778]
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6291 [D loss: 0.693134, acc.: 49.80%] [G loss: 0.731219]
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6292 [D loss: 0.690492, acc.: 52.54%] [G loss: 0.738448]
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6293 [D loss: 0.689280, acc.: 54.30%] [G loss: 0.730834]
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6294 [D loss: 0.693294, acc.: 51.95%] [G loss: 0.719881]
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6295 [D loss: 0.694152, acc.: 46.88%] [G loss: 0.712301]
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6296 [D loss: 0.695051, acc.: 47.07%] [G loss: 0.706170]
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6297 [D loss: 0.697057, acc.: 46.29%] [G loss: 0.699846]
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6298 [D loss: 0.697181, acc.: 49.41%] [G loss: 0.708395]
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6299 [D loss: 0.692602, acc.: 52.54%] [G loss: 0.721017]
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6300 [D loss: 0.691620, acc.: 51.37%] [G loss: 0.726041]
1/1 [==============================] - 0s 19ms/step
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6301 [D loss: 0.700334, acc.: 46.48%] [G loss: 0.717420]
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6302 [D loss: 0.702218, acc.: 48.05%] [G loss: 0.722267]
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6303 [D loss: 0.697490, acc.: 49.22%] [G loss: 0.719976]
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6304 [D loss: 0.696646, acc.: 48.44%] [G loss: 0.715572]
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6305 [D loss: 0.698884, acc.: 45.31%] [G loss: 0.702501]
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6306 [D loss: 0.692895, acc.: 53.32%] [G loss: 0.695425]
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6307 [D loss: 0.692663, acc.: 50.59%] [G loss: 0.702947]
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6308 [D loss: 0.695481, acc.: 47.46%] [G loss: 0.700240]
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6309 [D loss: 0.696074, acc.: 46.88%] [G loss: 0.701229]
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6310 [D loss: 0.693548, acc.: 49.80%] [G loss: 0.695903]
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6311 [D loss: 0.696743, acc.: 51.76%] [G loss: 0.714325]
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6312 [D loss: 0.695656, acc.: 52.34%] [G loss: 0.726317]
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6313 [D loss: 0.697794, acc.: 47.27%] [G loss: 0.734206]
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6314 [D loss: 0.693757, acc.: 52.93%] [G loss: 0.725621]
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6315 [D loss: 0.691906, acc.: 51.56%] [G loss: 0.730325]
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6316 [D loss: 0.693778, acc.: 51.17%] [G loss: 0.734488]
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6317 [D loss: 0.691988, acc.: 50.39%] [G loss: 0.731165]
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6318 [D loss: 0.686120, acc.: 52.15%] [G loss: 0.726078]
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6319 [D loss: 0.687084, acc.: 56.84%] [G loss: 0.728288]
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6320 [D loss: 0.687483, acc.: 54.30%] [G loss: 0.731382]
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6321 [D loss: 0.690595, acc.: 52.93%] [G loss: 0.722833]
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6322 [D loss: 0.692195, acc.: 53.12%] [G loss: 0.715694]
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6323 [D loss: 0.692359, acc.: 51.56%] [G loss: 0.710953]
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6324 [D loss: 0.700336, acc.: 44.34%] [G loss: 0.705095]
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6325 [D loss: 0.693951, acc.: 45.12%] [G loss: 0.712890]
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6326 [D loss: 0.691853, acc.: 49.41%] [G loss: 0.720680]
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6327 [D loss: 0.689580, acc.: 50.59%] [G loss: 0.723010]
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6328 [D loss: 0.692438, acc.: 48.24%] [G loss: 0.720827]
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6329 [D loss: 0.696327, acc.: 47.07%] [G loss: 0.722797]
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6330 [D loss: 0.696306, acc.: 46.09%] [G loss: 0.721549]
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6331 [D loss: 0.694022, acc.: 46.48%] [G loss: 0.716700]
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6332 [D loss: 0.695348, acc.: 49.80%] [G loss: 0.720065]
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6333 [D loss: 0.695287, acc.: 43.75%] [G loss: 0.719263]
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6334 [D loss: 0.691995, acc.: 49.02%] [G loss: 0.714353]
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6335 [D loss: 0.696131, acc.: 47.85%] [G loss: 0.710203]
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6336 [D loss: 0.686559, acc.: 52.73%] [G loss: 0.707230]
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6337 [D loss: 0.690907, acc.: 50.20%] [G loss: 0.704666]
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6338 [D loss: 0.693069, acc.: 48.05%] [G loss: 0.705326]
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6339 [D loss: 0.694999, acc.: 47.27%] [G loss: 0.703193]
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6340 [D loss: 0.695555, acc.: 49.22%] [G loss: 0.708378]
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6341 [D loss: 0.696603, acc.: 49.61%] [G loss: 0.718848]
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6342 [D loss: 0.695580, acc.: 51.76%] [G loss: 0.715976]
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6343 [D loss: 0.699142, acc.: 49.22%] [G loss: 0.718922]
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6344 [D loss: 0.693591, acc.: 50.59%] [G loss: 0.721519]
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6345 [D loss: 0.695498, acc.: 47.46%] [G loss: 0.713789]
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6346 [D loss: 0.697079, acc.: 46.48%] [G loss: 0.713856]
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6347 [D loss: 0.688226, acc.: 52.73%] [G loss: 0.715875]
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6348 [D loss: 0.689759, acc.: 53.12%] [G loss: 0.708983]
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6349 [D loss: 0.695110, acc.: 51.95%] [G loss: 0.709970]
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6350 [D loss: 0.695367, acc.: 48.24%] [G loss: 0.712166]
1/1 [==============================] - 0s 17ms/step
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6351 [D loss: 0.697337, acc.: 43.95%] [G loss: 0.702972]
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6352 [D loss: 0.696924, acc.: 45.12%] [G loss: 0.697893]
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6353 [D loss: 0.694336, acc.: 49.80%] [G loss: 0.709902]
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6354 [D loss: 0.698429, acc.: 46.48%] [G loss: 0.710569]
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6355 [D loss: 0.691801, acc.: 51.56%] [G loss: 0.713362]
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6356 [D loss: 0.687553, acc.: 54.30%] [G loss: 0.719162]
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6357 [D loss: 0.694052, acc.: 52.34%] [G loss: 0.721160]
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6358 [D loss: 0.695215, acc.: 51.17%] [G loss: 0.732116]
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6359 [D loss: 0.693124, acc.: 52.15%] [G loss: 0.733607]
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6360 [D loss: 0.695621, acc.: 48.05%] [G loss: 0.726046]
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6361 [D loss: 0.692303, acc.: 49.22%] [G loss: 0.722700]
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6362 [D loss: 0.691483, acc.: 51.17%] [G loss: 0.718684]
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6363 [D loss: 0.694757, acc.: 49.02%] [G loss: 0.715165]
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6364 [D loss: 0.700589, acc.: 46.68%] [G loss: 0.706495]
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6365 [D loss: 0.693247, acc.: 52.73%] [G loss: 0.700805]
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6366 [D loss: 0.696581, acc.: 48.63%] [G loss: 0.704652]
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6367 [D loss: 0.692878, acc.: 50.78%] [G loss: 0.700887]
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6368 [D loss: 0.694031, acc.: 45.70%] [G loss: 0.709597]
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6369 [D loss: 0.694985, acc.: 48.24%] [G loss: 0.707591]
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6370 [D loss: 0.697402, acc.: 48.44%] [G loss: 0.718792]
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6371 [D loss: 0.687419, acc.: 54.49%] [G loss: 0.726195]
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6372 [D loss: 0.687246, acc.: 55.66%] [G loss: 0.727600]
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6373 [D loss: 0.690844, acc.: 53.52%] [G loss: 0.740517]
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6374 [D loss: 0.688297, acc.: 53.91%] [G loss: 0.733330]
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6375 [D loss: 0.692651, acc.: 53.32%] [G loss: 0.725655]
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6376 [D loss: 0.689168, acc.: 51.56%] [G loss: 0.727786]
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6377 [D loss: 0.696386, acc.: 50.59%] [G loss: 0.723749]
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6378 [D loss: 0.690548, acc.: 52.54%] [G loss: 0.717191]
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6379 [D loss: 0.695704, acc.: 48.83%] [G loss: 0.707340]
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6380 [D loss: 0.690884, acc.: 51.95%] [G loss: 0.712002]
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6381 [D loss: 0.698237, acc.: 48.05%] [G loss: 0.705802]
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6382 [D loss: 0.697904, acc.: 45.70%] [G loss: 0.702698]
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6383 [D loss: 0.701281, acc.: 43.16%] [G loss: 0.708321]
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6384 [D loss: 0.696078, acc.: 48.63%] [G loss: 0.723421]
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6385 [D loss: 0.687629, acc.: 50.59%] [G loss: 0.741459]
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6386 [D loss: 0.684928, acc.: 52.73%] [G loss: 0.736005]
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6387 [D loss: 0.696317, acc.: 47.07%] [G loss: 0.733656]
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6388 [D loss: 0.691715, acc.: 52.73%] [G loss: 0.730239]
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6389 [D loss: 0.691537, acc.: 52.34%] [G loss: 0.722426]
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6390 [D loss: 0.687748, acc.: 53.71%] [G loss: 0.714624]
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6391 [D loss: 0.691365, acc.: 51.37%] [G loss: 0.709658]
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6392 [D loss: 0.693578, acc.: 47.46%] [G loss: 0.707312]
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6393 [D loss: 0.696402, acc.: 47.07%] [G loss: 0.703590]
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6394 [D loss: 0.695041, acc.: 49.02%] [G loss: 0.701949]
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6395 [D loss: 0.702254, acc.: 47.46%] [G loss: 0.706182]
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6396 [D loss: 0.698184, acc.: 46.88%] [G loss: 0.709638]
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6397 [D loss: 0.691471, acc.: 53.32%] [G loss: 0.718342]
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6398 [D loss: 0.695649, acc.: 47.66%] [G loss: 0.726419]
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6399 [D loss: 0.689752, acc.: 47.66%] [G loss: 0.736722]
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6400 [D loss: 0.693671, acc.: 48.24%] [G loss: 0.732395]
1/1 [==============================] - 0s 17ms/step
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6401 [D loss: 0.699428, acc.: 45.70%] [G loss: 0.729413]
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6402 [D loss: 0.696649, acc.: 50.00%] [G loss: 0.725041]
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6403 [D loss: 0.695912, acc.: 47.46%] [G loss: 0.718355]
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6404 [D loss: 0.692296, acc.: 49.02%] [G loss: 0.713788]
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6405 [D loss: 0.697538, acc.: 48.44%] [G loss: 0.715653]
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6406 [D loss: 0.689044, acc.: 51.56%] [G loss: 0.711224]
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6407 [D loss: 0.690894, acc.: 48.83%] [G loss: 0.704577]
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6408 [D loss: 0.692565, acc.: 48.63%] [G loss: 0.700697]
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6409 [D loss: 0.695013, acc.: 49.61%] [G loss: 0.706989]
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6410 [D loss: 0.693373, acc.: 52.15%] [G loss: 0.714167]
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6411 [D loss: 0.689993, acc.: 52.34%] [G loss: 0.717204]
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6412 [D loss: 0.689398, acc.: 54.49%] [G loss: 0.726198]
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6413 [D loss: 0.695770, acc.: 47.27%] [G loss: 0.720307]
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6414 [D loss: 0.686106, acc.: 52.93%] [G loss: 0.719614]
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6415 [D loss: 0.692901, acc.: 50.59%] [G loss: 0.716458]
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6416 [D loss: 0.693559, acc.: 46.88%] [G loss: 0.713725]
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6417 [D loss: 0.692202, acc.: 52.15%] [G loss: 0.708361]
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6418 [D loss: 0.696275, acc.: 46.88%] [G loss: 0.704853]
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6419 [D loss: 0.690710, acc.: 52.15%] [G loss: 0.702594]
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6420 [D loss: 0.690472, acc.: 53.32%] [G loss: 0.709618]
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6421 [D loss: 0.690424, acc.: 52.34%] [G loss: 0.699918]
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6422 [D loss: 0.691131, acc.: 51.37%] [G loss: 0.702407]
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6423 [D loss: 0.698882, acc.: 46.68%] [G loss: 0.704958]
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6424 [D loss: 0.697625, acc.: 50.00%] [G loss: 0.709490]
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6425 [D loss: 0.696639, acc.: 50.00%] [G loss: 0.717739]
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6426 [D loss: 0.695032, acc.: 50.00%] [G loss: 0.717525]
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6427 [D loss: 0.691685, acc.: 50.39%] [G loss: 0.727613]
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6428 [D loss: 0.689997, acc.: 51.56%] [G loss: 0.729292]
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6429 [D loss: 0.696322, acc.: 48.63%] [G loss: 0.729599]
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6430 [D loss: 0.693118, acc.: 50.78%] [G loss: 0.737117]
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6431 [D loss: 0.697578, acc.: 47.85%] [G loss: 0.729296]
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6432 [D loss: 0.694902, acc.: 48.63%] [G loss: 0.718755]
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6433 [D loss: 0.690881, acc.: 54.88%] [G loss: 0.717684]
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6434 [D loss: 0.691227, acc.: 53.12%] [G loss: 0.720870]
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6435 [D loss: 0.687605, acc.: 52.34%] [G loss: 0.718417]
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6436 [D loss: 0.689812, acc.: 52.34%] [G loss: 0.710668]
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6437 [D loss: 0.692106, acc.: 51.37%] [G loss: 0.699186]
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6438 [D loss: 0.695607, acc.: 47.07%] [G loss: 0.693528]
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6439 [D loss: 0.702845, acc.: 45.12%] [G loss: 0.698678]
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6440 [D loss: 0.697560, acc.: 48.24%] [G loss: 0.711552]
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6441 [D loss: 0.696884, acc.: 50.59%] [G loss: 0.724758]
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6442 [D loss: 0.689730, acc.: 52.54%] [G loss: 0.736763]
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6443 [D loss: 0.691643, acc.: 50.00%] [G loss: 0.724352]
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6444 [D loss: 0.691186, acc.: 49.80%] [G loss: 0.719060]
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6445 [D loss: 0.696371, acc.: 48.24%] [G loss: 0.720402]
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6446 [D loss: 0.696688, acc.: 51.56%] [G loss: 0.711181]
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6447 [D loss: 0.693161, acc.: 49.61%] [G loss: 0.711227]
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6448 [D loss: 0.696009, acc.: 48.05%] [G loss: 0.709212]
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6449 [D loss: 0.694611, acc.: 48.24%] [G loss: 0.691416]
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6450 [D loss: 0.698005, acc.: 44.73%] [G loss: 0.696778]
1/1 [==============================] - 0s 19ms/step
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6451 [D loss: 0.697234, acc.: 46.68%] [G loss: 0.696370]
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6452 [D loss: 0.699261, acc.: 45.90%] [G loss: 0.709308]
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6453 [D loss: 0.694955, acc.: 49.22%] [G loss: 0.707983]
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6454 [D loss: 0.694895, acc.: 49.80%] [G loss: 0.712259]
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6455 [D loss: 0.692087, acc.: 51.17%] [G loss: 0.731878]
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6456 [D loss: 0.690139, acc.: 52.15%] [G loss: 0.726314]
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6457 [D loss: 0.698539, acc.: 49.02%] [G loss: 0.718878]
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6458 [D loss: 0.696514, acc.: 48.24%] [G loss: 0.726162]
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6459 [D loss: 0.698027, acc.: 48.05%] [G loss: 0.722240]
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6460 [D loss: 0.695691, acc.: 46.29%] [G loss: 0.721661]
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6461 [D loss: 0.690546, acc.: 52.34%] [G loss: 0.715191]
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6462 [D loss: 0.693514, acc.: 52.93%] [G loss: 0.718197]
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6463 [D loss: 0.690274, acc.: 51.37%] [G loss: 0.704474]
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6464 [D loss: 0.693182, acc.: 48.83%] [G loss: 0.706259]
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6465 [D loss: 0.694209, acc.: 46.88%] [G loss: 0.707921]
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6466 [D loss: 0.691195, acc.: 50.20%] [G loss: 0.706645]
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6467 [D loss: 0.683507, acc.: 51.37%] [G loss: 0.707684]
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6468 [D loss: 0.692556, acc.: 49.02%] [G loss: 0.716970]
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6469 [D loss: 0.691581, acc.: 50.39%] [G loss: 0.716364]
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6470 [D loss: 0.690638, acc.: 51.76%] [G loss: 0.723556]
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6471 [D loss: 0.693257, acc.: 50.98%] [G loss: 0.732586]
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6472 [D loss: 0.696316, acc.: 47.85%] [G loss: 0.720009]
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6473 [D loss: 0.693061, acc.: 50.98%] [G loss: 0.719518]
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6474 [D loss: 0.689867, acc.: 51.56%] [G loss: 0.721102]
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6475 [D loss: 0.689025, acc.: 54.88%] [G loss: 0.719638]
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6476 [D loss: 0.688462, acc.: 52.34%] [G loss: 0.719745]
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6477 [D loss: 0.688695, acc.: 55.47%] [G loss: 0.713012]
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6478 [D loss: 0.689568, acc.: 52.54%] [G loss: 0.712354]
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6479 [D loss: 0.692934, acc.: 49.22%] [G loss: 0.704923]
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6480 [D loss: 0.694788, acc.: 45.70%] [G loss: 0.703160]
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6481 [D loss: 0.698892, acc.: 46.48%] [G loss: 0.709382]
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6482 [D loss: 0.695283, acc.: 49.02%] [G loss: 0.714865]
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6483 [D loss: 0.687169, acc.: 52.34%] [G loss: 0.722274]
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6484 [D loss: 0.689936, acc.: 50.39%] [G loss: 0.732669]
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6485 [D loss: 0.687170, acc.: 54.69%] [G loss: 0.735936]
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6486 [D loss: 0.697519, acc.: 48.83%] [G loss: 0.735612]
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6487 [D loss: 0.690865, acc.: 50.39%] [G loss: 0.737876]
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6488 [D loss: 0.695366, acc.: 46.68%] [G loss: 0.727753]
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6489 [D loss: 0.694292, acc.: 50.98%] [G loss: 0.720848]
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6490 [D loss: 0.696442, acc.: 50.20%] [G loss: 0.714930]
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6491 [D loss: 0.698455, acc.: 46.68%] [G loss: 0.701489]
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6492 [D loss: 0.700560, acc.: 50.39%] [G loss: 0.692443]
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6493 [D loss: 0.701618, acc.: 46.88%] [G loss: 0.697294]
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6494 [D loss: 0.701644, acc.: 45.51%] [G loss: 0.695386]
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6495 [D loss: 0.696347, acc.: 50.20%] [G loss: 0.715024]
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6496 [D loss: 0.691468, acc.: 51.95%] [G loss: 0.713822]
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6497 [D loss: 0.690377, acc.: 53.12%] [G loss: 0.713405]
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6498 [D loss: 0.688467, acc.: 53.91%] [G loss: 0.723663]
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6499 [D loss: 0.684471, acc.: 56.84%] [G loss: 0.724998]
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6500 [D loss: 0.688110, acc.: 54.49%] [G loss: 0.710023]
1/1 [==============================] - 0s 22ms/step
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6501 [D loss: 0.694658, acc.: 48.63%] [G loss: 0.714438]
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6502 [D loss: 0.694498, acc.: 51.17%] [G loss: 0.711734]
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6503 [D loss: 0.691728, acc.: 52.73%] [G loss: 0.701545]
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6504 [D loss: 0.693875, acc.: 51.37%] [G loss: 0.701164]
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6505 [D loss: 0.696246, acc.: 46.88%] [G loss: 0.696603]
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6506 [D loss: 0.696771, acc.: 48.24%] [G loss: 0.703035]
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6507 [D loss: 0.699834, acc.: 46.48%] [G loss: 0.700300]
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6508 [D loss: 0.696974, acc.: 48.05%] [G loss: 0.713404]
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6509 [D loss: 0.697205, acc.: 47.66%] [G loss: 0.710919]
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6510 [D loss: 0.693332, acc.: 49.22%] [G loss: 0.719099]
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6511 [D loss: 0.696685, acc.: 48.05%] [G loss: 0.717149]
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6512 [D loss: 0.691205, acc.: 52.54%] [G loss: 0.719354]
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6513 [D loss: 0.690304, acc.: 54.49%] [G loss: 0.720836]
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6514 [D loss: 0.692941, acc.: 50.78%] [G loss: 0.720674]
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6515 [D loss: 0.693719, acc.: 49.61%] [G loss: 0.717808]
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6516 [D loss: 0.692516, acc.: 49.02%] [G loss: 0.710803]
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6517 [D loss: 0.690069, acc.: 50.98%] [G loss: 0.715753]
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6518 [D loss: 0.687848, acc.: 56.25%] [G loss: 0.710317]
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6519 [D loss: 0.690779, acc.: 55.27%] [G loss: 0.702397]
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6520 [D loss: 0.695060, acc.: 48.63%] [G loss: 0.697698]
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6521 [D loss: 0.695204, acc.: 45.70%] [G loss: 0.698379]
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6522 [D loss: 0.695825, acc.: 49.02%] [G loss: 0.694260]
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6523 [D loss: 0.695496, acc.: 44.73%] [G loss: 0.701866]
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6524 [D loss: 0.696892, acc.: 47.46%] [G loss: 0.707918]
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6525 [D loss: 0.697692, acc.: 45.51%] [G loss: 0.724743]
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6526 [D loss: 0.690526, acc.: 51.95%] [G loss: 0.725036]
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6527 [D loss: 0.688514, acc.: 53.32%] [G loss: 0.729973]
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6528 [D loss: 0.691311, acc.: 50.20%] [G loss: 0.730713]
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6529 [D loss: 0.693603, acc.: 48.63%] [G loss: 0.732416]
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6530 [D loss: 0.695033, acc.: 50.20%] [G loss: 0.730997]
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6531 [D loss: 0.692785, acc.: 47.85%] [G loss: 0.719225]
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6532 [D loss: 0.691564, acc.: 46.88%] [G loss: 0.713570]
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6533 [D loss: 0.695676, acc.: 49.02%] [G loss: 0.711087]
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6534 [D loss: 0.696331, acc.: 45.12%] [G loss: 0.702705]
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6535 [D loss: 0.698234, acc.: 44.53%] [G loss: 0.698975]
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6536 [D loss: 0.699125, acc.: 45.51%] [G loss: 0.686138]
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6537 [D loss: 0.695490, acc.: 48.24%] [G loss: 0.699135]
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6538 [D loss: 0.702733, acc.: 44.53%] [G loss: 0.710127]
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6539 [D loss: 0.691578, acc.: 50.78%] [G loss: 0.719852]
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6540 [D loss: 0.690489, acc.: 50.39%] [G loss: 0.726189]
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6541 [D loss: 0.686888, acc.: 52.73%] [G loss: 0.729249]
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6542 [D loss: 0.690004, acc.: 49.41%] [G loss: 0.730326]
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6543 [D loss: 0.691173, acc.: 51.37%] [G loss: 0.730316]
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6544 [D loss: 0.695460, acc.: 49.02%] [G loss: 0.723489]
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6545 [D loss: 0.694808, acc.: 50.20%] [G loss: 0.724869]
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6546 [D loss: 0.692617, acc.: 51.17%] [G loss: 0.722062]
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6547 [D loss: 0.692565, acc.: 50.20%] [G loss: 0.713477]
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6548 [D loss: 0.693163, acc.: 46.48%] [G loss: 0.715463]
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6549 [D loss: 0.690844, acc.: 50.00%] [G loss: 0.713439]
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6550 [D loss: 0.688540, acc.: 52.34%] [G loss: 0.707333]
1/1 [==============================] - 0s 17ms/step
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6551 [D loss: 0.693280, acc.: 49.80%] [G loss: 0.705989]
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6552 [D loss: 0.701831, acc.: 41.80%] [G loss: 0.704447]
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6553 [D loss: 0.692944, acc.: 48.24%] [G loss: 0.712141]
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6554 [D loss: 0.686234, acc.: 51.95%] [G loss: 0.717143]
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6555 [D loss: 0.684026, acc.: 53.52%] [G loss: 0.727749]
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6556 [D loss: 0.684176, acc.: 54.10%] [G loss: 0.727817]
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6557 [D loss: 0.689432, acc.: 51.37%] [G loss: 0.734399]
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6558 [D loss: 0.693702, acc.: 51.37%] [G loss: 0.725914]
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6559 [D loss: 0.688955, acc.: 52.34%] [G loss: 0.716097]
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6560 [D loss: 0.691498, acc.: 48.63%] [G loss: 0.724248]
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6561 [D loss: 0.690320, acc.: 51.76%] [G loss: 0.718015]
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6562 [D loss: 0.692756, acc.: 50.39%] [G loss: 0.720775]
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6563 [D loss: 0.689379, acc.: 51.76%] [G loss: 0.712406]
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6564 [D loss: 0.688623, acc.: 50.20%] [G loss: 0.716316]
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6565 [D loss: 0.690622, acc.: 49.80%] [G loss: 0.711855]
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6566 [D loss: 0.689027, acc.: 51.17%] [G loss: 0.718104]
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6567 [D loss: 0.695359, acc.: 46.48%] [G loss: 0.726225]
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6568 [D loss: 0.691082, acc.: 51.37%] [G loss: 0.725588]
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6569 [D loss: 0.689464, acc.: 46.88%] [G loss: 0.729945]
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6570 [D loss: 0.685769, acc.: 50.00%] [G loss: 0.726180]
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6571 [D loss: 0.686403, acc.: 50.20%] [G loss: 0.722905]
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6572 [D loss: 0.685098, acc.: 47.85%] [G loss: 0.720761]
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6573 [D loss: 0.688649, acc.: 50.39%] [G loss: 0.717637]
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6574 [D loss: 0.687893, acc.: 52.73%] [G loss: 0.712305]
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6575 [D loss: 0.686884, acc.: 45.70%] [G loss: 0.709024]
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6576 [D loss: 0.695504, acc.: 47.66%] [G loss: 0.710722]
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6577 [D loss: 0.688405, acc.: 51.95%] [G loss: 0.705160]
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6578 [D loss: 0.694942, acc.: 47.66%] [G loss: 0.705112]
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6579 [D loss: 0.689294, acc.: 48.44%] [G loss: 0.711370]
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6580 [D loss: 0.690692, acc.: 49.61%] [G loss: 0.706048]
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6581 [D loss: 0.690570, acc.: 47.85%] [G loss: 0.710191]
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6582 [D loss: 0.682579, acc.: 53.71%] [G loss: 0.718642]
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6583 [D loss: 0.685899, acc.: 51.95%] [G loss: 0.724021]
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6584 [D loss: 0.686140, acc.: 49.80%] [G loss: 0.724260]
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6585 [D loss: 0.687685, acc.: 50.98%] [G loss: 0.723872]
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6586 [D loss: 0.683892, acc.: 52.73%] [G loss: 0.721454]
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6587 [D loss: 0.686486, acc.: 51.56%] [G loss: 0.726363]
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6588 [D loss: 0.687315, acc.: 48.63%] [G loss: 0.722223]
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6589 [D loss: 0.682975, acc.: 55.08%] [G loss: 0.726990]
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6590 [D loss: 0.687528, acc.: 49.61%] [G loss: 0.717941]
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6591 [D loss: 0.692160, acc.: 50.00%] [G loss: 0.717469]
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6592 [D loss: 0.689412, acc.: 48.83%] [G loss: 0.721312]
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6593 [D loss: 0.688563, acc.: 50.98%] [G loss: 0.722371]
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6594 [D loss: 0.690801, acc.: 49.41%] [G loss: 0.716784]
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6595 [D loss: 0.685234, acc.: 48.44%] [G loss: 0.725377]
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6596 [D loss: 0.692889, acc.: 49.02%] [G loss: 0.721882]
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6597 [D loss: 0.688837, acc.: 48.63%] [G loss: 0.726733]
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6598 [D loss: 0.691678, acc.: 48.05%] [G loss: 0.730229]
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6599 [D loss: 0.689167, acc.: 49.02%] [G loss: 0.732739]
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6600 [D loss: 0.685162, acc.: 51.17%] [G loss: 0.729312]
1/1 [==============================] - 0s 17ms/step
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6601 [D loss: 0.680324, acc.: 50.78%] [G loss: 0.734864]
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6602 [D loss: 0.692748, acc.: 49.61%] [G loss: 0.727328]
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6603 [D loss: 0.684551, acc.: 50.20%] [G loss: 0.721978]
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6604 [D loss: 0.691375, acc.: 49.02%] [G loss: 0.722270]
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6605 [D loss: 0.693709, acc.: 44.14%] [G loss: 0.715800]
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6606 [D loss: 0.691204, acc.: 48.24%] [G loss: 0.717036]
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6607 [D loss: 0.694125, acc.: 47.46%] [G loss: 0.720052]
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6608 [D loss: 0.689351, acc.: 49.02%] [G loss: 0.715155]
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6609 [D loss: 0.690297, acc.: 47.66%] [G loss: 0.714619]
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6610 [D loss: 0.686571, acc.: 48.83%] [G loss: 0.714664]
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6611 [D loss: 0.686334, acc.: 52.54%] [G loss: 0.718407]
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6612 [D loss: 0.689452, acc.: 51.37%] [G loss: 0.717956]
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6613 [D loss: 0.693591, acc.: 50.20%] [G loss: 0.725940]
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6614 [D loss: 0.682080, acc.: 50.78%] [G loss: 0.731862]
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6615 [D loss: 0.711841, acc.: 46.68%] [G loss: 0.709719]
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6616 [D loss: 0.715410, acc.: 46.09%] [G loss: 0.707390]
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6617 [D loss: 0.703860, acc.: 51.56%] [G loss: 0.698846]
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6618 [D loss: 0.699197, acc.: 48.24%] [G loss: 0.700014]
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6619 [D loss: 0.699297, acc.: 44.14%] [G loss: 0.710972]
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6620 [D loss: 0.698569, acc.: 45.51%] [G loss: 0.714588]
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6621 [D loss: 0.693798, acc.: 47.07%] [G loss: 0.720484]
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6622 [D loss: 0.696656, acc.: 48.63%] [G loss: 0.717693]
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6623 [D loss: 0.695874, acc.: 48.63%] [G loss: 0.725431]
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6624 [D loss: 0.696039, acc.: 45.90%] [G loss: 0.720695]
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6625 [D loss: 0.691965, acc.: 49.80%] [G loss: 0.717279]
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6626 [D loss: 0.692947, acc.: 50.00%] [G loss: 0.710365]
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6627 [D loss: 0.697949, acc.: 44.73%] [G loss: 0.710147]
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6628 [D loss: 0.689651, acc.: 50.39%] [G loss: 0.716853]
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6629 [D loss: 0.698631, acc.: 45.90%] [G loss: 0.709695]
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6630 [D loss: 0.696144, acc.: 45.12%] [G loss: 0.710298]
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6631 [D loss: 0.698021, acc.: 44.53%] [G loss: 0.711545]
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6632 [D loss: 0.697904, acc.: 46.48%] [G loss: 0.716366]
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6633 [D loss: 0.695130, acc.: 47.27%] [G loss: 0.711046]
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6634 [D loss: 0.694449, acc.: 49.22%] [G loss: 0.711701]
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6635 [D loss: 0.690606, acc.: 53.32%] [G loss: 0.720797]
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6636 [D loss: 0.692850, acc.: 50.78%] [G loss: 0.713424]
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6637 [D loss: 0.694048, acc.: 47.07%] [G loss: 0.708105]
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6638 [D loss: 0.694443, acc.: 49.02%] [G loss: 0.711804]
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6639 [D loss: 0.695922, acc.: 47.07%] [G loss: 0.715976]
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6640 [D loss: 0.688592, acc.: 56.25%] [G loss: 0.708006]
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6641 [D loss: 0.697359, acc.: 44.53%] [G loss: 0.718579]
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6642 [D loss: 0.692452, acc.: 50.00%] [G loss: 0.718434]
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6643 [D loss: 0.694966, acc.: 48.44%] [G loss: 0.719737]
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6644 [D loss: 0.686545, acc.: 53.32%] [G loss: 0.724243]
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6645 [D loss: 0.696084, acc.: 49.22%] [G loss: 0.728850]
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6646 [D loss: 0.696502, acc.: 50.59%] [G loss: 0.726312]
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6647 [D loss: 0.690780, acc.: 53.12%] [G loss: 0.717073]
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6648 [D loss: 0.693239, acc.: 49.02%] [G loss: 0.721654]
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6649 [D loss: 0.693158, acc.: 49.80%] [G loss: 0.717835]
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6650 [D loss: 0.695833, acc.: 48.63%] [G loss: 0.719604]
1/1 [==============================] - 0s 18ms/step
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6651 [D loss: 0.691389, acc.: 53.52%] [G loss: 0.711877]
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6652 [D loss: 0.693677, acc.: 51.17%] [G loss: 0.709948]
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6653 [D loss: 0.696421, acc.: 46.48%] [G loss: 0.704263]
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6654 [D loss: 0.694893, acc.: 48.63%] [G loss: 0.698299]
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6655 [D loss: 0.696460, acc.: 46.88%] [G loss: 0.694138]
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6656 [D loss: 0.698997, acc.: 42.77%] [G loss: 0.704218]
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6657 [D loss: 0.698560, acc.: 46.29%] [G loss: 0.698984]
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6658 [D loss: 0.697191, acc.: 44.73%] [G loss: 0.700913]
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6659 [D loss: 0.693267, acc.: 49.41%] [G loss: 0.707137]
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6660 [D loss: 0.692844, acc.: 46.88%] [G loss: 0.722191]
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6661 [D loss: 0.690602, acc.: 48.44%] [G loss: 0.719645]
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6662 [D loss: 0.693200, acc.: 49.61%] [G loss: 0.718681]
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6663 [D loss: 0.698728, acc.: 47.85%] [G loss: 0.724159]
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6664 [D loss: 0.693248, acc.: 51.76%] [G loss: 0.718820]
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6665 [D loss: 0.692136, acc.: 51.37%] [G loss: 0.717166]
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6666 [D loss: 0.694217, acc.: 48.63%] [G loss: 0.719937]
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6667 [D loss: 0.690666, acc.: 52.93%] [G loss: 0.719352]
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6668 [D loss: 0.692556, acc.: 50.20%] [G loss: 0.715919]
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6669 [D loss: 0.689517, acc.: 51.37%] [G loss: 0.717712]
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6670 [D loss: 0.693617, acc.: 51.95%] [G loss: 0.719463]
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6671 [D loss: 0.694194, acc.: 45.31%] [G loss: 0.711171]
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6672 [D loss: 0.690362, acc.: 50.39%] [G loss: 0.720538]
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6673 [D loss: 0.685711, acc.: 53.71%] [G loss: 0.729524]
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6674 [D loss: 0.687513, acc.: 51.37%] [G loss: 0.724745]
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6675 [D loss: 0.687256, acc.: 53.12%] [G loss: 0.744457]
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6676 [D loss: 0.687437, acc.: 55.08%] [G loss: 0.742655]
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6677 [D loss: 0.689087, acc.: 53.12%] [G loss: 0.743155]
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6678 [D loss: 0.691658, acc.: 51.56%] [G loss: 0.739314]
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6679 [D loss: 0.693600, acc.: 50.00%] [G loss: 0.735736]
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6680 [D loss: 0.695413, acc.: 47.66%] [G loss: 0.733541]
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6681 [D loss: 0.695143, acc.: 51.17%] [G loss: 0.725434]
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6682 [D loss: 0.693796, acc.: 52.15%] [G loss: 0.725919]
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6683 [D loss: 0.694069, acc.: 48.05%] [G loss: 0.719146]
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6684 [D loss: 0.691929, acc.: 46.68%] [G loss: 0.712665]
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6685 [D loss: 0.693713, acc.: 49.02%] [G loss: 0.708796]
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6686 [D loss: 0.691612, acc.: 50.00%] [G loss: 0.704793]
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6687 [D loss: 0.688232, acc.: 52.34%] [G loss: 0.709215]
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6688 [D loss: 0.693750, acc.: 47.85%] [G loss: 0.709731]
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6689 [D loss: 0.690329, acc.: 50.98%] [G loss: 0.712502]
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6690 [D loss: 0.702368, acc.: 45.12%] [G loss: 0.707296]
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6691 [D loss: 0.700442, acc.: 47.27%] [G loss: 0.724088]
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6692 [D loss: 0.693523, acc.: 47.27%] [G loss: 0.714794]
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6693 [D loss: 0.693594, acc.: 47.27%] [G loss: 0.712646]
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6694 [D loss: 0.696204, acc.: 45.90%] [G loss: 0.710710]
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6695 [D loss: 0.695260, acc.: 47.66%] [G loss: 0.713122]
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6696 [D loss: 0.692816, acc.: 52.34%] [G loss: 0.713253]
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6697 [D loss: 0.691649, acc.: 49.02%] [G loss: 0.710417]
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6698 [D loss: 0.693307, acc.: 49.22%] [G loss: 0.709285]
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6699 [D loss: 0.693325, acc.: 51.17%] [G loss: 0.713766]
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6700 [D loss: 0.695667, acc.: 48.24%] [G loss: 0.718940]
1/1 [==============================] - 0s 19ms/step
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6701 [D loss: 0.694568, acc.: 49.22%] [G loss: 0.710438]
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6702 [D loss: 0.693989, acc.: 48.63%] [G loss: 0.711906]
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6703 [D loss: 0.697843, acc.: 49.02%] [G loss: 0.710405]
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6704 [D loss: 0.694934, acc.: 49.61%] [G loss: 0.717667]
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6705 [D loss: 0.698618, acc.: 50.78%] [G loss: 0.714210]
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6706 [D loss: 0.693304, acc.: 53.32%] [G loss: 0.718532]
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6707 [D loss: 0.694570, acc.: 50.00%] [G loss: 0.717137]
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6708 [D loss: 0.691860, acc.: 50.59%] [G loss: 0.714910]
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6709 [D loss: 0.691649, acc.: 53.91%] [G loss: 0.712901]
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6710 [D loss: 0.691665, acc.: 53.32%] [G loss: 0.715334]
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6711 [D loss: 0.691714, acc.: 53.12%] [G loss: 0.707022]
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6712 [D loss: 0.693254, acc.: 50.39%] [G loss: 0.706264]
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6713 [D loss: 0.695933, acc.: 47.46%] [G loss: 0.700942]
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6714 [D loss: 0.697387, acc.: 45.51%] [G loss: 0.701262]
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6715 [D loss: 0.691529, acc.: 50.00%] [G loss: 0.709480]
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6716 [D loss: 0.697117, acc.: 46.09%] [G loss: 0.710173]
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6717 [D loss: 0.696591, acc.: 48.44%] [G loss: 0.712283]
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6718 [D loss: 0.697756, acc.: 47.07%] [G loss: 0.715520]
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6719 [D loss: 0.693409, acc.: 47.66%] [G loss: 0.718283]
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6720 [D loss: 0.692079, acc.: 51.37%] [G loss: 0.718769]
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6721 [D loss: 0.690606, acc.: 49.80%] [G loss: 0.719577]
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6722 [D loss: 0.692715, acc.: 49.22%] [G loss: 0.719556]
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6723 [D loss: 0.689930, acc.: 56.45%] [G loss: 0.717372]
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6724 [D loss: 0.693328, acc.: 48.63%] [G loss: 0.725577]
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6725 [D loss: 0.690716, acc.: 50.78%] [G loss: 0.716808]
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6726 [D loss: 0.693593, acc.: 49.80%] [G loss: 0.716785]
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6727 [D loss: 0.691987, acc.: 52.54%] [G loss: 0.710385]
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6728 [D loss: 0.691743, acc.: 51.76%] [G loss: 0.718319]
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6729 [D loss: 0.687103, acc.: 57.03%] [G loss: 0.716366]
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6730 [D loss: 0.689517, acc.: 51.17%] [G loss: 0.717451]
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6731 [D loss: 0.690217, acc.: 50.59%] [G loss: 0.718300]
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6732 [D loss: 0.697224, acc.: 45.70%] [G loss: 0.713099]
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6733 [D loss: 0.689338, acc.: 50.59%] [G loss: 0.718857]
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6734 [D loss: 0.696054, acc.: 44.53%] [G loss: 0.715069]
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6735 [D loss: 0.687766, acc.: 48.63%] [G loss: 0.720993]
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6736 [D loss: 0.686867, acc.: 49.61%] [G loss: 0.725566]
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6737 [D loss: 0.696701, acc.: 47.07%] [G loss: 0.729032]
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6738 [D loss: 0.691558, acc.: 47.85%] [G loss: 0.727275]
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6739 [D loss: 0.690293, acc.: 50.59%] [G loss: 0.724447]
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6740 [D loss: 0.695401, acc.: 46.68%] [G loss: 0.719602]
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6741 [D loss: 0.693461, acc.: 45.90%] [G loss: 0.722151]
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6742 [D loss: 0.695464, acc.: 47.85%] [G loss: 0.719286]
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6743 [D loss: 0.691246, acc.: 48.24%] [G loss: 0.714652]
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6744 [D loss: 0.695060, acc.: 46.29%] [G loss: 0.717851]
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6745 [D loss: 0.695390, acc.: 47.85%] [G loss: 0.714121]
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6746 [D loss: 0.697816, acc.: 45.90%] [G loss: 0.712922]
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6747 [D loss: 0.691984, acc.: 53.71%] [G loss: 0.711278]
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6748 [D loss: 0.692781, acc.: 50.20%] [G loss: 0.712318]
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6749 [D loss: 0.694142, acc.: 49.61%] [G loss: 0.709655]
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6750 [D loss: 0.693848, acc.: 49.80%] [G loss: 0.706286]
1/1 [==============================] - 0s 19ms/step
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6751 [D loss: 0.697656, acc.: 47.46%] [G loss: 0.707595]
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6752 [D loss: 0.700934, acc.: 43.55%] [G loss: 0.708938]
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6753 [D loss: 0.700329, acc.: 44.34%] [G loss: 0.706493]
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6754 [D loss: 0.696284, acc.: 49.41%] [G loss: 0.705780]
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6755 [D loss: 0.695676, acc.: 49.41%] [G loss: 0.709864]
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6756 [D loss: 0.692501, acc.: 47.85%] [G loss: 0.715991]
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6757 [D loss: 0.694000, acc.: 50.39%] [G loss: 0.715485]
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6758 [D loss: 0.689310, acc.: 52.15%] [G loss: 0.721836]
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6759 [D loss: 0.690607, acc.: 51.56%] [G loss: 0.729681]
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6760 [D loss: 0.688664, acc.: 53.32%] [G loss: 0.714179]
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6761 [D loss: 0.693356, acc.: 48.83%] [G loss: 0.721622]
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6762 [D loss: 0.687570, acc.: 52.15%] [G loss: 0.721690]
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6763 [D loss: 0.691255, acc.: 51.17%] [G loss: 0.707810]
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6764 [D loss: 0.694475, acc.: 47.27%] [G loss: 0.711148]
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6765 [D loss: 0.696622, acc.: 44.14%] [G loss: 0.703375]
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6766 [D loss: 0.696430, acc.: 49.22%] [G loss: 0.702288]
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6767 [D loss: 0.698427, acc.: 45.31%] [G loss: 0.699059]
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6768 [D loss: 0.694924, acc.: 51.17%] [G loss: 0.702928]
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6769 [D loss: 0.693699, acc.: 48.44%] [G loss: 0.713172]
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6770 [D loss: 0.696260, acc.: 49.02%] [G loss: 0.712021]
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6771 [D loss: 0.694504, acc.: 47.07%] [G loss: 0.715014]
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6772 [D loss: 0.693708, acc.: 50.78%] [G loss: 0.714347]
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6773 [D loss: 0.691760, acc.: 48.05%] [G loss: 0.723538]
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6774 [D loss: 0.693851, acc.: 47.85%] [G loss: 0.721071]
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6775 [D loss: 0.693839, acc.: 48.44%] [G loss: 0.718452]
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6776 [D loss: 0.690648, acc.: 48.63%] [G loss: 0.716517]
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6777 [D loss: 0.690831, acc.: 49.41%] [G loss: 0.717239]
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6778 [D loss: 0.692073, acc.: 51.95%] [G loss: 0.713200]
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6779 [D loss: 0.690373, acc.: 48.24%] [G loss: 0.714600]
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6780 [D loss: 0.691267, acc.: 48.44%] [G loss: 0.718063]
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6781 [D loss: 0.687901, acc.: 50.00%] [G loss: 0.720616]
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6782 [D loss: 0.688790, acc.: 52.73%] [G loss: 0.719252]
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6783 [D loss: 0.691149, acc.: 49.02%] [G loss: 0.721142]
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6784 [D loss: 0.688034, acc.: 51.76%] [G loss: 0.725044]
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6785 [D loss: 0.686179, acc.: 52.15%] [G loss: 0.728339]
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6786 [D loss: 0.689739, acc.: 51.37%] [G loss: 0.723061]
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6787 [D loss: 0.689415, acc.: 49.41%] [G loss: 0.715213]
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6788 [D loss: 0.692258, acc.: 52.54%] [G loss: 0.705844]
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6789 [D loss: 0.696586, acc.: 48.44%] [G loss: 0.709830]
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6790 [D loss: 0.696137, acc.: 49.61%] [G loss: 0.701571]
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6791 [D loss: 0.694183, acc.: 49.41%] [G loss: 0.712020]
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6792 [D loss: 0.692631, acc.: 47.07%] [G loss: 0.715710]
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6793 [D loss: 0.689506, acc.: 50.98%] [G loss: 0.720483]
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6794 [D loss: 0.696971, acc.: 45.31%] [G loss: 0.714736]
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6795 [D loss: 0.698461, acc.: 44.92%] [G loss: 0.720174]
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6796 [D loss: 0.693568, acc.: 50.20%] [G loss: 0.718490]
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6797 [D loss: 0.697844, acc.: 44.73%] [G loss: 0.713467]
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6798 [D loss: 0.698307, acc.: 44.92%] [G loss: 0.718655]
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6799 [D loss: 0.690370, acc.: 53.71%] [G loss: 0.724159]
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6800 [D loss: 0.695608, acc.: 46.48%] [G loss: 0.726127]
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6801 [D loss: 0.688158, acc.: 55.66%] [G loss: 0.719117]
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6802 [D loss: 0.691860, acc.: 50.59%] [G loss: 0.723275]
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6803 [D loss: 0.689591, acc.: 51.17%] [G loss: 0.720388]
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6804 [D loss: 0.688477, acc.: 52.15%] [G loss: 0.723782]
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6805 [D loss: 0.693473, acc.: 49.02%] [G loss: 0.713591]
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6806 [D loss: 0.694925, acc.: 48.44%] [G loss: 0.709682]
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6807 [D loss: 0.694201, acc.: 49.61%] [G loss: 0.705844]
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6808 [D loss: 0.692671, acc.: 48.83%] [G loss: 0.704529]
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6809 [D loss: 0.695736, acc.: 49.80%] [G loss: 0.709221]
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6810 [D loss: 0.697481, acc.: 46.68%] [G loss: 0.713534]
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6811 [D loss: 0.692266, acc.: 52.15%] [G loss: 0.709983]
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6812 [D loss: 0.690139, acc.: 51.37%] [G loss: 0.712715]
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6813 [D loss: 0.694755, acc.: 53.32%] [G loss: 0.718204]
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6814 [D loss: 0.690031, acc.: 50.59%] [G loss: 0.720742]
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6815 [D loss: 0.690183, acc.: 52.54%] [G loss: 0.720570]
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6816 [D loss: 0.692826, acc.: 51.56%] [G loss: 0.731085]
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6817 [D loss: 0.692544, acc.: 50.59%] [G loss: 0.731925]
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6818 [D loss: 0.694007, acc.: 47.85%] [G loss: 0.715068]
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6819 [D loss: 0.693409, acc.: 49.02%] [G loss: 0.715994]
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6820 [D loss: 0.697841, acc.: 46.29%] [G loss: 0.704440]
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6821 [D loss: 0.698944, acc.: 46.29%] [G loss: 0.714312]
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6822 [D loss: 0.695557, acc.: 46.29%] [G loss: 0.718397]
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6823 [D loss: 0.696651, acc.: 48.24%] [G loss: 0.710173]
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6824 [D loss: 0.691912, acc.: 52.54%] [G loss: 0.725059]
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6825 [D loss: 0.691221, acc.: 50.39%] [G loss: 0.730680]
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6826 [D loss: 0.696691, acc.: 45.70%] [G loss: 0.720107]
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6827 [D loss: 0.694425, acc.: 45.51%] [G loss: 0.731787]
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6828 [D loss: 0.696291, acc.: 48.63%] [G loss: 0.734922]
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6829 [D loss: 0.698639, acc.: 45.70%] [G loss: 0.721012]
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6830 [D loss: 0.694172, acc.: 50.00%] [G loss: 0.721913]
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6831 [D loss: 0.696232, acc.: 48.63%] [G loss: 0.713693]
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6832 [D loss: 0.699221, acc.: 45.51%] [G loss: 0.706621]
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6833 [D loss: 0.700377, acc.: 43.36%] [G loss: 0.713830]
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6834 [D loss: 0.695495, acc.: 48.63%] [G loss: 0.714587]
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6835 [D loss: 0.697767, acc.: 45.31%] [G loss: 0.712968]
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6836 [D loss: 0.690658, acc.: 49.02%] [G loss: 0.712308]
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6837 [D loss: 0.689289, acc.: 52.73%] [G loss: 0.710207]
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6838 [D loss: 0.690166, acc.: 49.02%] [G loss: 0.711531]
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6839 [D loss: 0.691341, acc.: 51.56%] [G loss: 0.705487]
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6840 [D loss: 0.695356, acc.: 46.29%] [G loss: 0.708690]
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6841 [D loss: 0.696368, acc.: 45.31%] [G loss: 0.705127]
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6842 [D loss: 0.685897, acc.: 55.47%] [G loss: 0.711248]
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6843 [D loss: 0.697471, acc.: 44.73%] [G loss: 0.718653]
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6844 [D loss: 0.693707, acc.: 51.56%] [G loss: 0.712031]
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6845 [D loss: 0.689859, acc.: 52.54%] [G loss: 0.701219]
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6846 [D loss: 0.689390, acc.: 53.52%] [G loss: 0.716332]
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6847 [D loss: 0.696127, acc.: 50.00%] [G loss: 0.718546]
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6848 [D loss: 0.697675, acc.: 49.22%] [G loss: 0.723988]
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6849 [D loss: 0.693174, acc.: 49.02%] [G loss: 0.723722]
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6850 [D loss: 0.690019, acc.: 54.30%] [G loss: 0.729439]
1/1 [==============================] - 0s 20ms/step
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6851 [D loss: 0.687754, acc.: 55.47%] [G loss: 0.719338]
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6852 [D loss: 0.686915, acc.: 53.12%] [G loss: 0.722907]
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6853 [D loss: 0.688178, acc.: 50.98%] [G loss: 0.736545]
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6854 [D loss: 0.696125, acc.: 45.12%] [G loss: 0.719721]
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6855 [D loss: 0.697807, acc.: 47.07%] [G loss: 0.719712]
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6856 [D loss: 0.692628, acc.: 49.61%] [G loss: 0.714922]
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6857 [D loss: 0.690003, acc.: 50.39%] [G loss: 0.714118]
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6858 [D loss: 0.693716, acc.: 47.07%] [G loss: 0.711653]
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6859 [D loss: 0.703402, acc.: 41.99%] [G loss: 0.714104]
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6860 [D loss: 0.699578, acc.: 46.68%] [G loss: 0.714578]
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6861 [D loss: 0.697260, acc.: 46.48%] [G loss: 0.718639]
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6862 [D loss: 0.695268, acc.: 48.05%] [G loss: 0.725227]
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6863 [D loss: 0.695402, acc.: 48.63%] [G loss: 0.729732]
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6864 [D loss: 0.693053, acc.: 48.63%] [G loss: 0.727606]
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6865 [D loss: 0.690111, acc.: 50.59%] [G loss: 0.730121]
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6866 [D loss: 0.695915, acc.: 48.63%] [G loss: 0.719800]
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6867 [D loss: 0.697599, acc.: 47.85%] [G loss: 0.718789]
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6868 [D loss: 0.697776, acc.: 44.73%] [G loss: 0.711401]
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6869 [D loss: 0.691020, acc.: 47.27%] [G loss: 0.718066]
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6870 [D loss: 0.690264, acc.: 49.80%] [G loss: 0.715589]
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6871 [D loss: 0.697149, acc.: 47.66%] [G loss: 0.716457]
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6872 [D loss: 0.691613, acc.: 52.34%] [G loss: 0.720150]
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6873 [D loss: 0.683861, acc.: 55.86%] [G loss: 0.727390]
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6874 [D loss: 0.684922, acc.: 55.08%] [G loss: 0.726156]
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6875 [D loss: 0.689040, acc.: 51.37%] [G loss: 0.733542]
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6876 [D loss: 0.693739, acc.: 47.27%] [G loss: 0.728504]
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6877 [D loss: 0.688240, acc.: 49.61%] [G loss: 0.726764]
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6878 [D loss: 0.683524, acc.: 52.15%] [G loss: 0.725589]
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6879 [D loss: 0.698319, acc.: 47.27%] [G loss: 0.717706]
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6880 [D loss: 0.693708, acc.: 50.00%] [G loss: 0.710956]
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6881 [D loss: 0.695827, acc.: 45.31%] [G loss: 0.715035]
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6882 [D loss: 0.694506, acc.: 48.24%] [G loss: 0.710078]
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6883 [D loss: 0.695107, acc.: 50.20%] [G loss: 0.717616]
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6884 [D loss: 0.691150, acc.: 51.17%] [G loss: 0.709555]
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6885 [D loss: 0.691332, acc.: 50.59%] [G loss: 0.700168]
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6886 [D loss: 0.693632, acc.: 49.61%] [G loss: 0.699462]
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6887 [D loss: 0.696450, acc.: 48.44%] [G loss: 0.696747]
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6888 [D loss: 0.701191, acc.: 46.68%] [G loss: 0.692415]
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6889 [D loss: 0.702292, acc.: 44.53%] [G loss: 0.699557]
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6890 [D loss: 0.697864, acc.: 45.90%] [G loss: 0.696279]
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6891 [D loss: 0.696335, acc.: 46.09%] [G loss: 0.711009]
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6892 [D loss: 0.694019, acc.: 47.27%] [G loss: 0.710842]
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6893 [D loss: 0.692092, acc.: 49.02%] [G loss: 0.723286]
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6894 [D loss: 0.694871, acc.: 50.59%] [G loss: 0.727350]
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6895 [D loss: 0.689522, acc.: 51.56%] [G loss: 0.726642]
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6896 [D loss: 0.689176, acc.: 52.73%] [G loss: 0.723308]
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6897 [D loss: 0.686053, acc.: 56.25%] [G loss: 0.728654]
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6898 [D loss: 0.685774, acc.: 56.64%] [G loss: 0.716920]
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6899 [D loss: 0.688114, acc.: 56.05%] [G loss: 0.713656]
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6900 [D loss: 0.688715, acc.: 51.95%] [G loss: 0.702844]
1/1 [==============================] - 0s 21ms/step
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6901 [D loss: 0.696735, acc.: 51.37%] [G loss: 0.702051]
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6902 [D loss: 0.692122, acc.: 49.61%] [G loss: 0.708316]
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6903 [D loss: 0.697269, acc.: 44.34%] [G loss: 0.722219]
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6904 [D loss: 0.696784, acc.: 44.73%] [G loss: 0.733496]
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6905 [D loss: 0.696311, acc.: 45.12%] [G loss: 0.735211]
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6906 [D loss: 0.696967, acc.: 45.31%] [G loss: 0.738878]
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6907 [D loss: 0.696011, acc.: 45.51%] [G loss: 0.729146]
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6908 [D loss: 0.699263, acc.: 45.70%] [G loss: 0.723872]
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6909 [D loss: 0.694069, acc.: 50.39%] [G loss: 0.724158]
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6910 [D loss: 0.692925, acc.: 51.37%] [G loss: 0.725640]
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6911 [D loss: 0.691211, acc.: 51.17%] [G loss: 0.714666]
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6912 [D loss: 0.691091, acc.: 47.85%] [G loss: 0.717093]
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6913 [D loss: 0.691315, acc.: 47.07%] [G loss: 0.700366]
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6914 [D loss: 0.693279, acc.: 49.41%] [G loss: 0.700468]
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6915 [D loss: 0.690364, acc.: 47.07%] [G loss: 0.717002]
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6916 [D loss: 0.684241, acc.: 51.17%] [G loss: 0.722037]
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6917 [D loss: 0.687566, acc.: 51.95%] [G loss: 0.727777]
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6918 [D loss: 0.691382, acc.: 50.39%] [G loss: 0.734958]
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6919 [D loss: 0.689921, acc.: 52.15%] [G loss: 0.726075]
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6920 [D loss: 0.685974, acc.: 53.91%] [G loss: 0.729097]
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6921 [D loss: 0.688712, acc.: 52.73%] [G loss: 0.728709]
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6922 [D loss: 0.689796, acc.: 48.83%] [G loss: 0.724432]
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6923 [D loss: 0.691530, acc.: 47.66%] [G loss: 0.715740]
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6924 [D loss: 0.694201, acc.: 46.88%] [G loss: 0.712689]
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6925 [D loss: 0.695083, acc.: 46.68%] [G loss: 0.709611]
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6926 [D loss: 0.702082, acc.: 43.95%] [G loss: 0.705404]
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6927 [D loss: 0.699680, acc.: 41.02%] [G loss: 0.704507]
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6928 [D loss: 0.703123, acc.: 42.77%] [G loss: 0.710001]
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6929 [D loss: 0.694161, acc.: 44.14%] [G loss: 0.724631]
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6930 [D loss: 0.693625, acc.: 45.90%] [G loss: 0.728852]
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6931 [D loss: 0.692339, acc.: 46.48%] [G loss: 0.731532]
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6932 [D loss: 0.692020, acc.: 50.00%] [G loss: 0.726230]
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6933 [D loss: 0.689425, acc.: 52.54%] [G loss: 0.722207]
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6934 [D loss: 0.687442, acc.: 52.15%] [G loss: 0.729250]
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6935 [D loss: 0.683492, acc.: 54.69%] [G loss: 0.724394]
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6936 [D loss: 0.681969, acc.: 54.10%] [G loss: 0.716603]
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6937 [D loss: 0.688472, acc.: 47.27%] [G loss: 0.709101]
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6938 [D loss: 0.690856, acc.: 48.63%] [G loss: 0.706590]
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6939 [D loss: 0.693066, acc.: 46.29%] [G loss: 0.701940]
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6940 [D loss: 0.694316, acc.: 48.63%] [G loss: 0.720688]
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6941 [D loss: 0.688057, acc.: 50.00%] [G loss: 0.718950]
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6942 [D loss: 0.696285, acc.: 44.34%] [G loss: 0.734393]
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6943 [D loss: 0.691435, acc.: 48.24%] [G loss: 0.736872]
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6944 [D loss: 0.692930, acc.: 46.29%] [G loss: 0.728233]
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6945 [D loss: 0.687049, acc.: 49.41%] [G loss: 0.726185]
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6946 [D loss: 0.685154, acc.: 47.46%] [G loss: 0.727832]
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6947 [D loss: 0.691239, acc.: 50.78%] [G loss: 0.727825]
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6948 [D loss: 0.691560, acc.: 49.61%] [G loss: 0.723700]
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6949 [D loss: 0.689906, acc.: 49.41%] [G loss: 0.718754]
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6950 [D loss: 0.691753, acc.: 45.51%] [G loss: 0.715357]
1/1 [==============================] - 0s 23ms/step
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6951 [D loss: 0.687507, acc.: 47.07%] [G loss: 0.711733]
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6952 [D loss: 0.690627, acc.: 46.09%] [G loss: 0.718890]
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6953 [D loss: 0.690708, acc.: 45.31%] [G loss: 0.718937]
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6954 [D loss: 0.687380, acc.: 52.73%] [G loss: 0.726064]
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6955 [D loss: 0.685861, acc.: 51.17%] [G loss: 0.730124]
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6956 [D loss: 0.696570, acc.: 52.54%] [G loss: 0.741464]
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6957 [D loss: 0.692316, acc.: 50.98%] [G loss: 0.737938]
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6958 [D loss: 0.694776, acc.: 47.07%] [G loss: 0.724951]
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6959 [D loss: 0.693657, acc.: 45.51%] [G loss: 0.716866]
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6960 [D loss: 0.694885, acc.: 47.66%] [G loss: 0.724467]
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6961 [D loss: 0.689228, acc.: 49.22%] [G loss: 0.714847]
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6962 [D loss: 0.688480, acc.: 44.92%] [G loss: 0.705477]
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6963 [D loss: 0.687900, acc.: 45.70%] [G loss: 0.705289]
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6964 [D loss: 0.705464, acc.: 39.45%] [G loss: 0.699793]
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6965 [D loss: 0.691112, acc.: 44.53%] [G loss: 0.708382]
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6966 [D loss: 0.692161, acc.: 44.92%] [G loss: 0.716743]
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6967 [D loss: 0.692950, acc.: 48.83%] [G loss: 0.726723]
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6968 [D loss: 0.686980, acc.: 49.61%] [G loss: 0.731722]
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6969 [D loss: 0.684388, acc.: 53.32%] [G loss: 0.731553]
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6970 [D loss: 0.684136, acc.: 50.98%] [G loss: 0.733909]
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6971 [D loss: 0.686617, acc.: 48.24%] [G loss: 0.725607]
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6972 [D loss: 0.690106, acc.: 50.98%] [G loss: 0.727010]
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6973 [D loss: 0.684993, acc.: 51.95%] [G loss: 0.721142]
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6974 [D loss: 0.687054, acc.: 48.44%] [G loss: 0.718072]
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6975 [D loss: 0.688537, acc.: 46.48%] [G loss: 0.712356]
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6976 [D loss: 0.687225, acc.: 47.07%] [G loss: 0.704420]
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6977 [D loss: 0.696273, acc.: 42.58%] [G loss: 0.707711]
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6978 [D loss: 0.693591, acc.: 47.46%] [G loss: 0.706561]
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6979 [D loss: 0.691949, acc.: 49.22%] [G loss: 0.717201]
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6980 [D loss: 0.692614, acc.: 43.55%] [G loss: 0.719259]
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6981 [D loss: 0.685928, acc.: 48.05%] [G loss: 0.718249]
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6982 [D loss: 0.693123, acc.: 46.29%] [G loss: 0.714338]
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6983 [D loss: 0.689952, acc.: 49.02%] [G loss: 0.721954]
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6984 [D loss: 0.685623, acc.: 49.61%] [G loss: 0.720401]
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6985 [D loss: 0.688803, acc.: 47.85%] [G loss: 0.722532]
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6986 [D loss: 0.680028, acc.: 53.12%] [G loss: 0.717965]
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6987 [D loss: 0.689258, acc.: 49.22%] [G loss: 0.722994]
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6988 [D loss: 0.690647, acc.: 47.66%] [G loss: 0.717322]
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6989 [D loss: 0.688925, acc.: 51.76%] [G loss: 0.717061]
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6990 [D loss: 0.691660, acc.: 49.61%] [G loss: 0.724082]
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6991 [D loss: 0.687295, acc.: 52.15%] [G loss: 0.721614]
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6992 [D loss: 0.693248, acc.: 46.68%] [G loss: 0.722707]
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6993 [D loss: 0.694086, acc.: 48.05%] [G loss: 0.727616]
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6994 [D loss: 0.687288, acc.: 50.78%] [G loss: 0.724071]
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6995 [D loss: 0.686258, acc.: 47.27%] [G loss: 0.724135]
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6996 [D loss: 0.686148, acc.: 48.63%] [G loss: 0.721634]
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6997 [D loss: 0.686342, acc.: 49.02%] [G loss: 0.727141]
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6998 [D loss: 0.684455, acc.: 47.85%] [G loss: 0.719886]
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6999 [D loss: 0.686860, acc.: 49.41%] [G loss: 0.717369]
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7000 [D loss: 0.690333, acc.: 45.51%] [G loss: 0.717412]
1/1 [==============================] - 0s 19ms/step
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7001 [D loss: 0.675937, acc.: 53.52%] [G loss: 0.716308]
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7002 [D loss: 0.686993, acc.: 50.39%] [G loss: 0.725237]
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7003 [D loss: 0.688392, acc.: 49.61%] [G loss: 0.717560]
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7004 [D loss: 0.683115, acc.: 53.12%] [G loss: 0.724330]
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7005 [D loss: 0.685816, acc.: 53.71%] [G loss: 0.714986]
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7006 [D loss: 0.676933, acc.: 56.05%] [G loss: 0.719675]
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7007 [D loss: 0.684136, acc.: 49.02%] [G loss: 0.720668]
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7008 [D loss: 0.690412, acc.: 47.85%] [G loss: 0.717114]
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7009 [D loss: 0.679347, acc.: 48.63%] [G loss: 0.722745]
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7010 [D loss: 0.690683, acc.: 45.90%] [G loss: 0.715582]
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7011 [D loss: 0.690667, acc.: 48.05%] [G loss: 0.709833]
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7012 [D loss: 0.694401, acc.: 45.12%] [G loss: 0.720812]
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7013 [D loss: 0.687858, acc.: 47.07%] [G loss: 0.722383]
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7014 [D loss: 0.686647, acc.: 47.85%] [G loss: 0.715801]
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7015 [D loss: 0.682892, acc.: 48.44%] [G loss: 0.719953]
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7016 [D loss: 0.687203, acc.: 49.61%] [G loss: 0.723297]
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7017 [D loss: 0.685161, acc.: 47.66%] [G loss: 0.725190]
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7018 [D loss: 0.683791, acc.: 49.80%] [G loss: 0.729710]
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7019 [D loss: 0.690785, acc.: 48.44%] [G loss: 0.728187]
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7020 [D loss: 0.686910, acc.: 50.78%] [G loss: 0.733139]
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7021 [D loss: 0.691543, acc.: 47.46%] [G loss: 0.727238]
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7022 [D loss: 0.679648, acc.: 53.32%] [G loss: 0.729566]
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7023 [D loss: 0.683430, acc.: 52.15%] [G loss: 0.717543]
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7024 [D loss: 0.678060, acc.: 55.27%] [G loss: 0.722632]
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7025 [D loss: 0.678376, acc.: 54.88%] [G loss: 0.726088]
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7026 [D loss: 0.687372, acc.: 51.37%] [G loss: 0.715380]
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7027 [D loss: 0.690384, acc.: 52.34%] [G loss: 0.716285]
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7028 [D loss: 0.686745, acc.: 50.78%] [G loss: 0.713166]
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7029 [D loss: 0.683122, acc.: 53.52%] [G loss: 0.721050]
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7030 [D loss: 0.686750, acc.: 52.73%] [G loss: 0.726719]
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7031 [D loss: 0.693141, acc.: 45.31%] [G loss: 0.716865]
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7032 [D loss: 0.691621, acc.: 49.02%] [G loss: 0.721724]
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7033 [D loss: 0.688088, acc.: 45.90%] [G loss: 0.726504]
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7034 [D loss: 0.697541, acc.: 43.36%] [G loss: 0.722580]
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7035 [D loss: 0.690504, acc.: 47.85%] [G loss: 0.723395]
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7036 [D loss: 0.684221, acc.: 51.95%] [G loss: 0.721483]
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7037 [D loss: 0.686818, acc.: 47.66%] [G loss: 0.713230]
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7038 [D loss: 0.683380, acc.: 52.15%] [G loss: 0.722094]
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7039 [D loss: 0.681584, acc.: 53.71%] [G loss: 0.716244]
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7040 [D loss: 0.692806, acc.: 48.83%] [G loss: 0.707940]
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7041 [D loss: 0.716781, acc.: 44.53%] [G loss: 0.693366]
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7042 [D loss: 0.705298, acc.: 46.88%] [G loss: 0.708256]
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7043 [D loss: 0.699910, acc.: 44.92%] [G loss: 0.715552]
8/8 [==============================] - 0s 5ms/step
7044 [D loss: 0.697721, acc.: 49.61%] [G loss: 0.739937]
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7045 [D loss: 0.694084, acc.: 49.61%] [G loss: 0.730329]
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7046 [D loss: 0.702063, acc.: 46.88%] [G loss: 0.725364]
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7047 [D loss: 0.697001, acc.: 47.66%] [G loss: 0.719038]
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7048 [D loss: 0.697255, acc.: 46.88%] [G loss: 0.725909]
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7049 [D loss: 0.699364, acc.: 50.20%] [G loss: 0.723294]
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7050 [D loss: 0.693842, acc.: 50.39%] [G loss: 0.719950]
1/1 [==============================] - 0s 18ms/step
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7051 [D loss: 0.696345, acc.: 45.12%] [G loss: 0.710763]
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7052 [D loss: 0.691274, acc.: 47.27%] [G loss: 0.716870]
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7053 [D loss: 0.691433, acc.: 51.17%] [G loss: 0.724628]
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7054 [D loss: 0.690607, acc.: 50.20%] [G loss: 0.724772]
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7055 [D loss: 0.686383, acc.: 50.78%] [G loss: 0.737011]
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7056 [D loss: 0.691015, acc.: 50.00%] [G loss: 0.733197]
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7057 [D loss: 0.689495, acc.: 51.56%] [G loss: 0.731353]
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7058 [D loss: 0.693130, acc.: 46.88%] [G loss: 0.728572]
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7059 [D loss: 0.695265, acc.: 48.05%] [G loss: 0.723348]
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7060 [D loss: 0.697133, acc.: 47.85%] [G loss: 0.712891]
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7061 [D loss: 0.699685, acc.: 45.51%] [G loss: 0.708241]
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7062 [D loss: 0.697537, acc.: 43.55%] [G loss: 0.710581]
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7063 [D loss: 0.698376, acc.: 45.90%] [G loss: 0.714833]
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7064 [D loss: 0.698680, acc.: 46.09%] [G loss: 0.717512]
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7065 [D loss: 0.694664, acc.: 49.22%] [G loss: 0.738406]
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7066 [D loss: 0.680140, acc.: 54.30%] [G loss: 0.758614]
8/8 [==============================] - 0s 5ms/step
7067 [D loss: 0.683179, acc.: 56.25%] [G loss: 0.758569]
8/8 [==============================] - 0s 7ms/step
7068 [D loss: 0.690025, acc.: 48.05%] [G loss: 0.742990]
8/8 [==============================] - 0s 5ms/step
7069 [D loss: 0.692064, acc.: 49.02%] [G loss: 0.730835]
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7070 [D loss: 0.689380, acc.: 52.93%] [G loss: 0.733464]
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7071 [D loss: 0.695987, acc.: 48.05%] [G loss: 0.720360]
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7072 [D loss: 0.700400, acc.: 47.85%] [G loss: 0.706974]
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7073 [D loss: 0.705989, acc.: 40.82%] [G loss: 0.693652]
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7074 [D loss: 0.705620, acc.: 41.99%] [G loss: 0.695263]
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7075 [D loss: 0.703258, acc.: 42.77%] [G loss: 0.703211]
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7076 [D loss: 0.698419, acc.: 45.90%] [G loss: 0.709169]
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7077 [D loss: 0.700290, acc.: 44.92%] [G loss: 0.724262]
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7078 [D loss: 0.691893, acc.: 51.37%] [G loss: 0.736628]
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7079 [D loss: 0.692138, acc.: 50.20%] [G loss: 0.742598]
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7080 [D loss: 0.691826, acc.: 49.61%] [G loss: 0.749942]
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7081 [D loss: 0.692309, acc.: 50.59%] [G loss: 0.741750]
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7082 [D loss: 0.694814, acc.: 48.24%] [G loss: 0.732301]
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7083 [D loss: 0.694541, acc.: 47.07%] [G loss: 0.726003]
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7084 [D loss: 0.689575, acc.: 51.95%] [G loss: 0.728004]
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7085 [D loss: 0.697982, acc.: 48.44%] [G loss: 0.718358]
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7086 [D loss: 0.695658, acc.: 50.39%] [G loss: 0.711630]
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7087 [D loss: 0.697163, acc.: 47.07%] [G loss: 0.699040]
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7088 [D loss: 0.698145, acc.: 42.97%] [G loss: 0.697230]
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7089 [D loss: 0.699400, acc.: 44.92%] [G loss: 0.708947]
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7090 [D loss: 0.697450, acc.: 46.88%] [G loss: 0.708014]
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7091 [D loss: 0.690359, acc.: 49.41%] [G loss: 0.721878]
8/8 [==============================] - 0s 5ms/step
7092 [D loss: 0.689803, acc.: 52.15%] [G loss: 0.729089]
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7093 [D loss: 0.688742, acc.: 50.78%] [G loss: 0.737402]
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7094 [D loss: 0.690291, acc.: 52.93%] [G loss: 0.731508]
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7095 [D loss: 0.689847, acc.: 50.39%] [G loss: 0.733212]
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7096 [D loss: 0.691973, acc.: 50.59%] [G loss: 0.729249]
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7097 [D loss: 0.692861, acc.: 52.34%] [G loss: 0.729860]
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7098 [D loss: 0.688907, acc.: 55.27%] [G loss: 0.722966]
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7099 [D loss: 0.692333, acc.: 49.41%] [G loss: 0.717731]
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7100 [D loss: 0.697853, acc.: 47.46%] [G loss: 0.696284]
1/1 [==============================] - 0s 17ms/step
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7101 [D loss: 0.706337, acc.: 44.34%] [G loss: 0.704118]
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7102 [D loss: 0.695522, acc.: 50.20%] [G loss: 0.713737]
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7103 [D loss: 0.697032, acc.: 48.83%] [G loss: 0.725961]
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7104 [D loss: 0.695810, acc.: 45.90%] [G loss: 0.739344]
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7105 [D loss: 0.699445, acc.: 45.70%] [G loss: 0.735544]
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7106 [D loss: 0.696297, acc.: 45.70%] [G loss: 0.733801]
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7107 [D loss: 0.692076, acc.: 49.61%] [G loss: 0.728510]
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7108 [D loss: 0.693249, acc.: 51.37%] [G loss: 0.734829]
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7109 [D loss: 0.690962, acc.: 52.34%] [G loss: 0.739087]
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7110 [D loss: 0.685419, acc.: 52.34%] [G loss: 0.728038]
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7111 [D loss: 0.681023, acc.: 55.08%] [G loss: 0.731872]
8/8 [==============================] - 0s 5ms/step
7112 [D loss: 0.684699, acc.: 51.76%] [G loss: 0.730776]
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7113 [D loss: 0.682650, acc.: 50.98%] [G loss: 0.724718]
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7114 [D loss: 0.686895, acc.: 51.95%] [G loss: 0.721054]
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7115 [D loss: 0.685346, acc.: 53.52%] [G loss: 0.722246]
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7116 [D loss: 0.684990, acc.: 50.39%] [G loss: 0.718194]
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7117 [D loss: 0.688669, acc.: 47.27%] [G loss: 0.723486]
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7118 [D loss: 0.684104, acc.: 50.98%] [G loss: 0.722481]
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7119 [D loss: 0.690660, acc.: 47.66%] [G loss: 0.720119]
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7120 [D loss: 0.686208, acc.: 51.17%] [G loss: 0.724895]
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7121 [D loss: 0.685107, acc.: 51.56%] [G loss: 0.722926]
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7122 [D loss: 0.694942, acc.: 48.24%] [G loss: 0.717216]
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7123 [D loss: 0.698426, acc.: 47.07%] [G loss: 0.694353]
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7124 [D loss: 0.704840, acc.: 43.95%] [G loss: 0.690982]
8/8 [==============================] - 0s 5ms/step
7125 [D loss: 0.715127, acc.: 47.46%] [G loss: 0.698562]
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7126 [D loss: 0.699964, acc.: 48.05%] [G loss: 0.715064]
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7127 [D loss: 0.701691, acc.: 44.14%] [G loss: 0.724189]
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7128 [D loss: 0.692343, acc.: 51.17%] [G loss: 0.736146]
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7129 [D loss: 0.692707, acc.: 51.76%] [G loss: 0.735676]
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7130 [D loss: 0.697864, acc.: 46.68%] [G loss: 0.729208]
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7131 [D loss: 0.699260, acc.: 46.29%] [G loss: 0.724780]
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7132 [D loss: 0.695520, acc.: 48.83%] [G loss: 0.727026]
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7133 [D loss: 0.687604, acc.: 55.08%] [G loss: 0.742359]
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7134 [D loss: 0.692939, acc.: 48.83%] [G loss: 0.715703]
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7135 [D loss: 0.699243, acc.: 43.95%] [G loss: 0.711290]
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7136 [D loss: 0.696274, acc.: 49.02%] [G loss: 0.710481]
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7137 [D loss: 0.693093, acc.: 47.85%] [G loss: 0.730729]
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7138 [D loss: 0.689519, acc.: 53.52%] [G loss: 0.736825]
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7139 [D loss: 0.690477, acc.: 49.02%] [G loss: 0.733296]
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7140 [D loss: 0.698453, acc.: 45.70%] [G loss: 0.722807]
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7141 [D loss: 0.697107, acc.: 48.44%] [G loss: 0.722484]
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7142 [D loss: 0.691364, acc.: 51.17%] [G loss: 0.722647]
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7143 [D loss: 0.689920, acc.: 52.15%] [G loss: 0.724357]
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7144 [D loss: 0.686653, acc.: 50.00%] [G loss: 0.723527]
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7145 [D loss: 0.686830, acc.: 52.73%] [G loss: 0.722228]
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7146 [D loss: 0.695379, acc.: 49.61%] [G loss: 0.699603]
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7147 [D loss: 0.691560, acc.: 49.61%] [G loss: 0.699316]
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7148 [D loss: 0.689416, acc.: 50.20%] [G loss: 0.704173]
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7149 [D loss: 0.691069, acc.: 49.80%] [G loss: 0.717152]
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7150 [D loss: 0.687128, acc.: 50.00%] [G loss: 0.718452]
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7151 [D loss: 0.697791, acc.: 41.80%] [G loss: 0.718739]
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7152 [D loss: 0.695696, acc.: 48.24%] [G loss: 0.706741]
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7153 [D loss: 0.686738, acc.: 51.76%] [G loss: 0.723950]
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7154 [D loss: 0.693548, acc.: 48.44%] [G loss: 0.723436]
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7155 [D loss: 0.689398, acc.: 48.83%] [G loss: 0.713119]
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7156 [D loss: 0.685413, acc.: 52.34%] [G loss: 0.722509]
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7157 [D loss: 0.694655, acc.: 47.46%] [G loss: 0.712811]
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7158 [D loss: 0.699402, acc.: 53.12%] [G loss: 0.700427]
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7159 [D loss: 0.701788, acc.: 47.85%] [G loss: 0.706517]
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7160 [D loss: 0.693817, acc.: 51.17%] [G loss: 0.709249]
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7161 [D loss: 0.689954, acc.: 56.05%] [G loss: 0.714624]
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7162 [D loss: 0.692455, acc.: 51.95%] [G loss: 0.725918]
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7163 [D loss: 0.687944, acc.: 56.45%] [G loss: 0.727222]
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7164 [D loss: 0.696131, acc.: 50.98%] [G loss: 0.726023]
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7165 [D loss: 0.695148, acc.: 52.93%] [G loss: 0.712993]
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7166 [D loss: 0.696964, acc.: 48.05%] [G loss: 0.718581]
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7167 [D loss: 0.700800, acc.: 44.73%] [G loss: 0.708813]
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7168 [D loss: 0.697562, acc.: 48.83%] [G loss: 0.714072]
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7169 [D loss: 0.698321, acc.: 45.51%] [G loss: 0.719072]
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7170 [D loss: 0.701660, acc.: 43.95%] [G loss: 0.703292]
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7171 [D loss: 0.699918, acc.: 43.75%] [G loss: 0.718373]
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7172 [D loss: 0.697866, acc.: 49.61%] [G loss: 0.714135]
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7173 [D loss: 0.697839, acc.: 45.90%] [G loss: 0.721450]
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7174 [D loss: 0.693810, acc.: 47.46%] [G loss: 0.710983]
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7175 [D loss: 0.697662, acc.: 49.02%] [G loss: 0.709484]
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7176 [D loss: 0.694782, acc.: 45.12%] [G loss: 0.708668]
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7177 [D loss: 0.695405, acc.: 46.09%] [G loss: 0.706960]
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7178 [D loss: 0.693886, acc.: 48.24%] [G loss: 0.705587]
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7179 [D loss: 0.695624, acc.: 50.20%] [G loss: 0.708696]
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7180 [D loss: 0.694446, acc.: 46.88%] [G loss: 0.711835]
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7181 [D loss: 0.694378, acc.: 47.66%] [G loss: 0.721067]
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7182 [D loss: 0.690104, acc.: 51.37%] [G loss: 0.732511]
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7183 [D loss: 0.687053, acc.: 48.83%] [G loss: 0.730467]
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7184 [D loss: 0.687874, acc.: 50.59%] [G loss: 0.729928]
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7185 [D loss: 0.688386, acc.: 50.78%] [G loss: 0.730453]
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7186 [D loss: 0.692474, acc.: 51.76%] [G loss: 0.727011]
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7187 [D loss: 0.690958, acc.: 51.37%] [G loss: 0.724683]
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7188 [D loss: 0.688680, acc.: 53.91%] [G loss: 0.719389]
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7189 [D loss: 0.696138, acc.: 51.37%] [G loss: 0.708816]
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7190 [D loss: 0.696539, acc.: 48.44%] [G loss: 0.701856]
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7191 [D loss: 0.698808, acc.: 43.95%] [G loss: 0.701591]
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7192 [D loss: 0.696731, acc.: 44.14%] [G loss: 0.704442]
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7193 [D loss: 0.695326, acc.: 50.39%] [G loss: 0.708032]
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7194 [D loss: 0.696195, acc.: 48.83%] [G loss: 0.710346]
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7195 [D loss: 0.698671, acc.: 46.48%] [G loss: 0.730064]
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7196 [D loss: 0.688347, acc.: 52.34%] [G loss: 0.726693]
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7197 [D loss: 0.689372, acc.: 53.32%] [G loss: 0.734108]
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7198 [D loss: 0.693589, acc.: 51.56%] [G loss: 0.727856]
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7199 [D loss: 0.691823, acc.: 52.54%] [G loss: 0.718892]
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7200 [D loss: 0.694953, acc.: 49.80%] [G loss: 0.719548]
1/1 [==============================] - 0s 20ms/step
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7201 [D loss: 0.691401, acc.: 51.37%] [G loss: 0.717621]
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7202 [D loss: 0.690388, acc.: 50.39%] [G loss: 0.722963]
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7203 [D loss: 0.693326, acc.: 46.48%] [G loss: 0.716116]
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7204 [D loss: 0.690764, acc.: 53.12%] [G loss: 0.726346]
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7205 [D loss: 0.687808, acc.: 53.91%] [G loss: 0.731715]
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7206 [D loss: 0.689665, acc.: 48.24%] [G loss: 0.737810]
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7207 [D loss: 0.689699, acc.: 50.78%] [G loss: 0.728024]
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7208 [D loss: 0.689011, acc.: 51.37%] [G loss: 0.722420]
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7209 [D loss: 0.690923, acc.: 53.32%] [G loss: 0.722531]
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7210 [D loss: 0.693087, acc.: 50.98%] [G loss: 0.711926]
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7211 [D loss: 0.695879, acc.: 46.88%] [G loss: 0.707278]
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7212 [D loss: 0.700126, acc.: 44.34%] [G loss: 0.710320]
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7213 [D loss: 0.697774, acc.: 47.27%] [G loss: 0.708950]
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7214 [D loss: 0.698084, acc.: 47.07%] [G loss: 0.707906]
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7215 [D loss: 0.692412, acc.: 52.34%] [G loss: 0.718085]
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7216 [D loss: 0.699188, acc.: 48.24%] [G loss: 0.720563]
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7217 [D loss: 0.693780, acc.: 49.02%] [G loss: 0.720632]
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7218 [D loss: 0.695980, acc.: 48.83%] [G loss: 0.721427]
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7219 [D loss: 0.696652, acc.: 46.68%] [G loss: 0.707449]
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7220 [D loss: 0.695987, acc.: 46.68%] [G loss: 0.710896]
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7221 [D loss: 0.694830, acc.: 47.27%] [G loss: 0.711562]
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7222 [D loss: 0.692967, acc.: 48.83%] [G loss: 0.716473]
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7223 [D loss: 0.688682, acc.: 48.24%] [G loss: 0.718319]
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7224 [D loss: 0.692897, acc.: 46.09%] [G loss: 0.727278]
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7225 [D loss: 0.688995, acc.: 47.85%] [G loss: 0.726088]
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7226 [D loss: 0.689522, acc.: 47.46%] [G loss: 0.737436]
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7227 [D loss: 0.684733, acc.: 54.49%] [G loss: 0.742313]
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7228 [D loss: 0.673673, acc.: 59.77%] [G loss: 0.751597]
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7229 [D loss: 0.683218, acc.: 50.39%] [G loss: 0.738146]
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7230 [D loss: 0.690121, acc.: 49.80%] [G loss: 0.726945]
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7231 [D loss: 0.695103, acc.: 50.00%] [G loss: 0.717996]
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7232 [D loss: 0.687224, acc.: 51.95%] [G loss: 0.717392]
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7233 [D loss: 0.689939, acc.: 50.98%] [G loss: 0.704981]
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7234 [D loss: 0.699154, acc.: 45.90%] [G loss: 0.705539]
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7235 [D loss: 0.694936, acc.: 49.80%] [G loss: 0.691242]
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7236 [D loss: 0.690363, acc.: 50.78%] [G loss: 0.709846]
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7237 [D loss: 0.690540, acc.: 50.98%] [G loss: 0.714321]
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7238 [D loss: 0.691287, acc.: 48.83%] [G loss: 0.725588]
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7239 [D loss: 0.691415, acc.: 47.85%] [G loss: 0.723024]
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7240 [D loss: 0.692283, acc.: 44.73%] [G loss: 0.723279]
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7241 [D loss: 0.690505, acc.: 49.22%] [G loss: 0.723220]
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7242 [D loss: 0.697509, acc.: 45.90%] [G loss: 0.723169]
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7243 [D loss: 0.684774, acc.: 50.39%] [G loss: 0.723605]
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7244 [D loss: 0.691249, acc.: 46.48%] [G loss: 0.723859]
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7245 [D loss: 0.688026, acc.: 48.63%] [G loss: 0.721969]
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7246 [D loss: 0.687924, acc.: 44.92%] [G loss: 0.722622]
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7247 [D loss: 0.689043, acc.: 50.20%] [G loss: 0.718640]
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7248 [D loss: 0.702470, acc.: 44.73%] [G loss: 0.713470]
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7249 [D loss: 0.696760, acc.: 47.46%] [G loss: 0.720589]
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7250 [D loss: 0.697444, acc.: 47.66%] [G loss: 0.719497]
1/1 [==============================] - 0s 19ms/step
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7251 [D loss: 0.693817, acc.: 49.02%] [G loss: 0.727959]
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7252 [D loss: 0.692027, acc.: 49.61%] [G loss: 0.717041]
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7253 [D loss: 0.692954, acc.: 51.56%] [G loss: 0.705227]
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7254 [D loss: 0.696088, acc.: 45.90%] [G loss: 0.713208]
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7255 [D loss: 0.701493, acc.: 44.73%] [G loss: 0.704527]
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7256 [D loss: 0.696424, acc.: 45.51%] [G loss: 0.700530]
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7257 [D loss: 0.705465, acc.: 41.21%] [G loss: 0.694338]
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7258 [D loss: 0.702413, acc.: 44.92%] [G loss: 0.700541]
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7259 [D loss: 0.695795, acc.: 50.20%] [G loss: 0.716550]
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7260 [D loss: 0.690595, acc.: 52.93%] [G loss: 0.729298]
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7261 [D loss: 0.691722, acc.: 51.56%] [G loss: 0.738741]
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7262 [D loss: 0.690450, acc.: 52.15%] [G loss: 0.741210]
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7263 [D loss: 0.690612, acc.: 52.73%] [G loss: 0.733310]
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7264 [D loss: 0.693638, acc.: 48.63%] [G loss: 0.739115]
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7265 [D loss: 0.691450, acc.: 49.41%] [G loss: 0.739453]
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7266 [D loss: 0.689561, acc.: 52.34%] [G loss: 0.732065]
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7267 [D loss: 0.683979, acc.: 53.71%] [G loss: 0.730949]
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7268 [D loss: 0.685050, acc.: 51.17%] [G loss: 0.728704]
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7269 [D loss: 0.687478, acc.: 53.91%] [G loss: 0.718842]
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7270 [D loss: 0.698256, acc.: 49.61%] [G loss: 0.704664]
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7271 [D loss: 0.698665, acc.: 48.44%] [G loss: 0.700800]
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7272 [D loss: 0.699137, acc.: 45.51%] [G loss: 0.716549]
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7273 [D loss: 0.694310, acc.: 50.59%] [G loss: 0.730963]
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7274 [D loss: 0.695480, acc.: 48.44%] [G loss: 0.741475]
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7275 [D loss: 0.692599, acc.: 50.78%] [G loss: 0.728923]
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7276 [D loss: 0.691714, acc.: 51.17%] [G loss: 0.728854]
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7277 [D loss: 0.698876, acc.: 47.07%] [G loss: 0.717241]
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7278 [D loss: 0.694905, acc.: 49.22%] [G loss: 0.716404]
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7279 [D loss: 0.694682, acc.: 50.00%] [G loss: 0.707280]
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7280 [D loss: 0.690422, acc.: 53.52%] [G loss: 0.721468]
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7281 [D loss: 0.687616, acc.: 52.73%] [G loss: 0.722561]
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7282 [D loss: 0.687181, acc.: 53.32%] [G loss: 0.712125]
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7283 [D loss: 0.679956, acc.: 53.71%] [G loss: 0.735338]
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7284 [D loss: 0.682262, acc.: 56.05%] [G loss: 0.748775]
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7285 [D loss: 0.694907, acc.: 48.44%] [G loss: 0.715765]
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7286 [D loss: 0.699578, acc.: 46.48%] [G loss: 0.710767]
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7287 [D loss: 0.700052, acc.: 45.70%] [G loss: 0.699959]
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7288 [D loss: 0.701790, acc.: 42.38%] [G loss: 0.702939]
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7289 [D loss: 0.695336, acc.: 44.14%] [G loss: 0.704458]
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7290 [D loss: 0.694759, acc.: 46.29%] [G loss: 0.703151]
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7291 [D loss: 0.698028, acc.: 44.34%] [G loss: 0.715320]
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7292 [D loss: 0.686129, acc.: 51.17%] [G loss: 0.716579]
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7293 [D loss: 0.687080, acc.: 50.59%] [G loss: 0.727015]
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7294 [D loss: 0.686934, acc.: 52.34%] [G loss: 0.740810]
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7295 [D loss: 0.689915, acc.: 52.15%] [G loss: 0.735845]
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7296 [D loss: 0.682913, acc.: 49.22%] [G loss: 0.736053]
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7297 [D loss: 0.685461, acc.: 52.34%] [G loss: 0.739255]
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7298 [D loss: 0.684181, acc.: 55.47%] [G loss: 0.728313]
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7299 [D loss: 0.679748, acc.: 55.08%] [G loss: 0.734813]
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7300 [D loss: 0.689515, acc.: 47.66%] [G loss: 0.739118]
1/1 [==============================] - 0s 17ms/step
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7301 [D loss: 0.687866, acc.: 51.37%] [G loss: 0.727185]
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7302 [D loss: 0.688568, acc.: 50.20%] [G loss: 0.719665]
8/8 [==============================] - 0s 5ms/step
7303 [D loss: 0.700659, acc.: 44.34%] [G loss: 0.710349]
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7304 [D loss: 0.704537, acc.: 48.05%] [G loss: 0.711540]
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7305 [D loss: 0.694392, acc.: 50.59%] [G loss: 0.719898]
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7306 [D loss: 0.689643, acc.: 48.44%] [G loss: 0.736962]
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7307 [D loss: 0.692591, acc.: 51.76%] [G loss: 0.719150]
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7308 [D loss: 0.691252, acc.: 50.59%] [G loss: 0.724537]
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7309 [D loss: 0.695054, acc.: 51.37%] [G loss: 0.715899]
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7310 [D loss: 0.691514, acc.: 50.39%] [G loss: 0.721238]
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7311 [D loss: 0.695655, acc.: 47.85%] [G loss: 0.710149]
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7312 [D loss: 0.692428, acc.: 48.63%] [G loss: 0.712947]
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7313 [D loss: 0.693180, acc.: 47.85%] [G loss: 0.715686]
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7314 [D loss: 0.693928, acc.: 45.70%] [G loss: 0.713472]
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7315 [D loss: 0.700789, acc.: 43.95%] [G loss: 0.714808]
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7316 [D loss: 0.700272, acc.: 45.12%] [G loss: 0.710456]
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7317 [D loss: 0.702306, acc.: 43.36%] [G loss: 0.716875]
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7318 [D loss: 0.702249, acc.: 44.53%] [G loss: 0.714288]
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7319 [D loss: 0.703599, acc.: 39.84%] [G loss: 0.714613]
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7320 [D loss: 0.696858, acc.: 50.20%] [G loss: 0.721973]
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7321 [D loss: 0.693657, acc.: 50.59%] [G loss: 0.723738]
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7322 [D loss: 0.688778, acc.: 52.15%] [G loss: 0.722317]
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7323 [D loss: 0.703142, acc.: 44.34%] [G loss: 0.701922]
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7324 [D loss: 0.693645, acc.: 52.15%] [G loss: 0.703452]
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7325 [D loss: 0.695784, acc.: 50.59%] [G loss: 0.724167]
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7326 [D loss: 0.692154, acc.: 50.00%] [G loss: 0.739855]
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7327 [D loss: 0.686927, acc.: 54.10%] [G loss: 0.747140]
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7328 [D loss: 0.696433, acc.: 45.51%] [G loss: 0.749742]
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7329 [D loss: 0.694473, acc.: 48.05%] [G loss: 0.732233]
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7330 [D loss: 0.696353, acc.: 49.22%] [G loss: 0.726938]
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7331 [D loss: 0.688293, acc.: 53.52%] [G loss: 0.735020]
8/8 [==============================] - 0s 5ms/step
7332 [D loss: 0.691041, acc.: 51.17%] [G loss: 0.731886]
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7333 [D loss: 0.693244, acc.: 49.41%] [G loss: 0.726406]
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7334 [D loss: 0.688402, acc.: 50.78%] [G loss: 0.718254]
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7335 [D loss: 0.686081, acc.: 50.98%] [G loss: 0.712524]
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7336 [D loss: 0.691571, acc.: 51.37%] [G loss: 0.703559]
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7337 [D loss: 0.692618, acc.: 48.83%] [G loss: 0.703365]
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7338 [D loss: 0.690947, acc.: 52.15%] [G loss: 0.708429]
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7339 [D loss: 0.686704, acc.: 56.25%] [G loss: 0.731296]
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7340 [D loss: 0.688763, acc.: 52.73%] [G loss: 0.743534]
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7341 [D loss: 0.688627, acc.: 51.37%] [G loss: 0.749894]
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7342 [D loss: 0.693068, acc.: 51.17%] [G loss: 0.741625]
8/8 [==============================] - 0s 5ms/step
7343 [D loss: 0.698263, acc.: 47.66%] [G loss: 0.740636]
8/8 [==============================] - 0s 5ms/step
7344 [D loss: 0.694889, acc.: 49.22%] [G loss: 0.728174]
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7345 [D loss: 0.694563, acc.: 49.22%] [G loss: 0.724177]
8/8 [==============================] - 0s 5ms/step
7346 [D loss: 0.685178, acc.: 55.08%] [G loss: 0.725397]
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7347 [D loss: 0.682742, acc.: 59.38%] [G loss: 0.720585]
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7348 [D loss: 0.688024, acc.: 52.15%] [G loss: 0.708553]
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7349 [D loss: 0.693483, acc.: 45.90%] [G loss: 0.694903]
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7350 [D loss: 0.706187, acc.: 44.92%] [G loss: 0.688829]
1/1 [==============================] - 0s 22ms/step
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7351 [D loss: 0.703639, acc.: 47.85%] [G loss: 0.702704]
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7352 [D loss: 0.702299, acc.: 48.24%] [G loss: 0.713356]
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7353 [D loss: 0.708939, acc.: 48.24%] [G loss: 0.720291]
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7354 [D loss: 0.700561, acc.: 43.55%] [G loss: 0.718187]
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7355 [D loss: 0.704750, acc.: 42.38%] [G loss: 0.709886]
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7356 [D loss: 0.694064, acc.: 48.05%] [G loss: 0.720174]
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7357 [D loss: 0.693966, acc.: 50.98%] [G loss: 0.718397]
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7358 [D loss: 0.702106, acc.: 40.04%] [G loss: 0.704385]
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7359 [D loss: 0.699830, acc.: 41.99%] [G loss: 0.709931]
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7360 [D loss: 0.691713, acc.: 48.24%] [G loss: 0.722569]
8/8 [==============================] - 0s 5ms/step
7361 [D loss: 0.691556, acc.: 50.00%] [G loss: 0.727614]
8/8 [==============================] - 0s 5ms/step
7362 [D loss: 0.692718, acc.: 50.39%] [G loss: 0.728791]
8/8 [==============================] - 0s 5ms/step
7363 [D loss: 0.692456, acc.: 52.15%] [G loss: 0.725924]
8/8 [==============================] - 0s 5ms/step
7364 [D loss: 0.699955, acc.: 47.46%] [G loss: 0.723832]
8/8 [==============================] - 0s 5ms/step
7365 [D loss: 0.697484, acc.: 47.85%] [G loss: 0.714897]
8/8 [==============================] - 0s 5ms/step
7366 [D loss: 0.693938, acc.: 49.41%] [G loss: 0.723075]
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7367 [D loss: 0.687932, acc.: 52.73%] [G loss: 0.719988]
8/8 [==============================] - 0s 5ms/step
7368 [D loss: 0.693381, acc.: 48.44%] [G loss: 0.713673]
8/8 [==============================] - 0s 5ms/step
7369 [D loss: 0.693230, acc.: 47.27%] [G loss: 0.708979]
8/8 [==============================] - 0s 5ms/step
7370 [D loss: 0.693357, acc.: 48.83%] [G loss: 0.701667]
8/8 [==============================] - 0s 5ms/step
7371 [D loss: 0.686225, acc.: 54.30%] [G loss: 0.709315]
8/8 [==============================] - 0s 5ms/step
7372 [D loss: 0.692257, acc.: 47.27%] [G loss: 0.713034]
8/8 [==============================] - 0s 5ms/step
7373 [D loss: 0.686400, acc.: 50.59%] [G loss: 0.717285]
8/8 [==============================] - 0s 5ms/step
7374 [D loss: 0.696419, acc.: 45.12%] [G loss: 0.723775]
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7375 [D loss: 0.690430, acc.: 51.76%] [G loss: 0.701039]
8/8 [==============================] - 0s 5ms/step
7376 [D loss: 0.695466, acc.: 49.02%] [G loss: 0.706694]
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7377 [D loss: 0.690576, acc.: 52.15%] [G loss: 0.709342]
8/8 [==============================] - 0s 7ms/step
7378 [D loss: 0.690631, acc.: 52.73%] [G loss: 0.713758]
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7379 [D loss: 0.694472, acc.: 44.53%] [G loss: 0.705675]
8/8 [==============================] - 0s 5ms/step
7380 [D loss: 0.695493, acc.: 48.44%] [G loss: 0.704328]
8/8 [==============================] - 0s 5ms/step
7381 [D loss: 0.700425, acc.: 44.53%] [G loss: 0.702252]
8/8 [==============================] - 0s 5ms/step
7382 [D loss: 0.697381, acc.: 50.59%] [G loss: 0.697445]
8/8 [==============================] - 0s 5ms/step
7383 [D loss: 0.698174, acc.: 47.07%] [G loss: 0.708058]
8/8 [==============================] - 0s 5ms/step
7384 [D loss: 0.699686, acc.: 44.92%] [G loss: 0.713484]
8/8 [==============================] - 0s 5ms/step
7385 [D loss: 0.694524, acc.: 46.09%] [G loss: 0.719926]
8/8 [==============================] - 0s 5ms/step
7386 [D loss: 0.689985, acc.: 47.07%] [G loss: 0.728193]
8/8 [==============================] - 0s 5ms/step
7387 [D loss: 0.691274, acc.: 50.98%] [G loss: 0.730628]
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7388 [D loss: 0.691164, acc.: 53.12%] [G loss: 0.729118]
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7389 [D loss: 0.683956, acc.: 56.05%] [G loss: 0.730478]
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7390 [D loss: 0.686131, acc.: 54.10%] [G loss: 0.731609]
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7391 [D loss: 0.686804, acc.: 52.54%] [G loss: 0.728765]
8/8 [==============================] - 0s 5ms/step
7392 [D loss: 0.690631, acc.: 52.15%] [G loss: 0.718820]
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7393 [D loss: 0.688894, acc.: 53.32%] [G loss: 0.728363]
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7394 [D loss: 0.691609, acc.: 47.66%] [G loss: 0.716643]
8/8 [==============================] - 0s 5ms/step
7395 [D loss: 0.693350, acc.: 51.95%] [G loss: 0.711581]
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7396 [D loss: 0.693572, acc.: 47.27%] [G loss: 0.718593]
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7397 [D loss: 0.693294, acc.: 49.02%] [G loss: 0.718330]
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7398 [D loss: 0.694108, acc.: 48.63%] [G loss: 0.717166]
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7399 [D loss: 0.692526, acc.: 52.54%] [G loss: 0.714741]
8/8 [==============================] - 0s 5ms/step
7400 [D loss: 0.698776, acc.: 41.80%] [G loss: 0.711769]
1/1 [==============================] - 0s 17ms/step
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7401 [D loss: 0.695362, acc.: 46.09%] [G loss: 0.709849]
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7402 [D loss: 0.698048, acc.: 44.73%] [G loss: 0.710675]
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7403 [D loss: 0.692226, acc.: 48.05%] [G loss: 0.706960]
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7404 [D loss: 0.697107, acc.: 47.85%] [G loss: 0.708745]
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7405 [D loss: 0.689608, acc.: 50.59%] [G loss: 0.708819]
8/8 [==============================] - 0s 5ms/step
7406 [D loss: 0.693089, acc.: 49.41%] [G loss: 0.710763]
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7407 [D loss: 0.692453, acc.: 50.59%] [G loss: 0.705492]
8/8 [==============================] - 0s 5ms/step
7408 [D loss: 0.690179, acc.: 51.95%] [G loss: 0.713266]
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7409 [D loss: 0.694711, acc.: 50.00%] [G loss: 0.716405]
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7410 [D loss: 0.691116, acc.: 50.20%] [G loss: 0.716097]
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7411 [D loss: 0.693281, acc.: 47.66%] [G loss: 0.726678]
8/8 [==============================] - 0s 5ms/step
7412 [D loss: 0.694439, acc.: 48.24%] [G loss: 0.721556]
8/8 [==============================] - 0s 5ms/step
7413 [D loss: 0.689458, acc.: 52.15%] [G loss: 0.714693]
8/8 [==============================] - 0s 5ms/step
7414 [D loss: 0.690296, acc.: 49.80%] [G loss: 0.715878]
8/8 [==============================] - 0s 5ms/step
7415 [D loss: 0.690655, acc.: 48.83%] [G loss: 0.714371]
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7416 [D loss: 0.689211, acc.: 51.37%] [G loss: 0.717257]
8/8 [==============================] - 0s 5ms/step
7417 [D loss: 0.693462, acc.: 47.66%] [G loss: 0.714409]
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7418 [D loss: 0.690847, acc.: 50.98%] [G loss: 0.715024]
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7419 [D loss: 0.692722, acc.: 49.80%] [G loss: 0.712902]
8/8 [==============================] - 0s 5ms/step
7420 [D loss: 0.690970, acc.: 53.52%] [G loss: 0.720841]
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7421 [D loss: 0.690803, acc.: 49.22%] [G loss: 0.730636]
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7422 [D loss: 0.692755, acc.: 50.59%] [G loss: 0.740320]
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7423 [D loss: 0.684498, acc.: 51.37%] [G loss: 0.746353]
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7424 [D loss: 0.694792, acc.: 46.68%] [G loss: 0.745722]
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7425 [D loss: 0.697467, acc.: 46.48%] [G loss: 0.719803]
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7426 [D loss: 0.693257, acc.: 49.80%] [G loss: 0.720161]
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7427 [D loss: 0.691365, acc.: 50.00%] [G loss: 0.720439]
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7428 [D loss: 0.695376, acc.: 45.70%] [G loss: 0.715169]
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7429 [D loss: 0.696076, acc.: 47.27%] [G loss: 0.704983]
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7430 [D loss: 0.692202, acc.: 46.48%] [G loss: 0.716681]
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7431 [D loss: 0.687704, acc.: 53.52%] [G loss: 0.720718]
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7432 [D loss: 0.688723, acc.: 51.37%] [G loss: 0.734957]
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7433 [D loss: 0.678119, acc.: 56.64%] [G loss: 0.760296]
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7434 [D loss: 0.687365, acc.: 51.56%] [G loss: 0.742298]
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7435 [D loss: 0.691888, acc.: 50.00%] [G loss: 0.736255]
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7436 [D loss: 0.694420, acc.: 48.83%] [G loss: 0.710010]
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7437 [D loss: 0.695485, acc.: 50.39%] [G loss: 0.707373]
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7438 [D loss: 0.690678, acc.: 49.80%] [G loss: 0.705292]
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7439 [D loss: 0.690085, acc.: 50.59%] [G loss: 0.693807]
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7440 [D loss: 0.699593, acc.: 47.07%] [G loss: 0.680843]
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7441 [D loss: 0.698286, acc.: 45.51%] [G loss: 0.676658]
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7442 [D loss: 0.699309, acc.: 45.90%] [G loss: 0.686304]
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7443 [D loss: 0.698827, acc.: 44.34%] [G loss: 0.719458]
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7444 [D loss: 0.691640, acc.: 48.24%] [G loss: 0.732402]
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7445 [D loss: 0.690342, acc.: 47.27%] [G loss: 0.743832]
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7446 [D loss: 0.689738, acc.: 47.27%] [G loss: 0.745846]
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7447 [D loss: 0.697735, acc.: 43.55%] [G loss: 0.741582]
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7448 [D loss: 0.688078, acc.: 50.59%] [G loss: 0.732556]
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7449 [D loss: 0.688016, acc.: 50.78%] [G loss: 0.732154]
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7450 [D loss: 0.688870, acc.: 48.24%] [G loss: 0.733178]
1/1 [==============================] - 0s 17ms/step
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7451 [D loss: 0.690176, acc.: 52.93%] [G loss: 0.733838]
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7452 [D loss: 0.689971, acc.: 50.20%] [G loss: 0.724824]
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7453 [D loss: 0.697177, acc.: 43.36%] [G loss: 0.697216]
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7454 [D loss: 0.694436, acc.: 45.12%] [G loss: 0.693480]
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7455 [D loss: 0.693766, acc.: 43.55%] [G loss: 0.690604]
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7456 [D loss: 0.687176, acc.: 50.98%] [G loss: 0.715279]
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7457 [D loss: 0.686469, acc.: 52.34%] [G loss: 0.738282]
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7458 [D loss: 0.688087, acc.: 54.69%] [G loss: 0.735881]
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7459 [D loss: 0.695246, acc.: 49.61%] [G loss: 0.723624]
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7460 [D loss: 0.687738, acc.: 50.00%] [G loss: 0.716804]
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7461 [D loss: 0.696039, acc.: 45.90%] [G loss: 0.724396]
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7462 [D loss: 0.695816, acc.: 51.76%] [G loss: 0.726050]
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7463 [D loss: 0.689400, acc.: 53.12%] [G loss: 0.720962]
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7464 [D loss: 0.697036, acc.: 43.16%] [G loss: 0.693737]
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7465 [D loss: 0.703235, acc.: 45.12%] [G loss: 0.685223]
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7466 [D loss: 0.705205, acc.: 44.92%] [G loss: 0.695729]
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7467 [D loss: 0.697131, acc.: 51.76%] [G loss: 0.725912]
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7468 [D loss: 0.691796, acc.: 52.15%] [G loss: 0.735043]
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7469 [D loss: 0.695451, acc.: 48.24%] [G loss: 0.750979]
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7470 [D loss: 0.695903, acc.: 49.41%] [G loss: 0.740902]
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7471 [D loss: 0.699968, acc.: 44.53%] [G loss: 0.730330]
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7472 [D loss: 0.695119, acc.: 48.83%] [G loss: 0.718636]
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7473 [D loss: 0.699353, acc.: 46.29%] [G loss: 0.713476]
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7474 [D loss: 0.691456, acc.: 48.63%] [G loss: 0.718364]
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7475 [D loss: 0.689278, acc.: 52.93%] [G loss: 0.711289]
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7476 [D loss: 0.695920, acc.: 47.27%] [G loss: 0.697335]
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7477 [D loss: 0.703180, acc.: 43.55%] [G loss: 0.694585]
8/8 [==============================] - 0s 5ms/step
7478 [D loss: 0.702474, acc.: 41.21%] [G loss: 0.700696]
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7479 [D loss: 0.695425, acc.: 48.24%] [G loss: 0.727286]
8/8 [==============================] - 0s 5ms/step
7480 [D loss: 0.688246, acc.: 49.80%] [G loss: 0.752058]
8/8 [==============================] - 0s 5ms/step
7481 [D loss: 0.688131, acc.: 50.20%] [G loss: 0.746717]
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7482 [D loss: 0.691422, acc.: 50.59%] [G loss: 0.742765]
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7483 [D loss: 0.692301, acc.: 47.85%] [G loss: 0.728111]
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7484 [D loss: 0.690448, acc.: 55.27%] [G loss: 0.738388]
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7485 [D loss: 0.692347, acc.: 49.22%] [G loss: 0.724579]
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7486 [D loss: 0.687840, acc.: 55.27%] [G loss: 0.716381]
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7487 [D loss: 0.691814, acc.: 51.95%] [G loss: 0.711260]
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7488 [D loss: 0.699418, acc.: 45.90%] [G loss: 0.700150]
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7489 [D loss: 0.698187, acc.: 48.05%] [G loss: 0.696330]
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7490 [D loss: 0.692852, acc.: 49.80%] [G loss: 0.710748]
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7491 [D loss: 0.690272, acc.: 50.39%] [G loss: 0.706009]
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7492 [D loss: 0.688267, acc.: 48.83%] [G loss: 0.726165]
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7493 [D loss: 0.693915, acc.: 46.29%] [G loss: 0.735003]
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7494 [D loss: 0.693913, acc.: 43.55%] [G loss: 0.719945]
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7495 [D loss: 0.695839, acc.: 45.70%] [G loss: 0.727965]
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7496 [D loss: 0.695438, acc.: 44.14%] [G loss: 0.727951]
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7497 [D loss: 0.690533, acc.: 52.54%] [G loss: 0.733966]
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7498 [D loss: 0.687089, acc.: 55.47%] [G loss: 0.738188]
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7499 [D loss: 0.679904, acc.: 59.57%] [G loss: 0.747380]
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7500 [D loss: 0.682664, acc.: 55.27%] [G loss: 0.727848]
1/1 [==============================] - 0s 20ms/step
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7501 [D loss: 0.691224, acc.: 51.37%] [G loss: 0.716053]
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7502 [D loss: 0.690004, acc.: 54.10%] [G loss: 0.711352]
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7503 [D loss: 0.696238, acc.: 48.83%] [G loss: 0.695120]
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7504 [D loss: 0.695046, acc.: 45.70%] [G loss: 0.700170]
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7505 [D loss: 0.700773, acc.: 44.53%] [G loss: 0.702051]
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7506 [D loss: 0.691741, acc.: 48.44%] [G loss: 0.699976]
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7507 [D loss: 0.692780, acc.: 43.75%] [G loss: 0.701421]
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7508 [D loss: 0.703513, acc.: 40.23%] [G loss: 0.689987]
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7509 [D loss: 0.698253, acc.: 45.12%] [G loss: 0.696136]
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7510 [D loss: 0.697438, acc.: 46.48%] [G loss: 0.712900]
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7511 [D loss: 0.690974, acc.: 49.80%] [G loss: 0.721515]
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7512 [D loss: 0.678869, acc.: 56.84%] [G loss: 0.739097]
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7513 [D loss: 0.680528, acc.: 58.40%] [G loss: 0.749685]
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7514 [D loss: 0.676958, acc.: 57.42%] [G loss: 0.765785]
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7515 [D loss: 0.686707, acc.: 51.56%] [G loss: 0.744869]
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7516 [D loss: 0.683712, acc.: 52.73%] [G loss: 0.741589]
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7517 [D loss: 0.693948, acc.: 47.85%] [G loss: 0.727261]
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7518 [D loss: 0.698551, acc.: 45.90%] [G loss: 0.725278]
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7519 [D loss: 0.691579, acc.: 46.68%] [G loss: 0.717535]
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7520 [D loss: 0.692883, acc.: 47.07%] [G loss: 0.704529]
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7521 [D loss: 0.704148, acc.: 42.58%] [G loss: 0.694303]
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7522 [D loss: 0.696814, acc.: 44.34%] [G loss: 0.704253]
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7523 [D loss: 0.701668, acc.: 38.48%] [G loss: 0.716533]
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7524 [D loss: 0.701645, acc.: 47.46%] [G loss: 0.743185]
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7525 [D loss: 0.692488, acc.: 55.08%] [G loss: 0.740462]
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7526 [D loss: 0.686910, acc.: 53.32%] [G loss: 0.760397]
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7527 [D loss: 0.690621, acc.: 52.54%] [G loss: 0.742366]
8/8 [==============================] - 0s 5ms/step
7528 [D loss: 0.698134, acc.: 46.68%] [G loss: 0.727404]
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7529 [D loss: 0.696330, acc.: 48.24%] [G loss: 0.712006]
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7530 [D loss: 0.693504, acc.: 46.88%] [G loss: 0.712581]
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7531 [D loss: 0.693021, acc.: 50.20%] [G loss: 0.704353]
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7532 [D loss: 0.691666, acc.: 50.98%] [G loss: 0.705719]
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7533 [D loss: 0.700531, acc.: 45.90%] [G loss: 0.690739]
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7534 [D loss: 0.688953, acc.: 49.80%] [G loss: 0.698760]
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7535 [D loss: 0.699470, acc.: 45.31%] [G loss: 0.715813]
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7536 [D loss: 0.691028, acc.: 45.70%] [G loss: 0.734788]
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7537 [D loss: 0.690961, acc.: 50.00%] [G loss: 0.741428]
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7538 [D loss: 0.692779, acc.: 50.39%] [G loss: 0.755175]
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7539 [D loss: 0.696658, acc.: 46.09%] [G loss: 0.751905]
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7540 [D loss: 0.703400, acc.: 46.48%] [G loss: 0.734589]
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7541 [D loss: 0.695412, acc.: 49.61%] [G loss: 0.735447]
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7542 [D loss: 0.694571, acc.: 53.32%] [G loss: 0.734725]
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7543 [D loss: 0.688669, acc.: 55.47%] [G loss: 0.746182]
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7544 [D loss: 0.690055, acc.: 51.76%] [G loss: 0.713050]
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7545 [D loss: 0.702991, acc.: 44.34%] [G loss: 0.711258]
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7546 [D loss: 0.700341, acc.: 46.68%] [G loss: 0.714686]
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7547 [D loss: 0.693523, acc.: 48.63%] [G loss: 0.723946]
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7548 [D loss: 0.686457, acc.: 55.86%] [G loss: 0.740876]
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7549 [D loss: 0.690815, acc.: 52.93%] [G loss: 0.749627]
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7550 [D loss: 0.693838, acc.: 53.52%] [G loss: 0.743278]
1/1 [==============================] - 0s 17ms/step
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7551 [D loss: 0.689048, acc.: 55.86%] [G loss: 0.734319]
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7552 [D loss: 0.702187, acc.: 46.88%] [G loss: 0.729682]
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7553 [D loss: 0.688578, acc.: 54.88%] [G loss: 0.731127]
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7554 [D loss: 0.687658, acc.: 53.71%] [G loss: 0.729532]
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7555 [D loss: 0.691786, acc.: 54.10%] [G loss: 0.725522]
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7556 [D loss: 0.696061, acc.: 50.00%] [G loss: 0.712852]
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7557 [D loss: 0.710247, acc.: 38.67%] [G loss: 0.710390]
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7558 [D loss: 0.702139, acc.: 45.90%] [G loss: 0.722152]
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7559 [D loss: 0.687975, acc.: 51.95%] [G loss: 0.747036]
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7560 [D loss: 0.684133, acc.: 51.95%] [G loss: 0.754242]
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7561 [D loss: 0.695179, acc.: 45.51%] [G loss: 0.743429]
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7562 [D loss: 0.687319, acc.: 53.32%] [G loss: 0.742358]
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7563 [D loss: 0.691318, acc.: 51.76%] [G loss: 0.738805]
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7564 [D loss: 0.675948, acc.: 58.98%] [G loss: 0.740667]
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7565 [D loss: 0.694779, acc.: 50.39%] [G loss: 0.734309]
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7566 [D loss: 0.685971, acc.: 53.12%] [G loss: 0.723512]
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7567 [D loss: 0.683192, acc.: 51.95%] [G loss: 0.712277]
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7568 [D loss: 0.686220, acc.: 49.80%] [G loss: 0.706323]
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7569 [D loss: 0.687643, acc.: 49.61%] [G loss: 0.698588]
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7570 [D loss: 0.692584, acc.: 49.22%] [G loss: 0.701785]
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7571 [D loss: 0.692312, acc.: 47.66%] [G loss: 0.701115]
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7572 [D loss: 0.700568, acc.: 47.27%] [G loss: 0.706980]
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7573 [D loss: 0.691809, acc.: 47.27%] [G loss: 0.713341]
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7574 [D loss: 0.687987, acc.: 47.85%] [G loss: 0.714338]
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7575 [D loss: 0.688086, acc.: 49.02%] [G loss: 0.717619]
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7576 [D loss: 0.690870, acc.: 48.83%] [G loss: 0.714847]
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7577 [D loss: 0.694384, acc.: 47.27%] [G loss: 0.719451]
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7578 [D loss: 0.691802, acc.: 49.41%] [G loss: 0.718018]
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7579 [D loss: 0.690831, acc.: 47.27%] [G loss: 0.715686]
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7580 [D loss: 0.684107, acc.: 49.80%] [G loss: 0.721106]
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7581 [D loss: 0.689632, acc.: 50.20%] [G loss: 0.721661]
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7582 [D loss: 0.687933, acc.: 48.63%] [G loss: 0.714091]
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7583 [D loss: 0.696700, acc.: 44.34%] [G loss: 0.712609]
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7584 [D loss: 0.687038, acc.: 48.24%] [G loss: 0.706045]
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7585 [D loss: 0.691569, acc.: 44.92%] [G loss: 0.707992]
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7586 [D loss: 0.689393, acc.: 46.88%] [G loss: 0.711211]
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7587 [D loss: 0.680039, acc.: 51.17%] [G loss: 0.724493]
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7588 [D loss: 0.682573, acc.: 52.34%] [G loss: 0.722659]
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7589 [D loss: 0.680615, acc.: 51.95%] [G loss: 0.729167]
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7590 [D loss: 0.688618, acc.: 51.56%] [G loss: 0.723863]
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7591 [D loss: 0.692248, acc.: 49.80%] [G loss: 0.721251]
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7592 [D loss: 0.685228, acc.: 52.34%] [G loss: 0.721809]
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7593 [D loss: 0.678302, acc.: 51.56%] [G loss: 0.720079]
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7594 [D loss: 0.683500, acc.: 54.69%] [G loss: 0.722809]
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7595 [D loss: 0.678843, acc.: 53.71%] [G loss: 0.715937]
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7596 [D loss: 0.677763, acc.: 52.15%] [G loss: 0.711953]
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7597 [D loss: 0.678742, acc.: 52.15%] [G loss: 0.708975]
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7598 [D loss: 0.697127, acc.: 46.09%] [G loss: 0.715549]
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7599 [D loss: 0.690172, acc.: 47.85%] [G loss: 0.716629]
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7600 [D loss: 0.684486, acc.: 48.05%] [G loss: 0.720856]
1/1 [==============================] - 0s 17ms/step
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7601 [D loss: 0.684463, acc.: 51.17%] [G loss: 0.732128]
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7602 [D loss: 0.688317, acc.: 47.85%] [G loss: 0.718511]
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7603 [D loss: 0.691217, acc.: 48.05%] [G loss: 0.729647]
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7604 [D loss: 0.674947, acc.: 51.37%] [G loss: 0.728552]
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7605 [D loss: 0.688068, acc.: 48.63%] [G loss: 0.724815]
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7606 [D loss: 0.679627, acc.: 50.20%] [G loss: 0.719611]
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7607 [D loss: 0.689262, acc.: 50.78%] [G loss: 0.720971]
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7608 [D loss: 0.698313, acc.: 45.90%] [G loss: 0.724685]
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7609 [D loss: 0.685082, acc.: 49.02%] [G loss: 0.722804]
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7610 [D loss: 0.692883, acc.: 45.51%] [G loss: 0.720374]
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7611 [D loss: 0.688870, acc.: 48.83%] [G loss: 0.723080]
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7612 [D loss: 0.684948, acc.: 47.85%] [G loss: 0.728892]
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7613 [D loss: 0.682677, acc.: 51.17%] [G loss: 0.727905]
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7614 [D loss: 0.684859, acc.: 49.61%] [G loss: 0.725871]
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7615 [D loss: 0.683334, acc.: 50.98%] [G loss: 0.724356]
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7616 [D loss: 0.688890, acc.: 48.05%] [G loss: 0.722048]
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7617 [D loss: 0.687078, acc.: 51.95%] [G loss: 0.722134]
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7618 [D loss: 0.680194, acc.: 49.61%] [G loss: 0.718720]
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7619 [D loss: 0.685133, acc.: 46.68%] [G loss: 0.719481]
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7620 [D loss: 0.685468, acc.: 50.00%] [G loss: 0.713258]
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7621 [D loss: 0.690508, acc.: 42.19%] [G loss: 0.714491]
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7622 [D loss: 0.684541, acc.: 49.02%] [G loss: 0.713459]
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7623 [D loss: 0.688767, acc.: 48.24%] [G loss: 0.724544]
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7624 [D loss: 0.685479, acc.: 50.98%] [G loss: 0.731177]
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7625 [D loss: 0.681663, acc.: 49.02%] [G loss: 0.737142]
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7626 [D loss: 0.683632, acc.: 49.22%] [G loss: 0.738158]
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7627 [D loss: 0.687586, acc.: 48.83%] [G loss: 0.737953]
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7628 [D loss: 0.682047, acc.: 53.12%] [G loss: 0.734635]
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7629 [D loss: 0.685830, acc.: 48.83%] [G loss: 0.729477]
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7630 [D loss: 0.683664, acc.: 49.22%] [G loss: 0.723557]
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7631 [D loss: 0.685520, acc.: 49.61%] [G loss: 0.723324]
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7632 [D loss: 0.680268, acc.: 51.56%] [G loss: 0.718847]
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7633 [D loss: 0.685279, acc.: 50.59%] [G loss: 0.724940]
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7634 [D loss: 0.675221, acc.: 52.93%] [G loss: 0.720782]
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7635 [D loss: 0.689565, acc.: 49.41%] [G loss: 0.719110]
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7636 [D loss: 0.682403, acc.: 52.93%] [G loss: 0.733098]
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7637 [D loss: 0.679621, acc.: 51.37%] [G loss: 0.731058]
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7638 [D loss: 0.686615, acc.: 51.95%] [G loss: 0.722359]
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7639 [D loss: 0.686729, acc.: 49.61%] [G loss: 0.722361]
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7640 [D loss: 0.681268, acc.: 51.37%] [G loss: 0.731588]
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7641 [D loss: 0.690059, acc.: 47.66%] [G loss: 0.724594]
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7642 [D loss: 0.684805, acc.: 51.76%] [G loss: 0.722467]
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7643 [D loss: 0.679627, acc.: 50.00%] [G loss: 0.722361]
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7644 [D loss: 0.688135, acc.: 47.85%] [G loss: 0.715861]
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7645 [D loss: 0.687280, acc.: 48.05%] [G loss: 0.714161]
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7646 [D loss: 0.684209, acc.: 50.20%] [G loss: 0.728664]
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7647 [D loss: 0.685209, acc.: 49.41%] [G loss: 0.716488]
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7648 [D loss: 0.689287, acc.: 48.63%] [G loss: 0.722047]
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7649 [D loss: 0.675156, acc.: 50.20%] [G loss: 0.727457]
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7650 [D loss: 0.683115, acc.: 48.24%] [G loss: 0.730096]
1/1 [==============================] - 0s 21ms/step
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7651 [D loss: 0.698886, acc.: 44.73%] [G loss: 0.733654]
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7652 [D loss: 0.686063, acc.: 49.61%] [G loss: 0.730852]
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7653 [D loss: 0.693337, acc.: 50.39%] [G loss: 0.732166]
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7654 [D loss: 0.679999, acc.: 51.56%] [G loss: 0.736340]
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7655 [D loss: 0.680649, acc.: 47.85%] [G loss: 0.730532]
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7656 [D loss: 0.689398, acc.: 46.88%] [G loss: 0.718688]
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7657 [D loss: 0.679961, acc.: 49.41%] [G loss: 0.718267]
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7658 [D loss: 0.685396, acc.: 49.41%] [G loss: 0.720736]
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7659 [D loss: 0.689325, acc.: 46.88%] [G loss: 0.721437]
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7660 [D loss: 0.685278, acc.: 50.59%] [G loss: 0.723840]
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7661 [D loss: 0.682924, acc.: 51.95%] [G loss: 0.730038]
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7662 [D loss: 0.683218, acc.: 53.32%] [G loss: 0.735319]
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7663 [D loss: 0.683206, acc.: 51.76%] [G loss: 0.722783]
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7664 [D loss: 0.692593, acc.: 49.41%] [G loss: 0.725947]
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7665 [D loss: 0.688133, acc.: 46.88%] [G loss: 0.715790]
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7666 [D loss: 0.691103, acc.: 44.73%] [G loss: 0.712826]
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7667 [D loss: 0.686335, acc.: 48.05%] [G loss: 0.714341]
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7668 [D loss: 0.694014, acc.: 46.09%] [G loss: 0.712167]
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7669 [D loss: 0.685478, acc.: 46.68%] [G loss: 0.720886]
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7670 [D loss: 0.682951, acc.: 48.63%] [G loss: 0.719710]
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7671 [D loss: 0.683938, acc.: 48.44%] [G loss: 0.728485]
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7672 [D loss: 0.680928, acc.: 49.61%] [G loss: 0.732204]
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7673 [D loss: 0.677116, acc.: 51.56%] [G loss: 0.733282]
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7674 [D loss: 0.681350, acc.: 50.00%] [G loss: 0.730099]
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7675 [D loss: 0.680075, acc.: 51.37%] [G loss: 0.739845]
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7676 [D loss: 0.680517, acc.: 52.34%] [G loss: 0.733008]
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7677 [D loss: 0.683942, acc.: 52.93%] [G loss: 0.724341]
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7678 [D loss: 0.680208, acc.: 50.00%] [G loss: 0.725086]
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7679 [D loss: 0.685840, acc.: 50.00%] [G loss: 0.721971]
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7680 [D loss: 0.689458, acc.: 47.85%] [G loss: 0.724671]
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7681 [D loss: 0.690118, acc.: 46.09%] [G loss: 0.716966]
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7682 [D loss: 0.691563, acc.: 45.31%] [G loss: 0.721168]
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7683 [D loss: 0.682755, acc.: 50.20%] [G loss: 0.730985]
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7684 [D loss: 0.683297, acc.: 47.27%] [G loss: 0.728401]
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7685 [D loss: 0.685087, acc.: 52.54%] [G loss: 0.735585]
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7686 [D loss: 0.682066, acc.: 48.83%] [G loss: 0.736079]
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7687 [D loss: 0.691463, acc.: 46.68%] [G loss: 0.730273]
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7688 [D loss: 0.686465, acc.: 50.39%] [G loss: 0.728970]
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7689 [D loss: 0.684120, acc.: 51.76%] [G loss: 0.724453]
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7690 [D loss: 0.680067, acc.: 52.15%] [G loss: 0.727191]
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7691 [D loss: 0.683099, acc.: 50.98%] [G loss: 0.717672]
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7692 [D loss: 0.689005, acc.: 46.68%] [G loss: 0.722870]
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7693 [D loss: 0.696794, acc.: 43.75%] [G loss: 0.703437]
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7694 [D loss: 0.707210, acc.: 47.66%] [G loss: 0.696515]
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7695 [D loss: 0.710101, acc.: 43.16%] [G loss: 0.721803]
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7696 [D loss: 0.697292, acc.: 51.17%] [G loss: 0.727465]
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7697 [D loss: 0.696295, acc.: 43.36%] [G loss: 0.738489]
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7698 [D loss: 0.694971, acc.: 45.31%] [G loss: 0.748413]
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7699 [D loss: 0.697189, acc.: 43.55%] [G loss: 0.738446]
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7700 [D loss: 0.699716, acc.: 47.07%] [G loss: 0.724060]
1/1 [==============================] - 0s 18ms/step
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7701 [D loss: 0.696144, acc.: 51.56%] [G loss: 0.734430]
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7702 [D loss: 0.700147, acc.: 42.58%] [G loss: 0.727222]
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7703 [D loss: 0.693101, acc.: 46.88%] [G loss: 0.726072]
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7704 [D loss: 0.694289, acc.: 48.05%] [G loss: 0.735484]
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7705 [D loss: 0.691017, acc.: 52.73%] [G loss: 0.745848]
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7706 [D loss: 0.691060, acc.: 48.63%] [G loss: 0.746210]
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7707 [D loss: 0.690946, acc.: 51.17%] [G loss: 0.747528]
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7708 [D loss: 0.689740, acc.: 50.78%] [G loss: 0.736919]
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7709 [D loss: 0.685185, acc.: 56.45%] [G loss: 0.741846]
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7710 [D loss: 0.681502, acc.: 56.25%] [G loss: 0.743601]
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7711 [D loss: 0.683985, acc.: 57.23%] [G loss: 0.734460]
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7712 [D loss: 0.694622, acc.: 44.53%] [G loss: 0.707740]
8/8 [==============================] - 0s 5ms/step
7713 [D loss: 0.695852, acc.: 47.66%] [G loss: 0.701234]
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7714 [D loss: 0.703031, acc.: 44.92%] [G loss: 0.700968]
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7715 [D loss: 0.694016, acc.: 43.95%] [G loss: 0.706396]
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7716 [D loss: 0.702576, acc.: 44.53%] [G loss: 0.723030]
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7717 [D loss: 0.695193, acc.: 45.90%] [G loss: 0.749086]
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7718 [D loss: 0.696087, acc.: 48.24%] [G loss: 0.738631]
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7719 [D loss: 0.694226, acc.: 53.32%] [G loss: 0.737022]
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7720 [D loss: 0.686595, acc.: 55.66%] [G loss: 0.744514]
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7721 [D loss: 0.691908, acc.: 53.32%] [G loss: 0.735113]
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7722 [D loss: 0.692201, acc.: 52.15%] [G loss: 0.718446]
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7723 [D loss: 0.688847, acc.: 54.10%] [G loss: 0.698824]
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7724 [D loss: 0.693288, acc.: 47.85%] [G loss: 0.696039]
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7725 [D loss: 0.698714, acc.: 47.85%] [G loss: 0.706381]
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7726 [D loss: 0.692638, acc.: 46.68%] [G loss: 0.704740]
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7727 [D loss: 0.691666, acc.: 50.78%] [G loss: 0.718589]
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7728 [D loss: 0.690929, acc.: 51.37%] [G loss: 0.720865]
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7729 [D loss: 0.692777, acc.: 48.83%] [G loss: 0.733776]
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7730 [D loss: 0.688410, acc.: 52.93%] [G loss: 0.732927]
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7731 [D loss: 0.693444, acc.: 45.31%] [G loss: 0.741675]
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7732 [D loss: 0.689761, acc.: 47.66%] [G loss: 0.729731]
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7733 [D loss: 0.680770, acc.: 52.73%] [G loss: 0.735427]
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7734 [D loss: 0.682897, acc.: 54.69%] [G loss: 0.722072]
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7735 [D loss: 0.684681, acc.: 53.71%] [G loss: 0.719134]
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7736 [D loss: 0.688133, acc.: 51.37%] [G loss: 0.713635]
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7737 [D loss: 0.687384, acc.: 50.59%] [G loss: 0.715426]
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7738 [D loss: 0.694842, acc.: 47.07%] [G loss: 0.717527]
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7739 [D loss: 0.685771, acc.: 52.54%] [G loss: 0.724392]
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7740 [D loss: 0.697024, acc.: 52.93%] [G loss: 0.748546]
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7741 [D loss: 0.723681, acc.: 48.63%] [G loss: 0.746846]
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7742 [D loss: 0.692773, acc.: 49.22%] [G loss: 0.746200]
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7743 [D loss: 0.693159, acc.: 47.27%] [G loss: 0.753419]
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7744 [D loss: 0.690061, acc.: 48.24%] [G loss: 0.746100]
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7745 [D loss: 0.698537, acc.: 46.88%] [G loss: 0.725620]
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7746 [D loss: 0.703695, acc.: 45.51%] [G loss: 0.719610]
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7747 [D loss: 0.701347, acc.: 41.60%] [G loss: 0.735041]
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7748 [D loss: 0.693681, acc.: 50.98%] [G loss: 0.719522]
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7749 [D loss: 0.692636, acc.: 52.54%] [G loss: 0.734345]
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7750 [D loss: 0.692673, acc.: 50.78%] [G loss: 0.739805]
1/1 [==============================] - 0s 18ms/step
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7751 [D loss: 0.686241, acc.: 52.73%] [G loss: 0.752298]
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7752 [D loss: 0.687588, acc.: 52.73%] [G loss: 0.748256]
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7753 [D loss: 0.687649, acc.: 53.91%] [G loss: 0.743566]
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7754 [D loss: 0.689537, acc.: 51.56%] [G loss: 0.732850]
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7755 [D loss: 0.695974, acc.: 47.66%] [G loss: 0.716833]
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7756 [D loss: 0.698834, acc.: 48.24%] [G loss: 0.716122]
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7757 [D loss: 0.700888, acc.: 42.77%] [G loss: 0.710319]
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7758 [D loss: 0.706393, acc.: 39.26%] [G loss: 0.709909]
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7759 [D loss: 0.705892, acc.: 37.11%] [G loss: 0.701901]
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7760 [D loss: 0.699851, acc.: 39.26%] [G loss: 0.712820]
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7761 [D loss: 0.697991, acc.: 40.04%] [G loss: 0.726949]
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7762 [D loss: 0.692854, acc.: 47.27%] [G loss: 0.731131]
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7763 [D loss: 0.684205, acc.: 56.05%] [G loss: 0.734990]
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7764 [D loss: 0.686829, acc.: 49.02%] [G loss: 0.750563]
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7765 [D loss: 0.690512, acc.: 48.63%] [G loss: 0.726963]
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7766 [D loss: 0.682805, acc.: 54.88%] [G loss: 0.718371]
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7767 [D loss: 0.692038, acc.: 51.76%] [G loss: 0.713419]
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7768 [D loss: 0.687868, acc.: 50.00%] [G loss: 0.710393]
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7769 [D loss: 0.688072, acc.: 50.20%] [G loss: 0.708847]
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7770 [D loss: 0.692114, acc.: 47.46%] [G loss: 0.709421]
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7771 [D loss: 0.694883, acc.: 47.07%] [G loss: 0.713059]
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7772 [D loss: 0.689648, acc.: 50.59%] [G loss: 0.720570]
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7773 [D loss: 0.689035, acc.: 51.56%] [G loss: 0.731084]
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7774 [D loss: 0.688526, acc.: 52.73%] [G loss: 0.744484]
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7775 [D loss: 0.678143, acc.: 55.27%] [G loss: 0.743543]
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7776 [D loss: 0.679658, acc.: 54.88%] [G loss: 0.751037]
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7777 [D loss: 0.680614, acc.: 50.78%] [G loss: 0.740568]
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7778 [D loss: 0.684556, acc.: 50.39%] [G loss: 0.733222]
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7779 [D loss: 0.690330, acc.: 49.80%] [G loss: 0.726798]
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7780 [D loss: 0.685921, acc.: 50.78%] [G loss: 0.724532]
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7781 [D loss: 0.680631, acc.: 51.37%] [G loss: 0.719778]
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7782 [D loss: 0.685979, acc.: 51.37%] [G loss: 0.709352]
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7783 [D loss: 0.699213, acc.: 44.14%] [G loss: 0.702100]
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7784 [D loss: 0.693380, acc.: 46.48%] [G loss: 0.706135]
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7785 [D loss: 0.703496, acc.: 44.53%] [G loss: 0.715550]
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7786 [D loss: 0.696368, acc.: 49.02%] [G loss: 0.730642]
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7787 [D loss: 0.693568, acc.: 49.61%] [G loss: 0.743737]
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7788 [D loss: 0.694091, acc.: 47.07%] [G loss: 0.743032]
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7789 [D loss: 0.689714, acc.: 46.88%] [G loss: 0.730604]
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7790 [D loss: 0.695117, acc.: 45.51%] [G loss: 0.729675]
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7791 [D loss: 0.688499, acc.: 49.61%] [G loss: 0.728921]
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7792 [D loss: 0.697984, acc.: 45.70%] [G loss: 0.715669]
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7793 [D loss: 0.699624, acc.: 45.12%] [G loss: 0.688908]
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7794 [D loss: 0.700983, acc.: 47.85%] [G loss: 0.684551]
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7795 [D loss: 0.702457, acc.: 46.09%] [G loss: 0.707095]
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7796 [D loss: 0.699208, acc.: 50.00%] [G loss: 0.707709]
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7797 [D loss: 0.694914, acc.: 52.34%] [G loss: 0.729677]
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7798 [D loss: 0.695610, acc.: 46.09%] [G loss: 0.736281]
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7799 [D loss: 0.688193, acc.: 49.22%] [G loss: 0.735074]
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7800 [D loss: 0.689132, acc.: 53.32%] [G loss: 0.728996]
1/1 [==============================] - 0s 19ms/step
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7801 [D loss: 0.689033, acc.: 50.20%] [G loss: 0.730059]
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7802 [D loss: 0.687471, acc.: 51.95%] [G loss: 0.724159]
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7803 [D loss: 0.686535, acc.: 56.45%] [G loss: 0.727842]
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7804 [D loss: 0.684854, acc.: 56.25%] [G loss: 0.724562]
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7805 [D loss: 0.694824, acc.: 47.46%] [G loss: 0.716885]
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7806 [D loss: 0.689920, acc.: 47.27%] [G loss: 0.708962]
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7807 [D loss: 0.694046, acc.: 45.70%] [G loss: 0.704716]
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7808 [D loss: 0.688442, acc.: 49.80%] [G loss: 0.723579]
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7809 [D loss: 0.689360, acc.: 51.17%] [G loss: 0.725952]
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7810 [D loss: 0.689882, acc.: 47.46%] [G loss: 0.740151]
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7811 [D loss: 0.682113, acc.: 53.91%] [G loss: 0.735025]
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7812 [D loss: 0.689752, acc.: 50.39%] [G loss: 0.741486]
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7813 [D loss: 0.684309, acc.: 49.80%] [G loss: 0.733730]
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7814 [D loss: 0.693146, acc.: 47.85%] [G loss: 0.723148]
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7815 [D loss: 0.682670, acc.: 49.61%] [G loss: 0.719528]
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7816 [D loss: 0.684701, acc.: 49.02%] [G loss: 0.716953]
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7817 [D loss: 0.691250, acc.: 48.24%] [G loss: 0.709588]
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7818 [D loss: 0.696537, acc.: 47.07%] [G loss: 0.710967]
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7819 [D loss: 0.692232, acc.: 45.31%] [G loss: 0.708343]
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7820 [D loss: 0.689010, acc.: 47.85%] [G loss: 0.711962]
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7821 [D loss: 0.688940, acc.: 45.31%] [G loss: 0.717781]
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7822 [D loss: 0.685723, acc.: 48.83%] [G loss: 0.721268]
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7823 [D loss: 0.685722, acc.: 50.59%] [G loss: 0.732095]
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7824 [D loss: 0.685079, acc.: 52.34%] [G loss: 0.731847]
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7825 [D loss: 0.683064, acc.: 51.76%] [G loss: 0.735422]
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7826 [D loss: 0.685947, acc.: 45.70%] [G loss: 0.731650]
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7827 [D loss: 0.682455, acc.: 51.37%] [G loss: 0.724659]
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7828 [D loss: 0.692074, acc.: 47.46%] [G loss: 0.729068]
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7829 [D loss: 0.684877, acc.: 48.63%] [G loss: 0.733863]
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7830 [D loss: 0.682546, acc.: 52.54%] [G loss: 0.729324]
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7831 [D loss: 0.683891, acc.: 50.39%] [G loss: 0.716617]
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7832 [D loss: 0.680299, acc.: 54.10%] [G loss: 0.725128]
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7833 [D loss: 0.686709, acc.: 50.39%] [G loss: 0.724741]
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7834 [D loss: 0.681434, acc.: 52.93%] [G loss: 0.730318]
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7835 [D loss: 0.684760, acc.: 50.39%] [G loss: 0.728101]
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7836 [D loss: 0.682487, acc.: 48.05%] [G loss: 0.733908]
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7837 [D loss: 0.686166, acc.: 46.09%] [G loss: 0.734910]
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7838 [D loss: 0.683421, acc.: 47.66%] [G loss: 0.730810]
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7839 [D loss: 0.685430, acc.: 46.88%] [G loss: 0.727293]
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7840 [D loss: 0.684895, acc.: 46.88%] [G loss: 0.724014]
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7841 [D loss: 0.686073, acc.: 49.02%] [G loss: 0.721136]
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7842 [D loss: 0.693673, acc.: 47.46%] [G loss: 0.718090]
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7843 [D loss: 0.705133, acc.: 50.00%] [G loss: 0.710712]
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7844 [D loss: 0.702909, acc.: 49.61%] [G loss: 0.711313]
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7845 [D loss: 0.697751, acc.: 48.83%] [G loss: 0.731982]
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7846 [D loss: 0.696426, acc.: 45.51%] [G loss: 0.729273]
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7847 [D loss: 0.694680, acc.: 51.17%] [G loss: 0.723831]
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7848 [D loss: 0.686780, acc.: 54.10%] [G loss: 0.720312]
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7849 [D loss: 0.699816, acc.: 46.29%] [G loss: 0.711425]
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7850 [D loss: 0.702690, acc.: 42.77%] [G loss: 0.711854]
1/1 [==============================] - 0s 18ms/step
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7851 [D loss: 0.702387, acc.: 47.07%] [G loss: 0.698914]
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7852 [D loss: 0.706001, acc.: 43.16%] [G loss: 0.696849]
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7853 [D loss: 0.696295, acc.: 45.90%] [G loss: 0.706464]
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7854 [D loss: 0.695114, acc.: 50.20%] [G loss: 0.714390]
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7855 [D loss: 0.696901, acc.: 44.34%] [G loss: 0.715195]
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7856 [D loss: 0.696004, acc.: 52.93%] [G loss: 0.717977]
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7857 [D loss: 0.692802, acc.: 51.17%] [G loss: 0.726317]
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7858 [D loss: 0.693064, acc.: 46.88%] [G loss: 0.726468]
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7859 [D loss: 0.695789, acc.: 48.83%] [G loss: 0.729739]
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7860 [D loss: 0.697204, acc.: 47.85%] [G loss: 0.735567]
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7861 [D loss: 0.690551, acc.: 49.61%] [G loss: 0.731569]
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7862 [D loss: 0.690183, acc.: 49.41%] [G loss: 0.729811]
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7863 [D loss: 0.689641, acc.: 50.59%] [G loss: 0.727105]
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7864 [D loss: 0.691269, acc.: 45.12%] [G loss: 0.729115]
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7865 [D loss: 0.689877, acc.: 49.22%] [G loss: 0.728694]
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7866 [D loss: 0.704068, acc.: 45.51%] [G loss: 0.706046]
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7867 [D loss: 0.700558, acc.: 47.07%] [G loss: 0.705637]
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7868 [D loss: 0.706155, acc.: 43.16%] [G loss: 0.725797]
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7869 [D loss: 0.690262, acc.: 52.73%] [G loss: 0.736640]
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7870 [D loss: 0.683530, acc.: 56.64%] [G loss: 0.738460]
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7871 [D loss: 0.688191, acc.: 51.95%] [G loss: 0.740488]
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7872 [D loss: 0.689737, acc.: 49.61%] [G loss: 0.744252]
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7873 [D loss: 0.680900, acc.: 53.71%] [G loss: 0.736152]
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7874 [D loss: 0.688344, acc.: 53.52%] [G loss: 0.721301]
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7875 [D loss: 0.693654, acc.: 51.17%] [G loss: 0.721847]
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7876 [D loss: 0.694193, acc.: 51.56%] [G loss: 0.715010]
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7877 [D loss: 0.700265, acc.: 47.27%] [G loss: 0.711862]
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7878 [D loss: 0.694669, acc.: 50.78%] [G loss: 0.724835]
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7879 [D loss: 0.699629, acc.: 48.63%] [G loss: 0.746640]
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7880 [D loss: 0.694715, acc.: 49.41%] [G loss: 0.744588]
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7881 [D loss: 0.690890, acc.: 50.00%] [G loss: 0.741264]
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7882 [D loss: 0.698211, acc.: 49.41%] [G loss: 0.728247]
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7883 [D loss: 0.695121, acc.: 48.63%] [G loss: 0.733569]
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7884 [D loss: 0.692747, acc.: 50.20%] [G loss: 0.719438]
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7885 [D loss: 0.694218, acc.: 48.24%] [G loss: 0.719908]
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7886 [D loss: 0.697047, acc.: 46.09%] [G loss: 0.713601]
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7887 [D loss: 0.695922, acc.: 45.70%] [G loss: 0.704426]
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7888 [D loss: 0.696779, acc.: 44.73%] [G loss: 0.707549]
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7889 [D loss: 0.701827, acc.: 48.44%] [G loss: 0.704500]
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7890 [D loss: 0.693371, acc.: 51.17%] [G loss: 0.716455]
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7891 [D loss: 0.693625, acc.: 49.61%] [G loss: 0.729724]
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7892 [D loss: 0.689048, acc.: 52.93%] [G loss: 0.737304]
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7893 [D loss: 0.689003, acc.: 52.15%] [G loss: 0.729420]
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7894 [D loss: 0.694688, acc.: 48.44%] [G loss: 0.728586]
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7895 [D loss: 0.690016, acc.: 51.17%] [G loss: 0.726603]
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7896 [D loss: 0.689435, acc.: 50.98%] [G loss: 0.726837]
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7897 [D loss: 0.684862, acc.: 54.49%] [G loss: 0.726672]
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7898 [D loss: 0.684882, acc.: 52.93%] [G loss: 0.721654]
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7899 [D loss: 0.693057, acc.: 46.68%] [G loss: 0.708174]
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7900 [D loss: 0.694969, acc.: 46.88%] [G loss: 0.706630]
1/1 [==============================] - 0s 18ms/step
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7901 [D loss: 0.683891, acc.: 48.24%] [G loss: 0.711725]
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7902 [D loss: 0.687437, acc.: 50.98%] [G loss: 0.729599]
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7903 [D loss: 0.685496, acc.: 50.59%] [G loss: 0.738669]
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7904 [D loss: 0.687609, acc.: 49.61%] [G loss: 0.737624]
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7905 [D loss: 0.676144, acc.: 52.73%] [G loss: 0.736082]
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7906 [D loss: 0.687403, acc.: 51.76%] [G loss: 0.733001]
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7907 [D loss: 0.689759, acc.: 50.59%] [G loss: 0.730514]
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7908 [D loss: 0.682390, acc.: 53.91%] [G loss: 0.740061]
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7909 [D loss: 0.688586, acc.: 49.61%] [G loss: 0.730712]
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7910 [D loss: 0.686040, acc.: 48.63%] [G loss: 0.727605]
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7911 [D loss: 0.691880, acc.: 48.05%] [G loss: 0.727247]
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7912 [D loss: 0.685429, acc.: 50.59%] [G loss: 0.725716]
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7913 [D loss: 0.678519, acc.: 50.20%] [G loss: 0.728398]
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7914 [D loss: 0.689542, acc.: 50.00%] [G loss: 0.731435]
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7915 [D loss: 0.685015, acc.: 43.75%] [G loss: 0.733201]
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7916 [D loss: 0.696391, acc.: 44.53%] [G loss: 0.721526]
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7917 [D loss: 0.705744, acc.: 40.82%] [G loss: 0.705386]
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7918 [D loss: 0.703666, acc.: 48.44%] [G loss: 0.711677]
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7919 [D loss: 0.692654, acc.: 51.17%] [G loss: 0.716921]
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7920 [D loss: 0.698689, acc.: 50.00%] [G loss: 0.711723]
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7921 [D loss: 0.692586, acc.: 48.44%] [G loss: 0.715820]
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7922 [D loss: 0.690090, acc.: 49.61%] [G loss: 0.724784]
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7923 [D loss: 0.684658, acc.: 51.76%] [G loss: 0.739607]
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7924 [D loss: 0.687880, acc.: 51.56%] [G loss: 0.721642]
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7925 [D loss: 0.689978, acc.: 51.17%] [G loss: 0.731675]
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7926 [D loss: 0.698207, acc.: 45.12%] [G loss: 0.706241]
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7927 [D loss: 0.698241, acc.: 43.95%] [G loss: 0.709292]
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7928 [D loss: 0.693358, acc.: 51.56%] [G loss: 0.710435]
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7929 [D loss: 0.694771, acc.: 45.90%] [G loss: 0.718531]
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7930 [D loss: 0.690236, acc.: 44.73%] [G loss: 0.705720]
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7931 [D loss: 0.688122, acc.: 48.44%] [G loss: 0.721208]
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7932 [D loss: 0.687634, acc.: 48.44%] [G loss: 0.724794]
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7933 [D loss: 0.690384, acc.: 47.27%] [G loss: 0.734998]
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7934 [D loss: 0.691990, acc.: 50.00%] [G loss: 0.730054]
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7935 [D loss: 0.693568, acc.: 46.88%] [G loss: 0.725992]
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7936 [D loss: 0.711549, acc.: 47.46%] [G loss: 0.712741]
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7937 [D loss: 0.699650, acc.: 46.48%] [G loss: 0.707801]
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7938 [D loss: 0.696668, acc.: 45.90%] [G loss: 0.708986]
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7939 [D loss: 0.709089, acc.: 45.70%] [G loss: 0.704133]
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7940 [D loss: 0.694155, acc.: 49.80%] [G loss: 0.703235]
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7941 [D loss: 0.691125, acc.: 52.54%] [G loss: 0.711835]
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7942 [D loss: 0.694384, acc.: 51.56%] [G loss: 0.715376]
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7943 [D loss: 0.697130, acc.: 47.07%] [G loss: 0.712834]
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7944 [D loss: 0.690880, acc.: 52.73%] [G loss: 0.716407]
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7945 [D loss: 0.698284, acc.: 48.83%] [G loss: 0.732274]
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7946 [D loss: 0.695179, acc.: 48.83%] [G loss: 0.723685]
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7947 [D loss: 0.689569, acc.: 50.20%] [G loss: 0.726466]
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7948 [D loss: 0.687376, acc.: 52.34%] [G loss: 0.727835]
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7949 [D loss: 0.688859, acc.: 50.39%] [G loss: 0.723541]
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7950 [D loss: 0.685374, acc.: 54.10%] [G loss: 0.728923]
1/1 [==============================] - 0s 18ms/step
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7951 [D loss: 0.686729, acc.: 52.93%] [G loss: 0.726623]
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7952 [D loss: 0.694401, acc.: 49.02%] [G loss: 0.720139]
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7953 [D loss: 0.696706, acc.: 48.44%] [G loss: 0.718199]
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7954 [D loss: 0.694362, acc.: 51.37%] [G loss: 0.709830]
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7955 [D loss: 0.692825, acc.: 46.68%] [G loss: 0.711230]
8/8 [==============================] - 0s 5ms/step
7956 [D loss: 0.699173, acc.: 44.14%] [G loss: 0.712912]
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7957 [D loss: 0.701030, acc.: 42.58%] [G loss: 0.723726]
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7958 [D loss: 0.695265, acc.: 48.83%] [G loss: 0.733234]
8/8 [==============================] - 0s 5ms/step
7959 [D loss: 0.689193, acc.: 50.39%] [G loss: 0.744463]
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7960 [D loss: 0.690717, acc.: 51.17%] [G loss: 0.737570]
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7961 [D loss: 0.694419, acc.: 50.78%] [G loss: 0.735573]
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7962 [D loss: 0.690067, acc.: 48.83%] [G loss: 0.734847]
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7963 [D loss: 0.685765, acc.: 53.91%] [G loss: 0.735151]
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7964 [D loss: 0.689201, acc.: 53.52%] [G loss: 0.727304]
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7965 [D loss: 0.692424, acc.: 46.48%] [G loss: 0.711983]
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7966 [D loss: 0.701010, acc.: 47.66%] [G loss: 0.700285]
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7967 [D loss: 0.698987, acc.: 44.92%] [G loss: 0.702794]
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7968 [D loss: 0.704479, acc.: 46.48%] [G loss: 0.711214]
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7969 [D loss: 0.704866, acc.: 41.99%] [G loss: 0.722558]
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7970 [D loss: 0.695852, acc.: 48.63%] [G loss: 0.720591]
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7971 [D loss: 0.697924, acc.: 46.09%] [G loss: 0.717033]
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7972 [D loss: 0.699958, acc.: 45.51%] [G loss: 0.722399]
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7973 [D loss: 0.690426, acc.: 51.76%] [G loss: 0.717514]
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7974 [D loss: 0.690963, acc.: 52.54%] [G loss: 0.717618]
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7975 [D loss: 0.691270, acc.: 52.93%] [G loss: 0.712836]
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7976 [D loss: 0.692224, acc.: 50.20%] [G loss: 0.712987]
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7977 [D loss: 0.693650, acc.: 47.85%] [G loss: 0.716274]
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7978 [D loss: 0.690139, acc.: 51.95%] [G loss: 0.726167]
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7979 [D loss: 0.685250, acc.: 51.95%] [G loss: 0.742214]
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7980 [D loss: 0.682000, acc.: 53.52%] [G loss: 0.753558]
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7981 [D loss: 0.688239, acc.: 53.91%] [G loss: 0.751386]
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7982 [D loss: 0.686406, acc.: 55.86%] [G loss: 0.752898]
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7983 [D loss: 0.696779, acc.: 49.22%] [G loss: 0.729980]
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7984 [D loss: 0.693626, acc.: 50.00%] [G loss: 0.717026]
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7985 [D loss: 0.693045, acc.: 50.20%] [G loss: 0.720807]
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7986 [D loss: 0.687931, acc.: 54.69%] [G loss: 0.711611]
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7987 [D loss: 0.691130, acc.: 48.24%] [G loss: 0.706512]
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7988 [D loss: 0.700641, acc.: 45.12%] [G loss: 0.691257]
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7989 [D loss: 0.701173, acc.: 49.61%] [G loss: 0.699113]
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7990 [D loss: 0.701441, acc.: 45.31%] [G loss: 0.724450]
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7991 [D loss: 0.694647, acc.: 49.61%] [G loss: 0.747286]
8/8 [==============================] - 0s 5ms/step
7992 [D loss: 0.685229, acc.: 51.56%] [G loss: 0.775314]
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7993 [D loss: 0.691047, acc.: 50.98%] [G loss: 0.756192]
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7994 [D loss: 0.701281, acc.: 45.90%] [G loss: 0.742268]
8/8 [==============================] - 0s 5ms/step
7995 [D loss: 0.704024, acc.: 47.27%] [G loss: 0.718300]
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7996 [D loss: 0.692023, acc.: 52.73%] [G loss: 0.734427]
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7997 [D loss: 0.688774, acc.: 55.66%] [G loss: 0.728118]
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7998 [D loss: 0.690415, acc.: 48.83%] [G loss: 0.714496]
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7999 [D loss: 0.694917, acc.: 47.07%] [G loss: 0.711989]
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8000 [D loss: 0.696076, acc.: 50.78%] [G loss: 0.721239]
1/1 [==============================] - 0s 18ms/step
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8001 [D loss: 0.692502, acc.: 50.78%] [G loss: 0.714702]
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8002 [D loss: 0.696224, acc.: 50.59%] [G loss: 0.736208]
8/8 [==============================] - 0s 5ms/step
8003 [D loss: 0.691812, acc.: 51.95%] [G loss: 0.732590]
8/8 [==============================] - 0s 5ms/step
8004 [D loss: 0.694368, acc.: 50.78%] [G loss: 0.724986]
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8005 [D loss: 0.694226, acc.: 49.80%] [G loss: 0.714393]
8/8 [==============================] - 0s 5ms/step
8006 [D loss: 0.689892, acc.: 51.95%] [G loss: 0.720960]
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8007 [D loss: 0.690915, acc.: 51.37%] [G loss: 0.712441]
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8008 [D loss: 0.692480, acc.: 54.49%] [G loss: 0.703063]
8/8 [==============================] - 0s 5ms/step
8009 [D loss: 0.695047, acc.: 46.88%] [G loss: 0.701602]
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8010 [D loss: 0.698409, acc.: 47.66%] [G loss: 0.702394]
8/8 [==============================] - 0s 5ms/step
8011 [D loss: 0.691701, acc.: 52.15%] [G loss: 0.721967]
8/8 [==============================] - 0s 5ms/step
8012 [D loss: 0.688488, acc.: 56.45%] [G loss: 0.748496]
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8013 [D loss: 0.686496, acc.: 53.71%] [G loss: 0.763679]
8/8 [==============================] - 0s 5ms/step
8014 [D loss: 0.692872, acc.: 51.17%] [G loss: 0.757416]
8/8 [==============================] - 0s 5ms/step
8015 [D loss: 0.695624, acc.: 51.76%] [G loss: 0.741726]
8/8 [==============================] - 0s 5ms/step
8016 [D loss: 0.693971, acc.: 49.22%] [G loss: 0.737030]
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8017 [D loss: 0.697086, acc.: 46.09%] [G loss: 0.724030]
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8018 [D loss: 0.690306, acc.: 54.69%] [G loss: 0.727206]
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8019 [D loss: 0.691529, acc.: 54.69%] [G loss: 0.712318]
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8020 [D loss: 0.703142, acc.: 44.53%] [G loss: 0.697351]
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8021 [D loss: 0.698604, acc.: 45.12%] [G loss: 0.690724]
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8022 [D loss: 0.697866, acc.: 45.12%] [G loss: 0.703552]
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8023 [D loss: 0.694267, acc.: 49.22%] [G loss: 0.720970]
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8024 [D loss: 0.686937, acc.: 51.76%] [G loss: 0.749817]
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8025 [D loss: 0.684210, acc.: 51.37%] [G loss: 0.750833]
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8026 [D loss: 0.681715, acc.: 50.98%] [G loss: 0.749871]
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8027 [D loss: 0.696742, acc.: 44.14%] [G loss: 0.735686]
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8028 [D loss: 0.689827, acc.: 50.00%] [G loss: 0.738017]
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8029 [D loss: 0.689021, acc.: 48.63%] [G loss: 0.745032]
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8030 [D loss: 0.693188, acc.: 49.41%] [G loss: 0.718503]
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8031 [D loss: 0.692978, acc.: 51.17%] [G loss: 0.705318]
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8032 [D loss: 0.700494, acc.: 46.48%] [G loss: 0.699654]
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8033 [D loss: 0.689554, acc.: 48.24%] [G loss: 0.701379]
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8034 [D loss: 0.689592, acc.: 48.05%] [G loss: 0.710404]
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8035 [D loss: 0.689582, acc.: 51.17%] [G loss: 0.724270]
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8036 [D loss: 0.682209, acc.: 51.56%] [G loss: 0.741873]
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8037 [D loss: 0.690217, acc.: 51.17%] [G loss: 0.732779]
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8038 [D loss: 0.687342, acc.: 53.52%] [G loss: 0.731369]
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8039 [D loss: 0.689557, acc.: 51.56%] [G loss: 0.729342]
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8040 [D loss: 0.694638, acc.: 52.54%] [G loss: 0.714924]
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8041 [D loss: 0.688671, acc.: 50.00%] [G loss: 0.729494]
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8042 [D loss: 0.697464, acc.: 51.17%] [G loss: 0.721483]
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8043 [D loss: 0.696955, acc.: 47.27%] [G loss: 0.719029]
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8044 [D loss: 0.700750, acc.: 47.46%] [G loss: 0.714644]
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8045 [D loss: 0.696761, acc.: 50.78%] [G loss: 0.708662]
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8046 [D loss: 0.707326, acc.: 41.80%] [G loss: 0.713322]
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8047 [D loss: 0.702910, acc.: 45.90%] [G loss: 0.733926]
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8048 [D loss: 0.693519, acc.: 46.68%] [G loss: 0.753864]
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8049 [D loss: 0.681587, acc.: 52.34%] [G loss: 0.779528]
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8050 [D loss: 0.689587, acc.: 46.09%] [G loss: 0.756794]
1/1 [==============================] - 0s 17ms/step
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8051 [D loss: 0.693399, acc.: 49.22%] [G loss: 0.731455]
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8052 [D loss: 0.693787, acc.: 52.73%] [G loss: 0.730161]
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8053 [D loss: 0.689393, acc.: 52.73%] [G loss: 0.728827]
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8054 [D loss: 0.686682, acc.: 49.80%] [G loss: 0.719381]
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8055 [D loss: 0.687441, acc.: 50.59%] [G loss: 0.707905]
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8056 [D loss: 0.697470, acc.: 47.66%] [G loss: 0.701323]
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8057 [D loss: 0.704944, acc.: 42.58%] [G loss: 0.708724]
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8058 [D loss: 0.688160, acc.: 48.44%] [G loss: 0.725095]
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8059 [D loss: 0.692480, acc.: 50.59%] [G loss: 0.729157]
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8060 [D loss: 0.694688, acc.: 44.34%] [G loss: 0.727428]
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8061 [D loss: 0.691491, acc.: 47.66%] [G loss: 0.732529]
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8062 [D loss: 0.701457, acc.: 43.16%] [G loss: 0.721838]
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8063 [D loss: 0.693690, acc.: 43.95%] [G loss: 0.715390]
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8064 [D loss: 0.693313, acc.: 49.22%] [G loss: 0.728212]
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8065 [D loss: 0.689503, acc.: 50.39%] [G loss: 0.729615]
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8066 [D loss: 0.688754, acc.: 51.56%] [G loss: 0.718734]
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8067 [D loss: 0.696678, acc.: 46.88%] [G loss: 0.715274]
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8068 [D loss: 0.695218, acc.: 48.05%] [G loss: 0.711306]
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8069 [D loss: 0.696479, acc.: 49.61%] [G loss: 0.714249]
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8070 [D loss: 0.697611, acc.: 46.88%] [G loss: 0.734169]
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8071 [D loss: 0.695835, acc.: 50.00%] [G loss: 0.736741]
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8072 [D loss: 0.691755, acc.: 45.90%] [G loss: 0.737031]
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8073 [D loss: 0.697430, acc.: 48.24%] [G loss: 0.728955]
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8074 [D loss: 0.697668, acc.: 47.07%] [G loss: 0.729166]
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8075 [D loss: 0.699761, acc.: 43.95%] [G loss: 0.721977]
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8076 [D loss: 0.696010, acc.: 52.15%] [G loss: 0.715263]
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8077 [D loss: 0.702094, acc.: 45.31%] [G loss: 0.710307]
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8078 [D loss: 0.699508, acc.: 44.92%] [G loss: 0.705354]
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8079 [D loss: 0.703761, acc.: 43.55%] [G loss: 0.695292]
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8080 [D loss: 0.696638, acc.: 47.46%] [G loss: 0.718711]
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8081 [D loss: 0.692651, acc.: 46.09%] [G loss: 0.721276]
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8082 [D loss: 0.686344, acc.: 50.20%] [G loss: 0.742126]
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8083 [D loss: 0.683330, acc.: 50.98%] [G loss: 0.742121]
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8084 [D loss: 0.690341, acc.: 46.09%] [G loss: 0.736965]
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8085 [D loss: 0.695777, acc.: 47.85%] [G loss: 0.717371]
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8086 [D loss: 0.693746, acc.: 50.78%] [G loss: 0.722484]
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8087 [D loss: 0.687695, acc.: 50.39%] [G loss: 0.723188]
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8088 [D loss: 0.678188, acc.: 55.08%] [G loss: 0.723219]
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8089 [D loss: 0.684757, acc.: 54.10%] [G loss: 0.715065]
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8090 [D loss: 0.687675, acc.: 48.44%] [G loss: 0.708019]
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8091 [D loss: 0.691288, acc.: 51.17%] [G loss: 0.699812]
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8092 [D loss: 0.683750, acc.: 52.73%] [G loss: 0.706430]
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8093 [D loss: 0.688439, acc.: 51.17%] [G loss: 0.720164]
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8094 [D loss: 0.686511, acc.: 52.73%] [G loss: 0.727352]
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8095 [D loss: 0.683305, acc.: 52.15%] [G loss: 0.734967]
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8096 [D loss: 0.682519, acc.: 51.56%] [G loss: 0.739295]
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8097 [D loss: 0.694675, acc.: 47.66%] [G loss: 0.735907]
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8098 [D loss: 0.687159, acc.: 50.00%] [G loss: 0.725717]
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8099 [D loss: 0.691080, acc.: 49.61%] [G loss: 0.732416]
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8100 [D loss: 0.687440, acc.: 49.41%] [G loss: 0.727584]
1/1 [==============================] - 0s 18ms/step
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8101 [D loss: 0.691754, acc.: 47.07%] [G loss: 0.718614]
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8102 [D loss: 0.686440, acc.: 49.41%] [G loss: 0.719438]
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8103 [D loss: 0.688307, acc.: 50.39%] [G loss: 0.720402]
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8104 [D loss: 0.686305, acc.: 45.51%] [G loss: 0.719312]
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8105 [D loss: 0.684314, acc.: 48.05%] [G loss: 0.735692]
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8106 [D loss: 0.673188, acc.: 53.32%] [G loss: 0.755955]
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8107 [D loss: 0.685120, acc.: 51.17%] [G loss: 0.744276]
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8108 [D loss: 0.685152, acc.: 50.39%] [G loss: 0.745917]
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8109 [D loss: 0.684911, acc.: 48.05%] [G loss: 0.739675]
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8110 [D loss: 0.681202, acc.: 51.17%] [G loss: 0.736365]
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8111 [D loss: 0.689040, acc.: 48.83%] [G loss: 0.727710]
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8112 [D loss: 0.679657, acc.: 52.93%] [G loss: 0.726517]
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8113 [D loss: 0.675882, acc.: 51.95%] [G loss: 0.726533]
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8114 [D loss: 0.688816, acc.: 49.80%] [G loss: 0.722077]
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8115 [D loss: 0.682756, acc.: 53.12%] [G loss: 0.727684]
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8116 [D loss: 0.680661, acc.: 51.95%] [G loss: 0.733073]
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8117 [D loss: 0.685861, acc.: 48.05%] [G loss: 0.731239]
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8118 [D loss: 0.670471, acc.: 58.59%] [G loss: 0.716809]
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8119 [D loss: 0.685667, acc.: 52.93%] [G loss: 0.721490]
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8120 [D loss: 0.686188, acc.: 51.37%] [G loss: 0.720788]
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8121 [D loss: 0.688367, acc.: 48.05%] [G loss: 0.716762]
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8122 [D loss: 0.691632, acc.: 45.31%] [G loss: 0.713300]
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8123 [D loss: 0.689664, acc.: 47.46%] [G loss: 0.719037]
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8124 [D loss: 0.691273, acc.: 48.24%] [G loss: 0.726673]
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8125 [D loss: 0.686456, acc.: 51.17%] [G loss: 0.733454]
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8126 [D loss: 0.691184, acc.: 46.68%] [G loss: 0.719683]
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8127 [D loss: 0.707209, acc.: 48.44%] [G loss: 0.720092]
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8128 [D loss: 0.706424, acc.: 42.97%] [G loss: 0.719848]
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8129 [D loss: 0.701160, acc.: 44.53%] [G loss: 0.725504]
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8130 [D loss: 0.693039, acc.: 42.97%] [G loss: 0.733770]
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8131 [D loss: 0.693992, acc.: 48.24%] [G loss: 0.729616]
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8132 [D loss: 0.689702, acc.: 48.63%] [G loss: 0.718294]
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8133 [D loss: 0.692134, acc.: 49.61%] [G loss: 0.714872]
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8134 [D loss: 0.692549, acc.: 49.02%] [G loss: 0.726198]
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8135 [D loss: 0.700909, acc.: 48.44%] [G loss: 0.717314]
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8136 [D loss: 0.689932, acc.: 53.71%] [G loss: 0.726446]
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8137 [D loss: 0.689162, acc.: 51.17%] [G loss: 0.720672]
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8138 [D loss: 0.693279, acc.: 50.00%] [G loss: 0.733666]
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8139 [D loss: 0.691917, acc.: 49.41%] [G loss: 0.736589]
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8140 [D loss: 0.688009, acc.: 50.98%] [G loss: 0.735706]
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8141 [D loss: 0.686810, acc.: 50.00%] [G loss: 0.723240]
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8142 [D loss: 0.686022, acc.: 52.54%] [G loss: 0.736882]
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8143 [D loss: 0.687253, acc.: 53.32%] [G loss: 0.724744]
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8144 [D loss: 0.682492, acc.: 52.54%] [G loss: 0.724331]
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8145 [D loss: 0.690243, acc.: 48.63%] [G loss: 0.709775]
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8146 [D loss: 0.692218, acc.: 48.05%] [G loss: 0.719385]
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8147 [D loss: 0.690012, acc.: 48.44%] [G loss: 0.714691]
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8148 [D loss: 0.693226, acc.: 46.29%] [G loss: 0.716808]
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8149 [D loss: 0.691481, acc.: 42.19%] [G loss: 0.739986]
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8150 [D loss: 0.687316, acc.: 44.92%] [G loss: 0.728219]
1/1 [==============================] - 0s 18ms/step
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8151 [D loss: 0.691869, acc.: 47.85%] [G loss: 0.735921]
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8152 [D loss: 0.684775, acc.: 46.68%] [G loss: 0.754688]
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8153 [D loss: 0.682891, acc.: 47.66%] [G loss: 0.749259]
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8154 [D loss: 0.690018, acc.: 48.44%] [G loss: 0.722962]
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8155 [D loss: 0.686783, acc.: 55.27%] [G loss: 0.717215]
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8156 [D loss: 0.687527, acc.: 50.98%] [G loss: 0.711022]
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8157 [D loss: 0.706318, acc.: 43.36%] [G loss: 0.697170]
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8158 [D loss: 0.699081, acc.: 47.85%] [G loss: 0.699432]
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8159 [D loss: 0.694306, acc.: 47.27%] [G loss: 0.733740]
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8160 [D loss: 0.699668, acc.: 47.85%] [G loss: 0.738426]
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8161 [D loss: 0.703717, acc.: 45.70%] [G loss: 0.750060]
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8162 [D loss: 0.695476, acc.: 45.90%] [G loss: 0.753339]
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8163 [D loss: 0.692109, acc.: 44.53%] [G loss: 0.740913]
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8164 [D loss: 0.688745, acc.: 53.71%] [G loss: 0.739443]
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8165 [D loss: 0.689656, acc.: 52.34%] [G loss: 0.738248]
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8166 [D loss: 0.693845, acc.: 51.37%] [G loss: 0.714303]
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8167 [D loss: 0.700347, acc.: 45.70%] [G loss: 0.699901]
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8168 [D loss: 0.704604, acc.: 45.31%] [G loss: 0.702296]
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8169 [D loss: 0.691851, acc.: 48.63%] [G loss: 0.728948]
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8170 [D loss: 0.693516, acc.: 45.70%] [G loss: 0.740559]
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8171 [D loss: 0.689994, acc.: 48.83%] [G loss: 0.741170]
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8172 [D loss: 0.691991, acc.: 49.61%] [G loss: 0.739531]
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8173 [D loss: 0.690861, acc.: 50.39%] [G loss: 0.737478]
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8174 [D loss: 0.682633, acc.: 53.12%] [G loss: 0.740119]
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8175 [D loss: 0.689835, acc.: 50.00%] [G loss: 0.728994]
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8176 [D loss: 0.683362, acc.: 50.39%] [G loss: 0.705755]
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8177 [D loss: 0.686274, acc.: 50.59%] [G loss: 0.709310]
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8178 [D loss: 0.697640, acc.: 43.95%] [G loss: 0.723056]
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8179 [D loss: 0.689671, acc.: 50.20%] [G loss: 0.736003]
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8180 [D loss: 0.688397, acc.: 50.39%] [G loss: 0.758239]
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8181 [D loss: 0.685310, acc.: 52.93%] [G loss: 0.770985]
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8182 [D loss: 0.694140, acc.: 49.61%] [G loss: 0.752854]
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8183 [D loss: 0.693218, acc.: 51.17%] [G loss: 0.748788]
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8184 [D loss: 0.698165, acc.: 48.83%] [G loss: 0.739708]
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8185 [D loss: 0.692777, acc.: 50.59%] [G loss: 0.733906]
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8186 [D loss: 0.690560, acc.: 50.39%] [G loss: 0.724991]
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8187 [D loss: 0.691226, acc.: 49.41%] [G loss: 0.721344]
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8188 [D loss: 0.702063, acc.: 46.48%] [G loss: 0.703775]
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8189 [D loss: 0.709048, acc.: 40.04%] [G loss: 0.704863]
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8190 [D loss: 0.699124, acc.: 45.51%] [G loss: 0.722367]
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8191 [D loss: 0.694921, acc.: 50.20%] [G loss: 0.735364]
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8192 [D loss: 0.692582, acc.: 50.78%] [G loss: 0.742931]
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8193 [D loss: 0.699032, acc.: 49.02%] [G loss: 0.744248]
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8194 [D loss: 0.699693, acc.: 45.70%] [G loss: 0.745768]
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8195 [D loss: 0.703121, acc.: 45.51%] [G loss: 0.729434]
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8196 [D loss: 0.701680, acc.: 41.41%] [G loss: 0.723516]
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8197 [D loss: 0.692974, acc.: 53.71%] [G loss: 0.720761]
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8198 [D loss: 0.693576, acc.: 52.15%] [G loss: 0.716825]
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8199 [D loss: 0.697974, acc.: 49.22%] [G loss: 0.709580]
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8200 [D loss: 0.702287, acc.: 45.31%] [G loss: 0.706792]
1/1 [==============================] - 0s 17ms/step
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8201 [D loss: 0.698169, acc.: 49.80%] [G loss: 0.720301]
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8202 [D loss: 0.696895, acc.: 48.44%] [G loss: 0.727870]
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8203 [D loss: 0.690448, acc.: 48.24%] [G loss: 0.737331]
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8204 [D loss: 0.690959, acc.: 53.71%] [G loss: 0.750644]
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8205 [D loss: 0.690632, acc.: 47.85%] [G loss: 0.743290]
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8206 [D loss: 0.688024, acc.: 49.80%] [G loss: 0.739783]
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8207 [D loss: 0.685000, acc.: 52.73%] [G loss: 0.742361]
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8208 [D loss: 0.680176, acc.: 55.27%] [G loss: 0.742096]
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8209 [D loss: 0.681161, acc.: 53.71%] [G loss: 0.738453]
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8210 [D loss: 0.681422, acc.: 51.17%] [G loss: 0.735828]
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8211 [D loss: 0.688532, acc.: 50.39%] [G loss: 0.718650]
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8212 [D loss: 0.684047, acc.: 53.32%] [G loss: 0.738815]
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8213 [D loss: 0.676135, acc.: 53.91%] [G loss: 0.744177]
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8214 [D loss: 0.686465, acc.: 50.20%] [G loss: 0.743042]
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8215 [D loss: 0.691555, acc.: 48.24%] [G loss: 0.727919]
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8216 [D loss: 0.694578, acc.: 46.29%] [G loss: 0.720093]
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8217 [D loss: 0.698818, acc.: 44.73%] [G loss: 0.712751]
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8218 [D loss: 0.693956, acc.: 46.29%] [G loss: 0.702053]
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8219 [D loss: 0.696610, acc.: 46.68%] [G loss: 0.711163]
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8220 [D loss: 0.695089, acc.: 46.09%] [G loss: 0.725381]
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8221 [D loss: 0.696377, acc.: 45.31%] [G loss: 0.704060]
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8222 [D loss: 0.699059, acc.: 48.05%] [G loss: 0.703369]
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8223 [D loss: 0.695925, acc.: 50.20%] [G loss: 0.716197]
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8224 [D loss: 0.686529, acc.: 53.91%] [G loss: 0.729776]
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8225 [D loss: 0.692609, acc.: 49.41%] [G loss: 0.723965]
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8226 [D loss: 0.702435, acc.: 45.12%] [G loss: 0.724160]
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8227 [D loss: 0.691872, acc.: 53.12%] [G loss: 0.726259]
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8228 [D loss: 0.687578, acc.: 51.37%] [G loss: 0.730638]
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8229 [D loss: 0.694959, acc.: 50.78%] [G loss: 0.715606]
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8230 [D loss: 0.693785, acc.: 48.24%] [G loss: 0.704572]
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8231 [D loss: 0.695306, acc.: 46.68%] [G loss: 0.703715]
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8232 [D loss: 0.697693, acc.: 43.16%] [G loss: 0.708758]
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8233 [D loss: 0.699929, acc.: 48.24%] [G loss: 0.721996]
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8234 [D loss: 0.700567, acc.: 45.12%] [G loss: 0.719537]
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8235 [D loss: 0.692024, acc.: 49.22%] [G loss: 0.729172]
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8236 [D loss: 0.687971, acc.: 51.95%] [G loss: 0.738438]
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8237 [D loss: 0.692910, acc.: 46.88%] [G loss: 0.741698]
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8238 [D loss: 0.690066, acc.: 51.56%] [G loss: 0.733121]
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8239 [D loss: 0.687705, acc.: 51.76%] [G loss: 0.731353]
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8240 [D loss: 0.687609, acc.: 51.95%] [G loss: 0.725465]
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8241 [D loss: 0.694180, acc.: 48.24%] [G loss: 0.730826]
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8242 [D loss: 0.690586, acc.: 49.61%] [G loss: 0.717365]
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8243 [D loss: 0.695397, acc.: 48.05%] [G loss: 0.728883]
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8244 [D loss: 0.705184, acc.: 45.51%] [G loss: 0.721504]
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8245 [D loss: 0.693386, acc.: 48.44%] [G loss: 0.725584]
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8246 [D loss: 0.701688, acc.: 45.51%] [G loss: 0.725197]
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8247 [D loss: 0.706551, acc.: 43.75%] [G loss: 0.717152]
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8248 [D loss: 0.697972, acc.: 48.83%] [G loss: 0.712345]
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8249 [D loss: 0.699124, acc.: 46.29%] [G loss: 0.706024]
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8250 [D loss: 0.698449, acc.: 46.09%] [G loss: 0.708887]
1/1 [==============================] - 0s 18ms/step
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8251 [D loss: 0.706555, acc.: 43.36%] [G loss: 0.703449]
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8252 [D loss: 0.697007, acc.: 48.44%] [G loss: 0.721225]
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8253 [D loss: 0.693105, acc.: 46.88%] [G loss: 0.734258]
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8254 [D loss: 0.685537, acc.: 50.98%] [G loss: 0.743815]
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8255 [D loss: 0.688012, acc.: 52.73%] [G loss: 0.752279]
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8256 [D loss: 0.685054, acc.: 51.95%] [G loss: 0.732754]
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8257 [D loss: 0.697277, acc.: 47.27%] [G loss: 0.721280]
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8258 [D loss: 0.696276, acc.: 48.05%] [G loss: 0.723141]
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8259 [D loss: 0.692239, acc.: 49.41%] [G loss: 0.711860]
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8260 [D loss: 0.691278, acc.: 47.66%] [G loss: 0.718702]
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8261 [D loss: 0.693124, acc.: 49.41%] [G loss: 0.717217]
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8262 [D loss: 0.690113, acc.: 53.71%] [G loss: 0.724230]
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8263 [D loss: 0.701495, acc.: 44.92%] [G loss: 0.724416]
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8264 [D loss: 0.694717, acc.: 47.46%] [G loss: 0.727993]
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8265 [D loss: 0.694149, acc.: 48.63%] [G loss: 0.728631]
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8266 [D loss: 0.688530, acc.: 46.68%] [G loss: 0.731092]
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8267 [D loss: 0.690728, acc.: 46.09%] [G loss: 0.733223]
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8268 [D loss: 0.686507, acc.: 49.02%] [G loss: 0.734713]
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8269 [D loss: 0.679498, acc.: 58.59%] [G loss: 0.724832]
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8270 [D loss: 0.690034, acc.: 49.61%] [G loss: 0.735919]
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8271 [D loss: 0.689571, acc.: 52.93%] [G loss: 0.717276]
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8272 [D loss: 0.693280, acc.: 49.80%] [G loss: 0.723728]
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8273 [D loss: 0.687338, acc.: 52.15%] [G loss: 0.741676]
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8274 [D loss: 0.680759, acc.: 55.66%] [G loss: 0.767997]
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8275 [D loss: 0.690130, acc.: 50.59%] [G loss: 0.772303]
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8276 [D loss: 0.697851, acc.: 45.51%] [G loss: 0.740225]
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8277 [D loss: 0.699023, acc.: 46.29%] [G loss: 0.729119]
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8278 [D loss: 0.689065, acc.: 54.30%] [G loss: 0.757632]
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8279 [D loss: 0.682777, acc.: 57.23%] [G loss: 0.758607]
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8280 [D loss: 0.696174, acc.: 47.07%] [G loss: 0.726246]
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8281 [D loss: 0.693963, acc.: 46.48%] [G loss: 0.707760]
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8282 [D loss: 0.694458, acc.: 46.29%] [G loss: 0.734096]
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8283 [D loss: 0.687682, acc.: 51.95%] [G loss: 0.748039]
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8284 [D loss: 0.685183, acc.: 52.93%] [G loss: 0.758742]
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8285 [D loss: 0.693242, acc.: 50.59%] [G loss: 0.749899]
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8286 [D loss: 0.697278, acc.: 46.09%] [G loss: 0.730637]
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8287 [D loss: 0.682203, acc.: 62.70%] [G loss: 0.751123]
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8288 [D loss: 0.690297, acc.: 52.34%] [G loss: 0.723801]
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8289 [D loss: 0.699892, acc.: 44.14%] [G loss: 0.714698]
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8290 [D loss: 0.701069, acc.: 43.36%] [G loss: 0.707028]
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8291 [D loss: 0.691698, acc.: 51.37%] [G loss: 0.719950]
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8292 [D loss: 0.688339, acc.: 53.52%] [G loss: 0.750744]
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8293 [D loss: 0.691822, acc.: 50.59%] [G loss: 0.747787]
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8294 [D loss: 0.691551, acc.: 43.16%] [G loss: 0.732457]
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8295 [D loss: 0.692888, acc.: 46.48%] [G loss: 0.727962]
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8296 [D loss: 0.685206, acc.: 54.10%] [G loss: 0.755155]
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8297 [D loss: 0.685806, acc.: 52.34%] [G loss: 0.723969]
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8298 [D loss: 0.694096, acc.: 47.27%] [G loss: 0.710002]
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8299 [D loss: 0.703221, acc.: 46.68%] [G loss: 0.709219]
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8300 [D loss: 0.694435, acc.: 49.41%] [G loss: 0.713533]
1/1 [==============================] - 0s 18ms/step
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8301 [D loss: 0.699636, acc.: 45.90%] [G loss: 0.724369]
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8302 [D loss: 0.691430, acc.: 51.37%] [G loss: 0.734543]
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8303 [D loss: 0.690765, acc.: 50.98%] [G loss: 0.725715]
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8304 [D loss: 0.686780, acc.: 51.56%] [G loss: 0.732361]
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8305 [D loss: 0.685575, acc.: 53.12%] [G loss: 0.734564]
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8306 [D loss: 0.686226, acc.: 51.17%] [G loss: 0.734714]
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8307 [D loss: 0.683925, acc.: 52.15%] [G loss: 0.732480]
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8308 [D loss: 0.678744, acc.: 53.32%] [G loss: 0.727949]
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8309 [D loss: 0.689209, acc.: 49.80%] [G loss: 0.717469]
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8310 [D loss: 0.688790, acc.: 50.98%] [G loss: 0.713441]
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8311 [D loss: 0.692988, acc.: 49.80%] [G loss: 0.714984]
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8312 [D loss: 0.688563, acc.: 50.59%] [G loss: 0.717236]
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8313 [D loss: 0.692167, acc.: 51.17%] [G loss: 0.721208]
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8314 [D loss: 0.686130, acc.: 53.52%] [G loss: 0.728360]
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8315 [D loss: 0.690926, acc.: 50.20%] [G loss: 0.723933]
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8316 [D loss: 0.692294, acc.: 47.46%] [G loss: 0.715744]
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8317 [D loss: 0.701560, acc.: 43.55%] [G loss: 0.695967]
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8318 [D loss: 0.705515, acc.: 44.53%] [G loss: 0.687719]
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8319 [D loss: 0.711058, acc.: 42.38%] [G loss: 0.695168]
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8320 [D loss: 0.699517, acc.: 46.48%] [G loss: 0.722851]
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8321 [D loss: 0.693108, acc.: 48.63%] [G loss: 0.740900]
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8322 [D loss: 0.693823, acc.: 47.07%] [G loss: 0.744414]
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8323 [D loss: 0.692528, acc.: 49.02%] [G loss: 0.733473]
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8324 [D loss: 0.692050, acc.: 51.95%] [G loss: 0.734759]
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8325 [D loss: 0.690800, acc.: 50.78%] [G loss: 0.737972]
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8326 [D loss: 0.699917, acc.: 47.07%] [G loss: 0.727092]
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8327 [D loss: 0.698141, acc.: 47.27%] [G loss: 0.712318]
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8328 [D loss: 0.690889, acc.: 49.61%] [G loss: 0.706252]
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8329 [D loss: 0.695234, acc.: 48.63%] [G loss: 0.709368]
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8330 [D loss: 0.691579, acc.: 49.80%] [G loss: 0.727385]
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8331 [D loss: 0.693548, acc.: 50.78%] [G loss: 0.732993]
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8332 [D loss: 0.693857, acc.: 48.44%] [G loss: 0.738979]
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8333 [D loss: 0.692850, acc.: 49.02%] [G loss: 0.734315]
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8334 [D loss: 0.700369, acc.: 49.02%] [G loss: 0.719733]
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8335 [D loss: 0.702246, acc.: 51.76%] [G loss: 0.726672]
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8336 [D loss: 0.698309, acc.: 50.00%] [G loss: 0.724296]
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8337 [D loss: 0.691501, acc.: 51.37%] [G loss: 0.733914]
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8338 [D loss: 0.689777, acc.: 50.98%] [G loss: 0.740261]
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8339 [D loss: 0.689833, acc.: 51.37%] [G loss: 0.744503]
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8340 [D loss: 0.684117, acc.: 58.20%] [G loss: 0.742756]
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8341 [D loss: 0.684300, acc.: 55.86%] [G loss: 0.745470]
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8342 [D loss: 0.681723, acc.: 55.27%] [G loss: 0.743949]
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8343 [D loss: 0.691046, acc.: 49.80%] [G loss: 0.735631]
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8344 [D loss: 0.686992, acc.: 49.80%] [G loss: 0.724511]
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8345 [D loss: 0.686846, acc.: 49.61%] [G loss: 0.743514]
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8346 [D loss: 0.704056, acc.: 43.75%] [G loss: 0.739664]
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8347 [D loss: 0.688924, acc.: 52.34%] [G loss: 0.742498]
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8348 [D loss: 0.690834, acc.: 49.02%] [G loss: 0.741452]
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8349 [D loss: 0.690342, acc.: 48.83%] [G loss: 0.733833]
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8350 [D loss: 0.684844, acc.: 53.91%] [G loss: 0.725053]
1/1 [==============================] - 0s 19ms/step
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8351 [D loss: 0.678609, acc.: 54.69%] [G loss: 0.728015]
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8352 [D loss: 0.682015, acc.: 53.32%] [G loss: 0.724420]
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8353 [D loss: 0.683821, acc.: 54.49%] [G loss: 0.712626]
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8354 [D loss: 0.689680, acc.: 50.00%] [G loss: 0.718800]
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8355 [D loss: 0.689530, acc.: 52.15%] [G loss: 0.723951]
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8356 [D loss: 0.686753, acc.: 51.95%] [G loss: 0.720382]
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8357 [D loss: 0.691479, acc.: 48.24%] [G loss: 0.723999]
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8358 [D loss: 0.685570, acc.: 47.85%] [G loss: 0.731199]
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8359 [D loss: 0.692678, acc.: 46.29%] [G loss: 0.737422]
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8360 [D loss: 0.694474, acc.: 49.41%] [G loss: 0.737120]
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8361 [D loss: 0.687784, acc.: 48.63%] [G loss: 0.731279]
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8362 [D loss: 0.683456, acc.: 50.59%] [G loss: 0.737845]
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8363 [D loss: 0.683679, acc.: 51.56%] [G loss: 0.745257]
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8364 [D loss: 0.686344, acc.: 49.61%] [G loss: 0.728344]
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8365 [D loss: 0.694993, acc.: 44.14%] [G loss: 0.728508]
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8366 [D loss: 0.689129, acc.: 53.52%] [G loss: 0.726160]
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8367 [D loss: 0.674795, acc.: 52.34%] [G loss: 0.746867]
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8368 [D loss: 0.690051, acc.: 48.83%] [G loss: 0.737818]
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8369 [D loss: 0.685994, acc.: 48.63%] [G loss: 0.738599]
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8370 [D loss: 0.691918, acc.: 48.44%] [G loss: 0.736400]
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8371 [D loss: 0.693749, acc.: 47.66%] [G loss: 0.722597]
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8372 [D loss: 0.693897, acc.: 47.85%] [G loss: 0.724363]
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8373 [D loss: 0.693367, acc.: 49.22%] [G loss: 0.717661]
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8374 [D loss: 0.700537, acc.: 45.90%] [G loss: 0.718139]
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8375 [D loss: 0.697232, acc.: 47.85%] [G loss: 0.733203]
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8376 [D loss: 0.685727, acc.: 53.91%] [G loss: 0.751164]
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8377 [D loss: 0.694856, acc.: 48.63%] [G loss: 0.750553]
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8378 [D loss: 0.696160, acc.: 45.90%] [G loss: 0.737315]
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8379 [D loss: 0.697147, acc.: 45.31%] [G loss: 0.723960]
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8380 [D loss: 0.690607, acc.: 50.39%] [G loss: 0.711195]
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8381 [D loss: 0.682145, acc.: 56.45%] [G loss: 0.714591]
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8382 [D loss: 0.696958, acc.: 48.24%] [G loss: 0.716791]
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8383 [D loss: 0.686683, acc.: 55.08%] [G loss: 0.729596]
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8384 [D loss: 0.687232, acc.: 51.37%] [G loss: 0.735259]
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8385 [D loss: 0.694613, acc.: 47.66%] [G loss: 0.741654]
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8386 [D loss: 0.685048, acc.: 53.91%] [G loss: 0.760376]
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8387 [D loss: 0.694168, acc.: 46.68%] [G loss: 0.751546]
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8388 [D loss: 0.698411, acc.: 47.66%] [G loss: 0.741017]
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8389 [D loss: 0.693984, acc.: 51.37%] [G loss: 0.746351]
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8390 [D loss: 0.689261, acc.: 52.93%] [G loss: 0.740496]
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8391 [D loss: 0.696890, acc.: 46.48%] [G loss: 0.743206]
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8392 [D loss: 0.690881, acc.: 53.71%] [G loss: 0.726960]
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8393 [D loss: 0.692782, acc.: 50.39%] [G loss: 0.730841]
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8394 [D loss: 0.691777, acc.: 50.39%] [G loss: 0.736539]
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8395 [D loss: 0.694837, acc.: 50.39%] [G loss: 0.735927]
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8396 [D loss: 0.687801, acc.: 50.20%] [G loss: 0.738522]
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8397 [D loss: 0.686573, acc.: 52.54%] [G loss: 0.744076]
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8398 [D loss: 0.706403, acc.: 44.73%] [G loss: 0.713870]
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8399 [D loss: 0.701112, acc.: 42.58%] [G loss: 0.721713]
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8400 [D loss: 0.694600, acc.: 44.92%] [G loss: 0.721464]
1/1 [==============================] - 0s 18ms/step
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8401 [D loss: 0.695518, acc.: 48.83%] [G loss: 0.717796]
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8402 [D loss: 0.701835, acc.: 44.53%] [G loss: 0.720145]
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8403 [D loss: 0.691340, acc.: 53.52%] [G loss: 0.729809]
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8404 [D loss: 0.692183, acc.: 53.32%] [G loss: 0.738726]
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8405 [D loss: 0.694305, acc.: 53.52%] [G loss: 0.743456]
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8406 [D loss: 0.692235, acc.: 51.17%] [G loss: 0.734190]
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8407 [D loss: 0.703269, acc.: 50.20%] [G loss: 0.738086]
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8408 [D loss: 0.698863, acc.: 50.59%] [G loss: 0.727425]
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8409 [D loss: 0.695915, acc.: 51.37%] [G loss: 0.719737]
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8410 [D loss: 0.692247, acc.: 51.17%] [G loss: 0.714900]
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8411 [D loss: 0.692530, acc.: 48.44%] [G loss: 0.714603]
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8412 [D loss: 0.706511, acc.: 45.51%] [G loss: 0.714525]
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8413 [D loss: 0.698761, acc.: 48.05%] [G loss: 0.721143]
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8414 [D loss: 0.692279, acc.: 51.17%] [G loss: 0.748631]
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8415 [D loss: 0.691443, acc.: 51.56%] [G loss: 0.757782]
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8416 [D loss: 0.699666, acc.: 50.39%] [G loss: 0.751416]
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8417 [D loss: 0.698132, acc.: 46.48%] [G loss: 0.743732]
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8418 [D loss: 0.687890, acc.: 50.00%] [G loss: 0.754527]
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8419 [D loss: 0.677535, acc.: 57.03%] [G loss: 0.749191]
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8420 [D loss: 0.685097, acc.: 53.71%] [G loss: 0.737049]
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8421 [D loss: 0.678989, acc.: 55.08%] [G loss: 0.719863]
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8422 [D loss: 0.686564, acc.: 50.59%] [G loss: 0.722421]
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8423 [D loss: 0.689627, acc.: 48.24%] [G loss: 0.719861]
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8424 [D loss: 0.690459, acc.: 48.24%] [G loss: 0.741565]
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8425 [D loss: 0.690558, acc.: 53.12%] [G loss: 0.772096]
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8426 [D loss: 0.683758, acc.: 51.56%] [G loss: 0.765419]
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8427 [D loss: 0.686372, acc.: 50.20%] [G loss: 0.761909]
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8428 [D loss: 0.692453, acc.: 47.46%] [G loss: 0.739603]
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8429 [D loss: 0.684914, acc.: 49.41%] [G loss: 0.737625]
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8430 [D loss: 0.689618, acc.: 52.54%] [G loss: 0.734665]
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8431 [D loss: 0.687518, acc.: 51.76%] [G loss: 0.730320]
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8432 [D loss: 0.690986, acc.: 49.41%] [G loss: 0.706606]
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8433 [D loss: 0.699730, acc.: 47.85%] [G loss: 0.707730]
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8434 [D loss: 0.694199, acc.: 47.27%] [G loss: 0.707457]
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8435 [D loss: 0.690265, acc.: 49.22%] [G loss: 0.718959]
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8436 [D loss: 0.692227, acc.: 48.63%] [G loss: 0.727592]
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8437 [D loss: 0.713537, acc.: 50.20%] [G loss: 0.714424]
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8438 [D loss: 0.699607, acc.: 45.31%] [G loss: 0.725779]
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8439 [D loss: 0.688344, acc.: 50.59%] [G loss: 0.727603]
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8440 [D loss: 0.694806, acc.: 46.88%] [G loss: 0.738597]
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8441 [D loss: 0.701830, acc.: 44.73%] [G loss: 0.731978]
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8442 [D loss: 0.694194, acc.: 47.66%] [G loss: 0.723551]
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8443 [D loss: 0.692489, acc.: 52.54%] [G loss: 0.728196]
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8444 [D loss: 0.689627, acc.: 50.39%] [G loss: 0.751738]
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8445 [D loss: 0.689429, acc.: 48.63%] [G loss: 0.732652]
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8446 [D loss: 0.692185, acc.: 48.44%] [G loss: 0.735770]
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8447 [D loss: 0.690790, acc.: 49.22%] [G loss: 0.732292]
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8448 [D loss: 0.686170, acc.: 48.83%] [G loss: 0.739016]
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8449 [D loss: 0.683935, acc.: 51.95%] [G loss: 0.730549]
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8450 [D loss: 0.692483, acc.: 50.00%] [G loss: 0.719962]
1/1 [==============================] - 0s 20ms/step
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8451 [D loss: 0.687626, acc.: 51.37%] [G loss: 0.725942]
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8452 [D loss: 0.684343, acc.: 51.56%] [G loss: 0.722619]
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8453 [D loss: 0.697771, acc.: 46.68%] [G loss: 0.723045]
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8454 [D loss: 0.683573, acc.: 51.76%] [G loss: 0.720051]
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8455 [D loss: 0.689220, acc.: 48.63%] [G loss: 0.739538]
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8456 [D loss: 0.686759, acc.: 48.05%] [G loss: 0.758853]
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8457 [D loss: 0.685889, acc.: 53.12%] [G loss: 0.772006]
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8458 [D loss: 0.681838, acc.: 53.32%] [G loss: 0.752039]
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8459 [D loss: 0.691298, acc.: 48.44%] [G loss: 0.742774]
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8460 [D loss: 0.694248, acc.: 47.27%] [G loss: 0.729336]
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8461 [D loss: 0.684231, acc.: 50.78%] [G loss: 0.724995]
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8462 [D loss: 0.707441, acc.: 48.05%] [G loss: 0.715721]
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8463 [D loss: 0.700469, acc.: 47.27%] [G loss: 0.716355]
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8464 [D loss: 0.696431, acc.: 51.17%] [G loss: 0.714836]
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8465 [D loss: 0.704712, acc.: 48.63%] [G loss: 0.733885]
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8466 [D loss: 0.689218, acc.: 50.00%] [G loss: 0.744630]
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8467 [D loss: 0.691989, acc.: 50.20%] [G loss: 0.748262]
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8468 [D loss: 0.700988, acc.: 45.31%] [G loss: 0.726522]
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8469 [D loss: 0.702470, acc.: 45.31%] [G loss: 0.727726]
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8470 [D loss: 0.697543, acc.: 52.73%] [G loss: 0.721914]
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8471 [D loss: 0.696491, acc.: 48.24%] [G loss: 0.725158]
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8472 [D loss: 0.686126, acc.: 53.12%] [G loss: 0.710201]
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8473 [D loss: 0.695025, acc.: 47.66%] [G loss: 0.700845]
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8474 [D loss: 0.698070, acc.: 47.07%] [G loss: 0.707563]
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8475 [D loss: 0.694267, acc.: 50.39%] [G loss: 0.715873]
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8476 [D loss: 0.691744, acc.: 47.66%] [G loss: 0.708652]
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8477 [D loss: 0.691765, acc.: 48.44%] [G loss: 0.721640]
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8478 [D loss: 0.695807, acc.: 45.12%] [G loss: 0.719940]
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8479 [D loss: 0.691377, acc.: 50.78%] [G loss: 0.722394]
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8480 [D loss: 0.690023, acc.: 53.52%] [G loss: 0.725796]
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8481 [D loss: 0.689713, acc.: 51.95%] [G loss: 0.717959]
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8482 [D loss: 0.692290, acc.: 52.54%] [G loss: 0.728311]
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8483 [D loss: 0.684768, acc.: 53.12%] [G loss: 0.734029]
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8484 [D loss: 0.679012, acc.: 53.71%] [G loss: 0.736900]
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8485 [D loss: 0.687187, acc.: 49.41%] [G loss: 0.740761]
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8486 [D loss: 0.688525, acc.: 46.29%] [G loss: 0.747790]
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8487 [D loss: 0.683480, acc.: 51.56%] [G loss: 0.748459]
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8488 [D loss: 0.693714, acc.: 48.24%] [G loss: 0.738226]
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8489 [D loss: 0.681085, acc.: 51.56%] [G loss: 0.729217]
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8490 [D loss: 0.695002, acc.: 46.68%] [G loss: 0.730342]
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8491 [D loss: 0.687574, acc.: 47.66%] [G loss: 0.721126]
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8492 [D loss: 0.694676, acc.: 44.92%] [G loss: 0.709290]
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8493 [D loss: 0.698270, acc.: 41.80%] [G loss: 0.710162]
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8494 [D loss: 0.690119, acc.: 43.36%] [G loss: 0.711578]
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8495 [D loss: 0.684988, acc.: 50.39%] [G loss: 0.721830]
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8496 [D loss: 0.689181, acc.: 46.29%] [G loss: 0.722650]
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8497 [D loss: 0.692593, acc.: 44.73%] [G loss: 0.727610]
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8498 [D loss: 0.701294, acc.: 46.09%] [G loss: 0.712891]
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8499 [D loss: 0.696807, acc.: 44.92%] [G loss: 0.716778]
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8500 [D loss: 0.694783, acc.: 42.97%] [G loss: 0.731741]
1/1 [==============================] - 0s 21ms/step
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8501 [D loss: 0.696810, acc.: 46.48%] [G loss: 0.717255]
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8502 [D loss: 0.692877, acc.: 50.00%] [G loss: 0.721880]
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8503 [D loss: 0.695535, acc.: 43.95%] [G loss: 0.717651]
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8504 [D loss: 0.685380, acc.: 49.80%] [G loss: 0.719498]
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8505 [D loss: 0.679659, acc.: 49.22%] [G loss: 0.736465]
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8506 [D loss: 0.690778, acc.: 45.90%] [G loss: 0.744052]
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8507 [D loss: 0.683021, acc.: 49.80%] [G loss: 0.733430]
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8508 [D loss: 0.690402, acc.: 46.48%] [G loss: 0.733816]
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8509 [D loss: 0.688061, acc.: 49.02%] [G loss: 0.739514]
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8510 [D loss: 0.688373, acc.: 50.00%] [G loss: 0.728640]
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8511 [D loss: 0.696171, acc.: 47.85%] [G loss: 0.729647]
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8512 [D loss: 0.695217, acc.: 44.53%] [G loss: 0.713317]
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8513 [D loss: 0.695653, acc.: 47.85%] [G loss: 0.720016]
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8514 [D loss: 0.691601, acc.: 49.22%] [G loss: 0.720413]
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8515 [D loss: 0.684082, acc.: 50.20%] [G loss: 0.723934]
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8516 [D loss: 0.687715, acc.: 51.37%] [G loss: 0.725028]
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8517 [D loss: 0.699509, acc.: 46.09%] [G loss: 0.717869]
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8518 [D loss: 0.690940, acc.: 49.22%] [G loss: 0.713483]
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8519 [D loss: 0.689289, acc.: 50.20%] [G loss: 0.729732]
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8520 [D loss: 0.691135, acc.: 49.41%] [G loss: 0.739652]
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8521 [D loss: 0.683712, acc.: 53.12%] [G loss: 0.749190]
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8522 [D loss: 0.691214, acc.: 50.00%] [G loss: 0.747957]
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8523 [D loss: 0.700978, acc.: 50.20%] [G loss: 0.725919]
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8524 [D loss: 0.699861, acc.: 45.90%] [G loss: 0.723790]
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8525 [D loss: 0.692050, acc.: 48.05%] [G loss: 0.725739]
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8526 [D loss: 0.692355, acc.: 53.32%] [G loss: 0.720572]
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8527 [D loss: 0.696961, acc.: 44.92%] [G loss: 0.709947]
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8528 [D loss: 0.696046, acc.: 44.92%] [G loss: 0.718851]
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8529 [D loss: 0.692637, acc.: 46.68%] [G loss: 0.724540]
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8530 [D loss: 0.688149, acc.: 50.20%] [G loss: 0.731843]
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8531 [D loss: 0.688244, acc.: 53.71%] [G loss: 0.734569]
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8532 [D loss: 0.692565, acc.: 46.48%] [G loss: 0.740087]
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8533 [D loss: 0.687947, acc.: 50.59%] [G loss: 0.730550]
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8534 [D loss: 0.687900, acc.: 51.76%] [G loss: 0.732100]
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8535 [D loss: 0.681592, acc.: 51.95%] [G loss: 0.737873]
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8536 [D loss: 0.686961, acc.: 52.54%] [G loss: 0.722997]
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8537 [D loss: 0.686962, acc.: 50.59%] [G loss: 0.716567]
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8538 [D loss: 0.677688, acc.: 48.83%] [G loss: 0.731047]
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8539 [D loss: 0.682070, acc.: 50.00%] [G loss: 0.745474]
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8540 [D loss: 0.681373, acc.: 48.83%] [G loss: 0.748783]
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8541 [D loss: 0.692925, acc.: 48.44%] [G loss: 0.736648]
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8542 [D loss: 0.693616, acc.: 45.51%] [G loss: 0.727067]
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8543 [D loss: 0.688938, acc.: 47.66%] [G loss: 0.720396]
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8544 [D loss: 0.682391, acc.: 53.91%] [G loss: 0.721850]
8/8 [==============================] - 0s 5ms/step
8545 [D loss: 0.699720, acc.: 46.09%] [G loss: 0.718871]
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8546 [D loss: 0.686460, acc.: 49.61%] [G loss: 0.718275]
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8547 [D loss: 0.689528, acc.: 48.24%] [G loss: 0.717490]
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8548 [D loss: 0.692097, acc.: 44.14%] [G loss: 0.719579]
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8549 [D loss: 0.685449, acc.: 54.69%] [G loss: 0.738326]
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8550 [D loss: 0.686783, acc.: 49.80%] [G loss: 0.748114]
1/1 [==============================] - 0s 22ms/step
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8551 [D loss: 0.683514, acc.: 52.73%] [G loss: 0.738112]
8/8 [==============================] - 0s 5ms/step
8552 [D loss: 0.690283, acc.: 49.02%] [G loss: 0.726273]
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8553 [D loss: 0.677045, acc.: 52.34%] [G loss: 0.730845]
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8554 [D loss: 0.687110, acc.: 48.83%] [G loss: 0.729232]
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8555 [D loss: 0.687084, acc.: 50.00%] [G loss: 0.729635]
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8556 [D loss: 0.680612, acc.: 54.30%] [G loss: 0.725339]
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8557 [D loss: 0.690040, acc.: 47.27%] [G loss: 0.720108]
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8558 [D loss: 0.690365, acc.: 47.66%] [G loss: 0.732063]
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8559 [D loss: 0.683047, acc.: 51.37%] [G loss: 0.761586]
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8560 [D loss: 0.685060, acc.: 52.15%] [G loss: 0.763105]
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8561 [D loss: 0.685186, acc.: 48.24%] [G loss: 0.743694]
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8562 [D loss: 0.698766, acc.: 43.95%] [G loss: 0.725633]
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8563 [D loss: 0.695725, acc.: 47.66%] [G loss: 0.719326]
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8564 [D loss: 0.698363, acc.: 48.24%] [G loss: 0.721877]
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8565 [D loss: 0.696697, acc.: 42.19%] [G loss: 0.709124]
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8566 [D loss: 0.703964, acc.: 43.55%] [G loss: 0.712595]
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8567 [D loss: 0.702550, acc.: 47.27%] [G loss: 0.721985]
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8568 [D loss: 0.694787, acc.: 47.85%] [G loss: 0.734224]
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8569 [D loss: 0.694159, acc.: 49.22%] [G loss: 0.745646]
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8570 [D loss: 0.695145, acc.: 50.00%] [G loss: 0.722991]
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8571 [D loss: 0.695009, acc.: 50.20%] [G loss: 0.725634]
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8572 [D loss: 0.699506, acc.: 46.48%] [G loss: 0.730743]
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8573 [D loss: 0.693091, acc.: 50.98%] [G loss: 0.726792]
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8574 [D loss: 0.694725, acc.: 50.20%] [G loss: 0.716404]
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8575 [D loss: 0.694194, acc.: 46.88%] [G loss: 0.730426]
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8576 [D loss: 0.698490, acc.: 45.31%] [G loss: 0.717515]
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8577 [D loss: 0.691321, acc.: 49.22%] [G loss: 0.733122]
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8578 [D loss: 0.686732, acc.: 55.27%] [G loss: 0.745842]
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8579 [D loss: 0.687586, acc.: 48.05%] [G loss: 0.750209]
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8580 [D loss: 0.677675, acc.: 56.25%] [G loss: 0.762926]
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8581 [D loss: 0.687317, acc.: 47.85%] [G loss: 0.740772]
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8582 [D loss: 0.691834, acc.: 48.44%] [G loss: 0.749389]
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8583 [D loss: 0.692606, acc.: 49.61%] [G loss: 0.742039]
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8584 [D loss: 0.694961, acc.: 49.41%] [G loss: 0.720118]
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8585 [D loss: 0.698736, acc.: 46.68%] [G loss: 0.718332]
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8586 [D loss: 0.697989, acc.: 44.14%] [G loss: 0.708121]
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8587 [D loss: 0.699527, acc.: 41.80%] [G loss: 0.706276]
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8588 [D loss: 0.699994, acc.: 43.55%] [G loss: 0.716130]
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8589 [D loss: 0.698522, acc.: 41.99%] [G loss: 0.717400]
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8590 [D loss: 0.704949, acc.: 45.51%] [G loss: 0.728772]
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8591 [D loss: 0.694513, acc.: 48.83%] [G loss: 0.741621]
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8592 [D loss: 0.688189, acc.: 53.71%] [G loss: 0.763601]
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8593 [D loss: 0.689873, acc.: 54.10%] [G loss: 0.749157]
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8594 [D loss: 0.691663, acc.: 51.95%] [G loss: 0.741279]
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8595 [D loss: 0.688908, acc.: 54.69%] [G loss: 0.731081]
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8596 [D loss: 0.695308, acc.: 51.37%] [G loss: 0.730786]
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8597 [D loss: 0.695344, acc.: 44.92%] [G loss: 0.721896]
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8598 [D loss: 0.692103, acc.: 45.31%] [G loss: 0.713699]
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8599 [D loss: 0.695841, acc.: 48.83%] [G loss: 0.701305]
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8600 [D loss: 0.684300, acc.: 47.07%] [G loss: 0.728334]
1/1 [==============================] - 0s 18ms/step
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8601 [D loss: 0.689564, acc.: 45.70%] [G loss: 0.737922]
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8602 [D loss: 0.687798, acc.: 48.83%] [G loss: 0.745441]
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8603 [D loss: 0.689641, acc.: 49.22%] [G loss: 0.747579]
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8604 [D loss: 0.689537, acc.: 47.46%] [G loss: 0.729996]
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8605 [D loss: 0.688613, acc.: 51.95%] [G loss: 0.735719]
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8606 [D loss: 0.680989, acc.: 54.49%] [G loss: 0.729289]
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8607 [D loss: 0.688234, acc.: 51.76%] [G loss: 0.726493]
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8608 [D loss: 0.693330, acc.: 48.44%] [G loss: 0.711071]
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8609 [D loss: 0.696132, acc.: 46.29%] [G loss: 0.705181]
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8610 [D loss: 0.728006, acc.: 47.66%] [G loss: 0.681508]
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8611 [D loss: 0.707785, acc.: 47.85%] [G loss: 0.719449]
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8612 [D loss: 0.692676, acc.: 53.71%] [G loss: 0.733646]
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8613 [D loss: 0.693821, acc.: 50.00%] [G loss: 0.726416]
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8614 [D loss: 0.696041, acc.: 47.66%] [G loss: 0.731776]
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8615 [D loss: 0.699044, acc.: 44.34%] [G loss: 0.731913]
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8616 [D loss: 0.687636, acc.: 55.27%] [G loss: 0.736839]
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8617 [D loss: 0.687897, acc.: 52.93%] [G loss: 0.729504]
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8618 [D loss: 0.692078, acc.: 50.78%] [G loss: 0.708658]
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8619 [D loss: 0.696707, acc.: 46.09%] [G loss: 0.705495]
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8620 [D loss: 0.694477, acc.: 49.02%] [G loss: 0.697181]
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8621 [D loss: 0.698063, acc.: 45.51%] [G loss: 0.706041]
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8622 [D loss: 0.692470, acc.: 52.15%] [G loss: 0.713411]
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8623 [D loss: 0.693767, acc.: 51.95%] [G loss: 0.727381]
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8624 [D loss: 0.688162, acc.: 52.15%] [G loss: 0.730407]
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8625 [D loss: 0.693404, acc.: 46.88%] [G loss: 0.730530]
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8626 [D loss: 0.696428, acc.: 47.85%] [G loss: 0.725161]
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8627 [D loss: 0.691060, acc.: 50.78%] [G loss: 0.721453]
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8628 [D loss: 0.690153, acc.: 50.39%] [G loss: 0.726603]
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8629 [D loss: 0.690225, acc.: 51.17%] [G loss: 0.714275]
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8630 [D loss: 0.699454, acc.: 48.24%] [G loss: 0.711499]
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8631 [D loss: 0.693439, acc.: 45.12%] [G loss: 0.717887]
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8632 [D loss: 0.696450, acc.: 41.41%] [G loss: 0.730881]
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8633 [D loss: 0.680402, acc.: 50.20%] [G loss: 0.737790]
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8634 [D loss: 0.687937, acc.: 49.80%] [G loss: 0.751816]
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8635 [D loss: 0.684807, acc.: 52.34%] [G loss: 0.750739]
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8636 [D loss: 0.690509, acc.: 52.34%] [G loss: 0.735964]
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8637 [D loss: 0.686375, acc.: 50.00%] [G loss: 0.746911]
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8638 [D loss: 0.687747, acc.: 53.52%] [G loss: 0.741531]
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8639 [D loss: 0.689948, acc.: 50.20%] [G loss: 0.735569]
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8640 [D loss: 0.695553, acc.: 47.46%] [G loss: 0.732215]
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8641 [D loss: 0.693673, acc.: 51.56%] [G loss: 0.714005]
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8642 [D loss: 0.693201, acc.: 47.27%] [G loss: 0.718939]
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8643 [D loss: 0.689651, acc.: 50.78%] [G loss: 0.715204]
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8644 [D loss: 0.690869, acc.: 51.56%] [G loss: 0.720247]
8/8 [==============================] - 0s 5ms/step
8645 [D loss: 0.694254, acc.: 45.70%] [G loss: 0.730139]
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8646 [D loss: 0.697437, acc.: 48.83%] [G loss: 0.722667]
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8647 [D loss: 0.695555, acc.: 49.80%] [G loss: 0.723359]
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8648 [D loss: 0.698237, acc.: 45.90%] [G loss: 0.714556]
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8649 [D loss: 0.696937, acc.: 48.63%] [G loss: 0.716201]
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8650 [D loss: 0.693487, acc.: 51.37%] [G loss: 0.715555]
1/1 [==============================] - 0s 20ms/step
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8651 [D loss: 0.687973, acc.: 56.05%] [G loss: 0.721649]
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8652 [D loss: 0.697250, acc.: 53.71%] [G loss: 0.729402]
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8653 [D loss: 0.691309, acc.: 52.93%] [G loss: 0.729340]
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8654 [D loss: 0.694860, acc.: 49.02%] [G loss: 0.717463]
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8655 [D loss: 0.691596, acc.: 49.61%] [G loss: 0.740312]
8/8 [==============================] - 0s 5ms/step
8656 [D loss: 0.689057, acc.: 52.54%] [G loss: 0.742630]
8/8 [==============================] - 0s 7ms/step
8657 [D loss: 0.687153, acc.: 53.52%] [G loss: 0.735792]
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8658 [D loss: 0.685754, acc.: 49.61%] [G loss: 0.739800]
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8659 [D loss: 0.683767, acc.: 52.93%] [G loss: 0.737978]
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8660 [D loss: 0.685386, acc.: 53.32%] [G loss: 0.725646]
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8661 [D loss: 0.687215, acc.: 53.71%] [G loss: 0.725858]
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8662 [D loss: 0.680338, acc.: 56.84%] [G loss: 0.728811]
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8663 [D loss: 0.690040, acc.: 50.78%] [G loss: 0.713160]
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8664 [D loss: 0.698123, acc.: 48.63%] [G loss: 0.703829]
8/8 [==============================] - 0s 5ms/step
8665 [D loss: 0.690536, acc.: 47.85%] [G loss: 0.715030]
8/8 [==============================] - 0s 5ms/step
8666 [D loss: 0.697649, acc.: 42.38%] [G loss: 0.707574]
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8667 [D loss: 0.690465, acc.: 48.44%] [G loss: 0.715903]
8/8 [==============================] - 0s 5ms/step
8668 [D loss: 0.690111, acc.: 42.58%] [G loss: 0.720644]
8/8 [==============================] - 0s 5ms/step
8669 [D loss: 0.693406, acc.: 49.22%] [G loss: 0.719160]
8/8 [==============================] - 0s 5ms/step
8670 [D loss: 0.694286, acc.: 47.46%] [G loss: 0.724993]
8/8 [==============================] - 0s 5ms/step
8671 [D loss: 0.690121, acc.: 49.22%] [G loss: 0.729478]
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8672 [D loss: 0.688659, acc.: 48.63%] [G loss: 0.741617]
8/8 [==============================] - 0s 5ms/step
8673 [D loss: 0.691965, acc.: 48.24%] [G loss: 0.733675]
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8674 [D loss: 0.682166, acc.: 50.98%] [G loss: 0.726337]
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8675 [D loss: 0.688741, acc.: 48.83%] [G loss: 0.723001]
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8676 [D loss: 0.693202, acc.: 46.88%] [G loss: 0.716846]
8/8 [==============================] - 0s 5ms/step
8677 [D loss: 0.688012, acc.: 46.09%] [G loss: 0.733317]
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8678 [D loss: 0.691748, acc.: 46.68%] [G loss: 0.732096]
8/8 [==============================] - 0s 5ms/step
8679 [D loss: 0.688314, acc.: 49.02%] [G loss: 0.734411]
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8680 [D loss: 0.696738, acc.: 47.07%] [G loss: 0.731306]
8/8 [==============================] - 0s 5ms/step
8681 [D loss: 0.697726, acc.: 47.07%] [G loss: 0.718151]
8/8 [==============================] - 0s 5ms/step
8682 [D loss: 0.703582, acc.: 45.12%] [G loss: 0.719980]
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8683 [D loss: 0.702758, acc.: 41.80%] [G loss: 0.713224]
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8684 [D loss: 0.707323, acc.: 43.55%] [G loss: 0.713811]
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8685 [D loss: 0.695968, acc.: 48.44%] [G loss: 0.725159]
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8686 [D loss: 0.693766, acc.: 50.78%] [G loss: 0.729792]
8/8 [==============================] - 0s 5ms/step
8687 [D loss: 0.695881, acc.: 44.34%] [G loss: 0.718388]
8/8 [==============================] - 0s 5ms/step
8688 [D loss: 0.692557, acc.: 50.20%] [G loss: 0.728871]
8/8 [==============================] - 0s 5ms/step
8689 [D loss: 0.688450, acc.: 53.12%] [G loss: 0.729992]
8/8 [==============================] - 0s 5ms/step
8690 [D loss: 0.692584, acc.: 48.44%] [G loss: 0.717289]
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8691 [D loss: 0.687459, acc.: 44.34%] [G loss: 0.724119]
8/8 [==============================] - 0s 5ms/step
8692 [D loss: 0.686147, acc.: 49.02%] [G loss: 0.723043]
8/8 [==============================] - 0s 5ms/step
8693 [D loss: 0.684341, acc.: 51.76%] [G loss: 0.737075]
8/8 [==============================] - 0s 5ms/step
8694 [D loss: 0.682551, acc.: 52.54%] [G loss: 0.752983]
8/8 [==============================] - 0s 5ms/step
8695 [D loss: 0.679600, acc.: 53.32%] [G loss: 0.740995]
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8696 [D loss: 0.682731, acc.: 56.05%] [G loss: 0.736257]
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8697 [D loss: 0.675846, acc.: 56.64%] [G loss: 0.739723]
8/8 [==============================] - 0s 5ms/step
8698 [D loss: 0.681076, acc.: 54.10%] [G loss: 0.742087]
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8699 [D loss: 0.686387, acc.: 51.56%] [G loss: 0.708812]
8/8 [==============================] - 0s 5ms/step
8700 [D loss: 0.697701, acc.: 43.36%] [G loss: 0.712909]
1/1 [==============================] - 0s 20ms/step
8/8 [==============================] - 0s 5ms/step
8701 [D loss: 0.691874, acc.: 48.44%] [G loss: 0.730730]
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8702 [D loss: 0.690161, acc.: 51.56%] [G loss: 0.742239]
8/8 [==============================] - 0s 5ms/step
8703 [D loss: 0.693447, acc.: 48.24%] [G loss: 0.752784]
8/8 [==============================] - 0s 5ms/step
8704 [D loss: 0.700051, acc.: 39.45%] [G loss: 0.724369]
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8705 [D loss: 0.697388, acc.: 47.46%] [G loss: 0.737651]
8/8 [==============================] - 0s 5ms/step
8706 [D loss: 0.683280, acc.: 54.30%] [G loss: 0.754567]
8/8 [==============================] - 0s 5ms/step
8707 [D loss: 0.686179, acc.: 54.10%] [G loss: 0.738434]
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8708 [D loss: 0.692577, acc.: 48.63%] [G loss: 0.714036]
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8709 [D loss: 0.691747, acc.: 48.44%] [G loss: 0.728338]
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8710 [D loss: 0.691029, acc.: 49.80%] [G loss: 0.734042]
8/8 [==============================] - 0s 5ms/step
8711 [D loss: 0.694259, acc.: 45.12%] [G loss: 0.743159]
8/8 [==============================] - 0s 5ms/step
8712 [D loss: 0.695986, acc.: 47.46%] [G loss: 0.729087]
8/8 [==============================] - 0s 5ms/step
8713 [D loss: 0.710108, acc.: 41.99%] [G loss: 0.711739]
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8714 [D loss: 0.698332, acc.: 47.46%] [G loss: 0.718465]
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8715 [D loss: 0.690914, acc.: 54.49%] [G loss: 0.730474]
8/8 [==============================] - 0s 5ms/step
8716 [D loss: 0.695777, acc.: 45.70%] [G loss: 0.720350]
8/8 [==============================] - 0s 5ms/step
8717 [D loss: 0.695986, acc.: 50.00%] [G loss: 0.705162]
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8718 [D loss: 0.687929, acc.: 52.73%] [G loss: 0.706373]
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8719 [D loss: 0.682873, acc.: 57.42%] [G loss: 0.742786]
8/8 [==============================] - 0s 5ms/step
8720 [D loss: 0.679309, acc.: 54.88%] [G loss: 0.734012]
8/8 [==============================] - 0s 5ms/step
8721 [D loss: 0.683033, acc.: 51.95%] [G loss: 0.740368]
8/8 [==============================] - 0s 5ms/step
8722 [D loss: 0.693467, acc.: 42.97%] [G loss: 0.728522]
8/8 [==============================] - 0s 5ms/step
8723 [D loss: 0.690866, acc.: 46.09%] [G loss: 0.733150]
8/8 [==============================] - 0s 5ms/step
8724 [D loss: 0.686041, acc.: 49.61%] [G loss: 0.731252]
8/8 [==============================] - 0s 5ms/step
8725 [D loss: 0.687652, acc.: 48.63%] [G loss: 0.722096]
8/8 [==============================] - 0s 5ms/step
8726 [D loss: 0.676660, acc.: 49.22%] [G loss: 0.716921]
8/8 [==============================] - 0s 5ms/step
8727 [D loss: 0.691369, acc.: 44.14%] [G loss: 0.716934]
8/8 [==============================] - 0s 6ms/step
8728 [D loss: 0.685087, acc.: 49.61%] [G loss: 0.732962]
8/8 [==============================] - 0s 5ms/step
8729 [D loss: 0.681666, acc.: 50.39%] [G loss: 0.735296]
8/8 [==============================] - 0s 5ms/step
8730 [D loss: 0.685726, acc.: 51.76%] [G loss: 0.746296]
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8731 [D loss: 0.694079, acc.: 51.17%] [G loss: 0.742109]
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8732 [D loss: 0.692088, acc.: 52.34%] [G loss: 0.740346]
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8733 [D loss: 0.689705, acc.: 49.80%] [G loss: 0.732330]
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8734 [D loss: 0.689524, acc.: 50.78%] [G loss: 0.729324]
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8735 [D loss: 0.688605, acc.: 50.20%] [G loss: 0.726906]
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8736 [D loss: 0.693038, acc.: 44.92%] [G loss: 0.717352]
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8737 [D loss: 0.696304, acc.: 43.75%] [G loss: 0.718411]
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8738 [D loss: 0.690623, acc.: 47.66%] [G loss: 0.730918]
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8739 [D loss: 0.687655, acc.: 46.88%] [G loss: 0.739691]
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8740 [D loss: 0.673386, acc.: 54.49%] [G loss: 0.746098]
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8741 [D loss: 0.679481, acc.: 49.61%] [G loss: 0.750965]
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8742 [D loss: 0.690495, acc.: 48.83%] [G loss: 0.730213]
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8743 [D loss: 0.683541, acc.: 52.54%] [G loss: 0.725198]
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8744 [D loss: 0.685956, acc.: 51.37%] [G loss: 0.727118]
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8745 [D loss: 0.686215, acc.: 47.07%] [G loss: 0.716452]
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8746 [D loss: 0.692856, acc.: 45.90%] [G loss: 0.719943]
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8747 [D loss: 0.690086, acc.: 47.66%] [G loss: 0.715129]
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8748 [D loss: 0.688023, acc.: 50.78%] [G loss: 0.719698]
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8749 [D loss: 0.687137, acc.: 53.91%] [G loss: 0.725937]
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8750 [D loss: 0.693913, acc.: 47.46%] [G loss: 0.738751]
1/1 [==============================] - 0s 20ms/step
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8751 [D loss: 0.689426, acc.: 48.83%] [G loss: 0.735300]
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8752 [D loss: 0.695090, acc.: 47.27%] [G loss: 0.736045]
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8753 [D loss: 0.686461, acc.: 54.69%] [G loss: 0.730730]
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8754 [D loss: 0.686918, acc.: 51.56%] [G loss: 0.728870]
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8755 [D loss: 0.690492, acc.: 50.39%] [G loss: 0.715832]
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8756 [D loss: 0.685143, acc.: 50.59%] [G loss: 0.729386]
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8757 [D loss: 0.685337, acc.: 51.17%] [G loss: 0.734578]
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8758 [D loss: 0.688688, acc.: 46.88%] [G loss: 0.741159]
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8759 [D loss: 0.694652, acc.: 47.46%] [G loss: 0.738029]
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8760 [D loss: 0.677067, acc.: 52.73%] [G loss: 0.742057]
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8761 [D loss: 0.682582, acc.: 51.95%] [G loss: 0.752854]
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8762 [D loss: 0.676487, acc.: 48.24%] [G loss: 0.750497]
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8763 [D loss: 0.684565, acc.: 49.80%] [G loss: 0.737724]
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8764 [D loss: 0.690008, acc.: 46.68%] [G loss: 0.736672]
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8765 [D loss: 0.694570, acc.: 47.07%] [G loss: 0.724440]
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8766 [D loss: 0.700010, acc.: 42.19%] [G loss: 0.709572]
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8767 [D loss: 0.698264, acc.: 45.90%] [G loss: 0.706402]
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8768 [D loss: 0.696095, acc.: 43.95%] [G loss: 0.718282]
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8769 [D loss: 0.700698, acc.: 42.58%] [G loss: 0.708994]
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8770 [D loss: 0.705072, acc.: 44.53%] [G loss: 0.708355]
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8771 [D loss: 0.692637, acc.: 49.41%] [G loss: 0.714188]
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8772 [D loss: 0.690498, acc.: 48.83%] [G loss: 0.726862]
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8773 [D loss: 0.694959, acc.: 47.07%] [G loss: 0.729916]
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8774 [D loss: 0.695709, acc.: 49.41%] [G loss: 0.715813]
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8775 [D loss: 0.687122, acc.: 54.69%] [G loss: 0.732936]
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8776 [D loss: 0.685445, acc.: 51.56%] [G loss: 0.742957]
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8777 [D loss: 0.687000, acc.: 51.95%] [G loss: 0.746642]
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8778 [D loss: 0.696264, acc.: 48.44%] [G loss: 0.756600]
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8779 [D loss: 0.690111, acc.: 48.24%] [G loss: 0.746632]
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8780 [D loss: 0.685076, acc.: 55.47%] [G loss: 0.735815]
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8781 [D loss: 0.687458, acc.: 53.32%] [G loss: 0.742725]
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8782 [D loss: 0.689976, acc.: 49.80%] [G loss: 0.727487]
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8783 [D loss: 0.691095, acc.: 50.00%] [G loss: 0.720246]
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8784 [D loss: 0.694963, acc.: 50.20%] [G loss: 0.709627]
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8785 [D loss: 0.692512, acc.: 49.80%] [G loss: 0.738734]
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8786 [D loss: 0.687694, acc.: 50.98%] [G loss: 0.741884]
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8787 [D loss: 0.693354, acc.: 48.44%] [G loss: 0.746601]
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8788 [D loss: 0.695854, acc.: 46.29%] [G loss: 0.743696]
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8789 [D loss: 0.685454, acc.: 50.00%] [G loss: 0.732874]
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8790 [D loss: 0.692439, acc.: 47.46%] [G loss: 0.734411]
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8791 [D loss: 0.691064, acc.: 52.93%] [G loss: 0.724271]
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8792 [D loss: 0.692658, acc.: 49.22%] [G loss: 0.720699]
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8793 [D loss: 0.700434, acc.: 46.29%] [G loss: 0.702116]
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8794 [D loss: 0.698350, acc.: 47.85%] [G loss: 0.712145]
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8795 [D loss: 0.691460, acc.: 48.05%] [G loss: 0.732220]
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8796 [D loss: 0.692982, acc.: 46.09%] [G loss: 0.738569]
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8797 [D loss: 0.700009, acc.: 41.41%] [G loss: 0.725459]
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8798 [D loss: 0.702724, acc.: 43.95%] [G loss: 0.719312]
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8799 [D loss: 0.696819, acc.: 48.05%] [G loss: 0.712459]
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8800 [D loss: 0.695964, acc.: 47.46%] [G loss: 0.719166]
1/1 [==============================] - 0s 18ms/step
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8801 [D loss: 0.691154, acc.: 49.02%] [G loss: 0.715062]
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8802 [D loss: 0.689472, acc.: 49.22%] [G loss: 0.723871]
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8803 [D loss: 0.701406, acc.: 48.83%] [G loss: 0.716716]
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8804 [D loss: 0.689415, acc.: 52.34%] [G loss: 0.726210]
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8805 [D loss: 0.688039, acc.: 52.34%] [G loss: 0.737654]
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8806 [D loss: 0.683791, acc.: 54.30%] [G loss: 0.736519]
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8807 [D loss: 0.696518, acc.: 50.98%] [G loss: 0.730645]
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8808 [D loss: 0.691533, acc.: 50.78%] [G loss: 0.737361]
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8809 [D loss: 0.695637, acc.: 51.76%] [G loss: 0.755472]
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8810 [D loss: 0.690750, acc.: 54.49%] [G loss: 0.742097]
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8811 [D loss: 0.698607, acc.: 50.39%] [G loss: 0.719102]
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8812 [D loss: 0.692892, acc.: 51.37%] [G loss: 0.730204]
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8813 [D loss: 0.693071, acc.: 52.15%] [G loss: 0.732405]
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8814 [D loss: 0.698441, acc.: 45.51%] [G loss: 0.728806]
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8815 [D loss: 0.691320, acc.: 50.00%] [G loss: 0.738861]
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8816 [D loss: 0.695139, acc.: 48.44%] [G loss: 0.746316]
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8817 [D loss: 0.691093, acc.: 45.70%] [G loss: 0.746523]
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8818 [D loss: 0.687583, acc.: 48.63%] [G loss: 0.751141]
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8819 [D loss: 0.682483, acc.: 53.12%] [G loss: 0.749836]
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8820 [D loss: 0.683572, acc.: 58.40%] [G loss: 0.734937]
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8821 [D loss: 0.689573, acc.: 53.71%] [G loss: 0.726677]
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8822 [D loss: 0.698867, acc.: 46.88%] [G loss: 0.723877]
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8823 [D loss: 0.693329, acc.: 50.78%] [G loss: 0.723156]
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8824 [D loss: 0.694483, acc.: 49.61%] [G loss: 0.730369]
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8825 [D loss: 0.693356, acc.: 48.44%] [G loss: 0.731418]
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8826 [D loss: 0.695085, acc.: 50.00%] [G loss: 0.724140]
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8827 [D loss: 0.698710, acc.: 45.31%] [G loss: 0.724844]
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8828 [D loss: 0.697208, acc.: 45.70%] [G loss: 0.727325]
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8829 [D loss: 0.693424, acc.: 54.30%] [G loss: 0.730413]
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8830 [D loss: 0.689408, acc.: 51.37%] [G loss: 0.737512]
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8831 [D loss: 0.691964, acc.: 50.59%] [G loss: 0.719793]
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8832 [D loss: 0.691464, acc.: 51.76%] [G loss: 0.726492]
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8833 [D loss: 0.688634, acc.: 50.59%] [G loss: 0.726808]
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8834 [D loss: 0.691484, acc.: 47.85%] [G loss: 0.723295]
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8835 [D loss: 0.687391, acc.: 50.20%] [G loss: 0.731330]
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8836 [D loss: 0.701934, acc.: 46.09%] [G loss: 0.717707]
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8837 [D loss: 0.711147, acc.: 50.78%] [G loss: 0.710948]
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8838 [D loss: 0.701758, acc.: 46.48%] [G loss: 0.741272]
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8839 [D loss: 0.701218, acc.: 48.83%] [G loss: 0.730943]
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8840 [D loss: 0.692192, acc.: 50.78%] [G loss: 0.732518]
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8841 [D loss: 0.688419, acc.: 59.77%] [G loss: 0.741312]
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8842 [D loss: 0.687560, acc.: 59.18%] [G loss: 0.729428]
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8843 [D loss: 0.702804, acc.: 48.05%] [G loss: 0.723997]
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8844 [D loss: 0.697140, acc.: 48.24%] [G loss: 0.708911]
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8845 [D loss: 0.692382, acc.: 51.56%] [G loss: 0.730219]
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8846 [D loss: 0.697464, acc.: 48.44%] [G loss: 0.733327]
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8847 [D loss: 0.691322, acc.: 50.39%] [G loss: 0.737963]
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8848 [D loss: 0.696606, acc.: 44.53%] [G loss: 0.730853]
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8849 [D loss: 0.704570, acc.: 41.02%] [G loss: 0.715595]
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8850 [D loss: 0.701106, acc.: 49.61%] [G loss: 0.720315]
1/1 [==============================] - 0s 32ms/step
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8851 [D loss: 0.691468, acc.: 52.93%] [G loss: 0.737061]
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8852 [D loss: 0.685236, acc.: 57.03%] [G loss: 0.735289]
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8853 [D loss: 0.694683, acc.: 52.54%] [G loss: 0.734492]
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8854 [D loss: 0.687698, acc.: 52.73%] [G loss: 0.749811]
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8855 [D loss: 0.684564, acc.: 57.62%] [G loss: 0.753769]
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8856 [D loss: 0.679571, acc.: 56.84%] [G loss: 0.752021]
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8857 [D loss: 0.678678, acc.: 57.81%] [G loss: 0.750896]
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8858 [D loss: 0.682481, acc.: 53.12%] [G loss: 0.744186]
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8859 [D loss: 0.684080, acc.: 52.15%] [G loss: 0.739982]
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8860 [D loss: 0.688422, acc.: 52.73%] [G loss: 0.728023]
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8861 [D loss: 0.684787, acc.: 52.15%] [G loss: 0.726597]
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8862 [D loss: 0.691645, acc.: 48.05%] [G loss: 0.719765]
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8863 [D loss: 0.689143, acc.: 50.78%] [G loss: 0.716993]
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8864 [D loss: 0.690824, acc.: 47.66%] [G loss: 0.724475]
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8865 [D loss: 0.693775, acc.: 47.46%] [G loss: 0.727343]
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8866 [D loss: 0.694229, acc.: 45.31%] [G loss: 0.730572]
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8867 [D loss: 0.694918, acc.: 48.44%] [G loss: 0.718173]
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8868 [D loss: 0.685874, acc.: 54.30%] [G loss: 0.732340]
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8869 [D loss: 0.687889, acc.: 54.49%] [G loss: 0.729492]
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8870 [D loss: 0.693091, acc.: 50.39%] [G loss: 0.721193]
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8871 [D loss: 0.694318, acc.: 45.70%] [G loss: 0.726626]
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8872 [D loss: 0.696117, acc.: 46.29%] [G loss: 0.727453]
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8873 [D loss: 0.691190, acc.: 53.32%] [G loss: 0.735143]
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8874 [D loss: 0.696861, acc.: 46.68%] [G loss: 0.751736]
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8875 [D loss: 0.701569, acc.: 45.90%] [G loss: 0.719239]
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8876 [D loss: 0.693107, acc.: 50.78%] [G loss: 0.749621]
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8877 [D loss: 0.692514, acc.: 49.22%] [G loss: 0.724715]
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8878 [D loss: 0.701657, acc.: 43.36%] [G loss: 0.721403]
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8879 [D loss: 0.688164, acc.: 50.00%] [G loss: 0.724167]
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8880 [D loss: 0.683385, acc.: 50.98%] [G loss: 0.746735]
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8881 [D loss: 0.688278, acc.: 48.63%] [G loss: 0.749363]
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8882 [D loss: 0.689046, acc.: 47.27%] [G loss: 0.745907]
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8883 [D loss: 0.688380, acc.: 50.20%] [G loss: 0.752488]
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8884 [D loss: 0.689367, acc.: 54.88%] [G loss: 0.760176]
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8885 [D loss: 0.677639, acc.: 54.10%] [G loss: 0.747330]
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8886 [D loss: 0.700070, acc.: 43.55%] [G loss: 0.716607]
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8887 [D loss: 0.690471, acc.: 49.41%] [G loss: 0.716708]
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8888 [D loss: 0.695904, acc.: 47.85%] [G loss: 0.716003]
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8889 [D loss: 0.697456, acc.: 46.29%] [G loss: 0.721274]
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8890 [D loss: 0.692342, acc.: 48.24%] [G loss: 0.726084]
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8891 [D loss: 0.693763, acc.: 49.61%] [G loss: 0.734269]
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8892 [D loss: 0.694993, acc.: 43.16%] [G loss: 0.721659]
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8893 [D loss: 0.694841, acc.: 46.29%] [G loss: 0.715476]
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8894 [D loss: 0.694260, acc.: 49.41%] [G loss: 0.724978]
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8895 [D loss: 0.689130, acc.: 50.20%] [G loss: 0.727899]
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8896 [D loss: 0.686361, acc.: 53.91%] [G loss: 0.727732]
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8897 [D loss: 0.685096, acc.: 54.69%] [G loss: 0.730305]
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8898 [D loss: 0.690781, acc.: 48.83%] [G loss: 0.724349]
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8899 [D loss: 0.689327, acc.: 50.39%] [G loss: 0.739542]
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8900 [D loss: 0.689392, acc.: 48.63%] [G loss: 0.739165]
1/1 [==============================] - 0s 19ms/step
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8901 [D loss: 0.685964, acc.: 44.92%] [G loss: 0.742781]
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8902 [D loss: 0.694081, acc.: 46.29%] [G loss: 0.738926]
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8903 [D loss: 0.694863, acc.: 49.61%] [G loss: 0.737585]
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8904 [D loss: 0.687849, acc.: 48.24%] [G loss: 0.733011]
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8905 [D loss: 0.676708, acc.: 49.80%] [G loss: 0.737337]
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8906 [D loss: 0.691541, acc.: 49.61%] [G loss: 0.725501]
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8907 [D loss: 0.684864, acc.: 50.78%] [G loss: 0.733798]
8/8 [==============================] - 0s 5ms/step
8908 [D loss: 0.680595, acc.: 53.12%] [G loss: 0.738908]
8/8 [==============================] - 0s 5ms/step
8909 [D loss: 0.688795, acc.: 50.20%] [G loss: 0.732865]
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8910 [D loss: 0.677485, acc.: 55.66%] [G loss: 0.745484]
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8911 [D loss: 0.688481, acc.: 46.88%] [G loss: 0.728451]
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8912 [D loss: 0.689464, acc.: 49.61%] [G loss: 0.732212]
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8913 [D loss: 0.683083, acc.: 49.41%] [G loss: 0.740720]
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8914 [D loss: 0.683510, acc.: 49.80%] [G loss: 0.745026]
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8915 [D loss: 0.690906, acc.: 45.90%] [G loss: 0.716605]
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8916 [D loss: 0.698236, acc.: 46.09%] [G loss: 0.719153]
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8917 [D loss: 0.696541, acc.: 48.63%] [G loss: 0.743223]
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8918 [D loss: 0.686714, acc.: 49.41%] [G loss: 0.735984]
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8919 [D loss: 0.688968, acc.: 48.05%] [G loss: 0.736457]
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8920 [D loss: 0.688205, acc.: 50.39%] [G loss: 0.736066]
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8921 [D loss: 0.686091, acc.: 50.59%] [G loss: 0.737899]
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8922 [D loss: 0.691666, acc.: 48.83%] [G loss: 0.727984]
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8923 [D loss: 0.681836, acc.: 54.10%] [G loss: 0.714291]
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8924 [D loss: 0.693710, acc.: 46.68%] [G loss: 0.715001]
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8925 [D loss: 0.688713, acc.: 48.83%] [G loss: 0.721136]
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8926 [D loss: 0.686836, acc.: 49.02%] [G loss: 0.735148]
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8927 [D loss: 0.690196, acc.: 50.00%] [G loss: 0.743051]
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8928 [D loss: 0.686875, acc.: 51.56%] [G loss: 0.734556]
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8929 [D loss: 0.694230, acc.: 52.54%] [G loss: 0.727170]
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8930 [D loss: 0.703097, acc.: 44.14%] [G loss: 0.728805]
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8931 [D loss: 0.699716, acc.: 47.07%] [G loss: 0.712808]
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8932 [D loss: 0.703216, acc.: 45.12%] [G loss: 0.718760]
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8933 [D loss: 0.694532, acc.: 48.83%] [G loss: 0.731396]
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8934 [D loss: 0.696394, acc.: 48.24%] [G loss: 0.712770]
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8935 [D loss: 0.699631, acc.: 47.07%] [G loss: 0.717936]
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8936 [D loss: 0.692012, acc.: 48.63%] [G loss: 0.722084]
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8937 [D loss: 0.691294, acc.: 51.95%] [G loss: 0.722890]
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8938 [D loss: 0.687608, acc.: 52.15%] [G loss: 0.729277]
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8939 [D loss: 0.685272, acc.: 53.12%] [G loss: 0.735216]
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8940 [D loss: 0.693925, acc.: 49.02%] [G loss: 0.724551]
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8941 [D loss: 0.690445, acc.: 48.83%] [G loss: 0.726077]
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8942 [D loss: 0.689749, acc.: 52.15%] [G loss: 0.731456]
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8943 [D loss: 0.679097, acc.: 52.34%] [G loss: 0.726363]
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8944 [D loss: 0.675853, acc.: 51.17%] [G loss: 0.745679]
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8945 [D loss: 0.681295, acc.: 54.69%] [G loss: 0.744503]
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8946 [D loss: 0.682171, acc.: 55.08%] [G loss: 0.756516]
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8947 [D loss: 0.681037, acc.: 54.88%] [G loss: 0.758736]
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8948 [D loss: 0.683132, acc.: 53.12%] [G loss: 0.755503]
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8949 [D loss: 0.683166, acc.: 46.68%] [G loss: 0.739693]
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8950 [D loss: 0.675596, acc.: 51.76%] [G loss: 0.739220]
1/1 [==============================] - 0s 18ms/step
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8951 [D loss: 0.694334, acc.: 48.83%] [G loss: 0.730975]
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8952 [D loss: 0.702560, acc.: 45.90%] [G loss: 0.700158]
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8953 [D loss: 0.696318, acc.: 46.68%] [G loss: 0.697637]
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8954 [D loss: 0.688047, acc.: 49.80%] [G loss: 0.728303]
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8955 [D loss: 0.689954, acc.: 50.78%] [G loss: 0.732850]
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8956 [D loss: 0.686567, acc.: 51.95%] [G loss: 0.759028]
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8957 [D loss: 0.684638, acc.: 51.17%] [G loss: 0.741795]
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8958 [D loss: 0.688533, acc.: 52.93%] [G loss: 0.742291]
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8959 [D loss: 0.695360, acc.: 47.85%] [G loss: 0.740554]
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8960 [D loss: 0.708066, acc.: 46.68%] [G loss: 0.744907]
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8961 [D loss: 0.697825, acc.: 50.39%] [G loss: 0.748140]
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8962 [D loss: 0.712748, acc.: 47.46%] [G loss: 0.722918]
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8963 [D loss: 0.703551, acc.: 45.90%] [G loss: 0.722309]
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8964 [D loss: 0.700496, acc.: 47.85%] [G loss: 0.717924]
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8965 [D loss: 0.690778, acc.: 52.15%] [G loss: 0.725952]
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8966 [D loss: 0.685575, acc.: 58.20%] [G loss: 0.754436]
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8967 [D loss: 0.680304, acc.: 54.69%] [G loss: 0.783258]
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8968 [D loss: 0.679823, acc.: 55.47%] [G loss: 0.794232]
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8969 [D loss: 0.693942, acc.: 51.76%] [G loss: 0.752142]
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8970 [D loss: 0.698247, acc.: 47.46%] [G loss: 0.741117]
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8971 [D loss: 0.693841, acc.: 46.88%] [G loss: 0.728266]
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8972 [D loss: 0.700404, acc.: 45.51%] [G loss: 0.720052]
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8973 [D loss: 0.707549, acc.: 43.75%] [G loss: 0.710444]
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8974 [D loss: 0.705534, acc.: 44.53%] [G loss: 0.705397]
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8975 [D loss: 0.706228, acc.: 42.38%] [G loss: 0.718475]
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8976 [D loss: 0.695359, acc.: 48.44%] [G loss: 0.738679]
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8977 [D loss: 0.693092, acc.: 50.39%] [G loss: 0.760007]
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8978 [D loss: 0.690641, acc.: 54.10%] [G loss: 0.751184]
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8979 [D loss: 0.695712, acc.: 48.83%] [G loss: 0.747001]
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8980 [D loss: 0.687050, acc.: 56.45%] [G loss: 0.747628]
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8981 [D loss: 0.678496, acc.: 60.74%] [G loss: 0.759121]
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8982 [D loss: 0.689424, acc.: 50.00%] [G loss: 0.729919]
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8983 [D loss: 0.696056, acc.: 46.48%] [G loss: 0.705656]
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8984 [D loss: 0.695400, acc.: 48.63%] [G loss: 0.715913]
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8985 [D loss: 0.691525, acc.: 49.02%] [G loss: 0.729060]
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8986 [D loss: 0.692096, acc.: 47.46%] [G loss: 0.740991]
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8987 [D loss: 0.686613, acc.: 50.78%] [G loss: 0.748154]
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8988 [D loss: 0.690436, acc.: 49.41%] [G loss: 0.737530]
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8989 [D loss: 0.693197, acc.: 47.46%] [G loss: 0.738215]
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8990 [D loss: 0.678918, acc.: 58.40%] [G loss: 0.748519]
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8991 [D loss: 0.677814, acc.: 57.42%] [G loss: 0.748316]
8/8 [==============================] - 0s 5ms/step
8992 [D loss: 0.682640, acc.: 54.10%] [G loss: 0.741813]
8/8 [==============================] - 0s 5ms/step
8993 [D loss: 0.683600, acc.: 53.32%] [G loss: 0.723051]
8/8 [==============================] - 0s 5ms/step
8994 [D loss: 0.687575, acc.: 52.15%] [G loss: 0.730659]
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8995 [D loss: 0.691670, acc.: 50.98%] [G loss: 0.744448]
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8996 [D loss: 0.692695, acc.: 52.15%] [G loss: 0.763417]
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8997 [D loss: 0.694641, acc.: 48.63%] [G loss: 0.755558]
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8998 [D loss: 0.704114, acc.: 47.85%] [G loss: 0.725496]
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8999 [D loss: 0.705128, acc.: 47.85%] [G loss: 0.727970]
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9000 [D loss: 0.689418, acc.: 55.08%] [G loss: 0.750414]
1/1 [==============================] - 0s 19ms/step
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9001 [D loss: 0.698094, acc.: 49.02%] [G loss: 0.734700]
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9002 [D loss: 0.702617, acc.: 45.70%] [G loss: 0.724183]
8/8 [==============================] - 0s 5ms/step
9003 [D loss: 0.695604, acc.: 52.73%] [G loss: 0.728875]
8/8 [==============================] - 0s 5ms/step
9004 [D loss: 0.689981, acc.: 53.12%] [G loss: 0.746340]
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9005 [D loss: 0.686150, acc.: 53.12%] [G loss: 0.750547]
8/8 [==============================] - 0s 5ms/step
9006 [D loss: 0.699276, acc.: 49.22%] [G loss: 0.740467]
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9007 [D loss: 0.696208, acc.: 48.63%] [G loss: 0.737941]
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9008 [D loss: 0.680539, acc.: 56.25%] [G loss: 0.753052]
8/8 [==============================] - 0s 5ms/step
9009 [D loss: 0.686133, acc.: 55.08%] [G loss: 0.761228]
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9010 [D loss: 0.691810, acc.: 54.88%] [G loss: 0.742315]
8/8 [==============================] - 0s 5ms/step
9011 [D loss: 0.692971, acc.: 47.85%] [G loss: 0.722571]
8/8 [==============================] - 0s 5ms/step
9012 [D loss: 0.688451, acc.: 51.76%] [G loss: 0.734111]
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9013 [D loss: 0.686612, acc.: 49.02%] [G loss: 0.766237]
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9014 [D loss: 0.676629, acc.: 54.10%] [G loss: 0.786143]
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9015 [D loss: 0.693119, acc.: 52.54%] [G loss: 0.770202]
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9016 [D loss: 0.692477, acc.: 46.29%] [G loss: 0.743674]
8/8 [==============================] - 0s 5ms/step
9017 [D loss: 0.688790, acc.: 52.34%] [G loss: 0.738054]
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9018 [D loss: 0.684709, acc.: 55.66%] [G loss: 0.751273]
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9019 [D loss: 0.683036, acc.: 55.47%] [G loss: 0.731890]
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9020 [D loss: 0.686637, acc.: 50.78%] [G loss: 0.708323]
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9021 [D loss: 0.692502, acc.: 50.59%] [G loss: 0.701904]
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9022 [D loss: 0.693889, acc.: 49.02%] [G loss: 0.719734]
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9023 [D loss: 0.688700, acc.: 50.20%] [G loss: 0.737420]
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9024 [D loss: 0.688803, acc.: 46.88%] [G loss: 0.755092]
8/8 [==============================] - 0s 5ms/step
9025 [D loss: 0.691202, acc.: 48.83%] [G loss: 0.737533]
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9026 [D loss: 0.696224, acc.: 44.53%] [G loss: 0.730953]
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9027 [D loss: 0.684536, acc.: 53.71%] [G loss: 0.734675]
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9028 [D loss: 0.691510, acc.: 47.66%] [G loss: 0.734724]
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9029 [D loss: 0.692380, acc.: 52.54%] [G loss: 0.732456]
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9030 [D loss: 0.691242, acc.: 50.78%] [G loss: 0.717568]
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9031 [D loss: 0.692158, acc.: 49.61%] [G loss: 0.738708]
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9032 [D loss: 0.685300, acc.: 51.76%] [G loss: 0.727876]
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9033 [D loss: 0.683520, acc.: 52.15%] [G loss: 0.737817]
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9034 [D loss: 0.687707, acc.: 48.44%] [G loss: 0.740903]
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9035 [D loss: 0.694321, acc.: 48.83%] [G loss: 0.737362]
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9036 [D loss: 0.691778, acc.: 47.27%] [G loss: 0.731680]
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9037 [D loss: 0.694385, acc.: 44.92%] [G loss: 0.718524]
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9038 [D loss: 0.690912, acc.: 46.88%] [G loss: 0.711451]
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9039 [D loss: 0.691913, acc.: 45.31%] [G loss: 0.708095]
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9040 [D loss: 0.689309, acc.: 47.07%] [G loss: 0.705899]
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9041 [D loss: 0.689453, acc.: 46.68%] [G loss: 0.716206]
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9042 [D loss: 0.687963, acc.: 48.24%] [G loss: 0.735228]
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9043 [D loss: 0.678178, acc.: 51.56%] [G loss: 0.740368]
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9044 [D loss: 0.673092, acc.: 56.05%] [G loss: 0.749680]
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9045 [D loss: 0.684956, acc.: 52.34%] [G loss: 0.743733]
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9046 [D loss: 0.685906, acc.: 51.76%] [G loss: 0.749293]
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9047 [D loss: 0.672661, acc.: 56.05%] [G loss: 0.737334]
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9048 [D loss: 0.680003, acc.: 54.10%] [G loss: 0.730458]
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9049 [D loss: 0.689155, acc.: 45.70%] [G loss: 0.722783]
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9050 [D loss: 0.693360, acc.: 47.66%] [G loss: 0.715597]
1/1 [==============================] - 0s 19ms/step
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9051 [D loss: 0.681372, acc.: 47.66%] [G loss: 0.719720]
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9052 [D loss: 0.686379, acc.: 44.92%] [G loss: 0.733822]
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9053 [D loss: 0.682174, acc.: 49.41%] [G loss: 0.736518]
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9054 [D loss: 0.694604, acc.: 45.70%] [G loss: 0.746239]
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9055 [D loss: 0.696241, acc.: 46.29%] [G loss: 0.742289]
8/8 [==============================] - 0s 5ms/step
9056 [D loss: 0.679658, acc.: 57.23%] [G loss: 0.732891]
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9057 [D loss: 0.684536, acc.: 49.61%] [G loss: 0.740356]
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9058 [D loss: 0.682556, acc.: 53.12%] [G loss: 0.737846]
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9059 [D loss: 0.682063, acc.: 52.93%] [G loss: 0.732803]
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9060 [D loss: 0.689989, acc.: 48.44%] [G loss: 0.721877]
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9061 [D loss: 0.690946, acc.: 47.66%] [G loss: 0.727955]
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9062 [D loss: 0.686963, acc.: 46.68%] [G loss: 0.728233]
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9063 [D loss: 0.688597, acc.: 49.02%] [G loss: 0.723496]
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9064 [D loss: 0.696094, acc.: 43.95%] [G loss: 0.729354]
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9065 [D loss: 0.678379, acc.: 51.95%] [G loss: 0.727794]
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9066 [D loss: 0.691412, acc.: 52.34%] [G loss: 0.727158]
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9067 [D loss: 0.684523, acc.: 52.15%] [G loss: 0.729437]
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9068 [D loss: 0.693716, acc.: 48.83%] [G loss: 0.723817]
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9069 [D loss: 0.689990, acc.: 48.05%] [G loss: 0.724842]
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9070 [D loss: 0.688934, acc.: 48.05%] [G loss: 0.735528]
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9071 [D loss: 0.685235, acc.: 53.52%] [G loss: 0.735066]
8/8 [==============================] - 0s 5ms/step
9072 [D loss: 0.684031, acc.: 50.39%] [G loss: 0.729571]
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9073 [D loss: 0.692167, acc.: 49.41%] [G loss: 0.733007]
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9074 [D loss: 0.677167, acc.: 53.32%] [G loss: 0.728413]
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9075 [D loss: 0.681873, acc.: 50.78%] [G loss: 0.728364]
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9076 [D loss: 0.681039, acc.: 49.02%] [G loss: 0.726971]
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9077 [D loss: 0.687885, acc.: 49.22%] [G loss: 0.717979]
8/8 [==============================] - 0s 5ms/step
9078 [D loss: 0.693825, acc.: 45.70%] [G loss: 0.716530]
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9079 [D loss: 0.683875, acc.: 51.17%] [G loss: 0.710338]
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9080 [D loss: 0.687870, acc.: 47.27%] [G loss: 0.721469]
8/8 [==============================] - 0s 5ms/step
9081 [D loss: 0.690031, acc.: 49.22%] [G loss: 0.720134]
8/8 [==============================] - 0s 5ms/step
9082 [D loss: 0.684856, acc.: 50.20%] [G loss: 0.725689]
8/8 [==============================] - 0s 5ms/step
9083 [D loss: 0.677925, acc.: 49.41%] [G loss: 0.729073]
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9084 [D loss: 0.685228, acc.: 49.41%] [G loss: 0.727551]
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9085 [D loss: 0.687713, acc.: 47.66%] [G loss: 0.727247]
8/8 [==============================] - 0s 5ms/step
9086 [D loss: 0.683424, acc.: 52.73%] [G loss: 0.730359]
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9087 [D loss: 0.674574, acc.: 52.54%] [G loss: 0.726673]
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9088 [D loss: 0.680937, acc.: 52.93%] [G loss: 0.723529]
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9089 [D loss: 0.682175, acc.: 46.68%] [G loss: 0.716993]
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9090 [D loss: 0.685420, acc.: 50.20%] [G loss: 0.717399]
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9091 [D loss: 0.684982, acc.: 49.22%] [G loss: 0.726086]
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9092 [D loss: 0.683385, acc.: 48.24%] [G loss: 0.731944]
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9093 [D loss: 0.679859, acc.: 49.80%] [G loss: 0.729915]
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9094 [D loss: 0.678868, acc.: 53.52%] [G loss: 0.731361]
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9095 [D loss: 0.687164, acc.: 45.70%] [G loss: 0.730796]
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9096 [D loss: 0.683567, acc.: 50.20%] [G loss: 0.730758]
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9097 [D loss: 0.684182, acc.: 46.09%] [G loss: 0.727446]
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9098 [D loss: 0.682647, acc.: 48.44%] [G loss: 0.729306]
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9099 [D loss: 0.684285, acc.: 47.85%] [G loss: 0.729333]
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9100 [D loss: 0.695797, acc.: 44.92%] [G loss: 0.718707]
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9101 [D loss: 0.686855, acc.: 48.83%] [G loss: 0.723258]
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9102 [D loss: 0.677351, acc.: 49.41%] [G loss: 0.726042]
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9103 [D loss: 0.685819, acc.: 48.05%] [G loss: 0.726766]
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9104 [D loss: 0.680368, acc.: 48.44%] [G loss: 0.736670]
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9105 [D loss: 0.678074, acc.: 50.00%] [G loss: 0.730742]
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9106 [D loss: 0.673924, acc.: 50.59%] [G loss: 0.734956]
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9107 [D loss: 0.674476, acc.: 53.52%] [G loss: 0.723735]
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9108 [D loss: 0.678409, acc.: 47.66%] [G loss: 0.723537]
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9109 [D loss: 0.678574, acc.: 48.63%] [G loss: 0.722137]
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9110 [D loss: 0.681086, acc.: 49.02%] [G loss: 0.718097]
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9111 [D loss: 0.686770, acc.: 47.07%] [G loss: 0.712633]
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9112 [D loss: 0.678393, acc.: 50.59%] [G loss: 0.713450]
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9113 [D loss: 0.694699, acc.: 42.38%] [G loss: 0.713574]
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9114 [D loss: 0.689874, acc.: 45.90%] [G loss: 0.716295]
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9115 [D loss: 0.678585, acc.: 46.09%] [G loss: 0.717770]
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9116 [D loss: 0.689240, acc.: 44.14%] [G loss: 0.725796]
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9117 [D loss: 0.687554, acc.: 46.29%] [G loss: 0.723041]
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9118 [D loss: 0.682834, acc.: 45.90%] [G loss: 0.727888]
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9119 [D loss: 0.676665, acc.: 50.20%] [G loss: 0.728481]
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9120 [D loss: 0.683782, acc.: 49.41%] [G loss: 0.733819]
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9121 [D loss: 0.674362, acc.: 50.59%] [G loss: 0.729180]
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9122 [D loss: 0.676900, acc.: 50.78%] [G loss: 0.727324]
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9123 [D loss: 0.680273, acc.: 50.39%] [G loss: 0.737290]
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9124 [D loss: 0.678713, acc.: 49.80%] [G loss: 0.727441]
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9125 [D loss: 0.685198, acc.: 49.02%] [G loss: 0.724665]
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9126 [D loss: 0.681333, acc.: 51.95%] [G loss: 0.723126]
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9127 [D loss: 0.676022, acc.: 47.46%] [G loss: 0.724764]
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9128 [D loss: 0.682982, acc.: 48.44%] [G loss: 0.722458]
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9129 [D loss: 0.693874, acc.: 46.88%] [G loss: 0.731108]
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9130 [D loss: 0.689796, acc.: 47.27%] [G loss: 0.736818]
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9131 [D loss: 0.685193, acc.: 47.07%] [G loss: 0.732685]
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9132 [D loss: 0.682192, acc.: 51.17%] [G loss: 0.730582]
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9133 [D loss: 0.680514, acc.: 49.02%] [G loss: 0.727973]
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9134 [D loss: 0.682947, acc.: 48.63%] [G loss: 0.717954]
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9135 [D loss: 0.682125, acc.: 48.83%] [G loss: 0.716088]
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9136 [D loss: 0.682559, acc.: 46.88%] [G loss: 0.710944]
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9137 [D loss: 0.687031, acc.: 46.09%] [G loss: 0.714088]
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9138 [D loss: 0.690070, acc.: 47.07%] [G loss: 0.716550]
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9139 [D loss: 0.688736, acc.: 46.68%] [G loss: 0.722633]
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9140 [D loss: 0.683258, acc.: 49.02%] [G loss: 0.726472]
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9141 [D loss: 0.684012, acc.: 49.22%] [G loss: 0.729376]
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9142 [D loss: 0.685815, acc.: 47.85%] [G loss: 0.728245]
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9143 [D loss: 0.691351, acc.: 46.48%] [G loss: 0.721834]
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9144 [D loss: 0.680386, acc.: 50.00%] [G loss: 0.727626]
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9145 [D loss: 0.678921, acc.: 46.68%] [G loss: 0.723271]
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9146 [D loss: 0.690423, acc.: 42.97%] [G loss: 0.717357]
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9147 [D loss: 0.688121, acc.: 45.90%] [G loss: 0.718649]
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9148 [D loss: 0.686255, acc.: 49.61%] [G loss: 0.726058]
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9149 [D loss: 0.684484, acc.: 48.83%] [G loss: 0.728379]
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9150 [D loss: 0.684153, acc.: 50.00%] [G loss: 0.737599]
1/1 [==============================] - 0s 19ms/step
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9151 [D loss: 0.680431, acc.: 50.20%] [G loss: 0.735845]
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9152 [D loss: 0.681112, acc.: 50.59%] [G loss: 0.735036]
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9153 [D loss: 0.675243, acc.: 52.54%] [G loss: 0.739892]
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9154 [D loss: 0.689930, acc.: 48.05%] [G loss: 0.742991]
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9155 [D loss: 0.687995, acc.: 49.22%] [G loss: 0.734277]
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9156 [D loss: 0.690485, acc.: 47.07%] [G loss: 0.733988]
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9157 [D loss: 0.680787, acc.: 51.95%] [G loss: 0.731253]
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9158 [D loss: 0.681553, acc.: 50.20%] [G loss: 0.717319]
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9159 [D loss: 0.687313, acc.: 46.09%] [G loss: 0.715263]
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9160 [D loss: 0.691856, acc.: 42.19%] [G loss: 0.714204]
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9161 [D loss: 0.687734, acc.: 49.22%] [G loss: 0.729579]
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9162 [D loss: 0.679835, acc.: 48.63%] [G loss: 0.730995]
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9163 [D loss: 0.682203, acc.: 47.46%] [G loss: 0.743146]
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9164 [D loss: 0.675699, acc.: 49.02%] [G loss: 0.728205]
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9165 [D loss: 0.691352, acc.: 46.09%] [G loss: 0.726396]
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9166 [D loss: 0.685652, acc.: 48.24%] [G loss: 0.729623]
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9167 [D loss: 0.681963, acc.: 53.52%] [G loss: 0.730720]
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9168 [D loss: 0.690628, acc.: 44.34%] [G loss: 0.724536]
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9169 [D loss: 0.684409, acc.: 47.27%] [G loss: 0.718782]
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9170 [D loss: 0.685034, acc.: 49.41%] [G loss: 0.714809]
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9171 [D loss: 0.684124, acc.: 51.17%] [G loss: 0.724688]
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9172 [D loss: 0.682405, acc.: 52.93%] [G loss: 0.726210]
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9173 [D loss: 0.693770, acc.: 44.34%] [G loss: 0.723440]
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9174 [D loss: 0.683339, acc.: 51.76%] [G loss: 0.723565]
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9175 [D loss: 0.693129, acc.: 43.55%] [G loss: 0.719614]
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9176 [D loss: 0.688934, acc.: 48.44%] [G loss: 0.725394]
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9177 [D loss: 0.676563, acc.: 50.59%] [G loss: 0.719962]
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9178 [D loss: 0.675129, acc.: 52.54%] [G loss: 0.720779]
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9179 [D loss: 0.677472, acc.: 51.37%] [G loss: 0.721964]
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9180 [D loss: 0.691345, acc.: 47.07%] [G loss: 0.720770]
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9181 [D loss: 0.679790, acc.: 50.00%] [G loss: 0.731970]
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9182 [D loss: 0.676397, acc.: 52.54%] [G loss: 0.733778]
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9183 [D loss: 0.685226, acc.: 49.80%] [G loss: 0.738656]
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9184 [D loss: 0.685817, acc.: 52.34%] [G loss: 0.741806]
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9185 [D loss: 0.673765, acc.: 51.56%] [G loss: 0.744286]
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9186 [D loss: 0.673959, acc.: 53.32%] [G loss: 0.740880]
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9187 [D loss: 0.675579, acc.: 51.56%] [G loss: 0.738325]
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9188 [D loss: 0.689249, acc.: 46.29%] [G loss: 0.729523]
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9189 [D loss: 0.681900, acc.: 51.56%] [G loss: 0.726082]
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9190 [D loss: 0.688475, acc.: 43.55%] [G loss: 0.728120]
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9191 [D loss: 0.695495, acc.: 45.90%] [G loss: 0.719350]
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9192 [D loss: 0.683977, acc.: 47.66%] [G loss: 0.722883]
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9193 [D loss: 0.681327, acc.: 48.24%] [G loss: 0.731203]
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9194 [D loss: 0.683024, acc.: 50.59%] [G loss: 0.725458]
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9195 [D loss: 0.683988, acc.: 49.61%] [G loss: 0.724947]
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9196 [D loss: 0.682350, acc.: 50.39%] [G loss: 0.720050]
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9197 [D loss: 0.688702, acc.: 46.88%] [G loss: 0.716291]
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9198 [D loss: 0.672998, acc.: 50.00%] [G loss: 0.717243]
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9199 [D loss: 0.676605, acc.: 52.34%] [G loss: 0.720461]
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9200 [D loss: 0.680999, acc.: 50.98%] [G loss: 0.717880]
1/1 [==============================] - 0s 20ms/step
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9201 [D loss: 0.681923, acc.: 49.02%] [G loss: 0.719254]
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9202 [D loss: 0.673445, acc.: 50.39%] [G loss: 0.720887]
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9203 [D loss: 0.686842, acc.: 49.22%] [G loss: 0.733271]
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9204 [D loss: 0.678875, acc.: 50.20%] [G loss: 0.738356]
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9205 [D loss: 0.688351, acc.: 49.41%] [G loss: 0.731343]
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9206 [D loss: 0.678117, acc.: 51.17%] [G loss: 0.727321]
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9207 [D loss: 0.710740, acc.: 50.59%] [G loss: 0.727852]
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9208 [D loss: 0.701684, acc.: 42.77%] [G loss: 0.720077]
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9209 [D loss: 0.700814, acc.: 42.19%] [G loss: 0.727744]
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9210 [D loss: 0.696445, acc.: 40.23%] [G loss: 0.739346]
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9211 [D loss: 0.691611, acc.: 45.31%] [G loss: 0.758926]
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9212 [D loss: 0.705008, acc.: 35.74%] [G loss: 0.751252]
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9213 [D loss: 0.709414, acc.: 42.97%] [G loss: 0.734654]
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9214 [D loss: 0.687266, acc.: 48.63%] [G loss: 0.808672]
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9215 [D loss: 0.697154, acc.: 47.66%] [G loss: 0.741001]
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9216 [D loss: 0.695711, acc.: 47.27%] [G loss: 0.748921]
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9217 [D loss: 0.694656, acc.: 49.41%] [G loss: 0.735427]
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9218 [D loss: 0.694799, acc.: 57.62%] [G loss: 0.739870]
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9219 [D loss: 0.690607, acc.: 54.88%] [G loss: 0.756974]
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9220 [D loss: 0.684821, acc.: 52.54%] [G loss: 0.772625]
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9221 [D loss: 0.685886, acc.: 52.34%] [G loss: 0.753274]
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9222 [D loss: 0.692500, acc.: 48.24%] [G loss: 0.751034]
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9223 [D loss: 0.694902, acc.: 50.00%] [G loss: 0.701992]
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9224 [D loss: 0.700459, acc.: 43.75%] [G loss: 0.701895]
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9225 [D loss: 0.702858, acc.: 44.34%] [G loss: 0.693879]
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9226 [D loss: 0.701760, acc.: 44.73%] [G loss: 0.707563]
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9227 [D loss: 0.697370, acc.: 44.73%] [G loss: 0.725162]
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9228 [D loss: 0.691665, acc.: 49.02%] [G loss: 0.745253]
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9229 [D loss: 0.698561, acc.: 45.31%] [G loss: 0.730052]
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9230 [D loss: 0.696956, acc.: 46.68%] [G loss: 0.725637]
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9231 [D loss: 0.691369, acc.: 49.22%] [G loss: 0.732786]
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9232 [D loss: 0.690488, acc.: 48.24%] [G loss: 0.731779]
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9233 [D loss: 0.692930, acc.: 48.05%] [G loss: 0.719408]
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9234 [D loss: 0.691911, acc.: 47.07%] [G loss: 0.721582]
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9235 [D loss: 0.693125, acc.: 47.07%] [G loss: 0.727978]
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9236 [D loss: 0.679965, acc.: 55.27%] [G loss: 0.742890]
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9237 [D loss: 0.690776, acc.: 52.34%] [G loss: 0.747764]
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9238 [D loss: 0.690911, acc.: 50.98%] [G loss: 0.755993]
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9239 [D loss: 0.696545, acc.: 49.02%] [G loss: 0.743011]
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9240 [D loss: 0.699470, acc.: 48.24%] [G loss: 0.723007]
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9241 [D loss: 0.697141, acc.: 43.36%] [G loss: 0.721432]
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9242 [D loss: 0.700284, acc.: 45.31%] [G loss: 0.733967]
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9243 [D loss: 0.691129, acc.: 47.66%] [G loss: 0.730075]
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9244 [D loss: 0.700002, acc.: 43.95%] [G loss: 0.728956]
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9245 [D loss: 0.688483, acc.: 54.69%] [G loss: 0.725079]
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9246 [D loss: 0.691542, acc.: 49.22%] [G loss: 0.746546]
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9247 [D loss: 0.693238, acc.: 49.02%] [G loss: 0.731458]
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9248 [D loss: 0.693656, acc.: 48.83%] [G loss: 0.732140]
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9249 [D loss: 0.690156, acc.: 50.39%] [G loss: 0.721829]
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9250 [D loss: 0.690592, acc.: 49.02%] [G loss: 0.713142]
1/1 [==============================] - 0s 18ms/step
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9251 [D loss: 0.689750, acc.: 52.15%] [G loss: 0.716769]
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9252 [D loss: 0.702857, acc.: 43.16%] [G loss: 0.709727]
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9253 [D loss: 0.701162, acc.: 42.77%] [G loss: 0.716290]
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9254 [D loss: 0.703094, acc.: 42.77%] [G loss: 0.718450]
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9255 [D loss: 0.692906, acc.: 49.61%] [G loss: 0.734023]
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9256 [D loss: 0.693783, acc.: 47.85%] [G loss: 0.755779]
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9257 [D loss: 0.683449, acc.: 56.05%] [G loss: 0.756754]
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9258 [D loss: 0.705250, acc.: 45.51%] [G loss: 0.744912]
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9259 [D loss: 0.694151, acc.: 48.63%] [G loss: 0.742496]
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9260 [D loss: 0.687180, acc.: 52.15%] [G loss: 0.760915]
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9261 [D loss: 0.688560, acc.: 51.76%] [G loss: 0.758534]
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9262 [D loss: 0.692032, acc.: 49.61%] [G loss: 0.736967]
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9263 [D loss: 0.688992, acc.: 51.37%] [G loss: 0.746193]
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9264 [D loss: 0.687867, acc.: 49.02%] [G loss: 0.762291]
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9265 [D loss: 0.679508, acc.: 53.52%] [G loss: 0.755079]
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9266 [D loss: 0.683372, acc.: 51.76%] [G loss: 0.758744]
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9267 [D loss: 0.678228, acc.: 50.20%] [G loss: 0.753916]
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9268 [D loss: 0.690772, acc.: 47.85%] [G loss: 0.744212]
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9269 [D loss: 0.689645, acc.: 50.20%] [G loss: 0.754590]
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9270 [D loss: 0.686386, acc.: 54.69%] [G loss: 0.726080]
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9271 [D loss: 0.693160, acc.: 47.46%] [G loss: 0.716480]
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9272 [D loss: 0.679904, acc.: 52.54%] [G loss: 0.703347]
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9273 [D loss: 0.689188, acc.: 52.15%] [G loss: 0.712533]
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9274 [D loss: 0.695071, acc.: 47.66%] [G loss: 0.726890]
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9275 [D loss: 0.688144, acc.: 52.15%] [G loss: 0.720029]
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9276 [D loss: 0.692711, acc.: 46.68%] [G loss: 0.733521]
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9277 [D loss: 0.703707, acc.: 45.12%] [G loss: 0.716395]
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9278 [D loss: 0.701131, acc.: 43.16%] [G loss: 0.711291]
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9279 [D loss: 0.701179, acc.: 46.88%] [G loss: 0.725564]
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9280 [D loss: 0.694551, acc.: 47.85%] [G loss: 0.731473]
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9281 [D loss: 0.696195, acc.: 45.12%] [G loss: 0.733766]
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9282 [D loss: 0.693979, acc.: 50.98%] [G loss: 0.724860]
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9283 [D loss: 0.696022, acc.: 45.51%] [G loss: 0.735782]
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9284 [D loss: 0.695444, acc.: 47.85%] [G loss: 0.731567]
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9285 [D loss: 0.695243, acc.: 49.61%] [G loss: 0.737301]
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9286 [D loss: 0.693661, acc.: 48.05%] [G loss: 0.734559]
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9287 [D loss: 0.697642, acc.: 50.00%] [G loss: 0.732400]
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9288 [D loss: 0.689279, acc.: 53.32%] [G loss: 0.736101]
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9289 [D loss: 0.690953, acc.: 50.59%] [G loss: 0.735829]
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9290 [D loss: 0.691074, acc.: 50.39%] [G loss: 0.727862]
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9291 [D loss: 0.687507, acc.: 51.56%] [G loss: 0.726066]
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9292 [D loss: 0.691695, acc.: 48.44%] [G loss: 0.730680]
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9293 [D loss: 0.687150, acc.: 54.10%] [G loss: 0.725854]
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9294 [D loss: 0.693418, acc.: 46.68%] [G loss: 0.709976]
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9295 [D loss: 0.686248, acc.: 47.27%] [G loss: 0.716844]
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9296 [D loss: 0.698426, acc.: 42.77%] [G loss: 0.721986]
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9297 [D loss: 0.689908, acc.: 51.95%] [G loss: 0.719371]
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9298 [D loss: 0.683233, acc.: 52.93%] [G loss: 0.735883]
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9299 [D loss: 0.686510, acc.: 53.71%] [G loss: 0.746831]
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9300 [D loss: 0.693693, acc.: 45.70%] [G loss: 0.746253]
1/1 [==============================] - 0s 19ms/step
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9301 [D loss: 0.686852, acc.: 51.17%] [G loss: 0.739330]
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9302 [D loss: 0.686951, acc.: 49.80%] [G loss: 0.726386]
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9303 [D loss: 0.693898, acc.: 50.39%] [G loss: 0.716106]
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9304 [D loss: 0.687219, acc.: 50.59%] [G loss: 0.727384]
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9305 [D loss: 0.699257, acc.: 44.34%] [G loss: 0.715586]
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9306 [D loss: 0.693636, acc.: 50.20%] [G loss: 0.721914]
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9307 [D loss: 0.694987, acc.: 44.53%] [G loss: 0.743620]
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9308 [D loss: 0.678992, acc.: 54.10%] [G loss: 0.757313]
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9309 [D loss: 0.684773, acc.: 50.59%] [G loss: 0.750923]
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9310 [D loss: 0.696692, acc.: 49.61%] [G loss: 0.742115]
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9311 [D loss: 0.690706, acc.: 51.56%] [G loss: 0.733584]
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9312 [D loss: 0.686479, acc.: 56.84%] [G loss: 0.726148]
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9313 [D loss: 0.695344, acc.: 51.56%] [G loss: 0.719470]
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9314 [D loss: 0.699023, acc.: 50.20%] [G loss: 0.718629]
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9315 [D loss: 0.700765, acc.: 43.16%] [G loss: 0.726849]
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9316 [D loss: 0.694432, acc.: 46.88%] [G loss: 0.755137]
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9317 [D loss: 0.688250, acc.: 51.76%] [G loss: 0.761072]
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9318 [D loss: 0.685854, acc.: 47.85%] [G loss: 0.776419]
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9319 [D loss: 0.702189, acc.: 42.77%] [G loss: 0.770923]
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9320 [D loss: 0.694597, acc.: 50.98%] [G loss: 0.743317]
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9321 [D loss: 0.682183, acc.: 58.79%] [G loss: 0.767919]
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9322 [D loss: 0.683465, acc.: 59.96%] [G loss: 0.761780]
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9323 [D loss: 0.693017, acc.: 52.54%] [G loss: 0.737065]
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9324 [D loss: 0.689248, acc.: 50.39%] [G loss: 0.746810]
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9325 [D loss: 0.688893, acc.: 55.66%] [G loss: 0.773376]
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9326 [D loss: 0.691923, acc.: 48.24%] [G loss: 0.724161]
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9327 [D loss: 0.689582, acc.: 50.00%] [G loss: 0.751100]
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9328 [D loss: 0.684054, acc.: 53.91%] [G loss: 0.738073]
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9329 [D loss: 0.700633, acc.: 45.51%] [G loss: 0.718719]
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9330 [D loss: 0.706878, acc.: 45.12%] [G loss: 0.702646]
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9331 [D loss: 0.694875, acc.: 49.80%] [G loss: 0.721372]
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9332 [D loss: 0.700136, acc.: 48.83%] [G loss: 0.734012]
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9333 [D loss: 0.693760, acc.: 48.83%] [G loss: 0.731584]
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9334 [D loss: 0.692518, acc.: 47.85%] [G loss: 0.729812]
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9335 [D loss: 0.681555, acc.: 55.66%] [G loss: 0.731685]
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9336 [D loss: 0.685405, acc.: 52.15%] [G loss: 0.737137]
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9337 [D loss: 0.673398, acc.: 54.49%] [G loss: 0.726304]
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9338 [D loss: 0.695367, acc.: 46.48%] [G loss: 0.710537]
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9339 [D loss: 0.712025, acc.: 46.88%] [G loss: 0.710879]
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9340 [D loss: 0.711750, acc.: 48.05%] [G loss: 0.743209]
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9341 [D loss: 0.694940, acc.: 51.17%] [G loss: 0.748750]
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9342 [D loss: 0.698255, acc.: 47.27%] [G loss: 0.727772]
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9343 [D loss: 0.697113, acc.: 48.63%] [G loss: 0.738892]
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9344 [D loss: 0.688140, acc.: 51.37%] [G loss: 0.744708]
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9345 [D loss: 0.700215, acc.: 47.85%] [G loss: 0.727524]
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9346 [D loss: 0.695841, acc.: 49.41%] [G loss: 0.725696]
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9347 [D loss: 0.686963, acc.: 52.54%] [G loss: 0.747060]
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9348 [D loss: 0.682141, acc.: 53.91%] [G loss: 0.765108]
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9349 [D loss: 0.686467, acc.: 51.76%] [G loss: 0.789667]
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9350 [D loss: 0.695365, acc.: 46.88%] [G loss: 0.750023]
1/1 [==============================] - 0s 19ms/step
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9351 [D loss: 0.692447, acc.: 51.95%] [G loss: 0.743638]
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9352 [D loss: 0.684785, acc.: 58.01%] [G loss: 0.768152]
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9353 [D loss: 0.690829, acc.: 50.59%] [G loss: 0.736484]
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9354 [D loss: 0.700367, acc.: 45.90%] [G loss: 0.712082]
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9355 [D loss: 0.699949, acc.: 50.00%] [G loss: 0.728770]
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9356 [D loss: 0.687286, acc.: 54.49%] [G loss: 0.751127]
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9357 [D loss: 0.691199, acc.: 50.98%] [G loss: 0.762718]
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9358 [D loss: 0.690814, acc.: 50.20%] [G loss: 0.747980]
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9359 [D loss: 0.700100, acc.: 45.90%] [G loss: 0.748337]
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9360 [D loss: 0.684439, acc.: 58.40%] [G loss: 0.751752]
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9361 [D loss: 0.680668, acc.: 53.32%] [G loss: 0.761581]
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9362 [D loss: 0.691303, acc.: 50.20%] [G loss: 0.736207]
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9363 [D loss: 0.695326, acc.: 47.27%] [G loss: 0.735168]
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9364 [D loss: 0.682353, acc.: 54.69%] [G loss: 0.749066]
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9365 [D loss: 0.683604, acc.: 53.91%] [G loss: 0.753017]
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9366 [D loss: 0.687534, acc.: 50.98%] [G loss: 0.762845]
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9367 [D loss: 0.690214, acc.: 46.68%] [G loss: 0.739881]
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9368 [D loss: 0.680855, acc.: 55.66%] [G loss: 0.738157]
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9369 [D loss: 0.696097, acc.: 47.46%] [G loss: 0.750173]
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9370 [D loss: 0.699431, acc.: 44.34%] [G loss: 0.714312]
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9371 [D loss: 0.701711, acc.: 46.48%] [G loss: 0.708629]
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9372 [D loss: 0.691628, acc.: 49.41%] [G loss: 0.720264]
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9373 [D loss: 0.700681, acc.: 44.73%] [G loss: 0.722510]
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9374 [D loss: 0.698099, acc.: 50.00%] [G loss: 0.719501]
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9375 [D loss: 0.694608, acc.: 49.22%] [G loss: 0.735418]
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9376 [D loss: 0.689944, acc.: 48.63%] [G loss: 0.744897]
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9377 [D loss: 0.691967, acc.: 47.85%] [G loss: 0.740386]
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9378 [D loss: 0.689091, acc.: 50.59%] [G loss: 0.737174]
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9379 [D loss: 0.690264, acc.: 51.95%] [G loss: 0.738208]
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9380 [D loss: 0.692634, acc.: 47.66%] [G loss: 0.723673]
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9381 [D loss: 0.691385, acc.: 51.17%] [G loss: 0.741695]
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9382 [D loss: 0.693095, acc.: 46.29%] [G loss: 0.738854]
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9383 [D loss: 0.698515, acc.: 48.24%] [G loss: 0.731702]
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9384 [D loss: 0.682365, acc.: 52.54%] [G loss: 0.734892]
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9385 [D loss: 0.690669, acc.: 49.22%] [G loss: 0.742478]
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9386 [D loss: 0.683547, acc.: 53.12%] [G loss: 0.731100]
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9387 [D loss: 0.689127, acc.: 51.17%] [G loss: 0.727431]
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9388 [D loss: 0.682520, acc.: 50.59%] [G loss: 0.738194]
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9389 [D loss: 0.683748, acc.: 52.15%] [G loss: 0.733151]
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9390 [D loss: 0.689938, acc.: 49.80%] [G loss: 0.729312]
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9391 [D loss: 0.693932, acc.: 49.61%] [G loss: 0.720791]
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9392 [D loss: 0.691707, acc.: 49.02%] [G loss: 0.725878]
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9393 [D loss: 0.685245, acc.: 55.27%] [G loss: 0.734195]
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9394 [D loss: 0.684429, acc.: 51.76%] [G loss: 0.752052]
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9395 [D loss: 0.694695, acc.: 48.83%] [G loss: 0.742684]
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9396 [D loss: 0.695718, acc.: 47.85%] [G loss: 0.737705]
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9397 [D loss: 0.694849, acc.: 47.46%] [G loss: 0.740573]
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9398 [D loss: 0.687371, acc.: 50.59%] [G loss: 0.744783]
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9399 [D loss: 0.683772, acc.: 47.85%] [G loss: 0.751714]
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9400 [D loss: 0.676857, acc.: 51.76%] [G loss: 0.749549]
1/1 [==============================] - 0s 20ms/step
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9401 [D loss: 0.686236, acc.: 51.37%] [G loss: 0.740624]
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9402 [D loss: 0.685357, acc.: 51.56%] [G loss: 0.749296]
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9403 [D loss: 0.681631, acc.: 50.39%] [G loss: 0.763794]
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9404 [D loss: 0.685076, acc.: 50.20%] [G loss: 0.745938]
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9405 [D loss: 0.688767, acc.: 45.51%] [G loss: 0.741927]
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9406 [D loss: 0.693917, acc.: 49.02%] [G loss: 0.740435]
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9407 [D loss: 0.695061, acc.: 48.44%] [G loss: 0.752509]
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9408 [D loss: 0.687153, acc.: 51.76%] [G loss: 0.776139]
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9409 [D loss: 0.699091, acc.: 50.00%] [G loss: 0.736160]
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9410 [D loss: 0.702763, acc.: 48.05%] [G loss: 0.737022]
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9411 [D loss: 0.700292, acc.: 45.12%] [G loss: 0.716629]
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9412 [D loss: 0.695421, acc.: 49.61%] [G loss: 0.712823]
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9413 [D loss: 0.696451, acc.: 48.63%] [G loss: 0.704955]
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9414 [D loss: 0.691891, acc.: 46.48%] [G loss: 0.719583]
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9415 [D loss: 0.692188, acc.: 48.05%] [G loss: 0.712511]
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9416 [D loss: 0.686660, acc.: 49.22%] [G loss: 0.736062]
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9417 [D loss: 0.685892, acc.: 50.39%] [G loss: 0.744296]
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9418 [D loss: 0.687668, acc.: 48.44%] [G loss: 0.750336]
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9419 [D loss: 0.684520, acc.: 50.98%] [G loss: 0.764042]
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9420 [D loss: 0.682550, acc.: 52.34%] [G loss: 0.776021]
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9421 [D loss: 0.675534, acc.: 56.45%] [G loss: 0.766791]
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9422 [D loss: 0.687989, acc.: 48.63%] [G loss: 0.756966]
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9423 [D loss: 0.678569, acc.: 54.49%] [G loss: 0.751220]
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9424 [D loss: 0.680214, acc.: 53.32%] [G loss: 0.747873]
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9425 [D loss: 0.681244, acc.: 53.12%] [G loss: 0.754414]
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9426 [D loss: 0.673330, acc.: 56.25%] [G loss: 0.731925]
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9427 [D loss: 0.690649, acc.: 48.83%] [G loss: 0.732581]
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9428 [D loss: 0.682662, acc.: 51.56%] [G loss: 0.732745]
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9429 [D loss: 0.678689, acc.: 53.71%] [G loss: 0.744629]
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9430 [D loss: 0.687066, acc.: 53.32%] [G loss: 0.738923]
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9431 [D loss: 0.677031, acc.: 55.08%] [G loss: 0.716208]
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9432 [D loss: 0.693582, acc.: 49.61%] [G loss: 0.725748]
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9433 [D loss: 0.698336, acc.: 46.48%] [G loss: 0.716588]
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9434 [D loss: 0.684311, acc.: 50.59%] [G loss: 0.703639]
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9435 [D loss: 0.692978, acc.: 49.22%] [G loss: 0.718881]
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9436 [D loss: 0.699682, acc.: 43.55%] [G loss: 0.721105]
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9437 [D loss: 0.698916, acc.: 46.88%] [G loss: 0.739131]
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9438 [D loss: 0.698106, acc.: 44.53%] [G loss: 0.741966]
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9439 [D loss: 0.689537, acc.: 50.59%] [G loss: 0.745517]
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9440 [D loss: 0.692175, acc.: 49.61%] [G loss: 0.755385]
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9441 [D loss: 0.688996, acc.: 53.91%] [G loss: 0.744466]
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9442 [D loss: 0.688252, acc.: 50.39%] [G loss: 0.743435]
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9443 [D loss: 0.690037, acc.: 51.76%] [G loss: 0.756949]
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9444 [D loss: 0.694016, acc.: 48.83%] [G loss: 0.729826]
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9445 [D loss: 0.690282, acc.: 53.32%] [G loss: 0.733977]
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9446 [D loss: 0.683342, acc.: 53.91%] [G loss: 0.750215]
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9447 [D loss: 0.701712, acc.: 44.92%] [G loss: 0.725985]
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9448 [D loss: 0.692867, acc.: 47.85%] [G loss: 0.717352]
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9449 [D loss: 0.693187, acc.: 43.95%] [G loss: 0.728986]
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9450 [D loss: 0.694808, acc.: 45.12%] [G loss: 0.717087]
1/1 [==============================] - 0s 19ms/step
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9451 [D loss: 0.700106, acc.: 40.62%] [G loss: 0.725319]
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9452 [D loss: 0.690865, acc.: 48.05%] [G loss: 0.725961]
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9453 [D loss: 0.687294, acc.: 50.20%] [G loss: 0.716525]
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9454 [D loss: 0.690419, acc.: 47.07%] [G loss: 0.715820]
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9455 [D loss: 0.695058, acc.: 48.24%] [G loss: 0.724031]
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9456 [D loss: 0.690572, acc.: 50.98%] [G loss: 0.722431]
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9457 [D loss: 0.684124, acc.: 54.49%] [G loss: 0.752621]
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9458 [D loss: 0.690662, acc.: 47.85%] [G loss: 0.752467]
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9459 [D loss: 0.680195, acc.: 53.12%] [G loss: 0.741587]
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9460 [D loss: 0.680464, acc.: 52.34%] [G loss: 0.760212]
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9461 [D loss: 0.687272, acc.: 50.98%] [G loss: 0.735634]
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9462 [D loss: 0.689732, acc.: 49.80%] [G loss: 0.737061]
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9463 [D loss: 0.697885, acc.: 44.34%] [G loss: 0.715870]
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9464 [D loss: 0.701433, acc.: 41.99%] [G loss: 0.720571]
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9465 [D loss: 0.701983, acc.: 46.48%] [G loss: 0.716638]
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9466 [D loss: 0.699474, acc.: 47.27%] [G loss: 0.708415]
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9467 [D loss: 0.698630, acc.: 48.05%] [G loss: 0.716244]
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9468 [D loss: 0.689231, acc.: 49.61%] [G loss: 0.727883]
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9469 [D loss: 0.693304, acc.: 50.59%] [G loss: 0.728852]
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9470 [D loss: 0.699072, acc.: 45.12%] [G loss: 0.730709]
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9471 [D loss: 0.691850, acc.: 50.78%] [G loss: 0.729813]
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9472 [D loss: 0.690126, acc.: 54.88%] [G loss: 0.740074]
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9473 [D loss: 0.691878, acc.: 52.34%] [G loss: 0.751106]
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9474 [D loss: 0.683654, acc.: 53.52%] [G loss: 0.762061]
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9475 [D loss: 0.682848, acc.: 56.64%] [G loss: 0.756573]
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9476 [D loss: 0.681166, acc.: 56.64%] [G loss: 0.757229]
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9477 [D loss: 0.685713, acc.: 54.10%] [G loss: 0.757612]
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9478 [D loss: 0.687080, acc.: 52.15%] [G loss: 0.763932]
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9479 [D loss: 0.684288, acc.: 53.32%] [G loss: 0.766917]
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9480 [D loss: 0.691907, acc.: 47.66%] [G loss: 0.759132]
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9481 [D loss: 0.687319, acc.: 48.83%] [G loss: 0.755834]
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9482 [D loss: 0.693090, acc.: 47.46%] [G loss: 0.748049]
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9483 [D loss: 0.677924, acc.: 53.52%] [G loss: 0.750516]
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9484 [D loss: 0.689021, acc.: 51.76%] [G loss: 0.745890]
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9485 [D loss: 0.692077, acc.: 48.44%] [G loss: 0.716565]
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9486 [D loss: 0.694905, acc.: 45.90%] [G loss: 0.726080]
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9487 [D loss: 0.686473, acc.: 50.20%] [G loss: 0.730783]
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9488 [D loss: 0.688564, acc.: 51.56%] [G loss: 0.754092]
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9489 [D loss: 0.686283, acc.: 50.78%] [G loss: 0.772351]
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9490 [D loss: 0.702102, acc.: 49.61%] [G loss: 0.754529]
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9491 [D loss: 0.706246, acc.: 44.14%] [G loss: 0.735465]
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9492 [D loss: 0.706185, acc.: 45.90%] [G loss: 0.718683]
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9493 [D loss: 0.711985, acc.: 45.51%] [G loss: 0.713142]
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9494 [D loss: 0.700161, acc.: 42.77%] [G loss: 0.730187]
8/8 [==============================] - 0s 5ms/step
9495 [D loss: 0.688604, acc.: 53.71%] [G loss: 0.769468]
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9496 [D loss: 0.691850, acc.: 47.85%] [G loss: 0.753779]
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9497 [D loss: 0.687464, acc.: 50.98%] [G loss: 0.733667]
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9498 [D loss: 0.692909, acc.: 48.63%] [G loss: 0.738453]
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9499 [D loss: 0.681344, acc.: 55.86%] [G loss: 0.738386]
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9500 [D loss: 0.684687, acc.: 54.10%] [G loss: 0.731167]
1/1 [==============================] - 0s 18ms/step
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9501 [D loss: 0.684595, acc.: 49.61%] [G loss: 0.726776]
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9502 [D loss: 0.696105, acc.: 47.27%] [G loss: 0.706993]
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9503 [D loss: 0.685880, acc.: 51.37%] [G loss: 0.731826]
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9504 [D loss: 0.696733, acc.: 51.95%] [G loss: 0.745390]
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9505 [D loss: 0.685128, acc.: 52.54%] [G loss: 0.768477]
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9506 [D loss: 0.685601, acc.: 49.80%] [G loss: 0.763540]
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9507 [D loss: 0.694171, acc.: 46.09%] [G loss: 0.749830]
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9508 [D loss: 0.704166, acc.: 42.58%] [G loss: 0.728168]
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9509 [D loss: 0.696694, acc.: 51.56%] [G loss: 0.753688]
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9510 [D loss: 0.685490, acc.: 55.47%] [G loss: 0.746299]
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9511 [D loss: 0.693651, acc.: 48.63%] [G loss: 0.731731]
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9512 [D loss: 0.693047, acc.: 48.63%] [G loss: 0.721230]
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9513 [D loss: 0.684084, acc.: 54.88%] [G loss: 0.735859]
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9514 [D loss: 0.683586, acc.: 56.84%] [G loss: 0.729368]
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9515 [D loss: 0.689639, acc.: 50.00%] [G loss: 0.734159]
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9516 [D loss: 0.684677, acc.: 49.80%] [G loss: 0.731900]
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9517 [D loss: 0.681441, acc.: 52.34%] [G loss: 0.730481]
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9518 [D loss: 0.691397, acc.: 50.20%] [G loss: 0.707653]
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9519 [D loss: 0.696258, acc.: 43.95%] [G loss: 0.710639]
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9520 [D loss: 0.693343, acc.: 47.07%] [G loss: 0.708386]
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9521 [D loss: 0.697281, acc.: 47.85%] [G loss: 0.702482]
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9522 [D loss: 0.701292, acc.: 45.90%] [G loss: 0.715027]
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9523 [D loss: 0.697376, acc.: 45.12%] [G loss: 0.735122]
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9524 [D loss: 0.694729, acc.: 49.61%] [G loss: 0.740689]
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9525 [D loss: 0.693012, acc.: 49.22%] [G loss: 0.733964]
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9526 [D loss: 0.688852, acc.: 50.39%] [G loss: 0.740375]
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9527 [D loss: 0.689013, acc.: 53.12%] [G loss: 0.745821]
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9528 [D loss: 0.684760, acc.: 56.84%] [G loss: 0.739138]
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9529 [D loss: 0.690303, acc.: 52.15%] [G loss: 0.735124]
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9530 [D loss: 0.687638, acc.: 53.52%] [G loss: 0.717447]
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9531 [D loss: 0.698709, acc.: 50.98%] [G loss: 0.719978]
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9532 [D loss: 0.691116, acc.: 50.20%] [G loss: 0.730731]
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9533 [D loss: 0.691624, acc.: 55.47%] [G loss: 0.754679]
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9534 [D loss: 0.694375, acc.: 48.83%] [G loss: 0.743814]
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9535 [D loss: 0.693532, acc.: 46.29%] [G loss: 0.759727]
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9536 [D loss: 0.702228, acc.: 51.95%] [G loss: 0.728989]
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9537 [D loss: 0.697591, acc.: 51.76%] [G loss: 0.734845]
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9538 [D loss: 0.691462, acc.: 50.78%] [G loss: 0.730227]
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9539 [D loss: 0.703111, acc.: 45.51%] [G loss: 0.715815]
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9540 [D loss: 0.697459, acc.: 48.05%] [G loss: 0.720330]
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9541 [D loss: 0.688695, acc.: 50.78%] [G loss: 0.755309]
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9542 [D loss: 0.680815, acc.: 52.15%] [G loss: 0.775615]
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9543 [D loss: 0.685952, acc.: 50.78%] [G loss: 0.777728]
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9544 [D loss: 0.699677, acc.: 46.29%] [G loss: 0.745914]
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9545 [D loss: 0.694352, acc.: 50.59%] [G loss: 0.745729]
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9546 [D loss: 0.687472, acc.: 50.39%] [G loss: 0.751074]
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9547 [D loss: 0.681544, acc.: 56.05%] [G loss: 0.759497]
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9548 [D loss: 0.690844, acc.: 49.80%] [G loss: 0.734352]
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9549 [D loss: 0.693418, acc.: 49.22%] [G loss: 0.721210]
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9550 [D loss: 0.705747, acc.: 44.14%] [G loss: 0.697850]
1/1 [==============================] - 0s 20ms/step
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9551 [D loss: 0.703008, acc.: 49.80%] [G loss: 0.726881]
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9552 [D loss: 0.691429, acc.: 50.39%] [G loss: 0.741264]
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9553 [D loss: 0.697878, acc.: 42.97%] [G loss: 0.736104]
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9554 [D loss: 0.695125, acc.: 49.41%] [G loss: 0.717340]
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9555 [D loss: 0.692055, acc.: 51.76%] [G loss: 0.725374]
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9556 [D loss: 0.698650, acc.: 49.02%] [G loss: 0.715248]
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9557 [D loss: 0.702866, acc.: 44.73%] [G loss: 0.709391]
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9558 [D loss: 0.701935, acc.: 47.66%] [G loss: 0.729352]
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9559 [D loss: 0.691432, acc.: 50.59%] [G loss: 0.741767]
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9560 [D loss: 0.697096, acc.: 49.02%] [G loss: 0.744135]
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9561 [D loss: 0.689303, acc.: 52.15%] [G loss: 0.755857]
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9562 [D loss: 0.697502, acc.: 44.53%] [G loss: 0.765114]
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9563 [D loss: 0.688795, acc.: 50.00%] [G loss: 0.748362]
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9564 [D loss: 0.678068, acc.: 54.49%] [G loss: 0.751531]
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9565 [D loss: 0.685975, acc.: 52.93%] [G loss: 0.744972]
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9566 [D loss: 0.686988, acc.: 48.83%] [G loss: 0.729455]
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9567 [D loss: 0.700361, acc.: 48.44%] [G loss: 0.730006]
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9568 [D loss: 0.700044, acc.: 48.44%] [G loss: 0.733088]
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9569 [D loss: 0.692511, acc.: 47.85%] [G loss: 0.754414]
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9570 [D loss: 0.691077, acc.: 49.61%] [G loss: 0.763089]
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9571 [D loss: 0.696514, acc.: 47.66%] [G loss: 0.757460]
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9572 [D loss: 0.693987, acc.: 49.02%] [G loss: 0.748951]
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9573 [D loss: 0.687190, acc.: 51.76%] [G loss: 0.737473]
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9574 [D loss: 0.681566, acc.: 52.54%] [G loss: 0.747903]
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9575 [D loss: 0.691521, acc.: 46.48%] [G loss: 0.751371]
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9576 [D loss: 0.684923, acc.: 52.15%] [G loss: 0.731249]
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9577 [D loss: 0.690210, acc.: 53.32%] [G loss: 0.731433]
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9578 [D loss: 0.698436, acc.: 46.88%] [G loss: 0.740944]
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9579 [D loss: 0.696855, acc.: 46.68%] [G loss: 0.761821]
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9580 [D loss: 0.697167, acc.: 46.88%] [G loss: 0.750894]
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9581 [D loss: 0.690934, acc.: 50.20%] [G loss: 0.729196]
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9582 [D loss: 0.701612, acc.: 41.02%] [G loss: 0.735637]
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9583 [D loss: 0.697791, acc.: 49.80%] [G loss: 0.735603]
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9584 [D loss: 0.687337, acc.: 53.32%] [G loss: 0.741617]
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9585 [D loss: 0.690349, acc.: 52.34%] [G loss: 0.722931]
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9586 [D loss: 0.683661, acc.: 52.93%] [G loss: 0.730926]
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9587 [D loss: 0.689215, acc.: 48.63%] [G loss: 0.716396]
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9588 [D loss: 0.693154, acc.: 46.48%] [G loss: 0.715934]
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9589 [D loss: 0.686180, acc.: 50.39%] [G loss: 0.720910]
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9590 [D loss: 0.693671, acc.: 49.61%] [G loss: 0.726903]
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9591 [D loss: 0.694954, acc.: 49.22%] [G loss: 0.725419]
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9592 [D loss: 0.688482, acc.: 52.34%] [G loss: 0.722197]
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9593 [D loss: 0.694315, acc.: 47.85%] [G loss: 0.722889]
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9594 [D loss: 0.693910, acc.: 50.59%] [G loss: 0.722368]
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9595 [D loss: 0.691640, acc.: 49.41%] [G loss: 0.726275]
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9596 [D loss: 0.689057, acc.: 54.49%] [G loss: 0.729132]
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9597 [D loss: 0.690537, acc.: 53.12%] [G loss: 0.712328]
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9598 [D loss: 0.702441, acc.: 46.68%] [G loss: 0.713113]
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9599 [D loss: 0.696445, acc.: 50.39%] [G loss: 0.720996]
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9600 [D loss: 0.679664, acc.: 53.32%] [G loss: 0.754723]
1/1 [==============================] - 0s 19ms/step
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9601 [D loss: 0.682899, acc.: 54.10%] [G loss: 0.754474]
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9602 [D loss: 0.692318, acc.: 48.05%] [G loss: 0.740579]
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9603 [D loss: 0.697975, acc.: 45.12%] [G loss: 0.746825]
8/8 [==============================] - 0s 5ms/step
9604 [D loss: 0.688305, acc.: 51.76%] [G loss: 0.759845]
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9605 [D loss: 0.692977, acc.: 49.61%] [G loss: 0.777024]
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9606 [D loss: 0.695871, acc.: 46.09%] [G loss: 0.725637]
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9607 [D loss: 0.692927, acc.: 48.63%] [G loss: 0.716146]
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9608 [D loss: 0.688832, acc.: 51.95%] [G loss: 0.725498]
8/8 [==============================] - 0s 5ms/step
9609 [D loss: 0.688959, acc.: 50.59%] [G loss: 0.722937]
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9610 [D loss: 0.694763, acc.: 48.44%] [G loss: 0.725166]
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9611 [D loss: 0.694799, acc.: 49.80%] [G loss: 0.725354]
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9612 [D loss: 0.701158, acc.: 45.90%] [G loss: 0.725489]
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9613 [D loss: 0.700990, acc.: 50.00%] [G loss: 0.726131]
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9614 [D loss: 0.692767, acc.: 50.98%] [G loss: 0.721579]
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9615 [D loss: 0.700263, acc.: 46.29%] [G loss: 0.720350]
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9616 [D loss: 0.709776, acc.: 44.92%] [G loss: 0.700837]
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9617 [D loss: 0.707685, acc.: 43.75%] [G loss: 0.716084]
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9618 [D loss: 0.702840, acc.: 43.55%] [G loss: 0.732464]
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9619 [D loss: 0.699956, acc.: 46.68%] [G loss: 0.740866]
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9620 [D loss: 0.695099, acc.: 47.66%] [G loss: 0.734890]
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9621 [D loss: 0.696007, acc.: 44.92%] [G loss: 0.726016]
8/8 [==============================] - 0s 5ms/step
9622 [D loss: 0.700120, acc.: 46.29%] [G loss: 0.716972]
8/8 [==============================] - 0s 5ms/step
9623 [D loss: 0.695631, acc.: 45.31%] [G loss: 0.720177]
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9624 [D loss: 0.703554, acc.: 40.82%] [G loss: 0.717083]
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9625 [D loss: 0.698533, acc.: 47.85%] [G loss: 0.720993]
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9626 [D loss: 0.693529, acc.: 50.39%] [G loss: 0.753900]
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9627 [D loss: 0.700864, acc.: 42.19%] [G loss: 0.749630]
8/8 [==============================] - 0s 5ms/step
9628 [D loss: 0.699489, acc.: 46.09%] [G loss: 0.731843]
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9629 [D loss: 0.702090, acc.: 48.05%] [G loss: 0.725694]
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9630 [D loss: 0.688263, acc.: 56.25%] [G loss: 0.738278]
8/8 [==============================] - 0s 5ms/step
9631 [D loss: 0.695113, acc.: 53.71%] [G loss: 0.740993]
8/8 [==============================] - 0s 5ms/step
9632 [D loss: 0.695065, acc.: 46.88%] [G loss: 0.725565]
8/8 [==============================] - 0s 5ms/step
9633 [D loss: 0.691621, acc.: 51.56%] [G loss: 0.730072]
8/8 [==============================] - 0s 5ms/step
9634 [D loss: 0.690687, acc.: 52.15%] [G loss: 0.735760]
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9635 [D loss: 0.693028, acc.: 49.80%] [G loss: 0.725563]
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9636 [D loss: 0.695071, acc.: 44.92%] [G loss: 0.720676]
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9637 [D loss: 0.698717, acc.: 46.09%] [G loss: 0.718801]
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9638 [D loss: 0.694297, acc.: 52.34%] [G loss: 0.732745]
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9639 [D loss: 0.690456, acc.: 53.12%] [G loss: 0.716186]
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9640 [D loss: 0.701544, acc.: 44.14%] [G loss: 0.720118]
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9641 [D loss: 0.692343, acc.: 48.63%] [G loss: 0.729926]
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9642 [D loss: 0.693719, acc.: 50.00%] [G loss: 0.739784]
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9643 [D loss: 0.690469, acc.: 51.37%] [G loss: 0.741731]
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9644 [D loss: 0.696510, acc.: 46.09%] [G loss: 0.743134]
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9645 [D loss: 0.692069, acc.: 51.76%] [G loss: 0.737438]
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9646 [D loss: 0.693480, acc.: 48.83%] [G loss: 0.739029]
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9647 [D loss: 0.686549, acc.: 53.52%] [G loss: 0.724958]
8/8 [==============================] - 0s 5ms/step
9648 [D loss: 0.689594, acc.: 51.95%] [G loss: 0.735230]
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9649 [D loss: 0.694873, acc.: 46.09%] [G loss: 0.717202]
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9650 [D loss: 0.693507, acc.: 51.17%] [G loss: 0.722476]
1/1 [==============================] - 0s 34ms/step
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9651 [D loss: 0.695280, acc.: 45.31%] [G loss: 0.719580]
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9652 [D loss: 0.691828, acc.: 47.07%] [G loss: 0.721126]
8/8 [==============================] - 0s 7ms/step
9653 [D loss: 0.688180, acc.: 51.95%] [G loss: 0.723341]
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9654 [D loss: 0.687152, acc.: 51.17%] [G loss: 0.725875]
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9655 [D loss: 0.695109, acc.: 47.07%] [G loss: 0.713640]
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9656 [D loss: 0.690986, acc.: 49.61%] [G loss: 0.718488]
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9657 [D loss: 0.693761, acc.: 49.41%] [G loss: 0.720903]
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9658 [D loss: 0.689067, acc.: 48.24%] [G loss: 0.713645]
8/8 [==============================] - 0s 5ms/step
9659 [D loss: 0.696436, acc.: 43.36%] [G loss: 0.707144]
8/8 [==============================] - 0s 6ms/step
9660 [D loss: 0.690844, acc.: 44.73%] [G loss: 0.726058]
8/8 [==============================] - 0s 5ms/step
9661 [D loss: 0.685043, acc.: 52.34%] [G loss: 0.731068]
8/8 [==============================] - 0s 5ms/step
9662 [D loss: 0.674052, acc.: 54.49%] [G loss: 0.737861]
8/8 [==============================] - 0s 5ms/step
9663 [D loss: 0.697085, acc.: 45.12%] [G loss: 0.736532]
8/8 [==============================] - 0s 5ms/step
9664 [D loss: 0.696371, acc.: 48.63%] [G loss: 0.712745]
8/8 [==============================] - 0s 5ms/step
9665 [D loss: 0.694281, acc.: 48.44%] [G loss: 0.713939]
8/8 [==============================] - 0s 5ms/step
9666 [D loss: 0.688978, acc.: 51.37%] [G loss: 0.705421]
8/8 [==============================] - 0s 4ms/step
9667 [D loss: 0.693728, acc.: 49.61%] [G loss: 0.703529]
8/8 [==============================] - 0s 5ms/step
9668 [D loss: 0.703548, acc.: 47.85%] [G loss: 0.693471]
8/8 [==============================] - 0s 5ms/step
9669 [D loss: 0.702627, acc.: 44.92%] [G loss: 0.711695]
8/8 [==============================] - 0s 5ms/step
9670 [D loss: 0.697615, acc.: 48.24%] [G loss: 0.728887]
8/8 [==============================] - 0s 5ms/step
9671 [D loss: 0.694332, acc.: 51.37%] [G loss: 0.752993]
8/8 [==============================] - 0s 5ms/step
9672 [D loss: 0.692832, acc.: 50.78%] [G loss: 0.747335]
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9673 [D loss: 0.693373, acc.: 48.05%] [G loss: 0.744304]
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9674 [D loss: 0.695389, acc.: 52.15%] [G loss: 0.732806]
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9675 [D loss: 0.691391, acc.: 49.41%] [G loss: 0.731049]
8/8 [==============================] - 0s 5ms/step
9676 [D loss: 0.693180, acc.: 49.02%] [G loss: 0.724997]
8/8 [==============================] - 0s 5ms/step
9677 [D loss: 0.696668, acc.: 49.02%] [G loss: 0.716039]
8/8 [==============================] - 0s 6ms/step
9678 [D loss: 0.695005, acc.: 50.59%] [G loss: 0.720070]
8/8 [==============================] - 0s 5ms/step
9679 [D loss: 0.693373, acc.: 46.88%] [G loss: 0.725200]
8/8 [==============================] - 0s 5ms/step
9680 [D loss: 0.690494, acc.: 49.61%] [G loss: 0.725947]
8/8 [==============================] - 0s 5ms/step
9681 [D loss: 0.694842, acc.: 47.27%] [G loss: 0.722618]
8/8 [==============================] - 0s 5ms/step
9682 [D loss: 0.690220, acc.: 46.48%] [G loss: 0.718574]
8/8 [==============================] - 0s 5ms/step
9683 [D loss: 0.685953, acc.: 51.95%] [G loss: 0.717367]
8/8 [==============================] - 0s 5ms/step
9684 [D loss: 0.700330, acc.: 44.14%] [G loss: 0.710487]
8/8 [==============================] - 0s 5ms/step
9685 [D loss: 0.697543, acc.: 45.51%] [G loss: 0.713007]
8/8 [==============================] - 0s 5ms/step
9686 [D loss: 0.688829, acc.: 49.02%] [G loss: 0.720855]
8/8 [==============================] - 0s 5ms/step
9687 [D loss: 0.693380, acc.: 44.73%] [G loss: 0.729143]
8/8 [==============================] - 0s 5ms/step
9688 [D loss: 0.689343, acc.: 49.22%] [G loss: 0.734482]
8/8 [==============================] - 0s 5ms/step
9689 [D loss: 0.684964, acc.: 54.49%] [G loss: 0.734730]
8/8 [==============================] - 0s 5ms/step
9690 [D loss: 0.685535, acc.: 52.54%] [G loss: 0.730467]
8/8 [==============================] - 0s 5ms/step
9691 [D loss: 0.689479, acc.: 48.83%] [G loss: 0.728218]
8/8 [==============================] - 0s 5ms/step
9692 [D loss: 0.685837, acc.: 52.15%] [G loss: 0.721873]
8/8 [==============================] - 0s 5ms/step
9693 [D loss: 0.690883, acc.: 50.98%] [G loss: 0.721052]
8/8 [==============================] - 0s 5ms/step
9694 [D loss: 0.685631, acc.: 51.56%] [G loss: 0.722469]
8/8 [==============================] - 0s 5ms/step
9695 [D loss: 0.687749, acc.: 50.20%] [G loss: 0.718136]
8/8 [==============================] - 0s 5ms/step
9696 [D loss: 0.680387, acc.: 54.30%] [G loss: 0.730165]
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9697 [D loss: 0.692626, acc.: 48.05%] [G loss: 0.728917]
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9698 [D loss: 0.694775, acc.: 48.83%] [G loss: 0.718659]
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9699 [D loss: 0.694414, acc.: 47.07%] [G loss: 0.714906]
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9700 [D loss: 0.693663, acc.: 45.31%] [G loss: 0.716484]
1/1 [==============================] - 0s 17ms/step
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9701 [D loss: 0.690129, acc.: 49.02%] [G loss: 0.726990]
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9702 [D loss: 0.688230, acc.: 49.22%] [G loss: 0.719369]
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9703 [D loss: 0.690200, acc.: 50.20%] [G loss: 0.721882]
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9704 [D loss: 0.691659, acc.: 47.46%] [G loss: 0.732025]
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9705 [D loss: 0.674231, acc.: 51.76%] [G loss: 0.741690]
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9706 [D loss: 0.685144, acc.: 51.17%] [G loss: 0.754372]
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9707 [D loss: 0.682570, acc.: 47.85%] [G loss: 0.745158]
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9708 [D loss: 0.679418, acc.: 51.37%] [G loss: 0.748611]
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9709 [D loss: 0.686222, acc.: 45.12%] [G loss: 0.746533]
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9710 [D loss: 0.682739, acc.: 48.63%] [G loss: 0.736955]
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9711 [D loss: 0.681533, acc.: 50.59%] [G loss: 0.745237]
8/8 [==============================] - 0s 5ms/step
9712 [D loss: 0.674205, acc.: 51.95%] [G loss: 0.737903]
8/8 [==============================] - 0s 5ms/step
9713 [D loss: 0.689447, acc.: 49.22%] [G loss: 0.725321]
8/8 [==============================] - 0s 5ms/step
9714 [D loss: 0.685469, acc.: 50.20%] [G loss: 0.719215]
8/8 [==============================] - 0s 5ms/step
9715 [D loss: 0.688612, acc.: 49.22%] [G loss: 0.715317]
8/8 [==============================] - 0s 5ms/step
9716 [D loss: 0.687372, acc.: 47.85%] [G loss: 0.722182]
8/8 [==============================] - 0s 5ms/step
9717 [D loss: 0.703330, acc.: 49.61%] [G loss: 0.700046]
8/8 [==============================] - 0s 5ms/step
9718 [D loss: 0.703334, acc.: 46.09%] [G loss: 0.699484]
8/8 [==============================] - 0s 5ms/step
9719 [D loss: 0.697107, acc.: 49.22%] [G loss: 0.708724]
8/8 [==============================] - 0s 5ms/step
9720 [D loss: 0.697654, acc.: 47.07%] [G loss: 0.704456]
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9721 [D loss: 0.693657, acc.: 45.51%] [G loss: 0.703435]
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9722 [D loss: 0.703301, acc.: 45.12%] [G loss: 0.698157]
8/8 [==============================] - 0s 5ms/step
9723 [D loss: 0.702727, acc.: 46.68%] [G loss: 0.709942]
8/8 [==============================] - 0s 5ms/step
9724 [D loss: 0.695168, acc.: 47.46%] [G loss: 0.726006]
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9725 [D loss: 0.694423, acc.: 47.85%] [G loss: 0.740374]
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9726 [D loss: 0.692074, acc.: 51.37%] [G loss: 0.748892]
8/8 [==============================] - 0s 5ms/step
9727 [D loss: 0.686175, acc.: 48.24%] [G loss: 0.733096]
8/8 [==============================] - 0s 5ms/step
9728 [D loss: 0.693267, acc.: 46.09%] [G loss: 0.736335]
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9729 [D loss: 0.685638, acc.: 49.61%] [G loss: 0.748351]
8/8 [==============================] - 0s 5ms/step
9730 [D loss: 0.684131, acc.: 48.44%] [G loss: 0.737358]
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9731 [D loss: 0.695007, acc.: 49.61%] [G loss: 0.724437]
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9732 [D loss: 0.695820, acc.: 48.05%] [G loss: 0.712815]
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9733 [D loss: 0.696595, acc.: 47.85%] [G loss: 0.723183]
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9734 [D loss: 0.697943, acc.: 48.44%] [G loss: 0.731648]
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9735 [D loss: 0.688446, acc.: 52.15%] [G loss: 0.734879]
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9736 [D loss: 0.693054, acc.: 52.73%] [G loss: 0.735974]
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9737 [D loss: 0.688650, acc.: 55.47%] [G loss: 0.740896]
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9738 [D loss: 0.689537, acc.: 58.01%] [G loss: 0.730654]
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9739 [D loss: 0.694652, acc.: 53.32%] [G loss: 0.718198]
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9740 [D loss: 0.690732, acc.: 54.10%] [G loss: 0.711178]
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9741 [D loss: 0.704987, acc.: 48.44%] [G loss: 0.710827]
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9742 [D loss: 0.711530, acc.: 45.51%] [G loss: 0.710819]
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9743 [D loss: 0.693851, acc.: 49.02%] [G loss: 0.744846]
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9744 [D loss: 0.695707, acc.: 45.90%] [G loss: 0.751123]
8/8 [==============================] - 0s 5ms/step
9745 [D loss: 0.688219, acc.: 52.15%] [G loss: 0.750706]
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9746 [D loss: 0.697071, acc.: 47.07%] [G loss: 0.739327]
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9747 [D loss: 0.693030, acc.: 49.80%] [G loss: 0.735144]
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9748 [D loss: 0.693873, acc.: 50.00%] [G loss: 0.742535]
8/8 [==============================] - 0s 5ms/step
9749 [D loss: 0.685653, acc.: 52.93%] [G loss: 0.731735]
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9750 [D loss: 0.695379, acc.: 45.70%] [G loss: 0.716365]
1/1 [==============================] - 0s 19ms/step
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9751 [D loss: 0.694092, acc.: 49.02%] [G loss: 0.719107]
8/8 [==============================] - 0s 5ms/step
9752 [D loss: 0.690755, acc.: 49.41%] [G loss: 0.729122]
8/8 [==============================] - 0s 5ms/step
9753 [D loss: 0.688800, acc.: 53.32%] [G loss: 0.727913]
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9754 [D loss: 0.690981, acc.: 48.83%] [G loss: 0.731384]
8/8 [==============================] - 0s 5ms/step
9755 [D loss: 0.697873, acc.: 45.31%] [G loss: 0.718715]
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9756 [D loss: 0.687685, acc.: 50.20%] [G loss: 0.720005]
8/8 [==============================] - 0s 5ms/step
9757 [D loss: 0.684657, acc.: 51.76%] [G loss: 0.717708]
8/8 [==============================] - 0s 5ms/step
9758 [D loss: 0.689872, acc.: 46.29%] [G loss: 0.708655]
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9759 [D loss: 0.694259, acc.: 46.29%] [G loss: 0.699976]
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9760 [D loss: 0.690351, acc.: 48.63%] [G loss: 0.710009]
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9761 [D loss: 0.691880, acc.: 45.51%] [G loss: 0.725985]
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9762 [D loss: 0.689445, acc.: 51.76%] [G loss: 0.726727]
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9763 [D loss: 0.694938, acc.: 50.39%] [G loss: 0.716678]
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9764 [D loss: 0.696102, acc.: 45.70%] [G loss: 0.725971]
8/8 [==============================] - 0s 5ms/step
9765 [D loss: 0.686354, acc.: 52.34%] [G loss: 0.723626]
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9766 [D loss: 0.680791, acc.: 54.88%] [G loss: 0.729236]
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9767 [D loss: 0.686912, acc.: 46.88%] [G loss: 0.740739]
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9768 [D loss: 0.681473, acc.: 48.24%] [G loss: 0.745130]
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9769 [D loss: 0.683690, acc.: 47.46%] [G loss: 0.763016]
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9770 [D loss: 0.694758, acc.: 47.46%] [G loss: 0.732648]
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9771 [D loss: 0.695772, acc.: 44.73%] [G loss: 0.725916]
8/8 [==============================] - 0s 5ms/step
9772 [D loss: 0.687121, acc.: 53.71%] [G loss: 0.727221]
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9773 [D loss: 0.689458, acc.: 54.30%] [G loss: 0.724716]
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9774 [D loss: 0.696054, acc.: 50.39%] [G loss: 0.708887]
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9775 [D loss: 0.697650, acc.: 48.83%] [G loss: 0.705660]
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9776 [D loss: 0.704797, acc.: 44.53%] [G loss: 0.716302]
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9777 [D loss: 0.693052, acc.: 47.66%] [G loss: 0.736016]
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9778 [D loss: 0.690352, acc.: 52.15%] [G loss: 0.741284]
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9779 [D loss: 0.696455, acc.: 49.41%] [G loss: 0.740094]
8/8 [==============================] - 0s 5ms/step
9780 [D loss: 0.684818, acc.: 55.27%] [G loss: 0.754092]
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9781 [D loss: 0.680965, acc.: 55.27%] [G loss: 0.748197]
8/8 [==============================] - 0s 5ms/step
9782 [D loss: 0.686136, acc.: 51.37%] [G loss: 0.716323]
8/8 [==============================] - 0s 5ms/step
9783 [D loss: 0.686181, acc.: 48.05%] [G loss: 0.728651]
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9784 [D loss: 0.683798, acc.: 51.37%] [G loss: 0.721207]
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9785 [D loss: 0.693364, acc.: 49.61%] [G loss: 0.744285]
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9786 [D loss: 0.688312, acc.: 50.98%] [G loss: 0.745214]
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9787 [D loss: 0.687265, acc.: 46.88%] [G loss: 0.771991]
8/8 [==============================] - 0s 5ms/step
9788 [D loss: 0.696003, acc.: 45.31%] [G loss: 0.766005]
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9789 [D loss: 0.680763, acc.: 52.73%] [G loss: 0.754330]
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9790 [D loss: 0.673990, acc.: 57.23%] [G loss: 0.772443]
8/8 [==============================] - 0s 5ms/step
9791 [D loss: 0.689078, acc.: 51.56%] [G loss: 0.751567]
8/8 [==============================] - 0s 5ms/step
9792 [D loss: 0.687413, acc.: 50.39%] [G loss: 0.731658]
8/8 [==============================] - 0s 5ms/step
9793 [D loss: 0.691102, acc.: 48.44%] [G loss: 0.720562]
8/8 [==============================] - 0s 5ms/step
9794 [D loss: 0.692108, acc.: 48.44%] [G loss: 0.741399]
8/8 [==============================] - 0s 5ms/step
9795 [D loss: 0.682951, acc.: 53.12%] [G loss: 0.726302]
8/8 [==============================] - 0s 5ms/step
9796 [D loss: 0.686323, acc.: 51.56%] [G loss: 0.751961]
8/8 [==============================] - 0s 5ms/step
9797 [D loss: 0.681973, acc.: 52.54%] [G loss: 0.736360]
8/8 [==============================] - 0s 5ms/step
9798 [D loss: 0.680329, acc.: 53.91%] [G loss: 0.714775]
8/8 [==============================] - 0s 5ms/step
9799 [D loss: 0.694409, acc.: 50.59%] [G loss: 0.733132]
8/8 [==============================] - 0s 5ms/step
9800 [D loss: 0.695035, acc.: 50.59%] [G loss: 0.715952]
1/1 [==============================] - 0s 19ms/step
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9801 [D loss: 0.683173, acc.: 49.22%] [G loss: 0.717042]
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9802 [D loss: 0.689778, acc.: 49.02%] [G loss: 0.712560]
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9803 [D loss: 0.695732, acc.: 46.29%] [G loss: 0.731643]
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9804 [D loss: 0.678855, acc.: 51.17%] [G loss: 0.737361]
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9805 [D loss: 0.690553, acc.: 49.80%] [G loss: 0.727217]
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9806 [D loss: 0.688853, acc.: 50.20%] [G loss: 0.732901]
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9807 [D loss: 0.688547, acc.: 48.24%] [G loss: 0.726826]
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9808 [D loss: 0.695950, acc.: 48.05%] [G loss: 0.703080]
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9809 [D loss: 0.717906, acc.: 45.90%] [G loss: 0.695326]
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9810 [D loss: 0.701717, acc.: 50.59%] [G loss: 0.718530]
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9811 [D loss: 0.694168, acc.: 54.88%] [G loss: 0.762714]
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9812 [D loss: 0.681152, acc.: 57.81%] [G loss: 0.762683]
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9813 [D loss: 0.682410, acc.: 53.52%] [G loss: 0.748466]
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9814 [D loss: 0.698356, acc.: 46.68%] [G loss: 0.737523]
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9815 [D loss: 0.685863, acc.: 50.00%] [G loss: 0.729434]
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9816 [D loss: 0.690469, acc.: 46.29%] [G loss: 0.715334]
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9817 [D loss: 0.698586, acc.: 45.70%] [G loss: 0.720365]
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9818 [D loss: 0.689288, acc.: 48.63%] [G loss: 0.738589]
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9819 [D loss: 0.679011, acc.: 56.05%] [G loss: 0.747305]
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9820 [D loss: 0.684505, acc.: 52.54%] [G loss: 0.755543]
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9821 [D loss: 0.690465, acc.: 52.93%] [G loss: 0.743872]
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9822 [D loss: 0.687894, acc.: 51.56%] [G loss: 0.734924]
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9823 [D loss: 0.688621, acc.: 52.15%] [G loss: 0.743808]
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9824 [D loss: 0.690006, acc.: 51.17%] [G loss: 0.723202]
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9825 [D loss: 0.691441, acc.: 49.80%] [G loss: 0.734974]
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9826 [D loss: 0.698390, acc.: 46.68%] [G loss: 0.730980]
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9827 [D loss: 0.690802, acc.: 49.02%] [G loss: 0.739579]
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9828 [D loss: 0.687970, acc.: 48.63%] [G loss: 0.751298]
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9829 [D loss: 0.686070, acc.: 53.12%] [G loss: 0.756487]
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9830 [D loss: 0.688430, acc.: 52.54%] [G loss: 0.758025]
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9831 [D loss: 0.687589, acc.: 52.73%] [G loss: 0.749806]
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9832 [D loss: 0.688363, acc.: 52.73%] [G loss: 0.756341]
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9833 [D loss: 0.691136, acc.: 51.17%] [G loss: 0.741404]
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9834 [D loss: 0.692397, acc.: 54.49%] [G loss: 0.730321]
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9835 [D loss: 0.691661, acc.: 52.54%] [G loss: 0.712023]
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9836 [D loss: 0.692662, acc.: 50.00%] [G loss: 0.723281]
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9837 [D loss: 0.688873, acc.: 50.78%] [G loss: 0.732115]
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9838 [D loss: 0.695779, acc.: 47.85%] [G loss: 0.724842]
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9839 [D loss: 0.701910, acc.: 46.88%] [G loss: 0.707160]
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9840 [D loss: 0.687815, acc.: 53.32%] [G loss: 0.714496]
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9841 [D loss: 0.688581, acc.: 53.12%] [G loss: 0.716442]
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9842 [D loss: 0.688183, acc.: 48.83%] [G loss: 0.724988]
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9843 [D loss: 0.688307, acc.: 50.59%] [G loss: 0.719675]
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9844 [D loss: 0.686595, acc.: 53.91%] [G loss: 0.726186]
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9845 [D loss: 0.685730, acc.: 51.76%] [G loss: 0.729867]
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9846 [D loss: 0.677575, acc.: 55.47%] [G loss: 0.741586]
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9847 [D loss: 0.683115, acc.: 50.78%] [G loss: 0.745132]
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9848 [D loss: 0.692202, acc.: 49.80%] [G loss: 0.732947]
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9849 [D loss: 0.687185, acc.: 53.12%] [G loss: 0.732183]
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9850 [D loss: 0.687915, acc.: 52.34%] [G loss: 0.744414]
1/1 [==============================] - 0s 19ms/step
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9851 [D loss: 0.686305, acc.: 50.59%] [G loss: 0.747160]
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9852 [D loss: 0.682521, acc.: 52.54%] [G loss: 0.772287]
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9853 [D loss: 0.689899, acc.: 49.02%] [G loss: 0.760845]
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9854 [D loss: 0.684740, acc.: 52.15%] [G loss: 0.738616]
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9855 [D loss: 0.686604, acc.: 50.98%] [G loss: 0.728290]
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9856 [D loss: 0.702618, acc.: 48.05%] [G loss: 0.696374]
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9857 [D loss: 0.699823, acc.: 43.55%] [G loss: 0.710006]
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9858 [D loss: 0.691344, acc.: 52.34%] [G loss: 0.724457]
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9859 [D loss: 0.693210, acc.: 52.15%] [G loss: 0.750344]
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9860 [D loss: 0.700525, acc.: 49.80%] [G loss: 0.739141]
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9861 [D loss: 0.698339, acc.: 47.27%] [G loss: 0.728428]
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9862 [D loss: 0.700180, acc.: 48.83%] [G loss: 0.726351]
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9863 [D loss: 0.696798, acc.: 49.61%] [G loss: 0.717860]
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9864 [D loss: 0.691612, acc.: 51.95%] [G loss: 0.722482]
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9865 [D loss: 0.689331, acc.: 50.59%] [G loss: 0.724347]
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9866 [D loss: 0.697461, acc.: 51.76%] [G loss: 0.740995]
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9867 [D loss: 0.691598, acc.: 56.25%] [G loss: 0.748455]
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9868 [D loss: 0.682670, acc.: 54.88%] [G loss: 0.742833]
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9869 [D loss: 0.680618, acc.: 58.40%] [G loss: 0.745198]
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9870 [D loss: 0.683382, acc.: 55.86%] [G loss: 0.757738]
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9871 [D loss: 0.684121, acc.: 57.03%] [G loss: 0.734070]
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9872 [D loss: 0.681086, acc.: 57.42%] [G loss: 0.745487]
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9873 [D loss: 0.689689, acc.: 50.20%] [G loss: 0.734069]
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9874 [D loss: 0.686473, acc.: 49.61%] [G loss: 0.742540]
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9875 [D loss: 0.692209, acc.: 47.85%] [G loss: 0.750145]
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9876 [D loss: 0.703037, acc.: 43.95%] [G loss: 0.737109]
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9877 [D loss: 0.703688, acc.: 50.00%] [G loss: 0.719433]
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9878 [D loss: 0.690322, acc.: 51.76%] [G loss: 0.740414]
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9879 [D loss: 0.683495, acc.: 51.56%] [G loss: 0.757833]
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9880 [D loss: 0.678824, acc.: 56.05%] [G loss: 0.757605]
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9881 [D loss: 0.686901, acc.: 52.34%] [G loss: 0.740368]
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9882 [D loss: 0.688349, acc.: 51.17%] [G loss: 0.723750]
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9883 [D loss: 0.687971, acc.: 49.61%] [G loss: 0.739619]
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9884 [D loss: 0.699201, acc.: 46.88%] [G loss: 0.734932]
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9885 [D loss: 0.688998, acc.: 48.83%] [G loss: 0.750995]
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9886 [D loss: 0.692883, acc.: 47.27%] [G loss: 0.737148]
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9887 [D loss: 0.690114, acc.: 49.02%] [G loss: 0.748571]
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9888 [D loss: 0.688616, acc.: 53.71%] [G loss: 0.732860]
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9889 [D loss: 0.691620, acc.: 49.22%] [G loss: 0.736142]
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9890 [D loss: 0.696478, acc.: 45.90%] [G loss: 0.722639]
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9891 [D loss: 0.689794, acc.: 50.39%] [G loss: 0.716987]
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9892 [D loss: 0.691984, acc.: 53.12%] [G loss: 0.729956]
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9893 [D loss: 0.682450, acc.: 52.54%] [G loss: 0.750143]
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9894 [D loss: 0.691751, acc.: 49.41%] [G loss: 0.769979]
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9895 [D loss: 0.686568, acc.: 51.76%] [G loss: 0.749449]
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9896 [D loss: 0.680556, acc.: 53.52%] [G loss: 0.747202]
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9897 [D loss: 0.689472, acc.: 54.49%] [G loss: 0.773986]
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9898 [D loss: 0.689131, acc.: 50.59%] [G loss: 0.735645]
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9899 [D loss: 0.699339, acc.: 47.46%] [G loss: 0.712345]
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9900 [D loss: 0.694193, acc.: 48.05%] [G loss: 0.712020]
1/1 [==============================] - 0s 17ms/step
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9901 [D loss: 0.689866, acc.: 52.73%] [G loss: 0.725623]
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9902 [D loss: 0.696103, acc.: 47.27%] [G loss: 0.734516]
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9903 [D loss: 0.692909, acc.: 47.27%] [G loss: 0.730233]
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9904 [D loss: 0.692056, acc.: 48.44%] [G loss: 0.726037]
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9905 [D loss: 0.688036, acc.: 50.39%] [G loss: 0.726408]
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9906 [D loss: 0.678176, acc.: 51.56%] [G loss: 0.745543]
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9907 [D loss: 0.690146, acc.: 50.78%] [G loss: 0.725087]
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9908 [D loss: 0.683992, acc.: 49.80%] [G loss: 0.746590]
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9909 [D loss: 0.677231, acc.: 54.49%] [G loss: 0.741938]
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9910 [D loss: 0.679427, acc.: 51.95%] [G loss: 0.737348]
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9911 [D loss: 0.684152, acc.: 50.20%] [G loss: 0.748803]
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9912 [D loss: 0.690361, acc.: 50.00%] [G loss: 0.734307]
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9913 [D loss: 0.693614, acc.: 49.80%] [G loss: 0.743170]
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9914 [D loss: 0.687335, acc.: 50.20%] [G loss: 0.729308]
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9915 [D loss: 0.689350, acc.: 49.22%] [G loss: 0.726331]
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9916 [D loss: 0.691340, acc.: 48.83%] [G loss: 0.719306]
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9917 [D loss: 0.698228, acc.: 46.88%] [G loss: 0.736829]
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9918 [D loss: 0.685675, acc.: 51.76%] [G loss: 0.753562]
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9919 [D loss: 0.673615, acc.: 52.34%] [G loss: 0.759395]
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9920 [D loss: 0.680926, acc.: 49.80%] [G loss: 0.757312]
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9921 [D loss: 0.690575, acc.: 46.88%] [G loss: 0.747453]
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9922 [D loss: 0.677473, acc.: 52.93%] [G loss: 0.744762]
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9923 [D loss: 0.685682, acc.: 52.93%] [G loss: 0.732707]
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9924 [D loss: 0.689725, acc.: 45.51%] [G loss: 0.717937]
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9925 [D loss: 0.695201, acc.: 45.51%] [G loss: 0.712746]
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9926 [D loss: 0.699221, acc.: 44.14%] [G loss: 0.726542]
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9927 [D loss: 0.676487, acc.: 51.76%] [G loss: 0.750217]
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9928 [D loss: 0.676904, acc.: 52.93%] [G loss: 0.757777]
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9929 [D loss: 0.688666, acc.: 49.61%] [G loss: 0.759090]
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9930 [D loss: 0.682936, acc.: 53.12%] [G loss: 0.747617]
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9931 [D loss: 0.679532, acc.: 57.42%] [G loss: 0.757107]
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9932 [D loss: 0.687608, acc.: 51.37%] [G loss: 0.732787]
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9933 [D loss: 0.696942, acc.: 46.88%] [G loss: 0.712863]
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9934 [D loss: 0.694487, acc.: 46.48%] [G loss: 0.733142]
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9935 [D loss: 0.687736, acc.: 51.17%] [G loss: 0.782002]
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9936 [D loss: 0.682926, acc.: 49.80%] [G loss: 0.776443]
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9937 [D loss: 0.693824, acc.: 43.55%] [G loss: 0.735693]
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9938 [D loss: 0.685960, acc.: 53.91%] [G loss: 0.744876]
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9939 [D loss: 0.682118, acc.: 56.45%] [G loss: 0.747657]
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9940 [D loss: 0.685119, acc.: 48.24%] [G loss: 0.714907]
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9941 [D loss: 0.691068, acc.: 44.92%] [G loss: 0.714115]
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9942 [D loss: 0.685148, acc.: 48.24%] [G loss: 0.725931]
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9943 [D loss: 0.678640, acc.: 50.59%] [G loss: 0.733038]
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9944 [D loss: 0.680619, acc.: 52.34%] [G loss: 0.750602]
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9945 [D loss: 0.677162, acc.: 53.91%] [G loss: 0.755899]
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9946 [D loss: 0.677079, acc.: 56.05%] [G loss: 0.739487]
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9947 [D loss: 0.687737, acc.: 47.85%] [G loss: 0.737206]
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9948 [D loss: 0.682947, acc.: 51.37%] [G loss: 0.734549]
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9949 [D loss: 0.671927, acc.: 54.30%] [G loss: 0.727980]
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9950 [D loss: 0.689718, acc.: 48.63%] [G loss: 0.718134]
1/1 [==============================] - 0s 20ms/step
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9951 [D loss: 0.682532, acc.: 48.63%] [G loss: 0.720463]
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9952 [D loss: 0.686358, acc.: 50.59%] [G loss: 0.722162]
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9953 [D loss: 0.684747, acc.: 48.44%] [G loss: 0.726364]
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9954 [D loss: 0.689650, acc.: 46.29%] [G loss: 0.737185]
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9955 [D loss: 0.672376, acc.: 52.93%] [G loss: 0.740124]
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9956 [D loss: 0.685518, acc.: 49.80%] [G loss: 0.739639]
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9957 [D loss: 0.681807, acc.: 52.54%] [G loss: 0.725651]
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9958 [D loss: 0.684120, acc.: 50.98%] [G loss: 0.729239]
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9959 [D loss: 0.682986, acc.: 48.83%] [G loss: 0.725472]
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9960 [D loss: 0.684718, acc.: 50.98%] [G loss: 0.728062]
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9961 [D loss: 0.681403, acc.: 47.66%] [G loss: 0.723626]
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9962 [D loss: 0.686255, acc.: 45.90%] [G loss: 0.726024]
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9963 [D loss: 0.680185, acc.: 53.91%] [G loss: 0.745302]
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9964 [D loss: 0.683625, acc.: 53.32%] [G loss: 0.755865]
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9965 [D loss: 0.675604, acc.: 52.54%] [G loss: 0.763930]
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9966 [D loss: 0.674697, acc.: 53.91%] [G loss: 0.752928]
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9967 [D loss: 0.680486, acc.: 53.12%] [G loss: 0.748883]
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9968 [D loss: 0.688646, acc.: 50.98%] [G loss: 0.740139]
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9969 [D loss: 0.679106, acc.: 50.78%] [G loss: 0.740959]
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9970 [D loss: 0.690133, acc.: 50.00%] [G loss: 0.735459]
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9971 [D loss: 0.697294, acc.: 45.12%] [G loss: 0.714966]
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9972 [D loss: 0.685662, acc.: 46.09%] [G loss: 0.717443]
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9973 [D loss: 0.685115, acc.: 47.27%] [G loss: 0.716863]
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9974 [D loss: 0.690866, acc.: 44.73%] [G loss: 0.728060]
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9975 [D loss: 0.693143, acc.: 46.88%] [G loss: 0.742012]
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9976 [D loss: 0.679244, acc.: 48.63%] [G loss: 0.735256]
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9977 [D loss: 0.688661, acc.: 48.44%] [G loss: 0.737828]
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9978 [D loss: 0.683169, acc.: 46.29%] [G loss: 0.729440]
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9979 [D loss: 0.684426, acc.: 50.98%] [G loss: 0.733804]
8/8 [==============================] - 0s 5ms/step
9980 [D loss: 0.683329, acc.: 53.12%] [G loss: 0.730071]
8/8 [==============================] - 0s 5ms/step
9981 [D loss: 0.691794, acc.: 50.20%] [G loss: 0.715538]
8/8 [==============================] - 0s 5ms/step
9982 [D loss: 0.678386, acc.: 49.02%] [G loss: 0.722565]
8/8 [==============================] - 0s 5ms/step
9983 [D loss: 0.687336, acc.: 49.41%] [G loss: 0.723915]
8/8 [==============================] - 0s 5ms/step
9984 [D loss: 0.682555, acc.: 48.44%] [G loss: 0.731700]
8/8 [==============================] - 0s 5ms/step
9985 [D loss: 0.688533, acc.: 48.63%] [G loss: 0.726250]
8/8 [==============================] - 0s 5ms/step
9986 [D loss: 0.691226, acc.: 46.09%] [G loss: 0.722394]
8/8 [==============================] - 0s 5ms/step
9987 [D loss: 0.691712, acc.: 49.61%] [G loss: 0.719203]
8/8 [==============================] - 0s 5ms/step
9988 [D loss: 0.687352, acc.: 48.63%] [G loss: 0.734166]
8/8 [==============================] - 0s 5ms/step
9989 [D loss: 0.676411, acc.: 54.10%] [G loss: 0.749115]
8/8 [==============================] - 0s 5ms/step
9990 [D loss: 0.682857, acc.: 48.63%] [G loss: 0.739444]
8/8 [==============================] - 0s 5ms/step
9991 [D loss: 0.688949, acc.: 46.29%] [G loss: 0.733423]
8/8 [==============================] - 0s 5ms/step
9992 [D loss: 0.687950, acc.: 49.41%] [G loss: 0.736692]
8/8 [==============================] - 0s 5ms/step
9993 [D loss: 0.675181, acc.: 53.71%] [G loss: 0.761556]
8/8 [==============================] - 0s 5ms/step
9994 [D loss: 0.698430, acc.: 45.31%] [G loss: 0.730184]
8/8 [==============================] - 0s 5ms/step
9995 [D loss: 0.699843, acc.: 47.07%] [G loss: 0.719979]
8/8 [==============================] - 0s 5ms/step
9996 [D loss: 0.701985, acc.: 44.73%] [G loss: 0.720470]
8/8 [==============================] - 0s 5ms/step
9997 [D loss: 0.698761, acc.: 44.73%] [G loss: 0.735794]
8/8 [==============================] - 0s 5ms/step
9998 [D loss: 0.686684, acc.: 53.52%] [G loss: 0.753959]
8/8 [==============================] - 0s 5ms/step
9999 [D loss: 0.693468, acc.: 50.20%] [G loss: 0.763858]

Final Model Evaluation

Model Architecture

Generator

cgan.generator.summary()

Model: "model_1"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_4 (InputLayer)           [(None, 1)]          0           []                               
                                                                                                  
 embedding_1 (Embedding)        (None, 1, 100)       2600        ['input_4[0][0]']                
                                                                                                  
 input_3 (InputLayer)           [(None, 100)]        0           []                               
                                                                                                  
 flatten_2 (Flatten)            (None, 100)          0           ['embedding_1[0][0]']            
                                                                                                  
 multiply_1 (Multiply)          (None, 100)          0           ['input_3[0][0]',                
                                                                  'flatten_2[0][0]']              
                                                                                                  
 sequential_1 (Sequential)      (None, 28, 28, 1)    3780353     ['multiply_1[0][0]']             
                                                                                                  
==================================================================================================
Total params: 3,782,953
Trainable params: 3,782,953
Non-trainable params: 0
__________________________________________________________________________________________________

Discriminator

cgan.discriminator.summary()

Model: "model"
__________________________________________________________________________________________________
 Layer (type)                   Output Shape         Param #     Connected to                     
==================================================================================================
 input_2 (InputLayer)           [(None, 1)]          0           []                               
                                                                                                  
 embedding (Embedding)          (None, 1, 784)       20384       ['input_2[0][0]']                
                                                                                                  
 flatten_1 (Flatten)            (None, 784)          0           ['embedding[0][0]']              
                                                                                                  
 dense_1 (Dense)                (None, 784)          615440      ['flatten_1[0][0]']              
                                                                                                  
 input_1 (InputLayer)           [(None, 28, 28, 1)]  0           []                               
                                                                                                  
 reshape (Reshape)              (None, 28, 28, 1)    0           ['dense_1[0][0]']                
                                                                                                  
 multiply (Multiply)            (None, 28, 28, 1)    0           ['input_1[0][0]',                
                                                                  'reshape[0][0]']                
                                                                                                  
 sequential (Sequential)        (None, 1)            373761      ['multiply[0][0]']               
                                                                                                  
==================================================================================================
Total params: 1,009,585
Trainable params: 0
Non-trainable params: 1,009,585
__________________________________________________________________________________________________

Generated Images at Different Epochs

100 Epochs:

1000 Epochs:

2950 Epochs:

5000 Epochs:

10000 Epochs:

Samples of Generated Images VS Real Images

# Preprocess the data: normalize pixel values and reshape images
img_rows, img_cols, channels = 28, 28, 1  # Define image shape
upright_image_df.iloc[:, 1:] = upright_image_df.iloc[:, 1:] 

# Example usage
img_shape = (img_rows, img_cols, channels)
compare_images(cgan, upright_image_df, img_shape)

1/1 [==============================] - 0s 271ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 17ms/step
1/1 [==============================] - 0s 17ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 17ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 17ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 17ms/step
1/1 [==============================] - 0s 23ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 17ms/step

Results

From the generated images, we can see that most classes are represented clearly with great details. These classes include A, C, D, E, F, I, J, K, L, N, O, P, R, S, T, U, V, and X. The clarity and detail of these images indicate that the Generator has effectively learned to reproduce these letters. For instance, the letter "A" is clearly identifiable with distinct lines and shapes, and the letter "C" has smooth and clear curves. These classes exhibit sharp and well-defined features, comparable to real images, showcasing the Generator's capability to capture the essential characteristics of each class accurately.

However, there are some classes where the details are not fully captured. These include B, Y, W, Q, M, H, and G. In these classes, we observe distortions, where the shapes are not as well-defined as in real images, and instances of blurriness, where the features are not as sharp, making it harder to recognize the letters. For example, the letter "B" may have irregular shapes, and "W" might appear with missing or distorted lines.

Lastly, the Z class is producing images with a black background and only a few pixels. This indicates a significant issue with the Generator's ability to reproduce the letter "Z". The generated images for this class lack the necessary structure and detail, rendering them unrecognizable and drastically different from the real images. This specific failure suggests that the Generator has not effectively learned to capture the characteristics of the letter "Z".

Loss

plot_losses(cgan.d_losses, cgan.g_losses)

Results

We can observe that initially, our Generator starts with a very high loss, around 6. After approximately 200 epochs, the loss begins to decrease, stabilizing at around 0.7, and remains consistent throughout the rest of the training.

Conversely, our Discriminator starts with a very low loss, close to 0. After about 200 epochs, the loss begins to increase, leveling off at around 0.7, and remains stable for the duration of the training.

This pattern suggests that as training progresses, the Generator becomes more effective at producing realistic images, which makes it harder for the Discriminator to distinguish between real and generated images. The stabilization of both losses at similar values indicates that the model is approaching equilibrium, where the Generator and Discriminator are in balance. This balance is a key aspect of the training process for Generative Adversarial Networks (GANs), indicating that neither model is significantly outperforming the other.

Achieving this balance is crucial for the Generator to produce high-quality images, as it shows that the Discriminator cannot easily differentiate between real and generated data

Accuracy

Accuracy Throughout Training

plot_accuracy(cgan.d_accuracy)

Results

We can observe that initially, our Discriminator starts with very high accuracy, around 100%. As training progresses, after approximately 200 epochs, the accuracy begins to decrease and fluctuates between 40% and 60%.

This suggests that as the training continues, the Generator improves its ability to produce realistic images, making it more challenging for the Discriminator to correctly distinguish between real and generated images. The decrease in the Discriminator's accuracy indicates that the quality of the Generator's outputs is improving. The fluctuation in accuracy between 40% and 60% reflects a dynamic balance where the Discriminator is sometimes correct and sometimes incorrect, signifying a healthy competition between the Generator and the Discriminator.

Accuracy of Predicting Real Images

real_df = preprocessed_df.sample(n=1000, random_state=1) 
real_df.reset_index(drop=True, inplace=True)

X_real = preprocessed_df.iloc[:, 1:].values 
y_real = preprocessed_df.iloc[:, 0].values 
X_real = X_real.reshape(-1, 28, 28, 1) 

loss_real, accuracy_real = cgan.discriminator.evaluate([X_real, y_real], np.ones((len(X_real), 1)), verbose=1)
print(f"Discriminator Accuracy on Real Images: {accuracy_real * 100:.2f}%")

2844/2844 [==============================] - 8s 3ms/step - loss: 0.6908 - accuracy: 0.4705
Discriminator Accuracy on Real Images: 47.05%

Results

The Discriminator accuracy of 45.62% after training indicates that the GAN has reached a point where the Generator produces fairly realistic images, and the Discriminator is reasonably challenged.

Accuracy of Predicting Fake Images

def generate_fake_images(generator, num_images):
    # Generate noise for the generator
    noise = np.random.normal(0, 1, (num_images, 100))
    labels = np.random.randint(1, 27, num_images).reshape(-1, 1)
    # Generate fake images
    fake_images = generator.predict([noise, labels])
    return fake_images, labels


num_fake_images = 1000
fake_images, fake_labels = generate_fake_images(cgan.generator, num_fake_images)

fake_df = pd.DataFrame(fake_images.reshape(num_fake_images, -1)) 

fake_df.insert(0, 'Label', fake_labels)

# Prepare fake data for evaluation
X_fake = fake_df.iloc[:, 1:].values
y_fake = fake_df['Label'].values
X_fake = X_fake.reshape(-1, 28, 28, 1)

# Evaluate using the discriminator
loss_fake, accuracy_fake = cgan.discriminator.evaluate([X_fake, y_fake], np.zeros((len(X_fake), 1)), verbose=1)
print(f"Discriminator Accuracy on Fake Images: {accuracy_fake * 100:.2f}%")

32/32 [==============================] - 0s 11ms/step
32/32 [==============================] - 0s 3ms/step - loss: 0.6662 - accuracy: 0.6440
Discriminator Accuracy on Fake Images: 64.40%

Results

An accuracy of 61.00% means the Discriminator correctly identifies 61% of the generated images as fake. Indicating that the Discriminator has learned to some extent to distinguish fake images but still finds it challenging.

KL Divergence

num_samples = 1000
kl_divergence = compute_kl_divergence(cgan.generator, X_real, num_samples)
print(f"Estimated KL Divergence: {kl_divergence}")

32/32 [==============================] - 0s 5ms/step
Estimated KL Divergence: 0.17761265668841214

Results

The low KL Divergence suggests that there is some divergence between the distribution of real and generated images, but it is relatively low. A KL divergence close to 0 would be ideal, indicating that the Generator is producing images that are very similar to the real ones in distribution.

The value 0.2112 implies that the Generator is fairly successful in mimicking the real data distribution. This indicates that the Generator has learned to capture the essential features and variations present in the real images, producing outputs that are not easily distinguishable from real images by the Discriminator.

Save the Model

cgan.generator.save('generator_model.h5')
cgan.discriminator.save('discriminator_model.h5')

WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.

Final Verdict on The Performance of The Final Model

The clear and detailed representation of most classes, such as A, C, D, E, F, I, J, K, L, N, O, P, R, S, T, U, V, and X, demonstrates that the Generator has effectively learned to capture and reproduce these letters. The sharp and well-defined features in these images indicate that the Generator has a strong ability to produce high-quality outputs that closely resemble real images. However, the distorted and blurry representations in classes like B, Y, W, Q, M, H, and G, and the significant issues with the Z class, highlight areas where the Generator's performance is lacking.

The training losses of both the Generator and Discriminator provide valuable insights into the training dynamics. The initial high loss of the Generator, which decreases and stabilizes around 0.7 after 200 epochs, indicates that the Generator improves significantly over time. Conversely, the Discriminator's initial low loss, which increases and stabilizes around 0.7, shows that the Discriminator starts strong but becomes less certain as the Generator improves. This pattern suggests that the model is approaching equilibrium, where the Generator and Discriminator are balanced, making it harder for the Discriminator to distinguish between real and generated images. Achieving this balance is crucial for the Generator to produce high-quality images consistently.

At the start, the Discriminator achieves very high accuracy, around 100%. However, as training progresses, the accuracy decreases and fluctuates between 40% and 60%. This decrease suggests that the Generator's ability to produce realistic images has improved, making it more challenging for the Discriminator to distinguish between real and generated images. The fluctuation in accuracy indicates a dynamic balance between the Generator and Discriminator, reflecting a healthy and competitive training process.

The relatively low KL Divergence value of 0.2112 implies that the Generator is fairly successful in mimicking the real data distribution. While a KL Divergence close to 0 would be ideal, indicating near-perfect similarity between real and generated distributions, the current value shows that the Generator has learned to capture essential features and variations present in real images. This is a positive indicator of the Generator's ability to produce realistic outputs.

Together, these metrics form a comprehensive evaluation framework that allows us to understand the strengths and weaknesses of our GAN model. The consistency in generated image quality for most classes, the balanced training losses, and the relatively low KL Divergence all point to a generally well-performing model.

In conclusion, our GAN model demonstrates strong potential, with effective learning for most classes and a balanced training dynamic.

Generate Images

The Z Problem

---

From our evaluation, we discovered that the 'Z' class is producing images with a black background and only a few pixels. This indicates a significant issue with the Final CGAN's Generator's ability to reproduce the letter "Z". The generated images for this class lack the necessary structure and detail, rendering them unrecognizable and drastically different from the real images. This specific failure suggests that the Generator has not effectively learned to capture the characteristics of the letter "Z".

Images we are going to generate

---

There are 26 classes in total, and we will generate 10 images for each class (Total of 260 images).

How are we going to generate 260 images

---

To generate the 260 images mentioned, we will utilize our best CGAN model to generate images for the 25 classes (A - Y). This approach involves using our Final CGAN model, which has shown the ability to generate specific classes effectively. By leveraging this model, we aim to create 250 images (10 for each of the 25 classes) that accurately represent the unique characteristics of each letter from A to Y.

Given the challenge we face with the 'Z' class, where our best CGAN model struggles to generate recognizable images, we will use a DCGAN to address this issue. The DCGAN will be specifically trained on images of the 'Z' class. Unlike CGANs, DCGANs do not require class labels, making them suitable for generating images focused on a single class. This allows us to simplify the training process by avoiding the complexity of class conditioning. By training the DCGAN exclusively on images of the letter 'Z,' we aim to specialize the model, enabling it to produce higher-quality images for this specific class and effectively address the problem..

Generate all classes other than Z

save_root_dir = 'final_images'

# Create root directory if it doesn't exist
os.makedirs(save_root_dir, exist_ok=True)

# Number of images per class
num_samples_per_class = 10
num_classes = cgan.num_classes - 1

# Generate and save images
for class_label in range(1, num_classes + 1):
    # Create directory for the current class
    class_dir = os.path.join(save_root_dir, f'class_{map_labels(class_label)}')
    os.makedirs(class_dir, exist_ok=True)
    
    # Generate noise for the batch of images
    noise = np.random.normal(0, 1, (num_samples_per_class, cgan.latent_dim))

    # Generate labels for the batch of images
    sampled_labels = np.array([class_label] * num_samples_per_class).reshape(-1, 1)

    # Generate images using the generator
    gen_imgs = cgan.generator.predict([noise, sampled_labels])

    # Rescale images to 0 - 255
    gen_imgs = 255 * 0.5 * gen_imgs + 255 * 0.5
    gen_imgs = gen_imgs.astype(np.uint8)  # Convert to uint8 for saving as images
    
   # Save images to the class directory
    for i in range(num_samples_per_class):
        plt.imshow(gen_imgs[i,:,:,0], cmap='gray')
        plt.axis('off')
        plt.savefig(f'{class_dir}/image_{i}.png')
        plt.close()

1/1 [==============================] - 0s 226ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 30ms/step
1/1 [==============================] - 0s 21ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 21ms/step
1/1 [==============================] - 0s 23ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 17ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 19ms/step
1/1 [==============================] - 0s 21ms/step
1/1 [==============================] - 0s 18ms/step
1/1 [==============================] - 0s 20ms/step
1/1 [==============================] - 0s 24ms/step
1/1 [==============================] - 0s 21ms/step
1/1 [==============================] - 0s 19ms/step

Geneate Z class

z_alphabet_df = preprocessed_df[preprocessed_df[0] == 26]

class DCGAN():
    
    # this is the function to build the generator neural network
    def build_generator(self):
        model = Sequential()

        model.add(Dense(1500 * 7 * 7, activation="relu", input_dim=self.latent_dim))
        model.add(Reshape((7, 7, 1500)))
        
        model.add(UpSampling2D())
        model.add(Conv2D(128, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(UpSampling2D())
        model.add(Conv2D(64, kernel_size=3, padding="same"))
        model.add(BatchNormalization(momentum=0.8))
        model.add(Activation("relu"))
        
        model.add(Conv2D(self.channels, kernel_size=3, padding="same"))
        model.add(Activation("sigmoid"))

        model.summary()

        noise = Input(shape=(self.latent_dim,))
        img = model(noise)

        return Model(noise, img)
    
    def build_discriminator(self):
        model = Sequential(name='Discriminator')
        model.add(Conv2D(128, kernel_size=3, strides=2, input_shape=self.img_shape, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(128, kernel_size=3, strides=2, padding="same"))
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Conv2D(256, kernel_size=3, strides=2, padding="same"))  # New layer
        model.add(LeakyReLU(alpha=0.2))
        model.add(Dropout(0.4))
        
        model.add(Flatten())
        
        # Add one more dense layer
        model.add(Dense(256))  # Adjust the units as per your architecture needs
        model.add(LeakyReLU(alpha=0.2))
        
        model.add(Dense(1, activation='sigmoid'))
        model.summary()
        
        img = Input(shape=self.img_shape)
        validity = model(img)
        return Model(img, validity)
        
    def __init__(self, rows, cols, channels, z = 100):
        # Input shape
        self.img_rows = rows  # generated image height
        self.img_cols = cols  # generated image width
        self.channels = channels  # generated image channel
        self.img_shape = (self.img_rows, self.img_cols, self.channels)
        self.latent_dim = z  # the input is 1-D vector of noise
        # Reduce learning rate from 0.001 to 0.0002, and beta1 from 0.9 to 0.5, which can stablize training and reduce oscillation
        optimizer = Adam(learning_rate=0.0002, beta_1=0.5)
        # Build and compile the discriminator
        self.discriminator = self.build_discriminator()
        self.discriminator.compile(loss='binary_crossentropy',
            optimizer=optimizer,
            metrics=['accuracy'])
        # Build the generator
        self.generator = self.build_generator()
        # The generator takes noise as input and generates images
        z = Input(shape=(self.latent_dim,))
        img = self.generator(z)
        # For the combined model we will only train the generator
        self.discriminator.trainable = False
        # The discriminator takes generated images as input and determines validity
        valid = self.discriminator(img)
        # The combined model (stacked generator and discriminator)
        # Trains the generator to fool the discriminator
        self.combined = Model(z, valid)
        self.combined.compile(loss='binary_crossentropy',
            optimizer=optimizer)
        # Loss function
        self.d_losses = []
        self.g_losses = []
        # Accuracy
        self.d_accuracy = []
        
    def train(self, epochs, batch_size=128, save_interval=50):
        # Assuming your data is in a pandas DataFrame `df`
        # Extract image data and convert to numpy array
        X_train = z_alphabet_df.iloc[:, 1:].values  # assuming first column is labels, rest are pixels
        X_train = X_train.reshape(-1, self.img_rows, self.img_cols, self.channels)  # reshape to image shape
        # Adversarial ground truths
        valid = np.ones((batch_size, 1))
        fake = np.zeros((batch_size, 1))
        
        for epoch in range(epochs):
            # ---------------------
            # Train Discriminator
            # ---------------------
            # Select a random half of images
            idx = np.random.randint(0, X_train.shape[0], batch_size)
            imgs = X_train[idx]
            
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            gen_imgs = self.generator.predict(noise)
            
            # Train the discriminator (classify real images as 1 and generated images as 0)
            d_loss_real = self.discriminator.train_on_batch(imgs, valid)
            d_loss_fake = self.discriminator.train_on_batch(gen_imgs, fake)
            d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)
            
            # ---------------------
            # Train Generator
            # ---------------------
            # Sample noise and generate a batch of new images
            noise = np.random.normal(0, 1, (batch_size, self.latent_dim))
            
            # Train the generator (generator wants discriminator to predict generated images as 1)
            g_loss = self.combined.train_on_batch(noise, valid)

            # Store losses
            self.d_losses.append(d_loss[0])
            self.g_losses.append(g_loss)
            # Store accuracy
            self.d_accuracy.append(100 * d_loss[1])
            # Print progress
            print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100 * d_loss[1], g_loss))
            
            # If at save interval => save generated image samples
            if epoch % save_interval == 0:
                self.save_imgs(epoch)

    def save_imgs(self, epoch):
        r, c = 5, 5
        noise = np.random.normal(0, 1, (r * c, self.latent_dim))
        gen_imgs = self.generator.predict(noise)

        # Rescale images 0 - 1
        # gen_imgs = 0.5 * gen_imgs + 0.5

        fig, axs = plt.subplots(r, c)
        cnt = 0
        for i in range(r):
            for j in range(c):
                axs[i,j].imshow(gen_imgs[cnt, :,:,0], cmap='gray')
                axs[i,j].axis('off')
                cnt += 1
        os.makedirs('generated_images', exist_ok=True)
        os.makedirs('generated_images/generatedTrain', exist_ok=True)
        os.makedirs('generated_images/generatedTrain/Z', exist_ok=True)
        fig.savefig("generated_images/generatedTrain/Z/dcgan_{:d}.png".format(epoch))
        plt.close()

dcgan = DCGAN(28,28,1)
dcgan.train(epochs=3000, batch_size=256, save_interval=50)

Model: "Discriminator"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_4 (Conv2D)           (None, 14, 14, 128)       1280      
                                                                 
 leaky_re_lu_6 (LeakyReLU)   (None, 14, 14, 128)       0         
                                                                 
 dropout (Dropout)           (None, 14, 14, 128)       0         
                                                                 
 conv2d_5 (Conv2D)           (None, 7, 7, 128)         147584    
                                                                 
 leaky_re_lu_7 (LeakyReLU)   (None, 7, 7, 128)         0         
                                                                 
 dropout_1 (Dropout)         (None, 7, 7, 128)         0         
                                                                 
 conv2d_6 (Conv2D)           (None, 4, 4, 256)         295168    
                                                                 
 leaky_re_lu_8 (LeakyReLU)   (None, 4, 4, 256)         0         
                                                                 
 dropout_2 (Dropout)         (None, 4, 4, 256)         0         
                                                                 
 flatten_3 (Flatten)         (None, 4096)              0         
                                                                 
 dense_3 (Dense)             (None, 256)               1048832   
                                                                 
 leaky_re_lu_9 (LeakyReLU)   (None, 256)               0         
                                                                 
 dense_4 (Dense)             (None, 1)                 257       
                                                                 
=================================================================
Total params: 1,493,121
Trainable params: 1,493,121
Non-trainable params: 0
_________________________________________________________________
Model: "sequential_2"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense_5 (Dense)             (None, 73500)             7423500   
                                                                 
 reshape_2 (Reshape)         (None, 7, 7, 1500)        0         
                                                                 
 up_sampling2d (UpSampling2D  (None, 14, 14, 1500)     0         
 )                                                               
                                                                 
 conv2d_7 (Conv2D)           (None, 14, 14, 128)       1728128   
                                                                 
 batch_normalization (BatchN  (None, 14, 14, 128)      512       
 ormalization)                                                   
                                                                 
 activation_1 (Activation)   (None, 14, 14, 128)       0         
                                                                 
 up_sampling2d_1 (UpSampling  (None, 28, 28, 128)      0         
 2D)                                                             
                                                                 
 conv2d_8 (Conv2D)           (None, 28, 28, 64)        73792     
                                                                 
 batch_normalization_1 (Batc  (None, 28, 28, 64)       256       
 hNormalization)                                                 
                                                                 
 activation_2 (Activation)   (None, 28, 28, 64)        0         
                                                                 
 conv2d_9 (Conv2D)           (None, 28, 28, 1)         577       
                                                                 
 activation_3 (Activation)   (None, 28, 28, 1)         0         
                                                                 
=================================================================
Total params: 9,226,765
Trainable params: 9,226,381
Non-trainable params: 384
_________________________________________________________________
8/8 [==============================] - 0s 16ms/step
0 [D loss: 0.734602, acc.: 34.57%] [G loss: 0.654539]
1/1 [==============================] - 0s 103ms/step
8/8 [==============================] - 0s 4ms/step
1 [D loss: 0.689823, acc.: 50.00%] [G loss: 0.685502]
8/8 [==============================] - 0s 4ms/step
2 [D loss: 0.665462, acc.: 82.42%] [G loss: 0.707854]
8/8 [==============================] - 0s 7ms/step
3 [D loss: 0.632865, acc.: 99.61%] [G loss: 0.725222]
8/8 [==============================] - 0s 5ms/step
4 [D loss: 0.588496, acc.: 99.22%] [G loss: 0.734238]
8/8 [==============================] - 0s 4ms/step
5 [D loss: 0.544384, acc.: 97.85%] [G loss: 0.696655]
8/8 [==============================] - 0s 4ms/step
6 [D loss: 0.518465, acc.: 97.46%] [G loss: 0.593767]
8/8 [==============================] - 0s 5ms/step
7 [D loss: 0.452279, acc.: 97.27%] [G loss: 0.487117]
8/8 [==============================] - 0s 4ms/step
8 [D loss: 0.422017, acc.: 98.05%] [G loss: 0.440459]
8/8 [==============================] - 0s 4ms/step
9 [D loss: 0.352986, acc.: 98.24%] [G loss: 0.368782]
8/8 [==============================] - 0s 4ms/step
10 [D loss: 0.276212, acc.: 99.61%] [G loss: 0.225671]
8/8 [==============================] - 0s 4ms/step
11 [D loss: 0.212900, acc.: 99.22%] [G loss: 0.135939]
8/8 [==============================] - 0s 5ms/step
12 [D loss: 0.153234, acc.: 99.61%] [G loss: 0.128795]
8/8 [==============================] - 0s 6ms/step
13 [D loss: 0.112921, acc.: 99.41%] [G loss: 0.116613]
8/8 [==============================] - 0s 4ms/step
14 [D loss: 0.076523, acc.: 100.00%] [G loss: 0.058522]
8/8 [==============================] - 0s 4ms/step
15 [D loss: 0.068066, acc.: 99.80%] [G loss: 0.063937]
8/8 [==============================] - 0s 4ms/step
16 [D loss: 0.077065, acc.: 100.00%] [G loss: 0.108799]
8/8 [==============================] - 0s 4ms/step
17 [D loss: 0.084437, acc.: 99.61%] [G loss: 0.104907]
8/8 [==============================] - 0s 5ms/step
18 [D loss: 0.083657, acc.: 97.66%] [G loss: 0.012814]
8/8 [==============================] - 0s 4ms/step
19 [D loss: 0.039484, acc.: 100.00%] [G loss: 0.044527]
8/8 [==============================] - 0s 4ms/step
20 [D loss: 0.122014, acc.: 98.44%] [G loss: 0.542413]
8/8 [==============================] - 0s 4ms/step
21 [D loss: 1.022698, acc.: 40.62%] [G loss: 0.361601]
8/8 [==============================] - 0s 4ms/step
22 [D loss: 0.185547, acc.: 91.80%] [G loss: 0.453778]
8/8 [==============================] - 0s 4ms/step
23 [D loss: 0.136129, acc.: 94.14%] [G loss: 0.013465]
8/8 [==============================] - 0s 4ms/step
24 [D loss: 0.013598, acc.: 99.80%] [G loss: 0.007521]
8/8 [==============================] - 0s 5ms/step
25 [D loss: 0.020037, acc.: 99.80%] [G loss: 0.007562]
8/8 [==============================] - 0s 4ms/step
26 [D loss: 0.126568, acc.: 94.14%] [G loss: 0.040779]
8/8 [==============================] - 0s 5ms/step
27 [D loss: 0.205030, acc.: 91.99%] [G loss: 0.558615]
8/8 [==============================] - 0s 4ms/step
28 [D loss: 2.165884, acc.: 38.28%] [G loss: 1.851673]
8/8 [==============================] - 0s 4ms/step
29 [D loss: 2.353665, acc.: 10.55%] [G loss: 0.953111]
8/8 [==============================] - 0s 5ms/step
30 [D loss: 1.260338, acc.: 21.68%] [G loss: 0.673234]
8/8 [==============================] - 0s 4ms/step
31 [D loss: 0.726300, acc.: 40.62%] [G loss: 0.659902]
8/8 [==============================] - 0s 4ms/step
32 [D loss: 0.630184, acc.: 49.80%] [G loss: 0.638754]
8/8 [==============================] - 0s 4ms/step
33 [D loss: 0.670406, acc.: 50.78%] [G loss: 0.644573]
8/8 [==============================] - 0s 4ms/step
34 [D loss: 0.721309, acc.: 48.44%] [G loss: 0.634433]
8/8 [==============================] - 0s 4ms/step
35 [D loss: 0.782925, acc.: 43.55%] [G loss: 0.650821]
8/8 [==============================] - 0s 5ms/step
36 [D loss: 0.860918, acc.: 35.94%] [G loss: 0.618393]
8/8 [==============================] - 0s 4ms/step
37 [D loss: 0.888501, acc.: 36.13%] [G loss: 0.551020]
8/8 [==============================] - 0s 4ms/step
38 [D loss: 0.880432, acc.: 33.40%] [G loss: 0.515075]
8/8 [==============================] - 0s 4ms/step
39 [D loss: 0.815663, acc.: 40.62%] [G loss: 0.504276]
8/8 [==============================] - 0s 4ms/step
40 [D loss: 0.797407, acc.: 41.80%] [G loss: 0.497080]
8/8 [==============================] - 0s 4ms/step
41 [D loss: 0.788268, acc.: 42.19%] [G loss: 0.494494]
8/8 [==============================] - 0s 4ms/step
42 [D loss: 0.790202, acc.: 43.55%] [G loss: 0.489504]
8/8 [==============================] - 0s 5ms/step
43 [D loss: 0.804539, acc.: 42.38%] [G loss: 0.498007]
8/8 [==============================] - 0s 4ms/step
44 [D loss: 0.805697, acc.: 40.82%] [G loss: 0.514842]
8/8 [==============================] - 0s 4ms/step
45 [D loss: 0.789548, acc.: 37.89%] [G loss: 0.548967]
8/8 [==============================] - 0s 5ms/step
46 [D loss: 0.750876, acc.: 39.06%] [G loss: 0.597843]
8/8 [==============================] - 0s 4ms/step
47 [D loss: 0.726679, acc.: 38.09%] [G loss: 0.649523]
8/8 [==============================] - 0s 5ms/step
48 [D loss: 0.688150, acc.: 40.23%] [G loss: 0.703335]
8/8 [==============================] - 0s 4ms/step
49 [D loss: 0.670054, acc.: 55.27%] [G loss: 0.752844]
8/8 [==============================] - 0s 4ms/step
50 [D loss: 0.650543, acc.: 70.31%] [G loss: 0.787083]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 38ms/step
51 [D loss: 0.643376, acc.: 75.39%] [G loss: 0.807665]
8/8 [==============================] - 0s 5ms/step
52 [D loss: 0.647317, acc.: 71.48%] [G loss: 0.806165]
8/8 [==============================] - 0s 5ms/step
53 [D loss: 0.663794, acc.: 62.70%] [G loss: 0.778995]
8/8 [==============================] - 0s 5ms/step
54 [D loss: 0.701439, acc.: 48.83%] [G loss: 0.729625]
8/8 [==============================] - 0s 5ms/step
55 [D loss: 0.747982, acc.: 32.42%] [G loss: 0.705405]
8/8 [==============================] - 0s 5ms/step
56 [D loss: 0.758797, acc.: 26.37%] [G loss: 0.699249]
8/8 [==============================] - 0s 4ms/step
57 [D loss: 0.760902, acc.: 20.90%] [G loss: 0.716581]
8/8 [==============================] - 0s 4ms/step
58 [D loss: 0.755576, acc.: 20.12%] [G loss: 0.722426]
8/8 [==============================] - 0s 5ms/step
59 [D loss: 0.736089, acc.: 27.34%] [G loss: 0.731088]
8/8 [==============================] - 0s 4ms/step
60 [D loss: 0.729876, acc.: 29.30%] [G loss: 0.727241]
8/8 [==============================] - 0s 5ms/step
61 [D loss: 0.724128, acc.: 32.03%] [G loss: 0.723323]
8/8 [==============================] - 0s 5ms/step
62 [D loss: 0.728302, acc.: 26.76%] [G loss: 0.707841]
8/8 [==============================] - 0s 4ms/step
63 [D loss: 0.721900, acc.: 29.49%] [G loss: 0.689451]
8/8 [==============================] - 0s 4ms/step
64 [D loss: 0.727760, acc.: 28.71%] [G loss: 0.673019]
8/8 [==============================] - 0s 4ms/step
65 [D loss: 0.720403, acc.: 33.98%] [G loss: 0.666793]
8/8 [==============================] - 0s 4ms/step
66 [D loss: 0.713440, acc.: 39.26%] [G loss: 0.662906]
8/8 [==============================] - 0s 4ms/step
67 [D loss: 0.709373, acc.: 40.43%] [G loss: 0.656643]
8/8 [==============================] - 0s 5ms/step
68 [D loss: 0.701472, acc.: 43.95%] [G loss: 0.658902]
8/8 [==============================] - 0s 4ms/step
69 [D loss: 0.694105, acc.: 47.27%] [G loss: 0.662508]
8/8 [==============================] - 0s 5ms/step
70 [D loss: 0.696594, acc.: 45.31%] [G loss: 0.664267]
8/8 [==============================] - 0s 5ms/step
71 [D loss: 0.694982, acc.: 44.73%] [G loss: 0.664475]
8/8 [==============================] - 0s 4ms/step
72 [D loss: 0.687590, acc.: 47.66%] [G loss: 0.662145]
8/8 [==============================] - 0s 4ms/step
73 [D loss: 0.687539, acc.: 45.51%] [G loss: 0.658060]
8/8 [==============================] - 0s 4ms/step
74 [D loss: 0.688427, acc.: 47.07%] [G loss: 0.661040]
8/8 [==============================] - 0s 4ms/step
75 [D loss: 0.691490, acc.: 46.88%] [G loss: 0.654609]
8/8 [==============================] - 0s 4ms/step
76 [D loss: 0.691805, acc.: 46.09%] [G loss: 0.654138]
8/8 [==============================] - 0s 4ms/step
77 [D loss: 0.694030, acc.: 48.63%] [G loss: 0.656479]
8/8 [==============================] - 0s 4ms/step
78 [D loss: 0.697583, acc.: 45.51%] [G loss: 0.652121]
8/8 [==============================] - 0s 5ms/step
79 [D loss: 0.695128, acc.: 46.29%] [G loss: 0.654951]
8/8 [==============================] - 0s 4ms/step
80 [D loss: 0.693783, acc.: 46.88%] [G loss: 0.653996]
8/8 [==============================] - 0s 5ms/step
81 [D loss: 0.695266, acc.: 45.70%] [G loss: 0.656904]
8/8 [==============================] - 0s 4ms/step
82 [D loss: 0.694501, acc.: 43.75%] [G loss: 0.652746]
8/8 [==============================] - 0s 4ms/step
83 [D loss: 0.690724, acc.: 46.48%] [G loss: 0.659084]
8/8 [==============================] - 0s 4ms/step
84 [D loss: 0.689155, acc.: 47.07%] [G loss: 0.657010]
8/8 [==============================] - 0s 4ms/step
85 [D loss: 0.687891, acc.: 46.09%] [G loss: 0.655966]
8/8 [==============================] - 0s 5ms/step
86 [D loss: 0.691412, acc.: 48.44%] [G loss: 0.651536]
8/8 [==============================] - 0s 4ms/step
87 [D loss: 0.685464, acc.: 50.78%] [G loss: 0.660466]
8/8 [==============================] - 0s 4ms/step
88 [D loss: 0.689984, acc.: 50.00%] [G loss: 0.656799]
8/8 [==============================] - 0s 4ms/step
89 [D loss: 0.691163, acc.: 53.32%] [G loss: 0.672106]
8/8 [==============================] - 0s 4ms/step
90 [D loss: 0.683198, acc.: 57.23%] [G loss: 0.675590]
8/8 [==============================] - 0s 4ms/step
91 [D loss: 0.683483, acc.: 54.69%] [G loss: 0.690740]
8/8 [==============================] - 0s 5ms/step
92 [D loss: 0.674383, acc.: 60.94%] [G loss: 0.696411]
8/8 [==============================] - 0s 4ms/step
93 [D loss: 0.671238, acc.: 65.04%] [G loss: 0.710830]
8/8 [==============================] - 0s 5ms/step
94 [D loss: 0.670494, acc.: 66.02%] [G loss: 0.721843]
8/8 [==============================] - 0s 4ms/step
95 [D loss: 0.665297, acc.: 66.99%] [G loss: 0.728680]
8/8 [==============================] - 0s 4ms/step
96 [D loss: 0.661073, acc.: 68.36%] [G loss: 0.738456]
8/8 [==============================] - 0s 5ms/step
97 [D loss: 0.662261, acc.: 70.31%] [G loss: 0.741765]
8/8 [==============================] - 0s 4ms/step
98 [D loss: 0.667406, acc.: 65.82%] [G loss: 0.728139]
8/8 [==============================] - 0s 4ms/step
99 [D loss: 0.674935, acc.: 61.13%] [G loss: 0.727912]
8/8 [==============================] - 0s 4ms/step
100 [D loss: 0.682494, acc.: 57.81%] [G loss: 0.714271]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 4ms/step
101 [D loss: 0.695743, acc.: 51.76%] [G loss: 0.701735]
8/8 [==============================] - 0s 5ms/step
102 [D loss: 0.706885, acc.: 43.95%] [G loss: 0.690296]
8/8 [==============================] - 0s 4ms/step
103 [D loss: 0.717510, acc.: 42.97%] [G loss: 0.673774]
8/8 [==============================] - 0s 4ms/step
104 [D loss: 0.728730, acc.: 34.38%] [G loss: 0.670065]
8/8 [==============================] - 0s 4ms/step
105 [D loss: 0.731907, acc.: 30.27%] [G loss: 0.667913]
8/8 [==============================] - 0s 4ms/step
106 [D loss: 0.728437, acc.: 28.32%] [G loss: 0.666682]
8/8 [==============================] - 0s 4ms/step
107 [D loss: 0.724977, acc.: 28.71%] [G loss: 0.675648]
8/8 [==============================] - 0s 5ms/step
108 [D loss: 0.724502, acc.: 30.66%] [G loss: 0.672973]
8/8 [==============================] - 0s 4ms/step
109 [D loss: 0.720724, acc.: 30.86%] [G loss: 0.677780]
8/8 [==============================] - 0s 4ms/step
110 [D loss: 0.711717, acc.: 33.20%] [G loss: 0.685115]
8/8 [==============================] - 0s 5ms/step
111 [D loss: 0.710521, acc.: 35.94%] [G loss: 0.687130]
8/8 [==============================] - 0s 4ms/step
112 [D loss: 0.702318, acc.: 41.60%] [G loss: 0.684598]
8/8 [==============================] - 0s 4ms/step
113 [D loss: 0.703091, acc.: 42.97%] [G loss: 0.692457]
8/8 [==============================] - 0s 5ms/step
114 [D loss: 0.698340, acc.: 48.83%] [G loss: 0.694088]
8/8 [==============================] - 0s 4ms/step
115 [D loss: 0.695641, acc.: 51.56%] [G loss: 0.699031]
8/8 [==============================] - 0s 5ms/step
116 [D loss: 0.693580, acc.: 54.88%] [G loss: 0.696511]
8/8 [==============================] - 0s 4ms/step
117 [D loss: 0.686476, acc.: 61.33%] [G loss: 0.701350]
8/8 [==============================] - 0s 4ms/step
118 [D loss: 0.686072, acc.: 60.35%] [G loss: 0.702392]
8/8 [==============================] - 0s 4ms/step
119 [D loss: 0.683862, acc.: 61.13%] [G loss: 0.696376]
8/8 [==============================] - 0s 4ms/step
120 [D loss: 0.679386, acc.: 60.74%] [G loss: 0.698963]
8/8 [==============================] - 0s 4ms/step
121 [D loss: 0.684592, acc.: 58.40%] [G loss: 0.702800]
8/8 [==============================] - 0s 4ms/step
122 [D loss: 0.684069, acc.: 60.16%] [G loss: 0.702364]
8/8 [==============================] - 0s 5ms/step
123 [D loss: 0.682836, acc.: 58.20%] [G loss: 0.699749]
8/8 [==============================] - 0s 4ms/step
124 [D loss: 0.680604, acc.: 58.79%] [G loss: 0.696174]
8/8 [==============================] - 0s 4ms/step
125 [D loss: 0.677267, acc.: 59.96%] [G loss: 0.699359]
8/8 [==============================] - 0s 5ms/step
126 [D loss: 0.684386, acc.: 56.05%] [G loss: 0.694698]
8/8 [==============================] - 0s 4ms/step
127 [D loss: 0.682646, acc.: 57.62%] [G loss: 0.695443]
8/8 [==============================] - 0s 5ms/step
128 [D loss: 0.687620, acc.: 51.95%] [G loss: 0.687331]
8/8 [==============================] - 0s 5ms/step
129 [D loss: 0.690287, acc.: 51.17%] [G loss: 0.686291]
8/8 [==============================] - 0s 4ms/step
130 [D loss: 0.692919, acc.: 50.98%] [G loss: 0.675794]
8/8 [==============================] - 0s 5ms/step
131 [D loss: 0.696440, acc.: 50.78%] [G loss: 0.664019]
8/8 [==============================] - 0s 4ms/step
132 [D loss: 0.703091, acc.: 44.92%] [G loss: 0.661458]
8/8 [==============================] - 0s 5ms/step
133 [D loss: 0.704603, acc.: 47.27%] [G loss: 0.656256]
8/8 [==============================] - 0s 5ms/step
134 [D loss: 0.704836, acc.: 45.31%] [G loss: 0.654571]
8/8 [==============================] - 0s 4ms/step
135 [D loss: 0.709065, acc.: 45.31%] [G loss: 0.651655]
8/8 [==============================] - 0s 5ms/step
136 [D loss: 0.712379, acc.: 43.16%] [G loss: 0.649209]
8/8 [==============================] - 0s 4ms/step
137 [D loss: 0.712992, acc.: 43.75%] [G loss: 0.647815]
8/8 [==============================] - 0s 5ms/step
138 [D loss: 0.714913, acc.: 41.99%] [G loss: 0.649849]
8/8 [==============================] - 0s 4ms/step
139 [D loss: 0.712597, acc.: 41.99%] [G loss: 0.655662]
8/8 [==============================] - 0s 4ms/step
140 [D loss: 0.712031, acc.: 40.62%] [G loss: 0.658144]
8/8 [==============================] - 0s 5ms/step
141 [D loss: 0.714039, acc.: 41.41%] [G loss: 0.664519]
8/8 [==============================] - 0s 5ms/step
142 [D loss: 0.711165, acc.: 41.99%] [G loss: 0.661401]
8/8 [==============================] - 0s 4ms/step
143 [D loss: 0.710317, acc.: 39.65%] [G loss: 0.666324]
8/8 [==============================] - 0s 5ms/step
144 [D loss: 0.709606, acc.: 39.26%] [G loss: 0.666183]
8/8 [==============================] - 0s 4ms/step
145 [D loss: 0.704985, acc.: 45.31%] [G loss: 0.669855]
8/8 [==============================] - 0s 4ms/step
146 [D loss: 0.702509, acc.: 44.34%] [G loss: 0.672907]
8/8 [==============================] - 0s 4ms/step
147 [D loss: 0.702581, acc.: 46.48%] [G loss: 0.678600]
8/8 [==============================] - 0s 4ms/step
148 [D loss: 0.702031, acc.: 43.55%] [G loss: 0.683231]
8/8 [==============================] - 0s 5ms/step
149 [D loss: 0.696159, acc.: 50.20%] [G loss: 0.680214]
8/8 [==============================] - 0s 5ms/step
150 [D loss: 0.699667, acc.: 48.05%] [G loss: 0.689048]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 4ms/step
151 [D loss: 0.696611, acc.: 48.44%] [G loss: 0.698329]
8/8 [==============================] - 0s 4ms/step
152 [D loss: 0.695599, acc.: 49.22%] [G loss: 0.697997]
8/8 [==============================] - 0s 5ms/step
153 [D loss: 0.693996, acc.: 51.37%] [G loss: 0.702809]
8/8 [==============================] - 0s 4ms/step
154 [D loss: 0.692972, acc.: 51.37%] [G loss: 0.706043]
8/8 [==============================] - 0s 4ms/step
155 [D loss: 0.692367, acc.: 53.52%] [G loss: 0.710309]
8/8 [==============================] - 0s 5ms/step
156 [D loss: 0.691861, acc.: 56.64%] [G loss: 0.710927]
8/8 [==============================] - 0s 4ms/step
157 [D loss: 0.691968, acc.: 55.27%] [G loss: 0.715274]
8/8 [==============================] - 0s 4ms/step
158 [D loss: 0.691481, acc.: 55.08%] [G loss: 0.718979]
8/8 [==============================] - 0s 4ms/step
159 [D loss: 0.691038, acc.: 56.84%] [G loss: 0.714117]
8/8 [==============================] - 0s 4ms/step
160 [D loss: 0.689311, acc.: 57.42%] [G loss: 0.719747]
8/8 [==============================] - 0s 5ms/step
161 [D loss: 0.692422, acc.: 50.98%] [G loss: 0.727001]
8/8 [==============================] - 0s 4ms/step
162 [D loss: 0.690239, acc.: 54.10%] [G loss: 0.730902]
8/8 [==============================] - 0s 4ms/step
163 [D loss: 0.693901, acc.: 52.54%] [G loss: 0.726787]
8/8 [==============================] - 0s 5ms/step
164 [D loss: 0.694634, acc.: 52.54%] [G loss: 0.729176]
8/8 [==============================] - 0s 5ms/step
165 [D loss: 0.692246, acc.: 54.10%] [G loss: 0.727840]
8/8 [==============================] - 0s 5ms/step
166 [D loss: 0.692302, acc.: 53.71%] [G loss: 0.728909]
8/8 [==============================] - 0s 5ms/step
167 [D loss: 0.699684, acc.: 43.75%] [G loss: 0.723975]
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168 [D loss: 0.700621, acc.: 46.09%] [G loss: 0.721431]
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169 [D loss: 0.700892, acc.: 46.48%] [G loss: 0.719963]
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170 [D loss: 0.700278, acc.: 44.73%] [G loss: 0.714929]
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171 [D loss: 0.703165, acc.: 44.53%] [G loss: 0.717789]
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172 [D loss: 0.710811, acc.: 35.74%] [G loss: 0.713412]
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173 [D loss: 0.707699, acc.: 38.87%] [G loss: 0.710003]
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174 [D loss: 0.706842, acc.: 35.35%] [G loss: 0.705284]
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175 [D loss: 0.704661, acc.: 39.45%] [G loss: 0.705287]
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176 [D loss: 0.711575, acc.: 31.45%] [G loss: 0.704330]
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177 [D loss: 0.709558, acc.: 31.45%] [G loss: 0.702231]
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178 [D loss: 0.708349, acc.: 35.55%] [G loss: 0.699293]
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179 [D loss: 0.709632, acc.: 31.64%] [G loss: 0.701554]
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180 [D loss: 0.708595, acc.: 32.03%] [G loss: 0.702388]
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181 [D loss: 0.705338, acc.: 37.30%] [G loss: 0.704312]
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182 [D loss: 0.701985, acc.: 39.26%] [G loss: 0.707740]
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184 [D loss: 0.701864, acc.: 39.26%] [G loss: 0.705594]
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185 [D loss: 0.700069, acc.: 42.19%] [G loss: 0.708664]
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186 [D loss: 0.698082, acc.: 43.55%] [G loss: 0.708359]
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187 [D loss: 0.697577, acc.: 45.70%] [G loss: 0.708902]
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188 [D loss: 0.697632, acc.: 43.36%] [G loss: 0.709499]
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189 [D loss: 0.695020, acc.: 50.20%] [G loss: 0.708941]
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190 [D loss: 0.696464, acc.: 45.51%] [G loss: 0.708190]
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191 [D loss: 0.694437, acc.: 51.17%] [G loss: 0.708647]
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192 [D loss: 0.692684, acc.: 55.27%] [G loss: 0.709512]
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193 [D loss: 0.692504, acc.: 54.69%] [G loss: 0.710770]
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194 [D loss: 0.692548, acc.: 55.66%] [G loss: 0.710554]
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195 [D loss: 0.691792, acc.: 52.73%] [G loss: 0.710454]
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196 [D loss: 0.691114, acc.: 54.69%] [G loss: 0.712786]
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197 [D loss: 0.693957, acc.: 51.56%] [G loss: 0.711324]
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198 [D loss: 0.690635, acc.: 56.25%] [G loss: 0.710833]
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199 [D loss: 0.689719, acc.: 58.40%] [G loss: 0.714714]
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201 [D loss: 0.687945, acc.: 60.16%] [G loss: 0.711337]
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202 [D loss: 0.689594, acc.: 54.88%] [G loss: 0.712662]
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203 [D loss: 0.691620, acc.: 54.10%] [G loss: 0.710215]
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204 [D loss: 0.688259, acc.: 60.35%] [G loss: 0.710129]
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205 [D loss: 0.690365, acc.: 55.66%] [G loss: 0.707128]
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206 [D loss: 0.688185, acc.: 56.84%] [G loss: 0.704597]
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207 [D loss: 0.690970, acc.: 55.86%] [G loss: 0.700935]
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208 [D loss: 0.690915, acc.: 53.71%] [G loss: 0.699774]
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209 [D loss: 0.692103, acc.: 50.39%] [G loss: 0.698563]
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210 [D loss: 0.695136, acc.: 51.56%] [G loss: 0.696080]
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211 [D loss: 0.698078, acc.: 45.90%] [G loss: 0.692267]
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212 [D loss: 0.692896, acc.: 53.52%] [G loss: 0.691104]
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213 [D loss: 0.702653, acc.: 42.58%] [G loss: 0.685169]
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214 [D loss: 0.699227, acc.: 45.12%] [G loss: 0.686596]
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215 [D loss: 0.703749, acc.: 40.82%] [G loss: 0.678634]
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216 [D loss: 0.702798, acc.: 40.04%] [G loss: 0.680947]
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217 [D loss: 0.702831, acc.: 40.82%] [G loss: 0.680034]
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218 [D loss: 0.703749, acc.: 38.28%] [G loss: 0.676120]
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219 [D loss: 0.702994, acc.: 41.80%] [G loss: 0.676221]
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220 [D loss: 0.705212, acc.: 38.09%] [G loss: 0.677950]
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221 [D loss: 0.702089, acc.: 39.84%] [G loss: 0.678194]
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222 [D loss: 0.707684, acc.: 34.77%] [G loss: 0.677206]
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223 [D loss: 0.702227, acc.: 39.65%] [G loss: 0.680685]
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224 [D loss: 0.702770, acc.: 36.72%] [G loss: 0.680882]
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225 [D loss: 0.700233, acc.: 40.82%] [G loss: 0.681729]
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226 [D loss: 0.704140, acc.: 34.77%] [G loss: 0.684335]
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227 [D loss: 0.703272, acc.: 35.16%] [G loss: 0.685240]
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228 [D loss: 0.702217, acc.: 36.52%] [G loss: 0.686787]
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229 [D loss: 0.703290, acc.: 37.50%] [G loss: 0.688166]
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230 [D loss: 0.697899, acc.: 40.23%] [G loss: 0.689918]
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231 [D loss: 0.698765, acc.: 42.38%] [G loss: 0.694617]
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232 [D loss: 0.700847, acc.: 37.11%] [G loss: 0.695457]
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233 [D loss: 0.697555, acc.: 41.60%] [G loss: 0.697066]
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234 [D loss: 0.698058, acc.: 39.84%] [G loss: 0.699721]
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235 [D loss: 0.696333, acc.: 43.75%] [G loss: 0.702923]
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236 [D loss: 0.696218, acc.: 41.99%] [G loss: 0.704840]
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237 [D loss: 0.694840, acc.: 45.31%] [G loss: 0.708281]
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238 [D loss: 0.694342, acc.: 49.22%] [G loss: 0.708933]
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239 [D loss: 0.695352, acc.: 46.29%] [G loss: 0.710921]
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240 [D loss: 0.690971, acc.: 51.95%] [G loss: 0.714057]
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241 [D loss: 0.692813, acc.: 48.63%] [G loss: 0.716383]
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242 [D loss: 0.690662, acc.: 54.30%] [G loss: 0.716964]
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243 [D loss: 0.690908, acc.: 51.76%] [G loss: 0.718461]
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244 [D loss: 0.690208, acc.: 56.05%] [G loss: 0.721433]
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245 [D loss: 0.689799, acc.: 55.27%] [G loss: 0.721681]
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246 [D loss: 0.688198, acc.: 58.40%] [G loss: 0.723941]
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247 [D loss: 0.689005, acc.: 56.64%] [G loss: 0.725428]
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248 [D loss: 0.688447, acc.: 58.59%] [G loss: 0.724521]
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249 [D loss: 0.689593, acc.: 55.08%] [G loss: 0.723566]
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251 [D loss: 0.689400, acc.: 57.81%] [G loss: 0.722696]
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252 [D loss: 0.691081, acc.: 53.71%] [G loss: 0.720138]
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253 [D loss: 0.692196, acc.: 53.12%] [G loss: 0.723320]
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254 [D loss: 0.694522, acc.: 52.54%] [G loss: 0.719970]
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255 [D loss: 0.694769, acc.: 50.00%] [G loss: 0.717333]
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256 [D loss: 0.695514, acc.: 52.34%] [G loss: 0.715105]
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257 [D loss: 0.694966, acc.: 49.22%] [G loss: 0.715578]
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258 [D loss: 0.696449, acc.: 49.41%] [G loss: 0.708150]
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259 [D loss: 0.699314, acc.: 46.29%] [G loss: 0.707406]
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260 [D loss: 0.699032, acc.: 45.31%] [G loss: 0.707321]
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261 [D loss: 0.697606, acc.: 45.70%] [G loss: 0.705604]
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262 [D loss: 0.700097, acc.: 42.19%] [G loss: 0.702931]
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263 [D loss: 0.699469, acc.: 40.82%] [G loss: 0.700651]
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264 [D loss: 0.700848, acc.: 42.19%] [G loss: 0.702290]
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265 [D loss: 0.701165, acc.: 41.41%] [G loss: 0.702574]
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266 [D loss: 0.701848, acc.: 37.89%] [G loss: 0.698972]
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267 [D loss: 0.702765, acc.: 36.33%] [G loss: 0.699119]
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268 [D loss: 0.700756, acc.: 39.45%] [G loss: 0.699192]
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269 [D loss: 0.701299, acc.: 40.82%] [G loss: 0.699239]
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270 [D loss: 0.700815, acc.: 39.26%] [G loss: 0.700665]
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271 [D loss: 0.701746, acc.: 34.77%] [G loss: 0.702120]
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272 [D loss: 0.699362, acc.: 40.43%] [G loss: 0.700251]
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273 [D loss: 0.699390, acc.: 40.43%] [G loss: 0.700676]
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274 [D loss: 0.697333, acc.: 44.14%] [G loss: 0.700864]
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275 [D loss: 0.696840, acc.: 46.48%] [G loss: 0.701797]
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276 [D loss: 0.696552, acc.: 46.09%] [G loss: 0.702418]
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277 [D loss: 0.697193, acc.: 44.92%] [G loss: 0.703401]
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278 [D loss: 0.695606, acc.: 44.73%] [G loss: 0.702992]
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279 [D loss: 0.694601, acc.: 50.39%] [G loss: 0.704077]
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280 [D loss: 0.694114, acc.: 50.20%] [G loss: 0.704210]
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281 [D loss: 0.691683, acc.: 54.69%] [G loss: 0.703222]
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282 [D loss: 0.694418, acc.: 46.68%] [G loss: 0.704070]
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283 [D loss: 0.694706, acc.: 50.20%] [G loss: 0.706846]
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284 [D loss: 0.691781, acc.: 52.34%] [G loss: 0.705178]
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285 [D loss: 0.692221, acc.: 52.34%] [G loss: 0.706603]
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286 [D loss: 0.692185, acc.: 54.88%] [G loss: 0.705355]
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287 [D loss: 0.689347, acc.: 58.40%] [G loss: 0.710372]
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288 [D loss: 0.689301, acc.: 57.81%] [G loss: 0.710357]
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289 [D loss: 0.688489, acc.: 58.20%] [G loss: 0.708932]
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290 [D loss: 0.689570, acc.: 57.42%] [G loss: 0.707497]
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291 [D loss: 0.688501, acc.: 58.20%] [G loss: 0.707219]
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292 [D loss: 0.688514, acc.: 56.45%] [G loss: 0.706013]
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293 [D loss: 0.690075, acc.: 55.66%] [G loss: 0.706161]
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294 [D loss: 0.687982, acc.: 59.96%] [G loss: 0.699649]
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295 [D loss: 0.692952, acc.: 50.39%] [G loss: 0.700343]
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296 [D loss: 0.690585, acc.: 55.27%] [G loss: 0.702494]
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297 [D loss: 0.692447, acc.: 53.91%] [G loss: 0.694700]
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298 [D loss: 0.695736, acc.: 47.66%] [G loss: 0.692730]
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301 [D loss: 0.698737, acc.: 42.97%] [G loss: 0.685855]
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302 [D loss: 0.699657, acc.: 42.19%] [G loss: 0.681142]
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303 [D loss: 0.702067, acc.: 37.30%] [G loss: 0.681023]
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304 [D loss: 0.702573, acc.: 38.48%] [G loss: 0.681915]
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305 [D loss: 0.701874, acc.: 37.30%] [G loss: 0.676422]
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306 [D loss: 0.703133, acc.: 33.98%] [G loss: 0.678012]
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307 [D loss: 0.701409, acc.: 38.09%] [G loss: 0.677503]
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308 [D loss: 0.703514, acc.: 37.89%] [G loss: 0.678878]
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309 [D loss: 0.703209, acc.: 36.91%] [G loss: 0.679040]
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310 [D loss: 0.702485, acc.: 35.16%] [G loss: 0.682094]
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311 [D loss: 0.702728, acc.: 35.94%] [G loss: 0.683848]
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312 [D loss: 0.700146, acc.: 37.70%] [G loss: 0.685921]
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313 [D loss: 0.700748, acc.: 39.26%] [G loss: 0.687656]
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314 [D loss: 0.700115, acc.: 38.67%] [G loss: 0.688360]
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315 [D loss: 0.703023, acc.: 33.79%] [G loss: 0.691497]
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316 [D loss: 0.698685, acc.: 42.77%] [G loss: 0.695129]
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317 [D loss: 0.698413, acc.: 41.41%] [G loss: 0.694890]
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318 [D loss: 0.697025, acc.: 43.16%] [G loss: 0.694032]
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319 [D loss: 0.698185, acc.: 40.62%] [G loss: 0.697857]
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320 [D loss: 0.698583, acc.: 40.62%] [G loss: 0.699955]
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321 [D loss: 0.697057, acc.: 44.34%] [G loss: 0.699859]
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322 [D loss: 0.696185, acc.: 45.90%] [G loss: 0.701385]
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323 [D loss: 0.693734, acc.: 50.78%] [G loss: 0.704949]
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324 [D loss: 0.694560, acc.: 47.46%] [G loss: 0.708389]
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325 [D loss: 0.693904, acc.: 47.85%] [G loss: 0.707600]
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326 [D loss: 0.694554, acc.: 49.61%] [G loss: 0.707699]
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328 [D loss: 0.694050, acc.: 49.02%] [G loss: 0.709925]
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329 [D loss: 0.693600, acc.: 48.05%] [G loss: 0.710129]
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330 [D loss: 0.693931, acc.: 49.61%] [G loss: 0.709176]
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331 [D loss: 0.692646, acc.: 50.20%] [G loss: 0.712243]
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332 [D loss: 0.694764, acc.: 47.07%] [G loss: 0.712948]
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333 [D loss: 0.693310, acc.: 50.39%] [G loss: 0.713580]
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334 [D loss: 0.693101, acc.: 51.37%] [G loss: 0.711049]
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335 [D loss: 0.694504, acc.: 51.17%] [G loss: 0.709769]
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336 [D loss: 0.694113, acc.: 48.24%] [G loss: 0.711092]
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337 [D loss: 0.693658, acc.: 51.56%] [G loss: 0.709036]
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338 [D loss: 0.694102, acc.: 51.37%] [G loss: 0.710286]
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339 [D loss: 0.694934, acc.: 51.37%] [G loss: 0.709439]
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340 [D loss: 0.695592, acc.: 49.22%] [G loss: 0.708011]
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341 [D loss: 0.695408, acc.: 47.07%] [G loss: 0.709414]
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342 [D loss: 0.696442, acc.: 47.27%] [G loss: 0.708016]
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343 [D loss: 0.694507, acc.: 50.00%] [G loss: 0.707083]
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344 [D loss: 0.695645, acc.: 47.85%] [G loss: 0.709944]
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345 [D loss: 0.696947, acc.: 47.46%] [G loss: 0.708391]
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346 [D loss: 0.696830, acc.: 46.68%] [G loss: 0.710427]
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347 [D loss: 0.695344, acc.: 47.07%] [G loss: 0.708840]
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348 [D loss: 0.695559, acc.: 46.88%] [G loss: 0.709381]
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349 [D loss: 0.694825, acc.: 50.00%] [G loss: 0.709758]
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350 [D loss: 0.691127, acc.: 54.69%] [G loss: 0.706364]
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351 [D loss: 0.693686, acc.: 50.39%] [G loss: 0.707898]
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352 [D loss: 0.694193, acc.: 49.61%] [G loss: 0.706842]
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353 [D loss: 0.696547, acc.: 45.70%] [G loss: 0.706994]
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354 [D loss: 0.693873, acc.: 49.61%] [G loss: 0.706455]
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355 [D loss: 0.696310, acc.: 44.14%] [G loss: 0.707752]
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356 [D loss: 0.694409, acc.: 47.66%] [G loss: 0.703414]
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357 [D loss: 0.697701, acc.: 43.16%] [G loss: 0.702209]
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358 [D loss: 0.696934, acc.: 42.97%] [G loss: 0.701191]
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359 [D loss: 0.696041, acc.: 45.51%] [G loss: 0.701491]
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360 [D loss: 0.698746, acc.: 42.97%] [G loss: 0.697397]
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361 [D loss: 0.697227, acc.: 44.53%] [G loss: 0.697138]
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362 [D loss: 0.698620, acc.: 39.65%] [G loss: 0.698233]
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363 [D loss: 0.697585, acc.: 42.19%] [G loss: 0.694199]
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364 [D loss: 0.699198, acc.: 41.21%] [G loss: 0.695987]
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365 [D loss: 0.700529, acc.: 39.45%] [G loss: 0.691088]
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366 [D loss: 0.701077, acc.: 38.67%] [G loss: 0.692280]
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367 [D loss: 0.701258, acc.: 36.72%] [G loss: 0.698128]
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368 [D loss: 0.699712, acc.: 38.28%] [G loss: 0.694056]
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369 [D loss: 0.699255, acc.: 41.60%] [G loss: 0.695933]
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370 [D loss: 0.699712, acc.: 40.43%] [G loss: 0.698088]
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371 [D loss: 0.699854, acc.: 36.33%] [G loss: 0.699467]
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372 [D loss: 0.698810, acc.: 39.65%] [G loss: 0.701766]
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373 [D loss: 0.699564, acc.: 39.26%] [G loss: 0.704687]
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374 [D loss: 0.697107, acc.: 44.73%] [G loss: 0.704672]
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375 [D loss: 0.697324, acc.: 43.75%] [G loss: 0.707324]
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376 [D loss: 0.696759, acc.: 43.75%] [G loss: 0.706980]
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377 [D loss: 0.695320, acc.: 45.70%] [G loss: 0.710305]
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378 [D loss: 0.694115, acc.: 47.66%] [G loss: 0.713497]
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379 [D loss: 0.693889, acc.: 48.24%] [G loss: 0.714645]
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380 [D loss: 0.692621, acc.: 48.24%] [G loss: 0.718405]
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381 [D loss: 0.691801, acc.: 51.37%] [G loss: 0.719006]
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382 [D loss: 0.692006, acc.: 50.78%] [G loss: 0.719160]
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383 [D loss: 0.691373, acc.: 50.39%] [G loss: 0.725182]
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384 [D loss: 0.692241, acc.: 49.41%] [G loss: 0.718173]
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385 [D loss: 0.691141, acc.: 50.59%] [G loss: 0.724150]
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386 [D loss: 0.689865, acc.: 50.59%] [G loss: 0.720778]
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387 [D loss: 0.691889, acc.: 48.44%] [G loss: 0.724765]
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388 [D loss: 0.692289, acc.: 51.37%] [G loss: 0.721553]
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389 [D loss: 0.693388, acc.: 48.05%] [G loss: 0.721427]
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390 [D loss: 0.692693, acc.: 52.34%] [G loss: 0.720519]
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391 [D loss: 0.692544, acc.: 53.32%] [G loss: 0.719548]
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392 [D loss: 0.694241, acc.: 49.80%] [G loss: 0.715964]
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393 [D loss: 0.695214, acc.: 45.70%] [G loss: 0.716312]
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394 [D loss: 0.695549, acc.: 49.02%] [G loss: 0.714130]
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395 [D loss: 0.698347, acc.: 43.95%] [G loss: 0.711105]
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396 [D loss: 0.697827, acc.: 43.75%] [G loss: 0.707973]
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397 [D loss: 0.699734, acc.: 38.28%] [G loss: 0.710043]
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398 [D loss: 0.698723, acc.: 42.77%] [G loss: 0.708546]
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399 [D loss: 0.697729, acc.: 40.04%] [G loss: 0.709678]
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401 [D loss: 0.698804, acc.: 43.75%] [G loss: 0.707429]
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402 [D loss: 0.697992, acc.: 42.38%] [G loss: 0.707029]
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403 [D loss: 0.699125, acc.: 42.97%] [G loss: 0.705033]
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404 [D loss: 0.698073, acc.: 41.21%] [G loss: 0.705011]
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405 [D loss: 0.698728, acc.: 38.48%] [G loss: 0.706213]
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406 [D loss: 0.697057, acc.: 43.36%] [G loss: 0.707590]
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407 [D loss: 0.696978, acc.: 44.34%] [G loss: 0.707668]
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408 [D loss: 0.695907, acc.: 45.90%] [G loss: 0.707643]
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409 [D loss: 0.696574, acc.: 44.92%] [G loss: 0.707128]
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410 [D loss: 0.695687, acc.: 45.12%] [G loss: 0.708978]
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411 [D loss: 0.696130, acc.: 42.77%] [G loss: 0.708906]
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412 [D loss: 0.693199, acc.: 50.39%] [G loss: 0.710656]
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413 [D loss: 0.693211, acc.: 53.52%] [G loss: 0.710154]
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414 [D loss: 0.693439, acc.: 50.39%] [G loss: 0.709427]
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415 [D loss: 0.692535, acc.: 51.76%] [G loss: 0.710790]
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416 [D loss: 0.692719, acc.: 49.61%] [G loss: 0.712650]
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417 [D loss: 0.692363, acc.: 50.20%] [G loss: 0.710541]
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418 [D loss: 0.691867, acc.: 51.56%] [G loss: 0.710851]
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419 [D loss: 0.691351, acc.: 54.10%] [G loss: 0.711276]
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420 [D loss: 0.692212, acc.: 50.20%] [G loss: 0.712397]
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421 [D loss: 0.691928, acc.: 53.71%] [G loss: 0.710969]
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422 [D loss: 0.692244, acc.: 49.41%] [G loss: 0.710644]
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423 [D loss: 0.692035, acc.: 53.32%] [G loss: 0.710678]
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424 [D loss: 0.690980, acc.: 53.91%] [G loss: 0.710933]
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425 [D loss: 0.692484, acc.: 50.98%] [G loss: 0.710883]
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426 [D loss: 0.693656, acc.: 46.88%] [G loss: 0.709780]
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427 [D loss: 0.692720, acc.: 48.05%] [G loss: 0.709386]
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428 [D loss: 0.693822, acc.: 49.02%] [G loss: 0.708330]
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429 [D loss: 0.694529, acc.: 49.61%] [G loss: 0.710239]
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430 [D loss: 0.693106, acc.: 50.59%] [G loss: 0.709192]
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431 [D loss: 0.693226, acc.: 50.78%] [G loss: 0.707338]
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432 [D loss: 0.694892, acc.: 45.31%] [G loss: 0.706602]
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433 [D loss: 0.696815, acc.: 44.14%] [G loss: 0.705369]
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434 [D loss: 0.695198, acc.: 46.88%] [G loss: 0.702693]
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435 [D loss: 0.695461, acc.: 48.63%] [G loss: 0.702025]
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436 [D loss: 0.698235, acc.: 42.38%] [G loss: 0.702182]
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437 [D loss: 0.698811, acc.: 43.16%] [G loss: 0.702024]
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438 [D loss: 0.697150, acc.: 43.95%] [G loss: 0.700823]
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439 [D loss: 0.700186, acc.: 36.52%] [G loss: 0.700679]
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440 [D loss: 0.699575, acc.: 39.45%] [G loss: 0.702014]
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441 [D loss: 0.697585, acc.: 42.38%] [G loss: 0.699684]
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442 [D loss: 0.699176, acc.: 41.60%] [G loss: 0.697852]
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443 [D loss: 0.700630, acc.: 37.11%] [G loss: 0.699273]
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444 [D loss: 0.698858, acc.: 39.65%] [G loss: 0.697493]
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445 [D loss: 0.698740, acc.: 42.58%] [G loss: 0.698996]
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446 [D loss: 0.700136, acc.: 36.13%] [G loss: 0.699601]
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447 [D loss: 0.698267, acc.: 42.19%] [G loss: 0.699085]
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448 [D loss: 0.698656, acc.: 38.48%] [G loss: 0.699236]
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449 [D loss: 0.700253, acc.: 37.11%] [G loss: 0.699622]
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450 [D loss: 0.700520, acc.: 37.89%] [G loss: 0.700337]
1/1 [==============================] - 0s 19ms/step
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451 [D loss: 0.698963, acc.: 39.26%] [G loss: 0.699950]
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452 [D loss: 0.698244, acc.: 39.26%] [G loss: 0.700285]
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453 [D loss: 0.696406, acc.: 44.53%] [G loss: 0.701866]
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454 [D loss: 0.696983, acc.: 42.58%] [G loss: 0.700696]
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455 [D loss: 0.696528, acc.: 40.82%] [G loss: 0.702463]
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456 [D loss: 0.696331, acc.: 42.77%] [G loss: 0.701222]
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457 [D loss: 0.696364, acc.: 41.80%] [G loss: 0.702259]
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458 [D loss: 0.695800, acc.: 44.34%] [G loss: 0.701398]
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459 [D loss: 0.694382, acc.: 48.83%] [G loss: 0.704432]
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460 [D loss: 0.694290, acc.: 47.07%] [G loss: 0.704398]
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461 [D loss: 0.695008, acc.: 45.12%] [G loss: 0.705000]
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462 [D loss: 0.692795, acc.: 49.80%] [G loss: 0.705414]
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463 [D loss: 0.693449, acc.: 49.80%] [G loss: 0.706666]
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464 [D loss: 0.693898, acc.: 48.24%] [G loss: 0.706469]
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465 [D loss: 0.693108, acc.: 50.98%] [G loss: 0.707589]
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466 [D loss: 0.692225, acc.: 51.17%] [G loss: 0.707610]
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467 [D loss: 0.691215, acc.: 53.91%] [G loss: 0.706023]
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468 [D loss: 0.692837, acc.: 50.39%] [G loss: 0.707496]
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469 [D loss: 0.692530, acc.: 52.15%] [G loss: 0.707986]
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470 [D loss: 0.692550, acc.: 51.37%] [G loss: 0.707931]
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471 [D loss: 0.691686, acc.: 51.17%] [G loss: 0.708416]
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472 [D loss: 0.691886, acc.: 52.34%] [G loss: 0.708548]
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473 [D loss: 0.691201, acc.: 53.91%] [G loss: 0.708074]
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474 [D loss: 0.691527, acc.: 54.10%] [G loss: 0.706913]
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475 [D loss: 0.692946, acc.: 52.15%] [G loss: 0.707818]
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476 [D loss: 0.692395, acc.: 49.41%] [G loss: 0.707345]
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477 [D loss: 0.691328, acc.: 54.49%] [G loss: 0.705815]
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478 [D loss: 0.693957, acc.: 48.63%] [G loss: 0.706161]
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479 [D loss: 0.694822, acc.: 46.88%] [G loss: 0.705985]
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480 [D loss: 0.694999, acc.: 47.46%] [G loss: 0.703619]
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481 [D loss: 0.695402, acc.: 44.14%] [G loss: 0.703052]
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482 [D loss: 0.696139, acc.: 45.31%] [G loss: 0.702844]
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483 [D loss: 0.696257, acc.: 43.36%] [G loss: 0.702677]
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484 [D loss: 0.695499, acc.: 48.44%] [G loss: 0.702749]
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485 [D loss: 0.696918, acc.: 40.04%] [G loss: 0.699888]
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486 [D loss: 0.697114, acc.: 43.16%] [G loss: 0.701015]
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487 [D loss: 0.697804, acc.: 39.06%] [G loss: 0.701054]
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488 [D loss: 0.696735, acc.: 44.92%] [G loss: 0.701577]
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489 [D loss: 0.696222, acc.: 44.73%] [G loss: 0.701138]
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490 [D loss: 0.696154, acc.: 44.14%] [G loss: 0.701602]
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491 [D loss: 0.698938, acc.: 39.84%] [G loss: 0.702408]
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492 [D loss: 0.696187, acc.: 46.09%] [G loss: 0.702756]
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493 [D loss: 0.697568, acc.: 43.75%] [G loss: 0.702932]
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494 [D loss: 0.697806, acc.: 41.80%] [G loss: 0.702374]
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495 [D loss: 0.696949, acc.: 43.36%] [G loss: 0.705306]
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496 [D loss: 0.697131, acc.: 41.21%] [G loss: 0.705096]
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497 [D loss: 0.697102, acc.: 41.99%] [G loss: 0.707111]
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498 [D loss: 0.697701, acc.: 42.19%] [G loss: 0.705598]
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499 [D loss: 0.697838, acc.: 44.34%] [G loss: 0.709256]
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1/1 [==============================] - 0s 23ms/step
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501 [D loss: 0.697210, acc.: 41.60%] [G loss: 0.709887]
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502 [D loss: 0.697146, acc.: 45.51%] [G loss: 0.709279]
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503 [D loss: 0.696276, acc.: 47.66%] [G loss: 0.711613]
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504 [D loss: 0.696196, acc.: 46.88%] [G loss: 0.711469]
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505 [D loss: 0.696534, acc.: 45.31%] [G loss: 0.713125]
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506 [D loss: 0.697550, acc.: 43.75%] [G loss: 0.713520]
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507 [D loss: 0.696988, acc.: 45.12%] [G loss: 0.713237]
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508 [D loss: 0.695756, acc.: 44.73%] [G loss: 0.715137]
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509 [D loss: 0.696165, acc.: 44.53%] [G loss: 0.716000]
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510 [D loss: 0.695910, acc.: 48.44%] [G loss: 0.714002]
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511 [D loss: 0.695952, acc.: 48.83%] [G loss: 0.717094]
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512 [D loss: 0.696476, acc.: 47.46%] [G loss: 0.715843]
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513 [D loss: 0.696252, acc.: 46.88%] [G loss: 0.717396]
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514 [D loss: 0.695312, acc.: 49.22%] [G loss: 0.715439]
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515 [D loss: 0.696150, acc.: 48.24%] [G loss: 0.716189]
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516 [D loss: 0.696033, acc.: 48.63%] [G loss: 0.717467]
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517 [D loss: 0.697103, acc.: 47.85%] [G loss: 0.717533]
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518 [D loss: 0.696183, acc.: 48.44%] [G loss: 0.717870]
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519 [D loss: 0.695177, acc.: 50.20%] [G loss: 0.718620]
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520 [D loss: 0.695856, acc.: 48.83%] [G loss: 0.717274]
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521 [D loss: 0.695513, acc.: 49.22%] [G loss: 0.719269]
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522 [D loss: 0.696561, acc.: 48.44%] [G loss: 0.718202]
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523 [D loss: 0.694926, acc.: 50.20%] [G loss: 0.718057]
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524 [D loss: 0.697067, acc.: 48.44%] [G loss: 0.718875]
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525 [D loss: 0.696423, acc.: 48.44%] [G loss: 0.719604]
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526 [D loss: 0.694955, acc.: 50.20%] [G loss: 0.718599]
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527 [D loss: 0.695801, acc.: 49.22%] [G loss: 0.718078]
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528 [D loss: 0.695180, acc.: 50.20%] [G loss: 0.717325]
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529 [D loss: 0.696524, acc.: 48.05%] [G loss: 0.716289]
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530 [D loss: 0.696471, acc.: 49.41%] [G loss: 0.716682]
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531 [D loss: 0.695487, acc.: 50.00%] [G loss: 0.716631]
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532 [D loss: 0.696002, acc.: 47.85%] [G loss: 0.715659]
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533 [D loss: 0.696449, acc.: 47.46%] [G loss: 0.714170]
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534 [D loss: 0.695374, acc.: 47.46%] [G loss: 0.716255]
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535 [D loss: 0.695501, acc.: 49.41%] [G loss: 0.715596]
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536 [D loss: 0.695568, acc.: 50.39%] [G loss: 0.714994]
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537 [D loss: 0.695257, acc.: 47.85%] [G loss: 0.715638]
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538 [D loss: 0.694005, acc.: 51.37%] [G loss: 0.714032]
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539 [D loss: 0.695227, acc.: 47.27%] [G loss: 0.713480]
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540 [D loss: 0.693600, acc.: 48.05%] [G loss: 0.711677]
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541 [D loss: 0.694307, acc.: 50.20%] [G loss: 0.713238]
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542 [D loss: 0.693884, acc.: 48.24%] [G loss: 0.713767]
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543 [D loss: 0.694966, acc.: 48.83%] [G loss: 0.713387]
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544 [D loss: 0.694896, acc.: 49.41%] [G loss: 0.711846]
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545 [D loss: 0.693820, acc.: 49.02%] [G loss: 0.710087]
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546 [D loss: 0.694931, acc.: 50.59%] [G loss: 0.710716]
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547 [D loss: 0.695424, acc.: 46.48%] [G loss: 0.709749]
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548 [D loss: 0.695069, acc.: 49.61%] [G loss: 0.709850]
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549 [D loss: 0.694885, acc.: 46.68%] [G loss: 0.708624]
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550 [D loss: 0.695796, acc.: 45.51%] [G loss: 0.707120]
1/1 [==============================] - 0s 18ms/step
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551 [D loss: 0.695651, acc.: 47.66%] [G loss: 0.707463]
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552 [D loss: 0.696265, acc.: 42.38%] [G loss: 0.708670]
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553 [D loss: 0.695087, acc.: 46.88%] [G loss: 0.705695]
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554 [D loss: 0.695681, acc.: 45.12%] [G loss: 0.706189]
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555 [D loss: 0.697046, acc.: 43.95%] [G loss: 0.705947]
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556 [D loss: 0.695725, acc.: 44.53%] [G loss: 0.704493]
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557 [D loss: 0.696576, acc.: 44.92%] [G loss: 0.705645]
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558 [D loss: 0.696106, acc.: 46.29%] [G loss: 0.705128]
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559 [D loss: 0.696412, acc.: 43.36%] [G loss: 0.703618]
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560 [D loss: 0.696250, acc.: 44.53%] [G loss: 0.704681]
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561 [D loss: 0.697210, acc.: 43.36%] [G loss: 0.703737]
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562 [D loss: 0.696678, acc.: 41.21%] [G loss: 0.703351]
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563 [D loss: 0.696916, acc.: 41.80%] [G loss: 0.703301]
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564 [D loss: 0.697004, acc.: 40.62%] [G loss: 0.703241]
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565 [D loss: 0.696455, acc.: 44.14%] [G loss: 0.703559]
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566 [D loss: 0.696350, acc.: 42.97%] [G loss: 0.704087]
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567 [D loss: 0.695706, acc.: 43.95%] [G loss: 0.704301]
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568 [D loss: 0.695443, acc.: 44.14%] [G loss: 0.704045]
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569 [D loss: 0.696144, acc.: 42.58%] [G loss: 0.704843]
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570 [D loss: 0.695733, acc.: 42.58%] [G loss: 0.704416]
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571 [D loss: 0.696048, acc.: 42.97%] [G loss: 0.705626]
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572 [D loss: 0.695411, acc.: 43.95%] [G loss: 0.704915]
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573 [D loss: 0.695340, acc.: 46.29%] [G loss: 0.705171]
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574 [D loss: 0.695037, acc.: 48.05%] [G loss: 0.705523]
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575 [D loss: 0.694427, acc.: 49.61%] [G loss: 0.706419]
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576 [D loss: 0.694509, acc.: 45.12%] [G loss: 0.706309]
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577 [D loss: 0.694808, acc.: 46.68%] [G loss: 0.707219]
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578 [D loss: 0.694372, acc.: 47.07%] [G loss: 0.708865]
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579 [D loss: 0.693064, acc.: 50.20%] [G loss: 0.709492]
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580 [D loss: 0.693868, acc.: 49.61%] [G loss: 0.709069]
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581 [D loss: 0.692752, acc.: 51.95%] [G loss: 0.710358]
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582 [D loss: 0.693298, acc.: 53.32%] [G loss: 0.709980]
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583 [D loss: 0.692701, acc.: 50.00%] [G loss: 0.711231]
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584 [D loss: 0.692502, acc.: 53.91%] [G loss: 0.711912]
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585 [D loss: 0.692803, acc.: 49.41%] [G loss: 0.710995]
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586 [D loss: 0.691434, acc.: 54.49%] [G loss: 0.711528]
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587 [D loss: 0.692834, acc.: 51.95%] [G loss: 0.711635]
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588 [D loss: 0.692068, acc.: 52.93%] [G loss: 0.713125]
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589 [D loss: 0.691693, acc.: 53.71%] [G loss: 0.712685]
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590 [D loss: 0.692524, acc.: 53.32%] [G loss: 0.713914]
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591 [D loss: 0.691897, acc.: 53.52%] [G loss: 0.714333]
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592 [D loss: 0.692685, acc.: 51.95%] [G loss: 0.712928]
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593 [D loss: 0.692828, acc.: 52.93%] [G loss: 0.712884]
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594 [D loss: 0.691983, acc.: 52.54%] [G loss: 0.712273]
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595 [D loss: 0.692836, acc.: 49.61%] [G loss: 0.711109]
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596 [D loss: 0.692872, acc.: 50.20%] [G loss: 0.711503]
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597 [D loss: 0.693275, acc.: 51.95%] [G loss: 0.710199]
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598 [D loss: 0.693213, acc.: 49.41%] [G loss: 0.711552]
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599 [D loss: 0.694760, acc.: 48.83%] [G loss: 0.708771]
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600 [D loss: 0.694697, acc.: 49.22%] [G loss: 0.707728]
1/1 [==============================] - 0s 17ms/step
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601 [D loss: 0.694083, acc.: 47.85%] [G loss: 0.709223]
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602 [D loss: 0.694721, acc.: 47.66%] [G loss: 0.707398]
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603 [D loss: 0.694988, acc.: 44.14%] [G loss: 0.708044]
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604 [D loss: 0.694938, acc.: 45.31%] [G loss: 0.706482]
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605 [D loss: 0.695632, acc.: 45.31%] [G loss: 0.707087]
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606 [D loss: 0.697489, acc.: 42.38%] [G loss: 0.706360]
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607 [D loss: 0.695894, acc.: 43.75%] [G loss: 0.705505]
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608 [D loss: 0.697079, acc.: 41.80%] [G loss: 0.704667]
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609 [D loss: 0.696172, acc.: 44.92%] [G loss: 0.704656]
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610 [D loss: 0.696472, acc.: 44.14%] [G loss: 0.705160]
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611 [D loss: 0.696899, acc.: 44.34%] [G loss: 0.704168]
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612 [D loss: 0.698636, acc.: 36.72%] [G loss: 0.703074]
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613 [D loss: 0.696628, acc.: 43.16%] [G loss: 0.703677]
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614 [D loss: 0.696413, acc.: 42.97%] [G loss: 0.704232]
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615 [D loss: 0.696609, acc.: 42.58%] [G loss: 0.702528]
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616 [D loss: 0.697007, acc.: 41.41%] [G loss: 0.704156]
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617 [D loss: 0.696135, acc.: 44.14%] [G loss: 0.703509]
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618 [D loss: 0.696838, acc.: 41.41%] [G loss: 0.703296]
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619 [D loss: 0.696201, acc.: 43.36%] [G loss: 0.703614]
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620 [D loss: 0.696601, acc.: 42.19%] [G loss: 0.704610]
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621 [D loss: 0.696429, acc.: 40.82%] [G loss: 0.703596]
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622 [D loss: 0.695260, acc.: 44.92%] [G loss: 0.703696]
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623 [D loss: 0.694978, acc.: 46.68%] [G loss: 0.704087]
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624 [D loss: 0.694112, acc.: 48.83%] [G loss: 0.706059]
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625 [D loss: 0.695333, acc.: 44.53%] [G loss: 0.704158]
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626 [D loss: 0.695385, acc.: 42.77%] [G loss: 0.703889]
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627 [D loss: 0.695493, acc.: 43.16%] [G loss: 0.704663]
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628 [D loss: 0.694029, acc.: 44.92%] [G loss: 0.705278]
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629 [D loss: 0.694749, acc.: 46.29%] [G loss: 0.705811]
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630 [D loss: 0.694475, acc.: 44.92%] [G loss: 0.704685]
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631 [D loss: 0.694922, acc.: 43.55%] [G loss: 0.703600]
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632 [D loss: 0.693301, acc.: 48.44%] [G loss: 0.704473]
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633 [D loss: 0.693360, acc.: 46.88%] [G loss: 0.704552]
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634 [D loss: 0.693517, acc.: 47.27%] [G loss: 0.703552]
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635 [D loss: 0.693484, acc.: 47.07%] [G loss: 0.704739]
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636 [D loss: 0.693081, acc.: 49.22%] [G loss: 0.704211]
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637 [D loss: 0.693358, acc.: 47.27%] [G loss: 0.705288]
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638 [D loss: 0.692565, acc.: 50.20%] [G loss: 0.705580]
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639 [D loss: 0.692959, acc.: 50.78%] [G loss: 0.704213]
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640 [D loss: 0.691758, acc.: 53.71%] [G loss: 0.704806]
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641 [D loss: 0.692230, acc.: 52.73%] [G loss: 0.703842]
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642 [D loss: 0.693280, acc.: 50.20%] [G loss: 0.703413]
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643 [D loss: 0.692743, acc.: 51.56%] [G loss: 0.704140]
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644 [D loss: 0.691952, acc.: 51.17%] [G loss: 0.702651]
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645 [D loss: 0.693081, acc.: 48.63%] [G loss: 0.701649]
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646 [D loss: 0.693860, acc.: 45.51%] [G loss: 0.703604]
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647 [D loss: 0.692657, acc.: 50.98%] [G loss: 0.703125]
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648 [D loss: 0.692839, acc.: 49.61%] [G loss: 0.701696]
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649 [D loss: 0.693571, acc.: 45.31%] [G loss: 0.701529]
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650 [D loss: 0.694118, acc.: 48.05%] [G loss: 0.702370]
1/1 [==============================] - 0s 18ms/step
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651 [D loss: 0.693488, acc.: 49.61%] [G loss: 0.702691]
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652 [D loss: 0.694103, acc.: 47.07%] [G loss: 0.701352]
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653 [D loss: 0.694266, acc.: 46.09%] [G loss: 0.702692]
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654 [D loss: 0.693991, acc.: 48.44%] [G loss: 0.702615]
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655 [D loss: 0.694159, acc.: 46.88%] [G loss: 0.701590]
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656 [D loss: 0.694323, acc.: 49.22%] [G loss: 0.701805]
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657 [D loss: 0.694517, acc.: 49.22%] [G loss: 0.701031]
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658 [D loss: 0.695053, acc.: 48.63%] [G loss: 0.700752]
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659 [D loss: 0.694591, acc.: 47.27%] [G loss: 0.701609]
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660 [D loss: 0.695808, acc.: 43.16%] [G loss: 0.699864]
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661 [D loss: 0.695373, acc.: 44.73%] [G loss: 0.700512]
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662 [D loss: 0.694567, acc.: 44.92%] [G loss: 0.700088]
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663 [D loss: 0.694737, acc.: 46.68%] [G loss: 0.701834]
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664 [D loss: 0.695137, acc.: 43.55%] [G loss: 0.701619]
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665 [D loss: 0.696014, acc.: 41.41%] [G loss: 0.702023]
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666 [D loss: 0.695742, acc.: 41.99%] [G loss: 0.701851]
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667 [D loss: 0.694521, acc.: 48.44%] [G loss: 0.700679]
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668 [D loss: 0.695691, acc.: 43.16%] [G loss: 0.701942]
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669 [D loss: 0.695397, acc.: 44.34%] [G loss: 0.701290]
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670 [D loss: 0.695476, acc.: 43.75%] [G loss: 0.702918]
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671 [D loss: 0.695117, acc.: 42.38%] [G loss: 0.701640]
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672 [D loss: 0.695221, acc.: 43.95%] [G loss: 0.702237]
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673 [D loss: 0.695014, acc.: 45.31%] [G loss: 0.702047]
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674 [D loss: 0.695233, acc.: 42.58%] [G loss: 0.702961]
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675 [D loss: 0.695922, acc.: 42.58%] [G loss: 0.700616]
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676 [D loss: 0.695200, acc.: 44.92%] [G loss: 0.702827]
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677 [D loss: 0.694952, acc.: 45.90%] [G loss: 0.703148]
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678 [D loss: 0.695544, acc.: 44.14%] [G loss: 0.701829]
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679 [D loss: 0.695625, acc.: 40.23%] [G loss: 0.702081]
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680 [D loss: 0.696433, acc.: 41.02%] [G loss: 0.701878]
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681 [D loss: 0.695391, acc.: 43.75%] [G loss: 0.701426]
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682 [D loss: 0.694968, acc.: 45.51%] [G loss: 0.701625]
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683 [D loss: 0.696132, acc.: 40.82%] [G loss: 0.703237]
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684 [D loss: 0.695659, acc.: 43.55%] [G loss: 0.702079]
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685 [D loss: 0.696151, acc.: 42.58%] [G loss: 0.700714]
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686 [D loss: 0.695857, acc.: 45.12%] [G loss: 0.704087]
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687 [D loss: 0.695279, acc.: 43.36%] [G loss: 0.702735]
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688 [D loss: 0.695454, acc.: 42.77%] [G loss: 0.703134]
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689 [D loss: 0.694339, acc.: 49.80%] [G loss: 0.703002]
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690 [D loss: 0.695890, acc.: 44.34%] [G loss: 0.704305]
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691 [D loss: 0.695231, acc.: 47.66%] [G loss: 0.704511]
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692 [D loss: 0.695194, acc.: 44.53%] [G loss: 0.704730]
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693 [D loss: 0.695136, acc.: 45.90%] [G loss: 0.704798]
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694 [D loss: 0.694748, acc.: 46.29%] [G loss: 0.705479]
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695 [D loss: 0.695358, acc.: 43.75%] [G loss: 0.705553]
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696 [D loss: 0.694882, acc.: 45.90%] [G loss: 0.705659]
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697 [D loss: 0.694534, acc.: 48.44%] [G loss: 0.705963]
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698 [D loss: 0.694444, acc.: 49.22%] [G loss: 0.705779]
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699 [D loss: 0.693524, acc.: 47.85%] [G loss: 0.705130]
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700 [D loss: 0.693421, acc.: 49.80%] [G loss: 0.705924]
1/1 [==============================] - 0s 19ms/step
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701 [D loss: 0.694204, acc.: 48.63%] [G loss: 0.706633]
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702 [D loss: 0.693964, acc.: 47.66%] [G loss: 0.708120]
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703 [D loss: 0.693414, acc.: 49.22%] [G loss: 0.706916]
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704 [D loss: 0.694019, acc.: 50.00%] [G loss: 0.706836]
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705 [D loss: 0.694014, acc.: 48.24%] [G loss: 0.707714]
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706 [D loss: 0.693899, acc.: 50.00%] [G loss: 0.705911]
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707 [D loss: 0.693680, acc.: 46.68%] [G loss: 0.707297]
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708 [D loss: 0.694427, acc.: 46.48%] [G loss: 0.705806]
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709 [D loss: 0.694128, acc.: 49.61%] [G loss: 0.705531]
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710 [D loss: 0.694508, acc.: 45.70%] [G loss: 0.705886]
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711 [D loss: 0.694491, acc.: 45.12%] [G loss: 0.706356]
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712 [D loss: 0.694377, acc.: 47.46%] [G loss: 0.705523]
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713 [D loss: 0.694447, acc.: 47.27%] [G loss: 0.704346]
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714 [D loss: 0.694791, acc.: 44.34%] [G loss: 0.706298]
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715 [D loss: 0.695748, acc.: 43.95%] [G loss: 0.705630]
8/8 [==============================] - 0s 4ms/step
716 [D loss: 0.694846, acc.: 46.88%] [G loss: 0.705999]
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717 [D loss: 0.695213, acc.: 45.12%] [G loss: 0.704627]
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718 [D loss: 0.695496, acc.: 43.55%] [G loss: 0.704499]
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719 [D loss: 0.694964, acc.: 45.51%] [G loss: 0.704781]
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720 [D loss: 0.695188, acc.: 44.14%] [G loss: 0.704164]
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721 [D loss: 0.694953, acc.: 47.27%] [G loss: 0.702982]
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722 [D loss: 0.695703, acc.: 45.70%] [G loss: 0.704500]
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723 [D loss: 0.694188, acc.: 49.02%] [G loss: 0.702699]
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724 [D loss: 0.696103, acc.: 41.60%] [G loss: 0.703573]
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725 [D loss: 0.695706, acc.: 45.31%] [G loss: 0.703599]
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726 [D loss: 0.695709, acc.: 43.95%] [G loss: 0.704065]
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727 [D loss: 0.695888, acc.: 43.95%] [G loss: 0.704141]
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728 [D loss: 0.695718, acc.: 43.55%] [G loss: 0.704226]
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729 [D loss: 0.694618, acc.: 47.66%] [G loss: 0.705464]
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730 [D loss: 0.695506, acc.: 45.12%] [G loss: 0.704909]
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731 [D loss: 0.695320, acc.: 44.34%] [G loss: 0.704741]
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732 [D loss: 0.694737, acc.: 48.24%] [G loss: 0.706104]
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733 [D loss: 0.694871, acc.: 47.27%] [G loss: 0.705715]
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734 [D loss: 0.694802, acc.: 45.90%] [G loss: 0.705893]
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735 [D loss: 0.695096, acc.: 45.90%] [G loss: 0.706095]
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736 [D loss: 0.694415, acc.: 47.66%] [G loss: 0.707166]
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737 [D loss: 0.694249, acc.: 48.05%] [G loss: 0.706917]
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738 [D loss: 0.694693, acc.: 47.85%] [G loss: 0.707630]
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739 [D loss: 0.694152, acc.: 48.63%] [G loss: 0.707313]
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740 [D loss: 0.693774, acc.: 47.27%] [G loss: 0.707978]
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741 [D loss: 0.693612, acc.: 49.22%] [G loss: 0.708554]
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742 [D loss: 0.693511, acc.: 50.39%] [G loss: 0.707186]
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743 [D loss: 0.693619, acc.: 48.44%] [G loss: 0.709150]
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744 [D loss: 0.692932, acc.: 51.17%] [G loss: 0.708516]
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745 [D loss: 0.693390, acc.: 49.41%] [G loss: 0.709386]
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746 [D loss: 0.693232, acc.: 49.61%] [G loss: 0.708940]
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747 [D loss: 0.693297, acc.: 49.80%] [G loss: 0.708453]
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748 [D loss: 0.693365, acc.: 48.63%] [G loss: 0.709987]
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749 [D loss: 0.692485, acc.: 51.17%] [G loss: 0.709203]
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750 [D loss: 0.693071, acc.: 50.00%] [G loss: 0.709155]
1/1 [==============================] - 0s 18ms/step
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751 [D loss: 0.692585, acc.: 50.78%] [G loss: 0.709375]
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752 [D loss: 0.692667, acc.: 50.39%] [G loss: 0.708039]
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753 [D loss: 0.693734, acc.: 50.20%] [G loss: 0.710312]
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754 [D loss: 0.693656, acc.: 50.59%] [G loss: 0.709624]
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755 [D loss: 0.694089, acc.: 49.02%] [G loss: 0.708948]
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756 [D loss: 0.693957, acc.: 47.85%] [G loss: 0.709244]
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757 [D loss: 0.694380, acc.: 48.05%] [G loss: 0.708149]
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758 [D loss: 0.694760, acc.: 47.66%] [G loss: 0.707293]
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759 [D loss: 0.694942, acc.: 46.48%] [G loss: 0.706461]
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760 [D loss: 0.694972, acc.: 47.46%] [G loss: 0.707204]
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761 [D loss: 0.695479, acc.: 44.73%] [G loss: 0.705030]
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762 [D loss: 0.695658, acc.: 46.29%] [G loss: 0.705284]
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763 [D loss: 0.695764, acc.: 45.12%] [G loss: 0.705111]
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764 [D loss: 0.696341, acc.: 43.75%] [G loss: 0.704060]
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765 [D loss: 0.694857, acc.: 46.09%] [G loss: 0.704198]
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766 [D loss: 0.696384, acc.: 43.95%] [G loss: 0.704124]
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767 [D loss: 0.696329, acc.: 44.73%] [G loss: 0.703476]
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768 [D loss: 0.695587, acc.: 45.51%] [G loss: 0.703489]
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769 [D loss: 0.696430, acc.: 44.34%] [G loss: 0.703208]
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770 [D loss: 0.694897, acc.: 46.29%] [G loss: 0.702445]
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771 [D loss: 0.696738, acc.: 40.04%] [G loss: 0.703211]
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772 [D loss: 0.695500, acc.: 46.09%] [G loss: 0.703401]
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773 [D loss: 0.695818, acc.: 43.55%] [G loss: 0.704115]
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774 [D loss: 0.695631, acc.: 43.75%] [G loss: 0.704200]
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775 [D loss: 0.695079, acc.: 45.31%] [G loss: 0.704237]
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776 [D loss: 0.695557, acc.: 42.19%] [G loss: 0.703663]
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777 [D loss: 0.695507, acc.: 44.73%] [G loss: 0.703881]
8/8 [==============================] - 0s 4ms/step
778 [D loss: 0.695110, acc.: 44.34%] [G loss: 0.703281]
8/8 [==============================] - 0s 4ms/step
779 [D loss: 0.694176, acc.: 47.46%] [G loss: 0.703395]
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780 [D loss: 0.694574, acc.: 46.09%] [G loss: 0.703600]
8/8 [==============================] - 0s 4ms/step
781 [D loss: 0.693988, acc.: 47.07%] [G loss: 0.704192]
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782 [D loss: 0.693427, acc.: 47.85%] [G loss: 0.705231]
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783 [D loss: 0.694869, acc.: 45.12%] [G loss: 0.704996]
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784 [D loss: 0.694377, acc.: 46.68%] [G loss: 0.704683]
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785 [D loss: 0.693744, acc.: 48.83%] [G loss: 0.705687]
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786 [D loss: 0.693699, acc.: 49.22%] [G loss: 0.705201]
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787 [D loss: 0.693349, acc.: 50.20%] [G loss: 0.705089]
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788 [D loss: 0.693629, acc.: 47.27%] [G loss: 0.705701]
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789 [D loss: 0.693865, acc.: 48.05%] [G loss: 0.706080]
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790 [D loss: 0.693069, acc.: 51.56%] [G loss: 0.704546]
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791 [D loss: 0.693849, acc.: 47.66%] [G loss: 0.705278]
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792 [D loss: 0.693504, acc.: 50.59%] [G loss: 0.704279]
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793 [D loss: 0.693190, acc.: 51.95%] [G loss: 0.704380]
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794 [D loss: 0.693098, acc.: 51.56%] [G loss: 0.705022]
8/8 [==============================] - 0s 4ms/step
795 [D loss: 0.693811, acc.: 49.22%] [G loss: 0.704930]
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796 [D loss: 0.694170, acc.: 46.09%] [G loss: 0.703862]
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797 [D loss: 0.693416, acc.: 49.02%] [G loss: 0.703782]
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798 [D loss: 0.693756, acc.: 50.39%] [G loss: 0.703256]
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799 [D loss: 0.693110, acc.: 49.02%] [G loss: 0.703019]
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800 [D loss: 0.694153, acc.: 48.83%] [G loss: 0.704010]
1/1 [==============================] - 0s 20ms/step
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801 [D loss: 0.693564, acc.: 48.44%] [G loss: 0.702256]
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802 [D loss: 0.693976, acc.: 48.63%] [G loss: 0.702735]
8/8 [==============================] - 0s 5ms/step
803 [D loss: 0.693783, acc.: 48.44%] [G loss: 0.702574]
8/8 [==============================] - 0s 6ms/step
804 [D loss: 0.694277, acc.: 47.07%] [G loss: 0.702238]
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805 [D loss: 0.693684, acc.: 48.63%] [G loss: 0.702233]
8/8 [==============================] - 0s 5ms/step
806 [D loss: 0.694173, acc.: 46.68%] [G loss: 0.702313]
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807 [D loss: 0.694107, acc.: 46.29%] [G loss: 0.700801]
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808 [D loss: 0.694529, acc.: 44.34%] [G loss: 0.700770]
8/8 [==============================] - 0s 5ms/step
809 [D loss: 0.694759, acc.: 44.14%] [G loss: 0.699975]
8/8 [==============================] - 0s 6ms/step
810 [D loss: 0.694185, acc.: 49.41%] [G loss: 0.700296]
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811 [D loss: 0.694647, acc.: 43.75%] [G loss: 0.699874]
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812 [D loss: 0.693845, acc.: 46.29%] [G loss: 0.699883]
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813 [D loss: 0.694531, acc.: 46.29%] [G loss: 0.700936]
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814 [D loss: 0.694995, acc.: 42.97%] [G loss: 0.700295]
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815 [D loss: 0.694658, acc.: 44.53%] [G loss: 0.701402]
8/8 [==============================] - 0s 5ms/step
816 [D loss: 0.694717, acc.: 45.90%] [G loss: 0.699900]
8/8 [==============================] - 0s 5ms/step
817 [D loss: 0.694556, acc.: 46.48%] [G loss: 0.700710]
8/8 [==============================] - 0s 5ms/step
818 [D loss: 0.695167, acc.: 46.29%] [G loss: 0.700885]
8/8 [==============================] - 0s 5ms/step
819 [D loss: 0.694761, acc.: 44.14%] [G loss: 0.700638]
8/8 [==============================] - 0s 4ms/step
820 [D loss: 0.694633, acc.: 45.12%] [G loss: 0.700620]
8/8 [==============================] - 0s 5ms/step
821 [D loss: 0.694705, acc.: 44.92%] [G loss: 0.700524]
8/8 [==============================] - 0s 4ms/step
822 [D loss: 0.694111, acc.: 48.05%] [G loss: 0.700620]
8/8 [==============================] - 0s 4ms/step
823 [D loss: 0.694748, acc.: 45.31%] [G loss: 0.701245]
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824 [D loss: 0.694504, acc.: 46.48%] [G loss: 0.700819]
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825 [D loss: 0.694062, acc.: 46.68%] [G loss: 0.700538]
8/8 [==============================] - 0s 4ms/step
826 [D loss: 0.695004, acc.: 43.55%] [G loss: 0.700732]
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827 [D loss: 0.694958, acc.: 43.36%] [G loss: 0.702276]
8/8 [==============================] - 0s 5ms/step
828 [D loss: 0.694449, acc.: 47.27%] [G loss: 0.700837]
8/8 [==============================] - 0s 5ms/step
829 [D loss: 0.694249, acc.: 45.31%] [G loss: 0.701760]
8/8 [==============================] - 0s 4ms/step
830 [D loss: 0.694458, acc.: 46.48%] [G loss: 0.701838]
8/8 [==============================] - 0s 5ms/step
831 [D loss: 0.695427, acc.: 41.60%] [G loss: 0.700344]
8/8 [==============================] - 0s 5ms/step
832 [D loss: 0.694900, acc.: 44.34%] [G loss: 0.701341]
8/8 [==============================] - 0s 5ms/step
833 [D loss: 0.695667, acc.: 43.75%] [G loss: 0.701362]
8/8 [==============================] - 0s 5ms/step
834 [D loss: 0.695462, acc.: 41.99%] [G loss: 0.701615]
8/8 [==============================] - 0s 5ms/step
835 [D loss: 0.694934, acc.: 42.97%] [G loss: 0.702577]
8/8 [==============================] - 0s 4ms/step
836 [D loss: 0.694641, acc.: 41.21%] [G loss: 0.702796]
8/8 [==============================] - 0s 5ms/step
837 [D loss: 0.694579, acc.: 44.14%] [G loss: 0.702562]
8/8 [==============================] - 0s 5ms/step
838 [D loss: 0.694268, acc.: 45.70%] [G loss: 0.702028]
8/8 [==============================] - 0s 5ms/step
839 [D loss: 0.693974, acc.: 46.29%] [G loss: 0.703090]
8/8 [==============================] - 0s 8ms/step
840 [D loss: 0.694542, acc.: 44.53%] [G loss: 0.703871]
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841 [D loss: 0.694558, acc.: 46.09%] [G loss: 0.703215]
8/8 [==============================] - 0s 5ms/step
842 [D loss: 0.693966, acc.: 50.20%] [G loss: 0.704292]
8/8 [==============================] - 0s 5ms/step
843 [D loss: 0.694150, acc.: 44.34%] [G loss: 0.703964]
8/8 [==============================] - 0s 4ms/step
844 [D loss: 0.693763, acc.: 50.98%] [G loss: 0.704975]
8/8 [==============================] - 0s 4ms/step
845 [D loss: 0.693349, acc.: 49.41%] [G loss: 0.704752]
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846 [D loss: 0.693593, acc.: 51.37%] [G loss: 0.705495]
8/8 [==============================] - 0s 4ms/step
847 [D loss: 0.692794, acc.: 52.34%] [G loss: 0.704937]
8/8 [==============================] - 0s 4ms/step
848 [D loss: 0.693155, acc.: 50.20%] [G loss: 0.704169]
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849 [D loss: 0.692978, acc.: 51.56%] [G loss: 0.706595]
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850 [D loss: 0.692857, acc.: 50.39%] [G loss: 0.706454]
1/1 [==============================] - 0s 21ms/step
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851 [D loss: 0.693064, acc.: 49.61%] [G loss: 0.705791]
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852 [D loss: 0.692672, acc.: 50.39%] [G loss: 0.706174]
8/8 [==============================] - 0s 5ms/step
853 [D loss: 0.692599, acc.: 52.54%] [G loss: 0.705860]
8/8 [==============================] - 0s 4ms/step
854 [D loss: 0.692471, acc.: 50.39%] [G loss: 0.706458]
8/8 [==============================] - 0s 4ms/step
855 [D loss: 0.692171, acc.: 53.12%] [G loss: 0.706373]
8/8 [==============================] - 0s 4ms/step
856 [D loss: 0.692549, acc.: 50.98%] [G loss: 0.706398]
8/8 [==============================] - 0s 4ms/step
857 [D loss: 0.692624, acc.: 50.78%] [G loss: 0.705507]
8/8 [==============================] - 0s 4ms/step
858 [D loss: 0.692747, acc.: 52.34%] [G loss: 0.705630]
8/8 [==============================] - 0s 4ms/step
859 [D loss: 0.693248, acc.: 47.66%] [G loss: 0.705422]
8/8 [==============================] - 0s 4ms/step
860 [D loss: 0.692067, acc.: 52.15%] [G loss: 0.704119]
8/8 [==============================] - 0s 4ms/step
861 [D loss: 0.693078, acc.: 51.37%] [G loss: 0.702962]
8/8 [==============================] - 0s 4ms/step
862 [D loss: 0.693673, acc.: 47.27%] [G loss: 0.704767]
8/8 [==============================] - 0s 4ms/step
863 [D loss: 0.692895, acc.: 49.22%] [G loss: 0.702928]
8/8 [==============================] - 0s 5ms/step
864 [D loss: 0.694170, acc.: 46.09%] [G loss: 0.704617]
8/8 [==============================] - 0s 5ms/step
865 [D loss: 0.694132, acc.: 47.46%] [G loss: 0.702764]
8/8 [==============================] - 0s 5ms/step
866 [D loss: 0.693932, acc.: 48.05%] [G loss: 0.704400]
8/8 [==============================] - 0s 5ms/step
867 [D loss: 0.694581, acc.: 46.29%] [G loss: 0.701262]
8/8 [==============================] - 0s 5ms/step
868 [D loss: 0.695831, acc.: 40.82%] [G loss: 0.701741]
8/8 [==============================] - 0s 4ms/step
869 [D loss: 0.695360, acc.: 45.31%] [G loss: 0.701273]
8/8 [==============================] - 0s 5ms/step
870 [D loss: 0.695684, acc.: 41.21%] [G loss: 0.700831]
8/8 [==============================] - 0s 4ms/step
871 [D loss: 0.694851, acc.: 46.29%] [G loss: 0.701400]
8/8 [==============================] - 0s 5ms/step
872 [D loss: 0.695390, acc.: 44.14%] [G loss: 0.700096]
8/8 [==============================] - 0s 5ms/step
873 [D loss: 0.695870, acc.: 41.60%] [G loss: 0.700763]
8/8 [==============================] - 0s 5ms/step
874 [D loss: 0.697000, acc.: 39.06%] [G loss: 0.700609]
8/8 [==============================] - 0s 4ms/step
875 [D loss: 0.696058, acc.: 41.60%] [G loss: 0.701476]
8/8 [==============================] - 0s 4ms/step
876 [D loss: 0.696085, acc.: 42.77%] [G loss: 0.701172]
8/8 [==============================] - 0s 4ms/step
877 [D loss: 0.696663, acc.: 40.23%] [G loss: 0.699843]
8/8 [==============================] - 0s 5ms/step
878 [D loss: 0.696604, acc.: 40.04%] [G loss: 0.699798]
8/8 [==============================] - 0s 5ms/step
879 [D loss: 0.695933, acc.: 42.97%] [G loss: 0.700121]
8/8 [==============================] - 0s 4ms/step
880 [D loss: 0.696225, acc.: 43.55%] [G loss: 0.700521]
8/8 [==============================] - 0s 4ms/step
881 [D loss: 0.696120, acc.: 42.77%] [G loss: 0.700767]
8/8 [==============================] - 0s 5ms/step
882 [D loss: 0.695935, acc.: 42.19%] [G loss: 0.701479]
8/8 [==============================] - 0s 5ms/step
883 [D loss: 0.695395, acc.: 44.14%] [G loss: 0.702335]
8/8 [==============================] - 0s 5ms/step
884 [D loss: 0.695070, acc.: 45.51%] [G loss: 0.702344]
8/8 [==============================] - 0s 5ms/step
885 [D loss: 0.694920, acc.: 46.68%] [G loss: 0.702093]
8/8 [==============================] - 0s 4ms/step
886 [D loss: 0.695370, acc.: 43.75%] [G loss: 0.703119]
8/8 [==============================] - 0s 4ms/step
887 [D loss: 0.694784, acc.: 45.90%] [G loss: 0.703121]
8/8 [==============================] - 0s 4ms/step
888 [D loss: 0.694365, acc.: 48.05%] [G loss: 0.702662]
8/8 [==============================] - 0s 5ms/step
889 [D loss: 0.693756, acc.: 49.02%] [G loss: 0.703481]
8/8 [==============================] - 0s 4ms/step
890 [D loss: 0.694181, acc.: 48.44%] [G loss: 0.702978]
8/8 [==============================] - 0s 5ms/step
891 [D loss: 0.693708, acc.: 47.46%] [G loss: 0.703084]
8/8 [==============================] - 0s 4ms/step
892 [D loss: 0.693611, acc.: 48.63%] [G loss: 0.703994]
8/8 [==============================] - 0s 5ms/step
893 [D loss: 0.693538, acc.: 48.83%] [G loss: 0.703330]
8/8 [==============================] - 0s 5ms/step
894 [D loss: 0.693053, acc.: 49.41%] [G loss: 0.703934]
8/8 [==============================] - 0s 5ms/step
895 [D loss: 0.693232, acc.: 47.27%] [G loss: 0.704631]
8/8 [==============================] - 0s 4ms/step
896 [D loss: 0.693047, acc.: 49.80%] [G loss: 0.704930]
8/8 [==============================] - 0s 4ms/step
897 [D loss: 0.693253, acc.: 47.85%] [G loss: 0.704889]
8/8 [==============================] - 0s 5ms/step
898 [D loss: 0.692996, acc.: 51.37%] [G loss: 0.705036]
8/8 [==============================] - 0s 5ms/step
899 [D loss: 0.693202, acc.: 51.17%] [G loss: 0.705436]
8/8 [==============================] - 0s 4ms/step
900 [D loss: 0.693139, acc.: 47.07%] [G loss: 0.703547]
1/1 [==============================] - 0s 17ms/step
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901 [D loss: 0.693175, acc.: 48.83%] [G loss: 0.703987]
8/8 [==============================] - 0s 5ms/step
902 [D loss: 0.693254, acc.: 48.05%] [G loss: 0.705676]
8/8 [==============================] - 0s 5ms/step
903 [D loss: 0.693384, acc.: 48.44%] [G loss: 0.706614]
8/8 [==============================] - 0s 5ms/step
904 [D loss: 0.692750, acc.: 51.17%] [G loss: 0.705200]
8/8 [==============================] - 0s 4ms/step
905 [D loss: 0.692287, acc.: 51.17%] [G loss: 0.704051]
8/8 [==============================] - 0s 5ms/step
906 [D loss: 0.692505, acc.: 50.00%] [G loss: 0.704256]
8/8 [==============================] - 0s 4ms/step
907 [D loss: 0.693301, acc.: 49.22%] [G loss: 0.705897]
8/8 [==============================] - 0s 5ms/step
908 [D loss: 0.693121, acc.: 48.83%] [G loss: 0.705588]
8/8 [==============================] - 0s 5ms/step
909 [D loss: 0.693155, acc.: 48.05%] [G loss: 0.704726]
8/8 [==============================] - 0s 5ms/step
910 [D loss: 0.693955, acc.: 45.51%] [G loss: 0.703575]
8/8 [==============================] - 0s 4ms/step
911 [D loss: 0.693730, acc.: 46.68%] [G loss: 0.704270]
8/8 [==============================] - 0s 5ms/step
912 [D loss: 0.693833, acc.: 47.27%] [G loss: 0.704852]
8/8 [==============================] - 0s 4ms/step
913 [D loss: 0.693671, acc.: 46.88%] [G loss: 0.703197]
8/8 [==============================] - 0s 5ms/step
914 [D loss: 0.693952, acc.: 48.83%] [G loss: 0.703296]
8/8 [==============================] - 0s 5ms/step
915 [D loss: 0.694408, acc.: 45.12%] [G loss: 0.705087]
8/8 [==============================] - 0s 5ms/step
916 [D loss: 0.694940, acc.: 42.77%] [G loss: 0.702597]
8/8 [==============================] - 0s 5ms/step
917 [D loss: 0.694803, acc.: 43.36%] [G loss: 0.702851]
8/8 [==============================] - 0s 5ms/step
918 [D loss: 0.694879, acc.: 46.29%] [G loss: 0.705118]
8/8 [==============================] - 0s 5ms/step
919 [D loss: 0.695003, acc.: 43.75%] [G loss: 0.703359]
8/8 [==============================] - 0s 4ms/step
920 [D loss: 0.694899, acc.: 46.68%] [G loss: 0.703384]
8/8 [==============================] - 0s 5ms/step
921 [D loss: 0.695546, acc.: 45.31%] [G loss: 0.703542]
8/8 [==============================] - 0s 5ms/step
922 [D loss: 0.694124, acc.: 47.46%] [G loss: 0.703482]
8/8 [==============================] - 0s 5ms/step
923 [D loss: 0.694677, acc.: 47.27%] [G loss: 0.702469]
8/8 [==============================] - 0s 5ms/step
924 [D loss: 0.694425, acc.: 49.22%] [G loss: 0.702870]
8/8 [==============================] - 0s 4ms/step
925 [D loss: 0.695198, acc.: 45.90%] [G loss: 0.702779]
8/8 [==============================] - 0s 6ms/step
926 [D loss: 0.695379, acc.: 45.90%] [G loss: 0.703024]
8/8 [==============================] - 0s 5ms/step
927 [D loss: 0.694996, acc.: 45.12%] [G loss: 0.702626]
8/8 [==============================] - 0s 4ms/step
928 [D loss: 0.695040, acc.: 47.46%] [G loss: 0.703274]
8/8 [==============================] - 0s 5ms/step
929 [D loss: 0.695172, acc.: 45.51%] [G loss: 0.703478]
8/8 [==============================] - 0s 5ms/step
930 [D loss: 0.694526, acc.: 46.29%] [G loss: 0.703324]
8/8 [==============================] - 0s 4ms/step
931 [D loss: 0.694425, acc.: 46.48%] [G loss: 0.702648]
8/8 [==============================] - 0s 5ms/step
932 [D loss: 0.694246, acc.: 45.70%] [G loss: 0.702591]
8/8 [==============================] - 0s 4ms/step
933 [D loss: 0.694900, acc.: 44.73%] [G loss: 0.702595]
8/8 [==============================] - 0s 5ms/step
934 [D loss: 0.694961, acc.: 45.12%] [G loss: 0.702305]
8/8 [==============================] - 0s 5ms/step
935 [D loss: 0.694843, acc.: 46.88%] [G loss: 0.702727]
8/8 [==============================] - 0s 5ms/step
936 [D loss: 0.694288, acc.: 46.88%] [G loss: 0.702515]
8/8 [==============================] - 0s 4ms/step
937 [D loss: 0.694801, acc.: 44.92%] [G loss: 0.701804]
8/8 [==============================] - 0s 4ms/step
938 [D loss: 0.693878, acc.: 47.85%] [G loss: 0.703747]
8/8 [==============================] - 0s 5ms/step
939 [D loss: 0.694346, acc.: 46.09%] [G loss: 0.703223]
8/8 [==============================] - 0s 5ms/step
940 [D loss: 0.694335, acc.: 49.80%] [G loss: 0.702803]
8/8 [==============================] - 0s 4ms/step
941 [D loss: 0.694452, acc.: 47.07%] [G loss: 0.702581]
8/8 [==============================] - 0s 4ms/step
942 [D loss: 0.693973, acc.: 47.85%] [G loss: 0.703995]
8/8 [==============================] - 0s 5ms/step
943 [D loss: 0.693832, acc.: 46.48%] [G loss: 0.703314]
8/8 [==============================] - 0s 4ms/step
944 [D loss: 0.694054, acc.: 45.12%] [G loss: 0.703889]
8/8 [==============================] - 0s 4ms/step
945 [D loss: 0.694145, acc.: 49.22%] [G loss: 0.703455]
8/8 [==============================] - 0s 5ms/step
946 [D loss: 0.694044, acc.: 47.07%] [G loss: 0.701872]
8/8 [==============================] - 0s 5ms/step
947 [D loss: 0.693634, acc.: 48.05%] [G loss: 0.703767]
8/8 [==============================] - 0s 5ms/step
948 [D loss: 0.694053, acc.: 46.68%] [G loss: 0.703435]
8/8 [==============================] - 0s 5ms/step
949 [D loss: 0.694392, acc.: 46.68%] [G loss: 0.702988]
8/8 [==============================] - 0s 5ms/step
950 [D loss: 0.693692, acc.: 48.44%] [G loss: 0.702650]
1/1 [==============================] - 0s 19ms/step
8/8 [==============================] - 0s 5ms/step
951 [D loss: 0.693621, acc.: 47.46%] [G loss: 0.703399]
8/8 [==============================] - 0s 5ms/step
952 [D loss: 0.694326, acc.: 48.05%] [G loss: 0.703886]
8/8 [==============================] - 0s 4ms/step
953 [D loss: 0.693511, acc.: 50.78%] [G loss: 0.703782]
8/8 [==============================] - 0s 5ms/step
954 [D loss: 0.693963, acc.: 49.61%] [G loss: 0.702893]
8/8 [==============================] - 0s 5ms/step
955 [D loss: 0.694118, acc.: 46.88%] [G loss: 0.703801]
8/8 [==============================] - 0s 5ms/step
956 [D loss: 0.694312, acc.: 46.68%] [G loss: 0.702474]
8/8 [==============================] - 0s 4ms/step
957 [D loss: 0.694373, acc.: 46.88%] [G loss: 0.703552]
8/8 [==============================] - 0s 5ms/step
958 [D loss: 0.694095, acc.: 48.05%] [G loss: 0.702815]
8/8 [==============================] - 0s 4ms/step
959 [D loss: 0.694081, acc.: 47.46%] [G loss: 0.704001]
8/8 [==============================] - 0s 5ms/step
960 [D loss: 0.693549, acc.: 50.39%] [G loss: 0.702665]
8/8 [==============================] - 0s 5ms/step
961 [D loss: 0.693834, acc.: 47.46%] [G loss: 0.702695]
8/8 [==============================] - 0s 6ms/step
962 [D loss: 0.694654, acc.: 47.27%] [G loss: 0.703353]
8/8 [==============================] - 0s 5ms/step
963 [D loss: 0.693987, acc.: 47.07%] [G loss: 0.702472]
8/8 [==============================] - 0s 4ms/step
964 [D loss: 0.693927, acc.: 47.66%] [G loss: 0.703335]
8/8 [==============================] - 0s 5ms/step
965 [D loss: 0.694346, acc.: 46.88%] [G loss: 0.702471]
8/8 [==============================] - 0s 5ms/step
966 [D loss: 0.694374, acc.: 47.27%] [G loss: 0.703426]
8/8 [==============================] - 0s 4ms/step
967 [D loss: 0.693946, acc.: 48.44%] [G loss: 0.703864]
8/8 [==============================] - 0s 4ms/step
968 [D loss: 0.693569, acc.: 49.02%] [G loss: 0.703038]
8/8 [==============================] - 0s 4ms/step
969 [D loss: 0.693625, acc.: 48.44%] [G loss: 0.703035]
8/8 [==============================] - 0s 4ms/step
970 [D loss: 0.693930, acc.: 46.09%] [G loss: 0.702690]
8/8 [==============================] - 0s 5ms/step
971 [D loss: 0.694010, acc.: 47.07%] [G loss: 0.703277]
8/8 [==============================] - 0s 6ms/step
972 [D loss: 0.693662, acc.: 50.39%] [G loss: 0.702717]
8/8 [==============================] - 0s 5ms/step
973 [D loss: 0.694042, acc.: 47.85%] [G loss: 0.703577]
8/8 [==============================] - 0s 4ms/step
974 [D loss: 0.693976, acc.: 47.66%] [G loss: 0.703735]
8/8 [==============================] - 0s 4ms/step
975 [D loss: 0.694287, acc.: 46.29%] [G loss: 0.703901]
8/8 [==============================] - 0s 4ms/step
976 [D loss: 0.693416, acc.: 49.80%] [G loss: 0.703097]
8/8 [==============================] - 0s 4ms/step
977 [D loss: 0.693601, acc.: 48.44%] [G loss: 0.703702]
8/8 [==============================] - 0s 4ms/step
978 [D loss: 0.692640, acc.: 51.56%] [G loss: 0.703788]
8/8 [==============================] - 0s 4ms/step
979 [D loss: 0.693804, acc.: 49.02%] [G loss: 0.703706]
8/8 [==============================] - 0s 5ms/step
980 [D loss: 0.694003, acc.: 49.22%] [G loss: 0.704215]
8/8 [==============================] - 0s 4ms/step
981 [D loss: 0.694123, acc.: 46.68%] [G loss: 0.703907]
8/8 [==============================] - 0s 6ms/step
982 [D loss: 0.693689, acc.: 50.59%] [G loss: 0.703439]
8/8 [==============================] - 0s 4ms/step
983 [D loss: 0.694037, acc.: 48.63%] [G loss: 0.703760]
8/8 [==============================] - 0s 5ms/step
984 [D loss: 0.693082, acc.: 49.02%] [G loss: 0.704645]
8/8 [==============================] - 0s 4ms/step
985 [D loss: 0.693781, acc.: 46.68%] [G loss: 0.702979]
8/8 [==============================] - 0s 5ms/step
986 [D loss: 0.693151, acc.: 51.17%] [G loss: 0.703915]
8/8 [==============================] - 0s 4ms/step
987 [D loss: 0.693388, acc.: 47.85%] [G loss: 0.704282]
8/8 [==============================] - 0s 4ms/step
988 [D loss: 0.694026, acc.: 49.22%] [G loss: 0.703302]
8/8 [==============================] - 0s 4ms/step
989 [D loss: 0.693855, acc.: 45.90%] [G loss: 0.702136]
8/8 [==============================] - 0s 5ms/step
990 [D loss: 0.693760, acc.: 46.88%] [G loss: 0.704068]
8/8 [==============================] - 0s 4ms/step
991 [D loss: 0.694789, acc.: 46.09%] [G loss: 0.702595]
8/8 [==============================] - 0s 5ms/step
992 [D loss: 0.693931, acc.: 43.95%] [G loss: 0.703740]
8/8 [==============================] - 0s 4ms/step
993 [D loss: 0.694183, acc.: 46.88%] [G loss: 0.702979]
8/8 [==============================] - 0s 4ms/step
994 [D loss: 0.693028, acc.: 49.80%] [G loss: 0.702787]
8/8 [==============================] - 0s 7ms/step
995 [D loss: 0.694597, acc.: 47.07%] [G loss: 0.702491]
8/8 [==============================] - 0s 4ms/step
996 [D loss: 0.694459, acc.: 47.66%] [G loss: 0.702732]
8/8 [==============================] - 0s 4ms/step
997 [D loss: 0.693860, acc.: 48.63%] [G loss: 0.703204]
8/8 [==============================] - 0s 4ms/step
998 [D loss: 0.694230, acc.: 46.68%] [G loss: 0.703346]
8/8 [==============================] - 0s 4ms/step
999 [D loss: 0.694213, acc.: 47.85%] [G loss: 0.702373]
8/8 [==============================] - 0s 4ms/step
1000 [D loss: 0.694463, acc.: 45.51%] [G loss: 0.702819]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 4ms/step
1001 [D loss: 0.694879, acc.: 44.53%] [G loss: 0.703274]
8/8 [==============================] - 0s 5ms/step
1002 [D loss: 0.694300, acc.: 46.88%] [G loss: 0.703032]
8/8 [==============================] - 0s 4ms/step
1003 [D loss: 0.694346, acc.: 45.51%] [G loss: 0.702204]
8/8 [==============================] - 0s 5ms/step
1004 [D loss: 0.694606, acc.: 46.09%] [G loss: 0.703252]
8/8 [==============================] - 0s 5ms/step
1005 [D loss: 0.694771, acc.: 46.68%] [G loss: 0.702265]
8/8 [==============================] - 0s 5ms/step
1006 [D loss: 0.694853, acc.: 45.70%] [G loss: 0.701871]
8/8 [==============================] - 0s 4ms/step
1007 [D loss: 0.694998, acc.: 43.75%] [G loss: 0.701912]
8/8 [==============================] - 0s 4ms/step
1008 [D loss: 0.694708, acc.: 44.14%] [G loss: 0.702451]
8/8 [==============================] - 0s 4ms/step
1009 [D loss: 0.694760, acc.: 45.90%] [G loss: 0.702219]
8/8 [==============================] - 0s 4ms/step
1010 [D loss: 0.694043, acc.: 46.48%] [G loss: 0.702004]
8/8 [==============================] - 0s 4ms/step
1011 [D loss: 0.693875, acc.: 48.05%] [G loss: 0.701745]
8/8 [==============================] - 0s 5ms/step
1012 [D loss: 0.694473, acc.: 44.73%] [G loss: 0.701721]
8/8 [==============================] - 0s 4ms/step
1013 [D loss: 0.693763, acc.: 49.61%] [G loss: 0.701967]
8/8 [==============================] - 0s 4ms/step
1014 [D loss: 0.694757, acc.: 43.95%] [G loss: 0.702212]
8/8 [==============================] - 0s 5ms/step
1015 [D loss: 0.694737, acc.: 46.29%] [G loss: 0.701483]
8/8 [==============================] - 0s 4ms/step
1016 [D loss: 0.694031, acc.: 49.41%] [G loss: 0.700879]
8/8 [==============================] - 0s 4ms/step
1017 [D loss: 0.694032, acc.: 44.53%] [G loss: 0.701449]
8/8 [==============================] - 0s 5ms/step
1018 [D loss: 0.693937, acc.: 47.85%] [G loss: 0.701427]
8/8 [==============================] - 0s 4ms/step
1019 [D loss: 0.694200, acc.: 44.92%] [G loss: 0.701878]
8/8 [==============================] - 0s 4ms/step
1020 [D loss: 0.693887, acc.: 49.02%] [G loss: 0.702042]
8/8 [==============================] - 0s 4ms/step
1021 [D loss: 0.693820, acc.: 48.63%] [G loss: 0.701252]
8/8 [==============================] - 0s 4ms/step
1022 [D loss: 0.693819, acc.: 49.41%] [G loss: 0.701768]
8/8 [==============================] - 0s 4ms/step
1023 [D loss: 0.694150, acc.: 47.46%] [G loss: 0.701026]
8/8 [==============================] - 0s 4ms/step
1024 [D loss: 0.693684, acc.: 49.22%] [G loss: 0.701515]
8/8 [==============================] - 0s 5ms/step
1025 [D loss: 0.693345, acc.: 50.59%] [G loss: 0.700944]
8/8 [==============================] - 0s 5ms/step
1026 [D loss: 0.693546, acc.: 48.24%] [G loss: 0.702007]
8/8 [==============================] - 0s 5ms/step
1027 [D loss: 0.693650, acc.: 47.66%] [G loss: 0.701455]
8/8 [==============================] - 0s 4ms/step
1028 [D loss: 0.693121, acc.: 49.41%] [G loss: 0.701845]
8/8 [==============================] - 0s 4ms/step
1029 [D loss: 0.693909, acc.: 47.66%] [G loss: 0.700983]
8/8 [==============================] - 0s 4ms/step
1030 [D loss: 0.693718, acc.: 47.66%] [G loss: 0.701315]
8/8 [==============================] - 0s 4ms/step
1031 [D loss: 0.693431, acc.: 48.63%] [G loss: 0.701450]
8/8 [==============================] - 0s 4ms/step
1032 [D loss: 0.693546, acc.: 48.83%] [G loss: 0.700408]
8/8 [==============================] - 0s 4ms/step
1033 [D loss: 0.693509, acc.: 45.70%] [G loss: 0.700850]
8/8 [==============================] - 0s 4ms/step
1034 [D loss: 0.693408, acc.: 50.98%] [G loss: 0.700338]
8/8 [==============================] - 0s 5ms/step
1035 [D loss: 0.693086, acc.: 49.61%] [G loss: 0.700506]
8/8 [==============================] - 0s 4ms/step
1036 [D loss: 0.694021, acc.: 46.68%] [G loss: 0.701073]
8/8 [==============================] - 0s 4ms/step
1037 [D loss: 0.693655, acc.: 49.61%] [G loss: 0.700150]
8/8 [==============================] - 0s 4ms/step
1038 [D loss: 0.693941, acc.: 47.27%] [G loss: 0.700149]
8/8 [==============================] - 0s 5ms/step
1039 [D loss: 0.693983, acc.: 45.90%] [G loss: 0.699715]
8/8 [==============================] - 0s 5ms/step
1040 [D loss: 0.693482, acc.: 50.20%] [G loss: 0.699786]
8/8 [==============================] - 0s 5ms/step
1041 [D loss: 0.693718, acc.: 50.39%] [G loss: 0.699903]
8/8 [==============================] - 0s 5ms/step
1042 [D loss: 0.693847, acc.: 44.73%] [G loss: 0.700038]
8/8 [==============================] - 0s 4ms/step
1043 [D loss: 0.693710, acc.: 47.46%] [G loss: 0.699858]
8/8 [==============================] - 0s 5ms/step
1044 [D loss: 0.694245, acc.: 45.70%] [G loss: 0.699692]
8/8 [==============================] - 0s 4ms/step
1045 [D loss: 0.694054, acc.: 47.07%] [G loss: 0.699878]
8/8 [==============================] - 0s 5ms/step
1046 [D loss: 0.693753, acc.: 49.22%] [G loss: 0.699732]
8/8 [==============================] - 0s 5ms/step
1047 [D loss: 0.694043, acc.: 45.51%] [G loss: 0.699166]
8/8 [==============================] - 0s 4ms/step
1048 [D loss: 0.692946, acc.: 50.20%] [G loss: 0.699201]
8/8 [==============================] - 0s 5ms/step
1049 [D loss: 0.693823, acc.: 45.90%] [G loss: 0.697779]
8/8 [==============================] - 0s 4ms/step
1050 [D loss: 0.693550, acc.: 48.44%] [G loss: 0.698267]
1/1 [==============================] - 0s 16ms/step
8/8 [==============================] - 0s 4ms/step
1051 [D loss: 0.693394, acc.: 46.48%] [G loss: 0.698175]
8/8 [==============================] - 0s 4ms/step
1052 [D loss: 0.694339, acc.: 44.14%] [G loss: 0.698731]
8/8 [==============================] - 0s 5ms/step
1053 [D loss: 0.694192, acc.: 45.12%] [G loss: 0.697368]
8/8 [==============================] - 0s 5ms/step
1054 [D loss: 0.693620, acc.: 48.24%] [G loss: 0.698088]
8/8 [==============================] - 0s 4ms/step
1055 [D loss: 0.694354, acc.: 46.88%] [G loss: 0.697584]
8/8 [==============================] - 0s 5ms/step
1056 [D loss: 0.693902, acc.: 44.73%] [G loss: 0.696708]
8/8 [==============================] - 0s 4ms/step
1057 [D loss: 0.695035, acc.: 41.60%] [G loss: 0.697323]
8/8 [==============================] - 0s 4ms/step
1058 [D loss: 0.694185, acc.: 44.92%] [G loss: 0.698399]
8/8 [==============================] - 0s 5ms/step
1059 [D loss: 0.693400, acc.: 48.83%] [G loss: 0.698397]
8/8 [==============================] - 0s 4ms/step
1060 [D loss: 0.693334, acc.: 48.83%] [G loss: 0.697872]
8/8 [==============================] - 0s 7ms/step
1061 [D loss: 0.693893, acc.: 44.34%] [G loss: 0.697306]
8/8 [==============================] - 0s 5ms/step
1062 [D loss: 0.693748, acc.: 47.27%] [G loss: 0.698058]
8/8 [==============================] - 0s 4ms/step
1063 [D loss: 0.693901, acc.: 48.05%] [G loss: 0.697815]
8/8 [==============================] - 0s 4ms/step
1064 [D loss: 0.692841, acc.: 49.80%] [G loss: 0.697760]
8/8 [==============================] - 0s 4ms/step
1065 [D loss: 0.693249, acc.: 50.78%] [G loss: 0.698661]
8/8 [==============================] - 0s 4ms/step
1066 [D loss: 0.693488, acc.: 46.88%] [G loss: 0.698615]
8/8 [==============================] - 0s 4ms/step
1067 [D loss: 0.693247, acc.: 48.83%] [G loss: 0.698205]
8/8 [==============================] - 0s 4ms/step
1068 [D loss: 0.692835, acc.: 52.34%] [G loss: 0.698581]
8/8 [==============================] - 0s 4ms/step
1069 [D loss: 0.693350, acc.: 47.66%] [G loss: 0.698393]
8/8 [==============================] - 0s 4ms/step
1070 [D loss: 0.693037, acc.: 47.85%] [G loss: 0.697938]
8/8 [==============================] - 0s 7ms/step
1071 [D loss: 0.693439, acc.: 47.46%] [G loss: 0.698431]
8/8 [==============================] - 0s 4ms/step
1072 [D loss: 0.693931, acc.: 42.77%] [G loss: 0.698724]
8/8 [==============================] - 0s 4ms/step
1073 [D loss: 0.692725, acc.: 51.56%] [G loss: 0.699134]
8/8 [==============================] - 0s 5ms/step
1074 [D loss: 0.693770, acc.: 44.53%] [G loss: 0.698636]
8/8 [==============================] - 0s 5ms/step
1075 [D loss: 0.693394, acc.: 50.78%] [G loss: 0.696868]
8/8 [==============================] - 0s 4ms/step
1076 [D loss: 0.693030, acc.: 50.78%] [G loss: 0.697557]
8/8 [==============================] - 0s 4ms/step
1077 [D loss: 0.693600, acc.: 47.46%] [G loss: 0.697478]
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1078 [D loss: 0.693782, acc.: 47.07%] [G loss: 0.697840]
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1079 [D loss: 0.694114, acc.: 42.58%] [G loss: 0.697882]
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1080 [D loss: 0.694154, acc.: 43.75%] [G loss: 0.697044]
8/8 [==============================] - 0s 4ms/step
1081 [D loss: 0.694050, acc.: 46.68%] [G loss: 0.696546]
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1082 [D loss: 0.694113, acc.: 46.88%] [G loss: 0.696678]
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1083 [D loss: 0.695134, acc.: 42.97%] [G loss: 0.695549]
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1084 [D loss: 0.695769, acc.: 37.89%] [G loss: 0.696933]
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1085 [D loss: 0.694100, acc.: 48.05%] [G loss: 0.696797]
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1086 [D loss: 0.694449, acc.: 43.75%] [G loss: 0.695858]
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1087 [D loss: 0.695167, acc.: 41.60%] [G loss: 0.696493]
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1088 [D loss: 0.694392, acc.: 45.70%] [G loss: 0.696570]
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1089 [D loss: 0.694645, acc.: 42.58%] [G loss: 0.696761]
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1090 [D loss: 0.694820, acc.: 41.41%] [G loss: 0.696453]
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1091 [D loss: 0.695014, acc.: 45.31%] [G loss: 0.696948]
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1092 [D loss: 0.695559, acc.: 38.67%] [G loss: 0.697137]
8/8 [==============================] - 0s 4ms/step
1093 [D loss: 0.694545, acc.: 43.95%] [G loss: 0.697926]
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1094 [D loss: 0.694998, acc.: 41.99%] [G loss: 0.696987]
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1095 [D loss: 0.694738, acc.: 41.99%] [G loss: 0.698549]
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1096 [D loss: 0.694332, acc.: 42.38%] [G loss: 0.698065]
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1097 [D loss: 0.693753, acc.: 45.90%] [G loss: 0.698467]
8/8 [==============================] - 0s 4ms/step
1098 [D loss: 0.694274, acc.: 44.53%] [G loss: 0.698475]
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1099 [D loss: 0.693790, acc.: 47.66%] [G loss: 0.699063]
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1100 [D loss: 0.694129, acc.: 43.75%] [G loss: 0.699573]
1/1 [==============================] - 0s 18ms/step
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1101 [D loss: 0.693920, acc.: 47.46%] [G loss: 0.699289]
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1102 [D loss: 0.694135, acc.: 45.90%] [G loss: 0.700098]
8/8 [==============================] - 0s 4ms/step
1103 [D loss: 0.693620, acc.: 47.27%] [G loss: 0.699866]
8/8 [==============================] - 0s 4ms/step
1104 [D loss: 0.694097, acc.: 46.29%] [G loss: 0.700518]
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1105 [D loss: 0.693847, acc.: 47.46%] [G loss: 0.699908]
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1106 [D loss: 0.693318, acc.: 49.61%] [G loss: 0.701075]
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1107 [D loss: 0.693359, acc.: 49.61%] [G loss: 0.701389]
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1108 [D loss: 0.693365, acc.: 49.80%] [G loss: 0.700725]
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1109 [D loss: 0.693523, acc.: 50.59%] [G loss: 0.701256]
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1110 [D loss: 0.693523, acc.: 50.59%] [G loss: 0.701246]
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1111 [D loss: 0.692859, acc.: 51.37%] [G loss: 0.702062]
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1112 [D loss: 0.693132, acc.: 47.66%] [G loss: 0.701415]
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1113 [D loss: 0.692995, acc.: 51.37%] [G loss: 0.702320]
8/8 [==============================] - 0s 4ms/step
1114 [D loss: 0.693344, acc.: 48.05%] [G loss: 0.701828]
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1115 [D loss: 0.692753, acc.: 51.56%] [G loss: 0.702726]
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1116 [D loss: 0.693320, acc.: 50.59%] [G loss: 0.703281]
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1117 [D loss: 0.693006, acc.: 50.98%] [G loss: 0.702076]
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1118 [D loss: 0.692930, acc.: 52.93%] [G loss: 0.702031]
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1119 [D loss: 0.692917, acc.: 51.76%] [G loss: 0.701767]
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1120 [D loss: 0.692887, acc.: 50.78%] [G loss: 0.701355]
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1121 [D loss: 0.694110, acc.: 45.51%] [G loss: 0.701682]
8/8 [==============================] - 0s 5ms/step
1122 [D loss: 0.693299, acc.: 49.61%] [G loss: 0.700938]
8/8 [==============================] - 0s 4ms/step
1123 [D loss: 0.693838, acc.: 48.44%] [G loss: 0.700760]
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1124 [D loss: 0.694090, acc.: 45.12%] [G loss: 0.700317]
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1125 [D loss: 0.694338, acc.: 45.90%] [G loss: 0.700984]
8/8 [==============================] - 0s 5ms/step
1126 [D loss: 0.694065, acc.: 47.27%] [G loss: 0.700029]
8/8 [==============================] - 0s 4ms/step
1127 [D loss: 0.694355, acc.: 42.97%] [G loss: 0.699753]
8/8 [==============================] - 0s 4ms/step
1128 [D loss: 0.694136, acc.: 43.95%] [G loss: 0.699121]
8/8 [==============================] - 0s 5ms/step
1129 [D loss: 0.693788, acc.: 50.98%] [G loss: 0.699222]
8/8 [==============================] - 0s 5ms/step
1130 [D loss: 0.693785, acc.: 47.46%] [G loss: 0.698459]
8/8 [==============================] - 0s 5ms/step
1131 [D loss: 0.693556, acc.: 47.85%] [G loss: 0.699733]
8/8 [==============================] - 0s 4ms/step
1132 [D loss: 0.694289, acc.: 45.12%] [G loss: 0.698735]
8/8 [==============================] - 0s 4ms/step
1133 [D loss: 0.694114, acc.: 48.24%] [G loss: 0.699080]
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1134 [D loss: 0.693761, acc.: 46.09%] [G loss: 0.698576]
8/8 [==============================] - 0s 4ms/step
1135 [D loss: 0.694528, acc.: 44.34%] [G loss: 0.698459]
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1136 [D loss: 0.694265, acc.: 45.90%] [G loss: 0.698148]
8/8 [==============================] - 0s 4ms/step
1137 [D loss: 0.694405, acc.: 42.58%] [G loss: 0.698182]
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1138 [D loss: 0.693371, acc.: 51.76%] [G loss: 0.698457]
8/8 [==============================] - 0s 4ms/step
1139 [D loss: 0.694327, acc.: 45.51%] [G loss: 0.698670]
8/8 [==============================] - 0s 4ms/step
1140 [D loss: 0.693184, acc.: 47.66%] [G loss: 0.698139]
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1141 [D loss: 0.694867, acc.: 42.97%] [G loss: 0.698098]
8/8 [==============================] - 0s 4ms/step
1142 [D loss: 0.694617, acc.: 44.34%] [G loss: 0.698768]
8/8 [==============================] - 0s 4ms/step
1143 [D loss: 0.694129, acc.: 44.73%] [G loss: 0.697881]
8/8 [==============================] - 0s 4ms/step
1144 [D loss: 0.694282, acc.: 43.55%] [G loss: 0.698263]
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1145 [D loss: 0.694104, acc.: 44.14%] [G loss: 0.698940]
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1146 [D loss: 0.693976, acc.: 45.12%] [G loss: 0.697962]
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1147 [D loss: 0.694149, acc.: 45.31%] [G loss: 0.698619]
8/8 [==============================] - 0s 4ms/step
1148 [D loss: 0.694446, acc.: 46.29%] [G loss: 0.698681]
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1149 [D loss: 0.693465, acc.: 49.22%] [G loss: 0.698524]
8/8 [==============================] - 0s 4ms/step
1150 [D loss: 0.693776, acc.: 45.90%] [G loss: 0.699693]
1/1 [==============================] - 0s 19ms/step
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1151 [D loss: 0.694124, acc.: 45.31%] [G loss: 0.699172]
8/8 [==============================] - 0s 4ms/step
1152 [D loss: 0.693452, acc.: 47.46%] [G loss: 0.699272]
8/8 [==============================] - 0s 6ms/step
1153 [D loss: 0.693386, acc.: 48.63%] [G loss: 0.699406]
8/8 [==============================] - 0s 4ms/step
1154 [D loss: 0.693408, acc.: 48.63%] [G loss: 0.699967]
8/8 [==============================] - 0s 4ms/step
1155 [D loss: 0.693327, acc.: 48.05%] [G loss: 0.700025]
8/8 [==============================] - 0s 4ms/step
1156 [D loss: 0.693522, acc.: 49.02%] [G loss: 0.698930]
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1157 [D loss: 0.693476, acc.: 48.05%] [G loss: 0.699540]
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1158 [D loss: 0.693087, acc.: 49.22%] [G loss: 0.700492]
8/8 [==============================] - 0s 5ms/step
1159 [D loss: 0.692998, acc.: 48.44%] [G loss: 0.699928]
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1160 [D loss: 0.693160, acc.: 50.00%] [G loss: 0.699929]
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1161 [D loss: 0.692830, acc.: 51.76%] [G loss: 0.700102]
8/8 [==============================] - 0s 4ms/step
1162 [D loss: 0.693111, acc.: 48.83%] [G loss: 0.700223]
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1163 [D loss: 0.693521, acc.: 48.44%] [G loss: 0.700344]
8/8 [==============================] - 0s 4ms/step
1164 [D loss: 0.693422, acc.: 46.29%] [G loss: 0.700250]
8/8 [==============================] - 0s 4ms/step
1165 [D loss: 0.693267, acc.: 48.83%] [G loss: 0.699746]
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1166 [D loss: 0.693460, acc.: 48.83%] [G loss: 0.699296]
8/8 [==============================] - 0s 5ms/step
1167 [D loss: 0.692884, acc.: 48.83%] [G loss: 0.699228]
8/8 [==============================] - 0s 5ms/step
1168 [D loss: 0.693521, acc.: 47.46%] [G loss: 0.699727]
8/8 [==============================] - 0s 5ms/step
1169 [D loss: 0.693602, acc.: 48.44%] [G loss: 0.699050]
8/8 [==============================] - 0s 5ms/step
1170 [D loss: 0.693387, acc.: 48.44%] [G loss: 0.698771]
8/8 [==============================] - 0s 4ms/step
1171 [D loss: 0.693396, acc.: 48.24%] [G loss: 0.698471]
8/8 [==============================] - 0s 5ms/step
1172 [D loss: 0.693198, acc.: 47.85%] [G loss: 0.698080]
8/8 [==============================] - 0s 4ms/step
1173 [D loss: 0.693589, acc.: 48.44%] [G loss: 0.697368]
8/8 [==============================] - 0s 5ms/step
1174 [D loss: 0.693769, acc.: 47.07%] [G loss: 0.697899]
8/8 [==============================] - 0s 4ms/step
1175 [D loss: 0.694013, acc.: 45.31%] [G loss: 0.697139]
8/8 [==============================] - 0s 5ms/step
1176 [D loss: 0.694086, acc.: 47.85%] [G loss: 0.696122]
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1177 [D loss: 0.693792, acc.: 47.46%] [G loss: 0.696327]
8/8 [==============================] - 0s 5ms/step
1178 [D loss: 0.693685, acc.: 46.88%] [G loss: 0.695549]
8/8 [==============================] - 0s 4ms/step
1179 [D loss: 0.694235, acc.: 41.60%] [G loss: 0.696013]
8/8 [==============================] - 0s 4ms/step
1180 [D loss: 0.694526, acc.: 42.58%] [G loss: 0.695431]
8/8 [==============================] - 0s 4ms/step
1181 [D loss: 0.693858, acc.: 44.14%] [G loss: 0.695749]
8/8 [==============================] - 0s 4ms/step
1182 [D loss: 0.694271, acc.: 44.53%] [G loss: 0.694593]
8/8 [==============================] - 0s 4ms/step
1183 [D loss: 0.694583, acc.: 42.58%] [G loss: 0.695608]
8/8 [==============================] - 0s 5ms/step
1184 [D loss: 0.694625, acc.: 43.16%] [G loss: 0.694187]
8/8 [==============================] - 0s 4ms/step
1185 [D loss: 0.693918, acc.: 45.12%] [G loss: 0.694538]
8/8 [==============================] - 0s 4ms/step
1186 [D loss: 0.694956, acc.: 39.45%] [G loss: 0.694739]
8/8 [==============================] - 0s 4ms/step
1187 [D loss: 0.694304, acc.: 44.34%] [G loss: 0.694510]
8/8 [==============================] - 0s 5ms/step
1188 [D loss: 0.694802, acc.: 40.43%] [G loss: 0.695307]
8/8 [==============================] - 0s 4ms/step
1189 [D loss: 0.694954, acc.: 40.43%] [G loss: 0.695045]
8/8 [==============================] - 0s 4ms/step
1190 [D loss: 0.694513, acc.: 42.19%] [G loss: 0.694505]
8/8 [==============================] - 0s 4ms/step
1191 [D loss: 0.694135, acc.: 43.95%] [G loss: 0.695854]
8/8 [==============================] - 0s 4ms/step
1192 [D loss: 0.694420, acc.: 41.80%] [G loss: 0.696156]
8/8 [==============================] - 0s 4ms/step
1193 [D loss: 0.693713, acc.: 47.46%] [G loss: 0.695851]
8/8 [==============================] - 0s 4ms/step
1194 [D loss: 0.694461, acc.: 46.09%] [G loss: 0.696273]
8/8 [==============================] - 0s 4ms/step
1195 [D loss: 0.694116, acc.: 44.73%] [G loss: 0.696501]
8/8 [==============================] - 0s 4ms/step
1196 [D loss: 0.693405, acc.: 50.00%] [G loss: 0.697067]
8/8 [==============================] - 0s 4ms/step
1197 [D loss: 0.694064, acc.: 45.90%] [G loss: 0.697731]
8/8 [==============================] - 0s 4ms/step
1198 [D loss: 0.693471, acc.: 45.51%] [G loss: 0.697284]
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1199 [D loss: 0.693663, acc.: 45.90%] [G loss: 0.698294]
8/8 [==============================] - 0s 4ms/step
1200 [D loss: 0.694037, acc.: 43.55%] [G loss: 0.698290]
1/1 [==============================] - 0s 18ms/step
8/8 [==============================] - 0s 5ms/step
1201 [D loss: 0.693826, acc.: 45.31%] [G loss: 0.697986]
8/8 [==============================] - 0s 4ms/step
1202 [D loss: 0.693131, acc.: 49.80%] [G loss: 0.698021]
8/8 [==============================] - 0s 5ms/step
1203 [D loss: 0.693516, acc.: 47.46%] [G loss: 0.698609]
8/8 [==============================] - 0s 4ms/step
1204 [D loss: 0.693655, acc.: 46.48%] [G loss: 0.697917]
8/8 [==============================] - 0s 5ms/step
1205 [D loss: 0.693712, acc.: 46.48%] [G loss: 0.698220]
8/8 [==============================] - 0s 4ms/step
1206 [D loss: 0.693333, acc.: 48.63%] [G loss: 0.698633]
8/8 [==============================] - 0s 5ms/step
1207 [D loss: 0.693690, acc.: 46.29%] [G loss: 0.698287]
8/8 [==============================] - 0s 5ms/step
1208 [D loss: 0.693684, acc.: 48.05%] [G loss: 0.698577]
8/8 [==============================] - 0s 4ms/step
1209 [D loss: 0.693667, acc.: 44.92%] [G loss: 0.698153]
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1210 [D loss: 0.693499, acc.: 48.24%] [G loss: 0.698476]
8/8 [==============================] - 0s 4ms/step
1211 [D loss: 0.694064, acc.: 47.07%] [G loss: 0.698820]
8/8 [==============================] - 0s 4ms/step
1212 [D loss: 0.693583, acc.: 49.41%] [G loss: 0.697091]
8/8 [==============================] - 0s 5ms/step
1213 [D loss: 0.693506, acc.: 47.27%] [G loss: 0.698413]
8/8 [==============================] - 0s 5ms/step
1214 [D loss: 0.693786, acc.: 45.31%] [G loss: 0.697240]
8/8 [==============================] - 0s 4ms/step
1215 [D loss: 0.693847, acc.: 46.48%] [G loss: 0.697098]
8/8 [==============================] - 0s 4ms/step
1216 [D loss: 0.693902, acc.: 45.90%] [G loss: 0.696523]
8/8 [==============================] - 0s 5ms/step
1217 [D loss: 0.694069, acc.: 44.92%] [G loss: 0.697542]
8/8 [==============================] - 0s 5ms/step
1218 [D loss: 0.693074, acc.: 49.41%] [G loss: 0.696852]
8/8 [==============================] - 0s 5ms/step
1219 [D loss: 0.694026, acc.: 44.92%] [G loss: 0.697408]
8/8 [==============================] - 0s 4ms/step
1220 [D loss: 0.693454, acc.: 47.85%] [G loss: 0.697075]
8/8 [==============================] - 0s 4ms/step
1221 [D loss: 0.694124, acc.: 44.53%] [G loss: 0.697151]
8/8 [==============================] - 0s 4ms/step
1222 [D loss: 0.694178, acc.: 43.75%] [G loss: 0.696913]
8/8 [==============================] - 0s 4ms/step
1223 [D loss: 0.694314, acc.: 45.12%] [G loss: 0.696597]
8/8 [==============================] - 0s 5ms/step
1224 [D loss: 0.694305, acc.: 45.31%] [G loss: 0.698278]
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1225 [D loss: 0.694260, acc.: 42.77%] [G loss: 0.698223]
8/8 [==============================] - 0s 4ms/step
1226 [D loss: 0.694169, acc.: 44.73%] [G loss: 0.697360]
8/8 [==============================] - 0s 5ms/step
1227 [D loss: 0.693855, acc.: 43.95%] [G loss: 0.698212]
8/8 [==============================] - 0s 5ms/step
1228 [D loss: 0.693783, acc.: 47.85%] [G loss: 0.697503]
8/8 [==============================] - 0s 4ms/step
1229 [D loss: 0.694552, acc.: 42.58%] [G loss: 0.697723]
8/8 [==============================] - 0s 5ms/step
1230 [D loss: 0.693468, acc.: 47.46%] [G loss: 0.698561]
8/8 [==============================] - 0s 4ms/step
1231 [D loss: 0.693550, acc.: 48.83%] [G loss: 0.697600]
8/8 [==============================] - 0s 4ms/step
1232 [D loss: 0.694351, acc.: 42.38%] [G loss: 0.698532]
8/8 [==============================] - 0s 5ms/step
1233 [D loss: 0.693885, acc.: 46.88%] [G loss: 0.698085]
8/8 [==============================] - 0s 4ms/step
1234 [D loss: 0.693783, acc.: 46.88%] [G loss: 0.699020]
8/8 [==============================] - 0s 5ms/step
1235 [D loss: 0.693290, acc.: 49.02%] [G loss: 0.698877]
8/8 [==============================] - 0s 4ms/step
1236 [D loss: 0.693969, acc.: 48.05%] [G loss: 0.698931]
8/8 [==============================] - 0s 5ms/step
1237 [D loss: 0.693332, acc.: 49.80%] [G loss: 0.699379]
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1238 [D loss: 0.694081, acc.: 47.07%] [G loss: 0.698726]
8/8 [==============================] - 0s 4ms/step
1239 [D loss: 0.694185, acc.: 45.51%] [G loss: 0.699182]
8/8 [==============================] - 0s 4ms/step
1240 [D loss: 0.693891, acc.: 46.88%] [G loss: 0.699539]
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1241 [D loss: 0.694421, acc.: 45.90%] [G loss: 0.699772]
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1242 [D loss: 0.693092, acc.: 48.24%] [G loss: 0.699636]
8/8 [==============================] - 0s 4ms/step
1243 [D loss: 0.693419, acc.: 50.59%] [G loss: 0.699669]
8/8 [==============================] - 0s 4ms/step
1244 [D loss: 0.693756, acc.: 47.46%] [G loss: 0.700210]
8/8 [==============================] - 0s 5ms/step
1245 [D loss: 0.693452, acc.: 49.80%] [G loss: 0.700345]
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1246 [D loss: 0.693823, acc.: 46.88%] [G loss: 0.700406]
8/8 [==============================] - 0s 4ms/step
1247 [D loss: 0.693541, acc.: 50.00%] [G loss: 0.700618]
8/8 [==============================] - 0s 5ms/step
1248 [D loss: 0.693615, acc.: 47.46%] [G loss: 0.700423]
8/8 [==============================] - 0s 5ms/step
1249 [D loss: 0.693137, acc.: 51.37%] [G loss: 0.699574]
8/8 [==============================] - 0s 4ms/step
1250 [D loss: 0.693653, acc.: 48.83%] [G loss: 0.699860]
1/1 [==============================] - 0s 19ms/step
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1251 [D loss: 0.693321, acc.: 48.05%] [G loss: 0.700345]
8/8 [==============================] - 0s 5ms/step
1252 [D loss: 0.693323, acc.: 49.61%] [G loss: 0.701157]
8/8 [==============================] - 0s 4ms/step
1253 [D loss: 0.693793, acc.: 50.39%] [G loss: 0.701106]
8/8 [==============================] - 0s 4ms/step
1254 [D loss: 0.693550, acc.: 49.02%] [G loss: 0.700321]
8/8 [==============================] - 0s 4ms/step
1255 [D loss: 0.693225, acc.: 50.00%] [G loss: 0.700915]
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1256 [D loss: 0.692940, acc.: 51.56%] [G loss: 0.700940]
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1257 [D loss: 0.693935, acc.: 47.85%] [G loss: 0.701109]
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1258 [D loss: 0.693243, acc.: 50.20%] [G loss: 0.700829]
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1259 [D loss: 0.693355, acc.: 49.61%] [G loss: 0.701560]
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1260 [D loss: 0.692927, acc.: 49.61%] [G loss: 0.701781]
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1261 [D loss: 0.693619, acc.: 50.59%] [G loss: 0.699859]
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1262 [D loss: 0.692636, acc.: 50.98%] [G loss: 0.701749]
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1263 [D loss: 0.693600, acc.: 46.88%] [G loss: 0.699936]
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1264 [D loss: 0.693506, acc.: 48.05%] [G loss: 0.700335]
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1265 [D loss: 0.694137, acc.: 44.53%] [G loss: 0.700234]
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1266 [D loss: 0.693957, acc.: 47.66%] [G loss: 0.700562]
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1267 [D loss: 0.692794, acc.: 50.20%] [G loss: 0.700169]
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1268 [D loss: 0.693554, acc.: 48.05%] [G loss: 0.700443]
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1269 [D loss: 0.693618, acc.: 48.83%] [G loss: 0.700050]
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1270 [D loss: 0.694494, acc.: 42.77%] [G loss: 0.701594]
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1271 [D loss: 0.693419, acc.: 47.27%] [G loss: 0.700065]
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1272 [D loss: 0.694009, acc.: 46.09%] [G loss: 0.700985]
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1273 [D loss: 0.693703, acc.: 47.07%] [G loss: 0.700557]
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1274 [D loss: 0.693727, acc.: 47.66%] [G loss: 0.699615]
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1275 [D loss: 0.693805, acc.: 44.92%] [G loss: 0.700789]
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1276 [D loss: 0.693678, acc.: 49.22%] [G loss: 0.699960]
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1277 [D loss: 0.693029, acc.: 49.80%] [G loss: 0.700784]
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1278 [D loss: 0.693510, acc.: 49.41%] [G loss: 0.700715]
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1279 [D loss: 0.693782, acc.: 47.07%] [G loss: 0.700110]
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1280 [D loss: 0.693365, acc.: 48.83%] [G loss: 0.699458]
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1281 [D loss: 0.693751, acc.: 47.27%] [G loss: 0.700749]
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1282 [D loss: 0.693646, acc.: 49.22%] [G loss: 0.699926]
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1283 [D loss: 0.693141, acc.: 50.98%] [G loss: 0.701425]
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1284 [D loss: 0.693753, acc.: 47.07%] [G loss: 0.701239]
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1285 [D loss: 0.694373, acc.: 42.38%] [G loss: 0.700259]
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1286 [D loss: 0.693322, acc.: 45.70%] [G loss: 0.701723]
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1287 [D loss: 0.693619, acc.: 47.46%] [G loss: 0.701060]
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1288 [D loss: 0.693640, acc.: 46.88%] [G loss: 0.702244]
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1289 [D loss: 0.693341, acc.: 44.73%] [G loss: 0.701985]
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1290 [D loss: 0.693231, acc.: 48.05%] [G loss: 0.701622]
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1291 [D loss: 0.693663, acc.: 47.46%] [G loss: 0.701325]
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1292 [D loss: 0.693944, acc.: 44.92%] [G loss: 0.701810]
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1293 [D loss: 0.693625, acc.: 44.14%] [G loss: 0.701890]
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1294 [D loss: 0.693915, acc.: 48.24%] [G loss: 0.701480]
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1295 [D loss: 0.694061, acc.: 44.73%] [G loss: 0.700919]
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1296 [D loss: 0.694048, acc.: 43.95%] [G loss: 0.701325]
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1297 [D loss: 0.692990, acc.: 46.88%] [G loss: 0.701316]
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1298 [D loss: 0.694178, acc.: 47.66%] [G loss: 0.701794]
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1299 [D loss: 0.693710, acc.: 45.51%] [G loss: 0.700009]
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1300 [D loss: 0.693712, acc.: 48.05%] [G loss: 0.700997]
1/1 [==============================] - 0s 17ms/step
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1301 [D loss: 0.694135, acc.: 45.12%] [G loss: 0.701970]
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1302 [D loss: 0.693566, acc.: 48.83%] [G loss: 0.701318]
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1303 [D loss: 0.693498, acc.: 47.27%] [G loss: 0.701071]
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1304 [D loss: 0.693507, acc.: 45.70%] [G loss: 0.701565]
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1305 [D loss: 0.694149, acc.: 46.88%] [G loss: 0.701505]
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1306 [D loss: 0.693802, acc.: 46.88%] [G loss: 0.700915]
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1307 [D loss: 0.694366, acc.: 46.48%] [G loss: 0.700752]
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1308 [D loss: 0.693549, acc.: 47.66%] [G loss: 0.700967]
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1309 [D loss: 0.693289, acc.: 47.66%] [G loss: 0.701240]
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1310 [D loss: 0.694196, acc.: 43.95%] [G loss: 0.700941]
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1311 [D loss: 0.694226, acc.: 48.05%] [G loss: 0.700377]
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1312 [D loss: 0.694025, acc.: 45.70%] [G loss: 0.700051]
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1313 [D loss: 0.693593, acc.: 49.61%] [G loss: 0.699946]
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1314 [D loss: 0.694564, acc.: 41.80%] [G loss: 0.700061]
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1315 [D loss: 0.694387, acc.: 45.51%] [G loss: 0.698997]
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1316 [D loss: 0.694046, acc.: 47.27%] [G loss: 0.699703]
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1317 [D loss: 0.693562, acc.: 48.44%] [G loss: 0.699206]
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1318 [D loss: 0.693785, acc.: 48.83%] [G loss: 0.698794]
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1319 [D loss: 0.693028, acc.: 52.34%] [G loss: 0.698961]
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1320 [D loss: 0.693433, acc.: 48.44%] [G loss: 0.698788]
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1321 [D loss: 0.693862, acc.: 45.90%] [G loss: 0.698981]
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1322 [D loss: 0.693299, acc.: 46.48%] [G loss: 0.697990]
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1323 [D loss: 0.693526, acc.: 47.46%] [G loss: 0.698859]
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1324 [D loss: 0.693471, acc.: 48.83%] [G loss: 0.699058]
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1325 [D loss: 0.693415, acc.: 48.44%] [G loss: 0.699239]
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1326 [D loss: 0.693160, acc.: 50.98%] [G loss: 0.699022]
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1327 [D loss: 0.692665, acc.: 54.30%] [G loss: 0.698951]
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1328 [D loss: 0.693221, acc.: 53.32%] [G loss: 0.699532]
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1329 [D loss: 0.693426, acc.: 47.85%] [G loss: 0.699140]
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1330 [D loss: 0.692545, acc.: 54.49%] [G loss: 0.698614]
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1331 [D loss: 0.693375, acc.: 48.05%] [G loss: 0.699643]
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1332 [D loss: 0.693167, acc.: 50.59%] [G loss: 0.697878]
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1333 [D loss: 0.692652, acc.: 56.25%] [G loss: 0.698954]
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1334 [D loss: 0.692573, acc.: 53.52%] [G loss: 0.697655]
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1335 [D loss: 0.692725, acc.: 54.10%] [G loss: 0.697729]
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1336 [D loss: 0.693341, acc.: 50.98%] [G loss: 0.698597]
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1337 [D loss: 0.693278, acc.: 50.59%] [G loss: 0.696784]
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1338 [D loss: 0.694000, acc.: 47.27%] [G loss: 0.696123]
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1339 [D loss: 0.693351, acc.: 51.56%] [G loss: 0.696781]
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1340 [D loss: 0.694769, acc.: 43.36%] [G loss: 0.695709]
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1341 [D loss: 0.694649, acc.: 41.02%] [G loss: 0.694373]
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1342 [D loss: 0.694398, acc.: 42.19%] [G loss: 0.694386]
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1343 [D loss: 0.694330, acc.: 45.31%] [G loss: 0.693334]
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1344 [D loss: 0.695172, acc.: 41.99%] [G loss: 0.693500]
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1345 [D loss: 0.694987, acc.: 41.60%] [G loss: 0.693591]
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1346 [D loss: 0.695063, acc.: 39.26%] [G loss: 0.693008]
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1347 [D loss: 0.694764, acc.: 40.82%] [G loss: 0.693148]
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1348 [D loss: 0.694545, acc.: 43.55%] [G loss: 0.692786]
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1349 [D loss: 0.694983, acc.: 40.82%] [G loss: 0.692580]
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1350 [D loss: 0.694711, acc.: 40.43%] [G loss: 0.693079]
1/1 [==============================] - 0s 18ms/step
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1351 [D loss: 0.694606, acc.: 41.21%] [G loss: 0.693874]
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1352 [D loss: 0.694526, acc.: 42.97%] [G loss: 0.694086]
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1353 [D loss: 0.693805, acc.: 45.70%] [G loss: 0.694325]
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1354 [D loss: 0.694388, acc.: 42.19%] [G loss: 0.694677]
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1355 [D loss: 0.693518, acc.: 47.27%] [G loss: 0.694521]
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1356 [D loss: 0.693927, acc.: 44.92%] [G loss: 0.695467]
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1357 [D loss: 0.693639, acc.: 48.24%] [G loss: 0.695852]
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1358 [D loss: 0.693551, acc.: 46.09%] [G loss: 0.695454]
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1359 [D loss: 0.693324, acc.: 48.44%] [G loss: 0.696420]
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1360 [D loss: 0.692723, acc.: 55.27%] [G loss: 0.696192]
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1361 [D loss: 0.693317, acc.: 50.59%] [G loss: 0.696957]
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1362 [D loss: 0.692789, acc.: 52.73%] [G loss: 0.696215]
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1363 [D loss: 0.692989, acc.: 50.98%] [G loss: 0.696445]
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1364 [D loss: 0.692709, acc.: 52.54%] [G loss: 0.697342]
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1365 [D loss: 0.692277, acc.: 55.47%] [G loss: 0.696931]
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1366 [D loss: 0.692579, acc.: 52.73%] [G loss: 0.697513]
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1367 [D loss: 0.692746, acc.: 51.37%] [G loss: 0.697284]
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1368 [D loss: 0.691957, acc.: 53.12%] [G loss: 0.697380]
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1369 [D loss: 0.693217, acc.: 49.02%] [G loss: 0.696837]
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1370 [D loss: 0.692226, acc.: 52.93%] [G loss: 0.697732]
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1371 [D loss: 0.692548, acc.: 51.76%] [G loss: 0.696421]
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1372 [D loss: 0.693000, acc.: 50.39%] [G loss: 0.697046]
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1373 [D loss: 0.692876, acc.: 50.98%] [G loss: 0.695437]
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1374 [D loss: 0.693131, acc.: 51.17%] [G loss: 0.695530]
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1375 [D loss: 0.693168, acc.: 50.20%] [G loss: 0.695072]
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1376 [D loss: 0.693209, acc.: 48.44%] [G loss: 0.694796]
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1377 [D loss: 0.693571, acc.: 49.61%] [G loss: 0.694096]
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1378 [D loss: 0.694257, acc.: 47.85%] [G loss: 0.694349]
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1379 [D loss: 0.694328, acc.: 45.31%] [G loss: 0.693848]
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1380 [D loss: 0.694482, acc.: 47.27%] [G loss: 0.693433]
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1381 [D loss: 0.693780, acc.: 48.44%] [G loss: 0.692767]
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1382 [D loss: 0.695809, acc.: 44.14%] [G loss: 0.693068]
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1383 [D loss: 0.695991, acc.: 40.62%] [G loss: 0.693423]
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1384 [D loss: 0.694855, acc.: 43.16%] [G loss: 0.695318]
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1385 [D loss: 0.695799, acc.: 40.62%] [G loss: 0.696003]
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1386 [D loss: 0.694637, acc.: 42.97%] [G loss: 0.694735]
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1387 [D loss: 0.694816, acc.: 43.36%] [G loss: 0.695683]
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1388 [D loss: 0.694757, acc.: 41.02%] [G loss: 0.695796]
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1389 [D loss: 0.693760, acc.: 42.97%] [G loss: 0.696748]
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1390 [D loss: 0.693896, acc.: 46.68%] [G loss: 0.696956]
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1391 [D loss: 0.694076, acc.: 46.09%] [G loss: 0.695950]
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1392 [D loss: 0.693657, acc.: 45.70%] [G loss: 0.695754]
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1393 [D loss: 0.694051, acc.: 45.51%] [G loss: 0.695938]
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1394 [D loss: 0.693612, acc.: 46.68%] [G loss: 0.696586]
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1395 [D loss: 0.693836, acc.: 45.31%] [G loss: 0.696195]
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1396 [D loss: 0.694167, acc.: 42.97%] [G loss: 0.696815]
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1397 [D loss: 0.693974, acc.: 42.19%] [G loss: 0.696250]
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1398 [D loss: 0.693850, acc.: 46.09%] [G loss: 0.695968]
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1399 [D loss: 0.693817, acc.: 44.73%] [G loss: 0.696319]
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1400 [D loss: 0.693900, acc.: 46.29%] [G loss: 0.695874]
1/1 [==============================] - 0s 16ms/step
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1401 [D loss: 0.693536, acc.: 45.12%] [G loss: 0.696228]
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1402 [D loss: 0.693903, acc.: 45.90%] [G loss: 0.696024]
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1403 [D loss: 0.693507, acc.: 46.48%] [G loss: 0.696313]
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1404 [D loss: 0.693826, acc.: 45.51%] [G loss: 0.694981]
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1405 [D loss: 0.693870, acc.: 45.70%] [G loss: 0.696317]
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1406 [D loss: 0.693450, acc.: 48.24%] [G loss: 0.697010]
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1407 [D loss: 0.693800, acc.: 45.90%] [G loss: 0.695592]
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1408 [D loss: 0.693569, acc.: 47.85%] [G loss: 0.695785]
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1409 [D loss: 0.693432, acc.: 49.22%] [G loss: 0.695924]
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1410 [D loss: 0.693386, acc.: 47.07%] [G loss: 0.695104]
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1411 [D loss: 0.693868, acc.: 43.75%] [G loss: 0.695477]
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1412 [D loss: 0.693274, acc.: 48.63%] [G loss: 0.695072]
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1413 [D loss: 0.692814, acc.: 51.17%] [G loss: 0.695233]
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1414 [D loss: 0.693469, acc.: 44.73%] [G loss: 0.695586]
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1415 [D loss: 0.693035, acc.: 53.12%] [G loss: 0.694674]
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1416 [D loss: 0.693444, acc.: 47.66%] [G loss: 0.694712]
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1417 [D loss: 0.693203, acc.: 47.66%] [G loss: 0.694481]
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1418 [D loss: 0.693099, acc.: 47.27%] [G loss: 0.694458]
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1419 [D loss: 0.692633, acc.: 56.45%] [G loss: 0.693907]
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1420 [D loss: 0.692944, acc.: 52.93%] [G loss: 0.694158]
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1421 [D loss: 0.692691, acc.: 50.20%] [G loss: 0.693818]
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1422 [D loss: 0.693430, acc.: 49.02%] [G loss: 0.693021]
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1423 [D loss: 0.692645, acc.: 51.17%] [G loss: 0.692293]
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1424 [D loss: 0.693402, acc.: 50.78%] [G loss: 0.693105]
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1425 [D loss: 0.693987, acc.: 46.48%] [G loss: 0.691367]
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1426 [D loss: 0.694302, acc.: 43.75%] [G loss: 0.692495]
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1427 [D loss: 0.693523, acc.: 47.66%] [G loss: 0.691210]
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1428 [D loss: 0.694239, acc.: 48.24%] [G loss: 0.692013]
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1429 [D loss: 0.694374, acc.: 45.31%] [G loss: 0.691080]
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1430 [D loss: 0.693840, acc.: 46.88%] [G loss: 0.691086]
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1431 [D loss: 0.694076, acc.: 46.68%] [G loss: 0.691656]
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1432 [D loss: 0.694218, acc.: 45.90%] [G loss: 0.691664]
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1433 [D loss: 0.694682, acc.: 44.92%] [G loss: 0.692147]
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1434 [D loss: 0.694217, acc.: 46.29%] [G loss: 0.692328]
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1435 [D loss: 0.693786, acc.: 47.07%] [G loss: 0.693011]
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1436 [D loss: 0.694459, acc.: 44.14%] [G loss: 0.693215]
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1437 [D loss: 0.693617, acc.: 49.80%] [G loss: 0.693529]
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1438 [D loss: 0.694363, acc.: 43.16%] [G loss: 0.693446]
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1439 [D loss: 0.693959, acc.: 43.75%] [G loss: 0.694204]
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1440 [D loss: 0.693838, acc.: 45.90%] [G loss: 0.694646]
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1441 [D loss: 0.694116, acc.: 44.92%] [G loss: 0.694941]
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1442 [D loss: 0.694184, acc.: 46.68%] [G loss: 0.695287]
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1443 [D loss: 0.694013, acc.: 45.90%] [G loss: 0.695297]
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1444 [D loss: 0.693698, acc.: 45.51%] [G loss: 0.695714]
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1445 [D loss: 0.693827, acc.: 46.09%] [G loss: 0.695489]
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1446 [D loss: 0.693660, acc.: 48.83%] [G loss: 0.696525]
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1447 [D loss: 0.693874, acc.: 47.27%] [G loss: 0.696436]
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1448 [D loss: 0.693571, acc.: 46.09%] [G loss: 0.696387]
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1449 [D loss: 0.693420, acc.: 49.61%] [G loss: 0.697295]
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1450 [D loss: 0.693376, acc.: 47.85%] [G loss: 0.697277]
1/1 [==============================] - 0s 16ms/step
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1451 [D loss: 0.693380, acc.: 49.61%] [G loss: 0.697182]
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1452 [D loss: 0.693675, acc.: 45.70%] [G loss: 0.697210]
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1453 [D loss: 0.693809, acc.: 44.34%] [G loss: 0.698084]
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1454 [D loss: 0.693696, acc.: 47.85%] [G loss: 0.698030]
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1455 [D loss: 0.693437, acc.: 47.07%] [G loss: 0.698229]
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1456 [D loss: 0.693615, acc.: 47.66%] [G loss: 0.697949]
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1457 [D loss: 0.693590, acc.: 46.88%] [G loss: 0.697941]
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1458 [D loss: 0.693716, acc.: 48.63%] [G loss: 0.698357]
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1459 [D loss: 0.693800, acc.: 48.05%] [G loss: 0.697321]
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1460 [D loss: 0.693974, acc.: 45.51%] [G loss: 0.699044]
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1461 [D loss: 0.693938, acc.: 45.70%] [G loss: 0.697952]
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1462 [D loss: 0.693384, acc.: 50.78%] [G loss: 0.698291]
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1463 [D loss: 0.693359, acc.: 50.20%] [G loss: 0.698127]
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1464 [D loss: 0.693470, acc.: 47.46%] [G loss: 0.698505]
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1465 [D loss: 0.693880, acc.: 48.83%] [G loss: 0.698361]
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1466 [D loss: 0.693720, acc.: 49.61%] [G loss: 0.696617]
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1467 [D loss: 0.693668, acc.: 45.51%] [G loss: 0.697679]
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1468 [D loss: 0.693269, acc.: 49.02%] [G loss: 0.697238]
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1469 [D loss: 0.693955, acc.: 47.07%] [G loss: 0.698400]
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1470 [D loss: 0.693541, acc.: 45.90%] [G loss: 0.697534]
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1471 [D loss: 0.693007, acc.: 51.76%] [G loss: 0.696159]
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1472 [D loss: 0.693258, acc.: 48.63%] [G loss: 0.696444]
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1473 [D loss: 0.693564, acc.: 47.07%] [G loss: 0.696757]
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1474 [D loss: 0.693058, acc.: 49.22%] [G loss: 0.697223]
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1475 [D loss: 0.693468, acc.: 48.24%] [G loss: 0.696036]
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1476 [D loss: 0.693848, acc.: 46.88%] [G loss: 0.696291]
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1477 [D loss: 0.693584, acc.: 48.44%] [G loss: 0.695429]
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1478 [D loss: 0.693408, acc.: 48.83%] [G loss: 0.695255]
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1479 [D loss: 0.693042, acc.: 48.44%] [G loss: 0.696056]
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1480 [D loss: 0.693651, acc.: 46.09%] [G loss: 0.695247]
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1481 [D loss: 0.693100, acc.: 49.80%] [G loss: 0.694486]
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1482 [D loss: 0.694255, acc.: 41.21%] [G loss: 0.695671]
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1483 [D loss: 0.694147, acc.: 45.12%] [G loss: 0.694271]
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1484 [D loss: 0.694324, acc.: 45.12%] [G loss: 0.694693]
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1485 [D loss: 0.693759, acc.: 49.22%] [G loss: 0.694776]
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1486 [D loss: 0.694221, acc.: 43.75%] [G loss: 0.694057]
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1487 [D loss: 0.695061, acc.: 41.21%] [G loss: 0.693758]
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1488 [D loss: 0.694966, acc.: 40.23%] [G loss: 0.693711]
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1489 [D loss: 0.695194, acc.: 38.87%] [G loss: 0.693989]
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1490 [D loss: 0.694656, acc.: 40.43%] [G loss: 0.694754]
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1491 [D loss: 0.695318, acc.: 37.11%] [G loss: 0.694056]
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1492 [D loss: 0.694621, acc.: 38.87%] [G loss: 0.694691]
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1493 [D loss: 0.694827, acc.: 41.02%] [G loss: 0.694279]
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1494 [D loss: 0.695023, acc.: 38.48%] [G loss: 0.694133]
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1495 [D loss: 0.695108, acc.: 39.45%] [G loss: 0.694725]
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1496 [D loss: 0.694451, acc.: 43.16%] [G loss: 0.695907]
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1497 [D loss: 0.694413, acc.: 42.19%] [G loss: 0.695967]
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1498 [D loss: 0.694078, acc.: 41.80%] [G loss: 0.695512]
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1499 [D loss: 0.693996, acc.: 42.77%] [G loss: 0.696497]
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1500 [D loss: 0.693996, acc.: 45.12%] [G loss: 0.696953]
1/1 [==============================] - 0s 17ms/step
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1501 [D loss: 0.693627, acc.: 46.48%] [G loss: 0.697646]
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1502 [D loss: 0.693736, acc.: 48.05%] [G loss: 0.697726]
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1503 [D loss: 0.693537, acc.: 47.27%] [G loss: 0.698491]
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1504 [D loss: 0.692976, acc.: 49.61%] [G loss: 0.698067]
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1505 [D loss: 0.693264, acc.: 50.39%] [G loss: 0.699303]
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1506 [D loss: 0.693280, acc.: 49.61%] [G loss: 0.699976]
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1507 [D loss: 0.692557, acc.: 51.37%] [G loss: 0.700680]
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1508 [D loss: 0.692419, acc.: 55.47%] [G loss: 0.700133]
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1509 [D loss: 0.692242, acc.: 55.86%] [G loss: 0.700332]
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1510 [D loss: 0.692728, acc.: 52.15%] [G loss: 0.699408]
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1511 [D loss: 0.692876, acc.: 51.37%] [G loss: 0.699781]
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1512 [D loss: 0.692010, acc.: 56.25%] [G loss: 0.700382]
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1513 [D loss: 0.692386, acc.: 52.73%] [G loss: 0.699208]
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1514 [D loss: 0.693302, acc.: 48.63%] [G loss: 0.699638]
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1515 [D loss: 0.692969, acc.: 50.00%] [G loss: 0.699147]
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1516 [D loss: 0.693133, acc.: 50.59%] [G loss: 0.698481]
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1517 [D loss: 0.692814, acc.: 52.93%] [G loss: 0.699286]
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1518 [D loss: 0.693348, acc.: 48.63%] [G loss: 0.699339]
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1519 [D loss: 0.693416, acc.: 49.61%] [G loss: 0.698891]
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1520 [D loss: 0.693577, acc.: 47.85%] [G loss: 0.698639]
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1521 [D loss: 0.693791, acc.: 47.07%] [G loss: 0.698487]
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1522 [D loss: 0.694294, acc.: 41.99%] [G loss: 0.699168]
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1523 [D loss: 0.694362, acc.: 45.51%] [G loss: 0.698464]
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1524 [D loss: 0.694358, acc.: 44.53%] [G loss: 0.698815]
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1525 [D loss: 0.694088, acc.: 46.29%] [G loss: 0.698891]
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1526 [D loss: 0.694410, acc.: 44.34%] [G loss: 0.699384]
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1527 [D loss: 0.693341, acc.: 48.63%] [G loss: 0.699406]
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1528 [D loss: 0.693498, acc.: 49.02%] [G loss: 0.699197]
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1529 [D loss: 0.692869, acc.: 50.00%] [G loss: 0.699467]
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1530 [D loss: 0.693999, acc.: 46.48%] [G loss: 0.700488]
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1531 [D loss: 0.694557, acc.: 45.90%] [G loss: 0.699361]
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1532 [D loss: 0.693506, acc.: 49.41%] [G loss: 0.699720]
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1533 [D loss: 0.694162, acc.: 47.46%] [G loss: 0.699284]
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1534 [D loss: 0.694020, acc.: 47.85%] [G loss: 0.698721]
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1535 [D loss: 0.694917, acc.: 45.12%] [G loss: 0.698339]
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1536 [D loss: 0.694167, acc.: 45.12%] [G loss: 0.697942]
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1537 [D loss: 0.693386, acc.: 49.22%] [G loss: 0.698361]
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1538 [D loss: 0.694514, acc.: 44.92%] [G loss: 0.697729]
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1539 [D loss: 0.694301, acc.: 45.12%] [G loss: 0.697216]
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1540 [D loss: 0.694573, acc.: 45.31%] [G loss: 0.696389]
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1541 [D loss: 0.694770, acc.: 42.19%] [G loss: 0.696274]
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1542 [D loss: 0.694169, acc.: 45.12%] [G loss: 0.696508]
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1543 [D loss: 0.694380, acc.: 43.36%] [G loss: 0.696150]
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1544 [D loss: 0.694251, acc.: 43.16%] [G loss: 0.697447]
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1545 [D loss: 0.693749, acc.: 46.88%] [G loss: 0.697127]
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1546 [D loss: 0.693780, acc.: 46.29%] [G loss: 0.696313]
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1547 [D loss: 0.693785, acc.: 46.88%] [G loss: 0.696419]
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1548 [D loss: 0.693562, acc.: 49.02%] [G loss: 0.696297]
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1549 [D loss: 0.693479, acc.: 49.02%] [G loss: 0.696482]
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1550 [D loss: 0.693798, acc.: 46.09%] [G loss: 0.696962]
1/1 [==============================] - 0s 18ms/step
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1551 [D loss: 0.693366, acc.: 49.61%] [G loss: 0.695922]
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1552 [D loss: 0.693768, acc.: 47.85%] [G loss: 0.695709]
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1553 [D loss: 0.693900, acc.: 44.14%] [G loss: 0.695129]
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1554 [D loss: 0.693506, acc.: 48.44%] [G loss: 0.695375]
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1555 [D loss: 0.693790, acc.: 47.46%] [G loss: 0.694751]
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1556 [D loss: 0.694172, acc.: 43.75%] [G loss: 0.694846]
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1557 [D loss: 0.694117, acc.: 41.60%] [G loss: 0.694201]
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1558 [D loss: 0.694091, acc.: 45.31%] [G loss: 0.694041]
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1559 [D loss: 0.694682, acc.: 41.99%] [G loss: 0.693429]
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1560 [D loss: 0.694259, acc.: 45.31%] [G loss: 0.693510]
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1561 [D loss: 0.694390, acc.: 41.80%] [G loss: 0.693291]
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1562 [D loss: 0.693965, acc.: 44.73%] [G loss: 0.693570]
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1563 [D loss: 0.693275, acc.: 50.39%] [G loss: 0.692958]
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1564 [D loss: 0.693959, acc.: 46.48%] [G loss: 0.693642]
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1565 [D loss: 0.693718, acc.: 44.53%] [G loss: 0.693420]
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1566 [D loss: 0.693575, acc.: 46.88%] [G loss: 0.693719]
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1567 [D loss: 0.693562, acc.: 49.22%] [G loss: 0.693285]
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1568 [D loss: 0.693484, acc.: 49.02%] [G loss: 0.693473]
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1569 [D loss: 0.693544, acc.: 48.83%] [G loss: 0.693302]
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1570 [D loss: 0.693364, acc.: 45.51%] [G loss: 0.693288]
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1571 [D loss: 0.693535, acc.: 47.85%] [G loss: 0.694852]
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1572 [D loss: 0.692660, acc.: 54.30%] [G loss: 0.694207]
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1573 [D loss: 0.693353, acc.: 47.07%] [G loss: 0.694743]
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1574 [D loss: 0.692598, acc.: 51.17%] [G loss: 0.696022]
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1575 [D loss: 0.693191, acc.: 49.41%] [G loss: 0.694814]
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1576 [D loss: 0.692750, acc.: 54.69%] [G loss: 0.696525]
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1577 [D loss: 0.692432, acc.: 54.49%] [G loss: 0.696351]
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1578 [D loss: 0.692543, acc.: 52.34%] [G loss: 0.695818]
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1579 [D loss: 0.692462, acc.: 54.69%] [G loss: 0.696500]
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1580 [D loss: 0.692606, acc.: 51.95%] [G loss: 0.697930]
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1581 [D loss: 0.692820, acc.: 53.52%] [G loss: 0.696084]
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1582 [D loss: 0.692737, acc.: 49.80%] [G loss: 0.696705]
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1583 [D loss: 0.693075, acc.: 49.41%] [G loss: 0.696811]
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1584 [D loss: 0.692796, acc.: 51.17%] [G loss: 0.696426]
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1585 [D loss: 0.692890, acc.: 54.49%] [G loss: 0.696164]
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1586 [D loss: 0.694163, acc.: 45.70%] [G loss: 0.696196]
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1587 [D loss: 0.694579, acc.: 42.19%] [G loss: 0.695320]
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1588 [D loss: 0.693856, acc.: 45.51%] [G loss: 0.695092]
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1589 [D loss: 0.694224, acc.: 45.90%] [G loss: 0.694188]
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1590 [D loss: 0.693903, acc.: 46.68%] [G loss: 0.694488]
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1591 [D loss: 0.695216, acc.: 39.06%] [G loss: 0.694102]
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1592 [D loss: 0.694803, acc.: 40.04%] [G loss: 0.693875]
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1593 [D loss: 0.694175, acc.: 46.09%] [G loss: 0.694676]
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1594 [D loss: 0.694658, acc.: 40.62%] [G loss: 0.694860]
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1595 [D loss: 0.694423, acc.: 44.53%] [G loss: 0.694222]
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1596 [D loss: 0.695051, acc.: 39.65%] [G loss: 0.694427]
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1597 [D loss: 0.694541, acc.: 42.19%] [G loss: 0.694669]
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1598 [D loss: 0.693808, acc.: 47.27%] [G loss: 0.695460]
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1599 [D loss: 0.693990, acc.: 43.75%] [G loss: 0.695307]
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1600 [D loss: 0.694231, acc.: 43.75%] [G loss: 0.695218]
1/1 [==============================] - 0s 17ms/step
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1601 [D loss: 0.693622, acc.: 45.51%] [G loss: 0.696007]
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1602 [D loss: 0.693544, acc.: 46.88%] [G loss: 0.696090]
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1603 [D loss: 0.693637, acc.: 45.70%] [G loss: 0.696030]
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1604 [D loss: 0.693335, acc.: 48.44%] [G loss: 0.695786]
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1605 [D loss: 0.694035, acc.: 40.82%] [G loss: 0.696586]
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1606 [D loss: 0.693517, acc.: 47.46%] [G loss: 0.696642]
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1607 [D loss: 0.693924, acc.: 45.31%] [G loss: 0.696853]
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1608 [D loss: 0.693612, acc.: 46.29%] [G loss: 0.696939]
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1609 [D loss: 0.692985, acc.: 49.41%] [G loss: 0.697525]
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1610 [D loss: 0.694471, acc.: 43.75%] [G loss: 0.697762]
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1611 [D loss: 0.692750, acc.: 51.56%] [G loss: 0.697533]
8/8 [==============================] - 0s 4ms/step
1612 [D loss: 0.693058, acc.: 50.20%] [G loss: 0.697914]
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1613 [D loss: 0.693312, acc.: 51.17%] [G loss: 0.697555]
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1614 [D loss: 0.692701, acc.: 54.69%] [G loss: 0.697056]
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1615 [D loss: 0.692942, acc.: 53.91%] [G loss: 0.697429]
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1616 [D loss: 0.693091, acc.: 51.76%] [G loss: 0.697805]
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1617 [D loss: 0.693365, acc.: 48.24%] [G loss: 0.697146]
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1618 [D loss: 0.693895, acc.: 50.20%] [G loss: 0.697657]
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1619 [D loss: 0.693209, acc.: 49.22%] [G loss: 0.696995]
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1620 [D loss: 0.693378, acc.: 46.09%] [G loss: 0.696868]
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1621 [D loss: 0.692776, acc.: 51.56%] [G loss: 0.697246]
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1622 [D loss: 0.694258, acc.: 43.55%] [G loss: 0.696536]
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1623 [D loss: 0.692724, acc.: 48.83%] [G loss: 0.695574]
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1624 [D loss: 0.693760, acc.: 45.51%] [G loss: 0.696568]
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1625 [D loss: 0.693482, acc.: 47.85%] [G loss: 0.696910]
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1626 [D loss: 0.692995, acc.: 52.54%] [G loss: 0.696654]
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1627 [D loss: 0.693517, acc.: 46.48%] [G loss: 0.696905]
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1628 [D loss: 0.693680, acc.: 45.31%] [G loss: 0.696277]
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1629 [D loss: 0.693656, acc.: 48.83%] [G loss: 0.694604]
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1630 [D loss: 0.693554, acc.: 50.00%] [G loss: 0.695455]
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1631 [D loss: 0.693873, acc.: 49.22%] [G loss: 0.695209]
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1632 [D loss: 0.693363, acc.: 49.22%] [G loss: 0.694905]
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1633 [D loss: 0.693658, acc.: 45.31%] [G loss: 0.695982]
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1634 [D loss: 0.693742, acc.: 47.66%] [G loss: 0.694869]
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1635 [D loss: 0.694007, acc.: 47.85%] [G loss: 0.694724]
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1636 [D loss: 0.693643, acc.: 47.85%] [G loss: 0.695168]
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1637 [D loss: 0.693944, acc.: 44.53%] [G loss: 0.693730]
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1638 [D loss: 0.694219, acc.: 46.48%] [G loss: 0.693983]
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1639 [D loss: 0.694128, acc.: 45.90%] [G loss: 0.694438]
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1640 [D loss: 0.695232, acc.: 37.30%] [G loss: 0.694004]
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1641 [D loss: 0.694029, acc.: 44.92%] [G loss: 0.694493]
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1642 [D loss: 0.694149, acc.: 43.75%] [G loss: 0.695809]
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1643 [D loss: 0.693785, acc.: 45.90%] [G loss: 0.694191]
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1644 [D loss: 0.694017, acc.: 47.27%] [G loss: 0.694730]
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1645 [D loss: 0.694574, acc.: 44.34%] [G loss: 0.694323]
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1646 [D loss: 0.693763, acc.: 49.22%] [G loss: 0.694970]
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1647 [D loss: 0.694251, acc.: 41.99%] [G loss: 0.695604]
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1648 [D loss: 0.693955, acc.: 44.92%] [G loss: 0.695186]
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1649 [D loss: 0.693590, acc.: 48.05%] [G loss: 0.696165]
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1650 [D loss: 0.693718, acc.: 44.92%] [G loss: 0.695921]
1/1 [==============================] - 0s 17ms/step
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1651 [D loss: 0.693129, acc.: 51.56%] [G loss: 0.696169]
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1652 [D loss: 0.693186, acc.: 48.05%] [G loss: 0.696797]
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1653 [D loss: 0.692899, acc.: 51.17%] [G loss: 0.696175]
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1654 [D loss: 0.693005, acc.: 51.17%] [G loss: 0.696818]
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1655 [D loss: 0.692632, acc.: 50.98%] [G loss: 0.696719]
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1656 [D loss: 0.693156, acc.: 49.41%] [G loss: 0.696851]
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1657 [D loss: 0.693352, acc.: 49.61%] [G loss: 0.696752]
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1658 [D loss: 0.692822, acc.: 53.52%] [G loss: 0.696144]
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1659 [D loss: 0.692239, acc.: 52.73%] [G loss: 0.696024]
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1660 [D loss: 0.693187, acc.: 50.59%] [G loss: 0.697195]
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1661 [D loss: 0.693843, acc.: 46.29%] [G loss: 0.694940]
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1662 [D loss: 0.693691, acc.: 48.05%] [G loss: 0.695234]
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1663 [D loss: 0.692534, acc.: 54.49%] [G loss: 0.696427]
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1664 [D loss: 0.693560, acc.: 47.85%] [G loss: 0.694853]
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1665 [D loss: 0.693113, acc.: 47.66%] [G loss: 0.695641]
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1666 [D loss: 0.692819, acc.: 51.17%] [G loss: 0.695294]
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1667 [D loss: 0.693414, acc.: 49.02%] [G loss: 0.695514]
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1668 [D loss: 0.693157, acc.: 51.76%] [G loss: 0.694748]
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1669 [D loss: 0.692977, acc.: 49.41%] [G loss: 0.695287]
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1670 [D loss: 0.693382, acc.: 48.05%] [G loss: 0.693895]
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1671 [D loss: 0.694170, acc.: 45.90%] [G loss: 0.694606]
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1672 [D loss: 0.694035, acc.: 46.29%] [G loss: 0.694364]
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1673 [D loss: 0.693973, acc.: 44.73%] [G loss: 0.693860]
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1674 [D loss: 0.694411, acc.: 43.75%] [G loss: 0.693766]
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1675 [D loss: 0.693757, acc.: 45.51%] [G loss: 0.694477]
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1676 [D loss: 0.693978, acc.: 44.53%] [G loss: 0.694445]
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1677 [D loss: 0.693979, acc.: 45.12%] [G loss: 0.694455]
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1678 [D loss: 0.694282, acc.: 43.36%] [G loss: 0.694243]
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1679 [D loss: 0.693943, acc.: 46.48%] [G loss: 0.694797]
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1680 [D loss: 0.694313, acc.: 40.04%] [G loss: 0.694555]
8/8 [==============================] - 0s 4ms/step
1681 [D loss: 0.694261, acc.: 43.16%] [G loss: 0.693421]
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1682 [D loss: 0.694210, acc.: 43.36%] [G loss: 0.694651]
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1683 [D loss: 0.694213, acc.: 44.14%] [G loss: 0.694018]
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1684 [D loss: 0.693857, acc.: 43.95%] [G loss: 0.695139]
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1685 [D loss: 0.693774, acc.: 46.09%] [G loss: 0.694634]
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1686 [D loss: 0.694164, acc.: 42.38%] [G loss: 0.695019]
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1687 [D loss: 0.693735, acc.: 47.27%] [G loss: 0.695278]
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1688 [D loss: 0.693859, acc.: 46.29%] [G loss: 0.694967]
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1689 [D loss: 0.693218, acc.: 47.07%] [G loss: 0.695753]
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1690 [D loss: 0.693355, acc.: 48.44%] [G loss: 0.696095]
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1691 [D loss: 0.693555, acc.: 47.07%] [G loss: 0.696099]
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1692 [D loss: 0.693499, acc.: 47.66%] [G loss: 0.696885]
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1693 [D loss: 0.693525, acc.: 46.68%] [G loss: 0.696876]
8/8 [==============================] - 0s 4ms/step
1694 [D loss: 0.692888, acc.: 50.39%] [G loss: 0.696800]
8/8 [==============================] - 0s 4ms/step
1695 [D loss: 0.694310, acc.: 46.48%] [G loss: 0.696630]
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1696 [D loss: 0.693801, acc.: 44.34%] [G loss: 0.697198]
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1697 [D loss: 0.693437, acc.: 46.68%] [G loss: 0.696535]
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1698 [D loss: 0.693749, acc.: 48.05%] [G loss: 0.696940]
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1699 [D loss: 0.693304, acc.: 48.05%] [G loss: 0.697118]
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1700 [D loss: 0.693645, acc.: 50.59%] [G loss: 0.696787]
1/1 [==============================] - 0s 19ms/step
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1701 [D loss: 0.694240, acc.: 46.48%] [G loss: 0.696498]
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1702 [D loss: 0.693735, acc.: 47.85%] [G loss: 0.697608]
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1703 [D loss: 0.693907, acc.: 46.09%] [G loss: 0.695958]
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1704 [D loss: 0.692760, acc.: 50.59%] [G loss: 0.695627]
8/8 [==============================] - 0s 4ms/step
1705 [D loss: 0.693535, acc.: 48.44%] [G loss: 0.695942]
8/8 [==============================] - 0s 4ms/step
1706 [D loss: 0.693526, acc.: 47.85%] [G loss: 0.695560]
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1707 [D loss: 0.693537, acc.: 49.41%] [G loss: 0.695285]
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1708 [D loss: 0.693632, acc.: 45.90%] [G loss: 0.695867]
8/8 [==============================] - 0s 4ms/step
1709 [D loss: 0.692898, acc.: 51.17%] [G loss: 0.695355]
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1710 [D loss: 0.694046, acc.: 45.31%] [G loss: 0.694981]
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1711 [D loss: 0.693180, acc.: 51.17%] [G loss: 0.694970]
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1712 [D loss: 0.694051, acc.: 45.90%] [G loss: 0.695578]
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1713 [D loss: 0.693703, acc.: 44.92%] [G loss: 0.695814]
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1714 [D loss: 0.693470, acc.: 47.07%] [G loss: 0.695626]
8/8 [==============================] - 0s 4ms/step
1715 [D loss: 0.692780, acc.: 50.39%] [G loss: 0.695694]
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1716 [D loss: 0.693307, acc.: 46.09%] [G loss: 0.695520]
8/8 [==============================] - 0s 5ms/step
1717 [D loss: 0.693847, acc.: 45.51%] [G loss: 0.694959]
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1718 [D loss: 0.693311, acc.: 47.46%] [G loss: 0.694935]
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1719 [D loss: 0.693111, acc.: 50.00%] [G loss: 0.694669]
8/8 [==============================] - 0s 4ms/step
1720 [D loss: 0.693027, acc.: 51.56%] [G loss: 0.695485]
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1721 [D loss: 0.692786, acc.: 50.00%] [G loss: 0.695043]
8/8 [==============================] - 0s 4ms/step
1722 [D loss: 0.692629, acc.: 53.52%] [G loss: 0.694611]
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1723 [D loss: 0.693377, acc.: 48.63%] [G loss: 0.694950]
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1724 [D loss: 0.692998, acc.: 50.20%] [G loss: 0.695247]
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1725 [D loss: 0.693560, acc.: 47.66%] [G loss: 0.694063]
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1726 [D loss: 0.693284, acc.: 49.61%] [G loss: 0.694212]
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1727 [D loss: 0.693141, acc.: 51.56%] [G loss: 0.694899]
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1728 [D loss: 0.693043, acc.: 52.54%] [G loss: 0.694167]
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1729 [D loss: 0.693682, acc.: 49.22%] [G loss: 0.692985]
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1730 [D loss: 0.693615, acc.: 46.68%] [G loss: 0.692885]
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1731 [D loss: 0.694154, acc.: 44.14%] [G loss: 0.693260]
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1732 [D loss: 0.694121, acc.: 44.14%] [G loss: 0.692402]
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1733 [D loss: 0.694381, acc.: 45.12%] [G loss: 0.692856]
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1734 [D loss: 0.693296, acc.: 50.39%] [G loss: 0.692270]
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1735 [D loss: 0.695145, acc.: 42.19%] [G loss: 0.692898]
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1736 [D loss: 0.694148, acc.: 44.92%] [G loss: 0.691783]
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1737 [D loss: 0.694017, acc.: 45.90%] [G loss: 0.691666]
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1738 [D loss: 0.695115, acc.: 42.19%] [G loss: 0.692074]
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1739 [D loss: 0.694880, acc.: 42.97%] [G loss: 0.691317]
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1740 [D loss: 0.695125, acc.: 40.43%] [G loss: 0.692294]
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1741 [D loss: 0.694681, acc.: 42.19%] [G loss: 0.691110]
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1742 [D loss: 0.694925, acc.: 40.82%] [G loss: 0.693405]
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1743 [D loss: 0.694727, acc.: 42.38%] [G loss: 0.694158]
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1744 [D loss: 0.694280, acc.: 44.14%] [G loss: 0.695239]
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1745 [D loss: 0.694292, acc.: 42.38%] [G loss: 0.694198]
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1746 [D loss: 0.693597, acc.: 48.05%] [G loss: 0.695631]
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1747 [D loss: 0.693986, acc.: 48.05%] [G loss: 0.695865]
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1748 [D loss: 0.693836, acc.: 44.92%] [G loss: 0.695432]
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1749 [D loss: 0.693365, acc.: 47.66%] [G loss: 0.696498]
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1750 [D loss: 0.693388, acc.: 49.22%] [G loss: 0.696516]
1/1 [==============================] - 0s 19ms/step
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1751 [D loss: 0.693887, acc.: 48.24%] [G loss: 0.696975]
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1752 [D loss: 0.693075, acc.: 48.63%] [G loss: 0.697805]
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1753 [D loss: 0.692417, acc.: 53.52%] [G loss: 0.698082]
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1754 [D loss: 0.692698, acc.: 51.76%] [G loss: 0.698648]
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1755 [D loss: 0.691994, acc.: 52.54%] [G loss: 0.699085]
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1756 [D loss: 0.692378, acc.: 53.32%] [G loss: 0.699809]
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1757 [D loss: 0.692922, acc.: 48.44%] [G loss: 0.699405]
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1758 [D loss: 0.692655, acc.: 51.17%] [G loss: 0.699895]
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1759 [D loss: 0.692524, acc.: 53.12%] [G loss: 0.699273]
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1760 [D loss: 0.692191, acc.: 52.93%] [G loss: 0.700480]
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1761 [D loss: 0.692756, acc.: 51.17%] [G loss: 0.700054]
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1762 [D loss: 0.693057, acc.: 51.17%] [G loss: 0.700170]
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1763 [D loss: 0.693091, acc.: 46.68%] [G loss: 0.697897]
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1764 [D loss: 0.693311, acc.: 49.02%] [G loss: 0.699109]
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1765 [D loss: 0.693923, acc.: 46.29%] [G loss: 0.698404]
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1766 [D loss: 0.694411, acc.: 43.55%] [G loss: 0.697256]
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1767 [D loss: 0.693862, acc.: 47.27%] [G loss: 0.697202]
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1768 [D loss: 0.694104, acc.: 44.53%] [G loss: 0.697156]
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1769 [D loss: 0.694134, acc.: 44.34%] [G loss: 0.696370]
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1770 [D loss: 0.694558, acc.: 40.82%] [G loss: 0.696797]
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1771 [D loss: 0.694663, acc.: 40.43%] [G loss: 0.696496]
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1772 [D loss: 0.694797, acc.: 39.26%] [G loss: 0.696147]
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1773 [D loss: 0.694367, acc.: 42.97%] [G loss: 0.695946]
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1774 [D loss: 0.694693, acc.: 42.77%] [G loss: 0.695641]
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1775 [D loss: 0.694605, acc.: 42.77%] [G loss: 0.695013]
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1776 [D loss: 0.694227, acc.: 42.58%] [G loss: 0.694286]
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1777 [D loss: 0.694693, acc.: 43.16%] [G loss: 0.694666]
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1778 [D loss: 0.694342, acc.: 43.95%] [G loss: 0.694171]
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1779 [D loss: 0.693980, acc.: 43.95%] [G loss: 0.694569]
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1780 [D loss: 0.693778, acc.: 45.90%] [G loss: 0.694580]
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1781 [D loss: 0.693953, acc.: 44.92%] [G loss: 0.694435]
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1782 [D loss: 0.693705, acc.: 47.27%] [G loss: 0.694606]
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1783 [D loss: 0.693483, acc.: 47.66%] [G loss: 0.694348]
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1784 [D loss: 0.693616, acc.: 49.80%] [G loss: 0.695057]
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1785 [D loss: 0.693852, acc.: 48.05%] [G loss: 0.694802]
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1786 [D loss: 0.692904, acc.: 52.93%] [G loss: 0.695399]
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1787 [D loss: 0.693198, acc.: 51.17%] [G loss: 0.695218]
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1788 [D loss: 0.693197, acc.: 50.00%] [G loss: 0.694524]
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1789 [D loss: 0.692754, acc.: 54.49%] [G loss: 0.695305]
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1790 [D loss: 0.692961, acc.: 52.73%] [G loss: 0.696468]
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1791 [D loss: 0.693042, acc.: 51.37%] [G loss: 0.694522]
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1792 [D loss: 0.692435, acc.: 54.49%] [G loss: 0.695038]
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1793 [D loss: 0.693458, acc.: 48.24%] [G loss: 0.696069]
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1794 [D loss: 0.692583, acc.: 54.49%] [G loss: 0.694815]
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1795 [D loss: 0.693243, acc.: 48.44%] [G loss: 0.695351]
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1796 [D loss: 0.693226, acc.: 49.22%] [G loss: 0.695841]
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1797 [D loss: 0.693239, acc.: 46.88%] [G loss: 0.694726]
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1798 [D loss: 0.693965, acc.: 46.88%] [G loss: 0.694349]
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1799 [D loss: 0.693313, acc.: 49.41%] [G loss: 0.693874]
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1800 [D loss: 0.694192, acc.: 43.36%] [G loss: 0.694085]
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1801 [D loss: 0.694609, acc.: 43.16%] [G loss: 0.693772]
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1802 [D loss: 0.694576, acc.: 42.77%] [G loss: 0.693474]
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1803 [D loss: 0.693865, acc.: 47.66%] [G loss: 0.693262]
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1804 [D loss: 0.694995, acc.: 37.89%] [G loss: 0.692736]
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1805 [D loss: 0.695192, acc.: 40.43%] [G loss: 0.692459]
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1806 [D loss: 0.695038, acc.: 41.60%] [G loss: 0.692287]
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1807 [D loss: 0.695020, acc.: 40.23%] [G loss: 0.692715]
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1808 [D loss: 0.695093, acc.: 38.09%] [G loss: 0.692888]
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1809 [D loss: 0.694425, acc.: 44.34%] [G loss: 0.693550]
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1810 [D loss: 0.694786, acc.: 40.43%] [G loss: 0.692781]
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1811 [D loss: 0.694544, acc.: 42.19%] [G loss: 0.693871]
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1812 [D loss: 0.694818, acc.: 41.99%] [G loss: 0.693384]
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1813 [D loss: 0.694313, acc.: 43.55%] [G loss: 0.693977]
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1814 [D loss: 0.693960, acc.: 46.29%] [G loss: 0.694016]
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1815 [D loss: 0.693964, acc.: 44.53%] [G loss: 0.694276]
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1816 [D loss: 0.693952, acc.: 43.36%] [G loss: 0.694956]
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1817 [D loss: 0.693627, acc.: 47.07%] [G loss: 0.695320]
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1818 [D loss: 0.693496, acc.: 44.73%] [G loss: 0.696666]
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1819 [D loss: 0.693606, acc.: 49.61%] [G loss: 0.696899]
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1820 [D loss: 0.692640, acc.: 53.91%] [G loss: 0.696823]
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1821 [D loss: 0.693022, acc.: 52.73%] [G loss: 0.697536]
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1822 [D loss: 0.693253, acc.: 48.63%] [G loss: 0.697629]
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1823 [D loss: 0.692661, acc.: 54.49%] [G loss: 0.698004]
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1824 [D loss: 0.692106, acc.: 56.45%] [G loss: 0.698227]
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1825 [D loss: 0.692412, acc.: 53.12%] [G loss: 0.698985]
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1826 [D loss: 0.692309, acc.: 54.30%] [G loss: 0.697762]
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1827 [D loss: 0.692116, acc.: 55.66%] [G loss: 0.698716]
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1828 [D loss: 0.692384, acc.: 51.76%] [G loss: 0.698808]
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1829 [D loss: 0.692470, acc.: 51.95%] [G loss: 0.698186]
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1830 [D loss: 0.692511, acc.: 51.17%] [G loss: 0.697958]
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1831 [D loss: 0.693010, acc.: 50.78%] [G loss: 0.698215]
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1832 [D loss: 0.693286, acc.: 50.59%] [G loss: 0.697316]
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1833 [D loss: 0.692876, acc.: 52.93%] [G loss: 0.696116]
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1834 [D loss: 0.693071, acc.: 49.22%] [G loss: 0.695496]
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1835 [D loss: 0.694078, acc.: 46.29%] [G loss: 0.695196]
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1836 [D loss: 0.693664, acc.: 49.80%] [G loss: 0.693858]
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1837 [D loss: 0.694331, acc.: 45.31%] [G loss: 0.694991]
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1838 [D loss: 0.694249, acc.: 44.14%] [G loss: 0.694911]
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1839 [D loss: 0.694797, acc.: 43.16%] [G loss: 0.693467]
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1840 [D loss: 0.693911, acc.: 45.12%] [G loss: 0.693799]
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1841 [D loss: 0.693467, acc.: 48.24%] [G loss: 0.693189]
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1842 [D loss: 0.694814, acc.: 42.19%] [G loss: 0.693772]
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1843 [D loss: 0.694318, acc.: 45.12%] [G loss: 0.693822]
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1844 [D loss: 0.694257, acc.: 44.73%] [G loss: 0.693843]
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1845 [D loss: 0.694628, acc.: 44.73%] [G loss: 0.693636]
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1846 [D loss: 0.693703, acc.: 48.05%] [G loss: 0.694007]
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1847 [D loss: 0.694496, acc.: 46.09%] [G loss: 0.694060]
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1848 [D loss: 0.694381, acc.: 45.51%] [G loss: 0.692334]
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1849 [D loss: 0.694638, acc.: 42.58%] [G loss: 0.694317]
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1850 [D loss: 0.693885, acc.: 43.16%] [G loss: 0.694118]
1/1 [==============================] - 0s 17ms/step
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1851 [D loss: 0.694449, acc.: 41.60%] [G loss: 0.693907]
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1852 [D loss: 0.694110, acc.: 42.77%] [G loss: 0.694788]
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1853 [D loss: 0.693730, acc.: 44.53%] [G loss: 0.694546]
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1854 [D loss: 0.693336, acc.: 47.07%] [G loss: 0.694987]
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1855 [D loss: 0.694243, acc.: 43.36%] [G loss: 0.694572]
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1856 [D loss: 0.694250, acc.: 41.41%] [G loss: 0.694133]
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1857 [D loss: 0.694150, acc.: 43.95%] [G loss: 0.693667]
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1858 [D loss: 0.694153, acc.: 45.12%] [G loss: 0.695237]
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1859 [D loss: 0.694756, acc.: 41.41%] [G loss: 0.695258]
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1860 [D loss: 0.693679, acc.: 46.68%] [G loss: 0.695314]
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1861 [D loss: 0.693905, acc.: 46.68%] [G loss: 0.695260]
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1862 [D loss: 0.694182, acc.: 47.27%] [G loss: 0.695879]
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1863 [D loss: 0.693893, acc.: 47.07%] [G loss: 0.696057]
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1864 [D loss: 0.693414, acc.: 46.68%] [G loss: 0.696461]
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1865 [D loss: 0.693174, acc.: 49.02%] [G loss: 0.696994]
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1866 [D loss: 0.693238, acc.: 47.46%] [G loss: 0.697546]
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1867 [D loss: 0.693057, acc.: 54.49%] [G loss: 0.697897]
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1868 [D loss: 0.693968, acc.: 45.70%] [G loss: 0.697779]
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1869 [D loss: 0.693105, acc.: 49.41%] [G loss: 0.698096]
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1870 [D loss: 0.692511, acc.: 53.71%] [G loss: 0.698832]
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1871 [D loss: 0.692616, acc.: 53.32%] [G loss: 0.699794]
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1872 [D loss: 0.693439, acc.: 50.59%] [G loss: 0.699545]
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1873 [D loss: 0.692743, acc.: 49.41%] [G loss: 0.698610]
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1874 [D loss: 0.693317, acc.: 47.46%] [G loss: 0.699717]
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1875 [D loss: 0.692683, acc.: 54.69%] [G loss: 0.699349]
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1876 [D loss: 0.693426, acc.: 48.05%] [G loss: 0.698992]
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1877 [D loss: 0.693096, acc.: 50.59%] [G loss: 0.699203]
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1878 [D loss: 0.693069, acc.: 49.80%] [G loss: 0.699811]
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1879 [D loss: 0.693525, acc.: 49.41%] [G loss: 0.699362]
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1880 [D loss: 0.694170, acc.: 43.55%] [G loss: 0.699420]
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1881 [D loss: 0.694047, acc.: 47.85%] [G loss: 0.698637]
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1882 [D loss: 0.694067, acc.: 46.09%] [G loss: 0.698718]
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1883 [D loss: 0.693812, acc.: 47.07%] [G loss: 0.698913]
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1884 [D loss: 0.694023, acc.: 47.07%] [G loss: 0.698893]
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1885 [D loss: 0.695025, acc.: 43.55%] [G loss: 0.697754]
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1886 [D loss: 0.694046, acc.: 46.09%] [G loss: 0.698729]
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1887 [D loss: 0.693719, acc.: 46.68%] [G loss: 0.697818]
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1888 [D loss: 0.694681, acc.: 44.73%] [G loss: 0.698219]
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1889 [D loss: 0.693951, acc.: 50.00%] [G loss: 0.698493]
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1890 [D loss: 0.694528, acc.: 44.53%] [G loss: 0.698193]
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1891 [D loss: 0.694394, acc.: 44.73%] [G loss: 0.697692]
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1892 [D loss: 0.693717, acc.: 48.44%] [G loss: 0.698337]
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1893 [D loss: 0.694283, acc.: 43.36%] [G loss: 0.698831]
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1894 [D loss: 0.693533, acc.: 49.80%] [G loss: 0.697825]
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1895 [D loss: 0.693776, acc.: 49.02%] [G loss: 0.698505]
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1896 [D loss: 0.693301, acc.: 49.02%] [G loss: 0.698818]
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1897 [D loss: 0.693310, acc.: 47.66%] [G loss: 0.698166]
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1898 [D loss: 0.693659, acc.: 48.24%] [G loss: 0.698718]
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1899 [D loss: 0.693505, acc.: 48.63%] [G loss: 0.698386]
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1900 [D loss: 0.693024, acc.: 51.37%] [G loss: 0.698198]
1/1 [==============================] - 0s 17ms/step
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1901 [D loss: 0.692778, acc.: 52.34%] [G loss: 0.698607]
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1902 [D loss: 0.692674, acc.: 52.93%] [G loss: 0.698817]
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1903 [D loss: 0.693044, acc.: 50.98%] [G loss: 0.698409]
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1904 [D loss: 0.692818, acc.: 50.20%] [G loss: 0.698656]
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1905 [D loss: 0.692952, acc.: 51.37%] [G loss: 0.698078]
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1906 [D loss: 0.693460, acc.: 46.09%] [G loss: 0.697544]
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1907 [D loss: 0.693870, acc.: 48.24%] [G loss: 0.696814]
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1908 [D loss: 0.693590, acc.: 49.02%] [G loss: 0.696618]
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1909 [D loss: 0.693151, acc.: 52.15%] [G loss: 0.696139]
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1910 [D loss: 0.694033, acc.: 44.73%] [G loss: 0.695992]
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1911 [D loss: 0.693981, acc.: 46.48%] [G loss: 0.695944]
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1912 [D loss: 0.693724, acc.: 45.12%] [G loss: 0.694629]
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1913 [D loss: 0.693784, acc.: 48.05%] [G loss: 0.695311]
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1914 [D loss: 0.693927, acc.: 44.92%] [G loss: 0.694862]
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1915 [D loss: 0.693900, acc.: 44.53%] [G loss: 0.694197]
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1916 [D loss: 0.693770, acc.: 46.68%] [G loss: 0.694140]
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1917 [D loss: 0.694065, acc.: 46.09%] [G loss: 0.693324]
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1918 [D loss: 0.693645, acc.: 48.24%] [G loss: 0.693853]
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1919 [D loss: 0.694241, acc.: 43.95%] [G loss: 0.694574]
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1920 [D loss: 0.694097, acc.: 44.14%] [G loss: 0.693025]
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1921 [D loss: 0.693638, acc.: 47.46%] [G loss: 0.693584]
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1922 [D loss: 0.693443, acc.: 48.24%] [G loss: 0.693270]
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1923 [D loss: 0.693627, acc.: 44.53%] [G loss: 0.693937]
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1924 [D loss: 0.693687, acc.: 44.92%] [G loss: 0.694277]
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1925 [D loss: 0.692999, acc.: 46.48%] [G loss: 0.692956]
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1926 [D loss: 0.693929, acc.: 45.90%] [G loss: 0.693827]
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1927 [D loss: 0.693983, acc.: 43.16%] [G loss: 0.694469]
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1928 [D loss: 0.693269, acc.: 47.46%] [G loss: 0.694781]
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1929 [D loss: 0.693850, acc.: 44.53%] [G loss: 0.695018]
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1930 [D loss: 0.692924, acc.: 50.00%] [G loss: 0.695325]
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1931 [D loss: 0.692846, acc.: 49.02%] [G loss: 0.694704]
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1932 [D loss: 0.693159, acc.: 47.27%] [G loss: 0.696195]
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1933 [D loss: 0.692964, acc.: 50.78%] [G loss: 0.695088]
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1934 [D loss: 0.692618, acc.: 51.76%] [G loss: 0.694808]
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1935 [D loss: 0.692670, acc.: 51.76%] [G loss: 0.695232]
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1936 [D loss: 0.693123, acc.: 52.54%] [G loss: 0.695687]
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1937 [D loss: 0.693031, acc.: 50.98%] [G loss: 0.694668]
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1938 [D loss: 0.693357, acc.: 48.24%] [G loss: 0.696037]
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1939 [D loss: 0.693133, acc.: 49.41%] [G loss: 0.695710]
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1940 [D loss: 0.693041, acc.: 50.78%] [G loss: 0.695358]
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1941 [D loss: 0.693428, acc.: 48.05%] [G loss: 0.694576]
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1942 [D loss: 0.693400, acc.: 46.68%] [G loss: 0.695081]
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1943 [D loss: 0.693747, acc.: 48.83%] [G loss: 0.694672]
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1944 [D loss: 0.695012, acc.: 42.58%] [G loss: 0.694004]
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1945 [D loss: 0.694187, acc.: 47.66%] [G loss: 0.692957]
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1946 [D loss: 0.694774, acc.: 42.19%] [G loss: 0.693876]
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1947 [D loss: 0.693837, acc.: 48.24%] [G loss: 0.693325]
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1948 [D loss: 0.694129, acc.: 44.34%] [G loss: 0.693284]
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1949 [D loss: 0.694226, acc.: 43.36%] [G loss: 0.692680]
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1950 [D loss: 0.693976, acc.: 44.53%] [G loss: 0.692886]
1/1 [==============================] - 0s 19ms/step
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1951 [D loss: 0.694569, acc.: 41.80%] [G loss: 0.693673]
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1952 [D loss: 0.694153, acc.: 43.16%] [G loss: 0.693799]
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1953 [D loss: 0.694233, acc.: 43.75%] [G loss: 0.692826]
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1954 [D loss: 0.693896, acc.: 41.80%] [G loss: 0.693006]
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1955 [D loss: 0.693710, acc.: 44.53%] [G loss: 0.693219]
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1956 [D loss: 0.694427, acc.: 42.19%] [G loss: 0.693884]
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1957 [D loss: 0.693243, acc.: 49.02%] [G loss: 0.694388]
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1958 [D loss: 0.694055, acc.: 43.75%] [G loss: 0.694647]
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1959 [D loss: 0.693279, acc.: 47.27%] [G loss: 0.693976]
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1960 [D loss: 0.692950, acc.: 50.00%] [G loss: 0.694549]
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1961 [D loss: 0.693348, acc.: 46.09%] [G loss: 0.694773]
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1962 [D loss: 0.693345, acc.: 46.68%] [G loss: 0.695070]
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1963 [D loss: 0.692746, acc.: 51.76%] [G loss: 0.695209]
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1964 [D loss: 0.692803, acc.: 51.95%] [G loss: 0.695448]
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1965 [D loss: 0.692881, acc.: 50.00%] [G loss: 0.695800]
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1966 [D loss: 0.692845, acc.: 52.34%] [G loss: 0.696352]
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1967 [D loss: 0.692351, acc.: 55.66%] [G loss: 0.696230]
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1968 [D loss: 0.692826, acc.: 54.10%] [G loss: 0.696461]
8/8 [==============================] - 0s 5ms/step
1969 [D loss: 0.692496, acc.: 52.34%] [G loss: 0.696033]
8/8 [==============================] - 0s 4ms/step
1970 [D loss: 0.692184, acc.: 55.47%] [G loss: 0.696979]
8/8 [==============================] - 0s 5ms/step
1971 [D loss: 0.692501, acc.: 55.27%] [G loss: 0.696409]
8/8 [==============================] - 0s 5ms/step
1972 [D loss: 0.693190, acc.: 48.24%] [G loss: 0.696241]
8/8 [==============================] - 0s 5ms/step
1973 [D loss: 0.693209, acc.: 48.44%] [G loss: 0.696603]
8/8 [==============================] - 0s 5ms/step
1974 [D loss: 0.693116, acc.: 50.39%] [G loss: 0.695952]
8/8 [==============================] - 0s 5ms/step
1975 [D loss: 0.693369, acc.: 50.98%] [G loss: 0.696028]
8/8 [==============================] - 0s 4ms/step
1976 [D loss: 0.693889, acc.: 46.88%] [G loss: 0.695078]
8/8 [==============================] - 0s 5ms/step
1977 [D loss: 0.694314, acc.: 43.16%] [G loss: 0.695740]
8/8 [==============================] - 0s 4ms/step
1978 [D loss: 0.694530, acc.: 42.19%] [G loss: 0.694959]
8/8 [==============================] - 0s 4ms/step
1979 [D loss: 0.694878, acc.: 39.84%] [G loss: 0.695229]
8/8 [==============================] - 0s 5ms/step
1980 [D loss: 0.694549, acc.: 40.82%] [G loss: 0.695106]
8/8 [==============================] - 0s 5ms/step
1981 [D loss: 0.694287, acc.: 42.19%] [G loss: 0.695393]
8/8 [==============================] - 0s 4ms/step
1982 [D loss: 0.694666, acc.: 39.26%] [G loss: 0.695425]
8/8 [==============================] - 0s 4ms/step
1983 [D loss: 0.694657, acc.: 40.82%] [G loss: 0.695801]
8/8 [==============================] - 0s 5ms/step
1984 [D loss: 0.694894, acc.: 35.35%] [G loss: 0.696460]
8/8 [==============================] - 0s 5ms/step
1985 [D loss: 0.694444, acc.: 42.58%] [G loss: 0.695778]
8/8 [==============================] - 0s 4ms/step
1986 [D loss: 0.694471, acc.: 40.43%] [G loss: 0.696733]
8/8 [==============================] - 0s 4ms/step
1987 [D loss: 0.694093, acc.: 41.60%] [G loss: 0.696713]
8/8 [==============================] - 0s 4ms/step
1988 [D loss: 0.693954, acc.: 45.31%] [G loss: 0.697847]
8/8 [==============================] - 0s 5ms/step
1989 [D loss: 0.693844, acc.: 43.16%] [G loss: 0.697348]
8/8 [==============================] - 0s 5ms/step
1990 [D loss: 0.693392, acc.: 48.44%] [G loss: 0.698308]
8/8 [==============================] - 0s 5ms/step
1991 [D loss: 0.693729, acc.: 43.95%] [G loss: 0.697798]
8/8 [==============================] - 0s 5ms/step
1992 [D loss: 0.693680, acc.: 44.34%] [G loss: 0.699765]
8/8 [==============================] - 0s 5ms/step
1993 [D loss: 0.693683, acc.: 48.63%] [G loss: 0.698920]
8/8 [==============================] - 0s 4ms/step
1994 [D loss: 0.693953, acc.: 44.92%] [G loss: 0.699228]
8/8 [==============================] - 0s 4ms/step
1995 [D loss: 0.693692, acc.: 46.29%] [G loss: 0.699341]
8/8 [==============================] - 0s 4ms/step
1996 [D loss: 0.693234, acc.: 49.02%] [G loss: 0.699851]
8/8 [==============================] - 0s 4ms/step
1997 [D loss: 0.692836, acc.: 50.39%] [G loss: 0.700391]
8/8 [==============================] - 0s 4ms/step
1998 [D loss: 0.693083, acc.: 50.59%] [G loss: 0.700280]
8/8 [==============================] - 0s 5ms/step
1999 [D loss: 0.693313, acc.: 50.39%] [G loss: 0.699633]
8/8 [==============================] - 0s 5ms/step
2000 [D loss: 0.692956, acc.: 51.37%] [G loss: 0.700163]
1/1 [==============================] - 0s 19ms/step
8/8 [==============================] - 0s 4ms/step
2001 [D loss: 0.693279, acc.: 50.98%] [G loss: 0.699907]
8/8 [==============================] - 0s 4ms/step
2002 [D loss: 0.692925, acc.: 50.39%] [G loss: 0.699801]
8/8 [==============================] - 0s 4ms/step
2003 [D loss: 0.693084, acc.: 51.17%] [G loss: 0.699862]
8/8 [==============================] - 0s 4ms/step
2004 [D loss: 0.693387, acc.: 50.00%] [G loss: 0.699428]
8/8 [==============================] - 0s 4ms/step
2005 [D loss: 0.693201, acc.: 50.00%] [G loss: 0.699191]
8/8 [==============================] - 0s 4ms/step
2006 [D loss: 0.693843, acc.: 47.46%] [G loss: 0.698539]
8/8 [==============================] - 0s 4ms/step
2007 [D loss: 0.693597, acc.: 47.27%] [G loss: 0.698957]
8/8 [==============================] - 0s 4ms/step
2008 [D loss: 0.693764, acc.: 49.22%] [G loss: 0.698055]
8/8 [==============================] - 0s 4ms/step
2009 [D loss: 0.693521, acc.: 48.44%] [G loss: 0.698804]
8/8 [==============================] - 0s 4ms/step
2010 [D loss: 0.693129, acc.: 52.54%] [G loss: 0.697530]
8/8 [==============================] - 0s 5ms/step
2011 [D loss: 0.693218, acc.: 48.83%] [G loss: 0.697067]
8/8 [==============================] - 0s 4ms/step
2012 [D loss: 0.693609, acc.: 44.34%] [G loss: 0.697133]
8/8 [==============================] - 0s 5ms/step
2013 [D loss: 0.693295, acc.: 50.39%] [G loss: 0.697849]
8/8 [==============================] - 0s 5ms/step
2014 [D loss: 0.693575, acc.: 46.29%] [G loss: 0.697013]
8/8 [==============================] - 0s 4ms/step
2015 [D loss: 0.693535, acc.: 49.61%] [G loss: 0.696274]
8/8 [==============================] - 0s 4ms/step
2016 [D loss: 0.693612, acc.: 45.31%] [G loss: 0.696892]
8/8 [==============================] - 0s 4ms/step
2017 [D loss: 0.693345, acc.: 48.24%] [G loss: 0.697096]
8/8 [==============================] - 0s 5ms/step
2018 [D loss: 0.693183, acc.: 45.31%] [G loss: 0.697104]
8/8 [==============================] - 0s 4ms/step
2019 [D loss: 0.693463, acc.: 44.73%] [G loss: 0.696444]
8/8 [==============================] - 0s 5ms/step
2020 [D loss: 0.693575, acc.: 46.29%] [G loss: 0.696588]
8/8 [==============================] - 0s 4ms/step
2021 [D loss: 0.693504, acc.: 48.63%] [G loss: 0.696437]
8/8 [==============================] - 0s 5ms/step
2022 [D loss: 0.693498, acc.: 47.27%] [G loss: 0.696034]
8/8 [==============================] - 0s 4ms/step
2023 [D loss: 0.693636, acc.: 45.12%] [G loss: 0.695947]
8/8 [==============================] - 0s 4ms/step
2024 [D loss: 0.693420, acc.: 46.48%] [G loss: 0.696226]
8/8 [==============================] - 0s 4ms/step
2025 [D loss: 0.692877, acc.: 48.44%] [G loss: 0.696393]
8/8 [==============================] - 0s 4ms/step
2026 [D loss: 0.693277, acc.: 47.27%] [G loss: 0.695749]
8/8 [==============================] - 0s 4ms/step
2027 [D loss: 0.694171, acc.: 45.12%] [G loss: 0.694736]
8/8 [==============================] - 0s 4ms/step
2028 [D loss: 0.693923, acc.: 47.07%] [G loss: 0.694610]
8/8 [==============================] - 0s 4ms/step
2029 [D loss: 0.693437, acc.: 47.07%] [G loss: 0.695285]
8/8 [==============================] - 0s 4ms/step
2030 [D loss: 0.693685, acc.: 45.90%] [G loss: 0.694989]
8/8 [==============================] - 0s 4ms/step
2031 [D loss: 0.693536, acc.: 48.83%] [G loss: 0.694968]
8/8 [==============================] - 0s 5ms/step
2032 [D loss: 0.693582, acc.: 46.09%] [G loss: 0.694788]
8/8 [==============================] - 0s 4ms/step
2033 [D loss: 0.693241, acc.: 52.54%] [G loss: 0.695152]
8/8 [==============================] - 0s 5ms/step
2034 [D loss: 0.693540, acc.: 46.88%] [G loss: 0.695495]
8/8 [==============================] - 0s 5ms/step
2035 [D loss: 0.693224, acc.: 49.41%] [G loss: 0.694276]
8/8 [==============================] - 0s 5ms/step
2036 [D loss: 0.693326, acc.: 48.83%] [G loss: 0.694602]
8/8 [==============================] - 0s 5ms/step
2037 [D loss: 0.693571, acc.: 46.68%] [G loss: 0.695869]
8/8 [==============================] - 0s 4ms/step
2038 [D loss: 0.693913, acc.: 44.73%] [G loss: 0.694482]
8/8 [==============================] - 0s 5ms/step
2039 [D loss: 0.693525, acc.: 47.27%] [G loss: 0.693874]
8/8 [==============================] - 0s 4ms/step
2040 [D loss: 0.693413, acc.: 49.41%] [G loss: 0.694115]
8/8 [==============================] - 0s 4ms/step
2041 [D loss: 0.693938, acc.: 46.09%] [G loss: 0.694512]
8/8 [==============================] - 0s 5ms/step
2042 [D loss: 0.693791, acc.: 46.68%] [G loss: 0.694142]
8/8 [==============================] - 0s 4ms/step
2043 [D loss: 0.694021, acc.: 49.22%] [G loss: 0.694293]
8/8 [==============================] - 0s 4ms/step
2044 [D loss: 0.693562, acc.: 44.92%] [G loss: 0.693060]
8/8 [==============================] - 0s 4ms/step
2045 [D loss: 0.693179, acc.: 49.22%] [G loss: 0.693040]
8/8 [==============================] - 0s 4ms/step
2046 [D loss: 0.693850, acc.: 43.55%] [G loss: 0.693698]
8/8 [==============================] - 0s 4ms/step
2047 [D loss: 0.693684, acc.: 46.29%] [G loss: 0.693100]
8/8 [==============================] - 0s 4ms/step
2048 [D loss: 0.693648, acc.: 42.97%] [G loss: 0.693544]
8/8 [==============================] - 0s 4ms/step
2049 [D loss: 0.693933, acc.: 40.43%] [G loss: 0.693572]
8/8 [==============================] - 0s 5ms/step
2050 [D loss: 0.694145, acc.: 43.55%] [G loss: 0.694329]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 4ms/step
2051 [D loss: 0.692883, acc.: 49.41%] [G loss: 0.694633]
8/8 [==============================] - 0s 5ms/step
2052 [D loss: 0.693481, acc.: 46.68%] [G loss: 0.694527]
8/8 [==============================] - 0s 4ms/step
2053 [D loss: 0.694301, acc.: 44.92%] [G loss: 0.694227]
8/8 [==============================] - 0s 5ms/step
2054 [D loss: 0.693734, acc.: 43.75%] [G loss: 0.694558]
8/8 [==============================] - 0s 4ms/step
2055 [D loss: 0.693436, acc.: 47.85%] [G loss: 0.694599]
8/8 [==============================] - 0s 5ms/step
2056 [D loss: 0.693764, acc.: 45.70%] [G loss: 0.694254]
8/8 [==============================] - 0s 4ms/step
2057 [D loss: 0.693039, acc.: 49.41%] [G loss: 0.694396]
8/8 [==============================] - 0s 5ms/step
2058 [D loss: 0.692764, acc.: 50.59%] [G loss: 0.696263]
8/8 [==============================] - 0s 4ms/step
2059 [D loss: 0.693341, acc.: 48.63%] [G loss: 0.694900]
8/8 [==============================] - 0s 5ms/step
2060 [D loss: 0.693361, acc.: 48.05%] [G loss: 0.695232]
8/8 [==============================] - 0s 5ms/step
2061 [D loss: 0.693640, acc.: 47.85%] [G loss: 0.695691]
8/8 [==============================] - 0s 4ms/step
2062 [D loss: 0.693761, acc.: 45.12%] [G loss: 0.695266]
8/8 [==============================] - 0s 6ms/step
2063 [D loss: 0.693311, acc.: 52.54%] [G loss: 0.695049]
8/8 [==============================] - 0s 4ms/step
2064 [D loss: 0.693395, acc.: 49.80%] [G loss: 0.695879]
8/8 [==============================] - 0s 5ms/step
2065 [D loss: 0.692523, acc.: 53.52%] [G loss: 0.695488]
8/8 [==============================] - 0s 4ms/step
2066 [D loss: 0.693221, acc.: 49.41%] [G loss: 0.696131]
8/8 [==============================] - 0s 4ms/step
2067 [D loss: 0.693229, acc.: 49.22%] [G loss: 0.696301]
8/8 [==============================] - 0s 4ms/step
2068 [D loss: 0.692875, acc.: 52.54%] [G loss: 0.695964]
8/8 [==============================] - 0s 5ms/step
2069 [D loss: 0.693167, acc.: 50.00%] [G loss: 0.695959]
8/8 [==============================] - 0s 4ms/step
2070 [D loss: 0.693773, acc.: 49.02%] [G loss: 0.696466]
8/8 [==============================] - 0s 4ms/step
2071 [D loss: 0.693547, acc.: 48.24%] [G loss: 0.696555]
8/8 [==============================] - 0s 5ms/step
2072 [D loss: 0.693544, acc.: 46.48%] [G loss: 0.696442]
8/8 [==============================] - 0s 4ms/step
2073 [D loss: 0.694142, acc.: 45.51%] [G loss: 0.697420]
8/8 [==============================] - 0s 5ms/step
2074 [D loss: 0.693797, acc.: 44.92%] [G loss: 0.697421]
8/8 [==============================] - 0s 4ms/step
2075 [D loss: 0.693583, acc.: 46.48%] [G loss: 0.696933]
8/8 [==============================] - 0s 6ms/step
2076 [D loss: 0.693385, acc.: 44.92%] [G loss: 0.696371]
8/8 [==============================] - 0s 5ms/step
2077 [D loss: 0.693785, acc.: 45.70%] [G loss: 0.697252]
8/8 [==============================] - 0s 5ms/step
2078 [D loss: 0.693700, acc.: 45.31%] [G loss: 0.696738]
8/8 [==============================] - 0s 4ms/step
2079 [D loss: 0.693694, acc.: 47.66%] [G loss: 0.697530]
8/8 [==============================] - 0s 4ms/step
2080 [D loss: 0.693747, acc.: 46.68%] [G loss: 0.696585]
8/8 [==============================] - 0s 5ms/step
2081 [D loss: 0.693554, acc.: 47.07%] [G loss: 0.697991]
8/8 [==============================] - 0s 4ms/step
2082 [D loss: 0.693155, acc.: 51.56%] [G loss: 0.697139]
8/8 [==============================] - 0s 5ms/step
2083 [D loss: 0.693989, acc.: 47.66%] [G loss: 0.697773]
8/8 [==============================] - 0s 5ms/step
2084 [D loss: 0.694053, acc.: 46.88%] [G loss: 0.696639]
8/8 [==============================] - 0s 4ms/step
2085 [D loss: 0.693722, acc.: 46.68%] [G loss: 0.697310]
8/8 [==============================] - 0s 7ms/step
2086 [D loss: 0.693367, acc.: 50.00%] [G loss: 0.698385]
8/8 [==============================] - 0s 4ms/step
2087 [D loss: 0.693976, acc.: 45.31%] [G loss: 0.697892]
8/8 [==============================] - 0s 4ms/step
2088 [D loss: 0.693144, acc.: 47.85%] [G loss: 0.697601]
8/8 [==============================] - 0s 4ms/step
2089 [D loss: 0.692837, acc.: 51.56%] [G loss: 0.697885]
8/8 [==============================] - 0s 5ms/step
2090 [D loss: 0.693043, acc.: 49.61%] [G loss: 0.697409]
8/8 [==============================] - 0s 4ms/step
2091 [D loss: 0.692801, acc.: 49.41%] [G loss: 0.697381]
8/8 [==============================] - 0s 5ms/step
2092 [D loss: 0.693121, acc.: 49.41%] [G loss: 0.697130]
8/8 [==============================] - 0s 5ms/step
2093 [D loss: 0.693500, acc.: 45.90%] [G loss: 0.698302]
8/8 [==============================] - 0s 4ms/step
2094 [D loss: 0.693760, acc.: 48.24%] [G loss: 0.697065]
8/8 [==============================] - 0s 5ms/step
2095 [D loss: 0.693922, acc.: 42.38%] [G loss: 0.697303]
8/8 [==============================] - 0s 4ms/step
2096 [D loss: 0.693307, acc.: 50.20%] [G loss: 0.697486]
8/8 [==============================] - 0s 5ms/step
2097 [D loss: 0.693835, acc.: 46.88%] [G loss: 0.697244]
8/8 [==============================] - 0s 4ms/step
2098 [D loss: 0.693981, acc.: 45.70%] [G loss: 0.696566]
8/8 [==============================] - 0s 5ms/step
2099 [D loss: 0.694054, acc.: 49.02%] [G loss: 0.695832]
8/8 [==============================] - 0s 4ms/step
2100 [D loss: 0.694140, acc.: 43.75%] [G loss: 0.696841]
1/1 [==============================] - 0s 28ms/step
8/8 [==============================] - 0s 5ms/step
2101 [D loss: 0.694106, acc.: 47.27%] [G loss: 0.697028]
8/8 [==============================] - 0s 4ms/step
2102 [D loss: 0.694322, acc.: 46.48%] [G loss: 0.696473]
8/8 [==============================] - 0s 5ms/step
2103 [D loss: 0.693941, acc.: 46.68%] [G loss: 0.696306]
8/8 [==============================] - 0s 4ms/step
2104 [D loss: 0.693766, acc.: 43.95%] [G loss: 0.695265]
8/8 [==============================] - 0s 4ms/step
2105 [D loss: 0.694100, acc.: 45.12%] [G loss: 0.695715]
8/8 [==============================] - 0s 4ms/step
2106 [D loss: 0.693356, acc.: 46.88%] [G loss: 0.695797]
8/8 [==============================] - 0s 4ms/step
2107 [D loss: 0.693821, acc.: 45.70%] [G loss: 0.695335]
8/8 [==============================] - 0s 5ms/step
2108 [D loss: 0.694064, acc.: 44.14%] [G loss: 0.695470]
8/8 [==============================] - 0s 4ms/step
2109 [D loss: 0.694214, acc.: 44.92%] [G loss: 0.695468]
8/8 [==============================] - 0s 4ms/step
2110 [D loss: 0.693449, acc.: 47.85%] [G loss: 0.695997]
8/8 [==============================] - 0s 4ms/step
2111 [D loss: 0.693298, acc.: 49.02%] [G loss: 0.695533]
8/8 [==============================] - 0s 4ms/step
2112 [D loss: 0.693037, acc.: 48.63%] [G loss: 0.696059]
8/8 [==============================] - 0s 4ms/step
2113 [D loss: 0.693120, acc.: 48.24%] [G loss: 0.696499]
8/8 [==============================] - 0s 4ms/step
2114 [D loss: 0.692420, acc.: 52.73%] [G loss: 0.697494]
8/8 [==============================] - 0s 5ms/step
2115 [D loss: 0.692657, acc.: 50.39%] [G loss: 0.696472]
8/8 [==============================] - 0s 5ms/step
2116 [D loss: 0.692290, acc.: 53.52%] [G loss: 0.697238]
8/8 [==============================] - 0s 4ms/step
2117 [D loss: 0.692002, acc.: 56.25%] [G loss: 0.697703]
8/8 [==============================] - 0s 5ms/step
2118 [D loss: 0.692696, acc.: 51.95%] [G loss: 0.697421]
8/8 [==============================] - 0s 4ms/step
2119 [D loss: 0.692178, acc.: 52.93%] [G loss: 0.699160]
8/8 [==============================] - 0s 4ms/step
2120 [D loss: 0.692580, acc.: 49.61%] [G loss: 0.698262]
8/8 [==============================] - 0s 4ms/step
2121 [D loss: 0.691721, acc.: 55.66%] [G loss: 0.697772]
8/8 [==============================] - 0s 4ms/step
2122 [D loss: 0.691734, acc.: 52.34%] [G loss: 0.697112]
8/8 [==============================] - 0s 7ms/step
2123 [D loss: 0.693008, acc.: 49.41%] [G loss: 0.696846]
8/8 [==============================] - 0s 4ms/step
2124 [D loss: 0.694100, acc.: 46.48%] [G loss: 0.696014]
8/8 [==============================] - 0s 5ms/step
2125 [D loss: 0.693315, acc.: 50.59%] [G loss: 0.694272]
8/8 [==============================] - 0s 4ms/step
2126 [D loss: 0.694279, acc.: 46.29%] [G loss: 0.694847]
8/8 [==============================] - 0s 5ms/step
2127 [D loss: 0.694496, acc.: 41.41%] [G loss: 0.694203]
8/8 [==============================] - 0s 5ms/step
2128 [D loss: 0.694531, acc.: 41.60%] [G loss: 0.694868]
8/8 [==============================] - 0s 5ms/step
2129 [D loss: 0.694815, acc.: 43.16%] [G loss: 0.694865]
8/8 [==============================] - 0s 5ms/step
2130 [D loss: 0.694979, acc.: 37.89%] [G loss: 0.694623]
8/8 [==============================] - 0s 4ms/step
2131 [D loss: 0.694401, acc.: 41.99%] [G loss: 0.694611]
8/8 [==============================] - 0s 4ms/step
2132 [D loss: 0.693553, acc.: 47.27%] [G loss: 0.695553]
8/8 [==============================] - 0s 4ms/step
2133 [D loss: 0.692603, acc.: 50.98%] [G loss: 0.695889]
8/8 [==============================] - 0s 5ms/step
2134 [D loss: 0.692628, acc.: 52.73%] [G loss: 0.696156]
8/8 [==============================] - 0s 5ms/step
2135 [D loss: 0.693181, acc.: 50.59%] [G loss: 0.695590]
8/8 [==============================] - 0s 7ms/step
2136 [D loss: 0.692755, acc.: 51.95%] [G loss: 0.695752]
8/8 [==============================] - 0s 4ms/step
2137 [D loss: 0.692817, acc.: 51.17%] [G loss: 0.695018]
8/8 [==============================] - 0s 5ms/step
2138 [D loss: 0.693031, acc.: 48.24%] [G loss: 0.694527]
8/8 [==============================] - 0s 4ms/step
2139 [D loss: 0.693746, acc.: 50.39%] [G loss: 0.694879]
8/8 [==============================] - 0s 5ms/step
2140 [D loss: 0.693242, acc.: 47.46%] [G loss: 0.693480]
8/8 [==============================] - 0s 5ms/step
2141 [D loss: 0.693668, acc.: 46.88%] [G loss: 0.691645]
8/8 [==============================] - 0s 4ms/step
2142 [D loss: 0.693784, acc.: 48.24%] [G loss: 0.692131]
8/8 [==============================] - 0s 4ms/step
2143 [D loss: 0.693879, acc.: 43.75%] [G loss: 0.692294]
8/8 [==============================] - 0s 5ms/step
2144 [D loss: 0.694476, acc.: 40.23%] [G loss: 0.691455]
8/8 [==============================] - 0s 4ms/step
2145 [D loss: 0.694202, acc.: 43.95%] [G loss: 0.690877]
8/8 [==============================] - 0s 4ms/step
2146 [D loss: 0.694312, acc.: 42.38%] [G loss: 0.691823]
8/8 [==============================] - 0s 5ms/step
2147 [D loss: 0.693895, acc.: 46.09%] [G loss: 0.691718]
8/8 [==============================] - 0s 4ms/step
2148 [D loss: 0.694167, acc.: 43.55%] [G loss: 0.691507]
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2149 [D loss: 0.694000, acc.: 42.97%] [G loss: 0.692167]
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2150 [D loss: 0.693771, acc.: 46.68%] [G loss: 0.692271]
1/1 [==============================] - 0s 16ms/step
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2151 [D loss: 0.694194, acc.: 45.90%] [G loss: 0.692893]
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2152 [D loss: 0.693910, acc.: 46.48%] [G loss: 0.693430]
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2153 [D loss: 0.693787, acc.: 47.66%] [G loss: 0.693689]
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2154 [D loss: 0.693949, acc.: 44.92%] [G loss: 0.694099]
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2155 [D loss: 0.693709, acc.: 44.53%] [G loss: 0.694291]
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2156 [D loss: 0.693203, acc.: 48.24%] [G loss: 0.694224]
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2157 [D loss: 0.693762, acc.: 44.53%] [G loss: 0.693649]
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2158 [D loss: 0.693277, acc.: 50.00%] [G loss: 0.693601]
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2159 [D loss: 0.693377, acc.: 49.41%] [G loss: 0.694446]
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2160 [D loss: 0.693393, acc.: 47.85%] [G loss: 0.694578]
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2161 [D loss: 0.693251, acc.: 46.88%] [G loss: 0.693878]
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2162 [D loss: 0.693562, acc.: 43.95%] [G loss: 0.693619]
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2163 [D loss: 0.693202, acc.: 46.88%] [G loss: 0.694651]
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2164 [D loss: 0.693505, acc.: 46.48%] [G loss: 0.695038]
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2165 [D loss: 0.693637, acc.: 44.14%] [G loss: 0.693802]
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2166 [D loss: 0.693601, acc.: 45.90%] [G loss: 0.694819]
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2167 [D loss: 0.694166, acc.: 43.16%] [G loss: 0.694312]
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2168 [D loss: 0.693525, acc.: 41.99%] [G loss: 0.694698]
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2169 [D loss: 0.694008, acc.: 40.04%] [G loss: 0.695766]
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2170 [D loss: 0.694344, acc.: 40.43%] [G loss: 0.694554]
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2171 [D loss: 0.693895, acc.: 46.09%] [G loss: 0.694690]
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2172 [D loss: 0.693743, acc.: 42.77%] [G loss: 0.695064]
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2173 [D loss: 0.693711, acc.: 46.29%] [G loss: 0.694340]
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2174 [D loss: 0.694373, acc.: 41.60%] [G loss: 0.694720]
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2175 [D loss: 0.693349, acc.: 47.07%] [G loss: 0.695178]
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2176 [D loss: 0.693520, acc.: 47.85%] [G loss: 0.695965]
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2177 [D loss: 0.693937, acc.: 43.95%] [G loss: 0.695387]
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2178 [D loss: 0.693811, acc.: 43.36%] [G loss: 0.695590]
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2179 [D loss: 0.693480, acc.: 47.66%] [G loss: 0.695483]
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2180 [D loss: 0.693821, acc.: 47.85%] [G loss: 0.695356]
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2181 [D loss: 0.693755, acc.: 44.34%] [G loss: 0.695535]
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2182 [D loss: 0.693512, acc.: 45.90%] [G loss: 0.696574]
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2183 [D loss: 0.693545, acc.: 49.02%] [G loss: 0.696219]
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2184 [D loss: 0.693501, acc.: 44.92%] [G loss: 0.696423]
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2185 [D loss: 0.693197, acc.: 49.41%] [G loss: 0.696407]
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2186 [D loss: 0.692744, acc.: 50.39%] [G loss: 0.696578]
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2187 [D loss: 0.693154, acc.: 48.63%] [G loss: 0.697631]
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2188 [D loss: 0.693058, acc.: 49.02%] [G loss: 0.697266]
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2189 [D loss: 0.693131, acc.: 50.00%] [G loss: 0.697062]
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2190 [D loss: 0.693129, acc.: 50.78%] [G loss: 0.696949]
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2191 [D loss: 0.693273, acc.: 49.41%] [G loss: 0.697143]
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2192 [D loss: 0.692696, acc.: 52.15%] [G loss: 0.696773]
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2193 [D loss: 0.693611, acc.: 47.46%] [G loss: 0.697742]
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2194 [D loss: 0.693601, acc.: 46.48%] [G loss: 0.696689]
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2195 [D loss: 0.693706, acc.: 45.31%] [G loss: 0.697338]
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2196 [D loss: 0.693743, acc.: 45.90%] [G loss: 0.696288]
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2197 [D loss: 0.693549, acc.: 46.68%] [G loss: 0.696798]
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2198 [D loss: 0.693483, acc.: 47.07%] [G loss: 0.696304]
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2199 [D loss: 0.694122, acc.: 42.38%] [G loss: 0.696363]
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2200 [D loss: 0.693716, acc.: 45.70%] [G loss: 0.695898]
1/1 [==============================] - 0s 17ms/step
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2201 [D loss: 0.693672, acc.: 45.31%] [G loss: 0.695091]
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2202 [D loss: 0.693999, acc.: 41.02%] [G loss: 0.694818]
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2203 [D loss: 0.694370, acc.: 44.73%] [G loss: 0.695173]
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2204 [D loss: 0.693872, acc.: 44.53%] [G loss: 0.695129]
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2205 [D loss: 0.693620, acc.: 48.44%] [G loss: 0.694715]
8/8 [==============================] - 0s 4ms/step
2206 [D loss: 0.693768, acc.: 42.97%] [G loss: 0.694930]
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2207 [D loss: 0.693798, acc.: 43.75%] [G loss: 0.694826]
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2208 [D loss: 0.693588, acc.: 43.36%] [G loss: 0.694616]
8/8 [==============================] - 0s 4ms/step
2209 [D loss: 0.693171, acc.: 47.85%] [G loss: 0.695073]
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2210 [D loss: 0.693348, acc.: 47.27%] [G loss: 0.694769]
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2211 [D loss: 0.693158, acc.: 49.61%] [G loss: 0.695484]
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2212 [D loss: 0.692699, acc.: 51.17%] [G loss: 0.695029]
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2213 [D loss: 0.693752, acc.: 44.92%] [G loss: 0.694367]
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2214 [D loss: 0.693341, acc.: 47.85%] [G loss: 0.694948]
8/8 [==============================] - 0s 4ms/step
2215 [D loss: 0.692804, acc.: 51.37%] [G loss: 0.694177]
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2216 [D loss: 0.693696, acc.: 44.73%] [G loss: 0.694093]
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2217 [D loss: 0.692785, acc.: 50.78%] [G loss: 0.694697]
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2218 [D loss: 0.692568, acc.: 50.78%] [G loss: 0.693752]
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2219 [D loss: 0.693118, acc.: 48.44%] [G loss: 0.693659]
8/8 [==============================] - 0s 4ms/step
2220 [D loss: 0.693486, acc.: 45.70%] [G loss: 0.693282]
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2221 [D loss: 0.693369, acc.: 46.29%] [G loss: 0.691851]
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2222 [D loss: 0.695008, acc.: 42.58%] [G loss: 0.692861]
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2223 [D loss: 0.694652, acc.: 43.55%] [G loss: 0.693563]
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2224 [D loss: 0.694198, acc.: 43.36%] [G loss: 0.693354]
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2225 [D loss: 0.694128, acc.: 47.07%] [G loss: 0.692789]
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2226 [D loss: 0.694162, acc.: 43.75%] [G loss: 0.693443]
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2227 [D loss: 0.694170, acc.: 41.21%] [G loss: 0.694239]
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2228 [D loss: 0.694076, acc.: 41.99%] [G loss: 0.694174]
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2229 [D loss: 0.694097, acc.: 46.09%] [G loss: 0.694138]
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2230 [D loss: 0.694024, acc.: 43.75%] [G loss: 0.694914]
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2231 [D loss: 0.693909, acc.: 43.95%] [G loss: 0.694219]
8/8 [==============================] - 0s 4ms/step
2232 [D loss: 0.693596, acc.: 48.05%] [G loss: 0.695232]
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2233 [D loss: 0.693428, acc.: 46.29%] [G loss: 0.695757]
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2234 [D loss: 0.693480, acc.: 46.68%] [G loss: 0.695834]
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2235 [D loss: 0.693236, acc.: 49.22%] [G loss: 0.695654]
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2236 [D loss: 0.693357, acc.: 47.07%] [G loss: 0.695041]
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2237 [D loss: 0.693354, acc.: 46.88%] [G loss: 0.695313]
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2238 [D loss: 0.693331, acc.: 48.83%] [G loss: 0.695728]
8/8 [==============================] - 0s 5ms/step
2239 [D loss: 0.693058, acc.: 50.59%] [G loss: 0.695270]
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2240 [D loss: 0.693037, acc.: 47.66%] [G loss: 0.695441]
8/8 [==============================] - 0s 4ms/step
2241 [D loss: 0.692780, acc.: 51.56%] [G loss: 0.694534]
8/8 [==============================] - 0s 4ms/step
2242 [D loss: 0.693255, acc.: 49.02%] [G loss: 0.693987]
8/8 [==============================] - 0s 4ms/step
2243 [D loss: 0.693351, acc.: 46.09%] [G loss: 0.694381]
8/8 [==============================] - 0s 5ms/step
2244 [D loss: 0.693180, acc.: 47.66%] [G loss: 0.693802]
8/8 [==============================] - 0s 4ms/step
2245 [D loss: 0.693380, acc.: 45.31%] [G loss: 0.692939]
8/8 [==============================] - 0s 4ms/step
2246 [D loss: 0.694146, acc.: 42.19%] [G loss: 0.693006]
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2247 [D loss: 0.693468, acc.: 42.38%] [G loss: 0.693114]
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2248 [D loss: 0.694175, acc.: 42.19%] [G loss: 0.693161]
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2249 [D loss: 0.694747, acc.: 41.21%] [G loss: 0.692094]
8/8 [==============================] - 0s 5ms/step
2250 [D loss: 0.694402, acc.: 42.19%] [G loss: 0.693401]
1/1 [==============================] - 0s 17ms/step
8/8 [==============================] - 0s 6ms/step
2251 [D loss: 0.694888, acc.: 40.43%] [G loss: 0.693583]
8/8 [==============================] - 0s 4ms/step
2252 [D loss: 0.694830, acc.: 41.02%] [G loss: 0.692435]
8/8 [==============================] - 0s 4ms/step
2253 [D loss: 0.694937, acc.: 37.89%] [G loss: 0.692162]
8/8 [==============================] - 0s 4ms/step
2254 [D loss: 0.694677, acc.: 38.28%] [G loss: 0.692916]
8/8 [==============================] - 0s 4ms/step
2255 [D loss: 0.694551, acc.: 39.26%] [G loss: 0.693319]
8/8 [==============================] - 0s 4ms/step
2256 [D loss: 0.693811, acc.: 44.34%] [G loss: 0.693054]
8/8 [==============================] - 0s 5ms/step
2257 [D loss: 0.693862, acc.: 45.12%] [G loss: 0.693673]
8/8 [==============================] - 0s 4ms/step
2258 [D loss: 0.693997, acc.: 40.62%] [G loss: 0.693629]
8/8 [==============================] - 0s 4ms/step
2259 [D loss: 0.693069, acc.: 49.61%] [G loss: 0.694053]
8/8 [==============================] - 0s 5ms/step
2260 [D loss: 0.693269, acc.: 48.44%] [G loss: 0.694849]
8/8 [==============================] - 0s 5ms/step
2261 [D loss: 0.693045, acc.: 48.63%] [G loss: 0.694894]
8/8 [==============================] - 0s 4ms/step
2262 [D loss: 0.692559, acc.: 56.45%] [G loss: 0.696147]
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2263 [D loss: 0.692505, acc.: 53.91%] [G loss: 0.695903]
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2264 [D loss: 0.692971, acc.: 52.15%] [G loss: 0.696007]
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2265 [D loss: 0.692168, acc.: 54.10%] [G loss: 0.696192]
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2266 [D loss: 0.691809, acc.: 57.62%] [G loss: 0.696913]
8/8 [==============================] - 0s 4ms/step
2267 [D loss: 0.691603, acc.: 54.30%] [G loss: 0.696738]
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2268 [D loss: 0.691841, acc.: 54.49%] [G loss: 0.696942]
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2269 [D loss: 0.692503, acc.: 53.12%] [G loss: 0.697085]
8/8 [==============================] - 0s 4ms/step
2270 [D loss: 0.692859, acc.: 49.41%] [G loss: 0.696179]
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2271 [D loss: 0.692034, acc.: 51.56%] [G loss: 0.695477]
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2272 [D loss: 0.693710, acc.: 45.90%] [G loss: 0.695829]
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2273 [D loss: 0.694508, acc.: 43.75%] [G loss: 0.695131]
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2274 [D loss: 0.693332, acc.: 51.76%] [G loss: 0.694255]
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2275 [D loss: 0.694178, acc.: 44.53%] [G loss: 0.695445]
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2276 [D loss: 0.694254, acc.: 43.95%] [G loss: 0.694733]
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2277 [D loss: 0.695268, acc.: 38.28%] [G loss: 0.695764]
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2278 [D loss: 0.694111, acc.: 43.16%] [G loss: 0.696061]
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2279 [D loss: 0.694140, acc.: 44.34%] [G loss: 0.695799]
8/8 [==============================] - 0s 4ms/step
2280 [D loss: 0.694748, acc.: 40.23%] [G loss: 0.695891]
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2281 [D loss: 0.694166, acc.: 41.60%] [G loss: 0.696339]
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2282 [D loss: 0.694035, acc.: 43.55%] [G loss: 0.695967]
8/8 [==============================] - 0s 8ms/step
2283 [D loss: 0.693773, acc.: 44.53%] [G loss: 0.696448]
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2284 [D loss: 0.693928, acc.: 42.97%] [G loss: 0.696084]
8/8 [==============================] - 0s 7ms/step
2285 [D loss: 0.693999, acc.: 45.12%] [G loss: 0.696926]
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2286 [D loss: 0.694161, acc.: 41.41%] [G loss: 0.697596]
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2287 [D loss: 0.694515, acc.: 38.67%] [G loss: 0.697575]
8/8 [==============================] - 0s 8ms/step
2288 [D loss: 0.693733, acc.: 44.14%] [G loss: 0.698047]
8/8 [==============================] - 0s 7ms/step
2289 [D loss: 0.694546, acc.: 39.26%] [G loss: 0.697584]
8/8 [==============================] - 0s 6ms/step
2290 [D loss: 0.693583, acc.: 48.24%] [G loss: 0.697481]
8/8 [==============================] - 0s 7ms/step
2291 [D loss: 0.694007, acc.: 42.77%] [G loss: 0.697754]
8/8 [==============================] - 0s 6ms/step
2292 [D loss: 0.693430, acc.: 48.63%] [G loss: 0.697984]
8/8 [==============================] - 0s 7ms/step
2293 [D loss: 0.693708, acc.: 47.46%] [G loss: 0.698769]
8/8 [==============================] - 0s 5ms/step
2294 [D loss: 0.693698, acc.: 46.48%] [G loss: 0.698806]
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2295 [D loss: 0.693415, acc.: 49.02%] [G loss: 0.698288]
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2296 [D loss: 0.693015, acc.: 50.98%] [G loss: 0.699653]
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2297 [D loss: 0.693054, acc.: 50.39%] [G loss: 0.699844]
8/8 [==============================] - 0s 6ms/step
2298 [D loss: 0.692914, acc.: 53.52%] [G loss: 0.699209]
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2299 [D loss: 0.692755, acc.: 49.61%] [G loss: 0.699714]
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2300 [D loss: 0.692589, acc.: 54.30%] [G loss: 0.699653]
1/1 [==============================] - 0s 19ms/step
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2301 [D loss: 0.692930, acc.: 50.98%] [G loss: 0.699492]
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2302 [D loss: 0.692873, acc.: 51.37%] [G loss: 0.699151]
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2303 [D loss: 0.692900, acc.: 50.20%] [G loss: 0.699259]
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2304 [D loss: 0.693120, acc.: 48.05%] [G loss: 0.698673]
8/8 [==============================] - 0s 4ms/step
2305 [D loss: 0.692931, acc.: 50.98%] [G loss: 0.698331]
8/8 [==============================] - 0s 5ms/step
2306 [D loss: 0.692903, acc.: 47.46%] [G loss: 0.697218]
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2307 [D loss: 0.693359, acc.: 48.24%] [G loss: 0.697420]
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2308 [D loss: 0.692881, acc.: 54.69%] [G loss: 0.698470]
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2309 [D loss: 0.693394, acc.: 49.02%] [G loss: 0.698330]
8/8 [==============================] - 0s 4ms/step
2310 [D loss: 0.692534, acc.: 51.17%] [G loss: 0.697613]
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2311 [D loss: 0.693427, acc.: 49.80%] [G loss: 0.696916]
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2312 [D loss: 0.693154, acc.: 48.05%] [G loss: 0.697748]
8/8 [==============================] - 0s 4ms/step
2313 [D loss: 0.692430, acc.: 52.73%] [G loss: 0.697335]
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2314 [D loss: 0.694122, acc.: 44.14%] [G loss: 0.696948]
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2315 [D loss: 0.693482, acc.: 49.61%] [G loss: 0.694573]
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2316 [D loss: 0.693025, acc.: 48.63%] [G loss: 0.694866]
8/8 [==============================] - 0s 4ms/step
2317 [D loss: 0.695456, acc.: 43.36%] [G loss: 0.695553]
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2318 [D loss: 0.694018, acc.: 45.70%] [G loss: 0.694862]
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2319 [D loss: 0.694396, acc.: 40.62%] [G loss: 0.693978]
8/8 [==============================] - 0s 5ms/step
2320 [D loss: 0.694571, acc.: 41.02%] [G loss: 0.694288]
8/8 [==============================] - 0s 5ms/step
2321 [D loss: 0.694024, acc.: 46.48%] [G loss: 0.694522]
8/8 [==============================] - 0s 4ms/step
2322 [D loss: 0.693917, acc.: 46.88%] [G loss: 0.693765]
8/8 [==============================] - 0s 4ms/step
2323 [D loss: 0.694356, acc.: 43.55%] [G loss: 0.694272]
8/8 [==============================] - 0s 4ms/step
2324 [D loss: 0.694612, acc.: 40.82%] [G loss: 0.694377]
8/8 [==============================] - 0s 6ms/step
2325 [D loss: 0.694048, acc.: 43.16%] [G loss: 0.694452]
8/8 [==============================] - 0s 5ms/step
2326 [D loss: 0.693618, acc.: 47.27%] [G loss: 0.694978]
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2327 [D loss: 0.693805, acc.: 45.31%] [G loss: 0.694503]
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2328 [D loss: 0.693954, acc.: 43.36%] [G loss: 0.695813]
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2329 [D loss: 0.693614, acc.: 44.34%] [G loss: 0.696493]
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2330 [D loss: 0.692938, acc.: 51.56%] [G loss: 0.696509]
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2331 [D loss: 0.693283, acc.: 48.63%] [G loss: 0.697017]
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2332 [D loss: 0.692822, acc.: 51.76%] [G loss: 0.697177]
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2333 [D loss: 0.693048, acc.: 50.20%] [G loss: 0.697980]
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2334 [D loss: 0.693328, acc.: 48.83%] [G loss: 0.697622]
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2335 [D loss: 0.693073, acc.: 48.05%] [G loss: 0.698240]
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2336 [D loss: 0.692411, acc.: 51.56%] [G loss: 0.698417]
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2337 [D loss: 0.692810, acc.: 48.83%] [G loss: 0.698373]
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2338 [D loss: 0.692957, acc.: 52.34%] [G loss: 0.698316]
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2339 [D loss: 0.693397, acc.: 47.46%] [G loss: 0.698387]
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2340 [D loss: 0.692808, acc.: 49.02%] [G loss: 0.699097]
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2341 [D loss: 0.692328, acc.: 52.54%] [G loss: 0.698649]
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2342 [D loss: 0.692778, acc.: 52.73%] [G loss: 0.699060]
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2343 [D loss: 0.692509, acc.: 53.32%] [G loss: 0.698683]
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2344 [D loss: 0.693333, acc.: 49.41%] [G loss: 0.698004]
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2345 [D loss: 0.693919, acc.: 44.92%] [G loss: 0.698501]
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2346 [D loss: 0.693112, acc.: 51.17%] [G loss: 0.698617]
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2347 [D loss: 0.692945, acc.: 48.83%] [G loss: 0.698648]
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2348 [D loss: 0.693323, acc.: 50.39%] [G loss: 0.698656]
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2349 [D loss: 0.693158, acc.: 48.44%] [G loss: 0.698058]
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2350 [D loss: 0.693261, acc.: 49.02%] [G loss: 0.697913]
1/1 [==============================] - 0s 17ms/step
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2351 [D loss: 0.693350, acc.: 47.27%] [G loss: 0.698212]
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2352 [D loss: 0.693468, acc.: 49.02%] [G loss: 0.697134]
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2353 [D loss: 0.693610, acc.: 46.29%] [G loss: 0.697698]
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2354 [D loss: 0.694062, acc.: 43.75%] [G loss: 0.698022]
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2355 [D loss: 0.693914, acc.: 44.73%] [G loss: 0.697230]
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2356 [D loss: 0.693547, acc.: 47.46%] [G loss: 0.697462]
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2357 [D loss: 0.693923, acc.: 43.55%] [G loss: 0.697109]
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2358 [D loss: 0.693309, acc.: 47.66%] [G loss: 0.696566]
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2359 [D loss: 0.693596, acc.: 47.27%] [G loss: 0.697192]
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2360 [D loss: 0.693243, acc.: 49.02%] [G loss: 0.695927]
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2361 [D loss: 0.693254, acc.: 47.66%] [G loss: 0.696902]
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2362 [D loss: 0.693224, acc.: 50.78%] [G loss: 0.696459]
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2363 [D loss: 0.693028, acc.: 48.83%] [G loss: 0.696704]
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2364 [D loss: 0.692949, acc.: 51.95%] [G loss: 0.695349]
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2365 [D loss: 0.693010, acc.: 52.34%] [G loss: 0.696142]
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2366 [D loss: 0.692760, acc.: 52.34%] [G loss: 0.695215]
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2367 [D loss: 0.693181, acc.: 50.20%] [G loss: 0.694540]
8/8 [==============================] - 0s 4ms/step
2368 [D loss: 0.693007, acc.: 48.83%] [G loss: 0.694189]
8/8 [==============================] - 0s 4ms/step
2369 [D loss: 0.693818, acc.: 45.70%] [G loss: 0.694467]
8/8 [==============================] - 0s 5ms/step
2370 [D loss: 0.692533, acc.: 53.12%] [G loss: 0.694236]
8/8 [==============================] - 0s 4ms/step
2371 [D loss: 0.693572, acc.: 49.61%] [G loss: 0.693320]
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2372 [D loss: 0.693800, acc.: 48.63%] [G loss: 0.692890]
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2373 [D loss: 0.693504, acc.: 48.05%] [G loss: 0.692524]
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2374 [D loss: 0.693353, acc.: 47.27%] [G loss: 0.692924]
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2375 [D loss: 0.694170, acc.: 44.53%] [G loss: 0.694007]
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2376 [D loss: 0.694738, acc.: 44.34%] [G loss: 0.693175]
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2377 [D loss: 0.694650, acc.: 42.97%] [G loss: 0.692228]
8/8 [==============================] - 0s 4ms/step
2378 [D loss: 0.694401, acc.: 43.36%] [G loss: 0.692980]
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2379 [D loss: 0.694395, acc.: 40.43%] [G loss: 0.692605]
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2380 [D loss: 0.694158, acc.: 44.92%] [G loss: 0.692432]
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2381 [D loss: 0.694146, acc.: 43.36%] [G loss: 0.692491]
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2382 [D loss: 0.694076, acc.: 42.38%] [G loss: 0.693464]
8/8 [==============================] - 0s 4ms/step
2383 [D loss: 0.694439, acc.: 41.02%] [G loss: 0.692268]
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2384 [D loss: 0.694721, acc.: 41.02%] [G loss: 0.693101]
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2385 [D loss: 0.694015, acc.: 45.90%] [G loss: 0.693294]
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2386 [D loss: 0.694054, acc.: 45.51%] [G loss: 0.693351]
8/8 [==============================] - 0s 4ms/step
2387 [D loss: 0.693209, acc.: 47.46%] [G loss: 0.694037]
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2388 [D loss: 0.693590, acc.: 46.09%] [G loss: 0.694318]
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2389 [D loss: 0.693428, acc.: 49.41%] [G loss: 0.695041]
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2390 [D loss: 0.693178, acc.: 52.34%] [G loss: 0.695471]
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2391 [D loss: 0.693071, acc.: 50.20%] [G loss: 0.695938]
8/8 [==============================] - 0s 4ms/step
2392 [D loss: 0.692952, acc.: 51.76%] [G loss: 0.696260]
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2393 [D loss: 0.692633, acc.: 54.10%] [G loss: 0.696865]
8/8 [==============================] - 0s 4ms/step
2394 [D loss: 0.692418, acc.: 54.30%] [G loss: 0.697336]
8/8 [==============================] - 0s 4ms/step
2395 [D loss: 0.692720, acc.: 54.49%] [G loss: 0.697297]
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2396 [D loss: 0.692702, acc.: 52.15%] [G loss: 0.696412]
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2397 [D loss: 0.691752, acc.: 57.62%] [G loss: 0.696973]
8/8 [==============================] - 0s 4ms/step
2398 [D loss: 0.692620, acc.: 50.00%] [G loss: 0.697489]
8/8 [==============================] - 0s 4ms/step
2399 [D loss: 0.692151, acc.: 51.76%] [G loss: 0.697521]
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2400 [D loss: 0.692809, acc.: 50.20%] [G loss: 0.696265]
1/1 [==============================] - 0s 18ms/step
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2401 [D loss: 0.692946, acc.: 49.41%] [G loss: 0.695668]
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2402 [D loss: 0.692232, acc.: 52.54%] [G loss: 0.696123]
8/8 [==============================] - 0s 4ms/step
2403 [D loss: 0.692354, acc.: 52.93%] [G loss: 0.695762]
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2404 [D loss: 0.693642, acc.: 47.07%] [G loss: 0.695403]
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2405 [D loss: 0.693353, acc.: 48.63%] [G loss: 0.694894]
8/8 [==============================] - 0s 4ms/step
2406 [D loss: 0.693207, acc.: 46.29%] [G loss: 0.695549]
8/8 [==============================] - 0s 4ms/step
2407 [D loss: 0.693758, acc.: 47.66%] [G loss: 0.694833]
8/8 [==============================] - 0s 5ms/step
2408 [D loss: 0.692746, acc.: 50.00%] [G loss: 0.695248]
8/8 [==============================] - 0s 5ms/step
2409 [D loss: 0.694115, acc.: 43.75%] [G loss: 0.694034]
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2410 [D loss: 0.693605, acc.: 45.12%] [G loss: 0.694318]
8/8 [==============================] - 0s 5ms/step
2411 [D loss: 0.694153, acc.: 43.36%] [G loss: 0.695069]
8/8 [==============================] - 0s 4ms/step
2412 [D loss: 0.694105, acc.: 45.51%] [G loss: 0.694035]
8/8 [==============================] - 0s 4ms/step
2413 [D loss: 0.693787, acc.: 47.27%] [G loss: 0.694847]
8/8 [==============================] - 0s 5ms/step
2414 [D loss: 0.693295, acc.: 48.63%] [G loss: 0.694173]
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2415 [D loss: 0.693839, acc.: 45.51%] [G loss: 0.694387]
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2416 [D loss: 0.694102, acc.: 42.77%] [G loss: 0.694080]
8/8 [==============================] - 0s 5ms/step
2417 [D loss: 0.693651, acc.: 44.73%] [G loss: 0.694425]
8/8 [==============================] - 0s 4ms/step
2418 [D loss: 0.694153, acc.: 44.34%] [G loss: 0.693664]
8/8 [==============================] - 0s 5ms/step
2419 [D loss: 0.693628, acc.: 45.31%] [G loss: 0.694471]
8/8 [==============================] - 0s 5ms/step
2420 [D loss: 0.694620, acc.: 41.60%] [G loss: 0.693687]
8/8 [==============================] - 0s 5ms/step
2421 [D loss: 0.695119, acc.: 40.62%] [G loss: 0.693673]
8/8 [==============================] - 0s 4ms/step
2422 [D loss: 0.694128, acc.: 41.99%] [G loss: 0.693231]
8/8 [==============================] - 0s 5ms/step
2423 [D loss: 0.693920, acc.: 48.05%] [G loss: 0.693637]
8/8 [==============================] - 0s 5ms/step
2424 [D loss: 0.694259, acc.: 43.75%] [G loss: 0.693139]
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2425 [D loss: 0.694207, acc.: 43.95%] [G loss: 0.693690]
8/8 [==============================] - 0s 6ms/step
2426 [D loss: 0.693832, acc.: 41.60%] [G loss: 0.694544]
8/8 [==============================] - 0s 4ms/step
2427 [D loss: 0.693869, acc.: 46.68%] [G loss: 0.694582]
8/8 [==============================] - 0s 4ms/step
2428 [D loss: 0.693263, acc.: 49.41%] [G loss: 0.694061]
8/8 [==============================] - 0s 7ms/step
2429 [D loss: 0.693676, acc.: 48.24%] [G loss: 0.694777]
8/8 [==============================] - 0s 4ms/step
2430 [D loss: 0.693269, acc.: 49.22%] [G loss: 0.695221]
8/8 [==============================] - 0s 5ms/step
2431 [D loss: 0.693638, acc.: 45.51%] [G loss: 0.695049]
8/8 [==============================] - 0s 5ms/step
2432 [D loss: 0.693080, acc.: 49.61%] [G loss: 0.696193]
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2433 [D loss: 0.692929, acc.: 50.98%] [G loss: 0.696014]
8/8 [==============================] - 0s 4ms/step
2434 [D loss: 0.692950, acc.: 49.22%] [G loss: 0.695726]
8/8 [==============================] - 0s 4ms/step
2435 [D loss: 0.692760, acc.: 53.71%] [G loss: 0.696261]
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2436 [D loss: 0.692469, acc.: 55.66%] [G loss: 0.695814]
8/8 [==============================] - 0s 4ms/step
2437 [D loss: 0.692577, acc.: 50.78%] [G loss: 0.696370]
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2438 [D loss: 0.692512, acc.: 53.71%] [G loss: 0.696733]
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2439 [D loss: 0.692625, acc.: 49.41%] [G loss: 0.696541]
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2440 [D loss: 0.692849, acc.: 51.76%] [G loss: 0.696206]
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2441 [D loss: 0.692677, acc.: 52.15%] [G loss: 0.695668]
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2442 [D loss: 0.693160, acc.: 53.12%] [G loss: 0.696673]
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2443 [D loss: 0.693096, acc.: 48.44%] [G loss: 0.696890]
8/8 [==============================] - 0s 6ms/step
2444 [D loss: 0.691930, acc.: 55.86%] [G loss: 0.695555]
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2445 [D loss: 0.693580, acc.: 48.83%] [G loss: 0.694541]
8/8 [==============================] - 0s 4ms/step
2446 [D loss: 0.694475, acc.: 46.68%] [G loss: 0.695039]
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2447 [D loss: 0.693987, acc.: 45.90%] [G loss: 0.694606]
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2448 [D loss: 0.693202, acc.: 48.44%] [G loss: 0.693592]
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2449 [D loss: 0.693071, acc.: 50.78%] [G loss: 0.693778]
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2450 [D loss: 0.693851, acc.: 47.66%] [G loss: 0.693997]
1/1 [==============================] - 0s 16ms/step
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2451 [D loss: 0.694922, acc.: 44.73%] [G loss: 0.693258]
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2452 [D loss: 0.693946, acc.: 45.90%] [G loss: 0.693465]
8/8 [==============================] - 0s 4ms/step
2453 [D loss: 0.694030, acc.: 46.68%] [G loss: 0.693680]
8/8 [==============================] - 0s 5ms/step
2454 [D loss: 0.693505, acc.: 45.31%] [G loss: 0.693796]
8/8 [==============================] - 0s 4ms/step
2455 [D loss: 0.693743, acc.: 46.68%] [G loss: 0.693021]
8/8 [==============================] - 0s 4ms/step
2456 [D loss: 0.693036, acc.: 51.37%] [G loss: 0.693534]
8/8 [==============================] - 0s 4ms/step
2457 [D loss: 0.694238, acc.: 45.12%] [G loss: 0.693102]
8/8 [==============================] - 0s 4ms/step
2458 [D loss: 0.693247, acc.: 47.66%] [G loss: 0.691777]
8/8 [==============================] - 0s 5ms/step
2459 [D loss: 0.693830, acc.: 45.31%] [G loss: 0.691670]
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2460 [D loss: 0.694090, acc.: 46.48%] [G loss: 0.691874]
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2461 [D loss: 0.693784, acc.: 45.70%] [G loss: 0.691220]
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2462 [D loss: 0.693227, acc.: 48.24%] [G loss: 0.691975]
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2463 [D loss: 0.694060, acc.: 47.85%] [G loss: 0.692665]
8/8 [==============================] - 0s 7ms/step
2464 [D loss: 0.693524, acc.: 50.20%] [G loss: 0.691997]
8/8 [==============================] - 0s 4ms/step
2465 [D loss: 0.693033, acc.: 48.63%] [G loss: 0.692560]
8/8 [==============================] - 0s 5ms/step
2466 [D loss: 0.694382, acc.: 44.34%] [G loss: 0.692756]
8/8 [==============================] - 0s 5ms/step
2467 [D loss: 0.693215, acc.: 50.59%] [G loss: 0.693096]
8/8 [==============================] - 0s 4ms/step
2468 [D loss: 0.693388, acc.: 48.44%] [G loss: 0.692922]
8/8 [==============================] - 0s 5ms/step
2469 [D loss: 0.693199, acc.: 50.78%] [G loss: 0.692684]
8/8 [==============================] - 0s 4ms/step
2470 [D loss: 0.693199, acc.: 51.17%] [G loss: 0.692844]
8/8 [==============================] - 0s 4ms/step
2471 [D loss: 0.694030, acc.: 47.07%] [G loss: 0.693741]
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2472 [D loss: 0.692963, acc.: 48.24%] [G loss: 0.694083]
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2473 [D loss: 0.692657, acc.: 52.73%] [G loss: 0.694048]
8/8 [==============================] - 0s 4ms/step
2474 [D loss: 0.693450, acc.: 49.02%] [G loss: 0.694114]
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2475 [D loss: 0.693900, acc.: 47.46%] [G loss: 0.695776]
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2476 [D loss: 0.693634, acc.: 47.46%] [G loss: 0.694455]
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2477 [D loss: 0.693210, acc.: 50.39%] [G loss: 0.696072]
8/8 [==============================] - 0s 4ms/step
2478 [D loss: 0.692790, acc.: 51.37%] [G loss: 0.696766]
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2479 [D loss: 0.693455, acc.: 49.22%] [G loss: 0.697148]
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2480 [D loss: 0.693765, acc.: 46.09%] [G loss: 0.697527]
8/8 [==============================] - 0s 4ms/step
2481 [D loss: 0.693004, acc.: 50.98%] [G loss: 0.697310]
8/8 [==============================] - 0s 4ms/step
2482 [D loss: 0.693007, acc.: 48.24%] [G loss: 0.697567]
8/8 [==============================] - 0s 4ms/step
2483 [D loss: 0.692833, acc.: 50.78%] [G loss: 0.697495]
8/8 [==============================] - 0s 4ms/step
2484 [D loss: 0.693136, acc.: 51.37%] [G loss: 0.697441]
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2485 [D loss: 0.692662, acc.: 54.49%] [G loss: 0.696393]
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2486 [D loss: 0.693574, acc.: 49.61%] [G loss: 0.696753]
8/8 [==============================] - 0s 4ms/step
2487 [D loss: 0.693463, acc.: 51.17%] [G loss: 0.695356]
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2488 [D loss: 0.694828, acc.: 44.92%] [G loss: 0.697790]
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2489 [D loss: 0.693551, acc.: 49.41%] [G loss: 0.696274]
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2490 [D loss: 0.693194, acc.: 51.56%] [G loss: 0.696911]
8/8 [==============================] - 0s 4ms/step
2491 [D loss: 0.694622, acc.: 45.90%] [G loss: 0.695554]
8/8 [==============================] - 0s 4ms/step
2492 [D loss: 0.694107, acc.: 45.70%] [G loss: 0.695698]
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2493 [D loss: 0.693661, acc.: 50.98%] [G loss: 0.696644]
8/8 [==============================] - 0s 5ms/step
2494 [D loss: 0.694808, acc.: 45.70%] [G loss: 0.695554]
8/8 [==============================] - 0s 5ms/step
2495 [D loss: 0.693948, acc.: 45.70%] [G loss: 0.695772]
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2496 [D loss: 0.694076, acc.: 46.88%] [G loss: 0.695433]
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2497 [D loss: 0.694213, acc.: 43.55%] [G loss: 0.695037]
8/8 [==============================] - 0s 4ms/step
2498 [D loss: 0.693940, acc.: 43.75%] [G loss: 0.695266]
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2499 [D loss: 0.693973, acc.: 45.70%] [G loss: 0.696073]
8/8 [==============================] - 0s 4ms/step
2500 [D loss: 0.693492, acc.: 46.88%] [G loss: 0.695047]
1/1 [==============================] - 0s 18ms/step
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2501 [D loss: 0.693680, acc.: 47.66%] [G loss: 0.695826]
8/8 [==============================] - 0s 5ms/step
2502 [D loss: 0.694285, acc.: 43.16%] [G loss: 0.696137]
8/8 [==============================] - 0s 4ms/step
2503 [D loss: 0.693407, acc.: 47.46%] [G loss: 0.696391]
8/8 [==============================] - 0s 4ms/step
2504 [D loss: 0.694115, acc.: 44.34%] [G loss: 0.697136]
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2505 [D loss: 0.692588, acc.: 53.71%] [G loss: 0.697150]
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2506 [D loss: 0.693195, acc.: 48.83%] [G loss: 0.697579]
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2507 [D loss: 0.693238, acc.: 48.63%] [G loss: 0.697551]
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2508 [D loss: 0.693232, acc.: 49.61%] [G loss: 0.696906]
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2509 [D loss: 0.692499, acc.: 51.95%] [G loss: 0.697556]
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2510 [D loss: 0.693227, acc.: 46.68%] [G loss: 0.697203]
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2511 [D loss: 0.692569, acc.: 54.10%] [G loss: 0.696783]
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2512 [D loss: 0.692478, acc.: 52.54%] [G loss: 0.697337]
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2513 [D loss: 0.692542, acc.: 52.93%] [G loss: 0.696102]
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2514 [D loss: 0.692960, acc.: 48.44%] [G loss: 0.696291]
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2515 [D loss: 0.693119, acc.: 45.51%] [G loss: 0.695738]
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2516 [D loss: 0.691840, acc.: 50.59%] [G loss: 0.694495]
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2517 [D loss: 0.693147, acc.: 48.83%] [G loss: 0.695768]
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2518 [D loss: 0.693428, acc.: 49.41%] [G loss: 0.694202]
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2519 [D loss: 0.693431, acc.: 49.02%] [G loss: 0.695965]
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2520 [D loss: 0.693396, acc.: 48.63%] [G loss: 0.693976]
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2521 [D loss: 0.693883, acc.: 46.88%] [G loss: 0.693362]
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2522 [D loss: 0.694255, acc.: 43.16%] [G loss: 0.693531]
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2523 [D loss: 0.694357, acc.: 43.75%] [G loss: 0.694772]
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2524 [D loss: 0.695360, acc.: 40.82%] [G loss: 0.692508]
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2525 [D loss: 0.694753, acc.: 41.41%] [G loss: 0.693771]
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2526 [D loss: 0.694487, acc.: 43.95%] [G loss: 0.694056]
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2527 [D loss: 0.694240, acc.: 43.16%] [G loss: 0.694269]
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2528 [D loss: 0.693932, acc.: 43.36%] [G loss: 0.695022]
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2529 [D loss: 0.694019, acc.: 42.58%] [G loss: 0.694785]
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2530 [D loss: 0.693743, acc.: 43.16%] [G loss: 0.695627]
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2531 [D loss: 0.693748, acc.: 45.31%] [G loss: 0.696851]
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2532 [D loss: 0.693911, acc.: 44.53%] [G loss: 0.696905]
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2533 [D loss: 0.693454, acc.: 46.09%] [G loss: 0.696451]
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2534 [D loss: 0.693402, acc.: 49.41%] [G loss: 0.698046]
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2535 [D loss: 0.693085, acc.: 48.44%] [G loss: 0.698500]
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2536 [D loss: 0.693097, acc.: 49.02%] [G loss: 0.699049]
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2537 [D loss: 0.693052, acc.: 47.85%] [G loss: 0.697980]
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2538 [D loss: 0.693476, acc.: 45.70%] [G loss: 0.698951]
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2539 [D loss: 0.693345, acc.: 46.88%] [G loss: 0.698697]
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2540 [D loss: 0.693458, acc.: 46.48%] [G loss: 0.699252]
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2541 [D loss: 0.692830, acc.: 52.73%] [G loss: 0.698997]
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2542 [D loss: 0.692351, acc.: 56.05%] [G loss: 0.699551]
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2543 [D loss: 0.693019, acc.: 51.95%] [G loss: 0.699938]
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2544 [D loss: 0.692711, acc.: 52.34%] [G loss: 0.699507]
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2545 [D loss: 0.693052, acc.: 51.76%] [G loss: 0.698741]
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2546 [D loss: 0.692458, acc.: 53.32%] [G loss: 0.699030]
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2547 [D loss: 0.694057, acc.: 45.51%] [G loss: 0.698806]
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2548 [D loss: 0.694138, acc.: 44.14%] [G loss: 0.698296]
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2549 [D loss: 0.693631, acc.: 48.83%] [G loss: 0.697374]
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2550 [D loss: 0.694212, acc.: 43.95%] [G loss: 0.697554]
1/1 [==============================] - 0s 18ms/step
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2551 [D loss: 0.693865, acc.: 47.85%] [G loss: 0.697071]
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2552 [D loss: 0.693882, acc.: 48.83%] [G loss: 0.696861]
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2553 [D loss: 0.693464, acc.: 46.48%] [G loss: 0.696321]
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2554 [D loss: 0.693996, acc.: 46.29%] [G loss: 0.695732]
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2555 [D loss: 0.693653, acc.: 46.29%] [G loss: 0.696246]
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2556 [D loss: 0.693257, acc.: 49.41%] [G loss: 0.694750]
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2557 [D loss: 0.693786, acc.: 47.46%] [G loss: 0.694738]
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2558 [D loss: 0.694142, acc.: 43.95%] [G loss: 0.694532]
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2559 [D loss: 0.693368, acc.: 45.70%] [G loss: 0.694882]
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2560 [D loss: 0.693614, acc.: 45.70%] [G loss: 0.694440]
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2561 [D loss: 0.694153, acc.: 41.21%] [G loss: 0.693728]
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2562 [D loss: 0.693764, acc.: 41.60%] [G loss: 0.693663]
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2563 [D loss: 0.693965, acc.: 41.60%] [G loss: 0.693649]
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2564 [D loss: 0.693492, acc.: 45.70%] [G loss: 0.692220]
8/8 [==============================] - 0s 4ms/step
2565 [D loss: 0.693810, acc.: 47.85%] [G loss: 0.693547]
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2566 [D loss: 0.694231, acc.: 43.36%] [G loss: 0.692855]
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2567 [D loss: 0.694444, acc.: 40.43%] [G loss: 0.693133]
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2568 [D loss: 0.693782, acc.: 46.68%] [G loss: 0.693273]
8/8 [==============================] - 0s 4ms/step
2569 [D loss: 0.693844, acc.: 46.88%] [G loss: 0.693497]
8/8 [==============================] - 0s 4ms/step
2570 [D loss: 0.693398, acc.: 49.41%] [G loss: 0.694015]
8/8 [==============================] - 0s 4ms/step
2571 [D loss: 0.694131, acc.: 49.22%] [G loss: 0.693570]
8/8 [==============================] - 0s 6ms/step
2572 [D loss: 0.693250, acc.: 49.61%] [G loss: 0.694825]
8/8 [==============================] - 0s 4ms/step
2573 [D loss: 0.693352, acc.: 48.44%] [G loss: 0.695285]
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2574 [D loss: 0.693372, acc.: 49.02%] [G loss: 0.694741]
8/8 [==============================] - 0s 4ms/step
2575 [D loss: 0.692867, acc.: 51.56%] [G loss: 0.695135]
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2576 [D loss: 0.692654, acc.: 53.32%] [G loss: 0.695817]
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2577 [D loss: 0.692678, acc.: 53.12%] [G loss: 0.696779]
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2578 [D loss: 0.692224, acc.: 56.64%] [G loss: 0.696224]
8/8 [==============================] - 0s 4ms/step
2579 [D loss: 0.691956, acc.: 53.12%] [G loss: 0.696626]
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2580 [D loss: 0.692476, acc.: 53.91%] [G loss: 0.696261]
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2581 [D loss: 0.692129, acc.: 55.08%] [G loss: 0.697036]
8/8 [==============================] - 0s 4ms/step
2582 [D loss: 0.692836, acc.: 50.59%] [G loss: 0.697170]
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2583 [D loss: 0.691949, acc.: 53.91%] [G loss: 0.696877]
8/8 [==============================] - 0s 4ms/step
2584 [D loss: 0.692443, acc.: 52.73%] [G loss: 0.696514]
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2585 [D loss: 0.693067, acc.: 47.85%] [G loss: 0.696343]
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2586 [D loss: 0.692819, acc.: 50.59%] [G loss: 0.696359]
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2587 [D loss: 0.693823, acc.: 48.44%] [G loss: 0.696357]
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2588 [D loss: 0.693092, acc.: 49.02%] [G loss: 0.695503]
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2589 [D loss: 0.693015, acc.: 47.07%] [G loss: 0.695659]
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2590 [D loss: 0.693563, acc.: 47.07%] [G loss: 0.695054]
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2591 [D loss: 0.693772, acc.: 44.34%] [G loss: 0.695493]
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2592 [D loss: 0.693679, acc.: 48.63%] [G loss: 0.696194]
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2593 [D loss: 0.693596, acc.: 50.39%] [G loss: 0.694802]
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2594 [D loss: 0.694390, acc.: 46.48%] [G loss: 0.694568]
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2595 [D loss: 0.694016, acc.: 44.14%] [G loss: 0.695947]
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2596 [D loss: 0.693877, acc.: 45.70%] [G loss: 0.696979]
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2597 [D loss: 0.694476, acc.: 45.12%] [G loss: 0.696421]
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2598 [D loss: 0.694046, acc.: 46.68%] [G loss: 0.696152]
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2599 [D loss: 0.694067, acc.: 48.44%] [G loss: 0.695562]
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2600 [D loss: 0.693801, acc.: 47.27%] [G loss: 0.696436]
1/1 [==============================] - 0s 18ms/step
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2601 [D loss: 0.693193, acc.: 48.24%] [G loss: 0.696658]
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2602 [D loss: 0.693579, acc.: 45.90%] [G loss: 0.697468]
8/8 [==============================] - 0s 4ms/step
2603 [D loss: 0.694042, acc.: 45.70%] [G loss: 0.696086]
8/8 [==============================] - 0s 5ms/step
2604 [D loss: 0.693192, acc.: 46.29%] [G loss: 0.697291]
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2605 [D loss: 0.692815, acc.: 50.78%] [G loss: 0.697563]
8/8 [==============================] - 0s 4ms/step
2606 [D loss: 0.692397, acc.: 51.17%] [G loss: 0.698023]
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2607 [D loss: 0.693738, acc.: 43.36%] [G loss: 0.698555]
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2608 [D loss: 0.692766, acc.: 50.98%] [G loss: 0.697744]
8/8 [==============================] - 0s 4ms/step
2609 [D loss: 0.692888, acc.: 47.07%] [G loss: 0.698213]
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2610 [D loss: 0.692673, acc.: 50.59%] [G loss: 0.698513]
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2611 [D loss: 0.693335, acc.: 49.02%] [G loss: 0.697158]
8/8 [==============================] - 0s 4ms/step
2612 [D loss: 0.692577, acc.: 51.17%] [G loss: 0.697303]
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2613 [D loss: 0.692504, acc.: 51.76%] [G loss: 0.697126]
8/8 [==============================] - 0s 4ms/step
2614 [D loss: 0.693583, acc.: 46.68%] [G loss: 0.697372]
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2615 [D loss: 0.693062, acc.: 46.29%] [G loss: 0.695652]
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2616 [D loss: 0.694269, acc.: 43.36%] [G loss: 0.695889]
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2617 [D loss: 0.693702, acc.: 47.07%] [G loss: 0.696940]
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2618 [D loss: 0.693741, acc.: 46.48%] [G loss: 0.695893]
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2619 [D loss: 0.693965, acc.: 44.92%] [G loss: 0.696079]
8/8 [==============================] - 0s 4ms/step
2620 [D loss: 0.693842, acc.: 46.09%] [G loss: 0.696564]
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2621 [D loss: 0.693655, acc.: 43.16%] [G loss: 0.697479]
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2622 [D loss: 0.692858, acc.: 50.59%] [G loss: 0.697536]
8/8 [==============================] - 0s 4ms/step
2623 [D loss: 0.692197, acc.: 52.54%] [G loss: 0.698021]
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2624 [D loss: 0.692092, acc.: 54.49%] [G loss: 0.698190]
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2625 [D loss: 0.692514, acc.: 51.17%] [G loss: 0.698354]
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2626 [D loss: 0.693211, acc.: 47.66%] [G loss: 0.698501]
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2627 [D loss: 0.692616, acc.: 50.78%] [G loss: 0.699097]
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2628 [D loss: 0.693032, acc.: 51.95%] [G loss: 0.698412]
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2629 [D loss: 0.692269, acc.: 52.54%] [G loss: 0.697074]
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2630 [D loss: 0.692803, acc.: 49.80%] [G loss: 0.696648]
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2631 [D loss: 0.692679, acc.: 51.95%] [G loss: 0.695691]
8/8 [==============================] - 0s 4ms/step
2632 [D loss: 0.693273, acc.: 48.63%] [G loss: 0.694974]
8/8 [==============================] - 0s 4ms/step
2633 [D loss: 0.693103, acc.: 49.02%] [G loss: 0.695092]
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2634 [D loss: 0.691923, acc.: 52.34%] [G loss: 0.692783]
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2635 [D loss: 0.692877, acc.: 50.78%] [G loss: 0.692316]
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2636 [D loss: 0.693709, acc.: 47.07%] [G loss: 0.692115]
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2637 [D loss: 0.694562, acc.: 44.92%] [G loss: 0.694410]
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2638 [D loss: 0.693098, acc.: 43.75%] [G loss: 0.694622]
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2639 [D loss: 0.693445, acc.: 43.95%] [G loss: 0.694093]
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2640 [D loss: 0.693839, acc.: 46.09%] [G loss: 0.692944]
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2641 [D loss: 0.693776, acc.: 46.09%] [G loss: 0.692633]
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2642 [D loss: 0.693031, acc.: 46.09%] [G loss: 0.692188]
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2643 [D loss: 0.693666, acc.: 47.27%] [G loss: 0.691593]
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2644 [D loss: 0.694034, acc.: 42.38%] [G loss: 0.690420]
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2645 [D loss: 0.694909, acc.: 43.36%] [G loss: 0.690619]
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2646 [D loss: 0.693835, acc.: 46.09%] [G loss: 0.689497]
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2647 [D loss: 0.694173, acc.: 43.95%] [G loss: 0.689205]
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2648 [D loss: 0.694364, acc.: 44.73%] [G loss: 0.689568]
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2649 [D loss: 0.694628, acc.: 42.97%] [G loss: 0.690035]
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2650 [D loss: 0.694566, acc.: 41.02%] [G loss: 0.689800]
1/1 [==============================] - 0s 16ms/step
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2651 [D loss: 0.694347, acc.: 41.99%] [G loss: 0.690621]
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2652 [D loss: 0.694427, acc.: 44.34%] [G loss: 0.691379]
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2653 [D loss: 0.693361, acc.: 47.85%] [G loss: 0.691019]
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2654 [D loss: 0.693679, acc.: 47.66%] [G loss: 0.692129]
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2655 [D loss: 0.693289, acc.: 47.46%] [G loss: 0.692321]
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2656 [D loss: 0.693581, acc.: 45.90%] [G loss: 0.693529]
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2657 [D loss: 0.693322, acc.: 48.83%] [G loss: 0.692654]
8/8 [==============================] - 0s 4ms/step
2658 [D loss: 0.693275, acc.: 50.39%] [G loss: 0.693570]
8/8 [==============================] - 0s 4ms/step
2659 [D loss: 0.692827, acc.: 51.76%] [G loss: 0.694462]
8/8 [==============================] - 0s 4ms/step
2660 [D loss: 0.692728, acc.: 53.52%] [G loss: 0.693603]
8/8 [==============================] - 0s 4ms/step
2661 [D loss: 0.693129, acc.: 52.15%] [G loss: 0.695453]
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2662 [D loss: 0.692283, acc.: 55.47%] [G loss: 0.694698]
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2663 [D loss: 0.692945, acc.: 50.59%] [G loss: 0.694679]
8/8 [==============================] - 0s 4ms/step
2664 [D loss: 0.692693, acc.: 52.93%] [G loss: 0.695181]
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2665 [D loss: 0.692863, acc.: 50.20%] [G loss: 0.695617]
8/8 [==============================] - 0s 4ms/step
2666 [D loss: 0.692868, acc.: 50.20%] [G loss: 0.696048]
8/8 [==============================] - 0s 4ms/step
2667 [D loss: 0.693189, acc.: 49.41%] [G loss: 0.695959]
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2668 [D loss: 0.693124, acc.: 51.95%] [G loss: 0.695773]
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2669 [D loss: 0.692946, acc.: 53.12%] [G loss: 0.696374]
8/8 [==============================] - 0s 5ms/step
2670 [D loss: 0.693665, acc.: 46.09%] [G loss: 0.695755]
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2671 [D loss: 0.693373, acc.: 48.05%] [G loss: 0.695392]
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2672 [D loss: 0.693952, acc.: 44.34%] [G loss: 0.695117]
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2673 [D loss: 0.694099, acc.: 44.34%] [G loss: 0.694722]
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2674 [D loss: 0.694536, acc.: 40.23%] [G loss: 0.694421]
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2675 [D loss: 0.694444, acc.: 40.62%] [G loss: 0.694442]
8/8 [==============================] - 0s 4ms/step
2676 [D loss: 0.693931, acc.: 41.99%] [G loss: 0.693461]
8/8 [==============================] - 0s 4ms/step
2677 [D loss: 0.694084, acc.: 43.55%] [G loss: 0.694341]
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2678 [D loss: 0.694064, acc.: 42.58%] [G loss: 0.694130]
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2679 [D loss: 0.693509, acc.: 47.85%] [G loss: 0.694344]
8/8 [==============================] - 0s 4ms/step
2680 [D loss: 0.693167, acc.: 48.44%] [G loss: 0.694765]
8/8 [==============================] - 0s 4ms/step
2681 [D loss: 0.693296, acc.: 47.46%] [G loss: 0.694775]
8/8 [==============================] - 0s 4ms/step
2682 [D loss: 0.693715, acc.: 47.46%] [G loss: 0.695889]
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2683 [D loss: 0.693203, acc.: 48.63%] [G loss: 0.696837]
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2684 [D loss: 0.693213, acc.: 48.05%] [G loss: 0.696831]
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2685 [D loss: 0.692964, acc.: 50.39%] [G loss: 0.696918]
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2686 [D loss: 0.692537, acc.: 51.17%] [G loss: 0.697253]
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2687 [D loss: 0.691949, acc.: 52.93%] [G loss: 0.697525]
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2688 [D loss: 0.692065, acc.: 51.56%] [G loss: 0.697691]
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2689 [D loss: 0.691736, acc.: 53.91%] [G loss: 0.698441]
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2690 [D loss: 0.692534, acc.: 49.61%] [G loss: 0.697706]
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2691 [D loss: 0.692886, acc.: 47.07%] [G loss: 0.697008]
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2692 [D loss: 0.693190, acc.: 45.90%] [G loss: 0.697963]
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2693 [D loss: 0.692426, acc.: 52.54%] [G loss: 0.695921]
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2694 [D loss: 0.693490, acc.: 47.07%] [G loss: 0.696924]
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2695 [D loss: 0.694883, acc.: 45.12%] [G loss: 0.695066]
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2696 [D loss: 0.693019, acc.: 50.00%] [G loss: 0.696358]
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2697 [D loss: 0.693405, acc.: 46.88%] [G loss: 0.697808]
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2698 [D loss: 0.691931, acc.: 53.52%] [G loss: 0.695717]
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2699 [D loss: 0.694332, acc.: 46.68%] [G loss: 0.696842]
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2700 [D loss: 0.694313, acc.: 44.53%] [G loss: 0.695085]
1/1 [==============================] - 0s 17ms/step
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2701 [D loss: 0.694126, acc.: 46.29%] [G loss: 0.695657]
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2702 [D loss: 0.694072, acc.: 45.12%] [G loss: 0.695727]
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2703 [D loss: 0.694287, acc.: 42.77%] [G loss: 0.695319]
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2704 [D loss: 0.693957, acc.: 45.51%] [G loss: 0.695471]
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2705 [D loss: 0.693918, acc.: 44.73%] [G loss: 0.695129]
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2706 [D loss: 0.693467, acc.: 47.27%] [G loss: 0.695745]
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2707 [D loss: 0.693410, acc.: 49.41%] [G loss: 0.696402]
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2708 [D loss: 0.692312, acc.: 55.27%] [G loss: 0.696783]
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2709 [D loss: 0.692990, acc.: 50.00%] [G loss: 0.697003]
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2710 [D loss: 0.692343, acc.: 53.12%] [G loss: 0.697428]
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2711 [D loss: 0.691468, acc.: 53.91%] [G loss: 0.698817]
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2712 [D loss: 0.691951, acc.: 51.95%] [G loss: 0.699633]
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2713 [D loss: 0.690969, acc.: 55.08%] [G loss: 0.698390]
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2714 [D loss: 0.690830, acc.: 55.47%] [G loss: 0.701017]
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2715 [D loss: 0.691959, acc.: 52.73%] [G loss: 0.699850]
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2716 [D loss: 0.691878, acc.: 53.32%] [G loss: 0.697269]
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2717 [D loss: 0.693851, acc.: 48.24%] [G loss: 0.697673]
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2718 [D loss: 0.693894, acc.: 50.59%] [G loss: 0.694856]
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2719 [D loss: 0.695291, acc.: 45.31%] [G loss: 0.693629]
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2720 [D loss: 0.696241, acc.: 40.82%] [G loss: 0.691918]
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2721 [D loss: 0.695673, acc.: 40.82%] [G loss: 0.691557]
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2722 [D loss: 0.695077, acc.: 42.38%] [G loss: 0.691304]
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2723 [D loss: 0.695276, acc.: 41.99%] [G loss: 0.691531]
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2724 [D loss: 0.695063, acc.: 42.97%] [G loss: 0.691987]
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2725 [D loss: 0.695171, acc.: 37.89%] [G loss: 0.692586]
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2726 [D loss: 0.694726, acc.: 42.38%] [G loss: 0.692191]
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2727 [D loss: 0.694340, acc.: 41.80%] [G loss: 0.692003]
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2728 [D loss: 0.694102, acc.: 46.09%] [G loss: 0.693502]
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2729 [D loss: 0.693948, acc.: 44.73%] [G loss: 0.693234]
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2730 [D loss: 0.693809, acc.: 45.70%] [G loss: 0.693813]
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2731 [D loss: 0.693214, acc.: 50.39%] [G loss: 0.694006]
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2732 [D loss: 0.693059, acc.: 47.85%] [G loss: 0.694030]
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2733 [D loss: 0.692927, acc.: 52.15%] [G loss: 0.694581]
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2734 [D loss: 0.692835, acc.: 51.95%] [G loss: 0.695229]
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2735 [D loss: 0.692970, acc.: 48.44%] [G loss: 0.695666]
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2736 [D loss: 0.692843, acc.: 52.15%] [G loss: 0.694910]
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2737 [D loss: 0.692915, acc.: 49.41%] [G loss: 0.695589]
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2738 [D loss: 0.692770, acc.: 54.69%] [G loss: 0.695949]
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2739 [D loss: 0.692404, acc.: 52.93%] [G loss: 0.695835]
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2740 [D loss: 0.692885, acc.: 51.56%] [G loss: 0.694831]
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2741 [D loss: 0.693529, acc.: 48.63%] [G loss: 0.696323]
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2742 [D loss: 0.693266, acc.: 48.63%] [G loss: 0.696604]
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2743 [D loss: 0.692817, acc.: 50.98%] [G loss: 0.696693]
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2744 [D loss: 0.693629, acc.: 47.46%] [G loss: 0.694598]
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2745 [D loss: 0.693920, acc.: 47.46%] [G loss: 0.694922]
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2746 [D loss: 0.693756, acc.: 47.46%] [G loss: 0.696306]
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2747 [D loss: 0.693324, acc.: 48.63%] [G loss: 0.696264]
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2748 [D loss: 0.694105, acc.: 45.90%] [G loss: 0.696006]
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2749 [D loss: 0.693470, acc.: 46.48%] [G loss: 0.695468]
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2750 [D loss: 0.693251, acc.: 51.95%] [G loss: 0.696590]
1/1 [==============================] - 0s 19ms/step
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2751 [D loss: 0.693416, acc.: 47.46%] [G loss: 0.696803]
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2752 [D loss: 0.692743, acc.: 48.05%] [G loss: 0.696841]
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2753 [D loss: 0.693350, acc.: 50.78%] [G loss: 0.695830]
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2754 [D loss: 0.693550, acc.: 48.83%] [G loss: 0.697439]
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2755 [D loss: 0.693138, acc.: 52.15%] [G loss: 0.697374]
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2756 [D loss: 0.693270, acc.: 48.44%] [G loss: 0.697211]
8/8 [==============================] - 0s 4ms/step
2757 [D loss: 0.692665, acc.: 51.56%] [G loss: 0.696424]
8/8 [==============================] - 0s 7ms/step
2758 [D loss: 0.693617, acc.: 48.24%] [G loss: 0.696971]
8/8 [==============================] - 0s 4ms/step
2759 [D loss: 0.692832, acc.: 52.15%] [G loss: 0.697188]
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2760 [D loss: 0.692505, acc.: 52.73%] [G loss: 0.696705]
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2761 [D loss: 0.692721, acc.: 50.39%] [G loss: 0.697823]
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2762 [D loss: 0.692412, acc.: 49.80%] [G loss: 0.697446]
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2763 [D loss: 0.691872, acc.: 52.54%] [G loss: 0.697910]
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2764 [D loss: 0.691197, acc.: 55.27%] [G loss: 0.699113]
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2765 [D loss: 0.692696, acc.: 50.20%] [G loss: 0.697582]
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2766 [D loss: 0.692343, acc.: 49.61%] [G loss: 0.696657]
8/8 [==============================] - 0s 4ms/step
2767 [D loss: 0.694002, acc.: 48.63%] [G loss: 0.696836]
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2768 [D loss: 0.696439, acc.: 43.75%] [G loss: 0.697301]
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2769 [D loss: 0.693735, acc.: 49.22%] [G loss: 0.696179]
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2770 [D loss: 0.693575, acc.: 48.83%] [G loss: 0.695698]
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2771 [D loss: 0.694070, acc.: 43.36%] [G loss: 0.697341]
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2772 [D loss: 0.693866, acc.: 43.95%] [G loss: 0.698433]
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2773 [D loss: 0.693270, acc.: 49.02%] [G loss: 0.698516]
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2774 [D loss: 0.693946, acc.: 47.07%] [G loss: 0.698113]
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2775 [D loss: 0.693547, acc.: 47.07%] [G loss: 0.697680]
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2776 [D loss: 0.693304, acc.: 49.41%] [G loss: 0.698361]
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2777 [D loss: 0.693819, acc.: 46.68%] [G loss: 0.699182]
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2778 [D loss: 0.693145, acc.: 46.88%] [G loss: 0.697630]
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2779 [D loss: 0.693935, acc.: 44.14%] [G loss: 0.696965]
8/8 [==============================] - 0s 4ms/step
2780 [D loss: 0.694147, acc.: 42.97%] [G loss: 0.697202]
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2781 [D loss: 0.694819, acc.: 46.29%] [G loss: 0.697691]
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2782 [D loss: 0.693465, acc.: 50.59%] [G loss: 0.696886]
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2783 [D loss: 0.693933, acc.: 44.53%] [G loss: 0.695586]
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2784 [D loss: 0.694177, acc.: 43.55%] [G loss: 0.696937]
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2785 [D loss: 0.693822, acc.: 45.31%] [G loss: 0.696517]
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2786 [D loss: 0.694456, acc.: 45.31%] [G loss: 0.695710]
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2787 [D loss: 0.694421, acc.: 46.48%] [G loss: 0.696149]
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2788 [D loss: 0.694695, acc.: 39.45%] [G loss: 0.698075]
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2789 [D loss: 0.693946, acc.: 43.36%] [G loss: 0.697435]
8/8 [==============================] - 0s 4ms/step
2790 [D loss: 0.693619, acc.: 47.07%] [G loss: 0.696697]
8/8 [==============================] - 0s 4ms/step
2791 [D loss: 0.693628, acc.: 45.90%] [G loss: 0.696766]
8/8 [==============================] - 0s 4ms/step
2792 [D loss: 0.692761, acc.: 49.80%] [G loss: 0.697697]
8/8 [==============================] - 0s 4ms/step
2793 [D loss: 0.693387, acc.: 47.85%] [G loss: 0.697242]
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2794 [D loss: 0.692950, acc.: 51.56%] [G loss: 0.697127]
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2795 [D loss: 0.692686, acc.: 50.59%] [G loss: 0.696303]
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2796 [D loss: 0.692646, acc.: 54.88%] [G loss: 0.696766]
8/8 [==============================] - 0s 4ms/step
2797 [D loss: 0.692251, acc.: 57.42%] [G loss: 0.696344]
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2798 [D loss: 0.692592, acc.: 53.32%] [G loss: 0.698161]
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2799 [D loss: 0.692232, acc.: 54.49%] [G loss: 0.696837]
8/8 [==============================] - 0s 4ms/step
2800 [D loss: 0.692108, acc.: 54.49%] [G loss: 0.696106]
1/1 [==============================] - 0s 17ms/step
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2801 [D loss: 0.692378, acc.: 52.93%] [G loss: 0.696361]
8/8 [==============================] - 0s 4ms/step
2802 [D loss: 0.692367, acc.: 54.10%] [G loss: 0.694951]
8/8 [==============================] - 0s 5ms/step
2803 [D loss: 0.692320, acc.: 52.54%] [G loss: 0.693965]
8/8 [==============================] - 0s 4ms/step
2804 [D loss: 0.692489, acc.: 54.69%] [G loss: 0.693642]
8/8 [==============================] - 0s 4ms/step
2805 [D loss: 0.692528, acc.: 51.37%] [G loss: 0.693225]
8/8 [==============================] - 0s 4ms/step
2806 [D loss: 0.693961, acc.: 45.51%] [G loss: 0.692377]
8/8 [==============================] - 0s 4ms/step
2807 [D loss: 0.692335, acc.: 50.59%] [G loss: 0.692522]
8/8 [==============================] - 0s 5ms/step
2808 [D loss: 0.693357, acc.: 49.22%] [G loss: 0.692902]
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2809 [D loss: 0.693326, acc.: 48.83%] [G loss: 0.693471]
8/8 [==============================] - 0s 4ms/step
2810 [D loss: 0.694072, acc.: 44.92%] [G loss: 0.694086]
8/8 [==============================] - 0s 4ms/step
2811 [D loss: 0.693325, acc.: 49.41%] [G loss: 0.693287]
8/8 [==============================] - 0s 4ms/step
2812 [D loss: 0.694582, acc.: 43.95%] [G loss: 0.693545]
8/8 [==============================] - 0s 4ms/step
2813 [D loss: 0.694259, acc.: 47.27%] [G loss: 0.693210]
8/8 [==============================] - 0s 4ms/step
2814 [D loss: 0.693877, acc.: 45.70%] [G loss: 0.693393]
8/8 [==============================] - 0s 4ms/step
2815 [D loss: 0.694301, acc.: 44.34%] [G loss: 0.693433]
8/8 [==============================] - 0s 4ms/step
2816 [D loss: 0.695115, acc.: 41.02%] [G loss: 0.692360]
8/8 [==============================] - 0s 4ms/step
2817 [D loss: 0.694741, acc.: 36.91%] [G loss: 0.693372]
8/8 [==============================] - 0s 4ms/step
2818 [D loss: 0.694818, acc.: 40.82%] [G loss: 0.693582]
8/8 [==============================] - 0s 4ms/step
2819 [D loss: 0.694121, acc.: 43.36%] [G loss: 0.694185]
8/8 [==============================] - 0s 4ms/step
2820 [D loss: 0.694379, acc.: 41.60%] [G loss: 0.694235]
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2821 [D loss: 0.693963, acc.: 40.62%] [G loss: 0.694219]
8/8 [==============================] - 0s 4ms/step
2822 [D loss: 0.693970, acc.: 41.60%] [G loss: 0.694854]
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2823 [D loss: 0.693704, acc.: 43.95%] [G loss: 0.695553]
8/8 [==============================] - 0s 4ms/step
2824 [D loss: 0.693462, acc.: 44.73%] [G loss: 0.695145]
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2825 [D loss: 0.692967, acc.: 49.61%] [G loss: 0.696101]
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2826 [D loss: 0.693269, acc.: 45.90%] [G loss: 0.696432]
8/8 [==============================] - 0s 4ms/step
2827 [D loss: 0.693165, acc.: 47.07%] [G loss: 0.697235]
8/8 [==============================] - 0s 4ms/step
2828 [D loss: 0.692504, acc.: 53.12%] [G loss: 0.697562]
8/8 [==============================] - 0s 5ms/step
2829 [D loss: 0.692927, acc.: 49.02%] [G loss: 0.697769]
8/8 [==============================] - 0s 4ms/step
2830 [D loss: 0.691977, acc.: 55.08%] [G loss: 0.698220]
8/8 [==============================] - 0s 4ms/step
2831 [D loss: 0.691975, acc.: 53.12%] [G loss: 0.699308]
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2832 [D loss: 0.692418, acc.: 52.54%] [G loss: 0.698789]
8/8 [==============================] - 0s 4ms/step
2833 [D loss: 0.692654, acc.: 53.52%] [G loss: 0.699422]
8/8 [==============================] - 0s 4ms/step
2834 [D loss: 0.692400, acc.: 56.25%] [G loss: 0.698793]
8/8 [==============================] - 0s 4ms/step
2835 [D loss: 0.693521, acc.: 50.98%] [G loss: 0.697809]
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2836 [D loss: 0.691938, acc.: 54.88%] [G loss: 0.696843]
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2837 [D loss: 0.691976, acc.: 53.32%] [G loss: 0.695888]
8/8 [==============================] - 0s 4ms/step
2838 [D loss: 0.693681, acc.: 49.80%] [G loss: 0.695970]
8/8 [==============================] - 0s 4ms/step
2839 [D loss: 0.693703, acc.: 48.83%] [G loss: 0.694882]
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2840 [D loss: 0.695341, acc.: 44.14%] [G loss: 0.693682]
8/8 [==============================] - 0s 4ms/step
2841 [D loss: 0.695127, acc.: 44.73%] [G loss: 0.694401]
8/8 [==============================] - 0s 4ms/step
2842 [D loss: 0.694105, acc.: 47.66%] [G loss: 0.694233]
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2843 [D loss: 0.694497, acc.: 46.09%] [G loss: 0.694497]
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2844 [D loss: 0.694187, acc.: 45.51%] [G loss: 0.694456]
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2845 [D loss: 0.693877, acc.: 46.29%] [G loss: 0.694907]
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2846 [D loss: 0.694031, acc.: 44.73%] [G loss: 0.695320]
8/8 [==============================] - 0s 4ms/step
2847 [D loss: 0.693478, acc.: 43.95%] [G loss: 0.696230]
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2848 [D loss: 0.693872, acc.: 43.36%] [G loss: 0.695279]
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2849 [D loss: 0.693959, acc.: 44.34%] [G loss: 0.694931]
8/8 [==============================] - 0s 4ms/step
2850 [D loss: 0.694161, acc.: 44.73%] [G loss: 0.694757]
1/1 [==============================] - 0s 19ms/step
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2851 [D loss: 0.693769, acc.: 46.29%] [G loss: 0.694433]
8/8 [==============================] - 0s 4ms/step
2852 [D loss: 0.693446, acc.: 47.46%] [G loss: 0.694988]
8/8 [==============================] - 0s 4ms/step
2853 [D loss: 0.693825, acc.: 44.73%] [G loss: 0.695344]
8/8 [==============================] - 0s 4ms/step
2854 [D loss: 0.693319, acc.: 47.66%] [G loss: 0.695257]
8/8 [==============================] - 0s 4ms/step
2855 [D loss: 0.693061, acc.: 49.02%] [G loss: 0.694268]
8/8 [==============================] - 0s 5ms/step
2856 [D loss: 0.693459, acc.: 42.77%] [G loss: 0.694506]
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2857 [D loss: 0.693046, acc.: 46.68%] [G loss: 0.695770]
8/8 [==============================] - 0s 4ms/step
2858 [D loss: 0.693082, acc.: 47.27%] [G loss: 0.694596]
8/8 [==============================] - 0s 5ms/step
2859 [D loss: 0.693209, acc.: 45.90%] [G loss: 0.693629]
8/8 [==============================] - 0s 4ms/step
2860 [D loss: 0.694315, acc.: 42.97%] [G loss: 0.694400]
8/8 [==============================] - 0s 5ms/step
2861 [D loss: 0.694375, acc.: 42.19%] [G loss: 0.694362]
8/8 [==============================] - 0s 5ms/step
2862 [D loss: 0.694812, acc.: 42.38%] [G loss: 0.694866]
8/8 [==============================] - 0s 5ms/step
2863 [D loss: 0.694837, acc.: 44.14%] [G loss: 0.696966]
8/8 [==============================] - 0s 4ms/step
2864 [D loss: 0.693790, acc.: 46.88%] [G loss: 0.695150]
8/8 [==============================] - 0s 5ms/step
2865 [D loss: 0.692046, acc.: 53.52%] [G loss: 0.696229]
8/8 [==============================] - 0s 4ms/step
2866 [D loss: 0.692180, acc.: 55.27%] [G loss: 0.696197]
8/8 [==============================] - 0s 4ms/step
2867 [D loss: 0.692661, acc.: 51.56%] [G loss: 0.697125]
8/8 [==============================] - 0s 4ms/step
2868 [D loss: 0.692396, acc.: 51.37%] [G loss: 0.697471]
8/8 [==============================] - 0s 5ms/step
2869 [D loss: 0.692410, acc.: 53.71%] [G loss: 0.697096]
8/8 [==============================] - 0s 5ms/step
2870 [D loss: 0.693025, acc.: 54.30%] [G loss: 0.696035]
8/8 [==============================] - 0s 5ms/step
2871 [D loss: 0.693797, acc.: 46.48%] [G loss: 0.696076]
8/8 [==============================] - 0s 5ms/step
2872 [D loss: 0.693940, acc.: 46.88%] [G loss: 0.695434]
8/8 [==============================] - 0s 6ms/step
2873 [D loss: 0.693483, acc.: 45.70%] [G loss: 0.694241]
8/8 [==============================] - 0s 4ms/step
2874 [D loss: 0.693417, acc.: 46.68%] [G loss: 0.694395]
8/8 [==============================] - 0s 5ms/step
2875 [D loss: 0.692750, acc.: 50.78%] [G loss: 0.693461]
8/8 [==============================] - 0s 4ms/step
2876 [D loss: 0.693026, acc.: 51.17%] [G loss: 0.692814]
8/8 [==============================] - 0s 4ms/step
2877 [D loss: 0.692885, acc.: 50.39%] [G loss: 0.692841]
8/8 [==============================] - 0s 4ms/step
2878 [D loss: 0.693806, acc.: 44.73%] [G loss: 0.691628]
8/8 [==============================] - 0s 4ms/step
2879 [D loss: 0.694221, acc.: 41.80%] [G loss: 0.692999]
8/8 [==============================] - 0s 5ms/step
2880 [D loss: 0.693069, acc.: 49.41%] [G loss: 0.692312]
8/8 [==============================] - 0s 4ms/step
2881 [D loss: 0.694267, acc.: 46.09%] [G loss: 0.692367]
8/8 [==============================] - 0s 5ms/step
2882 [D loss: 0.693397, acc.: 48.63%] [G loss: 0.694086]
8/8 [==============================] - 0s 5ms/step
2883 [D loss: 0.693359, acc.: 49.61%] [G loss: 0.693747]
8/8 [==============================] - 0s 5ms/step
2884 [D loss: 0.693135, acc.: 49.80%] [G loss: 0.694525]
8/8 [==============================] - 0s 4ms/step
2885 [D loss: 0.692389, acc.: 49.80%] [G loss: 0.695911]
8/8 [==============================] - 0s 4ms/step
2886 [D loss: 0.692211, acc.: 50.00%] [G loss: 0.695581]
8/8 [==============================] - 0s 5ms/step
2887 [D loss: 0.693261, acc.: 49.02%] [G loss: 0.696035]
8/8 [==============================] - 0s 4ms/step
2888 [D loss: 0.692662, acc.: 51.76%] [G loss: 0.695715]
8/8 [==============================] - 0s 5ms/step
2889 [D loss: 0.693115, acc.: 47.27%] [G loss: 0.694956]
8/8 [==============================] - 0s 4ms/step
2890 [D loss: 0.693372, acc.: 49.41%] [G loss: 0.694420]
8/8 [==============================] - 0s 4ms/step
2891 [D loss: 0.692867, acc.: 47.85%] [G loss: 0.694526]
8/8 [==============================] - 0s 4ms/step
2892 [D loss: 0.693504, acc.: 45.70%] [G loss: 0.693208]
8/8 [==============================] - 0s 4ms/step
2893 [D loss: 0.694582, acc.: 44.14%] [G loss: 0.693164]
8/8 [==============================] - 0s 5ms/step
2894 [D loss: 0.695188, acc.: 43.95%] [G loss: 0.692745]
8/8 [==============================] - 0s 5ms/step
2895 [D loss: 0.694407, acc.: 45.90%] [G loss: 0.693666]
8/8 [==============================] - 0s 5ms/step
2896 [D loss: 0.693932, acc.: 45.90%] [G loss: 0.693250]
8/8 [==============================] - 0s 4ms/step
2897 [D loss: 0.693780, acc.: 44.34%] [G loss: 0.694358]
8/8 [==============================] - 0s 5ms/step
2898 [D loss: 0.694203, acc.: 43.36%] [G loss: 0.694707]
8/8 [==============================] - 0s 4ms/step
2899 [D loss: 0.694328, acc.: 44.53%] [G loss: 0.694251]
8/8 [==============================] - 0s 5ms/step
2900 [D loss: 0.694099, acc.: 45.12%] [G loss: 0.696321]
1/1 [==============================] - 0s 19ms/step
8/8 [==============================] - 0s 4ms/step
2901 [D loss: 0.693750, acc.: 46.48%] [G loss: 0.697317]
8/8 [==============================] - 0s 4ms/step
2902 [D loss: 0.693568, acc.: 46.48%] [G loss: 0.697059]
8/8 [==============================] - 0s 5ms/step
2903 [D loss: 0.692685, acc.: 51.95%] [G loss: 0.697676]
8/8 [==============================] - 0s 4ms/step
2904 [D loss: 0.692000, acc.: 53.52%] [G loss: 0.699427]
8/8 [==============================] - 0s 5ms/step
2905 [D loss: 0.692905, acc.: 49.61%] [G loss: 0.699590]
8/8 [==============================] - 0s 4ms/step
2906 [D loss: 0.692635, acc.: 49.80%] [G loss: 0.700279]
8/8 [==============================] - 0s 5ms/step
2907 [D loss: 0.692169, acc.: 53.91%] [G loss: 0.701191]
8/8 [==============================] - 0s 4ms/step
2908 [D loss: 0.693322, acc.: 47.07%] [G loss: 0.700635]
8/8 [==============================] - 0s 5ms/step
2909 [D loss: 0.694455, acc.: 42.38%] [G loss: 0.699130]
8/8 [==============================] - 0s 5ms/step
2910 [D loss: 0.694348, acc.: 45.31%] [G loss: 0.699301]
8/8 [==============================] - 0s 5ms/step
2911 [D loss: 0.694001, acc.: 44.73%] [G loss: 0.697251]
8/8 [==============================] - 0s 4ms/step
2912 [D loss: 0.693957, acc.: 46.29%] [G loss: 0.696050]
8/8 [==============================] - 0s 5ms/step
2913 [D loss: 0.694658, acc.: 44.92%] [G loss: 0.695949]
8/8 [==============================] - 0s 4ms/step
2914 [D loss: 0.694002, acc.: 46.29%] [G loss: 0.696336]
8/8 [==============================] - 0s 4ms/step
2915 [D loss: 0.693987, acc.: 46.48%] [G loss: 0.696660]
8/8 [==============================] - 0s 5ms/step
2916 [D loss: 0.694007, acc.: 44.92%] [G loss: 0.696231]
8/8 [==============================] - 0s 5ms/step
2917 [D loss: 0.693133, acc.: 48.05%] [G loss: 0.695656]
8/8 [==============================] - 0s 5ms/step
2918 [D loss: 0.693651, acc.: 45.12%] [G loss: 0.695768]
8/8 [==============================] - 0s 5ms/step
2919 [D loss: 0.693065, acc.: 48.83%] [G loss: 0.696614]
8/8 [==============================] - 0s 4ms/step
2920 [D loss: 0.693280, acc.: 48.05%] [G loss: 0.696202]
8/8 [==============================] - 0s 5ms/step
2921 [D loss: 0.693088, acc.: 50.00%] [G loss: 0.695620]
8/8 [==============================] - 0s 4ms/step
2922 [D loss: 0.692772, acc.: 49.02%] [G loss: 0.696483]
8/8 [==============================] - 0s 4ms/step
2923 [D loss: 0.692210, acc.: 53.71%] [G loss: 0.696111]
8/8 [==============================] - 0s 5ms/step
2924 [D loss: 0.692182, acc.: 55.66%] [G loss: 0.696673]
8/8 [==============================] - 0s 5ms/step
2925 [D loss: 0.691446, acc.: 55.47%] [G loss: 0.696370]
8/8 [==============================] - 0s 5ms/step
2926 [D loss: 0.691766, acc.: 52.15%] [G loss: 0.697634]
8/8 [==============================] - 0s 6ms/step
2927 [D loss: 0.691498, acc.: 56.25%] [G loss: 0.695643]
8/8 [==============================] - 0s 5ms/step
2928 [D loss: 0.690992, acc.: 55.47%] [G loss: 0.695599]
8/8 [==============================] - 0s 4ms/step
2929 [D loss: 0.691555, acc.: 52.93%] [G loss: 0.695735]
8/8 [==============================] - 0s 5ms/step
2930 [D loss: 0.692647, acc.: 51.56%] [G loss: 0.694000]
8/8 [==============================] - 0s 4ms/step
2931 [D loss: 0.691756, acc.: 52.15%] [G loss: 0.691636]
8/8 [==============================] - 0s 5ms/step
2932 [D loss: 0.693760, acc.: 48.44%] [G loss: 0.690003]
8/8 [==============================] - 0s 5ms/step
2933 [D loss: 0.694807, acc.: 44.34%] [G loss: 0.690561]
8/8 [==============================] - 0s 5ms/step
2934 [D loss: 0.694677, acc.: 44.73%] [G loss: 0.690936]
8/8 [==============================] - 0s 5ms/step
2935 [D loss: 0.694294, acc.: 44.34%] [G loss: 0.689923]
8/8 [==============================] - 0s 4ms/step
2936 [D loss: 0.693842, acc.: 47.27%] [G loss: 0.691652]
8/8 [==============================] - 0s 5ms/step
2937 [D loss: 0.695197, acc.: 45.51%] [G loss: 0.692015]
8/8 [==============================] - 0s 4ms/step
2938 [D loss: 0.693292, acc.: 48.44%] [G loss: 0.692237]
8/8 [==============================] - 0s 5ms/step
2939 [D loss: 0.694897, acc.: 45.70%] [G loss: 0.691847]
8/8 [==============================] - 0s 5ms/step
2940 [D loss: 0.693951, acc.: 48.24%] [G loss: 0.693672]
8/8 [==============================] - 0s 5ms/step
2941 [D loss: 0.693288, acc.: 47.46%] [G loss: 0.692059]
8/8 [==============================] - 0s 5ms/step
2942 [D loss: 0.693862, acc.: 47.46%] [G loss: 0.693362]
8/8 [==============================] - 0s 5ms/step
2943 [D loss: 0.693362, acc.: 48.83%] [G loss: 0.693947]
8/8 [==============================] - 0s 5ms/step
2944 [D loss: 0.693783, acc.: 45.51%] [G loss: 0.693100]
8/8 [==============================] - 0s 5ms/step
2945 [D loss: 0.692538, acc.: 48.63%] [G loss: 0.693174]
8/8 [==============================] - 0s 4ms/step
2946 [D loss: 0.691337, acc.: 54.30%] [G loss: 0.693925]
8/8 [==============================] - 0s 5ms/step
2947 [D loss: 0.692738, acc.: 49.61%] [G loss: 0.693090]
8/8 [==============================] - 0s 5ms/step
2948 [D loss: 0.692691, acc.: 47.27%] [G loss: 0.690573]
8/8 [==============================] - 0s 4ms/step
2949 [D loss: 0.694903, acc.: 45.31%] [G loss: 0.691057]
8/8 [==============================] - 0s 5ms/step
2950 [D loss: 0.695205, acc.: 45.70%] [G loss: 0.692376]
1/1 [==============================] - 0s 30ms/step
8/8 [==============================] - 0s 4ms/step
2951 [D loss: 0.695018, acc.: 44.92%] [G loss: 0.692299]
8/8 [==============================] - 0s 5ms/step
2952 [D loss: 0.693413, acc.: 48.24%] [G loss: 0.693444]
8/8 [==============================] - 0s 5ms/step
2953 [D loss: 0.693986, acc.: 49.61%] [G loss: 0.693782]
8/8 [==============================] - 0s 5ms/step
2954 [D loss: 0.692731, acc.: 50.39%] [G loss: 0.695307]
8/8 [==============================] - 0s 5ms/step
2955 [D loss: 0.693110, acc.: 51.17%] [G loss: 0.693626]
8/8 [==============================] - 0s 5ms/step
2956 [D loss: 0.693222, acc.: 50.59%] [G loss: 0.694800]
8/8 [==============================] - 0s 4ms/step
2957 [D loss: 0.691846, acc.: 52.34%] [G loss: 0.695755]
8/8 [==============================] - 0s 4ms/step
2958 [D loss: 0.693752, acc.: 45.31%] [G loss: 0.693965]
8/8 [==============================] - 0s 4ms/step
2959 [D loss: 0.693364, acc.: 48.63%] [G loss: 0.693600]
8/8 [==============================] - 0s 5ms/step
2960 [D loss: 0.694140, acc.: 46.29%] [G loss: 0.693173]
8/8 [==============================] - 0s 5ms/step
2961 [D loss: 0.693680, acc.: 46.29%] [G loss: 0.692394]
8/8 [==============================] - 0s 5ms/step
2962 [D loss: 0.694068, acc.: 43.55%] [G loss: 0.691329]
8/8 [==============================] - 0s 5ms/step
2963 [D loss: 0.694553, acc.: 46.29%] [G loss: 0.693210]
8/8 [==============================] - 0s 5ms/step
2964 [D loss: 0.694585, acc.: 46.68%] [G loss: 0.692384]
8/8 [==============================] - 0s 5ms/step
2965 [D loss: 0.693976, acc.: 45.51%] [G loss: 0.692456]
8/8 [==============================] - 0s 5ms/step
2966 [D loss: 0.694732, acc.: 47.27%] [G loss: 0.692916]
8/8 [==============================] - 0s 5ms/step
2967 [D loss: 0.694605, acc.: 41.21%] [G loss: 0.693670]
8/8 [==============================] - 0s 4ms/step
2968 [D loss: 0.693869, acc.: 47.66%] [G loss: 0.694304]
8/8 [==============================] - 0s 5ms/step
2969 [D loss: 0.693821, acc.: 46.29%] [G loss: 0.694903]
8/8 [==============================] - 0s 5ms/step
2970 [D loss: 0.693499, acc.: 47.85%] [G loss: 0.696187]
8/8 [==============================] - 0s 5ms/step
2971 [D loss: 0.693177, acc.: 50.39%] [G loss: 0.696389]
8/8 [==============================] - 0s 5ms/step
2972 [D loss: 0.693214, acc.: 46.29%] [G loss: 0.696425]
8/8 [==============================] - 0s 4ms/step
2973 [D loss: 0.692447, acc.: 52.73%] [G loss: 0.696042]
8/8 [==============================] - 0s 5ms/step
2974 [D loss: 0.693250, acc.: 48.05%] [G loss: 0.697689]
8/8 [==============================] - 0s 4ms/step
2975 [D loss: 0.692728, acc.: 49.02%] [G loss: 0.699902]
8/8 [==============================] - 0s 5ms/step
2976 [D loss: 0.692336, acc.: 50.78%] [G loss: 0.698109]
8/8 [==============================] - 0s 4ms/step
2977 [D loss: 0.692019, acc.: 53.71%] [G loss: 0.699430]
8/8 [==============================] - 0s 5ms/step
2978 [D loss: 0.692342, acc.: 54.88%] [G loss: 0.698098]
8/8 [==============================] - 0s 4ms/step
2979 [D loss: 0.692734, acc.: 51.37%] [G loss: 0.698815]
8/8 [==============================] - 0s 5ms/step
2980 [D loss: 0.692481, acc.: 52.15%] [G loss: 0.698556]
8/8 [==============================] - 0s 5ms/step
2981 [D loss: 0.693114, acc.: 48.24%] [G loss: 0.699121]
8/8 [==============================] - 0s 4ms/step
2982 [D loss: 0.693063, acc.: 49.22%] [G loss: 0.697316]
8/8 [==============================] - 0s 4ms/step
2983 [D loss: 0.693171, acc.: 49.02%] [G loss: 0.697115]
8/8 [==============================] - 0s 4ms/step
2984 [D loss: 0.693384, acc.: 49.41%] [G loss: 0.696984]
8/8 [==============================] - 0s 5ms/step
2985 [D loss: 0.694625, acc.: 45.51%] [G loss: 0.695648]
8/8 [==============================] - 0s 6ms/step
2986 [D loss: 0.693319, acc.: 44.53%] [G loss: 0.696105]
8/8 [==============================] - 0s 5ms/step
2987 [D loss: 0.694400, acc.: 47.07%] [G loss: 0.693612]
8/8 [==============================] - 0s 5ms/step
2988 [D loss: 0.694852, acc.: 44.92%] [G loss: 0.694280]
8/8 [==============================] - 0s 4ms/step
2989 [D loss: 0.693790, acc.: 48.83%] [G loss: 0.694246]
8/8 [==============================] - 0s 4ms/step
2990 [D loss: 0.694812, acc.: 47.46%] [G loss: 0.693946]
8/8 [==============================] - 0s 4ms/step
2991 [D loss: 0.693655, acc.: 50.20%] [G loss: 0.695173]
8/8 [==============================] - 0s 5ms/step
2992 [D loss: 0.692644, acc.: 50.39%] [G loss: 0.696242]
8/8 [==============================] - 0s 4ms/step
2993 [D loss: 0.692596, acc.: 50.20%] [G loss: 0.696317]
8/8 [==============================] - 0s 5ms/step
2994 [D loss: 0.692403, acc.: 50.00%] [G loss: 0.696922]
8/8 [==============================] - 0s 4ms/step
2995 [D loss: 0.693174, acc.: 48.44%] [G loss: 0.697782]
8/8 [==============================] - 0s 4ms/step
2996 [D loss: 0.692343, acc.: 50.00%] [G loss: 0.697869]
8/8 [==============================] - 0s 4ms/step
2997 [D loss: 0.692670, acc.: 44.53%] [G loss: 0.698650]
8/8 [==============================] - 0s 5ms/step
2998 [D loss: 0.693588, acc.: 46.09%] [G loss: 0.696193]
8/8 [==============================] - 0s 4ms/step
2999 [D loss: 0.692665, acc.: 51.17%] [G loss: 0.696845]

# Generate random noise
num_images = 10
noise = np.random.normal(0, 1, (num_images, dcgan.latent_dim))

# Generate images from the noise
gen_imgs = dcgan.generator.predict(noise)

# Directory to save the generated images
save_path = 'final_images/class_Z'
os.makedirs(save_path, exist_ok=True)

# Save the generated images
for i in range(num_images):
    plt.figure()
    plt.imshow(gen_imgs[i, :, :, 0], cmap='gray')
    plt.axis('off')
    plt.savefig(f"{save_path}/image_{i+1}.png")
    plt.close()

1/1 [==============================] - 0s 41ms/step

Conclusions

We have generated 260 images, with 10 images from each of the 26 classes. To achieve this, we used a combination of CGAN and DCGAN models. For the images from classes A to Y, we utilized the CGAN as the generated images required specific class conditioning, which CGANs handle effectively. However, for the final 'Z' class, we used a DCGAN because the CGAN was not performing well for this particular class. The DCGAN was more suitable for generating high-quality images specifically for the 'Z' class, focusing on this challenging aspect without the need for class labels.

The process of generating the 260 images began with exploratory data analysis (EDA), followed by dataset cleaning and feature engineering. After processing the data, we explored the use of DCGAN, starting with a base model and attempting various improvements to generate the best possible images. Similarly, for CGAN, we began with a base model and made adjustments in an effort to enhance the quality of the generated images and find the best-performing model. For WGAN, we also started with a base configuration and experimented with improvements to achieve the highest quality images.

The final CGAN model was evaluated by comparing the generated images with real images and analyzing metrics such as loss, accuracy, and KL divergence.

#⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣀⣤⡤⠴⠶⣦⣤⣀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣴⡾⠛⠉⠀⠀⠀⠀⠀⠈⠙⢿⣦⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣠⣾⠟⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢻⣧⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⣾⠟⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⢀⣠⣴⣶⣶⣶⣶⣶⣤⣤⣄⣀⣀⡀⢀⣴⡿⠋⠀⠀⢀⡀⠰⣾⣆⠀⠀⠀⠀⠀⠀⠀⢀⣾⠏⠀⢠⣤⣀⠀⠀⠀⠀⠀⠀
#⢀⣴⠛⠉⠀⠀⠀⠀⠀⠈⠉⠉⢉⣿⠟⢻⣿⡿⠿⠿⠿⠟⠋⠀⠀⠙⠿⣷⣤⣀⡀⠀⣀⣤⠿⠃⠀⣠⣿⡟⠁⠀⠀⠀⠀⠀⠀
#⣸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⣰⣿⠋⢠⣾⠟⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⠉⠙⠉⠉⠁⠀⠀⣰⣿⠟⠀⠀⠀⠀⠀⠀⠀⠀
#⢹⣧⡀⠀⠀⠀⠀⠀⠀⠀⣰⣿⠇⢠⣿⠋⣀⣤⡀⠀⠀⢀⣀⣀⣀⡀⠀⢀⣤⡄⢀⣠⣤⡄⠀⣰⣿⠋⣠⣶⣶⡄⠀⠀⠀⠀⠀
#⠀⠻⠿⣿⣶⠀⠀⠀⠀⣰⣿⡏⢠⣿⣷⣾⣿⡿⠃⣠⣾⠟⢉⣿⡟⢁⣴⠟⣽⣿⠟⣹⣿⠇⣰⣿⣿⣟⣁⣴⡿⠁⠀⠀⠀⠀⣄
#⠀⠀⠀⠀⠀⠀⠀⠀⣰⣿⡟⢀⣿⡿⠋⣾⡟⢁⣴⣿⣋⣠⣿⡏⣰⡿⢁⣼⡿⠃⢠⣿⣧⣾⣿⡿⢻⣿⡉⠁⠀⠀⠀⠀⠀⢻⣿
#⠀⠀⠀⠀⠀⠀⠀⣰⣿⡿⠀⠈⠻⠁⠀⠿⠿⠛⠙⠻⠛⠁⠻⠟⠋⠀⠈⠛⠁⠀⠘⠿⠛⠹⣿⠁⠀⠻⣿⣄⠀⠀⠀⠀⠀⢸⣿
#⠀⣠⡀⠀⠀⠀⢠⣿⡟⠁⠀⠀⠀⠀⠀⠀⠀⣠⠀⠀⠀⢀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠙⢿⣦⣄⡀⢀⣠⡿⠃
#⢸⡟⠁⠀⠀⣰⡿⠋⠀⠀⠀⠀⠀⠀⠀⢠⣿⠏⠀⢠⣿⠟⣠⣴⡾⣿⣿⠂⠀⣤⣤⠆⠀⣤⣤⡆⠀⠀⠀⠀⠈⠉⠛⠋⠉⠀⠀
#⠘⠷⠤⠴⠟⠋⠀⠀⠀⠀⠀⠀⠀⠀⢠⣿⠏⠀⣴⣿⣟⣼⡿⠋⢰⣿⣿⢃⣾⡿⠁⢀⣾⣿⠋⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣾⡟⢠⣾⣿⡏⢸⣿⠁⠀⣼⣿⠟⣿⡟⠀⣰⣿⡿⠁⠀⠀⣀⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠀⠀⠀⢀⣀⣀⣀⣀⡀⠀⠀⠀⠻⠿⢫⣿⠟⠀⠸⣿⣴⣾⠟⠁⠀⠻⣷⠟⠋⢸⡇⠀⢀⣴⣿⠟⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⢀⣴⠟⠛⠉⠛⠛⠛⠿⠿⣿⣶⣶⣤⣿⣏⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠻⠶⠟⠛⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⣹⣿⠛⠿⢿⣷⣶⣤⣀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠘⣷⡄⠀⠀⠀⠀⠀⠀⠀⢀⣾⡟⠁⠀⠀⠀⠀⠉⠙⠛⠻⠿⣶⣶⣤⣤⣀⣀⣀⣀⣀⣀⣀⣤⠾⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠀⠙⢿⣦⡀⠀⠀⠀⢀⣴⠿⠋⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠉⠛⠛⠛⠿⠿⠛⠛⠉⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
#⠀⠀⠀⠀⢀⣉⣛⠓⠒⠚⠋⠀⠀⠀⠀

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